1
2 """GNUmed clinical calculator(s)
3
4 THIS IS NOT A VERIFIED CALCULATOR. DO NOT USE FOR ACTUAL CARE.
5 """
6
7 __author__ = "K.Hilbert <Karsten.Hilbert@gmx.net>"
8 __license__ = "GPL v2 or later"
9
10
11 import sys
12 import logging
13 import decimal
14 import datetime as pydt
15
16
17 if __name__ == '__main__':
18 sys.path.insert(0, '../../')
19
20 from Gnumed.pycommon import gmDateTime
21 from Gnumed.pycommon import gmI18N
22 from Gnumed.pycommon import gmLog2
23
24 if __name__ == '__main__':
25 gmI18N.activate_locale()
26 gmI18N.install_domain()
27 gmDateTime.init()
28
29 from Gnumed.pycommon import gmTools
30 from Gnumed.pycommon import gmBorg
31 from Gnumed.business import gmLOINC
32
33
34 _log = logging.getLogger('gm.calc')
35
36
38
40 self.message = message
41 self.numeric_value = None
42 self.unit = None
43 self.date_valid = None
44 self.formula_name = None
45 self.formula_source = None
46 self.variables = {}
47 self.sub_results = []
48 self.warnings = [_('THIS IS NOT A VERIFIED MEASUREMENT. DO NOT USE FOR ACTUAL CARE.')]
49 self.hints = []
50
51
53 txt = '[cClinicalResult]: %s %s (%s)\n\n%s' % (
54 self.numeric_value,
55 self.unit,
56 self.date_valid,
57 self.format (
58 left_margin = 0,
59 width = 80,
60 eol = '\n',
61 with_formula = True,
62 with_warnings = True,
63 with_variables = True,
64 with_sub_results = True,
65 return_list = False
66 )
67 )
68 return txt
69
70
145
146
148
150 self.__cache = {}
151 self.__patient = patient
152
153
155 return self.__patient
156
162
163 patient = property(lambda x:x, _set_patient)
164
165
167 if key is None:
168 self.__cache = {}
169 return True
170 try:
171 del self.__cache[key]
172 return True
173 except KeyError:
174 _log.error('key [%s] does not exist in cache', key)
175 return False
176
177
178
179
180 - def get_EDC(self, lmp=None, nullipara=True):
181
182 result = cClinicalResult(_('unknown EDC'))
183 result.formula_name = 'EDC (Mittendorf 1990)'
184 result.formula_source = 'Mittendorf, R. et al., "The length of uncomplicated human gestation," OB/GYN, Vol. 75, No., 6 June, 1990, pp. 907-932.'
185
186 if lmp is None:
187 result.message = _('EDC: unknown LMP')
188 return result
189
190 result.variables['LMP'] = lmp
191 result.variables['nullipara'] = nullipara
192 if nullipara:
193 result.variables['parity_offset'] = 15
194 else:
195 result.variables['parity_offset'] = 10
196
197 now = gmDateTime.pydt_now_here()
198 if lmp > now:
199 result.warnings.append(_('LMP in the future'))
200
201 if self.__patient is None:
202 result.warnings.append(_('cannot run sanity checks, no patient'))
203 else:
204 if self.__patient['dob'] is None:
205 result.warnings.append(_('cannot run sanity checks, no DOB'))
206 else:
207 years, months, days, hours, minutes, seconds = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])
208
209
210 if years < 10:
211 result.warnings.append(_('patient less than 10 years old'))
212 if self.__patient['gender'] in [None, 'm']:
213 result.warnings.append(_('atypical gender for pregnancy: %s') % self.__patient.gender_string)
214 if self.__patient['deceased'] is not None:
215 result.warnings.append(_('patient already passed away'))
216
217 if lmp.month > 3:
218 edc_month = lmp.month - 3
219 edc_year = lmp.year + 1
220 else:
221 edc_month = lmp.month + 9
222 edc_year = lmp.year
223
224 result.numeric_value = gmDateTime.pydt_replace(dt = lmp, year = edc_year, month = edc_month, strict = False) + pydt.timedelta(days = result.variables['parity_offset'])
225
226 result.message = _('EDC: %s') % gmDateTime.pydt_strftime (
227 result.numeric_value,
228 format = '%Y %b %d'
229 )
230 result.date_valid = now
231
232 _log.debug('%s' % result)
233
234 return result
235
236
245
246 eGFRs = property(_get_egfrs, lambda x:x)
247
248
250
251
252 Schwartz = self.eGFR_Schwartz
253 if Schwartz.numeric_value is not None:
254 return Schwartz
255
256
257
258 CKD = self.eGFR_CKD_EPI
259 if CKD.numeric_value is not None:
260 if CKD.numeric_value > self.d(60):
261 return CKD
262
263
264 if self.__patient['dob'] is None:
265 return CKD
266
267 CG = self.eGFR_Cockcroft_Gault
268 MDRD = self.eGFR_MDRD_short
269 age = None
270 if age is None:
271 try:
272 age = CKD.variables['age@crea']
273 except KeyError:
274 _log.warning('CKD-EPI: no age@crea')
275 if age is None:
276 try:
277 age = CG.variables['age@crea']
278 except KeyError:
279 _log.warning('CG: no age@crea')
280 if age is None:
281 try:
282 age = MDRD.variables['age@crea']
283 except KeyError:
284 _log.warning('MDRD: no age@crea')
285 if age is None:
286 age = gmDateTime.calculate_apparent_age(start = self.__patient['dob'])[0]
287
288
289 if age > self.d(65):
290 if CG.numeric_value is not None:
291 return CG
292
293
294 if MDRD.numeric_value is None:
295 if (CKD.numeric_value is not None) or (CG.numeric_value is None):
296 return CKD
297 return CG
298
299 if MDRD.numeric_value > self.d(60):
300 if CKD.numeric_value is not None:
301
302 return CKD
303
304 return MDRD
305
306 eGFR = property(_get_egfr, lambda x:x)
307
308
310
311 try:
312 return self.__cache['MDRD_short']
313 except KeyError:
314 pass
315
316 result = cClinicalResult(_('unknown MDRD (4 vars/IDMS)'))
317 result.formula_name = 'eGFR from 4-variables IDMS-MDRD'
318 result.formula_source = '1/2013: http://en.wikipedia.org/Renal_function / http://www.ganfyd.org/index.php?title=Estimated_glomerular_filtration_rate (NHS)'
319 result.hints.append(_('best @ 30 < GFR < 60 ml/min'))
320
321 if self.__patient is None:
322 result.message = _('MDRD (4 vars/IDMS): no patient')
323 return result
324
325 if self.__patient['dob'] is None:
326 result.message = _('MDRD (4 vars/IDMS): no DOB (no age)')
327 return result
328
329
330 from Gnumed.business.gmPerson import map_gender2mf
331 result.variables['gender'] = self.__patient['gender']
332 result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
333 if result.variables['gender_mf'] == 'm':
334 result.variables['gender_multiplier'] = self.d(1)
335 elif result.variables['gender_mf'] == 'f':
336 result.variables['gender_multiplier'] = self.d('0.742')
337 else:
338 result.message = _('MDRD (4 vars/IDMS): neither male nor female')
339 return result
340
341
342 result.variables['serum_crea'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_creatinine_quantity, no_of_results = 1)
343 if result.variables['serum_crea'] is None:
344 result.message = _('MDRD (4 vars/IDMS): serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
345 return result
346 if result.variables['serum_crea']['val_num'] is None:
347 result.message = _('MDRD (4 vars/IDMS): creatinine value not numeric')
348 return result
349 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
350 if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
351 result.variables['unit_multiplier'] = self.d(175)
352 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
353 result.variables['unit_multiplier'] = self.d(30849)
354 else:
355 result.message = _('MDRD (4 vars/IDMS): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
356 return result
357
358
359 result.variables['dob'] = self.__patient['dob']
360 result.variables['age@crea'] = self.d (
361 gmDateTime.calculate_apparent_age (
362 start = result.variables['dob'],
363 end = result.variables['serum_crea']['clin_when']
364 )[0]
365 )
366 if (result.variables['age@crea'] > 84) or (result.variables['age@crea'] < 18):
367 result.message = _('MDRD (4 vars/IDMS): formula does not apply at age [%s] (17 < age < 85)') % result.variables['age@crea']
368 return result
369
370
371 result.variables['ethnicity_multiplier'] = self.d(1)
372 result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor'))
373
374
375 result.numeric_value = result.variables['unit_multiplier'] * \
376 pow(result.variables['serum_crea_val'], self.d('-1.154')) * \
377 pow(result.variables['age@crea'], self.d('-0.203')) * \
378 result.variables['ethnicity_multiplier'] * \
379 result.variables['gender_multiplier']
380 result.unit = 'ml/min/1.73m²'
381
382 BSA = self.body_surface_area
383 result.sub_results.append(BSA)
384 if BSA.numeric_value is None:
385 result.warnings.append(_('NOT corrected for non-average body surface (average = 1.73m²)'))
386 else:
387 result.variables['BSA'] = BSA.numeric_value
388 result_numeric_value = result.numeric_value / BSA.numeric_value
389
390 result.message = _('eGFR(MDRD): %.1f %s (%s) [4-vars, IDMS]') % (
391 result.numeric_value,
392 result.unit,
393 gmDateTime.pydt_strftime (
394 result.variables['serum_crea']['clin_when'],
395 format = '%Y %b %d'
396 )
397 )
398 result.date_valid = result.variables['serum_crea']['clin_when']
399
400 self.__cache['MDRD_short'] = result
401 _log.debug('%s' % result)
402
403 return result
404
405 eGFR_MDRD_short = property(_get_gfr_mdrd_short, lambda x:x)
406
407
409
410 try:
411 return self.__cache['CKD-EPI']
412 except KeyError:
413 pass
414
415 result = cClinicalResult(_('unknown CKD-EPI'))
416 result.formula_name = 'eGFR from CKD-EPI'
417 result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function'
418 result.hints.append(_('best @ GFR > 60 ml/min'))
419
420 if self.__patient is None:
421 result.message = _('CKD-EPI: no patient')
422 return result
423
424 if self.__patient['dob'] is None:
425 result.message = _('CKD-EPI: no DOB (no age)')
426 return result
427
428
429 from Gnumed.business.gmPerson import map_gender2mf
430 result.variables['gender'] = self.__patient['gender']
431 result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
432 if result.variables['gender_mf'] == 'm':
433 result.variables['gender_multiplier'] = self.d(1)
434 result.variables['k:gender_divisor'] = self.d('0.9')
435 result.variables['a:gender_power'] = self.d('-0.411')
436 elif result.variables['gender_mf'] == 'f':
437 result.variables['gender_multiplier'] = self.d('1.018')
438 result.variables['k:gender_divisor'] = self.d('0.7')
439 result.variables['a:gender_power'] = self.d('-0.329')
440 else:
441 result.message = _('CKD-EPI: neither male nor female')
442 return result
443
444
445 result.variables['serum_crea'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_creatinine_quantity, no_of_results = 1)
446 if result.variables['serum_crea'] is None:
447 result.message = _('CKD-EPI: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
448 return result
449 if result.variables['serum_crea']['val_num'] is None:
450 result.message = _('CKD-EPI: creatinine value not numeric')
451 return result
452 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
453 if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
454 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
455 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
456 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num']) / self.d('88.4')
457 else:
458 result.message = _('CKD-EPI: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
459 return result
460
461
462 result.variables['dob'] = self.__patient['dob']
463 result.variables['age@crea'] = self.d (
464 gmDateTime.calculate_apparent_age (
465 start = result.variables['dob'],
466 end = result.variables['serum_crea']['clin_when']
467 )[0]
468 )
469
470
471
472
473
474 result.variables['ethnicity_multiplier'] = self.d(1)
475 result.warnings.append(_('ethnicity: GNUmed does not know patient ethnicity, ignoring correction factor of 1.519 for "black"'))
476
477
478 result.numeric_value = (
479 self.d(141) * \
480 pow(min((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), result.variables['a:gender_power']) * \
481 pow(max((result.variables['serum_crea_val'] / result.variables['k:gender_divisor']), self.d(1)), self.d('-1.209')) * \
482 pow(self.d('0.993'), result.variables['age@crea']) * \
483 result.variables['gender_multiplier'] * \
484 result.variables['ethnicity_multiplier']
485 )
486 result.unit = 'ml/min/1.73m²'
487
488 result.message = _('eGFR(CKD-EPI): %.1f %s (%s)') % (
489 result.numeric_value,
490 result.unit,
491 gmDateTime.pydt_strftime (
492 result.variables['serum_crea']['clin_when'],
493 format = '%Y %b %d'
494 )
495 )
496 result.date_valid = result.variables['serum_crea']['clin_when']
497
498 self.__cache['CKD-EPI'] = result
499 _log.debug('%s' % result)
500
501 return result
502
503 eGFR_CKD_EPI = property(_get_gfr_ckd_epi, lambda x:x)
504
505
507
508 try:
509 return self.__cache['cockcroft_gault']
510 except KeyError:
511 pass
512
513 result = cClinicalResult(_('unknown Cockcroft-Gault'))
514 result.formula_name = 'eGFR from Cockcroft-Gault'
515 result.formula_source = '8/2014: http://en.wikipedia.org/Renal_function'
516 result.hints.append(_('best @ age >65'))
517
518 if self.__patient is None:
519 result.message = _('Cockcroft-Gault: no patient')
520 return result
521
522 if self.__patient['dob'] is None:
523 result.message = _('Cockcroft-Gault: no DOB (no age)')
524 return result
525
526
527 from Gnumed.business.gmPerson import map_gender2mf
528 result.variables['gender'] = self.__patient['gender']
529 result.variables['gender_mf'] = map_gender2mf[self.__patient['gender']]
530 if result.variables['gender_mf'] not in ['m', 'f']:
531 result.message = _('Cockcroft-Gault: neither male nor female')
532 return result
533
534
535 result.variables['serum_crea'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_creatinine_quantity, no_of_results = 1)
536 if result.variables['serum_crea'] is None:
537 result.message = _('Cockcroft-Gault: serum creatinine value not found (LOINC: %s)') % gmLOINC.LOINC_creatinine_quantity
538 return result
539 if result.variables['serum_crea']['val_num'] is None:
540 result.message = _('Cockcroft-Gault: creatinine value not numeric')
541 return result
542 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
543 if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
544 result.variables['unit_multiplier'] = self.d(72)
545 if result.variables['gender_mf'] == 'm':
546 result.variables['gender_multiplier'] = self.d('1')
547 else:
548 result.variables['gender_multiplier'] = self.d('0.85')
549 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
550 result.variables['unit_multiplier'] = self.d(1)
551 if result.variables['gender_mf'] == 'm':
552 result.variables['gender_multiplier'] = self.d('1.23')
553 else:
554 result.variables['gender_multiplier'] = self.d('1.04')
555 else:
556 result.message = _('Cockcroft-Gault: unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
557 return result
558
559
560 result.variables['dob'] = self.__patient['dob']
561 result.variables['age@crea'] = self.d (
562 gmDateTime.calculate_apparent_age (
563 start = result.variables['dob'],
564 end = result.variables['serum_crea']['clin_when']
565 )[0]
566 )
567 if (result.variables['age@crea'] < 18):
568 result.message = _('Cockcroft-Gault: formula does not apply at age [%s] (17 < age)') % result.variables['age@crea']
569 return result
570
571 result.variables['weight'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_weight, no_of_results = 1)
572 if result.variables['weight'] is None:
573 result.message = _('Cockcroft-Gault: weight not found')
574 return result
575 if result.variables['weight']['val_num'] is None:
576 result.message = _('Cockcroft-Gault: weight not numeric')
577 return result
578 if result.variables['weight']['val_unit'] == 'kg':
579 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
580 elif result.variables['weight']['val_unit'] == 'g':
581 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
582 else:
583 result.message = _('Cockcroft-Gault: weight not in kg or g')
584 return result
585
586
587 result.numeric_value = ((
588 (140 - result.variables['age@crea']) * result.variables['weight_kg'] * result.variables['gender_multiplier']) \
589 / \
590 (result.variables['unit_multiplier'] * result.variables['serum_crea_val'])
591 )
592 result.unit = 'ml/min'
593
594 result.message = _('eGFR(CG): %.1f %s (%s)') % (
595 result.numeric_value,
596 result.unit,
597 gmDateTime.pydt_strftime (
598 result.variables['serum_crea']['clin_when'],
599 format = '%Y %b %d'
600 )
601 )
602 result.date_valid = result.variables['serum_crea']['clin_when']
603
604 self.__cache['cockroft_gault'] = result
605 _log.debug('%s' % result)
606
607 return result
608
609 eGFR_Cockcroft_Gault = property(_get_gfr_cockcroft_gault, lambda x:x)
610
611
613
614 try:
615 return self.__cache['gfr_schwartz']
616 except KeyError:
617 pass
618
619 result = cClinicalResult(_('unknown eGFR (Schwartz)'))
620 result.formula_name = 'eGFR from updated Schwartz "bedside" formula (age < 19yrs)'
621 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'
622 result.hints.append(_('only applies @ age <18'))
623
624 if self.__patient is None:
625 result.message = _('eGFR (Schwartz): no patient')
626 return result
627
628 if self.__patient['dob'] is None:
629 result.message = _('eGFR (Schwartz): DOB needed for age')
630 return result
631
632 result.variables['dob'] = self.__patient['dob']
633
634
635 result.variables['serum_crea'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_creatinine_quantity, no_of_results = 1)
636 if result.variables['serum_crea'] is None:
637 result.message = _('eGFR (Schwartz): serum creatinine value not found (LOINC: %s') % gmLOINC.LOINC_creatinine_quantity
638 return result
639 if result.variables['serum_crea']['val_num'] is None:
640 result.message = _('eGFR (Schwartz): creatinine value not numeric')
641 return result
642 result.variables['serum_crea_val'] = self.d(result.variables['serum_crea']['val_num'])
643 if result.variables['serum_crea']['val_unit'] in ['mg/dl', 'mg/dL']:
644 result.variables['unit_multiplier'] = self.d(1)
645 elif result.variables['serum_crea']['val_unit'] in ['µmol/L', 'µmol/l']:
646 result.variables['unit_multiplier'] = self.d('0.00113')
647 else:
648 result.message = _('eGFR (Schwartz): unknown serum creatinine unit (%s)') % result.variables['serum_crea']['val_unit']
649 return result
650
651
652 result.variables['age@crea'] = self.d (
653 gmDateTime.calculate_apparent_age (
654 start = result.variables['dob'],
655 end = result.variables['serum_crea']['clin_when']
656 )[0]
657 )
658 if result.variables['age@crea'] > 17:
659 result.message = _('eGFR (Schwartz): formula does not apply at age [%s] (age must be <18)') % result.variables['age@crea']
660 return result
661
662
663 if result.variables['age@crea'] < 1:
664
665
666 result.variables['constant_for_age'] = self.d('0.41')
667 result.warnings.append(_('eGFR (Schwartz): not known whether pre-term birth, applying full-term formula'))
668 else:
669 result.variables['constant_for_age'] = self.d('0.41')
670
671
672 result.variables['height'] = self.__patient.emr.get_result_at_timestamp (
673 timestamp = result.variables['serum_crea']['clin_when'],
674 loinc = gmLOINC.LOINC_height,
675 tolerance_interval = '7 days'
676 )
677 if result.variables['height'] is None:
678 result.message = _('eGFR (Schwartz): height not found')
679 return result
680 if result.variables['height']['val_num'] is None:
681 result.message = _('eGFR (Schwartz): height not numeric')
682 return result
683 if result.variables['height']['val_unit'] == 'cm':
684 result.variables['height_cm'] = self.d(result.variables['height']['val_num'])
685 elif result.variables['height']['val_unit'] == 'mm':
686 result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10))
687 elif result.variables['height']['val_unit'] == 'm':
688 result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100)
689 else:
690 result.message = _('eGFR (Schwartz): height not in m, cm, or mm')
691 return result
692
693
694 result.numeric_value = (
695 result.variables['constant_for_age'] * result.variables['height_cm']
696 ) / (
697 result.variables['unit_multiplier'] * result.variables['serum_crea_val']
698 )
699 result.unit = 'ml/min/1.73m²'
700
701 result.message = _('eGFR (Schwartz): %.1f %s (%s)') % (
702 result.numeric_value,
703 result.unit,
704 gmDateTime.pydt_strftime (
705 result.variables['serum_crea']['clin_when'],
706 format = '%Y %b %d'
707 )
708 )
709 result.date_valid = result.variables['serum_crea']['clin_when']
710
711 self.__cache['gfr_schwartz'] = result
712 _log.debug('%s' % result)
713
714 return result
715
716 eGFR_Schwartz = property(_get_gfr_schwartz, lambda x:x)
717
718
720
721 try:
722 return self.__cache['body_surface_area']
723 except KeyError:
724 pass
725
726 result = cClinicalResult(_('unknown body surface area'))
727 result.formula_name = 'Du Bois Body Surface Area'
728 result.formula_source = '12/2012: http://en.wikipedia.org/wiki/Body_surface_area'
729
730 if self.__patient is None:
731 result.message = _('Body Surface Area: no patient')
732 return result
733
734 result.variables['height'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_height, no_of_results = 1)
735 if result.variables['height'] is None:
736 result.message = _('Body Surface Area: height not found')
737 return result
738 if result.variables['height']['val_num'] is None:
739 result.message = _('Body Surface Area: height not numeric')
740 return result
741 if result.variables['height']['val_unit'] == 'cm':
742 result.variables['height_cm'] = self.d(result.variables['height']['val_num'])
743 elif result.variables['height']['val_unit'] == 'mm':
744 result.variables['height_cm'] = self.d(result.variables['height']['val_num'] / self.d(10))
745 elif result.variables['height']['val_unit'] == 'm':
746 result.variables['height_cm'] = self.d(result.variables['height']['val_num'] * 100)
747 else:
748 result.message = _('Body Surface Area: height not in m, cm, or mm')
749 return result
750
751 result.variables['weight'] = self.__patient.emr.get_result_at_timestamp (
752 timestamp = result.variables['height']['clin_when'],
753 loinc = gmLOINC.LOINC_weight,
754 tolerance_interval = '10 days'
755 )
756 if result.variables['weight'] is None:
757 result.message = _('Body Surface Area: weight not found')
758 return result
759 if result.variables['weight']['val_num'] is None:
760 result.message = _('Body Surface Area: weight not numeric')
761 return result
762 if result.variables['weight']['val_unit'] == 'kg':
763 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
764 elif result.variables['weight']['val_unit'] == 'g':
765 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
766 else:
767 result.message = _('Body Surface Area: weight not in kg or g')
768 return result
769
770 result.numeric_value = self.d('0.007184') * \
771 pow(result.variables['weight_kg'], self.d('0.425')) * \
772 pow(result.variables['height_cm'], self.d('0.725'))
773 result.unit = 'm²'
774
775 result.message = _('BSA (DuBois): %.2f %s') % (
776 result.numeric_value,
777 result.unit
778 )
779 result.date_valid = gmDateTime.pydt_now_here()
780
781 self.__cache['body_surface_area'] = result
782 _log.debug('%s' % result)
783
784 return result
785
786 body_surface_area = property(_get_body_surface_area, lambda x:x)
787
788
790
791 try:
792 return self.__cache['body_mass_index']
793 except KeyError:
794 pass
795
796 result = cClinicalResult(_('unknown BMI'))
797 result.formula_name = 'BMI/Quetelet Index'
798 result.formula_source = '08/2014: https://en.wikipedia.org/wiki/Body_mass_index'
799
800 if self.__patient is None:
801 result.message = _('BMI: no patient')
802 return result
803
804 result.variables['height'] = self.__patient.emr.get_most_recent_results(loinc = gmLOINC.LOINC_height, no_of_results = 1)
805 if result.variables['height'] is None:
806 result.message = _('BMI: height not found')
807 return result
808 if result.variables['height']['val_num'] is None:
809 result.message = _('BMI: height not numeric')
810 return result
811 if result.variables['height']['val_unit'] == 'cm':
812 result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(100))
813 elif result.variables['height']['val_unit'] == 'mm':
814 result.variables['height_m'] = self.d(result.variables['height']['val_num'] / self.d(1000))
815 elif result.variables['height']['val_unit'] == 'm':
816 result.variables['height_m'] = self.d(result.variables['height']['val_num'])
817 else:
818 result.message = _('BMI: height not in m, cm, or mm')
819 return result
820
821 result.variables['weight'] = self.__patient.emr.get_result_at_timestamp (
822 timestamp = result.variables['height']['clin_when'],
823 loinc = gmLOINC.LOINC_weight,
824 tolerance_interval = '10 days'
825 )
826 if result.variables['weight'] is None:
827 result.message = _('BMI: weight not found')
828 return result
829 if result.variables['weight']['val_num'] is None:
830 result.message = _('BMI: weight not numeric')
831 return result
832 if result.variables['weight']['val_unit'] == 'kg':
833 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'])
834 elif result.variables['weight']['val_unit'] == 'g':
835 result.variables['weight_kg'] = self.d(result.variables['weight']['val_num'] / self.d(1000))
836 else:
837 result.message = _('BMI: weight not in kg or g')
838 return result
839
840 result.variables['dob'] = self.__patient['dob']
841 start = result.variables['dob']
842 end = result.variables['height']['clin_when']
843 multiplier = 1
844 if end < start:
845 start = result.variables['height']['clin_when']
846 end = result.variables['dob']
847 multiplier = -1
848 result.variables['age@height'] = multiplier * self.d(gmDateTime.calculate_apparent_age(start, end)[0])
849 if (result.variables['age@height'] < 18):
850 result.message = _('BMI (Quetelet): formula does not apply at age [%s] (0 < age < 18)') % result.variables['age@height']
851 return result
852
853
854 result.numeric_value = result.variables['weight_kg'] / (result.variables['height_m'] * result.variables['height_m'])
855 result.unit = 'kg/m²'
856
857 result.message = _('BMI (Quetelet): %.2f %s') % (
858 result.numeric_value,
859 result.unit
860 )
861 result.date_valid = gmDateTime.pydt_now_here()
862
863 self.__cache['body_mass_index'] = result
864 _log.debug('%s' % result)
865
866 return result
867
868 body_mass_index = property(_get_body_mass_index, lambda x:x)
869 bmi = property(_get_body_mass_index, lambda x:x)
870
871
872
873
874 - def d(self, initial):
875 if isinstance(initial, decimal.Decimal):
876 return initial
877
878 val = initial
879
880
881 if type(val) == type(float(1.4)):
882 val = str(val)
883
884
885 if isinstance(val, str):
886 val = val.replace(',', '.', 1)
887 val = val.strip()
888
889 try:
890 d = decimal.Decimal(val)
891 return d
892 except (TypeError, decimal.InvalidOperation):
893 return None
894
895
896
897
898 if __name__ == "__main__":
899
900 if len(sys.argv) == 1:
901 sys.exit()
902
903 if sys.argv[1] != 'test':
904 sys.exit()
905
906 from Gnumed.pycommon import gmLog2
907
922
923 test_clin_calc()
924