A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

Journal: JMIR public health and surveillance
PMID:

Abstract

BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals with multimorbidity who contract COVID-19 often face a significant reduction in life expectancy. The postpandemic period has also highlighted an increase in frailty, emphasizing the importance of integrating existing multimorbidity details into epidemiological risk assessments. Managing clinical data that include medical histories presents significant challenges, particularly due to the sparsity of data arising from the rarity of multimorbidity conditions. Also, the complex enumeration of combinatorial multimorbidity features introduces challenges associated with combinatorial explosions.

Authors

  • Dayana Benny
    Centre for Biostatistics, Epidemiology, and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.
  • Mario Giacobini
    Data Analysis and Modeling Unit, Department of Veterinary Sciences, University of Turin, Turin, Italy.
  • Alberto Catalano
    Centre for Biostatistics, Epidemiology, and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.
  • Giuseppe Costa
    Urology Unit, Camposampiero Civil Hospital, Camposampiero, Padua, Italy.
  • Roberto Gnavi
    Unit of Epidemiology, Regional Health Service, Local Health Unit Torino 3, Turin, Italy.
  • Fulvio Ricceri
    Centre for Biostatistics, Epidemiology, and Public Health, Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.