Combined use of the multidimensional prognostic index (MPI) and procalcitonin serum levels in predicting 1-month mortality risk in older patients hospitalized with community-acquired pneumonia (CAP): a prospective study.

BACKGROUND: Several scores and biomarkers, i.e., procalcitonin (PCT), were proposed to stratify the mortality risk in community-acquired pneumonia (CAP). AIM: Evaluating prognostic accuracy of PCT and Multidimensional Prognostic Index (MPI) for 1-month mortality risk in older patients with CAP. METHODS: At hospital admission and at discharge, patients were evaluated by a Comprehensive Geriatric Assessment to calculate MPI. Serum PCT was measured at admission and 1, 3, and 5 days after hospital admission. RESULTS: 49 patients were enrolled. The overall 1-month mortality was 44.5 for 100-persons year. Mortality rates were higher with the increasing of MPI. In survived patients, MPI at discharge showed higher predictive accuracy than MPI at admission. Adding PCT levels to admission MPI prognostic accuracy for 1-month mortality significantly increased. CONCLUSION: In older patients with CAP, MPI significantly predicted 1 month mortality. PCT levels significantly improved the accuracy of MPI at admission in predicting 1-month mortality.

Multidimensional Prognostic Index and pro-adrenomedullin plasma levels as mortality risk predictors in older patients hospitalized with community-acquired pneumonia: a prospective study.

BACKGROUND: To evaluate the prognostic accuracy of proadrenomedullin (proADM) in comparison with and in addition to the Multidimensional Prognostic Index (MPI), a validated predictive tool for mortality derived from a comprehensive geriatric assessment (CGA) to predict one-month mortality risk in older patients hospitalized with community-acquired pneumonia (CAP). METHODS: All patients aged 65 years and older, consecutively admitted to an acute geriatric ward with a diagnosis of CAP from February to July 2012. At admission and at discharge they were submitted to a standard CGA in order to calculate MPI. Moreover, plasma samples were taken at baseline and after one, three and five days of hospitalization for the analysis of pro-ADM. RESULTS: Fifty patients (mean age 86.2±7.5 years), with 31 at high risk of mortality (MPI-3) were enrolled. ProADM and MPI, both at admission and at discharge, were significant predictor of mortality. As expected, MPI at admission showed lower predictive accuracy than MPI at discharge (survival C-statistic 0.667 vs. 0.851). The addition of proADM to the MPI at admission significantly increased accuracy in predicting one-month mortality (C-statistics from 0.667 to 0.731, P=0.018 at baseline; from 0.667 to 0.733, P=0.008 at 1 day; from 0.633 to 0.724; P=0.019 at 3 days; from 0.667 to 0.828; P=0.003 at 5 days). Conversely, adding pro-ADM to the MPI at discharge did not significantly improve the model's prognostic accuracy. CONCLUSIONS: ProADM may significantly improve the prognostic accuracy of the MPI at admission in hospitalized elderly patients with CAP.