Development of a Nomogram for Predicting the Risk of Hospital-Acquired Pressure Injuries in Patients in the Cardiovascular Intensive Care Unit

Author:

Li Hao-yue,Zhang Yan,Shui Xiao-lan,Che Zhi-gang,Liu Qi-fan,Guo Shan-shan

Abstract

AbstractPurposeHospital-acquired pressure injuries (HAPIs) increase the medical burden of patients in the cardiovascular intensive care unit (CCU). Thus, identification of CCU patients with a risk for HAPIs is important. To establish a nomogram model for predicting the occurrence of HAPIs in patients in the CCU.MethodsThis was a retrospective cohort study in patients in the CCU at our hospital who developed HAPIs between January 2023 and June 2023. Patient data were extracted from the hospital’s information management system. Risk factors for HAPIs were identified using univariate and multivariate logistic regression analyses and the screened indicators were integrated into a nomogram. The effectiveness of the nomogram was evaluated and verified using receiver operating characteristic curve and decision curve analysis (DCA).ResultsIn this study, a total of 161 patients were enrolled. Univariate logistic regression analysis showed that vasopressor use (OR=2.51, 95%CI=1.24–5.09,p=.010) and NT-proBNP (OR=2.92, 95%CI=1.45–5.92,p=.003), lactic acid (OR=9.43, 95%CI=4.15–21.41,p<.000), procalcitonin (OR=1.37, 95%CI=1.07–1.75,p=.012), D-dimer (OR=1.16, 95%CI=1.05–1.28,p= .004), and albumin (OR=0.88, 95%CI=0.81–0.95,p=.002) levels were independent risk factors for HAPIs. Multivariate logistic regression analysis showed that vasopressor use (OR=3.05, 95%CI=1.20–7.73,p=.019) and lactic acid (OR=12.05, 95%Cl=4.13–35.21,p<.000), procalcitonin (OR=1.30, 95%Cl=1.01–1.69,p=.043) and albumin (OR=0.82, 95%Cl=0.73–0.93,p=.002) levels were independent risk factors for HAPIs. The nomogram was well-calibrated and showed good discriminative ability (AUC=.87). The DCA showed a better net benefit, and the results were confirmed within the validation cohort.ConclusionThe nomogram model developed in this study showed good predictability and can identify patients at risk of developing HAPIs and aid the formulation of targeted interventions.

Publisher

Cold Spring Harbor Laboratory

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