Development of a Simple Clinical Tool for Predicting Early Dropout in Cardiac Rehabilitation: A SINGLE-CENTER RISK MODEL.
Development of a Simple Clinical Tool for Predicting Early Dropout in Cardiac Rehabilitation: A SINGLE-CENTER RISK MODEL.
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DOI：
10.1097/hcr.0000000000000541
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发表时间：
2021-05-01
影响因子：
3.8
通讯作者：
Lagu T
中科院分区：
文献类型：
--
作者：
Pack QR;Visintainer P;Farah M;LaValley G;Szalai H;Lindenauer PK;Lagu T
尽管完成完整的计划有好处，但不坚持心脏康复（CR）是常见的。如果发现有早期脱落风险的患者并接受干预，则依从性可能会得到改善。使用2016年完成≥1次CR治疗的患者记录（衍生队列），我们采用多变量logistic回归在预测模型中识别与参加<12次CR治疗相关的独立患者水平特征。然后，我们在2017年入组的患者（验证队列）中评估了模型的区分度和有效性。在我们的衍生队列的657例患者中，318例（48%）完成了<12次治疗。不参加≥12次会议的独立危险因素是年龄<55岁（OR = 0.23，P < .001），年龄55 - 64岁（OR = 0.35，P <0.001），年龄≥75岁（OR = 0.64，P = 0.06），CR入组后30天内吸烟（OR = 0.40，P = 0.001），运动不良事件风险低（OR = 0.54，P = 0.03），非手术转诊诊断（OR = 0.66，P = 0.02）。我们的模型预测不依从风险为23- 90%，具有可接受的区分度和校准（C-统计量= 0.70，Harrell的E50和E90分别为2.0和3.6），但在验证队列中的542例患者中具有公平的有效性（C-统计量= 0.62，Harrell的E50和E90分别为2.1和11.3）。我们开发并评估了一个单中心简单风险模型，以预测不依从CR。尽管该模型存在局限性，但该工具可以帮助临床医生识别有早期脱落风险的患者，并指导干预措施以提高依从性，从而使所有患者都能实现CR的全部获益。
Nonadherence to cardiac rehabilitation (CR) is common despite the benefits of completing a full program. Adherence might be improved if patients at risk of early dropout were identified and received an intervention. Using records from patients who completed ≥1 CR session in 2016 (derivation cohort), we employed multivariable logistic regression to identify independent patient-level characteristics associated with attending <12 sessions of CR in a predictive model. We then evaluated model discrimination and validity among patients who enrolled in 2017 (validation cohort). Of the 657 patients in our derivation cohort, 318 (48%) completed <12 sessions. Independent risk factors for not attending ≥12 sessions were age <55 yr (OR = 0.23, P < .001), age 55 to 64 yr (OR = 0.35, P < .001), age ≥75 yr (OR = 0.64, P = .06), smoker within 30 d of CR enrollment (OR = 0.40, P = .001), low risk for exercise adverse events (OR = 0.54, P = .03), and nonsurgical referral diagnosis (OR = 0.66, P = .02). Our model predicted nonadherence risk from 23–90%, had acceptable discrimination and calibration (C-statistics = 0.70, Harrell’s E50 and E90 2.0 and 3.6, respectively) but had fair validity among 542 patients in the validation cohort (C-statistic = 0.62, Harrell’s E50 and E90 2.1 and 11.3, respectively). We developed and evaluated a single-center simple risk model to predict nonadherence to CR. Although the model has limitations, this tool may help clinicians identify patients at risk of early dropout and guide intervention efforts to improve adherence so that the full benefits of CR can be realized for all patients.