Prognostic model for mortality in heart failure patients: integrating palliative care needs assessment

Introduction Heart failure (HF) is a leading cause of morbidity and mortality worldwide, often associated with a high symptom burden and reduced quality of life. Identifying palliative care needs (PCN) early may enhance risk stratification and improve patient outcomes. The Integrated Palliative Care Outcome Scale (IPOS) provides a comprehensive assessment of PCN, but its prognostic value in HF remains underexplored Aims To develop a prognostic model incorporating palliative care needs (PCN) in hospitalized heart failure (HF) patients and assess its predictive value for mortality. Methods A prospective observational study was conducted on 160 HF patients in Vietnam. The Integrated Palliative Care Outcome Scale (IPOS) was used to evaluate PCN at admission, with PCN defined as having ≥2 items scored 4 or ≥3 items scored ≥3 on the IPOS. A multivariable Cox regression model was developed to predict one-year mortality, incorporating PCN and significant clinical predictors. Model performance was assessed using the concordance index (C-index) and calibration plots. Results PCN was identified in 59.38% of patients. The most prevalent physical symptoms were shortness of breath (57.50%), weakness (51.88%), and pain (45.63%), while emotional symptoms such as patient and family anxiety were reported at moderate levels (43.13% and 51.25%, respectively). Independent predictors of mortality included PCN (adjusted HR: 2.63, 95% CI: 1.06-6.53, p=0.037), lower eGFR (adjusted HR: 1.85, 95% CI: 1.12-3.05, p=0.016), intravenous medication use (adjusted HR: 2.10, 95% CI: 1.25-3.52, p=0.005), and prolonged HF duration (adjusted HR: 1.72, 95% CI: 1.08-2.74, p=0.022). The final prognostic model demonstrated good discrimination (C-index = 0.72) and calibration, with calibration plots showing close agreement between predicted and observed mortality rates. Conclusion PCN is a crucial prognostic factor in HF patients, independently associated with increased one-year mortality. The proposed prognostic model, which integrates PCN with clinical parameters such as eGFR, HF duration, and intravenous medication use, enhances risk stratification and may guide early palliative care interventions