def test_patients_registered_with_one_practice_between():
session = make_session()
patient_registered_in_2001 = Patient()
patient_registered_in_2002 = Patient()
patient_unregistered_in_2002 = Patient()
patient_registered_in_2001.RegistrationHistory = [
RegistrationHistory(StartDate="2001-01-01", EndDate="9999-01-01")
]
patient_registered_in_2002.RegistrationHistory = [
RegistrationHistory(StartDate="2002-01-01", EndDate="9999-01-01")
]
patient_unregistered_in_2002.RegistrationHistory = [
RegistrationHistory(StartDate="2001-01-01", EndDate="2002-01-01")
]
session.add(patient_registered_in_2001)
session.add(patient_registered_in_2002)
session.add(patient_unregistered_in_2002)
session.commit()
study = StudyDefinition(
population=patients.registered_with_one_practice_between(
"2001-12-01", "2003-01-01"
)
)
results = study.to_dicts()
assert [x["patient_id"] for x in results] == [
str(patient_registered_in_2001.Patient_ID)
]
"rate": "uniform",
"incidence": 0.2,
},
## STUDY POPULATION (required)
population=patients.satisfying(
"""
copd AND
(age >=35 AND age <= 110) AND
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",
column="id",
)
systolic_blood_pressure_codes = codelist(["2469."], system="ctv3")
diastolic_blood_pressure_codes = codelist(["246A."], system="ctv3")
study = StudyDefinition(
# Configure the expectations framework
default_expectations={
"date": {
"earliest": "1900-01-01",
"latest": "today"
},
"rate": "exponential_increase",
},
# This line defines the study population
population=patients.registered_with_one_practice_between(
"2019-02-01", "2020-02-01"),
# The rest of the lines define the covariates with associated GitHub issues
# https://github.com/ebmdatalab/tpp-sql-notebook/issues/33
age=patients.age_as_of(
"2020-02-01",
return_expectations={
"rate": "universal",
"int": {
"distribution": "population_ages"
},
},
),
# https://github.com/ebmdatalab/tpp-sql-notebook/issues/46
sex=patients.sex(return_expectations={
"rate": "universal",
"category": {
return_expectations={"incidence": 0.8},
),
age_cat=patients.satisfying(
"age >=18 AND age <= 110",
return_expectations={"incidence": 0.9},
age=patients.age_as_of(
"2020-02-29",
return_expectations={
"rate": "universal",
"int": {
"distribution": "population_ages"
},
},
),
),
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},