Struja Tristan, Baechli Ciril, Koch Daniel, Haubitz Sebastian, Eckart Andreas, Kutz Alexander, Kaeslin Martha, Mueller Beat, Schuetz Philipp
Kantonsspital Aarau, Medical University Clinic, Aarau, Switzerland.
Medical Faculty of the University of Basel, Basel, Switzerland.
J Gen Intern Med. 2020 Jul;35(7):2017-2024. doi: 10.1007/s11606-020-05638-z. Epub 2020 Jan 21.
Several clinical risk scores for unplanned 30-day readmission have been published, but there is a lack of external validation and head-to-head comparison.
Retrospective replication of six clinical risk scores (LACE, HOSPITAL, SEMI, RRS, PARA, Tsui et al.)f DESIGN: Models were fitted with the original intercept and beta coefficients as reported. Otherwise, a logistic model was refitted (SEMI and Tsui et al). We performed subgroup analyses on main admission specialty. This report adheres to the TRIPOD statement for reporting of prediction models.
We used our prospective cohort of 15,639 medical patients from a Swiss tertiary care institution from 2016 through 2018.
Thirty-day readmission rate and area under the curve (AUC < 0.50 worse than chance, > 0.70 acceptable, > 0.80 excellent) CONCLUSIONS: Among several readmission risk scores, HOSPITAL, PARA, and the score from Tsui et al. showed the best predictive abilities and have high potential to improve patient care. Interventional research is now needed to understand the effects of these scores when used in clinical routine.
Among the six risk scores externally validated, calibration of the models was overall poor with overprediction of events, except for the HOSPITAL and the PARA scores. Discriminative abilities (AUC) were as follows: LACE 0.53 (95% CI 0.50-0.56), HOSPITAL 0.73 (95% CI 0.72-0.74), SEMI 0.47 (95% CI 0.46-0.49), RRS 0.64 (95% CI 0.62-0.66), PARA 0.72 (95% CI 0.72-0.74), and the score from Tsui et al. 0.73 (95% CI 0.72-0.75). Performance in subgroups did not differ from the overall performance, except for oncology patients in the PARA score (0.57, 95% CI 0.54-0.60), and nephrology patients in the SEMI index (0.25, 95% CI 0.18-0.31), respectively.
已发表了几种用于非计划30天再入院的临床风险评分,但缺乏外部验证和直接比较。
对六个临床风险评分(LACE、HOSPITAL、SEMI、RRS、PARA、Tsui等人的评分)进行回顾性复制。
模型按照报告的原始截距和β系数进行拟合。否则,对逻辑模型进行重新拟合(SEMI和Tsui等人的评分)。我们对主要入院专科进行了亚组分析。本报告遵循预测模型报告的TRIPOD声明。
我们使用了来自瑞士一家三级医疗机构的15639例内科患者的前瞻性队列,时间跨度为2016年至2018年。
30天再入院率和曲线下面积(AUC<0.50表示比随机预测更差,>0.70表示可接受,>0.80表示优秀)
在几种再入院风险评分中,HOSPITAL、PARA以及Tsui等人的评分显示出最佳预测能力,并且在改善患者护理方面具有很大潜力。现在需要进行干预性研究,以了解这些评分在临床常规应用中的效果。
在外部验证的六个风险评分中,除了HOSPITAL和PARA评分外,模型的校准总体较差,事件预测过度。判别能力(AUC)如下:LACE为0.53(95%CI 0.50 - 0.56),HOSPITAL为0.73(95%CI 0.72 - 0.74),SEMI为0.47(95%CI 0.46 - 0.49),RRS为0.64(95%CI 0.62 - 0.66),PARA为0.72(95%CI 0.72 - 0.74),Tsui等人的评分为0.73(95%CI 0.72 - 0.75)。亚组中的表现与总体表现没有差异,除了PARA评分中的肿瘤患者(0.57,95%CI 0.54 - 0.60)和SEMI指数中的肾病患者(0.25,95%CI 0.18 - 0.31)。