def test_meds():
session = make_session()
asthma_medication = MedicationDictionary(
FullName="Asthma Drug", DMD_ID="0", MultilexDrug_ID="0"
)
patient_with_med = Patient()
patient_with_med.MedicationIssues = [
MedicationIssue(MedicationDictionary=asthma_medication)
]
patient_without_med = Patient()
session.add(patient_with_med)
session.add(patient_without_med)
session.commit()
study = StudyDefinition(
population=patients.all(),
asthma_meds=patients.with_these_medications(
codelist(asthma_medication.DMD_ID, "snomed")
),
)
results = study.to_dicts()
assert [x["asthma_meds"] for x in results] == ["1", "0"]
def test_meds_with_count():
session = make_session()
asthma_medication = MedicationDictionary(
FullName="Asthma Drug", DMD_ID="0", MultilexDrug_ID="0"
)
patient_with_med = Patient()
patient_with_med.MedicationIssues = [
MedicationIssue(
MedicationDictionary=asthma_medication, ConsultationDate="2010-01-01"
),
MedicationIssue(
MedicationDictionary=asthma_medication, ConsultationDate="2015-01-01"
),
MedicationIssue(
MedicationDictionary=asthma_medication, ConsultationDate="2018-01-01"
),
MedicationIssue(
MedicationDictionary=asthma_medication, ConsultationDate="2020-01-01"
),
]
patient_without_med = Patient()
session.add(patient_with_med)
session.add(patient_without_med)
session.commit()
study = StudyDefinition(
population=patients.all(),
asthma_meds=patients.with_these_medications(
codelist(asthma_medication.DMD_ID, "snomed"),
on_or_after="2012-01-01",
return_number_of_matches_in_period=True,
),
)
results = study.to_dicts()
assert [x["asthma_meds"] for x in results] == ["3", "0"]
ever_smoked AND
has_follow_up AND NOT
recent_asthma AND NOT
other_respiratory AND NOT
nebules AND NOT
ltra_single
""",
has_follow_up=patients.registered_with_one_practice_between(
"2019-02-28", "2020-02-29"),
recent_asthma=patients.with_these_clinical_events(
asthma_codes,
between=["2017-02-28", "2020-02-29"],
),
#### NEBULES
nebules=patients.with_these_medications(
nebulised_med_codes,
between=["2019-02-28", "2020-02-29"],
),
),
## OUTCOMES (at least one outcome or covariate is required)
icu_date_admitted=patients.admitted_to_icu(
on_or_after="2020-03-01",
include_day=True,
returning="date_admitted",
return_expectations={"date": {
"earliest": "2020-03-01"
}},
),
died_date_cpns=patients.with_death_recorded_in_cpns(
on_or_after="2020-03-01",
returning="date_of_death",
include_month=True,
},
},
),
rural_urban=patients.address_as_of(
"2020-02-01",
returning="rural_urban_classification",
return_expectations={
"rate": "universal",
"category": {
"ratios": {
"rural": 0.1,
"urban": 0.9
}
},
},
),
recent_salbutamol_count=patients.with_these_medications(
salbutamol_codes,
between=["2018-02-01", "2020-02-01"],
returning="number_of_matches_in_period",
return_expectations={
"incidence": 0.6,
"int": {
"distribution": "normal",
"mean": 8,
"stddev": 2
},
},
),
)
has_follow_up=patients.registered_with_one_practice_between(
"2019-02-28", "2020-02-29", return_expectations={"incidence": 0.9}),
copd=patients.with_these_clinical_events(
copd_codes,
on_or_before="2020-02-29",
return_expectations={"incidence": 0.05},
),
### OTHER RESPIRATORY
other_respiratory=patients.with_these_clinical_events(
other_respiratory_codes,
on_or_before="2020-02-29",
return_expectations={"incidence": 0.05},
),
nebules=patients.with_these_medications(
nebulised_med_codes,
between=["2019-02-28", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
#### HIGH DOSE ICS - all preparation
high_dose_ics=patients.with_these_medications(
high_dose_ics_med_codes,
between=["2019-11-01", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
#### HIGH DOSE ICS - single ingredient preparations
high_dose_ics_single_ing=patients.with_these_medications(
high_dose_ics_single_ingredient_med_codes,
between=["2019-11-01", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
#### HIGH DOSE ICS - multiple ingredient preparation
ever_smoked=patients.with_these_clinical_events(
filter_codes_by_category(clear_smoking_codes, include=["S", "E"]),
on_or_before="2020-02-29",
return_expectations={"incidence": 0.9},
),
has_follow_up=patients.registered_with_one_practice_between(
"2019-02-28", "2020-02-29", return_expectations={"incidence": 0.9},
),
recent_asthma=patients.with_these_clinical_events(
asthma_codes,
between=["2017-02-28", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
other_respiratory=patients.with_these_clinical_events(
other_respiratory_codes,
on_or_before="2020-02-29",
return_expectations={"incidence": 0.05},
),
#### NEBULES
nebules=patients.with_these_medications(
nebulised_med_codes,
between=["2019-02-28", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
ltra_single=patients.with_these_medications(
leukotriene_med_codes,
between=["2019-11-01", "2020-02-29"],
return_expectations={"incidence": 0.05},
),
)
)
) AND
prednisolone_last_year > 0 AND
prednisolone_last_year < 5
""",
},
recent_asthma_code=patients.with_these_clinical_events(
asthma_codes,
between=['2017-02-01', '2020-02-01'],
),
asthma_code_ever=patients.with_these_clinical_events(asthma_codes),
copd_code_ever=patients.with_these_clinical_events(chronic_respiratory_disease_codes),
prednisolone_last_year=patients.with_these_medications(
pred_codes,
between=['2019-02-01', '2020-02-01'],
returning="number_of_matches_in_period",
),
),
# https://github.com/ebmdatalab/tpp-sql-notebook/issues/7
chronic_cardiac_disease=patients.with_these_clinical_events(
chronic_cardiac_disease_codes,
return_first_date_in_period=True,
include_month=True,
),
# https://github.com/ebmdatalab/tpp-sql-notebook/issues/30
diabetes=patients.with_these_clinical_events(
diabetes_codes,
return_first_date_in_period=True,
low_med_dose_ics_multiple_ingredient OR
low_med_dose_ics OR
ics_single OR
laba_ics OR
laba_lama_ics
)
)
""",
has_asthma=patients.with_these_clinical_events(
asthma_codes,
between=["2017-02-28", "2020-02-29"],
),
has_follow_up=patients.registered_with_one_practice_between(
"2019-02-28", "2020-02-29"),
nebules=patients.with_these_medications(
nebulised_med_codes,
between=["2019-02-28", "2020-02-29"],
),
any_asthma_med=patients.satisfying("""
ltra_single OR
laba_lama_ics OR
laba_lama OR
laba_ics OR
lama_single OR
laba_single OR
sama_single OR
saba_single OR
ics_single OR
low_med_dose_ics OR
low_med_dose_ics_multiple_ingredient OR
low_med_dose_ics_single_ingredient OR
high_dose_ics_multiple_ingredient OR