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Panminerva Med. 2018 Sep;60(3):80-85. doi: 10.23736/S0031-0808.18.03408-0. Epub 2018 Mar 15.

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

Author information

1
Department of Geriatric Care, Orthogeriatrics and Rehabilitation, Galliera Hospital, Genoa, Italy - alberto.pilotto@galliera.it.
2
Department of Geriatric Care, Orthogeriatrics and Rehabilitation, Galliera Hospital, Genoa, Italy.
3
Department of Women and Children's Health, University of Padua, Padua, Italy.
4
Department of Laboratory Medicine, Azienda ULSS 6 Euganea and Azienda Ospedaliera, Padua, Italy.
5
Department of Laboratory Medicine, Azienda ULSS 3 Serenissima, Venice, Italy.
6
Casa Sollievo della Sofferenza Institute for Research and Care, San Giovanni Rotondo, Foggia, Italy.

Abstract

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.

PMID:
29546738
DOI:
10.23736/S0031-0808.18.03408-0
[Indexed for MEDLINE]
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