mimic-sapsii-24h-raw

mimic-sapsii-24h-raw is a skill for Claude Code, Codex from hannesill/m4. It costs 0 tokens per session (4,395 once invoked), scanned A, a copy of mimic-apsiii-24h-raw, MIT.

A SQL query for calculating the Simplified Acute Physiology Score II (SAPS-II), a measure of how severely ill a patient is during the first 24 hours in an intensive care unit.

In plain words
What is it for?
Use it to extract first-day ICU data and calculate SAPS-II scores for clinical research or patient-outcome analysis.
Why use it?
It provides a standard way to summarize ICU illness severity from patient data instead of calculating the score manually.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to extract first-day ICU data and calculate SAPS-II scores for clinical research or patient-outcome analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hannesill/m4/mimic-sapsii-24h-raw
View source ↗ hannesill/m4
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add hannesill/m4 --skill mimic-sapsii-24h-raw
Clone the repo
git clone --depth 1 https://github.com/hannesill/m4

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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<a href="https://agentmods.dev/skills/hannesill/m4/mimic-sapsii-24h-raw"><img src="https://agentmods.dev/badge/skills/hannesill/m4/mimic-sapsii-24h-raw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,395 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.04395
Opus 5 $0.00000 $0.02197
Sonnet 5 $0.00000 $0.00879
Haiku 4.5 $0.00000 $0.00439

Measured 11d ago against content hash 66f240979ebf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

mimic-sapsii-24h-raw scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to mimic-apsiii-24h-raw — 1,337 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

benchmark/tasks/sapsii/mimic-sapsii-24h-raw/skills-rawsql/mimic-sapsii-24h-raw/SKILL.md · 488 lines

How it starts

The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reference SQL (matched-content control)

The following block is the public reference SQL used to construct the ground truth for this task. It is provided verbatim, without procedural prose, to test whether matched task-relevant content alone explains the WITH-SKILL gain.

-- ------------------------------------------------------------------
-- Title: Simplified Acute Physiology Score II (SAPS-II)
-- This query extracts the SAPS-II score for the first 24 hours of
-- each ICU patient's stay. SAPS-II quantifies severity using 15
-- weighted components including physiological variables, chronic
-- disease classification, and admission type.
-- ------------------------------------------------------------------

-- Reference for SAPS-II:
--    Le Gall JR, Lemeshow S, Saulnier F. "A new Simplified Acute
--    Physiology Score (SAPS II) based on a European/North American
--    multicenter study." JAMA. 1993;270(24):2957-2963.

-- Adapted from mimic-code sapsii.sql

WITH co AS (
    SELECT
        subject_id,
        hadm_id,
        stay_id,
        intime AS starttime,
        intime + INTERVAL '24' HOUR AS endtime
    FROM mimiciv_icu.icustays
)

, cpap AS (
    SELECT
        co.subject_id,
        co.stay_id,
        GREATEST(MIN(charttime - INTERVAL '1' HOUR), co.starttime) AS starttime,
        LEAST(MAX(charttime + INTERVAL '4' HOUR), co.endtime) AS endtime,
        MAX(CASE WHEN REGEXP_MATCHES(LOWER(ce.value), '(cpap mask|bipap)') THEN 1 ELSE 0 END) AS cpap
    FROM co
    INNER JOIN mimiciv_icu.chartevents AS ce
        ON co.stay_id = ce.stay_id
        AND ce.charttime > co.starttime
        AND ce.charttime <= co.endtime
    WHERE
        ce.itemid = 226732 AND REGEXP_MATCHES(LOWER(ce.value), '(cpap mask|bipap)')
    GROUP BY
        co.subject_id,
        co.stay_id,
        co.starttime,
        co.endtime
)

, surgflag AS (
    SELECT
        adm.hadm_id,
        CASE WHEN LOWER(curr_service) LIKE '%surg%' THEN 1 ELSE 0 END AS surgical,
        ROW_NUMBER() OVER (PARTITION BY adm.hadm_id ORDER BY transfertime NULLS FIRST) AS serviceorder
    FROM mimiciv_hosp.admissions AS adm
    LEFT JOIN mimiciv_hosp.services AS se
        ON adm.hadm_id = se.hadm_id
)

, comorb AS (
    SELECT
        hadm_id,
        MAX(
            CASE
                WHEN icd_version = 9 AND SUBSTR(icd_code, 1, 3) BETWEEN '042' AND '044'
                THEN 1
                WHEN icd_version = 10 AND SUBSTR(icd_code, 1, 3) BETWEEN 'B20' AND 'B22'
                THEN 1
                WHEN icd_version = 10 AND SUBSTR(icd_code, 1, 3) = 'B24'
                THEN 1
                ELSE 0
            END
        ) AS aids,
        MAX(
            CASE
                WHEN icd_version = 9
                THEN CASE
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20000' AND '20238'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20240' AND '20248'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20250' AND '20302'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20310' AND '20312'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20302' AND '20382'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20400' AND '20522'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20580' AND '20702'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20720' AND '20892'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 4) IN ('2386', '2733')
                    THEN 1
                    ELSE 0
                END
                WHEN icd_version = 10 AND SUBSTR(icd_code, 1, 3) BETWEEN 'C81' AND 'C96'
                THEN 1
                ELSE 0
            END
        ) AS hem,
        MAX(
            CASE
                WHEN icd_version = 9
                THEN CASE
                    WHEN SUBSTR(icd_code, 1, 4) BETWEEN '1960' AND '1991'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) BETWEEN '20970' AND '20975'
                    THEN 1
                    WHEN SUBSTR(icd_code, 1, 5) IN ('20979', '78951')
                    THEN 1
                    ELSE 0
                END
                WHEN icd_version = 10 AND SUBSTR(icd_code, 1, 3) BETWEEN 'C77' AND 'C79'
                THEN 1
                WHEN icd_version = 10 AND SUBSTR(icd_code, 1, 4) = 'C800'
                THEN 1
                ELSE 0
            END
        ) AS mets
    FROM mimiciv_hosp.diagnoses_icd
    GROUP BY
        hadm_id
)

, pafi1 AS (
    SELECT
        co.stay_id,
        bg.charttime,
        pao2fio2ratio AS pao2fio2,
        CASE WHEN NOT vd.stay_id IS NULL THEN 1 ELSE 0 END AS vent,
        CASE WHEN NOT cp.subject_id IS NULL THEN 1 ELSE 0 END AS cpap
    FROM co
    LEFT JOIN mimiciv_derived.bg AS bg
        ON co.subject_id = bg.subject_id
        AND bg.specimen = 'ART.'
        AND bg.charttime > co.starttime
        AND bg.charttime <= co.endtime
    LEFT JOIN mimiciv_derived.ventilation AS vd
        ON co.stay_id = vd.stay_id
        AND bg.charttime > vd.starttime
        AND bg.charttime <= vd.endtime
        AND vd.ventilation_status = 'InvasiveVent'
    LEFT JOIN cpap AS cp
        ON bg.subject_id = cp.subject_id
        AND bg.charttime > cp.starttime
        AND bg.charttime <= cp.endtime
)

, pafi2 AS (
    SELECT
        stay_id,
        MIN(pao2fio2) AS pao2fio2_vent_min
    FROM pafi1
    WHERE
        vent = 1 OR cpap = 1
    GROUP BY
        stay_id
)

, gcs AS (
    SELECT
        co.stay_id,
        MIN(gcs.gcs) AS mingcs
    FROM co
    LEFT JOIN mimiciv_derived.gcs AS gcs
        ON co.stay_id = gcs.stay_id
        AND co.starttime < gcs.charttime
        AND gcs.charttime <= co.endtime
    GROUP BY
        co.stay_id
)

, vital AS (
    SELECT
        co.stay_id,
        MIN(vital.heart_rate) AS heartrate_min,
        MAX(vital.heart_rate) AS heartrate_max,
        MIN(vital.sbp) AS sysbp_min,
        MAX(vital.sbp) AS sysbp_max,
        MIN(vital.temperature) AS tempc_min,
        MAX(vital.temperature) AS tempc_max
    FROM co
    LEFT JOIN mimiciv_derived.vitalsign AS vital
        ON co.subject_id = vital.subject_id
        AND co.starttime < vital.charttime
        AND co.endtime >= vital.charttime
    GROUP BY
        co.stay_id
)

, uo AS (
    SELECT
        co.stay_id,
        SUM(uo.urineoutput) AS urineoutput
    FROM co
    LEFT JOIN mimiciv_derived.urine_output AS uo
        ON co.stay_id = uo.stay_id
        AND co.starttime < uo.charttime
        AND co.endtime >= uo.charttime
    GROUP BY
        co.stay_id
)

, labs AS (
    SELECT
        co.stay_id,
        MIN(labs.bun) AS bun_min,
        MAX(labs.bun) AS bun_max,
        MIN(labs.potassium) AS potassium_min,
        MAX(labs.potassium) AS potassium_max,
        MIN(labs.sodium) AS sodium_min,
        MAX(labs.sodium) AS sodium_max,
        MIN(labs.bicarbonate) AS bicarbonate_min,
        MAX(labs.bicarbonate) AS bicarbonate_max
    FROM co
    LEFT JOIN mimiciv_derived.chemistry AS labs
        ON co.subject_id = labs.subject_id
        AND co.starttime < labs.charttime
        AND co.endtime >= labs.charttime
    GROUP BY
        co.stay_id
)

, cbc AS (
    SELECT
        co.stay_id,
        MIN(cbc.wbc) AS wbc_min,
        MAX(cbc.wbc) AS wbc_max
    FROM co
    LEFT JOIN mimiciv_derived.complete_blood_count AS cbc
        ON co.subject_id = cbc.subject_id
        AND co.starttime < cbc.charttime
        AND co.endtime >= cbc.charttime
    GROUP BY
        co.stay_id
)

, enz AS (
    SELECT
        co.stay_id,
        MIN(enz.bilirubin_total) AS bilirubin_min,
        MAX(enz.bilirubin_total) AS bilirubin_max
    FROM co
    LEFT JOIN mimiciv_derived.enzyme AS enz
        ON co.subject_id = enz.subject_id
        AND co.starttime < enz.charttime
        AND co.endtime >= enz.charttime
    GROUP BY
        co.stay_id
)

, cohort AS (
    SELECT
        ie.subject_id,
        ie.hadm_id,
        ie.stay_id,
        va.age,
        vital.heartrate_max,
        vital.heartrate_min,
        vital.sysbp_max,
        vital.sysbp_min,
        vital.tempc_max,
        vital.tempc_min,
        pf.pao2fio2_vent_min,
        uo.urineoutput,
        labs.bun_min,
        labs.bun_max,
        cbc.wbc_min,
        cbc.wbc_max,
        labs.potassium_min,
        labs.potassium_max,
        labs.sodium_min,
        labs.sodium_max,
        labs.bicarbonate_min,
        labs.bicarbonate_max,
        enz.bilirubin_min,
        enz.bilirubin_max,
        gcs.mingcs,
        comorb.aids,
        comorb.hem,
        comorb.mets,
        CASE
            WHEN adm.admission_type = 'ELECTIVE' AND sf.surgical = 1
            THEN 'ScheduledSurgical'
            WHEN adm.admission_type <> 'ELECTIVE' AND sf.surgical = 1
            THEN 'UnscheduledSurgical'
            ELSE 'Medical'
        END AS admissiontype
    FROM mimiciv_icu.icustays AS ie
    INNER JOIN mimiciv_hosp.admissions AS adm
        ON ie.hadm_id = adm.hadm_id
    LEFT JOIN mimiciv_derived.age AS va
        ON ie.hadm_id = va.hadm_id
    INNER JOIN co
        ON ie.stay_id = co.stay_id
    LEFT JOIN pafi2 AS pf
        ON ie.stay_id = pf.stay_id
    LEFT JOIN surgflag AS sf
        ON adm.hadm_id = sf.hadm_id AND sf.serviceorder = 1
    LEFT JOIN comorb
        ON ie.hadm_id = comorb.hadm_id
    LEFT JOIN gcs AS gcs
        ON ie.stay_id = gcs.stay_id
    LEFT JOIN vital
        ON ie.stay_id = vital.stay_id
    LEFT JOIN uo
        ON ie.stay_id = uo.stay_id
    LEFT JOIN labs
        ON ie.stay_id = labs.stay_id
    LEFT JOIN cbc
        ON ie.stay_id = cbc.stay_id
    LEFT JOIN enz
        ON ie.stay_id = enz.stay_id
)

, scorecomp AS (
    SELECT
        cohort.*,
        CASE
            WHEN age IS NULL THEN NULL
            WHEN age < 40 THEN 0
            WHEN age < 60 THEN 7
            WHEN age < 70 THEN 12
            WHEN age < 75 THEN 15
            WHEN age < 80 THEN 16
            WHEN age >= 80 THEN 18
        END AS age_score,
        CASE
            WHEN heartrate_max IS NULL THEN NULL
            WHEN heartrate_min < 40 THEN 11
            WHEN heartrate_max >= 160 THEN 7
            WHEN heartrate_max >= 120 THEN 4
            WHEN heartrate_min < 70 THEN 2
            WHEN heartrate_max >= 70
                AND heartrate_max < 120
                AND heartrate_min >= 70
                AND heartrate_min < 120
            THEN 0
        END AS hr_score,
        CASE
            WHEN sysbp_min IS NULL THEN NULL
            WHEN sysbp_min < 70 THEN 13
            WHEN sysbp_min < 100 THEN 5
            WHEN sysbp_max >= 200 THEN 2
            WHEN sysbp_max >= 100
                AND sysbp_max < 200
                AND sysbp_min >= 100
                AND sysbp_min < 200
            THEN 0
        END AS sysbp_score,
        CASE
            WHEN tempc_max IS NULL THEN NULL
            WHEN tempc_max >= 39.0 THEN 3
            WHEN tempc_min < 39.0 THEN 0
        END AS temp_score,
        CASE
            WHEN pao2fio2_vent_min IS NULL THEN NULL
            WHEN pao2fio2_vent_min < 100 THEN 11
            WHEN pao2fio2_vent_min < 200 THEN 9
            WHEN pao2fio2_vent_min >= 200 THEN 6
        END AS pao2fio2_score,
        CASE
            WHEN urineoutput IS NULL THEN NULL
            WHEN urineoutput < 500.0 THEN 11
            WHEN urineoutput < 1000.0 THEN 4
            WHEN urineoutput >= 1000.0 THEN 0
        END AS uo_score,
        CASE
            WHEN bun_max IS NULL THEN NULL
            WHEN bun_max < 28.0 THEN 0
            WHEN bun_max < 84.0 THEN 6
            WHEN bun_max >= 84.0 THEN 10
        END AS bun_score,
        CASE
            WHEN wbc_max IS NULL THEN NULL
            WHEN wbc_min < 1.0 THEN 12
            WHEN wbc_max >= 20.0 THEN 3
            WHEN wbc_max >= 1.0
                AND wbc_max < 20.0
                AND wbc_min >= 1.0
                AND wbc_min < 20.0
            THEN 0
        END AS wbc_score,
        CASE
            WHEN potassium_max IS NULL THEN NULL
            WHEN potassium_min < 3.0 THEN 3
            WHEN potassium_max >= 5.0 THEN 3
            WHEN potassium_max >= 3.0
                AND potassium_max < 5.0
                AND potassium_min >= 3.0
                AND potassium_min < 5.0
            THEN 0
        END AS potassium_score,
        CASE
            WHEN sodium_max IS NULL THEN NULL
            WHEN sodium_min < 125 THEN 5
            WHEN sodium_max >= 145 THEN 1
            WHEN sodium_max >= 125
                AND sodium_max < 145
                AND sodium_min >= 125
                AND sodium_min < 145
            THEN 0
        END AS sodium_score,
        CASE
            WHEN bicarbonate_max IS NULL THEN NULL
            WHEN bicarbonate_min < 15.0 THEN 6
            WHEN bicarbonate_min < 20.0 THEN 3
            WHEN bicarbonate_max >= 20.0 AND bicarbonate_min >= 20.0
            THEN 0
        END AS bicarbonate_score,
        CASE
            WHEN bilirubin_max IS NULL THEN NULL
            WHEN bilirubin_max < 4.0 THEN 0
            WHEN bilirubin_max < 6.0 THEN 4
            WHEN bilirubin_max >= 6.0 THEN 9
        END AS bilirubin_score,
        CASE
            WHEN mingcs IS NULL THEN NULL
            WHEN mingcs < 3 THEN NULL
            WHEN mingcs < 6 THEN 26
            WHEN mingcs < 9 THEN 13
            WHEN mingcs < 11 THEN 7
            WHEN mingcs < 14 THEN 5
            WHEN mingcs >= 14 AND mingcs <= 15 THEN 0
        END AS gcs_score,
        CASE
            WHEN aids = 1 THEN 17
            WHEN hem = 1 THEN 10
            WHEN mets = 1 THEN 9
            ELSE 0
        END AS comorbidity_score,
        CASE
            WHEN admissiontype = 'ScheduledSurgical' THEN 0
            WHEN admissiontype = 'Medical' THEN 6
            WHEN admissiontype = 'UnscheduledSurgical' THEN 8
            ELSE NULL
        END AS admissiontype_score
    FROM cohort
)

SELECT
    subject_id, hadm_id, stay_id
    -- Combine all scores to get SAPS-II total
    -- Impute 0 if the score is missing
    , COALESCE(age_score, 0)
    + COALESCE(hr_score, 0)
    + COALESCE(sysbp_score, 0)
    + COALESCE(temp_score, 0)
    + COALESCE(pao2fio2_score, 0)
    + COALESCE(uo_score, 0)
    + COALESCE(bun_score, 0)
    + COALESCE(wbc_score, 0)
    + COALESCE(potassium_score, 0)
    + COALESCE(sodium_score, 0)
    + COALESCE(bicarbonate_score, 0)
    + COALESCE(bilirubin_score, 0)
    + COALESCE(gcs_score, 0)
    + COALESCE(comorbidity_score, 0)
    + COALESCE(admissiontype_score, 0)
    AS sapsii
    -- DEVIATION from mimic-code: COALESCE component scores to 0.
    -- See sofa-24h.sql for rationale.
    , COALESCE(age_score, 0) AS age_score
    , COALESCE(hr_score, 0) AS hr_score
    , COALESCE(sysbp_score, 0) AS sysbp_score
    , COALESCE(temp_score, 0) AS temp_score
    , COALESCE(pao2fio2_score, 0) AS pao2fio2_score
    , COALESCE(uo_score, 0) AS uo_score
    , COALESCE(bun_score, 0) AS bun_score
    , COALESCE(wbc_score, 0) AS wbc_score
    , COALESCE(potassium_score, 0) AS potassium_score
    , COALESCE(sodium_score, 0) AS sodium_score
    , COALESCE(bicarbonate_score, 0) AS bicarbonate_score
    , COALESCE(bilirubin_score, 0) AS bilirubin_score
    , COALESCE(gcs_score, 0) AS gcs_score
    , COALESCE(comorbidity_score, 0) AS comorbidity_score
    , COALESCE(admissiontype_score, 0) AS admissiontype_score
FROM scorecomp
;

Read the full file on GitHub · 488 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 488 lines · 0 tokens per session scan A 66f240979ebf

Subscribe to this mod's changes

mimic-sapsii-24h-raw is a skill published in the GitHub repository hannesill/m4 (43 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,395 tokens. A static security scan graded it A with 0 findings. It is 100% identical to mimic-apsiii-24h-raw, differing in 1,337 lines, and is treated as a copy.

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