Impact of a Claims-Based Frailty Indicator on the Prediction of Long-Term Mortality After Transcatheter Aortic Valve Replacement in Medicare Beneficiaries.
Impact of a Claims-Based Frailty Indicator on the Prediction of Long-Term Mortality After Transcatheter Aortic Valve Replacement in Medicare Beneficiaries.
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DOI：
10.1161/circoutcomes.118.005048
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Yeh RW
中科院分区：
文献类型：
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作者：
Kundi H;Valsdottir LR;Popma JJ;Cohen DJ;Strom JB;Pinto DS;Shen C;Yeh RW
与单纯合并症相比，预先收集的虚弱标志物与经导管主动脉瓣置换术（TAVR）后1年死亡风险增加相关。尚不清楚在管理账单数据中回顾性采集的虚弱标志物信息是否同样可预测TAVR术后的长期死亡率。我们试图描述在医疗账单记录中确定的虚弱因素的预后重要性，并与经验证的虚弱指标进行比较，以预测TAVR后的长期死亡率。在2011年8月25日至2015年9月29日期间接受TAVR的成年患者被确定为Medicare按服务收费的受益人。约翰霍普金斯索赔为基础的虚弱指标被用来确定虚弱的病人。我们使用嵌套式考克斯回归模型来确定基于索赔的术后4年死亡率预测因子。依次引入四组变量，包括心脏风险因素，非心脏风险因素，患者手术风险因素和非传统的虚弱标志物，并评估其综合辨别力改善（IDI）。共确定了来自558家临床试验机构的52，338例TAVR患者，平均随访时间为16个月。研究期间共有14，174例（27.1%）患者死亡。TAVR术后4年的死亡率为53.9%。共有34，863例（66.6%）患者被定义为虚弱。4个模型的区分度分别为0.60（95%CI：0.59-60）、0.65（95%CI：0.64-0.65）、0.68（95%CI：0.67-0.68）和0.70（95%CI：0.69-0.70）。在索赔中确定的非传统虚弱标志物的添加改善了死亡率预测，超过了传统的风险因素（IDI：0.019，p < 0.001）。包括在索赔数据中识别的虚弱的风险预测模型可用于预测TAVR后的长期死亡风险。与索赔数据的联系可能会增强不收集虚弱信息的研究的死亡率风险预测。
Prospectively collected frailty markers are associated with an incremental 1-year mortality risk after transcatheter aortic valve replacement (TAVR) compared to comorbidities alone. Whether information on frailty markers captured retrospectively in administrative billing data is similarly predictive of long-term mortality after TAVR is unknown. We sought to characterize the prognostic importance of frailty factors as identified in healthcare billing records in comparison to validated measures of frailty for the prediction of long-term mortality after TAVR. Adult patients undergoing TAVR between August 25, 2011 and September 29, 2015 were identified among Medicare fee-for-service beneficiaries. The Johns Hopkins Claims-based Frailty Indicator was used to identify frail patients. We used nested Cox regression models to identify claims-based predictors of mortality up to 4 years post-procedure. Four groups of variables including cardiac risk factors, non-cardiac risk factors, patient procedural risk factors, and non-traditional markers of frailty were introduced sequentially, and their integrated discrimination improvement (IDI) was assessed. A total of 52,338 TAVR patients from 558 clinical sites were identified, with a mean follow-up time period of 16 months. In total, 14,174 (27.1%) patients died within the study period. The mortality rate was 53.9% at 4-years post TAVR. A total of 34,863 (66.6%) patients were defined as frail. The discrimination of each of the 4 models was 0.60 (95% CI: 0.59–60), 0.65 (95% CI: 0.64–0.65), 0.68 (95% CI: 0.67–0.68) and 0.70 (95% CI: 0.69–0.70), respectively. The addition of non-traditional frailty markers as identified in claims improved mortality prediction above and beyond traditional risk factors (IDI: 0.019, p < 0.001). Risk prediction models that include frailty as identified in claims data can be used to predict long-term mortality risk after TAVR. Linkage to claims data may allow enhanced mortality risk prediction for studies that do not collect information on frailty.