A Nomogram Prediction of Pressure Injury in Critical Ill Patients: A Retrospective Cohort Study

Overview

Journal Int Wound J

Specialties Emergency Medicine
Orthopedics

Date 2021 Sep 3

PMID 34477312

Citations 5

Authors

Wen Xu

Xueshu Yu

Hao Jiang

Yumin Wang

Yincai Ye

Affiliations

Soon will be listed here.

Abstract

Pressure injury (PI) is still a significant public health problem to be solved. Accurate prediction can lead to timely prophylaxis and therapy. However, the currently used Braden score shows insufficient predictive validity. We aimed to develop a nomogram to predict PI development in critically ill patients. We extracted data from Medical Information Mart for Intensive Care-IV v1.0. Variable selection was based on univariate logistic regression and all-subset regression. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the nomogram and Braden score. Decision curve analysis (DCA) was performed to identify and compare the clinical usefulness between the nomogram model and Braden score. We have developed a novel and practical nomogram that accurately predicts pressure ulcers. The AUC of the new model was better than that of the Braden score (P < .001). DCA showed that the nomogram model had a better net benefit than the Braden score at any given threshold. This finding needs to be confirmed by external validation as well as multicentre prospective studies.

Citing Articles

A nomogram to predict the risk of surgery-related pressure ulcers in patients undergoing cardiovascular surgery.

Wei X, Xu X, Chen Y J Int Med Res. 2024; 52(2):3000605241233149.

PMID: 38422046 PMC: 10906061. DOI: 10.1177/03000605241233149.

Risk factors and the nomogram model for intraoperatively acquired pressure injuries in children with brain tumours: A retrospective study.

Qu H, Tang X, Zeng W, Fu S, Zhou R, Mou S Int Wound J. 2023; 20(6):2250-2259.

PMID: 36780892 PMC: 10333024. DOI: 10.1111/iwj.14106.

Development and validation of a nomogram for predicting the risk of pressure injury in adult patients undergoing abdominal surgery.

Feng X, Wang M, Zhang Y, Liu Q, Guo M, Liang H Int J Nurs Sci. 2022; 9(4):438-444.

PMID: 36285073 PMC: 9587389. DOI: 10.1016/j.ijnss.2022.09.010.

Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.

Xu J, Chen D, Deng X, Pan X, Chen Y, Zhuang X Int Wound J. 2022; 19(7):1637-1649.

PMID: 35077000 PMC: 9615270. DOI: 10.1111/iwj.13764.

A nomogram prediction of pressure injury in critical ill patients: A retrospective cohort study.

Xu W, Yu X, Jiang H, Wang Y, Ye Y Int Wound J. 2021; 19(4):826-833.

PMID: 34477312 PMC: 9013588. DOI: 10.1111/iwj.13680.

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