KONSTANTINOS SIDERIS MD , MINGYUAN ZHANG MS , PETER WOHLFAHRT MD, PhD , ALFONSO F. SIU MD , JINCHENG SHEN PhD , SPENCER CARTER MD , CHRISTOS P. KYRIAKOPOULOS MD , IOSIF TALEB MD , OMAR WEVER-PINZON MD , KEVIN SHAH MD , CRAIG H. SELZMAN MD , CARLOS RODRIGUEZ-CORREA MD , CHRIS KAPELIOS MD , LINA BRINKER MD , RAMI ALHARETHI MD , RACHEL HESS MD , STAVROS G. DRAKOS MD, PhD , BENJAMIN A. STEINBERG MD , JAMES C. FANG MD , ABDALLAH G. KFOURY MD , JOSEF STEHLIK MD, MPH
{"title":"将患者报告的生活质量数据纳入心力衰竭风险评估。","authors":"KONSTANTINOS SIDERIS MD , MINGYUAN ZHANG MS , PETER WOHLFAHRT MD, PhD , ALFONSO F. SIU MD , JINCHENG SHEN PhD , SPENCER CARTER MD , CHRISTOS P. KYRIAKOPOULOS MD , IOSIF TALEB MD , OMAR WEVER-PINZON MD , KEVIN SHAH MD , CRAIG H. SELZMAN MD , CARLOS RODRIGUEZ-CORREA MD , CHRIS KAPELIOS MD , LINA BRINKER MD , RAMI ALHARETHI MD , RACHEL HESS MD , STAVROS G. DRAKOS MD, PhD , BENJAMIN A. STEINBERG MD , JAMES C. FANG MD , ABDALLAH G. KFOURY MD , JOSEF STEHLIK MD, MPH","doi":"10.1016/j.cardfail.2024.08.053","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Optimal management of outpatients with heart failure (HF) requires serially updating the estimates of their risk for adverse clinical outcomes to guide treatment. Patient-reported outcomes (PROs) are becoming increasingly used in clinical care. The purpose of this study was to determine whether the inclusion of PROs can improve the risk prediction for HF hospitalization and death in ambulatory patients with HF.</div></div><div><h3>Methods and Results</h3><div>We included consecutive patients with HF with reduced ejection fraction (HFrEF) and HF with preserved EF (HFpEF) seen in a HF clinic between 2015 and 2019 who completed PROs as part of routine care. Cox regression with a least absolute shrinkage and selection operator regularization and gradient boosting machine analyses were used to estimate risk for a combined outcome of HF hospitalization, heart transplant, left ventricular assist device implantation, or death. The performance of the prediction models was evaluated with the time-dependent concordance index <span><math><mrow><mo>(</mo><msub><mi>C</mi><mi>τ</mi></msub><mo>)</mo></mrow></math></span>. Among 1165 patients with HFrEF (mean age 59.1 ± 16.1, 68% male), the median follow-up was 487 days. Among 456 patients with HFpEF (mean age 64.2 ± 16.0 years, 55% male) the median follow-up was 494 days. Gradient boosting regression that included PROs had the best prediction performance – <span><math><msub><mi>C</mi><mi>τ</mi></msub></math></span> 0.73 for patients with HFrEF and 0.74 in patients with HFpEF, and showed very good stratification of risk by time to event analysis by quintile of risk. The Kansas City Cardiomyopathy Questionnaire overall summary score, visual analogue scale and Patient Reported Outcomes Measurement Information System dimensions of satisfaction with social roles and physical function had high variable importance measure in the models.</div></div><div><h3>Conclusions</h3><div>PROs improve risk prediction in both HFrEF and HFpEF, independent of traditional clinical factors. Routine assessment of PROs and leveraging the comprehensive data in the electronic health record in routine clinical care could help more accurately assess risk and support the intensification of treatment in patients with HF.</div></div>","PeriodicalId":15204,"journal":{"name":"Journal of Cardiac Failure","volume":"31 5","pages":"Pages 761-770"},"PeriodicalIF":6.7000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integration of Patient Reported Quality-of-life Data into Risk Assessment in Heart Failure\",\"authors\":\"KONSTANTINOS SIDERIS MD , MINGYUAN ZHANG MS , PETER WOHLFAHRT MD, PhD , ALFONSO F. SIU MD , JINCHENG SHEN PhD , SPENCER CARTER MD , CHRISTOS P. KYRIAKOPOULOS MD , IOSIF TALEB MD , OMAR WEVER-PINZON MD , KEVIN SHAH MD , CRAIG H. SELZMAN MD , CARLOS RODRIGUEZ-CORREA MD , CHRIS KAPELIOS MD , LINA BRINKER MD , RAMI ALHARETHI MD , RACHEL HESS MD , STAVROS G. DRAKOS MD, PhD , BENJAMIN A. STEINBERG MD , JAMES C. FANG MD , ABDALLAH G. KFOURY MD , JOSEF STEHLIK MD, MPH\",\"doi\":\"10.1016/j.cardfail.2024.08.053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Optimal management of outpatients with heart failure (HF) requires serially updating the estimates of their risk for adverse clinical outcomes to guide treatment. Patient-reported outcomes (PROs) are becoming increasingly used in clinical care. The purpose of this study was to determine whether the inclusion of PROs can improve the risk prediction for HF hospitalization and death in ambulatory patients with HF.</div></div><div><h3>Methods and Results</h3><div>We included consecutive patients with HF with reduced ejection fraction (HFrEF) and HF with preserved EF (HFpEF) seen in a HF clinic between 2015 and 2019 who completed PROs as part of routine care. Cox regression with a least absolute shrinkage and selection operator regularization and gradient boosting machine analyses were used to estimate risk for a combined outcome of HF hospitalization, heart transplant, left ventricular assist device implantation, or death. The performance of the prediction models was evaluated with the time-dependent concordance index <span><math><mrow><mo>(</mo><msub><mi>C</mi><mi>τ</mi></msub><mo>)</mo></mrow></math></span>. Among 1165 patients with HFrEF (mean age 59.1 ± 16.1, 68% male), the median follow-up was 487 days. Among 456 patients with HFpEF (mean age 64.2 ± 16.0 years, 55% male) the median follow-up was 494 days. Gradient boosting regression that included PROs had the best prediction performance – <span><math><msub><mi>C</mi><mi>τ</mi></msub></math></span> 0.73 for patients with HFrEF and 0.74 in patients with HFpEF, and showed very good stratification of risk by time to event analysis by quintile of risk. The Kansas City Cardiomyopathy Questionnaire overall summary score, visual analogue scale and Patient Reported Outcomes Measurement Information System dimensions of satisfaction with social roles and physical function had high variable importance measure in the models.</div></div><div><h3>Conclusions</h3><div>PROs improve risk prediction in both HFrEF and HFpEF, independent of traditional clinical factors. Routine assessment of PROs and leveraging the comprehensive data in the electronic health record in routine clinical care could help more accurately assess risk and support the intensification of treatment in patients with HF.</div></div>\",\"PeriodicalId\":15204,\"journal\":{\"name\":\"Journal of Cardiac Failure\",\"volume\":\"31 5\",\"pages\":\"Pages 761-770\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cardiac Failure\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071916424003816\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cardiac Failure","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071916424003816","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Integration of Patient Reported Quality-of-life Data into Risk Assessment in Heart Failure
Background
Optimal management of outpatients with heart failure (HF) requires serially updating the estimates of their risk for adverse clinical outcomes to guide treatment. Patient-reported outcomes (PROs) are becoming increasingly used in clinical care. The purpose of this study was to determine whether the inclusion of PROs can improve the risk prediction for HF hospitalization and death in ambulatory patients with HF.
Methods and Results
We included consecutive patients with HF with reduced ejection fraction (HFrEF) and HF with preserved EF (HFpEF) seen in a HF clinic between 2015 and 2019 who completed PROs as part of routine care. Cox regression with a least absolute shrinkage and selection operator regularization and gradient boosting machine analyses were used to estimate risk for a combined outcome of HF hospitalization, heart transplant, left ventricular assist device implantation, or death. The performance of the prediction models was evaluated with the time-dependent concordance index . Among 1165 patients with HFrEF (mean age 59.1 ± 16.1, 68% male), the median follow-up was 487 days. Among 456 patients with HFpEF (mean age 64.2 ± 16.0 years, 55% male) the median follow-up was 494 days. Gradient boosting regression that included PROs had the best prediction performance – 0.73 for patients with HFrEF and 0.74 in patients with HFpEF, and showed very good stratification of risk by time to event analysis by quintile of risk. The Kansas City Cardiomyopathy Questionnaire overall summary score, visual analogue scale and Patient Reported Outcomes Measurement Information System dimensions of satisfaction with social roles and physical function had high variable importance measure in the models.
Conclusions
PROs improve risk prediction in both HFrEF and HFpEF, independent of traditional clinical factors. Routine assessment of PROs and leveraging the comprehensive data in the electronic health record in routine clinical care could help more accurately assess risk and support the intensification of treatment in patients with HF.
期刊介绍:
Journal of Cardiac Failure publishes original, peer-reviewed communications of scientific excellence and review articles on clinical research, basic human studies, animal studies, and bench research with potential clinical applications to heart failure - pathogenesis, etiology, epidemiology, pathophysiological mechanisms, assessment, prevention, and treatment.