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New associations of the Multidimensional Prognostic Index

Neue Assoziationen des Multidimensionalen Prognostischen Index

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Zeitschrift für Gerontologie und Geriatrie Aims and scope Submit manuscript

Abstract

Background

The multidimensional prognostic index (MPI) is a validated, sensitive, and specific prognosis estimation tool based on a comprehensive geriatric assessment (CGA). The MPI accurately predicts mortality after 1 month and 1 year in older, multimorbid patients with acute disease or relapse of chronic conditions.

Objective

To evaluate whether the MPI predicts indicators of healthcare resources, i.e. grade of care (GC), length of hospital stay (LHS) and destination after hospital discharge in older patients in an acute medical setting.

Material and methods

In this study 135 hospitalized patients aged 70 years and older underwent a CGA evaluation to calculate the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI‑1, score 0–0.33), moderate (MPI-2, score 0.34–0.66) and high (MPI-3, score 0.67–1) risk of mortality. The GC, LHS and the discharge allocation were also recorded.

Results

The MPI score was significantly related to LHS (p = 0.011) and to GC (p < 0.001). In addition, MPI-3 patients were significantly more often transferred from other hospital settings (p = 0.007) as well as significantly less likely to be discharged home (p = 0.04) than other groups.

Conclusion

The CGA-based MPI values are significantly associated with use of indicators of healthcare resources, including GC, LHS and discharge allocation. These findings suggest that the MPI may be useful for resource planning in the care of older multimorbid patients admitted to hospital.

Zusammenfassung

Hintergrund

Der Multidimensionale Prognostische Index (MPI) ist ein validiertes, sensitives und spezifisches Instrument zur Abschätzung der Prognose auf der Basis des Comprehensive Geriatric Assessment (CGA). Der MPI eignet sich für eine genaue Vorhersage der Einmonats- und der Einjahresmortalität für ältere, multimorbide Patienten mit einer akuten Erkrankung oder mit einem Rezidiv bzw. einer Exazerbation einer chronischen Erkrankung.

Ziel

Verifiziert werden sollte, ob sich mit Hilfe des MPI bei älteren, hospitalisierten Patienten in einem akuten Setting Indikatoren gesundheitsassoziierter Ressourcen, wie Pflegegrad („grade of care“, GC), Dauer des stationären Aufenthalts („length of hospital stay“, LHS) und das Verlegungsziel, genau vorhersagen lassen.

Material und Methoden

Einhundertfünfunddreißig hospitalisierte Patienten im Alter über 70 Jahren wurden mit dem CGA untersucht, um den MPI bei Aufnahme und bei Entlassung zu berechnen. Dabei wurden die Patienten verschiedenen Risikobereichen zugeordnet: niedriges (MPI-1, Score 0–0,33), mittleres (MPI-2, 0,34–0,66) und hohes (MPI-3, 0,67–1) Mortalitätsrisiko. Zusätzlich wurden GC, LHS und Verlegungsziel erhoben.

Ergebnisse

Der MPI-Wert war signifikant mit der LHS (p = 0,011) und dem GC (p < 0,001) assoziiert. Zusätzlich wurden MPI-3-Patienten signifikant häufiger aus anderen Krankenhäusern bei Aufnahme verlegt (p = 0,007) als die der anderen Gruppen, und es war weniger wahrscheinlich, dass die MPI-3-Patienten nach Hause entlassen wurden (p = 0,04).

Diskussion

Die CGA-basierten MPI-Werte waren signifikant mit Indikatoren gesundheitsbezogener Ressourcen assoziiert, einschließlich GC, LHS und Verlegungsziel. Diese Ergebnisse deuten darauf hin, dass der MPI bei der Ressourcenplanung in der Versorgung von älteren, multimorbiden und hospitalisierten Patienten hilfreich sein könnte.

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Acknowledgements

The results were partly presented at the Annual Congress of the German Geriatrics Society 2017, where the study MPI_InGAH received the prize for the “Promotion of the interdisciplinary age medicine” of the German Geriatrics Society. The authors are grateful to the patients who took their time during the hospital stay to take part of that interview.

Author contributions

AMM and MCP conceived and designed the clinical trial. AMM performed the experiments. AMM, IB and GS analyzed the data. AMM wrote the paper. AMM, MCP and IB conceived the manuscript. AMM, MCP, IB, TB, PTB and AP performed critical revision.

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Authors and Affiliations

  1. Ageing Clinical Research, Dpt. II for Internal Medicine, University Hospital of Cologne, Cologne, Germany

    Anna Maria Meyer & M. Cristina Polidori MD PhD FRCP

  2. Institute of Medical Statistics and Computational Biology, University Hospital of Cologne, Cologne, Germany

    Ingrid Becker

  3. Scientific Directorate – Biostatistics, E.O. Galliera Hospital, Genova, Italy

    Giacomo Siri

  4. Nephrology, Rheumatology, Diabetology and Internal Medicine, Dpt. II for Internal Medicine, University Hospital of Cologne, Cologne, Germany

    Paul Thomas Brinkkötter & Thomas Benzing

  5. Department Geriatric Care, Orthogeriatrics and Rehabilitation, Frailty Area, E.O. Galliera Hospital, Genova, Italy

    Alberto Pilotto

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  1. Anna Maria Meyer
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  2. Ingrid Becker
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  3. Giacomo Siri
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  6. Alberto Pilotto
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  7. M. Cristina Polidori MD PhD FRCP
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Corresponding author

Correspondence to M. Cristina Polidori MD PhD FRCP.

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Conflict of interest

A.M. Meyer, I. Becker, G. Siri, P.T. Brinkkötter, T. Benzing, A. Pilotto and M. C. Polidori declare that they have no competing interests.

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

A. Pilotto and M.C. Polidori contributed equally to the manuscript.

Caption Electronic Supplementary Material

Supplement 1

 Calculating the multidimensional prognostic index (MPI) after Pilotto et al. [12]

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Meyer, A.M., Becker, I., Siri, G. et al. New associations of the Multidimensional Prognostic Index. Z Gerontol Geriat 52, 460–467 (2019). https://doi.org/10.1007/s00391-018-01471-6

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  • DOI: https://doi.org/10.1007/s00391-018-01471-6

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