Evidence map›Paper›PMID 42046044›Full record

ArticleBMC infectious diseases2026

Predicting 28-day and 90-day mortality in microbiologically-confirmed sepsis: a retrospective cohort study.

Zhu Lin, Nahui Li, Haisheng Liu, Hua Xu, Yanfei Zhu, Ning Luo, Shuying Yang

Abstract read
In one paragraph

Article in BMC infectious diseases, 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

7 authors.

Zhu LinDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China.
Nahui LiDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China.
Haisheng LiuDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China.
Hua XuDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China.
Yanfei ZhuDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China.
Ning LuoDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China. loloningning@163.com.
Shuying YangDepartment of Intensive Care Unit, Key Laboratory for Critical Care Medicine of the Ministry of Health, Emergency Medicine Research Institute, Tianjin First Central Hospital, Tianjin, 300192, China. ysy13662111090@163.com.

Funding

Tianjin Health Science and Technology Project TJWJ2022XK023Tianjin Medical Construction of Key Discipline (Specialty) Funded Project TJYXZDXK-013ATianjin Science and Technology Plan Project 21JCYBJC00090
6 · The paper itself

Abstract

objectiveSepsis patients with confirmed microbial infection represent a clinically important subgroup requiring specialized prognostic tools, though existing models fail to address their unique characteristics. SELECTING AND

methodsA retrospective analysis was conducted using the MIMIC-IV repository, selecting adult sepsis cases fulfilling sepsis-3.0 criteria with microbiological confirmation. Primary endpoints were 28- and 90-day all-cause mortality. Analytical approaches included nonparametric comparative tests, stepwise survival regression modeling, and comprehensive sensitivity evaluations.

resultsOur analysis encompassed 5,694 patients with culture-confirmed sepsis, demonstrating mortality rates of 15.8% (28-day) and 17.5% (90-day), respectively. Multivariable regression identified significant mortality predictors (all p < 0.001), including age, respiratory rate, hemoglobin, lactate levels, vasoactive drug use, CCI, LODS score, SIRS score, SAPS III, and OASIS. These variables were incorporated into model 2 and model 4, both of which demonstrated strong predictive performance for 28-day and 90-day mortality with model 2 (AUC: 0.798; specificity: 0.765; sensitivity: 0.678) and model 4 (AUC: 0.795; specificity: 0.730; sensitivity: 0.708). Both models demonstrated consistent predictive performance in subgroup analyses. However, no significant association was observed between infection site, pathogenic microorganism type, and patient prognosis (p ≥ 0.05).

conclusionThese findings establish clinically applicable risk stratification tools specifically designed for culture-positive sepsis, potentially enabling more tailored therapeutic decisions for this vulnerable patient cohort. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

SepsisAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesSurvival AnalysisMicroorganismsModelPrognosisSepsis

Identifiers

PMID42046044
PMCPMC13262308

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.