Evidence map›Paper›PMID 40448024›Full record

ArticleBMC infectious diseases2025

Construction and validation of a prediction model for short-term mortality risk in elderly patients with sepsis: a retrospective study.

Qingqing Li, Xueqiang Zhang, Li Wu, Guiping Xu

Abstract readValidation Study
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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2citing papers in PubMed, 1 pooled it
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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

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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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Qingqing LiDepartment of Anesthesiology, People's Hospital of Xinjiang Uygur Autonomous Region,Xinjiang Clinical Research Center for Anesthesia Management, Urumqi, 830001, China.
Xueqiang ZhangDepartment of Anesthesiology, Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, 830000, China.
Li WuDepartment of Anesthesiology, People's Hospital of Xinjiang Uygur Autonomous Region,Xinjiang Clinical Research Center for Anesthesia Management, Urumqi, 830001, China.
Guiping XuDepartment of Anesthesiology, People's Hospital of Xinjiang Uygur Autonomous Region,Xinjiang Clinical Research Center for Anesthesia Management, Urumqi, 830001, China. xuguipingmzk@163.com.

Funding

Autonomous region key research and development project No. 2022B03009-4
6 · The paper itself

Abstract

backgroundThis study aims to investigate the risk factors affecting short-term mortality in elderly patients with sepsis and a nomogram model was constructed.

methodsA retrospective collection was performed on clinical data of 1116 elderly patients (≥ 65 years) with sepsis hospitalized from January 2014 to December 2023. Patients were divided based on 30-day mortality: death group (392 cases) and survival group (724 cases). Differences in various biochemical indicators were compared, and Cox regression analysis was used to identify independent risk factors. The model's performance was evaluated using receiver operating characteristics (ROC) and Kaplan-Meier curves.

resultsUnivariate and multivariate Cox survival analysis were utilized to explore the risk factors for short-term mortality in elderly patients with sepsis. The analysis exhibited a significant association of age, procalcitonin, antiarrhythmic drugs, vasopressors, and albumin with patient survival time. Group differences in vitamin C positivity were observed, but this variable was not included in the prediction model. The nomogram model, demonstrated high diagnostic accuracy (C-index 0.790). Patients were divided into the high-risk group and the low-risk group based on the model's thresholds, showing significantly shorter survival times for the high-risk group.

conclusionIncreased age, use of antiarrhythmic drugs and vasopressors are independent risk factors for mortality in elderly patients with sepsis, whereas high albumin levels are protective factors. The developed nomogram provides an effective tool for predicting short-term mortality in this patient population.

Indexed as

SepsisAgedAged, 80 and overAge FactorsFemaleHumansKaplan-Meier EstimateMaleNomogramsProportional Hazards ModelsRetrospective StudiesRisk FactorsROC CurveElderlyNomogramRisk factorsSepsis

Identifiers

PMID40448024
PMCPMC12125762

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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.