Ampornpan Theeranut1, Suchada Ninbanphot2, Panita Limpawattana3. 1. Faculty of Nursing and Research and Training Center for Enhancing Quality of Life of Working Age People, Khon Kaen University, Khon Kaen, Thailand. 2. Intensive Care Unit of Internal Medicine, Faculty of Medicine, Khon Kaen University, Thailand. 3. Division of Geriatric Medicine, Department of Internal Medicine, Faculty of Medicine, Khon Kaen University, Thailand.
Abstract
BACKGROUND: Critically ill patients are at a higher risk of developing pressure ulcers (PUs) than non-critically ill patients. Tools that aid in the early identification of those who are most at risk of PUs could help health care providers deliver early interventions and reduce unfavourable outcomes. AIMS: To compare the validity of four PU risk tools (the Braden scale, the Braden [ALB] scale, the CALCULATE, and the COMHON index) and to demonstrate the optimal cut-off points for each tool in critically ill patients. DESIGN: This was a prospective descriptive study. METHOD: This study was conducted in the intensive care units (ICUs) of a tertiary care hospital in Thailand from January to April 2019. Baseline characteristics were collected at admission to the ICUs. Skin assessment was evaluated every 24 hours. PU assessment scores were collected every 72 hours. Receiver operating characteristic curves were used to compare the performance of the tests in predicting PUs. RESULTS: A total of 288 patients were recruited. The incidence of PUs was 11.1%. The Braden (ALB) scale performed the best based on the area under the receiver operating characteristic curves (area under curve 0.74), followed by the CALCULATE (area under curve 0.71), the Braden (area under curve 0.67) scale, and the COMHON (area under curve 0.61) index. At the optimal cut-off point, the Braden (ALB) scale (≤13)) and the CALCULATE (≥3) were similar in terms of performance with an area under the curve of 0.69. CONCLUSION: The Braden (ALB) performed the best at predicting PU development in ICU patients. RELEVANCE TO CLINICAL PRACTICE: The validity of all four PU risk tools was limited in Thai patients. The scales should thus be used in conjunction with clinical judgement to provide optimal outcomes. The development of better assessment tools for the prediction of PUs is required.
BACKGROUND:Critically illpatients are at a higher risk of developing pressure ulcers (PUs) than non-critically illpatients. Tools that aid in the early identification of those who are most at risk of PUs could help health care providers deliver early interventions and reduce unfavourable outcomes. AIMS: To compare the validity of four PU risk tools (the Braden scale, the Braden [ALB] scale, the CALCULATE, and the COMHON index) and to demonstrate the optimal cut-off points for each tool in critically illpatients. DESIGN: This was a prospective descriptive study. METHOD: This study was conducted in the intensive care units (ICUs) of a tertiary care hospital in Thailand from January to April 2019. Baseline characteristics were collected at admission to the ICUs. Skin assessment was evaluated every 24 hours. PU assessment scores were collected every 72 hours. Receiver operating characteristic curves were used to compare the performance of the tests in predicting PUs. RESULTS: A total of 288 patients were recruited. The incidence of PUs was 11.1%. The Braden (ALB) scale performed the best based on the area under the receiver operating characteristic curves (area under curve 0.74), followed by the CALCULATE (area under curve 0.71), the Braden (area under curve 0.67) scale, and the COMHON (area under curve 0.61) index. At the optimal cut-off point, the Braden (ALB) scale (≤13)) and the CALCULATE (≥3) were similar in terms of performance with an area under the curve of 0.69. CONCLUSION: The Braden (ALB) performed the best at predicting PU development in ICU patients. RELEVANCE TO CLINICAL PRACTICE: The validity of all four PU risk tools was limited in Thai patients. The scales should thus be used in conjunction with clinical judgement to provide optimal outcomes. The development of better assessment tools for the prediction of PUs is required.