首页 | 本学科首页   官方微博 | 高级检索  
     


Risk prediction models for the development of oral-mucosal pressure injuries in intubated patients in intensive care units: A prospective observational study
Affiliation:3862 Castle Point Road, Himrod, New York 14842, USA;STIK Muhammadiyah Pontianak, Indonesia
Abstract:PurposeOral-mucosal pressure injury (PI) is the most commonly encountered medical device-related PIs. This study was performed to identify risk factors and construct a risk prediction model for oral-mucosal PI development in intubated patients in the intensive care unit.MethodsThe study design was prospective, observational with medical record review. The inclusion criteria stipulated that 1) participants should be > 18 years of age, 2) there should be ETT use with holding methods including adhesive tape, gauze tying, and commercial devices. Data of 194 patient-days were analysed. The identification and validation of risk model development was performed using SPSS and the SciKit learn platform.ResultsThe risk prediction logistic models were composed of three factors (bite-block/airway, commercial ETT holder, and corticosteroid use) for lower oral-mucosal PI development and four factors (commercial ETT holder, vasopressor use, haematocrit, and serum albumin level) for upper oral-mucosal PI development among 10 significant input variables. The sensitivity and specificity for lower oral-mucosal PI development were 85.2% and 76.0%, respectively, and those for upper oral-mucosal PI development were 60.0% and 89.1%, respectively. Based on the results of the machine learning, the upper oral-mucosal PI development model had an accuracy of 79%, F1 score of 88%, precision of 86%, and recall of 91%.ConclusionsThe development of lower oral-mucosal PIs is affected by immobility-related factors and corticosteroid use, and that of upper oral-mucosal PIs by undernutrition-related factors and ETT holder use. The high sensitivities of the two logit models comprise important minimum data for positively predicting oral-mucosal PIs.
Keywords:Logistic model  Mucous membrane  Pressure ulcer  Risk factors  Machine learning
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号