A Predictive Nomogram for In-ICU Deterioration of Stage 1 Pressure Injuries: A Retrospective Study

BackgroundPreventing Stage 1 pressure injuries (PIs) from worsening in the ICU is a key clinical challenge. Early prediction of high-risk patients enables targeted prevention. We aimed to develop a model for this progression using admission data. MethodsIn this retrospective cohort study, eligible ICU patients with Stage 1 pressure injuries were randomly allocated into training (70%) and validation (30%) sets. Predictors were selected using LASSO regression. A multivariable logistic regression model was constructed and visualized as a nomogram. Model performance was evaluated by discrimination (AUC), calibration, and clinical utility (decision curve analysis). ResultsA total of 278 patients were randomly divided into training (n=195) and validation (n=83) sets. LASSO regression identified four independent predictors: diabetes (OR: 3.266; 95% CI: 1.451-7.352), maximum norepinephrine dose (OR: 13.032; 95% CI: 1.212-140.137), use of pneumatic compression pumps (OR: 3.308; 95% CI: 1.444-7.579), and albumin level at ICU admission (OR: 0.836 per unit increase; 95% CI: 0.777-0.900). The nomogram demonstrated excellent discrimination, with an AUC of 0.810 (95% CI: 0.748-0.872) in the training set and 0.805 (95% CI: 0.696-0.914) in the validation set. Good calibration and clinical utility were confirmed. ConclusionsA nomogram incorporating four readily available factors at ICU admission effectively predicts the risk of Stage 1 PI progression. This tool may aid early risk stratification and guide precise preventive measures.