Outcome of the multidimensional prognostic index in ultra-octogenarian patients hospitalized for cardiovascular diseases

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BackgroundThe multidimensional prognostic index (MPI) is a validated tool for prognostic stratification in acute and chronic setting of geriatric patients. However, only few data are available on patients with cardiovascular diseases.AimTo evaluate the potential role of MPI as predictor of 1-year and long-term outcome in ultra-octogenarians patients hospitalized for cardiovascular diseases.Methods and resultsWe conducted a prospective study on 216 patients (mean age 85 ± 4 years) hospitalized for cardiovascular disease enrolled from September 2011 to February 2014 in both Cardiology and Internal Medicine Departments. The mean follow-up was 33 ± 7 months. The primary end-point was 1-year all-cause mortality. In addition, 3-year all-cause mortality was also assessed in the overall cohort and outcome prediction was then evaluated separately in patients with a primary diagnosis of heart failure and acute coronary syndrome. At admission, 53% of patients had a MPI-1 low risk, 34% had a MPI-2 moderate risk and 13% had a MPI-3 high risk (13%). Internal medicine inpatients had worse risk profile and higher MPI risk class than patients admitted to the cardiovascular department. Fifty-four patients (25%) experienced the primary end-point. In the multivariate logistic regression model MPI score [hazard ratio (HR) 1.83, 95% confidence interval (CI) 1.23–2.71, P = 0.003], serum creatinine (HR 1.32, 95% CI 1.13–1.54, P < 0.001) and serum albumin (HR 0.43, 95% CI, P = 0.04) were independent predictors of 1-year mortality. The area under the receiver operating characteristic combining the MPI score with serum creatinine and albumin was 0.83 (CI 0.15–0.59, P < 0.001).ConclusionIn ultra-octogenarian inpatients hospitalized for cardiovascular disease, MPI score independently predicts a poorer outcome. An integrated model including MPI, serum creatinine and albumine might aid the prognostic stratification of hospitalized elderly populations.

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