Development of a nomogram for predicting nosocomial infections among patients after cardiac valve replacement surgery

Autor: Xue Yao, Na Li, Ranran Lu, Xujing Wang, Yujun Zhang, Shuhui Wang
Rok vydání: 2022
Předmět:
Zdroj: Journal of Clinical Nursing. 32:1466-1475
ISSN: 1365-2702
0962-1067
Popis: To construct a predictive nomogram of the risk of nosocomial infections among patients after cardiac valve replacement surgery.Nosocomial infections are a standout challenge that worsens the prognosis of patients after valve replacement surgery. However, studies on the nomogram of nosocomial infections in these patients have remained scarce.A retrospective cohort study.Patients (n = 720) following valve replacement surgery from 2018 to 2019 were selected. LASSO regression and multivariate logistic regression were utilised to ascertain predictors of nosocomial infections. The predictive performance of the nomogram was appraised by calibration and discrimination. Decision and impact curves were used to assess the clinical utility. Internal validation was implemented via 1000 bootstrap samples to mitigate overfitting. TRIPOD guidelines were used in this study.One hundred and fifty one patients (20.97%) experienced nosocomial infections following valve replacement surgery. Heart failure, preoperative anaemia, valve material, American Society of Anesthesiologists score ≥ IV, prolonged duration of surgery, duration of mechanical ventilation ≥ 24 h and indwelling nasogastric tube were predictors of nosocomial infections. Using these variables, we developed a predictive nomogram of the occurrence of nosocomial infections and the internal validation results demonstrated good discrimination and calibration of the nomogram. The clinical decision and impact curve revealed significant clinical utility.The present study constructed a nomogram for predicting the risk of nosocomial infections in patients following cardiac valve replacement surgery. This nomogram may strengthen the effective screening of patients at high risk of nosocomial infections.This risk warning tool can assist clinical staff in making decisions and providing individualised infection control measures for patients, which has a significant reference value for clinical practice.The data for this study were obtained from the hospital database, and the entire process of the study did not involve patient participation.
Databáze: OpenAIRE
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