def medication_count_12m_6m(med_codelist):
return patients.with_these_medications(
med_codelist,
between=["2019-03-01", "2020-08-31"],
returning="number_of_matches_in_period",
return_expectations={
"int": {
"distribution": "normal",
"mean": 3,
"stddev": 2
},
"incidence": 0.1,
},
)
def medication_latest(med_codelist):
return patients.with_these_medications(
med_codelist,
between=["2010-01-01", "2020-02-29"],
returning="date",
find_last_match_in_period=True,
include_month=True,
return_expectations={
"incidence": 0.2,
"date": {
"earliest": "2010-01-01",
"latest": "2020-02-29"
},
},
)
def test_column_refs_in_date_expressions_do_not_trigger_errors():
# Further down the road we want to actually interpret these expressions and
# generate appopriate dates, but for now we just need to not blow up when
# we encounter them
study = StudyDefinition(
population=patients.all(),
copd_exacerbation=patients.with_these_clinical_events(
codelist(["X"], system="ctv3"),
between=["2001-12-01", "2002-06-01"],
returning="date",
return_expectations={
"rate": "exponential_increase",
"incidence": 0.2,
"date": {
"earliest": "1990-01-01",
"latest": "today"
},
},
find_last_match_in_period=True,
date_format="YYYY-MM-DD",
),
drug_after_exacerbation=patients.with_these_medications(
codelist(["Y"], system="snomed"),
between=["copd_exacerbation", "copd_exacerbation + 3 months"],
returning="date",
return_expectations={
"rate": "exponential_increase",
"incidence": 0.2,
"date": {
"earliest": "1990-01-01",
"latest": "today"
},
},
find_first_match_in_period=True,
date_format="YYYY-MM-DD",
),
)
population_size = 10000
# Just ensure no exception is raised
study.make_df_from_expectations(population_size)
"2020-02-01",
returning="index_of_multiple_deprivation",
round_to_nearest=100,
return_expectations={
"rate": "universal",
"category": {"ratios": {"100": 0.1, "200": 0.2, "300": 0.7}},
},
),
# https://github.com/opensafely/risk-factors-research/issues/47
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}},
},
),
# https://codelists.opensafely.org/codelist/opensafely/asthma-inhaler-salbutamol-medication/2020-04-15/
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},
},
),
)
"NO_DM": "DEFAULT",
},
return_expectations={
"category": {
"ratios": {
"T1DM": 0.03,
"T2DM": 0.2,
"UNKNOWN_DM": 0.02,
"NO_DM": 0.75
}
},
"rate": "universal"
},
oad_lastyear_meds=patients.with_these_medications(
oad_med_codes,
between=["2019-02-01", "2020-02-01"],
returning="number_of_matches_in_period",
),
insulin_lastyear_meds=patients.with_these_medications(
insulin_med_codes,
between=["2019-02-01", "2020-02-01"],
returning="number_of_matches_in_period",
),
),
#EXETER ALGORITHM USING OPENSAFELY CODELISTS
diabetes_exeter_os=patients.categorised_as(
{
"T1DM_EX_OS": """
insulin_last6mo >= 2 AND t1dm_count >= t2dm_count * 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
bp_sys=patients.mean_recorded_value(systolic_blood_pressure_codes,
on_most_recent_day_of_measurement=True,
between=["2017-02-01", "2020-01-31"],
include_measurement_date=True,
date_format="YYYY-MM",
return_expectations={"float": {"distribution": "normal", "mean": 80, "stddev": 10},
"date": {"earliest": "2019-02-01", "latest": "2020-01-31"},
"incidence": 0.95,}),
## ace inhibitor
ace_inhibitor = patients.with_these_medications(ace_inhibitor_codes,
between=["1900-01-01", "2020-02-01"],
include_date_of_match = True,
date_format="YYYY-MM-DD",
returning="binary_flag",
return_expectations = {"incidence": 0.05,
"date": {"earliest": "1980-02-01",
"latest": "2020-01-31"}}),
## arb
arb_inhibitor = patients.with_these_medications(arb_inhibitor_codes,
between=["1900-01-01", "2020-02-01"],
include_date_of_match = True,
date_format="YYYY-MM-DD",
returning="binary_flag",
return_expectations = {"incidence": 0.05,
"date": {"earliest": "1980-02-01",
"latest": "2020-01-31"}}),
"0": 0.8,
"1": 0.1,
"2": 0.1
}
},
},
recent_asthma_code=patients.with_these_clinical_events(
asthma_codes,
between=["2017-02-01", "2020-01-31"],
),
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", "2020-01-31"],
returning="number_of_matches_in_period",
),
),
chronic_cardiac_disease=patients.with_these_clinical_events(
chronic_cardiac_disease_codes,
return_first_date_in_period=True,
include_month=True,
return_expectations={"date": {
"latest": "2020-01-31"
}},
),
type1_diabetes=patients.with_these_clinical_events(
diabetes_t1_codes,
on_or_before="2020-01-31",
return_first_date_in_period=True,
"2020-02-29",
return_expectations={"incidence": 0.9},
),
has_asthma=patients.with_these_clinical_events(
current_asthma_codes,
between=["2017-02-28", "2020-02-29"],
return_expectations={"incidence": 0.9},
),
# MEDICATIONS
nsaid_last_three_years=patients.with_these_medications(
nsaid_codes,
between=["2017-02-28", "2020-02-29"],
returning="date",
find_last_match_in_period=True,
include_month=True,
include_day=False,
return_expectations={
"date": {
"earliest": "2017-02-28",
"latest": "2020-02-29"
}
},
),
# ASPIRIN
aspirin_ten_years=patients.with_these_medications(
aspirin_med_codes,
between=["2010-02-01", "2020-02-29"],
returning="date",
find_last_match_in_period=True,
include_month=True,
include_day=False,
return_expectations={
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},
),
)
date_format="YYYY-MM-DD",
with_these_diagnoses=
ics_codes, # placeholder https://github.com/opensafely/cohort-extractor/issues/182#issuecomment-651782064
return_expectations={"date": {
"earliest": "2020-03-01"
}},
),
# MEDICATIONS
# NSAID
nsaid_last_three_years=patients.with_these_medications(
nsaid_codes,
between=["2017-02-28", "2020-02-29"],
returning="date",
find_last_match_in_period=True,
include_month=True,
include_day=False,
return_expectations={
"date": {
"earliest": "2017-02-28",
"latest": "2020-02-29"
}
},
),
nsaid_after_march=patients.with_these_medications(
nsaid_codes,
on_or_after="2020-03-01",
returning="date",
find_first_match_in_period=True,
include_month=True,
include_day=True,
return_expectations={
"date": {
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
"incidence": 0.01,
},
),
current_copd=patients.with_these_clinical_events(
current_copd_codes,
on_or_before=campaign_start,
returning="binary_flag",
return_expectations={
"incidence": 0.01,
},
),
# on a dmard - indicative of immunosuppression
dmards=patients.with_these_medications(
dmards_codes,
on_or_before=campaign_start,
returning="binary_flag",
return_expectations={
"incidence": 0.01,
},
),
# dementia
dementia=patients.with_these_clinical_events(
dementia_codes,
on_or_before=campaign_start,
returning="binary_flag",
return_expectations={
"incidence": 0.01,
},
),
dialysis=patients.with_these_clinical_events(
dialysis_codes,
on_or_before=campaign_start,
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,
include_day=True,
return_expectations={"date": {"earliest": "2020-03-01"}},
"0": 0.8,
"1": 0.1,
"2": 0.1
}
},
},
recent_asthma_code=patients.with_these_clinical_events(
asthma_codes,
between=["2017-02-01", "2020-11-16"],
),
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=["2019-11-16", "2020-11-16"],
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,
