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Using routinely collected clinical data for circadian medicine: A review of opportunities and challenges.
Kervezee, Laura; Dashti, Hassan S; Pilz, Luísa K; Skarke, Carsten; Ruben, Marc D.
Afiliação
  • Kervezee L; Group of Circadian Medicine, Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
  • Dashti HS; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.
  • Pilz LK; Department of Anesthesiology and Intensive Care Medicine CCM / CVK, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Skarke C; ECRC Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Ruben MD; Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America.
PLOS Digit Health ; 3(5): e0000511, 2024 May.
Article em En | MEDLINE | ID: mdl-38781189
ABSTRACT
A wealth of data is available from electronic health records (EHR) that are collected as part of routine clinical care in hospitals worldwide. These rich, longitudinal data offer an attractive object of study for the field of circadian medicine, which aims to translate knowledge of circadian rhythms to improve patient health. This narrative review aims to discuss opportunities for EHR in studies of circadian medicine, highlight the methodological challenges, and provide recommendations for using these data to advance the field. In the existing literature, we find that data collected in real-world clinical settings have the potential to shed light on key questions in circadian medicine, including how 24-hour rhythms in clinical features are associated with-or even predictive of-health outcomes, whether the effect of medication or other clinical activities depend on time of day, and how circadian rhythms in physiology may influence clinical reference ranges or sampling protocols. However, optimal use of EHR to advance circadian medicine requires careful consideration of the limitations and sources of bias that are inherent to these data sources. In particular, time of day influences almost every interaction between a patient and the healthcare system, creating operational 24-hour patterns in the data that have little or nothing to do with biology. Addressing these challenges could help to expand the evidence base for the use of EHR in the field of circadian medicine.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLOS Digit Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLOS Digit Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda