Predictors of mortality in heart failure patients: a retrospective cohort study at a tertiary care hospital in Vadodara

Authors

  • Payal Godria Department of Medicine, M.S. University, Government Medical College, Baroda, Gujarat, India
  • Chinmay Patel Department of Medicine, M.S. University, Government Medical College, Baroda, Gujarat, India
  • Pankil Thaker Department of Medicine, Gujarat University, Narendra Modi Medical College, Ahmedabad, Gujarat, India
  • Ronit Bhuva Department of Medicine, M.S. University, Government Medical College, Baroda, Gujarat, India
  • Harsh Kumar Patel Department of Medicine, M.S. University, Government Medical College, Baroda, Gujarat, India
  • Yashvi Patel Department of Medicine, Gujarat University, Narendra Modi Medical College, Ahmedabad, Gujarat, India
  • Dhruv Patel Department of Medicine, M.S. University, Government Medical College, Baroda, Gujarat, India
  • Divyang Bhudhrani Department of Medicine, Bachelors of Medicine and Bachelors of Surgery (M.B.B.S), Bukovinian State Medical University, Ukraine

DOI:

https://doi.org/10.18203/2320-6012.ijrms20253177

Keywords:

Chronic kidney disease, Survival analysis, NT-proBNP, Mortality predictors, Heart failure, Left ventricular ejection fraction

Abstract

Background: Heart failure (HF) remains a leading cause of morbidity and mortality worldwide, particularly in low- and middle-income countries. Understanding the factors contributing to mortality in HF patients can inform clinical decisions and improve patient outcomes. This study aims to identify the predictors of mortality in HF patients admitted to a tertiary care hospital in Vadodara, Gujarat.

Methods: This retrospective cohort study included 250 consecutive HF patients admitted to SSG Hospital, Vadodara, between January 2022 and December 2023. Patient data, including demographic characteristics, clinical features, comorbidities, left ventricular ejection fraction (LVEF), laboratory values and mortality outcomes, were collected from hospital records. Multivariable logistic regression was used to identify independent predictors of mortality. Kaplan-Meier survival curves were generated to analyze survival rates over the study period.

Results: The cohort consisted of 250 patients, with a mean age of 62.7±10.5 years. Males accounted for 58.9% of the cohort. Overall mortality was 29.3% during the follow-up period. Predictors of mortality included lower LVEF (OR 2.7, 95% CI 1.8-4.2, p<0.001), elevated NT-proBNP levels (OR 3.2, 95% CI 2.0-5.1, p<0.001) and chronic kidney disease (OR 2.5, 95% CI 1.6-4.0, p=0.002). Kaplan-Meier analysis revealed a significant difference in survival rates between patients with LVEF<40% and those with LVEF≥40% (p<0.001).

Conclusions: This study identified several key predictors of mortality in HF patients, including reduced LVEF, elevated NT-proBNP levels and chronic kidney disease. These findings underscore the need for close monitoring and management of these high-risk factors to improve survival outcomes in HF patients.

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References

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Published

2025-09-29

How to Cite

Godria, P., Patel, C., Thaker, P., Bhuva, R., Patel, H. K., Patel, Y., Patel, D., & Bhudhrani, D. (2025). Predictors of mortality in heart failure patients: a retrospective cohort study at a tertiary care hospital in Vadodara. International Journal of Research in Medical Sciences, 13(10), 4273–4276. https://doi.org/10.18203/2320-6012.ijrms20253177

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Original Research Articles