Evidence map›Paper›PMID 42092945›Full record

Observational studyCritical care (London, England)2026

Impact of the updated SOFA-2 score on sepsis diagnosis and prognosis: a retrospective multicenter cohort study.

Haibo Zhu, Peirong Li, Bing Wang, Hao Fu, Yehan Guo, Ziyi Han, Shuojing Huang, Yujie Xie, Jun He, Shixiang Zheng and 1 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Haibo Zhu *Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Peirong Li *Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Bing Wang *Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Hao Fu *Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Yehan GuoDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Ziyi HanDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Shuojing HuangDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Yujie XieDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China.
Jun HeDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China. hjbiocc@fjmu.edu.cn.
Shixiang ZhengDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China. jeromesuper@126.com.
Xiaopei ShenDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, University Town Fuzhou, 1st Xueyuan Road, Fuzhou, Fujian, 350122, China. xshen@fjmu.edu.cn.

Funding

Fujian Key Laboratory of Medical Bioinformatics Open Fund FKLMB-202002Fujian Science and Technology Innovation Joint Fund Project 2020Y9035Natural Science Foundation of Fujian Province 2023J01095Startup Fund for Scientific Research, Fujian Medical University 2022QH2002Startup Fund for Scientific Research, Fujian Medical University 2024QH1009The Natural Science Foundation of Fujian Province 2023J01321
6 · The paper itself

Abstract

backgroundThe Sepsis-3 criteria operationalized organ dysfunction using the original Sequential Organ Failure Assessment (SOFA-1) score, which was updated to SOFA-2 in October 2025 to align with modern intensive care unit (ICU) practices. However, the impact of adopting SOFA-2 for sepsis detection under the Sepsis-3 criteria has not yet been evaluated.

methodsWe conducted a retrospective multicenter cohort study using three large-scale ICU databases from the United States and the Netherlands. Adult patients with suspected infection within 72 h of ICU admission were included. Sepsis was independently identified according to Sepsis-3 criteria, utilizing either the SOFA-1 or SOFA-2 score. We systematically compared diagnostic concordance, the timeliness of sepsis detection, clinical outcomes and predictive performance of prognostic models between the two scoring systems. The primary outcome was ICU mortality, while secondary outcomes included hospital mortality and 28-day survival.

resultsThe study cohort comprised 74,615 adult patients with suspected infection. The diagnostic concordance of sepsis between SOFA-1 and SOFA-2 reached 89.62%. However, SOFA-1 and SOFA-2 uniquely identified an additional 3.54% and 6.84% of patients as having sepsis, respectively. The diagnostic discrepancies were primarily attributable to updates in respiratory and renal scoring criteria. ICU mortality was highest among the Concordant Positive group (15.63%). Notably, both discordant groups exhibited substantial mortality (SOFA-1 Only: 8.31%; SOFA-2 Only: 9.23%), both of which were significantly higher than those of patients not classified as having sepsis by either score (6.71%; P = .002 and P = 2.87 × 10

conclusionsSOFA-1 and SOFA-2 showed high concordance in sepsis detection, yet each identified distinct patient subgroups with significant mortality. A transitional strategy utilizing both SOFA-1 and SOFA-2 is advised until updated expert-validated sepsis criteria are established.

Indexed as

Organ Dysfunction ScoresSepsisAgedCohort StudiesFemaleHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedNetherlandsPrognosisRetrospective StudiesROC CurveUnited StatesIntensive Care UnitsPrognostic ModelsSepsisSepsis-3Sequential Organ Failure AssessmentSOFA-2

Identifiers

PMID42092945
PMCPMC13312726

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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.