MICMIC-IV 个人查询策略（+官方查询语句注释）

MICMIC-IV 查询策略（实际查询SQL例子注释）

说明通过注释学习MIMIC官方的查询语句，总结MIMIC数据库的结构和查询特点。

内容：SQL语言和mimic-iv数据库的结构
目的：通过学习mimic数据库的数据格式，方便查询mimic数据库；学习mimic数据库的组织形式，也能够建立并查询自己的数据库

概念和特点：
本文的许多概念和对mimic数据库的认识来源于：[1] Wang S , Mcdermott M , Chauhan G , et al. MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III[J]. 2019. 并参考了通用的CDISC的相关知识。

静态数据, 没有时间因素的影响，多是分类变量，比如，年龄，性别等。
静态表格，整个表格的数据是一个模式,，为静态，通过表格连接汇总成横向的单个表格。
动态数据, 多条记录，通常是随时间的不同而变化。
动态数据表格，每个动态表格中保存的数据都是一类，都有多条记录，规律：其中有2-3列是“核心列”，一般是测试的名称（itemid）和测试的值（valuenum和value）是查询的主体；其余的列是辅助列，包括时间，flag等辅助因素。

**特殊的提取策略:**比如年龄的提取,有专门的公式来进行换算，查询策略也特殊。
例：

-- The columns of the table patients: anchor_age, anchor_year, anchor_year_group
-- provide information regarding the actual patient year for the patient admission,
-- and the patient's age at that time.-- anchor_year is a shifted year for the patient.
-- anchor_year_group is a range of years - the patient's anchor_year occurred during this range.
-- anchor_age is the patient's age in the anchor_year.
-- Example: a patient has an anchor_year of 2153,
-- anchor_year_group of 2008 - 2010, and an anchor_age of 60.
-- The year 2153 for the patient corresponds to 2008, 2009, or 2010.
-- The patient was 60 in the shifted year of 2153, i.e. they were 60 in 2008, 2009, or 2010.
-- A patient admission in 2154 will occur in 2009-2011,
-- an admission in 2155 will occur in 2010-2012, and so on.-- Therefore, the age of a patient = hospital admission time - anchor_year + anchor_age
SELECT  ad.subject_id, ad.hadm_id, ad.admittime, pa.anchor_age, pa.anchor_year, DATETIME_DIFF(ad.admittime, DATETIME(pa.anchor_year, 1, 1, 0, 0,0),'YEAR') + pa.anchor_age AS age
FROM mimic_core.admissions ad
INNER JOIN mimic_core.patients pa
ON ad.subject_id = pa.subject_id
;

一般的提取策略：

静态数据的提取：
1.一般策略：按照文献的策略提取并存入到表格; 一般查询，使用加减函数（比如出院时间减去入院时间,获得住院时长等）
2. 静态数据表格有（方便查询）： mimic_core.admissions(缩写ad)；mimic_core.patients(pa)；mimic_core.transfers(); mimic_hosp.diagnoses_icd (diag)
附例：静态查询语句实例+标注

SELECT   ad.subject_id, ad.hadm_id, ad.admittime, pa.anchor_age, pa.anchor_year, pa.gender, ad.ethnicity--种族
FROM mimic_core.admissions ad
INNER JOIN mimic_core.patients pa--内部表连接
ON ad.subject_id = pa.subject_id--表链接条件
limit 10;

评论：1.查询命令相对简单，不涉及复杂的换算；

动态表格数据的提取：

动态表格有哪些？mimic_icu.chartevents(缩写ce); mimic_hosp.labevents(缩写le);

基本策略：
step 1.多条数据变为单条数据，通过求平均值，首次值或末次值，中位数，频数等（使用聚合函数）；
step 2.纵向数据变横向数据。
step 3.连接表格。
多次测量的数据有分为多个具体情形：

心率等生命体征和实验室检查，求平均值比较合适；
频次

附：随时间变化的变量的SQL查询典型语句学习（原始语句来源于micmic官方公布的github中的语句，略微改动）：

-- create a table which has fuzzy boundaries on hospital admission
-- involves first creating a lag/lead version of disch/admit time
-- get first/last heart rate measurement during hospitalization for each stay_id（查询目的）
WITH t1 AS --with的功能是建立临时表格，可以多次引用
(select ce.stay_id, min(charttime) as intime_hr--获得首次和末次的测量的时间, max(charttime) as outtime_hr, avg(valuenum) as heart_rateFROM mimic_icu.chartevents ce -- only look at heart ratewhere ce.itemid = 220045 --代码代表的是心率的测量（代码的含义在mimic_icu.d_items表中查询）group by ce.stay_id--没有分号
)
-- add in subject_id/hadm_id， 以下是查询的主体,主要目的是连接表格,所以可以建立多个临时表格然后进行连接
selectie.subject_id, ie.hadm_id, ie.stay_id, t1.intime_hr , t1.outtime_hr,t1.heart_rate
FROM mimic_icu.icustays ie
left join t1 --引用了上面建立的临时表的内容on ie.stay_id = t1.stay_id;

例2 提取CRRT治疗的相关参数，代表了治疗相关的参数查询

with crrt_settings as--临时表格,CRRT-连续肾脏替代治疗
(select ce.stay_id, ce.charttime, CASE WHEN ce.itemid = 227290 THEN ce.value END AS CRRT_mode, CASE WHEN ce.itemid = 224149 THEN ce.valuenum ELSE NULL END AS AccessPressure--纵向表格变横向表格的策略, 或许可以先查询到纵向的表格,然后到Python中再进行处理(不便于SQL中结合其它的表格?), CASE WHEN ce.itemid = 224144 THEN ce.valuenum ELSE NULL END AS BloodFlow -- (ml/min), CASE WHEN ce.itemid = 228004 THEN ce.valuenum ELSE NULL END AS Citrate -- (ACD-A), CASE WHEN ce.itemid = 225183 THEN ce.valuenum ELSE NULL END AS CurrentGoal, CASE WHEN ce.itemid = 225977 THEN ce.value ELSE NULL END AS DialysateFluid, CASE WHEN ce.itemid = 224154 THEN ce.valuenum ELSE NULL END AS DialysateRate, CASE WHEN ce.itemid = 224151 THEN ce.valuenum ELSE NULL END AS EffluentPressure, CASE WHEN ce.itemid = 224150 THEN ce.valuenum ELSE NULL END AS FilterPressure, CASE WHEN ce.itemid = 225958 THEN ce.value ELSE NULL END AS HeparinConcentration -- (units/mL), CASE WHEN ce.itemid = 224145 THEN ce.valuenum ELSE NULL END AS HeparinDose -- (per hour)-- below may not account for drug infusion/hyperalimentation/anticoagulants infused, CASE WHEN ce.itemid = 224191 THEN ce.valuenum ELSE NULL END AS HourlyPatientFluidRemoval, CASE WHEN ce.itemid = 228005 THEN ce.valuenum ELSE NULL END AS PrefilterReplacementRate, CASE WHEN ce.itemid = 228006 THEN ce.valuenum ELSE NULL END AS PostFilterReplacementRate, CASE WHEN ce.itemid = 225976 THEN ce.value ELSE NULL END AS ReplacementFluid, CASE WHEN ce.itemid = 224153 THEN ce.valuenum ELSE NULL END AS ReplacementRate, CASE WHEN ce.itemid = 224152 THEN ce.valuenum ELSE NULL END AS ReturnPressure, CASE WHEN ce.itemid = 226457 THEN ce.valuenum END AS UltrafiltrateOutput-- separate system integrity into sub components-- need to do this as 224146 has multiple unique values for a single charttime-- e.g. "Clots Present" and "Active" at same time, CASEWHEN ce.itemid = 224146AND ce.value IN ('Active', 'Initiated', 'Reinitiated', 'New Filter')THEN 1WHEN ce.itemid = 224146AND ce.value IN ('Recirculating', 'Discontinued')THEN 0ELSE NULL END as system_active, CASEWHEN ce.itemid = 224146AND ce.value IN ('Clots Present', 'Clots Present')THEN 1WHEN ce.itemid = 224146AND ce.value IN ('No Clot Present', 'No Clot Present')THEN 0ELSE NULL END as clots, CASE WHEN ce.itemid = 224146AND ce.value IN ('Clots Increasing', 'Clot Increasing')THEN 1ELSE NULL END as clots_increasing, CASEWHEN ce.itemid = 224146AND ce.value IN ('Clotted')THEN 1ELSE NULL END as clottedfrom mimic_icu.chartevents cewhere ce.itemid in(-- MetaVision ITEMIDs227290, -- CRRT Mode224146, -- System Integrity-- 225956,  -- Reason for CRRT Filter Change-- above itemid is one of: Clotted, Line Changed, Procedure-- only ~200 rows, not super useful224149, -- Access Pressure224144, -- Blood Flow (ml/min)228004, -- Citrate (ACD-A)225183, -- Current Goal225977, -- Dialysate Fluid224154, -- Dialysate Rate224151, -- Effluent Pressure224150, -- Filter Pressure225958, -- Heparin Concentration (units/mL)224145, -- Heparin Dose (per hour)224191, -- Hourly Patient Fluid Removal228005, -- PBP (Prefilter) Replacement Rate228006, -- Post Filter Replacement Rate225976, -- Replacement Fluid224153, -- Replacement Rate224152, -- Return Pressure226457  -- Ultrafiltrate Output)and ce.value is not null
)
-- use MAX() to collapse to a single row 多条变一条策略之一
-- there is only ever 1 row for unique combinations of stay_id/charttime/itemid
--临时表结束，主查询开始
select stay_id
, charttime
, MAX(crrt_mode) AS crrt_mode
, MAX(AccessPressure) AS access_pressure
, MAX(BloodFlow) AS blood_flow
, MAX(Citrate) AS citrate--柠檬酸盐
, MAX(CurrentGoal) AS current_goal
, MAX(DialysateFluid) AS dialysate_fluid--透析
, MAX(DialysateRate) AS dialysate_rate
, MAX(EffluentPressure) AS effluent_pressure
, MAX(FilterPressure) AS filter_pressure
, MAX(HeparinConcentration) AS heparin_concentration
, MAX(HeparinDose) AS heparin_dose
, MAX(HourlyPatientFluidRemoval) AS hourly_patient_fluid_removal
, MAX(PrefilterReplacementRate) AS prefilter_replacement_rate
, MAX(PostFilterReplacementRate) AS postfilter_replacement_rate
, MAX(ReplacementFluid) AS replacement_fluid
, MAX(ReplacementRate) AS replacement_rate
, MAX(ReturnPressure) AS return_pressure
, MAX(UltrafiltrateOutput) AS ultrafiltrate_output
, MAX(system_active) AS system_active
, MAX(clots) AS clots
, MAX(clots_increasing) AS clots_increasing
, MAX(clotted) AS clotted
from crrt_settings--引用临时表格
group by stay_id, charttime

例3 炎症指标的查询，代表了实验室指标的查询过程

-- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
--DROP TABLE IF EXISTS inflammation; CREATE TABLE inflammation AS
SELECTMAX(subject_id) AS subject_id, MAX(hadm_id) AS hadm_id, MAX(charttime) AS charttime, le.specimen_id-- convert from itemid into a meaningful column, MAX(CASE WHEN itemid = 50889 THEN valuenum ELSE NULL END) AS crp--C反应蛋白-- , CAST(NULL AS NUMERIC) AS il6-- , CAST(NULL AS NUMERIC) AS procalcitonin
FROM mimic_hosp.labevents le--实验室检查指标存储的表格之一,还有另外的存储地方（注意！）
WHERE le.itemid IN
(50889 -- crp-- 51652 -- high sensitivity CRP
)
AND valuenum IS NOT NULL--where语句的联合条件
-- lab values cannot be 0 and cannot be negative
AND valuenum > 0
GROUP BY le.specimen_id;

例:这是一个比较综合的例子, 查询charlson 合并症的相关资料, 通过ICD-9和10限定相关的疾病。

-- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
--DROP TABLE IF EXISTS charlson; CREATE TABLE charlson AS
-- ------------------------------------------------------------------
-- This query extracts Charlson Comorbidity Index (CCI) based on the recorded ICD-9 and ICD-10 codes.
--
-- Reference for CCI:
-- (1) Charlson ME, Pompei P, Ales KL, MacKenzie CR. (1987) A new method of classifying prognostic
-- comorbidity in longitudinal studies: development and validation.J Chronic Dis; 40(5):373-83.
--
-- (2) Charlson M, Szatrowski TP, Peterson J, Gold J. (1994) Validation of a combined comorbidity
-- index. J Clin Epidemiol; 47(11):1245-51.
--
-- Reference for ICD-9-CM and ICD-10 Coding Algorithms for Charlson Comorbidities:
-- (3) Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining Comorbidities in ICD-9-CM
-- and ICD-10 administrative data. Med Care. 2005 Nov; 43(11): 1130-9.
-- ------------------------------------------------------------------
WITH diag AS--建立临时表格, 诊断信息
(SELECT hadm_id--医院的ID, CASE WHEN icd_version = 9 THEN icd_code ELSE NULL END AS icd9_code, CASE WHEN icd_version = 10 THEN icd_code ELSE NULL END AS icd10_codeFROM mimic_hosp.diagnoses_icd diag
)
, com AS--另外一个临时表格，基于上个临时表；
(SELECTad.hadm_id-- Myocardial infarction, MAX(CASE WHENSUBSTR(icd9_code, 1, 3) IN ('410','412')--substr(string,start,length)函数格式ORSUBSTR(icd10_code, 1, 3) IN ('I21','I22')--从第一个字符开始，匹配前3个，code的解释见d_icd_dianosis表格ORSUBSTR(icd10_code, 1, 4) = 'I252'THEN 1 ELSE 0 END) AS myocardial_infarct--心肌梗死-- Congestive heart failure, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) = '428'ORSUBSTR(icd9_code, 1, 5) IN ('39891','40201','40211','40291','40401','40403','40411','40413','40491','40493')OR SUBSTR(icd9_code, 1, 4) BETWEEN '4254' AND '4259'ORSUBSTR(icd10_code, 1, 3) IN ('I43','I50')ORSUBSTR(icd10_code, 1, 4) IN ('I099','I110','I130','I132','I255','I420','I425','I426','I427','I428','I429','P290')THEN 1 ELSE 0 END) AS congestive_heart_failure--充血性心力衰竭-- Peripheral vascular disease, , MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('440','441')ORSUBSTR(icd9_code, 1, 4) IN ('0930','4373','4471','5571','5579','V434')ORSUBSTR(icd9_code, 1, 4) BETWEEN '4431' AND '4439'ORSUBSTR(icd10_code, 1, 3) IN ('I70','I71')ORSUBSTR(icd10_code, 1, 4) IN ('I731','I738','I739','I771','I790','I792','K551','K558','K559','Z958','Z959')THEN 1 ELSE 0 END) AS peripheral_vascular_disease--周围性血管疾病-- Cerebrovascular disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) BETWEEN '430' AND '438'ORSUBSTR(icd9_code, 1, 5) = '36234'ORSUBSTR(icd10_code, 1, 3) IN ('G45','G46')OR SUBSTR(icd10_code, 1, 3) BETWEEN 'I60' AND 'I69'ORSUBSTR(icd10_code, 1, 4) = 'H340'THEN 1 ELSE 0 END) AS cerebrovascular_disease--脑血管疾病-- Dementia, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) = '290'ORSUBSTR(icd9_code, 1, 4) IN ('2941','3312')ORSUBSTR(icd10_code, 1, 3) IN ('F00','F01','F02','F03','G30')ORSUBSTR(icd10_code, 1, 4) IN ('F051','G311')THEN 1 ELSE 0 END) AS dementia-- Chronic pulmonary disease,慢性肺疾病, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) BETWEEN '490' AND '505'ORSUBSTR(icd9_code, 1, 4) IN ('4168','4169','5064','5081','5088')OR SUBSTR(icd10_code, 1, 3) BETWEEN 'J40' AND 'J47'OR SUBSTR(icd10_code, 1, 3) BETWEEN 'J60' AND 'J67'ORSUBSTR(icd10_code, 1, 4) IN ('I278','I279','J684','J701','J703')THEN 1 ELSE 0 END) AS chronic_pulmonary_disease-- Rheumatic disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) = '725'ORSUBSTR(icd9_code, 1, 4) IN ('4465','7100','7101','7102','7103','7104','7140','7141','7142','7148')ORSUBSTR(icd10_code, 1, 3) IN ('M05','M06','M32','M33','M34')ORSUBSTR(icd10_code, 1, 4) IN ('M315','M351','M353','M360')THEN 1 ELSE 0 END) AS rheumatic_disease--风湿性疾病-- Peptic ulcer disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('531','532','533','534')ORSUBSTR(icd10_code, 1, 3) IN ('K25','K26','K27','K28')THEN 1 ELSE 0 END) AS peptic_ulcer_disease--消化性溃疡-- Mild liver disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('570','571')ORSUBSTR(icd9_code, 1, 4) IN ('0706','0709','5733','5734','5738','5739','V427')ORSUBSTR(icd9_code, 1, 5) IN ('07022','07023','07032','07033','07044','07054')ORSUBSTR(icd10_code, 1, 3) IN ('B18','K73','K74')ORSUBSTR(icd10_code, 1, 4) IN ('K700','K701','K702','K703','K709','K713','K714','K715','K717','K760','K762','K763','K764','K768','K769','Z944')THEN 1 ELSE 0 END) AS mild_liver_disease--轻微的肝脏疾病-- Diabetes without chronic complication, MAX(CASE WHEN SUBSTR(icd9_code, 1, 4) IN ('2500','2501','2502','2503','2508','2509') ORSUBSTR(icd10_code, 1, 4) IN ('E100','E10l','E106','E108','E109','E110','E111','E116','E118','E119','E120','E121','E126','E128','E129','E130','E131','E136','E138','E139','E140','E141','E146','E148','E149')THEN 1 ELSE 0 END) AS diabetes_without_cc--无慢性并发症的糖尿病-- Diabetes with chronic complication, MAX(CASE WHEN SUBSTR(icd9_code, 1, 4) IN ('2504','2505','2506','2507')ORSUBSTR(icd10_code, 1, 4) IN ('E102','E103','E104','E105','E107','E112','E113','E114','E115','E117','E122','E123','E124','E125','E127','E132','E133','E134','E135','E137','E142','E143','E144','E145','E147')THEN 1 ELSE 0 END) AS diabetes_with_cc--有慢性并发症的糖尿病-- Hemiplegia or paraplegia, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('342','343')ORSUBSTR(icd9_code, 1, 4) IN ('3341','3440','3441','3442','3443','3444','3445','3446','3449')OR SUBSTR(icd10_code, 1, 3) IN ('G81','G82')OR SUBSTR(icd10_code, 1, 4) IN ('G041','G114','G801','G802','G830','G831','G832','G833','G834','G839')THEN 1 ELSE 0 END) AS paraplegia--截瘫-- Renal disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('582','585','586','V56')ORSUBSTR(icd9_code, 1, 4) IN ('5880','V420','V451')ORSUBSTR(icd9_code, 1, 4) BETWEEN '5830' AND '5837'ORSUBSTR(icd9_code, 1, 5) IN ('40301','40311','40391','40402','40403','40412','40413','40492','40493')          ORSUBSTR(icd10_code, 1, 3) IN ('N18','N19')ORSUBSTR(icd10_code, 1, 4) IN ('I120','I131','N032','N033','N034','N035','N036','N037','N052','N053','N054','N055','N056','N057','N250','Z490','Z491','Z492','Z940','Z992')THEN 1 ELSE 0 END) AS renal_disease--肾脏疾病-- Any malignancy, including lymphoma and leukemia, except malignant neoplasm of skin, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) BETWEEN '140' AND '172'ORSUBSTR(icd9_code, 1, 4) BETWEEN '1740' AND '1958'ORSUBSTR(icd9_code, 1, 3) BETWEEN '200' AND '208'ORSUBSTR(icd9_code, 1, 4) = '2386'ORSUBSTR(icd10_code, 1, 3) IN ('C43','C88')ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C00' AND 'C26'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C30' AND 'C34'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C37' AND 'C41'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C45' AND 'C58'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C60' AND 'C76'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C81' AND 'C85'ORSUBSTR(icd10_code, 1, 3) BETWEEN 'C90' AND 'C97'THEN 1 ELSE 0 END) AS malignant_cancer--恶性肿瘤,包括淋巴瘤和白血病,不包括恶性皮肤肿瘤-- Moderate or severe liver disease, MAX(CASE WHEN SUBSTR(icd9_code, 1, 4) IN ('4560','4561','4562')ORSUBSTR(icd9_code, 1, 4) BETWEEN '5722' AND '5728'ORSUBSTR(icd10_code, 1, 4) IN ('I850','I859','I864','I982','K704','K711','K721','K729','K765','K766','K767')THEN 1 ELSE 0 END) AS severe_liver_disease--中重度肝疾病-- Metastatic solid tumor, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('196','197','198','199')OR SUBSTR(icd10_code, 1, 3) IN ('C77','C78','C79','C80')THEN 1 ELSE 0 END) AS metastatic_solid_tumor--转移性实体瘤-- AIDS/HIV, MAX(CASE WHEN SUBSTR(icd9_code, 1, 3) IN ('042','043','044')OR SUBSTR(icd10_code, 1, 3) IN ('B20','B21','B22','B24')THEN 1 ELSE 0 END) AS aidsFROM mimic_core.admissions adLEFT JOIN diagON ad.hadm_id = diag.hadm_idGROUP BY ad.hadm_id
)
, ag AS
(SELECT hadm_id, age, CASE WHEN age <= 40 THEN 0WHEN age <= 50 THEN 1WHEN age <= 60 THEN 2WHEN age <= 70 THEN 3ELSE 4 END AS age_scoreFROM mimic_derived.age
)--以下是主查询
SELECT ad.subject_id, ad.hadm_id, ag.age_score, myocardial_infarct, congestive_heart_failure, peripheral_vascular_disease, cerebrovascular_disease, dementia, chronic_pulmonary_disease, rheumatic_disease, peptic_ulcer_disease, mild_liver_disease, diabetes_without_cc, diabetes_with_cc, paraplegia, renal_disease, malignant_cancer, severe_liver_disease , metastatic_solid_tumor , aids-- Calculate the Charlson Comorbidity Score using the original-- weights from Charlson, 1987., age_score+ myocardial_infarct + congestive_heart_failure + peripheral_vascular_disease+ cerebrovascular_disease + dementia + chronic_pulmonary_disease+ rheumatic_disease + peptic_ulcer_disease+ GREATEST(mild_liver_disease, 3*severe_liver_disease)+ GREATEST(2*diabetes_with_cc, diabetes_without_cc)+ GREATEST(2*malignant_cancer, 6*metastatic_solid_tumor)+ 2*paraplegia + 2*renal_disease + 6*aidsAS charlson_comorbidity_index
FROM mimic_core.admissions ad
LEFT JOIN com--引用临时表
ON ad.hadm_id = com.hadm_id
LEFT JOIN ag--引用临时表
ON com.hadm_id = ag.hadm_id
;

例: ICU患者中多种方案结合时间查询实验室检查(前面有个例子,是从医院中查询实验室检查)

-- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY.
-- DROP TABLE IF EXISTS kdigo_creatinine; CREATE TABLE kdigo_creatinine AS
-- Extract all creatinine values from labevents around patient's ICU stay(查询目的)
WITH cr AS--建立临时表,肌酐的值
(SELECTie.hadm_id, ie.stay_id, le.charttime, AVG(le.valuenum) AS creat--求平均值, FROM mimic_icu.icustays ieLEFT JOIN mimic_hosp.labevents leON ie.subject_id = le.subject_idAND le.ITEMID = 50912--多个条件,可以在ON 语句中进行添加AND le.VALUENUM IS NOT NULLAND le.VALUENUM <= 150AND le.CHARTTIME BETWEEN DATETIME_SUB(ie.intime, INTERVAL '7' DAY) AND ie.outtimeGROUP BY ie.hadm_id, ie.stay_id, le.charttime--按照时间分组
)
, cr48 AS--在上个临时表的基础上, 建立临时表,操作集中在不同时间
(-- add in the lowest value in the previous 48 hours(目的)SELECT cr.stay_id, cr.charttime, MIN(cr48.creat) AS creat_low_past_48hrFROM cr--引用上个临时表-- add in all creatinine values in the last 48 hoursLEFT JOIN cr cr48ON cr.stay_id = cr48.stay_idAND cr48.charttime <  cr.charttimeAND cr48.charttime >= DATETIME_SUB(cr.charttime, INTERVAL '48' HOUR)GROUP BY cr.stay_id, cr.charttime
)
, cr7 AS
(-- add in the lowest value in the previous 7 daysSELECTcr.stay_id, cr.charttime, MIN(cr7.creat) AS creat_low_past_7dayFROM cr-- add in all creatinine values in the last 7 daysLEFT JOIN cr cr7ON cr.stay_id = cr7.stay_idAND cr7.charttime <  cr.charttimeAND cr7.charttime >= DATETIME_SUB(cr.charttime, INTERVAL '7' DAY)GROUP BY cr.stay_id, cr.charttime
)
--以下是主查询
SELECT cr.hadm_id, cr.stay_id, cr.charttime, cr.creat, cr48.creat_low_past_48hr, cr7.creat_low_past_7day
FROM cr
LEFT JOIN cr48ON cr.stay_id = cr48.stay_idAND cr.charttime = cr48.charttime
LEFT JOIN cr7ON cr.stay_id = cr7.stay_idAND cr.charttime = cr7.charttime
;

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