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Updated: Jan 18, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Nomogram for Risk Assessment of Pressure Injury in Hospitalized Patients: A Retrospective Case-control Study
Hongyan Zhang1, Qian Su2, Lian Chen3,4
1Department of Nursing, Gansu Provincial Hospital, Lanzhou City, Gansu Province, China.
Objective:
To develop and validate a nomogram model for pressure injury (PI) risk assessment in hospitalized patients, and provide a visual tool for hospital-acquired pressure injury (HAPI) risk assessment.
Methods:
This retrospective case-control study included 973 patients between January 2021 and December 2022 from 2 hospitals: the First Hospital of Lanzhou University and the Gansu Provincial Hospital. Patients were randomly divided into the development cohort (n=682) and validation cohort (n=291) according to a ratio of 7:3. In the development cohort, univariate and multivariate logistic regression analyses were used to identify PI risk factors of the nomogram. The nomogram model was validated by the concordance index (C-index), receiver operating characteristic curve analysis (ROC curve), and calibration curves with the Hosmer-Lemeshow goodness-of-fit test. The clinical utility of the model was assessed through decision curve analysis (DCA).
Results:
The nomogram model comprised 9 variables: age, length of hospital stay, alcohol consumption, self-care ability, changes in bowel status, Braden score, indwelling nasogastric tube, taking sedative analgesics, and taking diuretic drugs. The area under the ROC curve (AUC) was 0.862. In the validation cohort, the nomogram still had good discrimination (AUC: 0.871). The calibration curve and DCA showed that the risk assessment nomogram had good consistency and clinical utility.
Conclusions:
A high-performance nomogram model was established, which can accurately assess the risk of PI among hospitalized patients. Notably, this nomogram provides an accurate visual tool to nursing staff and caregivers for risk assessment, early intervention, and risk management of HAPI.
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