三级医院住院病人压力损伤评价布雷登量表最佳分界点的确定

Sook Hyun Park, hyeyeon Choi, Youn-Jung Son
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摘要

目的:本研究旨在建立用于压力性损伤评估的Braden量表的最佳分值,以检测韩国某三级医院住院患者的压力性损伤风险。方法:回顾性研究使用电子病历,时间为2022年1月至12月。研究共纳入654例患者。采用1:2倾向得分匹配法(PSM)对218例有压伤住院患者和436例无压伤住院患者进行分类分析,采用SPSS Version 26和R Machlt软件包程序进行广义估计方程求解。结果:Braden量表区分压力损伤的截止值为17分,ROC曲线下面积(AUC)为0.531(0.484 ~ 0.579)。敏感性为56.6%(45.5 ~ 67.7%),特异性为69.7%(66.0 ~ 73.4%)。布雷登量表的分界点为17分,区分入院时是否有压力性损伤(<i>p</i>< .03). 压伤组在压伤当日Braden评分为14分,除湿性外,其余各亚类评分均显著。结论:我们的研究结果表明,截断值为17是预测三级医院住院患者压力损伤风险的最佳值。未来的研究应评估不同临床环境下的最佳临界值。此外,有必要进行多中心大样本研究来验证17值在PI风险评估中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining Optimal Cut-off Score for the Braden Scale on Assessment of Pressure Injury for Tertiary Hospital Inpatients
Purpose : This study aims to establish an optimal cut-off score on the Braden scale for the assessment of pressure injury to detect pressure injury risks among inpatients in a South Korean tertiary hospital.Methods : This retrospective study used electronic medical records, from January to December 2022. A total of 654 patients were included in the study. Of these, 218 inpatients with pressure injuries and 436 without pressure injuries were classified and analyzed using 1:2 Propensity Score Matching (PSM), and the generalized estimating equation was performed using SPSS Version 26 and the R Machlt package program.Results : The cut-off value on the Braden scale for distinguishing pressure injury was 17 points, and the AUC (area under the ROC curve) was 0.531 (0.484–0.579). The sensitivity was 56.6% (45.5–67.7%) and the specificity was 69.7% (66.0– 73.4%). With 17 points, the Braden scale cut-off distinguished those who had pressure injuries from those who did not at the time of admission (p < .03). In the pressure injury group, the Braden score on the day of the pressure injury was 14, with significant results in all subcategories except the moisture category.Conclusion : Our findings revealed that a cut-off value of 17 was optimal for predicting the risk of pressure injuries among tertiary hospital inpatients. Future studies should evaluate the optimal cut-off values in different clinical environments. Additionally, it is necessary to conduct multicenter large sample studies to verify the effectiveness of a 17 value in PI risk assessments.
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