Prognostic Value of Nursing Diagnoses for Length of Stay and Mortality in Decompensated Heart Failure

AimTo evaluate the association between nursing diagnoses, in-hospital mortality and length of stay in adults hospitalized with decompensated heart failure.MethodsA prospective longitudinal study conducted between April 2018 and July 2019. Data were collected from medical records of patients admitted to the emergency department of a large cardiovascular teaching hospital. Sociodemographic and clinical variables, along with nursing diagnoses based on NANDA-I classification, were extracted. Cox proportional hazards regression identified factors associated with mortality, while generalized linear regression with a gamma distribution assessed predictors of length of stay. Discriminatory performance of nursing diagnoses for mortality was evaluated using ROC curve analysis.FindingsA total of 155 patients were included (mean age 62.6 years; 58.7% male); 29 (18.7%) died and 126 (81.3%) were discharged, with a median hospital stay of 5 days. Age, chronic kidney disease, and lower serum sodium were independent prognosis of mortality. The number of nursing diagnoses showed poor discriminative ability for mortality prediction (AUC = 0.59). However, each additional nursing diagnosis was associated with a 6.3% increase in hospital stay (p < 0.05). Patients with acute coronary syndrome or hypertension had on average, 20% shorter hospital stays.ConclusionThe number of nursing diagnoses was independently associated with longer hospitalization, suggesting that these assessments capture care complexity beyond traditional medical diagnoses. Integrating nursing diagnostic information into prognostic models may improve care planning and resource allocation for patients with decompensated hear failure.Implications for nursing knowledgeNursing diagnoses offer additional insights into patient complexity and can enhance clinical decision-making, staffing strategies, and individualized care planning to improve hospital outcomes.