Clinical and Epidemiological Characteristics of Rhabdomyolysis: A Retrospective Study.


Journal

International journal of clinical practice
ISSN: 1742-1241
Titre abrégé: Int J Clin Pract
Pays: India
ID NLM: 9712381

Informations de publication

Date de publication:
2023
Historique:
received: 07 04 2023
revised: 11 09 2023
accepted: 23 09 2023
medline: 1 11 2023
pubmed: 9 10 2023
entrez: 9 10 2023
Statut: epublish

Résumé

Rhabdomyolysis (RM) refers to a clinical syndrome in which muscle cells are damaged by various causes and the clinical manifestations are mainly muscle pain, weakness, and dark urine. Acute kidney injury (AKI) is a serious complication of RM with complex mechanisms and high mortality. Therefore, understanding the pathogenesis and clinical manifestations, early diagnosis and treatment of RM are crucial to improve its prognosis. Analysis of medical records of RM patients admitted to Tianjin Medical University General Hospital from October 2019 to October 2022. Statistical software SPSS 25.0 was used to analyze the data. The risk factors of RM-complicated AKI were analyzed by logistic regression. The receiver operating characteristic (ROC) curve was plotted, the area under the curve (AUC) was calculated, and the optimal cutoff value was determined by the Youden index. Among the 71 patients, the median age of the patients was 53.0 (30.0, 71.0) years and was 2.5 times higher in men than in women. Infection was the most common etiology. History of alcohol consumption, CK, and creatinine were independent influencing factors for AKI due to RM. Logistic regression analysis showed that CK combined with creatinine had a better predictive value than the single index. Our study revealed the clinical and laboratory characteristics of RM in the population attending the Tianjin Medical University General Hospital in the last three years, which is a reference for future multicenter, prospective studies.

Sections du résumé

Background UNASSIGNED
Rhabdomyolysis (RM) refers to a clinical syndrome in which muscle cells are damaged by various causes and the clinical manifestations are mainly muscle pain, weakness, and dark urine. Acute kidney injury (AKI) is a serious complication of RM with complex mechanisms and high mortality. Therefore, understanding the pathogenesis and clinical manifestations, early diagnosis and treatment of RM are crucial to improve its prognosis.
Method UNASSIGNED
Analysis of medical records of RM patients admitted to Tianjin Medical University General Hospital from October 2019 to October 2022. Statistical software SPSS 25.0 was used to analyze the data. The risk factors of RM-complicated AKI were analyzed by logistic regression. The receiver operating characteristic (ROC) curve was plotted, the area under the curve (AUC) was calculated, and the optimal cutoff value was determined by the Youden index.
Result UNASSIGNED
Among the 71 patients, the median age of the patients was 53.0 (30.0, 71.0) years and was 2.5 times higher in men than in women. Infection was the most common etiology. History of alcohol consumption, CK, and creatinine were independent influencing factors for AKI due to RM. Logistic regression analysis showed that CK combined with creatinine had a better predictive value than the single index.
Conclusion UNASSIGNED
Our study revealed the clinical and laboratory characteristics of RM in the population attending the Tianjin Medical University General Hospital in the last three years, which is a reference for future multicenter, prospective studies.

Identifiants

pubmed: 37808625
doi: 10.1155/2023/6396576
pmc: PMC10558265
doi:

Substances chimiques

Creatinine AYI8EX34EU

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6396576

Informations de copyright

Copyright © 2023 Keke Sun et al.

Déclaration de conflit d'intérêts

The authors declare that they have no conflicts of interest.

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Auteurs

Keke Sun (K)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Zhenhua Shi (Z)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Department of Intensive Care Unit, PLA 983rd Hospital, Tianjin, China.

Yushanjiang Abudureheman (Y)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Department of Critical Care Medicine, Hotan District People's Hospital, Xinjiang, China.

Qihui Liu (Q)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Yibo Zhao (Y)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Xiangqun Zhang (X)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Qi Lv (Q)

Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.

Yan Zhang (Y)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Songtao Shou (S)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Heng Jin (H)

Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

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Classifications MeSH