Multidimensional Prognostic Index and pro-adrenomedullin plasma levels as mortality risk predictors in older patients hospitalized with community-acquired pneumonia: A prospective study
Panminerva Medica, ISSN: 1827-1898, Vol: 60, Issue: 3, Page: 80-85
2018
- 7Citations
- 17Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations7
- Citation Indexes7
- Captures17
- Readers17
- 17
Article Description
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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85053770894&origin=inward; http://dx.doi.org/10.23736/s0031-0808.18.03408-0; http://www.ncbi.nlm.nih.gov/pubmed/29546738; https://www.minervamedica.it/index2.php?show=R41Y2018N03A0080; https://dx.doi.org/10.23736/s0031-0808.18.03408-0; https://www.minervamedica.it/alert.php
Edizioni Minerva Medica
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