Diaconu M, Popescu DC, Țînț D, Nechita AC. Development and internal validation of a rapid bedside score for predicting in-hospital mortality in acute heart failure. World J Cardiol 2026; 18(9): 124786 [DOI: 10.4330/wjc.124786]
Corresponding Author of This Article
Diana Țînț, Professor, Department of Medical and Surgical Specialties, Faculty of Medicine, “Transilvania” University, Nicolae Balcescu No. 56, Brasov 500019, Brasov, Romania. diana.tint@unitbv.ro
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Cardiac & Cardiovascular Systems
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Diaconu M, Popescu DC, Țînț D, Nechita AC. Development and internal validation of a rapid bedside score for predicting in-hospital mortality in acute heart failure. World J Cardiol 2026; 18(9): 124786 [DOI: 10.4330/wjc.124786]
World J Cardiol. Sep 26, 2026; 18(9): 124786 Published online Sep 26, 2026. doi: 10.4330/wjc.124786
Development and internal validation of a rapid bedside score for predicting in-hospital mortality in acute heart failure
Mara Diaconu, Dan Cristian Popescu, Diana Țînț, Alexandru Cristian Nechita
Mara Diaconu, Dan Cristian Popescu, Alexandru Cristian Nechita, Department of Cardiology, Clinical Emergency Hospital “Sfântul Pantelimon”, Bucharest 021652, București, Romania
Mara Diaconu, Dan Cristian Popescu, Alexandru Cristian Nechita, Faculty of Medicine, “Carol Davila” University of Medicine and Pharmacy, Bucharest 020021, Bucuresti, Romania
Mara Diaconu, Dan Cristian Popescu, Diana Țînț, Department of Medical and Surgical Specialties, Faculty of Medicine, “Transilvania” University, Brasov 500019, Brasov, Romania
Diana Țînț, Department of Cardiology, ICCO Clinics, Brasov 500059, Brasov, Romania
Author contributions: Diaconu M and Țînț D conceived and designed the study; Diaconu M performed formal analysis and data curation; Diaconu M and Nechita AC conducted the investigation; Diaconu M and Popescu DC developed the study methodology; Diaconu M wrote the manuscript; Țînț D supervised the work; Popescu DC, Țînț D and Nechita AC critically revised the manuscript; all authors critically reviewed and provided final approval of the manuscript; all authors were responsible for the decision to submit the manuscript for publication.
AI contribution statement: During the preparation of this manuscript, the authors used ChatGPT, OpenAI, 2026 to assist in language refinement and formatting of graphical data presentation. No AI tool was used in study design, data collection, statistical analysis, interpretation of results, formulation of conclusions or preparation of the references. The authors have critically reviewed and revised the output and take full responsibility for the content, integrity and accuracy of this publication.
Institutional review board statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Clinical Emergency Hospital “Sf. Pantelimon“ Bucharest, Romania (approval No. 77).
Informed consent statement: Patient consent was waived due to the retrospective nature of the study and the use of anonymized clinical data. The study was conducted in accordance with ethical standards and received approval from the institutional ethics committee.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Data sharing statement: The data used in this study are available from the corresponding author upon request. The data are not publicly accessible due to patient privacy and confidentiality constraints.
Corresponding author: Diana Țînț, Professor, Department of Medical and Surgical Specialties, Faculty of Medicine, “Transilvania” University, Nicolae Balcescu No. 56, Brasov 500019, Brasov, Romania. diana.tint@unitbv.ro
Received: June 24, 2026 Revised: July 21, 2026 Accepted: September 1, 2026 Published online: September 26, 2026 Processing time: 87 Days and 8.2 Hours
Abstract
BACKGROUND
Early risk stratification for in-hospital mortality in acute heart failure (AHF) is a challenging topic, particularly at the time of presentation, when rapid clinical decisions are required. Many existing risk scores rely on variables that are not immediately available or are impractical for bedside use.
AIM
To develop and internally validate Fast Assessment Score for triage in heart failure (FAST-HF), a rapid bedside risk score for predicting in-hospital mortality in patients with AHF.
METHODS
A total of 123 patients with AHF were retrospectively analysed. The primary outcome was in-hospital mortality. A multivariable logistic regression model included admission parameters-NT-proBNP, arterial lactate, serum sodium, systolic blood pressure and clinical congestion summarized by a congestion index. The multivariable model was converted into a simplified point-based bedside score using a Framingham-type scaling approach. Model performance was assessed using discrimination, calibration, decision curve analysis (DCA), Youden-based risk stratification and internal validation by bootstrapping with comparative area under the curve (AUC) analysis.
RESULTS
The multivariable model demonstrated excellent discrimination for in-hospital mortality (AUC = 0.889), which was preserved after simplification into the FAST-HF bedside score (AUC = 0.867). Calibration remained acceptable, with similar Brier scores for both models. A Youden-derived cut-off identified a high-risk subgroup (≥ 15 points) with 38.6% in-hospital mortality, while no deaths occurred in the low-risk group (≤ 8 points). DCA demonstrated consistent net clinical benefit across clinically relevant threshold probabilities.
CONCLUSION
FAST-HF provides a simple, rapid bedside approach for early in-hospital mortality prediction in AHF, with good internal performance and potential clinical utility. External validation in independent cohorts is warranted.
Core Tip: This single-centre retrospective study developed and internally validated the Fast Assessment Score for triage in heart failure (FAST-HF) score, a practical prognostic tool based on readily available clinical and biological parameters, including systolic blood pressure, congestion status, NT-proBNP, lactate and serum sodium. FAST-HF showed good discriminatory performance for predicting in-hospital mortality and may help identify high-risk patients early during admission. The score is intended as an exploratory bedside instrument that requires external validation before routine clinical implementation.
