chore: regenerate postgres/duckdb concepts from BigQuery sources

Author: alistairewj

mimic-iii/concepts_postgres/code_status.sql

@@ -1,6 +1,9 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.code_status; CREATE TABLE mimiciii_derived.code_status AS
-/* This query extracts: */ /*    i) a patient's first code status */ /*    ii) a patient's last code status */ /*    iii) the time of the first entry of DNR or CMO */
+/* This query extracts: */
+/*    i) a patient's first code status */
+/*    ii) a patient's last code status */
+/*    iii) the time of the first entry of DNR or CMO */
 WITH t1 AS (
   SELECT
     icustay_id,

mimic-iii/concepts_postgres/comorbidity/elixhauser_ahrq_v37.sql

@@ -1019,7 +1019,8 @@ WITH eliflg AS (
   GROUP BY
     d.hadm_id
 )
-/* now merge these flags together to define elixhauser */ /* most are straightforward.. but hypertension flags are a bit more complicated */
+/* now merge these flags together to define elixhauser */
+/* most are straightforward.. but hypertension flags are a bit more complicated */
 SELECT
   adm.subject_id,
   adm.hadm_id,

mimic-iii/concepts_postgres/comorbidity/elixhauser_ahrq_v37_no_drg.sql

@@ -1,6 +1,11 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.elixhauser_ahrq_v37_no_drg; CREATE TABLE mimiciii_derived.elixhauser_ahrq_v37_no_drg AS
-/* This code uses the latest version of Elixhauser provided by AHRQ */ /* However, it does *not* filter based on diagnosis related groups (DRGs) */ /* As such, "comorbidities" identified are more likely to be associated with the primary reason for their hospital stay */ /* The code: */ /*  removes "primary" ICD9_CODE (seq_num != 1) */ /*  uses AHRQ published rules to define comorbidities */
+/* This code uses the latest version of Elixhauser provided by AHRQ */
+/* However, it does *not* filter based on diagnosis related groups (DRGs) */
+/* As such, "comorbidities" identified are more likely to be associated with the primary reason for their hospital stay */
+/* The code: */
+/*  removes "primary" ICD9_CODE (seq_num != 1) */
+/*  uses AHRQ published rules to define comorbidities */
 WITH eliflg AS (
   SELECT
     hadm_id,
@@ -613,7 +618,8 @@ WITH eliflg AS (
   GROUP BY
     hadm_id
 )
-/* now merge these flags together to define elixhauser */ /* most are straightforward.. but hypertension flags are a bit more complicated */
+/* now merge these flags together to define elixhauser */
+/* most are straightforward.. but hypertension flags are a bit more complicated */
 SELECT
   adm.subject_id,
   adm.hadm_id,

mimic-iii/concepts_postgres/comorbidity/elixhauser_quan.sql

@@ -1,6 +1,17 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.elixhauser_quan; CREATE TABLE mimiciii_derived.elixhauser_quan AS
-/* This code calculates the Elixhauser comorbidities as defined in Quan et. al 2009: */ /* Quan, Hude, et al. "Coding algorithms for defining comorbidities in */ /* ICD-9-CM and ICD-10 administrative data." Medical care (2005): 1130-1139. */ /*  https://www.ncbi.nlm.nih.gov/pubmed/16224307 */ /* Quan defined an "Enhanced ICD-9" coding scheme for deriving Elixhauser */ /* comorbidities from ICD-9 billing codes. This script implements that calculation. */ /* The logic of the code is roughly that, if the comorbidity lists a length 3 */ /* ICD-9 code (e.g. 585), then we only require a match on the first 3 characters. */ /* This code derives each comorbidity as follows: */ /*  1) ICD9_CODE is directly compared to 5 character codes */ /*  2) The first 4 characters of ICD9_CODE are compared to 4 character codes */ /*  3) The first 3 characters of ICD9_CODE are compared to 3 character codes */
+/* This code calculates the Elixhauser comorbidities as defined in Quan et. al 2009: */
+/* Quan, Hude, et al. "Coding algorithms for defining comorbidities in */
+/* ICD-9-CM and ICD-10 administrative data." Medical care (2005): 1130-1139. */
+/*  https://www.ncbi.nlm.nih.gov/pubmed/16224307 */
+/* Quan defined an "Enhanced ICD-9" coding scheme for deriving Elixhauser */
+/* comorbidities from ICD-9 billing codes. This script implements that calculation. */
+/* The logic of the code is roughly that, if the comorbidity lists a length 3 */
+/* ICD-9 code (e.g. 585), then we only require a match on the first 3 characters. */
+/* This code derives each comorbidity as follows: */
+/*  1) ICD9_CODE is directly compared to 5 character codes */
+/*  2) The first 4 characters of ICD9_CODE are compared to 4 character codes */
+/*  3) The first 3 characters of ICD9_CODE are compared to 3 character codes */
 WITH eliflg AS (
   SELECT
     hadm_id,
@@ -388,7 +399,8 @@ WITH eliflg AS (
   GROUP BY
     hadm_id
 )
-/* now merge these flags together to define elixhauser */ /* most are straightforward.. but hypertension flags are a bit more complicated */
+/* now merge these flags together to define elixhauser */
+/* most are straightforward.. but hypertension flags are a bit more complicated */
 SELECT
   adm.hadm_id,
   chf AS congestive_heart_failure,

mimic-iii/concepts_postgres/comorbidity/elixhauser_score_ahrq.sql

@@ -1,6 +1,7 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.elixhauser_score_ahrq; CREATE TABLE mimiciii_derived.elixhauser_score_ahrq AS
-/* This query provides various methods of combining the Elixhauser components into a single score */ /* The methods are called "vanWalRaven" and "SID30", and "SID29" */
+/* This query provides various methods of combining the Elixhauser components into a single score */
+/* The methods are called "vanWalRaven" and "SID30", and "SID29" */
 SELECT
   subject_id,
   hadm_id, /* Below is the van Walraven score */

mimic-iii/concepts_postgres/comorbidity/elixhauser_score_quan.sql

@@ -1,6 +1,7 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.elixhauser_score_quan; CREATE TABLE mimiciii_derived.elixhauser_score_quan AS
-/* This query provides various methods of combining the Elixhauser components into a single score */ /* The methods are called "vanWalRaven" and "SID30", and "SID29" */
+/* This query provides various methods of combining the Elixhauser components into a single score */
+/* The methods are called "vanWalRaven" and "SID30", and "SID29" */
 SELECT
   hadm_id, /* Below is the van Walraven score */
   0 * aids + 0 * alcohol_abuse + -2 * blood_loss_anemia + 7 * congestive_heart_failure + 3 /* Cardiac arrhythmias are not included in van Walraven based on Quan 2007 */ * chronic_pulmonary + 3 * coagulopathy + -2 * deficiency_anemias + -3 * depression + 0 * diabetes_complicated + 0 * diabetes_uncomplicated + -7 * drug_abuse + 5 * fluid_electrolyte + 0 * hypertension + 0 * hypothyroidism + 11 * liver_disease + 9 * lymphoma + 12 * metastatic_cancer + 6 * other_neurological + -4 * obesity + 7 * paralysis + 2 * peripheral_vascular + 0 * peptic_ulcer + 0 * psychoses + 4 * pulmonary_circulation + 0 * rheumatoid_arthritis + 5 * renal_failure + 4 * solid_tumor + -1 * valvular_disease + 6 * weight_loss AS elixhauser_vanwalraven, /* Below is the 29 component SID score */

mimic-iii/concepts_postgres/demographics/heightweight.sql

@@ -1,6 +1,12 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.heightweight; CREATE TABLE mimiciii_derived.heightweight AS
-/* ------------------------------------------------------------------ */ /* Title: Extract height and weight for ICUSTAY_IDs */ /* Description: This query gets the first, minimum, and maximum weight and height */ /*        for a single ICUSTAY_ID. It extracts data from the CHARTEVENTS table. */ /* MIMIC version: MIMIC-III v1.4 */ /* ------------------------------------------------------------------ */ /* prep height */
+/* ------------------------------------------------------------------ */
+/* Title: Extract height and weight for ICUSTAY_IDs */
+/* Description: This query gets the first, minimum, and maximum weight and height */
+/*        for a single ICUSTAY_ID. It extracts data from the CHARTEVENTS table. */
+/* MIMIC version: MIMIC-III v1.4 */
+/* ------------------------------------------------------------------ */
+/* prep height */
 WITH ht_stg AS (
   SELECT
     c.subject_id,

mimic-iii/concepts_postgres/demographics/icustay_detail.sql

@@ -1,6 +1,13 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.icustay_detail; CREATE TABLE mimiciii_derived.icustay_detail AS
-/* ------------------------------------------------------------------ */ /* Title: Detailed information on ICUSTAY_ID */ /* Description: This query provides a useful set of information regarding patient */ /*              ICU stays. The information is combined from the admissions, patients, and */ /*              icustays tables. It includes age, length of stay, sequence, and expiry flags. */ /* MIMIC version: MIMIC-III v1.3 */ /* ------------------------------------------------------------------ */ /* This query extracts useful demographic/administrative information for patient ICU stays */
+/* ------------------------------------------------------------------ */
+/* Title: Detailed information on ICUSTAY_ID */
+/* Description: This query provides a useful set of information regarding patient */
+/*              ICU stays. The information is combined from the admissions, patients, and */
+/*              icustays tables. It includes age, length of stay, sequence, and expiry flags. */
+/* MIMIC version: MIMIC-III v1.3 */
+/* ------------------------------------------------------------------ */
+/* This query extracts useful demographic/administrative information for patient ICU stays */
 SELECT
   ie.subject_id,
   ie.hadm_id,

mimic-iii/concepts_postgres/demographics/icustay_hours.sql

@@ -1,6 +1,12 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.icustay_hours; CREATE TABLE mimiciii_derived.icustay_hours AS
-/* This query generates a row for every hour the patient is in the ICU. */ /* The hours are based on clock-hours (i.e. 02:00, 03:00). */ /* The hour clock starts 24 hours before the first heart rate measurement. */ /* Note that the time of the first heart rate measurement is ceilinged to the hour. */ /* this query extracts the cohort and every possible hour they were in the ICU */ /* this table can be to other tables on ICUSTAY_ID and (ENDTIME - 1 hour,ENDTIME] */ /* get first/last measurement time */
+/* This query generates a row for every hour the patient is in the ICU. */
+/* The hours are based on clock-hours (i.e. 02:00, 03:00). */
+/* The hour clock starts 24 hours before the first heart rate measurement. */
+/* Note that the time of the first heart rate measurement is ceilinged to the hour. */
+/* this query extracts the cohort and every possible hour they were in the ICU */
+/* this table can be to other tables on ICUSTAY_ID and (ENDTIME - 1 hour,ENDTIME] */
+/* get first/last measurement time */
 WITH all_hours AS (
   SELECT
     it.icustay_id, /* ceiling the intime to the nearest hour by adding 59 minutes then truncating */ /* note thart we truncate by parsing as string, rather than using DATETIME_TRUNC */ /* this is done to enable compatibility with psql */

mimic-iii/concepts_postgres/demographics/icustay_times.sql

@@ -1,6 +1,7 @@
 -- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
 DROP TABLE IF EXISTS mimiciii_derived.icustay_times; CREATE TABLE mimiciii_derived.icustay_times AS
-/* create a table which has fuzzy boundaries on hospital admission */ /* involves first creating a lag/lead version of disch/admit time */
+/* create a table which has fuzzy boundaries on hospital admission */
+/* involves first creating a lag/lead version of disch/admit time */
 WITH h AS (
   SELECT
     subject_id,