Prediction of medical admissions after psychiatric inpatient hospitalization in bipolar disorder: a retrospective cohort study

September 29, 2024

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Publicated to: Frontiers in Psychiatry. 15 1435199- - 2024-09-03 15(), DOI: 10.3389/fpsyt.2024.1435199

Authors:

Miola, Alessandro; De Prisco, Michele; Lussignoli, Marialaura; Meda, Nicola; Dughiero, Elisa; Costa, Riccardo; Nunez, Nicolas A; Fornaro, Michele; Veldic, Marin; Frye, Mark A; Vieta, Eduard; Solmi, Marco; Radua, Joaquim; Sambataro, Fabio

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Affiliations

Charite, Dept Child & Adolescent Psychiat, Berlin, Germany - Author

Federico II Univ Naples, Dept Psychiat, Naples, Italy - Author

Hosp Clin Barcelona, Bipolar & Depress Disorders Unit, Barcelona, Spain - Author

Inst Salud Carlos III, Ctr Invest Biomed Red Salud Mental CIBERSAM, Madrid, Spain - Author

Mayo Clin, Dept Psychiat & Psychol, Rochester, MN USA - Author

Ottawa Hosp, Dept Mental Hlth, Ottawa, ON, Canada - Author

Univ Barcelona UB, Dept Med, Fac Med & Ciencies Salut, Barcelona, Spain - Author

Univ Barcelona UB, Inst Neurosci UBNeuro, Fac Med & Hlth Sci, Dept Med, Barcelona, Spain - Author

Univ Barcelona, Inst Invest Biomed August Pi I Sunyer IDIBAPS, Barcelona, Spain - Author

Univ Ottawa, Dept Psychiat, Sci Lab, Ottawa, ON, Canada - Author

Univ Ottawa, Fac Med, Sch Epidemiol & Publ Hlth, Ottawa, ON, Canada - Author

Univ Ottawa, Ottawa Hosp Res Inst OHRI, Clin Epidemiol Program, Ottawa, ON, Canada - Author

Univ Padua, Dept Neurosci, Padua, Italy - Author

Univ Utah, Dept Psychiat, Salt Lake City, UT USA - Author

Abstract

Objective Bipolar Disorder (BD) is a severe mental illness associated with high rates of general medical comorbidity, reduced life expectancy, and premature mortality. Although BD has been associated with high medical hospitalization, the factors that contribute to this risk remain largely unexplored. We used baseline medical and psychiatric records to develop a supervised machine learning model to predict general medical admissions after discharge from psychiatric hospitalization.Methods In this retrospective three-year cohort study of 71 patients diagnosed with BD (mean age=52.19 years, females=56.33%), lasso regression models combining medical and psychiatric records, as well as those using them separately, were fitted and their predictive power was estimated using a leave-one-out cross-validation procedure.Results The proportion of medical admissions in patients with BD was higher compared with age- and sex-matched hospitalizations in the same region (25.4% vs. 8.48%). The lasso model fairly accurately predicted the outcome (area under the curve [AUC]=69.5%, 95%C.I.=55-84.1; sensitivity=61.1%, specificity=75.5%, balanced accuracy=68.3%). Notably, pre-existing cardiovascular, neurological, or osteomuscular diseases collectively accounted for more than 90% of the influence on the model. The accuracy of the model based on medical records was slightly inferior (AUC=68.7%, 95%C.I. = 54.6-82.9), while that of the model based on psychiatric records only was below chance (AUC=61.8%, 95%C.I.=46.2-77.4).Conclusion Our findings support the need to monitor medical comorbidities during clinical decision-making to tailor and implement effective preventive measures in people with BD. Further research with larger sample sizes and prospective cohorts is warranted to replicate these findings and validate the predictive model.

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Keywords

AdultAprenentatge automàticArea under the curveArticleBipolar disorderClinical decision makingClinical decision-makinClinical decision-makingCohort analysisComorbiditatComorbidityComplicacions (medicina)Complications (medicine)Controlled studyDemographicsDiagnostic test accuracy studyEconomic burdenElectrocardiogramFemaleGeneral medicine admissionHealthHospital dischargeHospital patientHospital patientsHospitalizationHumanLeast absolute shrinkage and selection operatorLife expectancyMachine learningMajor clinical studyMalalts hospitalitzatsMaleManic-depressive illnessMental diseaseMental-illnessMetaanalysisMood stabilizerMortalitObservational studyPeoplePhysical diseasesPredictionPremature mortalityPrevalenceRehospitalization ratesRetrospective studyRiskSensitivity and specificityTrastorn bipolar

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The work has been published in the journal Frontiers in Psychiatry due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Psychiatry and Mental Health.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-01:

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This work has been carried out with international collaboration, specifically with researchers from: Canada; Germany; Italy; United States of America.

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Awards linked to the item

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Open Access funding provided by Universita degli Studi di Padova | University of Padua, Open Science Committee.

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