Evidence map›Paper›PMID 36134327›Full record

ArticleInternational journal of clinical practice2022

A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit.

Jing Qi, Qin Xie, Zhenzhou Li, Chuanzheng Sun

Abstract read
In one paragraph

Article in International journal of clinical practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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

4 authors.

Jing QiDepartment of Emergency, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-9558-6742
Qin XieDepartment of Emergency, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0003-2008-5534
Zhenzhou LiDepartment of Emergency, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.
Chuanzheng SunDepartment of Emergency, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0003-2116-0233

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Trauma has a high incidence and mortality worldwide, and sepsis is one of the main causes of mortality in trauma patients. Therefore, it is essential to identify the risk factors of in-hospital mortality for trauma patients with sepsis. Methods: Data were extracted from the Medical Information Mart for Intensive Care III database and divided into a training set and internal validation set, and another Chinese dataset was used as external validation set. Then, risk factors were estimated using univariate and multivariate logistic regression analyses in the training set. Finally, a nomogram was created to predict the probability of in-hospital mortality for trauma patients with sepsis. Results: A total of 503 patients were enrolled in our study (335 in the training set and 168 in the validation set). Multivariate logistic regression analysis revealed that age (1.047 [1.025-1.071]), respiratory rate (1.258 [1.135-1.394]), PTT (1.026 [1.008-1.044]), ventilation (6.703 [1.528-29.408]), and vasopressor use (3.682 [1.502-9.025]) were independent factors associated with in-hospital mortality. The nomogram for trauma-related sepsis predicted in-hospital mortality with AUC values of 0.8939 in the training set, 0.8200 in the internal validation set, and 0.7779 in the external validation set. Conclusions: The new nomogram has a well predicted value for in-hospital mortality for patients with trauma and sepsis in intensive care units.

Indexed as

NomogramsSepsisHospital MortalityHumansIntensive Care UnitsRetrospective Studies

Identifiers

PMID36134327
PMCPMC9481405

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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.