Prognostic value of patient-reported outcomes in predicting 30 day all-cause readmission among older patients with heart failure.
Prognostic value of patient-reported outcomes in predicting 30 day all-cause readmission among older patients with heart failure.
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既往心力衰竭患者30天再入院的预测研究主要基于电子病历，很少涉及患者报告的结局。本研究旨在开发和验证包括患者报告结局的列线图，以预测老年心力衰竭患者30天全因再入院的可能性，并探索患者报告结局在预测模型中的价值。这是一项前瞻性队列研究。基于2019年3月至12月培训组的381例患者，开发了诺模图，并通过Logistic回归分析进行了内部验证。诺模图基于2020年7月至10月的170名患者进行了外部验证。使用受试者工作特征曲线、校准图和决策曲线分析评价诺模图的性能。训练组共分析381例患者的完整数据，外部验证组共入组170例患者。在培训组中，14.4%（n = 55）的患者在出院后30天内再次入院，在外部验证组中，15.9%（n = 27）的患者再次入院。诺模图包括6个因素：手术史、自行改变药物种类、信息获取能力、主观支持、抑郁水平、生活质量，均与老年心力衰竭患者30 d再入院显著相关。诺模图的受试者工作特征曲线下面积为0.949（95% CI：0.925，0.973，灵敏度：0.873，特异性：0.883）和0.804（95% CI：0.691，0.917，灵敏度：0.778，特异性：0.832），表明诺模图具有较好的区分能力。校准图显示了30天再入院的预测概率与观察到的概率之间的良好协调。决策曲线分析表明，诺模图的净效益在0- 85%的阈值概率之间更好。构建并证明了一种新颖且易于使用的列线图，强调了患者报告结局在预测研究中的重要作用。列线图的性能在外部验证队列中下降，并且在证明其临床相关性之前，必须在广泛的HF患者前瞻性队列中验证列线图。本研究的所有这些发现可以帮助专业人员识别HF患者的需求，以减少30天的再入院。
Previous prediction studies for 30 day readmission in patients with heart failure were built mainly based on electronic medical records and rarely involved patient‐reported outcomes. This study aims to develop and validate a nomogram including patient‐reported outcomes to predict the possibility of 30 day all‐cause readmission in older patients with heart failure and to explore the value of patient‐reported outcomes in prediction model. This was a prospective cohort study. The nomogram was developed and internally validated by Logistic regression analysis based on 381 patients in training group from March to December 2019. The nomogram was externally validated based on 170 patients from July to October 2020. Receiver operating characteristic curves, calibration plots and decision‐curve analysis were used to evaluate the performance of the nomogram. A total of 381 patients' complete data were analysed in the training group and 170 patients were enrolled in the external validation group. In the training group, 14.4% (n = 55) patients were readmitted to hospitals within 30 days of discharge and 15.9% (n = 27) patients were readmitted in the external validation group. The nomogram included six factors: history of surgery, changing the type of medicine by oneself, information acquisition ability, subjective support, depression level, quality of life, all of which were significantly associated with 30 day readmission in older patients with heart failure. The areas under the receiver operating characteristic curves of nomogram were 0.949 (95% CI: 0.925, 0.973, sensitivity: 0.873, specificity: 0.883) and 0.804 (95% CI: 0.691, 0.917, sensitivity: 0.778, specificity: 0.832) respectively in the training and external validation groups, which indicated that the nomogram had better discrimination ability. The calibration plots demonstrated favourable coordination between predictive probability of 30 day readmission and observed probability. Decision‐curve analysis showed that the net benefit of the nomogram was better between threshold probabilities of 0–85%. A novel and easy‐to‐use nomogram is constructed and demonstrated which emphasizes the important role of patient‐reported outcomes in predicting studies. The performance of the nomogram drops in the external validation cohort and the nomogram must be validated in a wide prospective cohort of HF patients before its clinical relevance can be demonstrated. All these findings in this study can assist professionals in identifying the needs of HF patients so as to reduce 30 day readmission.
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影响因子：
8.9
作者：
Fabbri M;Yost K;Finney Rutten LJ;Manemann SM;Boyd CM;Jensen D;Weston SA;Jiang R;Roger VL
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