Predictors and nomogram of in-hospital mortality in sepsis-induced myocardial injury: a retrospective cohort study.


Journal

BMC anesthesiology
ISSN: 1471-2253
Titre abrégé: BMC Anesthesiol
Pays: England
ID NLM: 100968535

Informations de publication

Date de publication:
07 07 2023
Historique:
received: 02 02 2023
accepted: 23 06 2023
medline: 10 7 2023
pubmed: 8 7 2023
entrez: 7 7 2023
Statut: epublish

Résumé

Sepsis-induced myocardial injury (SIMI) is a common organ dysfunction and is associated with higher mortality in patients with sepsis. We aim to construct a nomogram prediction model to assess the 28-day mortality in patients with SIMI. . We retrospectively extracted data from Medical Information Mart for Intensive Care (MIMIC-IV) open-source clinical database. SIMI was defined by Troponin T (higher than the 99th percentile of upper reference limit value) and patients with cardiovascular disease were excluded. A prediction model was constructed in the training cohort by backward stepwise Cox proportional hazards regression model. The concordance index (C-index), area under the receiver operating characteristics curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting and decision-curve analysis (DCA) were used to evaluate the nomogram. 1312 patients with sepsis were included in this study and 1037 (79%) of them presented with SIMI. The multivariate Cox regression analysis in all septic patients revealed that SIMI was independently associated with 28-day mortality of septic patients. The risk factors of diabetes, Apache II score, mechanical ventilation, vasoactive support, Troponin T and creatinine were included in the model and a nomogram was constructed based on the model. The C-index, AUC, NRI, IDI, calibration plotting and DCA showed that the performance of the nomogram was better than the single SOFA score and Troponin T. SIMI is related to the 28-day mortality of septic patients. The nomogram is a well-performed tool to predict accurately the 28-day mortality in patients with SIMI.

Sections du résumé

BACKGROUND
Sepsis-induced myocardial injury (SIMI) is a common organ dysfunction and is associated with higher mortality in patients with sepsis. We aim to construct a nomogram prediction model to assess the 28-day mortality in patients with SIMI. .
METHOD
We retrospectively extracted data from Medical Information Mart for Intensive Care (MIMIC-IV) open-source clinical database. SIMI was defined by Troponin T (higher than the 99th percentile of upper reference limit value) and patients with cardiovascular disease were excluded. A prediction model was constructed in the training cohort by backward stepwise Cox proportional hazards regression model. The concordance index (C-index), area under the receiver operating characteristics curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting and decision-curve analysis (DCA) were used to evaluate the nomogram.
RESULTS
1312 patients with sepsis were included in this study and 1037 (79%) of them presented with SIMI. The multivariate Cox regression analysis in all septic patients revealed that SIMI was independently associated with 28-day mortality of septic patients. The risk factors of diabetes, Apache II score, mechanical ventilation, vasoactive support, Troponin T and creatinine were included in the model and a nomogram was constructed based on the model. The C-index, AUC, NRI, IDI, calibration plotting and DCA showed that the performance of the nomogram was better than the single SOFA score and Troponin T.
CONCLUSION
SIMI is related to the 28-day mortality of septic patients. The nomogram is a well-performed tool to predict accurately the 28-day mortality in patients with SIMI.

Identifiants

pubmed: 37420185
doi: 10.1186/s12871-023-02189-8
pii: 10.1186/s12871-023-02189-8
pmc: PMC10327384
doi:

Substances chimiques

Troponin T 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

230

Informations de copyright

© 2023. The Author(s).

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Auteurs

Kai-Zhi Xu (KZ)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China.

Ping Xu (P)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China.

Juan-Juan Li (JJ)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China.

A-Fang Zuo (AF)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China.

Shu-Bao Wang (SB)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China.

Fang Han (F)

Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310000, China. hf200212@163.com.

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