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Evaluating three biomarkers as prognostic factors of in-hospital mortality and severity in heart failure: A prospective cohort

  • Pedro A. Segura-Saldaña
    ,
  • ,
  • Javier E. Alarcón-Santos
    ,
  • Cristian Aguilar
    ,
  • Mayita L. Alvarez-Vargas
    ,
  • Marcos Padilla-Reyes
  • Hospital Nacional Edgardo Rebagliati Martins, EsSalud
    ,
  • Universidad Peruana Cayetano Heredia
    ,
  • Torres de Salud National Research Center
    ,
  • ,
  • Red Latinoamericana de Cardiología
    ,
  • Heart National Institute
Research Output: Contribution to journal Article Peer-review

Open access

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 31-40 (10 pages)

Journal (Volume, Issue Number)

Revista Portuguesa de Cardiologia (Volume 41, Issue 1)

Publication milestones

  • Published - 01/2022

Publication status

Published - 01/2022

ISSN

0870-2551

Publication IDs

  • Scopus: 85115802542

Abstract

Objective: To identify the relationship between red blood cell distribution width (RDW, %), interleukin-6 (IL-6) (pg/ml), high sensitivity-c-reactive protein (hs-CRP) (mg/l), in-hospital mortality and disease severity among patients with heart failure (HF). Methods: Prospective cohort. We included adults diagnosed with acute non-ischemic HF in 2015. The dependent variables were in-hospital mortality (yes or no) and disease severity. The latter was assessed with the Get With The Guidelines-HF score. We used hierarchical regression models to describe the pattern of association between biomarkers, mortality, and severity. We used the Youden index to identify the best cut-off for mortality prediction. Results: We included 167 patients; the mean age was 72.61 (SD: 11.06). The majority of patients presented with New York Heart Association classification II (40.12%) or III (43.11%). After adjusting for age and gender, all biomarkers were associated with mortality. After adding comorbidities, only IL-6 was associated. The final model with all clinical variables showed no effect from any biomarker. The best cut-off for RDW, hs-CRP and IL-6 for mortality were 14.8, 68.7 and 52.9, respectively. IL-6 presented the highest sensitivity (100%), specificity (75.35%) and area under the curve (0.91). Conclusions: No biomarker is independent from the most important clinical variables; therefore it should not be used for management modifications.