How Different Pre-existing Mental Disorders and Their Co-occurrence Affects COVID-19 Clinical Outcomes? A Real-World Data Study in the Southern United States

  1. Shan Qiao
  2. Jiajia Zhang
  3. Shujie Chen
  4. Bankole Olatosi
  5. Suzanne Hardeman
  6. Meera Narasimhan
  7. Larisa Bruner
  8. Abdoulaye Diedhiou
  9. Cheryl Scott
  10. Ali Mansaray
  11. Sharon Weissman
  12. Xiaoming Li

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Abstract

Although a psychiatric history might be an independent risk factor for COVID-19 infection and mortality, no studies have systematically investigated how different clusters of pre-existing mental disorders may affect COVID-19 clinical outcomes or showed how the coexistence of mental disorder clusters is related to COVID-19 clinical outcomes.

Methods

Using a retrospective cohort study design, a total of 476,775 adult patients with lab-confirmed and probable COVID-19 between March 06, 2020 and April 14, 2021 in South Carolina, United States were included in the current study. The electronic health record data of COVID-19 patients were linked to all payer-based claims data through the SC Revenue and Fiscal Affairs Office. Pre-existing mental disorder diagnoses from Jan 2, 2019 to Jan 14, 2021 were extracted from the patients' healthcare utilization data via ICD-10 codes.

Results

There is an elevated risk of COVID-19-related hospitalization and death among participants with pre-existing mental disorders adjusting for key socio-demographic and comorbidity covariates. Co-occurrence of any two clusters was positively associated with COVID-19-related hospitalization and death. The odds ratio of being hospitalized was 1.26 (95% CI: 1.151, 1.383) for patients with internalizing and externalizing disorders, 1.65 (95% CI: 1.298, 2.092) for internalizing and thought disorders, 1.76 (95% CI: 1.217, 2.542) for externalizing and thought disorders, and 1.64 (95% CI: 1.274, 2.118) for three clusters of mental disorders.

Conclusions

Pre-existing internalizing disorders and thought disorders are positively related to COVID-19 hospitalization and death. Co-occurrence of any two clusters of mental disorders have elevated risk of COVID-19-related hospitalization and death compared to those with a single cluster.

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  1. Version published to 10.3389/fpubh.2022.831189
  2. ScreenIT

    SciScore for 10.1101/2021.10.21.21265340: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study protocol was approved by the institutional review board in University of South Carolina and relevant SC state agencies.
    Sex as a biological variableCovariates: Demographic characteristics included age at the time of COVID-19 diagnosis (18-49, ≥50), sex (female, male, and unknown), race (White, Black of African American, Asian, and other/unknown), and ethnicity (Hispanic or Latino, not Hispanic or Latino, and unknown).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All the analyses were done with SAS, version 9.4.
    SAS
    suggested: (SASqPCR, RRID:SCR_003056)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our findings need to be interpreted with caution due to the following limitations: First, our mental health data comes from a health utilization dataset. Therefore, we were not able to retrieve information of people who had mental disorders but failed to access to healthcare system due to any individual or structural level barriers. There is also missing information in the COVID-19 data. The missing data may impede the robustness of our findings. Second, the study is subject to common limitations of using ICD10 code to define mental health conditions. As other EHR based studies suggest, the quality of raw data may influence the validity of our results. Finally, we did not differentiate the severity category of the mental disorders within the same cluster. For example, we did not explore if patients with “acute” disorders have any different risk of worse COVID-19 outcomes compared to those with “recurrent” (more severe mental illness) disorders. Despite these limitations, the current study sheds lights on impacts of different clusters of mental disorders on COVID-19 clinical outcomes and the risk of presenting severe COVID-19 clinical outcomes among patients with co-occurrence of multiple clusters of mental disorders using a large statewide and real-world dataset. Our findings have significant implications for improving surveillance and triage in COVID-19 treatment considering that a high prevalence of psychiatric disorders (20.6% as of 2019) exists in the general population (...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.10.21.21265340v1 on medRxiv