Evidence map›Paper›PMID 37668842›Full record

ArticleAging clinical and experimental research2023

Predictive nomogram for in-hospital mortality among older patients with intra-abdominal sepsis incorporating skeletal muscle mass.

Qiujing Li, Na Shang, Tiecheng Yang, Qian Gao, Shubin Guo

Abstract read
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Article in Aging clinical and experimental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

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5citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

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

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Qiujing Li *Department of Emergency Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Na Shang *Department of Emergency Medicine, Capital Medical University of Rehabilitation Medicine, Beijing Bo'Ai Hospital, China Rehabilitation Research Center, Beijing, China.
Tiecheng YangDepartment of Emergency Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Qian GaoDepartment of Emergency Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Shubin GuoDepartment of Emergency Medicine, Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing Chao-Yang Hospital, Capital Medical University, No. 8, South Road of Worker's Stadium, BeijingChaoyang District, Beijing, 100020, China. shubin007@yeah.net.ORCID http://orcid.org/0000-0001-8870-4587

Funding

Open Project of the Beijing Key Laboratory 2020XFN-KFKT-02
6 · The paper itself

Abstract

backgroundStudies on prognostic factors for older patients with intra-abdominal sepsis are scarce, and the association between skeletal muscle mass and prognosis among such patients remains unclear.

aimsTo develop a nomogram to predict in-hospital mortality among older patients with intra-abdominal sepsis.

methodsOlder patients with intra-abdominal sepsis were prospectively recruited. Their demographics, clinical features, laboratory results, abdominal computed tomography-derived muscle mass, and in-hospital mortality were recorded. The predictors of mortality were selected via least absolute shrinkage and selection operator and multivariable logistic regression analyses, and a nomogram was developed. The nomogram was assessed and compared with Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, and Simplified Acute Physiology Score II.

resultsIn total, 464 patients were included, of whom 104 (22.4%) died. Six independent risk factors (skeletal muscle index, cognitive impairment, frailty, heart rate, red blood cell distribution width, and blood urea nitrogen) were incorporated into the nomogram. The Hosmer-Lemeshow goodness-of-fit test and calibration plot revealed a good consistency between the predicted and observed probabilities. The area under the receiver operating characteristic curve was 0.875 (95% confidence interval = 0.838-0.912), which was significantly higher than those of commonly used scoring systems. The decision curve analysis indicated the nomogram had good predictive performance. DISCUSSION: Our nomogram, which is predictive of in-hospital mortality among older patients with intra-abdominal sepsis, incorporates muscle mass, a factor that warrants consideration by clinicians. The model has a high prognostic ability and might be applied in clinical practice after external validation.

Indexed as

NomogramsSepsisBlood Urea NitrogenHospital MortalityHumansMuscle, SkeletalRetrospective StudiesIntra-abdominal sepsisMortalityNomogramOlder adultsSarcopenia

Identifiers

PMID37668842
PMCPMC10628031

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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.