--- name: first-icu-stay description: Identify first ICU stays and first hospital admissions for cohort selection. Use to exclude readmissions, create independent observations, or build adult patient cohorts. tier: validated category: clinical kind: methodology --- # First ICU Stay Selection Identifies first ICU stays and hospital admissions for cohort construction. Critical for avoiding correlated observations and inflated sample sizes from readmissions. ## When to Use This Skill - Creating research cohorts with independent observations - Excluding readmissions that may have different characteristics - Selecting incident (first-time) ICU patients - Matching cohorts by admission characteristics ## Pre-computed Table ```sql SELECT subject_id, hadm_id, stay_id, -- Demographics gender, dod, -- Date of death (if applicable) -- Hospital admission admittime, dischtime, los_hospital, -- Hospital length of stay (days) admission_age, race, hospital_expire_flag, hospstay_seq, -- Hospital admission sequence number first_hosp_stay, -- TRUE if first hospitalization -- ICU stay icu_intime, icu_outtime, los_icu, -- ICU length of stay (days) icustay_seq, -- ICU stay sequence within hospitalization first_icu_stay -- TRUE if first ICU stay of this hospitalization FROM mimiciv_derived.icustay_detail; ``` ## Key Columns Explained ### Hospital-Level - `hospstay_seq`: Order of hospital admission for this patient (1 = first ever) - `first_hosp_stay`: TRUE if this is the patient's first hospital admission ### ICU-Level (Within Hospitalization) - `icustay_seq`: Order of ICU stays within this hospitalization (1 = first ICU stay) - `first_icu_stay`: TRUE if this is the first ICU stay of the current hospitalization ## Age Calculation Age is calculated as: ```sql anchor_age + (YEAR(admittime) - anchor_year) ``` **Important**: MIMIC-IV shifts ages for patients > 89 years old at any admission. These patients have `anchor_age = 91` and ages are not exact. ## Common Cohort Selection Patterns ### First ICU Stay Only (Most Common) ```sql SELECT * FROM mimiciv_derived.icustay_detail WHERE first_icu_stay = TRUE; ``` ### First-Ever ICU Stay (Strictest) ```sql SELECT * FROM mimiciv_derived.icustay_detail WHERE first_hosp_stay = TRUE AND first_icu_stay = TRUE; ``` ### Adult Patients Only ```sql SELECT * FROM mimiciv_derived.icustay_detail WHERE admission_age >= 18 AND first_icu_stay = TRUE; ``` ### Exclude Very Short Stays ```sql SELECT * FROM mimiciv_derived.icustay_detail WHERE first_icu_stay = TRUE AND los_icu >= 1 -- At least 24 hours in ICU AND los_hospital >= 1; ``` ## Critical Implementation Notes 1. **Multiple ICU Stays**: One hospitalization can have multiple ICU stays. `first_icu_stay` identifies the first ICU stay within each hospitalization. 2. **Patient-Level vs Stay-Level**: Choose the right level of independence: - `first_hosp_stay = TRUE AND first_icu_stay = TRUE`: Most independent - `first_icu_stay = TRUE`: Independent within each hospitalization - All stays: May have correlated outcomes 3. **Age Shifting**: Ages > 89 are shifted to protect privacy. Anchor age is 91, actual age is approximated. 4. **Mortality Flags**: - `hospital_expire_flag`: Died during this hospitalization - `dod`: Date of death (may be after discharge) 5. **LOS Calculations**: - `los_hospital`: Days from admission to discharge - `los_icu`: Days from ICU admission to ICU discharge ## Example: Standard Adult Cohort ```sql SELECT stay_id, subject_id, hadm_id, admission_age, gender, los_icu, hospital_expire_flag FROM mimiciv_derived.icustay_detail WHERE first_icu_stay = TRUE AND admission_age >= 18 AND admission_age < 90 -- Exclude age-shifted patients AND los_icu >= 1; ``` ## Example: Readmission Analysis ```sql -- Patients with multiple ICU stays in same hospitalization SELECT hadm_id, COUNT(*) AS n_icu_stays FROM mimiciv_derived.icustay_detail GROUP BY hadm_id HAVING COUNT(*) > 1; -- Compare first vs subsequent stays SELECT first_icu_stay, COUNT(*) AS n_stays, ROUND(AVG(los_icu), 1) AS avg_los, ROUND(AVG(hospital_expire_flag), 3) AS mortality FROM mimiciv_derived.icustay_detail GROUP BY first_icu_stay; ``` ## Example: Age Distribution ```sql SELECT CASE WHEN admission_age < 40 THEN '<40' WHEN admission_age < 60 THEN '40-59' WHEN admission_age < 80 THEN '60-79' WHEN admission_age < 90 THEN '80-89' ELSE '90+' END AS age_group, COUNT(*) AS n_patients FROM mimiciv_derived.icustay_detail WHERE first_icu_stay = TRUE GROUP BY 1 ORDER BY 1; ``` ## Related Exclusion Criteria Common additional exclusions for research cohorts: - Comfort care / DNR orders if your local dataset includes a validated code-status concept - Organ donors - Very short stays (< 4-24 hours) - Missing key data elements - Specific diagnoses (trauma, cardiac surgery, etc.) ## References - Johnson AEW et al. "MIMIC-IV, a freely accessible electronic health record dataset." Scientific Data. 2023. --- Source attribution: hannesill Original project: https://github.com/hannesill/m4/blob/5f6688a2a98e9146731ed4d4c88d595ba7e71bf8/src/m4/skills/clinical/first-icu-stay/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Copyright (c) 2026 Hannes Ill Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. 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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: hannesill Original project: https://github.com/hannesill/m4/blob/5f6688a2a98e9146731ed4d4c88d595ba7e71bf8/src/m4/skills/clinical/first-icu-stay/SKILL.md Attribution basis: Recovered original package and original project license at a pinned revision Fields of work: Data & Analytics, Healthcare & Life Sciences Roles: Business Intelligence Analyst, Clinical Research, Data Analyst Specialties: Database Tools: Mimic Iv Country applicability: United States Classification basis: Source catalog labels Instruction SHA-256: 42e0341ba194df553d1e48b745586190af1cc48581ec014c85b09e299f19fffa Metadata reviewed: 2026-10-27 This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.