Evidence map›Paper›PMID 41959822›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Evaluation of SOFA-2 Score Performance Across Demographic Subgroups: An External Validation Study Using MIMIC-IV.

Jacob Ellen, Sicheng Hao, Catherine A Gao, Maria Del Pilar Arias, Martin Viola, An-Kwok Ian Wong, Heather Mattie, William Parker, Cristina Haidau, João Matos and 2 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jacob EllenHarvard Medical School, 25 Shattuck Street, Boston, MA 02108, USA.ORCID 0000-0001-5716-1444
Sicheng HaoLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Catherine A GaoDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0001-5576-3943
Maria Del Pilar AriasPICU, Ricardo Gutierrez Children's Hospital; Argentine Society of Intensive Care, SATI-Q Program.
Martin ViolaHarvard Medical School, 25 Shattuck Street, Boston, MA 02108, USA.ORCID 0000-0003-2941-5122
An-Kwok Ian WongDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, United States.
Heather MattieDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
William ParkerDepartment of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, USA.
Cristina HaidauDepartment of Computer Science, Northeastern Illinois University, Chicago, IL, USA.
João MatosCentre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.
Renato Carneiro de Freitas ChavesLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Leo Anthony CeliLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts.ORCID 0000-0001-6712-6626

Funding

Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AIOT2OD032701 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI BIHORAC, AZRA, CLERMONT, GILLES · 2022 to 2025
$24.6M
MUST Data Science Research Hub (MUDSReH) - Democratized Trusted Research Environment (dTRE)U54TW012043 · FIC · MBARARA UNIVERSITY/SCIENCE/ TECHNOLOGY · PI Leo Anthony G Celi, Jessica Elizabeth Haberer · 2021 to 2026
$6.9M
Improving the efficiency and equity of critical care allocation during a crisis with place-based disadvantage indicesR01LM014263 · NLM · UNIVERSITY OF CHICAGO · PI William F Parker · 2023 to 2026
$2.0M
Implementation partner-guided strategy to promote accuracy in ICU prognosticationR01HL176569 · NHLBI · DUKE UNIVERSITY · PI Deepshikha Charan Ashana, Christopher Ethan Cox · 2025 to 2026
$1.4M
Multiomic, mass spectrometry-based analysis of dried blood for deep phenotyping of sepsisR33GM146142 · NIGMS · DUKE UNIVERSITY · PI FOSTER, MATTHEW WOLF, MCMAHON, TIMOTHY J · 2024 to 2025
$1.4M
Overcoming inequities in Pulse oximetry Through clinical InformatiCs (OPTIC)R01HL177003 · NHLBI · DUKE UNIVERSITY · PI An-Kwok I Wong · 2025 to 2026
$1.4M
Machine learning to predict cure in severe pneumonia episodesK23HL169815 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Catherine A. Gao · 2024 to 2026
$501k
FIC NIH HHS U54 TW012043NHLBI NIH HHS K23 HL169815NHLBI NIH HHS R01 HL176569NHLBI NIH HHS R01 HL177003NIGMS NIH HHS R33 GM146142NIH HHS OT2 OD032701NLM NIH HHS R01 LM014263
6 · The paper itself

Abstract

The Sequential Organ Failure Assessment (SOFA)-2 score was recently validated for ICU mortality prediction across more than 3 million admissions but was not evaluated across demographic subgroups. We assessed the discrimination and calibration of the SOFA-2 score for ICU mortality across subgroups defined by age, sex, race and ethnicity, primary language, and insurance status. We conducted a retrospective cohort study of adult patients (aged 18 years or older) admitted to ICUs at Beth Israel Deaconess Medical Center between 2008 and 2022 (MIMIC-IV, version 3.1), selecting the first ICU admission per patient. First-day SOFA-2 scores (range, 0-24) were calculated using worst recorded values across 6 organ systems. Discrimination was assessed using AUROC, calibration using intercepts and slopes, and subgroup differences using bootstrap resampling. Among 64,015 ICU admissions (median age, 66 years [IQR, 54-78]; 56.1% male; 66.1% White), overall ICU mortality was 7.2% (n=4,596). Overall AUROC was acceptable at 0.77 (95% CI, 0.76-0.77). Notably, discrimination declined significantly with age: AUROC was 0.85 (95% CI, 0.83-0.87) for ages 18-44 and 0.72 (95% CI, 0.70-0.73) for ages 75 and older (difference in AUROC, -0.14; 95% CI, -0.16 to -0.11), with systematic underprediction of mortality in older patients (calibration intercept, 0.39). Discrimination was also significantly lower among non-English speakers (difference in AUROC, -0.04; 95% CI, -0.07 to -0.01) but did not differ significantly across documented racial and ethnic groups. Patients with unknown race/ethnicity (14.3% of the cohort) had nearly double the overall mortality rate and poor calibration. SOFA-2 demonstrated good overall performance for ICU mortality prediction but with clinically meaningful variation across demographic subgroups, particularly a substantial decline in discrimination with advancing age. These findings underscore the need for routine equity evaluation of clinical prediction tools before widespread implementation.

Identifiers

PMID41959822
PMCPMC13060984

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.