Module Gnumed.business.gmClinicalCalculator
GNUmed clinical calculator(s)
THIS IS NOT A VERIFIED CALCULATOR. DO NOT USE FOR ACTUAL CARE.
Expand source code
# -*- coding: utf-8 -*-
"""GNUmed clinical calculator(s)
THIS IS NOT A VERIFIED CALCULATOR. DO NOT USE FOR ACTUAL CARE.
"""
#============================================================
__author__ = "K.Hilbert <Karsten.Hilbert@gmx.net>"
__license__ = "GPL v2 or later"
# standard libs
import sys
import logging
import decimal
import datetime as pydt
if __name__ == '__main__':
sys.path.insert(0, '../../')
from Gnumed.pycommon import gmDateTime
from Gnumed.pycommon import gmI18N
if __name__ == '__main__':
_ = lambda x:x
gmI18N.activate_locale()
gmI18N.install_domain()
gmDateTime.init()
from Gnumed.pycommon import gmTools
from Gnumed.business import gmLOINC
_log = logging.getLogger('gm.calc')
#============================================================
class cClinicalResult(object):
def __init__(self, message=None):
self.message = message
self.numeric_value = None
self.unit = None
self.date_valid = None
self.formula_name = None
self.formula_source = None
self.variables = {}
self.sub_results = []
self.warnings = [_('THIS IS NOT A VERIFIED MEASUREMENT. DO NOT USE FOR ACTUAL CARE.')]
self.hints = []
#--------------------------------------------------------
def __str__(self):
txt = '[cClinicalResult]: %s %s (%s)\n\n%s' % (
self.numeric_value,
self.unit,
self.date_valid,
self.format (
left_margin = 0,
width = 80,
eol = '\n',
with_formula = True,
with_warnings = True,
with_variables = True,
with_sub_results = True,
return_list = False
)
)
return txt
#--------------------------------------------------------
def format(self, left_margin=0, eol='\n', width=None, with_formula=False, with_warnings=True, with_variables=False, with_sub_results=False, with_hints=True, return_list=False):
lines = []
lines.append(self.message)
if with_formula:
txt = gmTools.wrap (
text = '%s %s' % (
_('Algorithm:'),
self.formula_name
),
width = width,
initial_indent = ' ',
subsequent_indent = ' ' * 2,
eol = eol
)
lines.append(txt)
txt = gmTools.wrap (
text = '%s %s' % (
_('Source:'),
self.formula_source
),
width = width,
initial_indent = ' ',
subsequent_indent = ' ' * 2,
eol = eol
)
lines.append(txt)
if with_warnings:
if len(self.warnings) > 0:
lines.append(' Caveat:')
for w in self.warnings:
txt = gmTools.wrap(text = w, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol)
lines.append(txt)
if with_hints:
if len(self.hints) > 0:
lines.append(' Hints:')
for h in self.hints:
txt = gmTools.wrap(text = h, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol)
lines.append(txt)
if with_variables:
if len(self.variables) > 0:
lines.append(' %s' % _('Variables:'))
for key in self.variables:
txt = ' %s %s: %s' % (
gmTools.u_arrow2right,
key,
self.variables[key]
)
lines.append(txt)
if with_sub_results:
if len(self.sub_results) > 0:
lines.append(' %s' % _('Intermediate results:'))
for r in self.sub_results:
lines.extend(r.format (
left_margin = left_margin + 1,
width = width,
eol = eol,
with_formula = with_formula,
with_warnings = with_warnings,
with_variables = with_variables,
with_sub_results = False, # break cycles
return_list = True
))
lines = gmTools.strip_trailing_empty_lines(lines = lines, eol = eol)
if return_list:
return lines
left_margin = ' ' * left_margin
return left_margin + (eol + left_margin).join(lines) + eol
#============================================================
class cClinicalCalculator(object):
def __init__(self, patient=None):
self.__cache = {}
self.__patient = patient
#--------------------------------------------------------
def _get_patient(self):
return self.__patient
def _set_patient(self, patient):
if patient == self.__patient:
return
self.__patient = patient
self.remove_from_cache() # uncache all values
patient = property(lambda x:x, _set_patient)
#--------------------------------------------------------
def remove_from_cache(self, key=None):
if key is None:
self.__cache = {}
return True
try:
del self.__cache[key]
return True
except KeyError:
_log.error('key [%s] does not exist in cache', key)
return False
#--------------------------------------------------------
# formulae
#--------------------------------------------------------
def get_EDC(self, lmp=None, nullipara=True):
result = cClinicalResult(_('unknown EDC'))
result.formula_name = 'EDC (Mittendorf 1990)'
result.formula_source = 'Mittendorf, R. et al., "The length of uncomplicated human gestation," OB/GYN, Vol. 75, No., 6 June, 1990, pp. 907-932.'
if lmp is None:
result.message = _('EDC: unknown LMP')
return result
result.variables['LMP'] = lmp
result.variables['nullipara'] = nullipara
if nullipara:
result.variables['parity_offset'] = 15 # days
else:
result.variables['parity_offset'] = 10 # days
now = gmDateTime.pydt_now_here()
if lmp > now:
result.warnings.append(_('LMP in the future'))
if self.__patient is None:
result.warnings.append(_('cannot run sanity checks, no patient'))
else:
if self.__patient['dob'] is None:
result.warnings.append(_('cannot run sanity checks, no DOB'))
else:
years, months, days, hours, minutes, seconds = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])
# 5 years -- Myth ?
# http://www.mirror.co.uk/news/uk-news/top-10-crazy-amazing-and-world-789842
if years < 10:
result.warnings.append(_('patient less than 10 years old'))
if self.__patient['gender'] in [None, 'm']:
result.warnings.append(_('atypical gender for pregnancy: %s') % self.__patient.gender_string)
if self.__patient['deceased'] is not None:
result.warnings.append(_('patient already passed away'))
if lmp.month > 3:
edc_month = lmp.month - 3
edc_year = lmp.year + 1
else:
edc_month = lmp.month + 9
edc_year = lmp.year
result.numeric_value = gmDateTime.pydt_replace(dt = lmp, year = edc_year, month = edc_month, strict = False) + pydt.timedelta(days = result.variables['parity_offset'])
result.message = _('EDC: %s') % gmDateTime.pydt_strftime (
result.numeric_value,
format = '%Y %b %d'
)
result.date_valid = now
_log.debug('%s' % result)
return result
#--------------------------------------------------------
def _get_egfrs(self):
egfrs = [
self.eGFR_MDRD_short,
self.eGFR_Cockcroft_Gault,
self.eGFR_CKD_EPI,
self.eGFR_Schwartz
]
return egfrs
eGFRs = property(_get_egfrs)
#--------------------------------------------------------
def _get_egfr(self):
# < 18 ?
Schwartz = self.eGFR_Schwartz
if Schwartz.numeric_value is not None:
return Schwartz
# this logic is based on "KVH aktuell 2/2014 Seite 10-15"
# expect normal GFR
CKD = self.eGFR_CKD_EPI
if CKD.numeric_value is not None:
if CKD.numeric_value > self.d(60):
return CKD
# CKD at or below 60
if self.__patient['dob'] is None:
return CKD # no method will work, so return CKD anyway
CG = self.eGFR_Cockcroft_Gault
MDRD = self.eGFR_MDRD_short
age = None
if age is None:
try:
age = CKD.variables['age@crea']
except KeyError:
_log.warning('CKD-EPI: no age@crea')
if age is None:
try:
age = CG.variables['age@crea']
except KeyError:
_log.warning('CG: no age@crea')
if age is None:
try:
age = MDRD.variables['age@crea']
except KeyError:
_log.warning('MDRD: no age@crea')
if age is None:
age = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])[0]
# geriatric ?
if age > self.d(65):
if CG.numeric_value is not None:
return CG
# non-geriatric or CG not computable
if MDRD.numeric_value is None:
if (CKD.numeric_value is not None) or (CG.numeric_value is None):
return CKD
return CG
if MDRD.numeric_value > self.d(60):
if CKD.numeric_value is not None:
# probably normal after all (>60) -> use CKD-EPI
return CKD
return MDRD
eGFR = property(_get_egfr)
#--------------------------------------------------------
def _get_gfr_mdrd_short(self):
try:
return self.__cache['MDRD_short']
except KeyError:
pass
result = cClinicalResult(_('unknown MDRD (4 vars/IDMS)'))
result.formula_name = 'eGFR from 4-variables IDMS-MDRD'
result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS)'
result.hints.append(_('best @ 30 < GFR < 60 ml/min'))
if self.__patient is None:
result.message = _('MDRD (4 vars/IDMS): no patient')
return result
if self.__patient['dob'] is None:
result.message = _('MDRD (4 vars/IDMS): no DOB (no age)')
return result
# 1) gender
from Gnumed.business.gmPerson import map_gender2mf
result.variables['gender'] = self.__patient['gender']
result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
if result.variables['gender_mf'] == 'm':
result.variables['gender_multiplier'] = self.d(1)
elif result.variables['gender_mf'] == 'f':
result.variables['gender_multiplier'] = self.d('0.742')
else:
result.message = _('MDRD (4 vars/IDMS): neither male nor female')
return result
# 2) creatinine
creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1)
result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None
if result.variables['serum_crea'] is None:
result.message = _('MDRD (4 vars/IDMS): serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
return result
if result.variables['serum_crea']['val_num'] is None:
result.message = _('MDRD (4 vars/IDMS): creatinine value not numeric')
return result
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
result.variables['unit_multiplier'] = self.d(175) # older: 186
elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
result.variables['unit_multiplier'] = self.d(30849) # older: 32788
else:
result.message = _('MDRD (4 vars/IDMS): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
return result
# 3) age (at creatinine evaluation)
result.variables['dob'] = self.__patient['dob']
result.variables['age@crea'] = self.d (
gmDateTime.calculate_apparent_age (
start = result.variables['dob'],
end = result.variables['serum_crea']['clin_when']
)[0]
)
if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18):
result.message = _('MDRD (4 vars/IDMS): formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea']
return result
# 4) ethnicity
result.variables['ethnicity_multiplier'] = self.d(1) # non-black
result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor'))
# calculate
result.numeric_value = result.variables['unit_multiplier'] * \
pow(result.variables['serum_crea_val'], self.d('-1.154')) * \
pow(result.variables['age@crea'], self.d('-0.203')) * \
result.variables['ethnicity_multiplier'] * \
result.variables['gender_multiplier']
result.unit = 'ml/min/1.73m²'
BSA = self.body_surface_area
result.sub_results.append(BSA)
if BSA.numeric_value is None:
result.warnings.append(_('NOT corrected for non-average body surface (average = 1.73m²)'))
else:
result.variables['BSA'] = BSA.numeric_value
result.numeric_value = result.numeric_value / BSA.numeric_value
result.message = _('eGFR(MDRD): %.1f %s (%s) [4-vars, IDMS]') % (
result.numeric_value,
result.unit,
gmDateTime.pydt_strftime (
result.variables['serum_crea']['clin_when'],
format = '%Y %b %d'
)
)
result.date_valid = result.variables['serum_crea']['clin_when']
self.__cache['MDRD_short'] = result
_log.debug('%s' % result)
return result
eGFR_MDRD_short = property(_get_gfr_mdrd_short)
#--------------------------------------------------------
def _get_gfr_ckd_epi(self):
try:
return self.__cache['CKD-EPI']
except KeyError:
pass
result = cClinicalResult(_('unknown CKD-EPI'))
result.formula_name = 'eGFR from CKD-EPI'
result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function'
result.hints.append(_('best @ GFR > 60 ml/min'))
if self.__patient is None:
result.message = _('CKD-EPI: no patient')
return result
if self.__patient['dob'] is None:
result.message = _('CKD-EPI: no DOB (no age)')
return result
# 1) gender
from Gnumed.business.gmPerson import map_gender2mf
result.variables['gender'] = self.__patient['gender']
result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
if result.variables['gender_mf'] == 'm':
result.variables['gender_multiplier'] = self.d(1)
result.variables['k:gender_divisor'] = self.d('0.9')
result.variables['a:gender_power'] = self.d('-0.411')
elif result.variables['gender_mf'] == 'f':
result.variables['gender_multiplier'] = self.d('1.018')
result.variables['k:gender_divisor'] = self.d('0.7')
result.variables['a:gender_power'] = self.d('-0.329')
else:
result.message = _('CKD-EPI: neither male nor female')
return result
# 2) creatinine
creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1)
result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None
if result.variables['serum_crea'] is None:
result.message = _('CKD-EPI: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
return result
if result.variables['serum_crea']['val_num'] is None:
result.message = _('CKD-EPI: creatinine value not numeric')
return result
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) / self.d('88.4')
else:
result.message = _('CKD-EPI: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
return result
# 3) age (at creatinine evaluation)
result.variables['dob'] = self.__patient['dob']
result.variables['age@crea'] = self.d (
gmDateTime.calculate_apparent_age (
start = result.variables['dob'],
end = result.variables['serum_crea']['clin_when']
)[0]
)
# if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18):
# result.message = _('CKD-EPI: formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea']
# return result
# 4) ethnicity
result.variables['ethnicity_multiplier'] = self.d(1) # non-black
result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor of 1.519 for "black"'))
# calculate
result.numeric_value = (
self.d(141) * \
pow(min((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), result.variables['a:gender_power']) * \
pow(max((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), self.d('-1.209')) * \
pow(self.d('0.993'), result.variables['age@crea']) * \
result.variables['gender_multiplier'] * \
result.variables['ethnicity_multiplier']
)
result.unit = 'ml/min/1.73m²'
result.message = _('eGFR(CKD-EPI): %.1f %s (%s)') % (
result.numeric_value,
result.unit,
gmDateTime.pydt_strftime (
result.variables['serum_crea']['clin_when'],
format = '%Y %b %d'
)
)
result.date_valid = result.variables['serum_crea']['clin_when']
self.__cache['CKD-EPI'] = result
_log.debug('%s' % result)
return result
eGFR_CKD_EPI = property(_get_gfr_ckd_epi)
#--------------------------------------------------------
def _get_gfr_cockcroft_gault(self):
try:
return self.__cache['cockcroft_gault']
except KeyError:
pass
result = cClinicalResult(_('unknown Cockcroft-Gault'))
result.formula_name = 'eGFR from Cockcroft-Gault'
result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function'
result.hints.append(_('best @ age >65'))
if self.__patient is None:
result.message = _('Cockcroft-Gault: no patient')
return result
if self.__patient['dob'] is None:
result.message = _('Cockcroft-Gault: no DOB (no age)')
return result
# 1) gender
from Gnumed.business.gmPerson import map_gender2mf
result.variables['gender'] = self.__patient['gender']
result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
if result.variables['gender_mf'] not in ['m', 'f']:
result.message = _('Cockcroft-Gault: neither male nor female')
return result
# 2) creatinine
creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1)
result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None
if result.variables['serum_crea'] is None:
result.message = _('Cockcroft-Gault: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
return result
if result.variables['serum_crea']['val_num'] is None:
result.message = _('Cockcroft-Gault: creatinine value not numeric')
return result
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
result.variables['unit_multiplier'] = self.d(72)
if result.variables['gender_mf'] == 'm':
result.variables['gender_multiplier'] = self.d('1')
else: #result.variables['gender_mf'] == 'f'
result.variables['gender_multiplier'] = self.d('0.85')
elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
result.variables['unit_multiplier'] = self.d(1)
if result.variables['gender_mf'] == 'm':
result.variables['gender_multiplier'] = self.d('1.23')
else: #result.variables['gender_mf'] == 'f'
result.variables['gender_multiplier'] = self.d('1.04')
else:
result.message = _('Cockcroft-Gault: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
return result
# 3) age (at creatinine evaluation)
result.variables['dob'] = self.__patient['dob']
result.variables['age@crea'] = self.d (
gmDateTime.calculate_apparent_age (
start = result.variables['dob'],
end = result.variables['serum_crea']['clin_when']
)[0]
)
if (result.variables['age@crea'] < 18):
result.message = _('Cockcroft-Gault: formula does not apply at age [%s] (17 < age)') % result.variables['age@crea']
return result
weights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_weight, max_no_of_results = 1)
result.variables['weight'] = weights[0] if len(weights) > 0 else None
if result.variables['weight'] is None:
result.message = _('Cockcroft-Gault: weight not found')
return result
if result.variables['weight']['val_num'] is None:
result.message = _('Cockcroft-Gault: weight not numeric')
return result
if result.variables['weight']['val_unit'] == 'kg':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
elif result.variables['weight']['val_unit'] == 'g':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
else:
result.message = _('Cockcroft-Gault: weight not in kg or g')
return result
# calculate
result.numeric_value = ((
(140 - result.variables['age@crea']) * result.variables['weight_kg'] * result.variables['gender_multiplier']) \
/ \
(result.variables['unit_multiplier'] * result.variables['serum_crea_val'])
)
result.unit = 'ml/min' #/1.73m²
result.message = _('eGFR(CG): %.1f %s (%s)') % (
result.numeric_value,
result.unit,
gmDateTime.pydt_strftime (
result.variables['serum_crea']['clin_when'],
format = '%Y %b %d'
)
)
result.date_valid = result.variables['serum_crea']['clin_when']
self.__cache['cockroft_gault'] = result
_log.debug('%s' % result)
return result
eGFR_Cockcroft_Gault = property(_get_gfr_cockcroft_gault)
#--------------------------------------------------------
def _get_gfr_schwartz(self):
try:
return self.__cache['gfr_schwartz']
except KeyError:
pass
result = cClinicalResult(_('unknown eGFR (Schwartz)'))
result.formula_name = 'eGFR from updated Schwartz "bedside" formula (age < 19yrs)'
result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS) / doi 10.1681/ASN.2008030287 / doi: 10.2215/CJN.01640309'
result.hints.append(_('only applies @ age <18'))
if self.__patient is None:
result.message = _('eGFR (Schwartz): no patient')
return result
if self.__patient['dob'] is None:
result.message = _('eGFR (Schwartz): DOB needed for age')
return result
result.variables['dob'] = self.__patient['dob']
# creatinine
creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1)
result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None
if result.variables['serum_crea'] is None:
result.message = _('eGFR (Schwartz): serum creatinine value not found (LOINC: %s') % gmLOINC.LOINC_creatinine_quantity
return result
if result.variables['serum_crea']['val_num'] is None:
result.message = _('eGFR (Schwartz): creatinine value not numeric')
return result
result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
result.variables['unit_multiplier'] = self.d(1)
elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
result.variables['unit_multiplier'] = self.d('0.00113')
else:
result.message = _('eGFR (Schwartz): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
return result
# age
result.variables['age@crea'] = self.d (
gmDateTime.calculate_apparent_age (
start = result.variables['dob'],
end = result.variables['serum_crea']['clin_when']
)[0]
)
if result.variables['age@crea'] > 17:
result.message = _('eGFR (Schwartz): formula does not apply at age [%s] (age must be <18)') % result.variables['age@crea']
return result
# age-dependant constant
if result.variables['age@crea'] < 1:
# first year pre-term: k = 0.33
# first year full-term: k = (0.45) 0.41 (updated)
result.variables['constant_for_age'] = self.d('0.41')
result.warnings.append(_('eGFR (Schwartz): not known whether pre-term birth, applying full-term formula'))
else:
result.variables['constant_for_age'] = self.d('0.41')
# height
result.variables['height'] = self.__patient.emr.get_result_at_timestamp (
timestamp = result.variables['serum_crea']['clin_when'],
loinc = gmLOINC.LOINC_height,
tolerance_interval = '7 days'
)
if result.variables['height'] is None:
result.message = _('eGFR (Schwartz): height not found')
return result
if result.variables['height']['val_num'] is None:
result.message = _('eGFR (Schwartz): height not numeric')
return result
if result.variables['height']['val_unit'] == 'cm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'])
elif result.variables['height']['val_unit'] == 'mm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10))
elif result.variables['height']['val_unit'] == 'm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100)
else:
result.message = _('eGFR (Schwartz): height not in m, cm, or mm')
return result
# calculate
result.numeric_value = (
result.variables['constant_for_age'] * result.variables['height_cm']
) / (
result.variables['unit_multiplier'] * result.variables['serum_crea_val']
)
result.unit = 'ml/min/1.73m²'
result.message = _('eGFR (Schwartz): %.1f %s (%s)') % (
result.numeric_value,
result.unit,
gmDateTime.pydt_strftime (
result.variables['serum_crea']['clin_when'],
format = '%Y %b %d'
)
)
result.date_valid = result.variables['serum_crea']['clin_when']
self.__cache['gfr_schwartz'] = result
_log.debug('%s' % result)
return result
eGFR_Schwartz = property(_get_gfr_schwartz)
#--------------------------------------------------------
def _get_body_surface_area(self):
try:
return self.__cache['body_surface_area']
except KeyError:
pass
result = cClinicalResult(_('unknown body surface area'))
result.formula_name = 'Du Bois Body Surface Area'
result.formula_source = '12/2012: http://en.wikipedia.org/wiki/Body_surface_area'
if self.__patient is None:
result.message = _('Body Surface Area: no patient')
return result
heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1)
result.variables['height'] = heights[0] if len(heights) > 0 else None
if result.variables['height'] is None:
result.message = _('Body Surface Area: height not found')
return result
if result.variables['height']['val_num'] is None:
result.message = _('Body Surface Area: height not numeric')
return result
if result.variables['height']['val_unit'] == 'cm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'])
elif result.variables['height']['val_unit'] == 'mm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10))
elif result.variables['height']['val_unit'] == 'm':
result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100)
else:
result.message = _('Body Surface Area: height not in m, cm, or mm')
return result
result.variables['weight'] = self.__patient.emr.get_result_at_timestamp (
timestamp = result.variables['height']['clin_when'],
loinc = gmLOINC.LOINC_weight,
tolerance_interval = '10 days'
)
if result.variables['weight'] is None:
result.message = _('Body Surface Area: weight not found')
return result
if result.variables['weight']['val_num'] is None:
result.message = _('Body Surface Area: weight not numeric')
return result
if result.variables['weight']['val_unit'] == 'kg':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
elif result.variables['weight']['val_unit'] == 'g':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
else:
result.message = _('Body Surface Area: weight not in kg or g')
return result
result.numeric_value = self.d('0.007184') * \
pow(result.variables['weight_kg'], self.d('0.425')) * \
pow(result.variables['height_cm'], self.d('0.725'))
result.unit = 'm²'
result.message = _('BSA (DuBois): %.2f %s') % (
result.numeric_value,
result.unit
)
result.date_valid = gmDateTime.pydt_now_here()
self.__cache['body_surface_area'] = result
_log.debug('%s' % result)
return result
body_surface_area = property(_get_body_surface_area)
#--------------------------------------------------------
def _get_body_mass_index(self):
try:
return self.__cache['body_mass_index']
except KeyError:
pass
result = cClinicalResult(_('unknown BMI'))
result.formula_name = 'BMI/Quetelet Index'
result.formula_source = '08/2014: https://en.wikipedia.org/wiki/Body_mass_index'
if self.__patient is None:
result.message = _('BMI: no patient')
return result
heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1)
result.variables['height'] = heights[0] if len(heights) > 0 else None
if result.variables['height'] is None:
result.message = _('BMI: height not found')
return result
if result.variables['height']['val_num'] is None:
result.message = _('BMI: height not numeric')
return result
if result.variables['height']['val_unit'] == 'cm':
result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(100))
elif result.variables['height']['val_unit'] == 'mm':
result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(1000))
elif result.variables['height']['val_unit'] == 'm':
result.variables['height_m'] = self.d(result.variables['height']['val_num'])
else:
result.message = _('BMI: height not in m, cm, or mm')
return result
result.variables['weight'] = self.__patient.emr.get_result_at_timestamp (
timestamp = result.variables['height']['clin_when'],
loinc = gmLOINC.LOINC_weight,
tolerance_interval = '10 days'
)
if result.variables['weight'] is None:
result.message = _('BMI: weight not found')
return result
if result.variables['weight']['val_num'] is None:
result.message = _('BMI: weight not numeric')
return result
if result.variables['weight']['val_unit'] == 'kg':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
elif result.variables['weight']['val_unit'] == 'g':
result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
else:
result.message = _('BMI: weight not in kg or g')
return result
result.variables['dob'] = self.__patient['dob']
start = result.variables['dob']
end = result.variables['height']['clin_when']
multiplier = 1
if end < start:
start = result.variables['height']['clin_when']
end = result.variables['dob']
multiplier = -1
result.variables['age@height'] = multiplier * self.d(gmDateTime.calculate_apparent_age(start, end)[0])
if (result.variables['age@height'] < 18):
result.message = _('BMI (Quetelet): formula does not apply at age [%s] (0 < age < 18)') % result.variables['age@height']
return result
# bmi = mass kg / height m2
result.numeric_value = result.variables['weight_kg'] / (result.variables['height_m'] * result.variables['height_m'])
result.unit = 'kg/m²'
result.message = _('BMI (Quetelet): %.2f %s') % (
result.numeric_value,
result.unit
)
result.date_valid = max(result.variables['height']['clin_when'], result.variables['weight']['clin_when'])
self.__cache['body_mass_index'] = result
_log.debug('%s' % result)
return result
body_mass_index = property(_get_body_mass_index)
bmi = property(_get_body_mass_index)
#--------------------------------------------------------
# helper functions
#--------------------------------------------------------
def d(self, initial):
if isinstance(initial, decimal.Decimal):
return initial
val = initial
# float ? -> to string first
if type(val) == type(float(1.4)):
val = str(val)
# string ? -> "," to "."
if isinstance(val, str):
val = val.replace(',', '.', 1)
val = val.strip()
try:
d = decimal.Decimal(val)
return d
except (TypeError, decimal.InvalidOperation):
return None
#============================================================
# main
#------------------------------------------------------------
if __name__ == "__main__":
if len(sys.argv) == 1:
sys.exit()
if sys.argv[1] != 'test':
sys.exit()
#-----------------------------------------
def test_clin_calc():
from Gnumed.business import gmPraxis
branches = gmPraxis.get_praxis_branches()
gmPraxis.gmCurrentPraxisBranch(branches[0])
from Gnumed.business.gmPerson import cPatient
pat = cPatient(aPK_obj = 201)
calc = cClinicalCalculator(patient = pat)
#result = calc.eGFR_MDRD_short
#result = calc.eGFR_Schwartz
result = calc.eGFR
#result = calc.body_surface_area
#result = calc.get_EDC(lmp = gmDateTime.pydt_now_here())
#result = calc.body_mass_index
#result = calc.eGFRs
print('%s' % result.format(with_formula = True, with_warnings = True, with_variables = True, with_sub_results = True))
#-----------------------------------------
test_clin_calc()Classes
class cClinicalCalculator (patient=None)-
Expand source code
class cClinicalCalculator(object): def __init__(self, patient=None): self.__cache = {} self.__patient = patient #-------------------------------------------------------- def _get_patient(self): return self.__patient def _set_patient(self, patient): if patient == self.__patient: return self.__patient = patient self.remove_from_cache() # uncache all values patient = property(lambda x:x, _set_patient) #-------------------------------------------------------- def remove_from_cache(self, key=None): if key is None: self.__cache = {} return True try: del self.__cache[key] return True except KeyError: _log.error('key [%s] does not exist in cache', key) return False #-------------------------------------------------------- # formulae #-------------------------------------------------------- def get_EDC(self, lmp=None, nullipara=True): result = cClinicalResult(_('unknown EDC')) result.formula_name = 'EDC (Mittendorf 1990)' result.formula_source = 'Mittendorf, R. et al., "The length of uncomplicated human gestation," OB/GYN, Vol. 75, No., 6 June, 1990, pp. 907-932.' if lmp is None: result.message = _('EDC: unknown LMP') return result result.variables['LMP'] = lmp result.variables['nullipara'] = nullipara if nullipara: result.variables['parity_offset'] = 15 # days else: result.variables['parity_offset'] = 10 # days now = gmDateTime.pydt_now_here() if lmp > now: result.warnings.append(_('LMP in the future')) if self.__patient is None: result.warnings.append(_('cannot run sanity checks, no patient')) else: if self.__patient['dob'] is None: result.warnings.append(_('cannot run sanity checks, no DOB')) else: years, months, days, hours, minutes, seconds = gmDateTime.calculate_apparent_age(start = self.__patient['dob']) # 5 years -- Myth ? # http://www.mirror.co.uk/news/uk-news/top-10-crazy-amazing-and-world-789842 if years < 10: result.warnings.append(_('patient less than 10 years old')) if self.__patient['gender'] in [None, 'm']: result.warnings.append(_('atypical gender for pregnancy: %s') % self.__patient.gender_string) if self.__patient['deceased'] is not None: result.warnings.append(_('patient already passed away')) if lmp.month > 3: edc_month = lmp.month - 3 edc_year = lmp.year + 1 else: edc_month = lmp.month + 9 edc_year = lmp.year result.numeric_value = gmDateTime.pydt_replace(dt = lmp, year = edc_year, month = edc_month, strict = False) + pydt.timedelta(days = result.variables['parity_offset']) result.message = _('EDC: %s') % gmDateTime.pydt_strftime ( result.numeric_value, format = '%Y %b %d' ) result.date_valid = now _log.debug('%s' % result) return result #-------------------------------------------------------- def _get_egfrs(self): egfrs = [ self.eGFR_MDRD_short, self.eGFR_Cockcroft_Gault, self.eGFR_CKD_EPI, self.eGFR_Schwartz ] return egfrs eGFRs = property(_get_egfrs) #-------------------------------------------------------- def _get_egfr(self): # < 18 ? Schwartz = self.eGFR_Schwartz if Schwartz.numeric_value is not None: return Schwartz # this logic is based on "KVH aktuell 2/2014 Seite 10-15" # expect normal GFR CKD = self.eGFR_CKD_EPI if CKD.numeric_value is not None: if CKD.numeric_value > self.d(60): return CKD # CKD at or below 60 if self.__patient['dob'] is None: return CKD # no method will work, so return CKD anyway CG = self.eGFR_Cockcroft_Gault MDRD = self.eGFR_MDRD_short age = None if age is None: try: age = CKD.variables['age@crea'] except KeyError: _log.warning('CKD-EPI: no age@crea') if age is None: try: age = CG.variables['age@crea'] except KeyError: _log.warning('CG: no age@crea') if age is None: try: age = MDRD.variables['age@crea'] except KeyError: _log.warning('MDRD: no age@crea') if age is None: age = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])[0] # geriatric ? if age > self.d(65): if CG.numeric_value is not None: return CG # non-geriatric or CG not computable if MDRD.numeric_value is None: if (CKD.numeric_value is not None) or (CG.numeric_value is None): return CKD return CG if MDRD.numeric_value > self.d(60): if CKD.numeric_value is not None: # probably normal after all (>60) -> use CKD-EPI return CKD return MDRD eGFR = property(_get_egfr) #-------------------------------------------------------- def _get_gfr_mdrd_short(self): try: return self.__cache['MDRD_short'] except KeyError: pass result = cClinicalResult(_('unknown MDRD (4 vars/IDMS)')) result.formula_name = 'eGFR from 4-variables IDMS-MDRD' result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS)' result.hints.append(_('best @ 30 < GFR < 60 ml/min')) if self.__patient is None: result.message = _('MDRD (4 vars/IDMS): no patient') return result if self.__patient['dob'] is None: result.message = _('MDRD (4 vars/IDMS): no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d(1) elif result.variables['gender_mf'] == 'f': result.variables['gender_multiplier'] = self.d('0.742') else: result.message = _('MDRD (4 vars/IDMS): neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('MDRD (4 vars/IDMS): serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('MDRD (4 vars/IDMS): creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(175) # older: 186 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d(30849) # older: 32788 else: result.message = _('MDRD (4 vars/IDMS): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18): result.message = _('MDRD (4 vars/IDMS): formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea'] return result # 4) ethnicity result.variables['ethnicity_multiplier'] = self.d(1) # non-black result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor')) # calculate result.numeric_value = result.variables['unit_multiplier'] * \ pow(result.variables['serum_crea_val'], self.d('-1.154')) * \ pow(result.variables['age@crea'], self.d('-0.203')) * \ result.variables['ethnicity_multiplier'] * \ result.variables['gender_multiplier'] result.unit = 'ml/min/1.73m²' BSA = self.body_surface_area result.sub_results.append(BSA) if BSA.numeric_value is None: result.warnings.append(_('NOT corrected for non-average body surface (average = 1.73m²)')) else: result.variables['BSA'] = BSA.numeric_value result.numeric_value = result.numeric_value / BSA.numeric_value result.message = _('eGFR(MDRD): %.1f %s (%s) [4-vars, IDMS]') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['MDRD_short'] = result _log.debug('%s' % result) return result eGFR_MDRD_short = property(_get_gfr_mdrd_short) #-------------------------------------------------------- def _get_gfr_ckd_epi(self): try: return self.__cache['CKD-EPI'] except KeyError: pass result = cClinicalResult(_('unknown CKD-EPI')) result.formula_name = 'eGFR from CKD-EPI' result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function' result.hints.append(_('best @ GFR > 60 ml/min')) if self.__patient is None: result.message = _('CKD-EPI: no patient') return result if self.__patient['dob'] is None: result.message = _('CKD-EPI: no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d(1) result.variables['k:gender_divisor'] = self.d('0.9') result.variables['a:gender_power'] = self.d('-0.411') elif result.variables['gender_mf'] == 'f': result.variables['gender_multiplier'] = self.d('1.018') result.variables['k:gender_divisor'] = self.d('0.7') result.variables['a:gender_power'] = self.d('-0.329') else: result.message = _('CKD-EPI: neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('CKD-EPI: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('CKD-EPI: creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) / self.d('88.4') else: result.message = _('CKD-EPI: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) # if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18): # result.message = _('CKD-EPI: formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea'] # return result # 4) ethnicity result.variables['ethnicity_multiplier'] = self.d(1) # non-black result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor of 1.519 for "black"')) # calculate result.numeric_value = ( self.d(141) * \ pow(min((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), result.variables['a:gender_power']) * \ pow(max((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), self.d('-1.209')) * \ pow(self.d('0.993'), result.variables['age@crea']) * \ result.variables['gender_multiplier'] * \ result.variables['ethnicity_multiplier'] ) result.unit = 'ml/min/1.73m²' result.message = _('eGFR(CKD-EPI): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['CKD-EPI'] = result _log.debug('%s' % result) return result eGFR_CKD_EPI = property(_get_gfr_ckd_epi) #-------------------------------------------------------- def _get_gfr_cockcroft_gault(self): try: return self.__cache['cockcroft_gault'] except KeyError: pass result = cClinicalResult(_('unknown Cockcroft-Gault')) result.formula_name = 'eGFR from Cockcroft-Gault' result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function' result.hints.append(_('best @ age >65')) if self.__patient is None: result.message = _('Cockcroft-Gault: no patient') return result if self.__patient['dob'] is None: result.message = _('Cockcroft-Gault: no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] not in ['m', 'f']: result.message = _('Cockcroft-Gault: neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('Cockcroft-Gault: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('Cockcroft-Gault: creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(72) if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d('1') else: #result.variables['gender_mf'] == 'f' result.variables['gender_multiplier'] = self.d('0.85') elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d(1) if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d('1.23') else: #result.variables['gender_mf'] == 'f' result.variables['gender_multiplier'] = self.d('1.04') else: result.message = _('Cockcroft-Gault: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if (result.variables['age@crea'] < 18): result.message = _('Cockcroft-Gault: formula does not apply at age [%s] (17 < age)') % result.variables['age@crea'] return result weights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_weight, max_no_of_results = 1) result.variables['weight'] = weights[0] if len(weights) > 0 else None if result.variables['weight'] is None: result.message = _('Cockcroft-Gault: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('Cockcroft-Gault: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('Cockcroft-Gault: weight not in kg or g') return result # calculate result.numeric_value = (( (140 - result.variables['age@crea']) * result.variables['weight_kg'] * result.variables['gender_multiplier']) \ / \ (result.variables['unit_multiplier'] * result.variables['serum_crea_val']) ) result.unit = 'ml/min' #/1.73m² result.message = _('eGFR(CG): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['cockroft_gault'] = result _log.debug('%s' % result) return result eGFR_Cockcroft_Gault = property(_get_gfr_cockcroft_gault) #-------------------------------------------------------- def _get_gfr_schwartz(self): try: return self.__cache['gfr_schwartz'] except KeyError: pass result = cClinicalResult(_('unknown eGFR (Schwartz)')) result.formula_name = 'eGFR from updated Schwartz "bedside" formula (age < 19yrs)' result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS) / doi 10.1681/ASN.2008030287 / doi: 10.2215/CJN.01640309' result.hints.append(_('only applies @ age <18')) if self.__patient is None: result.message = _('eGFR (Schwartz): no patient') return result if self.__patient['dob'] is None: result.message = _('eGFR (Schwartz): DOB needed for age') return result result.variables['dob'] = self.__patient['dob'] # creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('eGFR (Schwartz): serum creatinine value not found (LOINC: %s') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('eGFR (Schwartz): creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(1) elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d('0.00113') else: result.message = _('eGFR (Schwartz): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # age result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if result.variables['age@crea'] > 17: result.message = _('eGFR (Schwartz): formula does not apply at age [%s] (age must be <18)') % result.variables['age@crea'] return result # age-dependant constant if result.variables['age@crea'] < 1: # first year pre-term: k = 0.33 # first year full-term: k = (0.45) 0.41 (updated) result.variables['constant_for_age'] = self.d('0.41') result.warnings.append(_('eGFR (Schwartz): not known whether pre-term birth, applying full-term formula')) else: result.variables['constant_for_age'] = self.d('0.41') # height result.variables['height'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['serum_crea']['clin_when'], loinc = gmLOINC.LOINC_height, tolerance_interval = '7 days' ) if result.variables['height'] is None: result.message = _('eGFR (Schwartz): height not found') return result if result.variables['height']['val_num'] is None: result.message = _('eGFR (Schwartz): height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_cm'] = self.d(result.variables['height']['val_num']) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100) else: result.message = _('eGFR (Schwartz): height not in m, cm, or mm') return result # calculate result.numeric_value = ( result.variables['constant_for_age'] * result.variables['height_cm'] ) / ( result.variables['unit_multiplier'] * result.variables['serum_crea_val'] ) result.unit = 'ml/min/1.73m²' result.message = _('eGFR (Schwartz): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['gfr_schwartz'] = result _log.debug('%s' % result) return result eGFR_Schwartz = property(_get_gfr_schwartz) #-------------------------------------------------------- def _get_body_surface_area(self): try: return self.__cache['body_surface_area'] except KeyError: pass result = cClinicalResult(_('unknown body surface area')) result.formula_name = 'Du Bois Body Surface Area' result.formula_source = '12/2012: http://en.wikipedia.org/wiki/Body_surface_area' if self.__patient is None: result.message = _('Body Surface Area: no patient') return result heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1) result.variables['height'] = heights[0] if len(heights) > 0 else None if result.variables['height'] is None: result.message = _('Body Surface Area: height not found') return result if result.variables['height']['val_num'] is None: result.message = _('Body Surface Area: height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_cm'] = self.d(result.variables['height']['val_num']) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100) else: result.message = _('Body Surface Area: height not in m, cm, or mm') return result result.variables['weight'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['height']['clin_when'], loinc = gmLOINC.LOINC_weight, tolerance_interval = '10 days' ) if result.variables['weight'] is None: result.message = _('Body Surface Area: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('Body Surface Area: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('Body Surface Area: weight not in kg or g') return result result.numeric_value = self.d('0.007184') * \ pow(result.variables['weight_kg'], self.d('0.425')) * \ pow(result.variables['height_cm'], self.d('0.725')) result.unit = 'm²' result.message = _('BSA (DuBois): %.2f %s') % ( result.numeric_value, result.unit ) result.date_valid = gmDateTime.pydt_now_here() self.__cache['body_surface_area'] = result _log.debug('%s' % result) return result body_surface_area = property(_get_body_surface_area) #-------------------------------------------------------- def _get_body_mass_index(self): try: return self.__cache['body_mass_index'] except KeyError: pass result = cClinicalResult(_('unknown BMI')) result.formula_name = 'BMI/Quetelet Index' result.formula_source = '08/2014: https://en.wikipedia.org/wiki/Body_mass_index' if self.__patient is None: result.message = _('BMI: no patient') return result heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1) result.variables['height'] = heights[0] if len(heights) > 0 else None if result.variables['height'] is None: result.message = _('BMI: height not found') return result if result.variables['height']['val_num'] is None: result.message = _('BMI: height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(100)) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(1000)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_m'] = self.d(result.variables['height']['val_num']) else: result.message = _('BMI: height not in m, cm, or mm') return result result.variables['weight'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['height']['clin_when'], loinc = gmLOINC.LOINC_weight, tolerance_interval = '10 days' ) if result.variables['weight'] is None: result.message = _('BMI: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('BMI: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('BMI: weight not in kg or g') return result result.variables['dob'] = self.__patient['dob'] start = result.variables['dob'] end = result.variables['height']['clin_when'] multiplier = 1 if end < start: start = result.variables['height']['clin_when'] end = result.variables['dob'] multiplier = -1 result.variables['age@height'] = multiplier * self.d(gmDateTime.calculate_apparent_age(start, end)[0]) if (result.variables['age@height'] < 18): result.message = _('BMI (Quetelet): formula does not apply at age [%s] (0 < age < 18)') % result.variables['age@height'] return result # bmi = mass kg / height m2 result.numeric_value = result.variables['weight_kg'] / (result.variables['height_m'] * result.variables['height_m']) result.unit = 'kg/m²' result.message = _('BMI (Quetelet): %.2f %s') % ( result.numeric_value, result.unit ) result.date_valid = max(result.variables['height']['clin_when'], result.variables['weight']['clin_when']) self.__cache['body_mass_index'] = result _log.debug('%s' % result) return result body_mass_index = property(_get_body_mass_index) bmi = property(_get_body_mass_index) #-------------------------------------------------------- # helper functions #-------------------------------------------------------- def d(self, initial): if isinstance(initial, decimal.Decimal): return initial val = initial # float ? -> to string first if type(val) == type(float(1.4)): val = str(val) # string ? -> "," to "." if isinstance(val, str): val = val.replace(',', '.', 1) val = val.strip() try: d = decimal.Decimal(val) return d except (TypeError, decimal.InvalidOperation): return NoneInstance variables
var bmi-
Expand source code
def _get_body_mass_index(self): try: return self.__cache['body_mass_index'] except KeyError: pass result = cClinicalResult(_('unknown BMI')) result.formula_name = 'BMI/Quetelet Index' result.formula_source = '08/2014: https://en.wikipedia.org/wiki/Body_mass_index' if self.__patient is None: result.message = _('BMI: no patient') return result heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1) result.variables['height'] = heights[0] if len(heights) > 0 else None if result.variables['height'] is None: result.message = _('BMI: height not found') return result if result.variables['height']['val_num'] is None: result.message = _('BMI: height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(100)) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(1000)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_m'] = self.d(result.variables['height']['val_num']) else: result.message = _('BMI: height not in m, cm, or mm') return result result.variables['weight'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['height']['clin_when'], loinc = gmLOINC.LOINC_weight, tolerance_interval = '10 days' ) if result.variables['weight'] is None: result.message = _('BMI: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('BMI: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('BMI: weight not in kg or g') return result result.variables['dob'] = self.__patient['dob'] start = result.variables['dob'] end = result.variables['height']['clin_when'] multiplier = 1 if end < start: start = result.variables['height']['clin_when'] end = result.variables['dob'] multiplier = -1 result.variables['age@height'] = multiplier * self.d(gmDateTime.calculate_apparent_age(start, end)[0]) if (result.variables['age@height'] < 18): result.message = _('BMI (Quetelet): formula does not apply at age [%s] (0 < age < 18)') % result.variables['age@height'] return result # bmi = mass kg / height m2 result.numeric_value = result.variables['weight_kg'] / (result.variables['height_m'] * result.variables['height_m']) result.unit = 'kg/m²' result.message = _('BMI (Quetelet): %.2f %s') % ( result.numeric_value, result.unit ) result.date_valid = max(result.variables['height']['clin_when'], result.variables['weight']['clin_when']) self.__cache['body_mass_index'] = result _log.debug('%s' % result) return result var body_mass_index-
Expand source code
def _get_body_mass_index(self): try: return self.__cache['body_mass_index'] except KeyError: pass result = cClinicalResult(_('unknown BMI')) result.formula_name = 'BMI/Quetelet Index' result.formula_source = '08/2014: https://en.wikipedia.org/wiki/Body_mass_index' if self.__patient is None: result.message = _('BMI: no patient') return result heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1) result.variables['height'] = heights[0] if len(heights) > 0 else None if result.variables['height'] is None: result.message = _('BMI: height not found') return result if result.variables['height']['val_num'] is None: result.message = _('BMI: height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(100)) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(1000)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_m'] = self.d(result.variables['height']['val_num']) else: result.message = _('BMI: height not in m, cm, or mm') return result result.variables['weight'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['height']['clin_when'], loinc = gmLOINC.LOINC_weight, tolerance_interval = '10 days' ) if result.variables['weight'] is None: result.message = _('BMI: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('BMI: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('BMI: weight not in kg or g') return result result.variables['dob'] = self.__patient['dob'] start = result.variables['dob'] end = result.variables['height']['clin_when'] multiplier = 1 if end < start: start = result.variables['height']['clin_when'] end = result.variables['dob'] multiplier = -1 result.variables['age@height'] = multiplier * self.d(gmDateTime.calculate_apparent_age(start, end)[0]) if (result.variables['age@height'] < 18): result.message = _('BMI (Quetelet): formula does not apply at age [%s] (0 < age < 18)') % result.variables['age@height'] return result # bmi = mass kg / height m2 result.numeric_value = result.variables['weight_kg'] / (result.variables['height_m'] * result.variables['height_m']) result.unit = 'kg/m²' result.message = _('BMI (Quetelet): %.2f %s') % ( result.numeric_value, result.unit ) result.date_valid = max(result.variables['height']['clin_when'], result.variables['weight']['clin_when']) self.__cache['body_mass_index'] = result _log.debug('%s' % result) return result var body_surface_area-
Expand source code
def _get_body_surface_area(self): try: return self.__cache['body_surface_area'] except KeyError: pass result = cClinicalResult(_('unknown body surface area')) result.formula_name = 'Du Bois Body Surface Area' result.formula_source = '12/2012: http://en.wikipedia.org/wiki/Body_surface_area' if self.__patient is None: result.message = _('Body Surface Area: no patient') return result heights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_height, max_no_of_results = 1) result.variables['height'] = heights[0] if len(heights) > 0 else None if result.variables['height'] is None: result.message = _('Body Surface Area: height not found') return result if result.variables['height']['val_num'] is None: result.message = _('Body Surface Area: height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_cm'] = self.d(result.variables['height']['val_num']) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100) else: result.message = _('Body Surface Area: height not in m, cm, or mm') return result result.variables['weight'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['height']['clin_when'], loinc = gmLOINC.LOINC_weight, tolerance_interval = '10 days' ) if result.variables['weight'] is None: result.message = _('Body Surface Area: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('Body Surface Area: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('Body Surface Area: weight not in kg or g') return result result.numeric_value = self.d('0.007184') * \ pow(result.variables['weight_kg'], self.d('0.425')) * \ pow(result.variables['height_cm'], self.d('0.725')) result.unit = 'm²' result.message = _('BSA (DuBois): %.2f %s') % ( result.numeric_value, result.unit ) result.date_valid = gmDateTime.pydt_now_here() self.__cache['body_surface_area'] = result _log.debug('%s' % result) return result var eGFR-
Expand source code
def _get_egfr(self): # < 18 ? Schwartz = self.eGFR_Schwartz if Schwartz.numeric_value is not None: return Schwartz # this logic is based on "KVH aktuell 2/2014 Seite 10-15" # expect normal GFR CKD = self.eGFR_CKD_EPI if CKD.numeric_value is not None: if CKD.numeric_value > self.d(60): return CKD # CKD at or below 60 if self.__patient['dob'] is None: return CKD # no method will work, so return CKD anyway CG = self.eGFR_Cockcroft_Gault MDRD = self.eGFR_MDRD_short age = None if age is None: try: age = CKD.variables['age@crea'] except KeyError: _log.warning('CKD-EPI: no age@crea') if age is None: try: age = CG.variables['age@crea'] except KeyError: _log.warning('CG: no age@crea') if age is None: try: age = MDRD.variables['age@crea'] except KeyError: _log.warning('MDRD: no age@crea') if age is None: age = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])[0] # geriatric ? if age > self.d(65): if CG.numeric_value is not None: return CG # non-geriatric or CG not computable if MDRD.numeric_value is None: if (CKD.numeric_value is not None) or (CG.numeric_value is None): return CKD return CG if MDRD.numeric_value > self.d(60): if CKD.numeric_value is not None: # probably normal after all (>60) -> use CKD-EPI return CKD return MDRD var eGFR_CKD_EPI-
Expand source code
def _get_gfr_ckd_epi(self): try: return self.__cache['CKD-EPI'] except KeyError: pass result = cClinicalResult(_('unknown CKD-EPI')) result.formula_name = 'eGFR from CKD-EPI' result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function' result.hints.append(_('best @ GFR > 60 ml/min')) if self.__patient is None: result.message = _('CKD-EPI: no patient') return result if self.__patient['dob'] is None: result.message = _('CKD-EPI: no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d(1) result.variables['k:gender_divisor'] = self.d('0.9') result.variables['a:gender_power'] = self.d('-0.411') elif result.variables['gender_mf'] == 'f': result.variables['gender_multiplier'] = self.d('1.018') result.variables['k:gender_divisor'] = self.d('0.7') result.variables['a:gender_power'] = self.d('-0.329') else: result.message = _('CKD-EPI: neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('CKD-EPI: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('CKD-EPI: creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) / self.d('88.4') else: result.message = _('CKD-EPI: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) # if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18): # result.message = _('CKD-EPI: formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea'] # return result # 4) ethnicity result.variables['ethnicity_multiplier'] = self.d(1) # non-black result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor of 1.519 for "black"')) # calculate result.numeric_value = ( self.d(141) * \ pow(min((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), result.variables['a:gender_power']) * \ pow(max((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), self.d('-1.209')) * \ pow(self.d('0.993'), result.variables['age@crea']) * \ result.variables['gender_multiplier'] * \ result.variables['ethnicity_multiplier'] ) result.unit = 'ml/min/1.73m²' result.message = _('eGFR(CKD-EPI): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['CKD-EPI'] = result _log.debug('%s' % result) return result var eGFR_Cockcroft_Gault-
Expand source code
def _get_gfr_cockcroft_gault(self): try: return self.__cache['cockcroft_gault'] except KeyError: pass result = cClinicalResult(_('unknown Cockcroft-Gault')) result.formula_name = 'eGFR from Cockcroft-Gault' result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function' result.hints.append(_('best @ age >65')) if self.__patient is None: result.message = _('Cockcroft-Gault: no patient') return result if self.__patient['dob'] is None: result.message = _('Cockcroft-Gault: no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] not in ['m', 'f']: result.message = _('Cockcroft-Gault: neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('Cockcroft-Gault: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('Cockcroft-Gault: creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(72) if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d('1') else: #result.variables['gender_mf'] == 'f' result.variables['gender_multiplier'] = self.d('0.85') elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d(1) if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d('1.23') else: #result.variables['gender_mf'] == 'f' result.variables['gender_multiplier'] = self.d('1.04') else: result.message = _('Cockcroft-Gault: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if (result.variables['age@crea'] < 18): result.message = _('Cockcroft-Gault: formula does not apply at age [%s] (17 < age)') % result.variables['age@crea'] return result weights = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_weight, max_no_of_results = 1) result.variables['weight'] = weights[0] if len(weights) > 0 else None if result.variables['weight'] is None: result.message = _('Cockcroft-Gault: weight not found') return result if result.variables['weight']['val_num'] is None: result.message = _('Cockcroft-Gault: weight not numeric') return result if result.variables['weight']['val_unit'] == 'kg': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num']) elif result.variables['weight']['val_unit'] == 'g': result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000)) else: result.message = _('Cockcroft-Gault: weight not in kg or g') return result # calculate result.numeric_value = (( (140 - result.variables['age@crea']) * result.variables['weight_kg'] * result.variables['gender_multiplier']) \ / \ (result.variables['unit_multiplier'] * result.variables['serum_crea_val']) ) result.unit = 'ml/min' #/1.73m² result.message = _('eGFR(CG): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['cockroft_gault'] = result _log.debug('%s' % result) return result var eGFR_MDRD_short-
Expand source code
def _get_gfr_mdrd_short(self): try: return self.__cache['MDRD_short'] except KeyError: pass result = cClinicalResult(_('unknown MDRD (4 vars/IDMS)')) result.formula_name = 'eGFR from 4-variables IDMS-MDRD' result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS)' result.hints.append(_('best @ 30 < GFR < 60 ml/min')) if self.__patient is None: result.message = _('MDRD (4 vars/IDMS): no patient') return result if self.__patient['dob'] is None: result.message = _('MDRD (4 vars/IDMS): no DOB (no age)') return result # 1) gender from Gnumed.business.gmPerson import map_gender2mf result.variables['gender'] = self.__patient['gender'] result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']] if result.variables['gender_mf'] == 'm': result.variables['gender_multiplier'] = self.d(1) elif result.variables['gender_mf'] == 'f': result.variables['gender_multiplier'] = self.d('0.742') else: result.message = _('MDRD (4 vars/IDMS): neither male nor female') return result # 2) creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('MDRD (4 vars/IDMS): serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('MDRD (4 vars/IDMS): creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(175) # older: 186 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d(30849) # older: 32788 else: result.message = _('MDRD (4 vars/IDMS): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # 3) age (at creatinine evaluation) result.variables['dob'] = self.__patient['dob'] result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18): result.message = _('MDRD (4 vars/IDMS): formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea'] return result # 4) ethnicity result.variables['ethnicity_multiplier'] = self.d(1) # non-black result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor')) # calculate result.numeric_value = result.variables['unit_multiplier'] * \ pow(result.variables['serum_crea_val'], self.d('-1.154')) * \ pow(result.variables['age@crea'], self.d('-0.203')) * \ result.variables['ethnicity_multiplier'] * \ result.variables['gender_multiplier'] result.unit = 'ml/min/1.73m²' BSA = self.body_surface_area result.sub_results.append(BSA) if BSA.numeric_value is None: result.warnings.append(_('NOT corrected for non-average body surface (average = 1.73m²)')) else: result.variables['BSA'] = BSA.numeric_value result.numeric_value = result.numeric_value / BSA.numeric_value result.message = _('eGFR(MDRD): %.1f %s (%s) [4-vars, IDMS]') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['MDRD_short'] = result _log.debug('%s' % result) return result var eGFR_Schwartz-
Expand source code
def _get_gfr_schwartz(self): try: return self.__cache['gfr_schwartz'] except KeyError: pass result = cClinicalResult(_('unknown eGFR (Schwartz)')) result.formula_name = 'eGFR from updated Schwartz "bedside" formula (age < 19yrs)' result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS) / doi 10.1681/ASN.2008030287 / doi: 10.2215/CJN.01640309' result.hints.append(_('only applies @ age <18')) if self.__patient is None: result.message = _('eGFR (Schwartz): no patient') return result if self.__patient['dob'] is None: result.message = _('eGFR (Schwartz): DOB needed for age') return result result.variables['dob'] = self.__patient['dob'] # creatinine creas = self.__patient.emr.get_most_recent_results_in_loinc_group(loincs = gmLOINC.LOINC_creatinine_quantity, max_no_of_results = 1) result.variables['serum_crea'] = creas[0] if len(creas) > 0 else None if result.variables['serum_crea'] is None: result.message = _('eGFR (Schwartz): serum creatinine value not found (LOINC: %s') % gmLOINC.LOINC_creatinine_quantity return result if result.variables['serum_crea']['val_num'] is None: result.message = _('eGFR (Schwartz): creatinine value not numeric') return result result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']: result.variables['unit_multiplier'] = self.d(1) elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']: result.variables['unit_multiplier'] = self.d('0.00113') else: result.message = _('eGFR (Schwartz): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit'] return result # age result.variables['age@crea'] = self.d ( gmDateTime.calculate_apparent_age ( start = result.variables['dob'], end = result.variables['serum_crea']['clin_when'] )[0] ) if result.variables['age@crea'] > 17: result.message = _('eGFR (Schwartz): formula does not apply at age [%s] (age must be <18)') % result.variables['age@crea'] return result # age-dependant constant if result.variables['age@crea'] < 1: # first year pre-term: k = 0.33 # first year full-term: k = (0.45) 0.41 (updated) result.variables['constant_for_age'] = self.d('0.41') result.warnings.append(_('eGFR (Schwartz): not known whether pre-term birth, applying full-term formula')) else: result.variables['constant_for_age'] = self.d('0.41') # height result.variables['height'] = self.__patient.emr.get_result_at_timestamp ( timestamp = result.variables['serum_crea']['clin_when'], loinc = gmLOINC.LOINC_height, tolerance_interval = '7 days' ) if result.variables['height'] is None: result.message = _('eGFR (Schwartz): height not found') return result if result.variables['height']['val_num'] is None: result.message = _('eGFR (Schwartz): height not numeric') return result if result.variables['height']['val_unit'] == 'cm': result.variables['height_cm'] = self.d(result.variables['height']['val_num']) elif result.variables['height']['val_unit'] == 'mm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10)) elif result.variables['height']['val_unit'] == 'm': result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100) else: result.message = _('eGFR (Schwartz): height not in m, cm, or mm') return result # calculate result.numeric_value = ( result.variables['constant_for_age'] * result.variables['height_cm'] ) / ( result.variables['unit_multiplier'] * result.variables['serum_crea_val'] ) result.unit = 'ml/min/1.73m²' result.message = _('eGFR (Schwartz): %.1f %s (%s)') % ( result.numeric_value, result.unit, gmDateTime.pydt_strftime ( result.variables['serum_crea']['clin_when'], format = '%Y %b %d' ) ) result.date_valid = result.variables['serum_crea']['clin_when'] self.__cache['gfr_schwartz'] = result _log.debug('%s' % result) return result var eGFRs-
Expand source code
def _get_egfrs(self): egfrs = [ self.eGFR_MDRD_short, self.eGFR_Cockcroft_Gault, self.eGFR_CKD_EPI, self.eGFR_Schwartz ] return egfrs var patient-
Expand source code
patient = property(lambda x:x, _set_patient)
Methods
def d(self, initial)-
Expand source code
def d(self, initial): if isinstance(initial, decimal.Decimal): return initial val = initial # float ? -> to string first if type(val) == type(float(1.4)): val = str(val) # string ? -> "," to "." if isinstance(val, str): val = val.replace(',', '.', 1) val = val.strip() try: d = decimal.Decimal(val) return d except (TypeError, decimal.InvalidOperation): return None def get_EDC(self, lmp=None, nullipara=True)-
Expand source code
def get_EDC(self, lmp=None, nullipara=True): result = cClinicalResult(_('unknown EDC')) result.formula_name = 'EDC (Mittendorf 1990)' result.formula_source = 'Mittendorf, R. et al., "The length of uncomplicated human gestation," OB/GYN, Vol. 75, No., 6 June, 1990, pp. 907-932.' if lmp is None: result.message = _('EDC: unknown LMP') return result result.variables['LMP'] = lmp result.variables['nullipara'] = nullipara if nullipara: result.variables['parity_offset'] = 15 # days else: result.variables['parity_offset'] = 10 # days now = gmDateTime.pydt_now_here() if lmp > now: result.warnings.append(_('LMP in the future')) if self.__patient is None: result.warnings.append(_('cannot run sanity checks, no patient')) else: if self.__patient['dob'] is None: result.warnings.append(_('cannot run sanity checks, no DOB')) else: years, months, days, hours, minutes, seconds = gmDateTime.calculate_apparent_age(start = self.__patient['dob']) # 5 years -- Myth ? # http://www.mirror.co.uk/news/uk-news/top-10-crazy-amazing-and-world-789842 if years < 10: result.warnings.append(_('patient less than 10 years old')) if self.__patient['gender'] in [None, 'm']: result.warnings.append(_('atypical gender for pregnancy: %s') % self.__patient.gender_string) if self.__patient['deceased'] is not None: result.warnings.append(_('patient already passed away')) if lmp.month > 3: edc_month = lmp.month - 3 edc_year = lmp.year + 1 else: edc_month = lmp.month + 9 edc_year = lmp.year result.numeric_value = gmDateTime.pydt_replace(dt = lmp, year = edc_year, month = edc_month, strict = False) + pydt.timedelta(days = result.variables['parity_offset']) result.message = _('EDC: %s') % gmDateTime.pydt_strftime ( result.numeric_value, format = '%Y %b %d' ) result.date_valid = now _log.debug('%s' % result) return result def remove_from_cache(self, key=None)-
Expand source code
def remove_from_cache(self, key=None): if key is None: self.__cache = {} return True try: del self.__cache[key] return True except KeyError: _log.error('key [%s] does not exist in cache', key) return False
class cClinicalResult (message=None)-
Expand source code
class cClinicalResult(object): def __init__(self, message=None): self.message = message self.numeric_value = None self.unit = None self.date_valid = None self.formula_name = None self.formula_source = None self.variables = {} self.sub_results = [] self.warnings = [_('THIS IS NOT A VERIFIED MEASUREMENT. DO NOT USE FOR ACTUAL CARE.')] self.hints = [] #-------------------------------------------------------- def __str__(self): txt = '[cClinicalResult]: %s %s (%s)\n\n%s' % ( self.numeric_value, self.unit, self.date_valid, self.format ( left_margin = 0, width = 80, eol = '\n', with_formula = True, with_warnings = True, with_variables = True, with_sub_results = True, return_list = False ) ) return txt #-------------------------------------------------------- def format(self, left_margin=0, eol='\n', width=None, with_formula=False, with_warnings=True, with_variables=False, with_sub_results=False, with_hints=True, return_list=False): lines = [] lines.append(self.message) if with_formula: txt = gmTools.wrap ( text = '%s %s' % ( _('Algorithm:'), self.formula_name ), width = width, initial_indent = ' ', subsequent_indent = ' ' * 2, eol = eol ) lines.append(txt) txt = gmTools.wrap ( text = '%s %s' % ( _('Source:'), self.formula_source ), width = width, initial_indent = ' ', subsequent_indent = ' ' * 2, eol = eol ) lines.append(txt) if with_warnings: if len(self.warnings) > 0: lines.append(' Caveat:') for w in self.warnings: txt = gmTools.wrap(text = w, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol) lines.append(txt) if with_hints: if len(self.hints) > 0: lines.append(' Hints:') for h in self.hints: txt = gmTools.wrap(text = h, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol) lines.append(txt) if with_variables: if len(self.variables) > 0: lines.append(' %s' % _('Variables:')) for key in self.variables: txt = ' %s %s: %s' % ( gmTools.u_arrow2right, key, self.variables[key] ) lines.append(txt) if with_sub_results: if len(self.sub_results) > 0: lines.append(' %s' % _('Intermediate results:')) for r in self.sub_results: lines.extend(r.format ( left_margin = left_margin + 1, width = width, eol = eol, with_formula = with_formula, with_warnings = with_warnings, with_variables = with_variables, with_sub_results = False, # break cycles return_list = True )) lines = gmTools.strip_trailing_empty_lines(lines = lines, eol = eol) if return_list: return lines left_margin = ' ' * left_margin return left_margin + (eol + left_margin).join(lines) + eolMethods
def format(self, left_margin=0, eol='\n', width=None, with_formula=False, with_warnings=True, with_variables=False, with_sub_results=False, with_hints=True, return_list=False)-
Expand source code
def format(self, left_margin=0, eol='\n', width=None, with_formula=False, with_warnings=True, with_variables=False, with_sub_results=False, with_hints=True, return_list=False): lines = [] lines.append(self.message) if with_formula: txt = gmTools.wrap ( text = '%s %s' % ( _('Algorithm:'), self.formula_name ), width = width, initial_indent = ' ', subsequent_indent = ' ' * 2, eol = eol ) lines.append(txt) txt = gmTools.wrap ( text = '%s %s' % ( _('Source:'), self.formula_source ), width = width, initial_indent = ' ', subsequent_indent = ' ' * 2, eol = eol ) lines.append(txt) if with_warnings: if len(self.warnings) > 0: lines.append(' Caveat:') for w in self.warnings: txt = gmTools.wrap(text = w, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol) lines.append(txt) if with_hints: if len(self.hints) > 0: lines.append(' Hints:') for h in self.hints: txt = gmTools.wrap(text = h, width = width, initial_indent = ' %s ' % gmTools.u_arrow2right, subsequent_indent = ' ', eol = eol) lines.append(txt) if with_variables: if len(self.variables) > 0: lines.append(' %s' % _('Variables:')) for key in self.variables: txt = ' %s %s: %s' % ( gmTools.u_arrow2right, key, self.variables[key] ) lines.append(txt) if with_sub_results: if len(self.sub_results) > 0: lines.append(' %s' % _('Intermediate results:')) for r in self.sub_results: lines.extend(r.format ( left_margin = left_margin + 1, width = width, eol = eol, with_formula = with_formula, with_warnings = with_warnings, with_variables = with_variables, with_sub_results = False, # break cycles return_list = True )) lines = gmTools.strip_trailing_empty_lines(lines = lines, eol = eol) if return_list: return lines left_margin = ' ' * left_margin return left_margin + (eol + left_margin).join(lines) + eol