Derivation and validation of a two‐variable index to predict 30‐day outcomes following heart failure hospitalization-Reference-Cited by-同舟云学术

Derivation and validation of a two‐variable index to predict 30‐day outcomes following heart failure hospitalization

Published:2021-05 Issue:4 Volume:8 Page:2690-2697
ISSN:2055-5822
Container-title:ESC Heart Failure
language:en
Short-container-title:ESC Heart Failure

Author:

Averbuch Tauben¹²,Lee Shun Fu²,Mamas Mamas Andreas³,Oz Urun Erbas⁴,Perez Richard⁴,Connolly Stuart James¹²,Ko Dennis Tien‐Wei⁵⁶,Van Spall Harriette Gillian Christine¹²⁴⁷

Affiliation:

1. Department of Medicine McMaster University Hamilton Ontario Canada

2. Population Health Research Institute Hamilton Ontario Canada

3. Department of Cardiology Keele University Keele UK

4. ICES Hamilton Ontario Canada

5. Sunnybrook Health Sciences Centre Toronto Ontario Canada

6. ICES Toronto Ontario Canada

7. Department of Health Research Methods, Evidence, and Impact McMaster University Hamilton Ontario Canada

Funder

Canadian Institutes of Health Research

Ontario Ministry of Health and Long-Term Care

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ehf2.13324

Reference22 articles.

1. The current and future financial burden of hospital admissions for heart failure in Canada: a cost analysis

2. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community

3. Utility of the LACE index at the bedside in predicting 30-day readmission or death in patients hospitalized with heart failure

4. Health Quality Ontario.Adopting a common approach to transitional care planning: helping health links improve transitions and coordination of care [Internet].2013.http://www.hqontario.ca/Portals/0/documents/qi/health-links/bp-improve-package-traditional-care-planning-en.pdf(1 September 2020).

5. Effect of Patient-Centered Transitional Care Services on Clinical Outcomes in Patients Hospitalized for Heart Failure

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1. On Expert-Machine Partnership to Predict Mortality of Congestive Heart Failure Patients;Information Systems Management;2024-02-09

2. Developing a Machine Learning Algorithm for Improved Management of Congestive Heart Failure Patients in the Emergency Department;Journal of Cardiology and Cardiovascular Medicine;2023-10-24

3. Prognostic value of patient‐reported outcomes in predicting 30 day all‐cause readmission among older patients with heart failure;ESC Heart Failure;2022-06-09

4. Machine learning and LACE index for predicting 30-day readmissions after heart failure hospitalization in elderly patients;Internal and Emergency Medicine;2022-06-04

5. Applications of artificial intelligence and machine learning in heart failure;European Heart Journal - Digital Health;2022-05-13