key: cord-0279856-b6iwlx0k authors: Qiao, S.; zhang, j.; Chen, S.; Olatosi, B.; Hardeman, S.; Narasimhan, M.; Bruner, L.; Abdoulaye, D.; Scott, C. L.; Mansaray, A. B.; Weissman, S.; Li, X. title: How different pre-existing mental disorders and their co-occurrence affects clinical outcomes of COVID-19? A study based on real-world data in the Southern United States date: 2021-10-25 journal: nan DOI: 10.1101/2021.10.21.21265340 sha: e9f7cdbf586d90186e2fcd2bfae6eed7c8094940 doc_id: 279856 cord_uid: b6iwlx0k Importance: A growing body of research focuses on the impact of pre-existing mental disorders on clinical outcomes of COVID-19 illness. 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. Objective: To explore how different pre-existing mental disorders and their co-occurrence affects COVID-19-related clinical outcomes based on real-world data. Design, Setting, and Participants: 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. Main Outcomes and Measures: Key COVID-19 clinical outcomes included severity, hospitalization, and death. COVID-19 severity was defined as asymptomatic, mild, and moderate/severe. 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. Mental disorders were categorized into internalizing disorders, externalizing disorders, and thought disorders. Results: Of the 476,775 COVID-19 patients, 55,300 had pre-existing mental disorders. There is an elevated risk of COVID-19-related hospitalization and death among participants with pre-existing mental disorders adjusting for key socio-demographic covariates (i.e., age, gender, race, ethnicity, residence, smoking). Co-occurrence of any two clusters was positively associated with COVID-19-related hospitalization and death. The odds ratio of being hospitalized was 2.50 (95%CI 2.284, 2.728) for patients with internalizing and externalizing disorders, 3.34 (95%CI 2.637, 4.228) for internalizing and thought disorders, 3.29 (95%CI 2.288, 4.733) for externalizing and thought disorders, and 3.35 (95%CI 2.604, 4.310) for three clusters of mental disorders. Conclusions and Relevance: Pre-existing internalizing disorders, externalizing 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. Outbreaking in late 2019, the coronavirus disease 2019 caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) has rapidly become a global public health crisis. The World Health Organization (WHO) declared COVID-19 a pandemic on March 11, 2020 (1) . The COVID-19 pandemic has continued to evolve causing a tremendous death toll and severe somatic complications in millions globally. People who have existing mental disorders including internalizing disorders (e.g., depression, generalized anxiety disorder, panic disorder, and posttraumatic stress disorder), externalizing disorders (e.g., conduct disorder, alcohol dependence, cannabis dependence, other drug dependence, and tobacco addiction), and thought disorders (e.g., obsessive-compulsive disorder, mania, and schizophrenia) may be particularly vulnerable (2) (3) (4) (5) (6) (7) (8) . They may be more susceptible to contracting COVID-19 and show general deterioration of mental health (2) (3) (4) (5) (6) (7) (8) . Studies show patients with suspected and diagnosed psychiatric issues have shown elevated psychiatric distress, additional anxiety symptoms, poor sleep, and quality of life concerns during the COVID-19 pandemic (9, 10) . In addition, the COVID-19 pandemic may impede the physical health of people with mental disorders because of reduced or interrupted access to healthcare services. This change in access may undermine the management of chronic diseases and exacerbate psychiatric disorders (11, 12) . Also, physical distancing requirements during the pandemic may lead to decreased social support and further worsen mental health status (13). A growing body of research focuses on the impact of pre-existing mental disorders on clinical outcomes of COVID-19 illness among this vulnerable population. According to cohort studies in South Korea and United Kingdom (UK), pre-existing mental disorders were associated with risk of severe COVID-19 clinical outcomes (hospitalization, intensive care unit [ICU] admission, invasive ventilation, or death) after adjusting for age, sex, ethnicity, somatic All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 25, 2021. ; https://doi.org/10.1101/2021. 10.21.21265340 doi: medRxiv preprint comorbidities, and regional COVID-19 influential factors (14) (15) (16) (17) . Recently, a medical record review study and a large electronic health record (EHR) case-control study in the United States found a higher mortality rate among COVID-19 patients with mental disorders compared to the general population (18, 19) . Similarly, an Italian cross-sectional study among patients hospitalized with COVID-19 showed patients with severe psychiatric disorders died at a younger age than those without a psychiatric disorder after controlling for other clinically relevant variables. Although existing literature suggests that a psychiatric history might be an independent risk factor for COVID-19 infection and mortality, there are still some knowledge gaps worth further exploration. First, no studies have systematically investigated how different clusters of pre-existing mental disorders may affect COVID-19 clinical outcomes (20) . Increasing evidence reveals that sets of mental disorders and symptoms predictably co-occur (21, 22) . That is, some mental disorders are more highly correlated with each other. Studies about the structure of psychopathology result in the incorporation of disorder clusters in research and the growth of transdiagnostic treatment (23, 24) . For example, according to an existing psychopathology structure model, i.e., "three factor model" (25) , mental disorders can be organized into three broad clusters (or higher-order factors): "internalizing disorders" (people with internalizing disorders keep maladaptive emotions and cognitions to themselves or internalize problems, e.g., depression and anxiety), "externalizing disorders" (mental disorders characterized by externalizing behaviors, maladaptive behaviors directed toward an individual's environment, which cause impairment or interference in life functioning, e.g., antisocial and substance use disorders), and "thought disorders" (disturbance in cognition that adversely affects language and thought content, and thereby communication, e.g., schizophrenia and schizotypal personality All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (25) (26) (27) . Examining the different roles of these mental disorder clusters in affecting COVID-19 clinical outcomes will advance our understanding of the intersection of mental disorders and infectious diseases in the context of the COVID-19 pandemic. Second, there is a dearth of evidence that shows how the coexistence of different clusters of mental disorders is related to COVID-19 clinical outcomes. Co-occurrence of different mental disorders are not infrequent events. Literature suggests that the co-occurrence of two or more conditions or disorders rates are very high in psychiatry and conform roughly to the rule of 50%. That is, about a half of people who meet the diagnostic criteria for one disorder meet the diagnostic criteria for a second disorder (28) . Indeed, one 40-year longitudinal assessment among a cohort of 1,037 people in New Zealand reported that 85% of the participants with a mental disorder developed accumulated comorbid diagnoses by age 45 (25) . It will be important for COVID-19 prevention and treatment to understand the impact of mental disorders (comorbidities) have on COVID-19 outcomes to inform effective surveillance and treatment. Therefore, the current study aims to understand 1) how each cluster of pre-existing mental disorders (i.e., internalizing disorders, externalizing disorders, and thought disorders) is associated with COVID- 19 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The data sources for the SC COVID-19 Cases (S3C) is described in a previous study conducted by our team (29) . Mandatory reporting of COVID-19 cases to SC Department of Health and Environmental Control (DHEC) is required by SC Law and Regulations (30, 31) . Specifically, all the key information of COVID-19 cases was collected through the SC statewide Case Report All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Table 1 for ICD-10 code). A binary variable (Any clusters of mental disorders) was created based on the status of existing mental disorders. Patients who had at least one cluster of mental disorders before the COVID-19 diagnosis were defined as "Yes" for this variable and the rest were defined as "No". Key COVID-19 clinical outcomes included severity, hospitalization, and death (29) . COVID-19 severity was defined as asymptomatic, mild, and moderate/severe. COVID-19 patients who show no symptoms were categorized as asymptomatic; those who present any of various mild signs and symptoms of COVID-19 (e.g., fever, cough, sore throat, malaise, headache, muscle pain, nausea, vomiting, diarrhea, loss of taste and smell) were categorized as mild; and those with difficulty breathing or developed pneumonia or acute respiratory distress syndrome (ARDS) were categorized as moderate/severe. Hospitalization was assessed using response to the CRF question "Was the patient hospitalized?" ("yes", "no", or "unknown"). We then dichotomized the hospitalization (1=yes, 0=no or unknown). Death was measured by the question "Did the patient die as a result of this illness?" with the same three response items ("yes", "no", or "unknown"). It was dichotomized in the same way (1=death, 0=alive or unknown). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 25, 2021. ; https://doi.org/10.1101/2021.10.21.21265340 doi: medRxiv preprint 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). We created a binary variable of rural/urban residence according to the list of rural counties designated by the Office of Rural Health Policy (33). We also included smoking (never smoker, former smoker, current smoker, other/unknown), an established lifestyle factor associated with clinical outcomes of COVID-19 disease as one of covariates in statistical analysis (34) . Descriptive statistics were computed for all study variables using means and standard deviations (SD) for the continuous variables and frequency counts and percentages for the categorical variables. Differences by each cluster of mental disorders by key COVID-19 outcomes (i.e., severity, hospitalization, and death) and covariates were tested using a t-test or Chi-square tests as appropriate. A Venn Diagram was used to illustrate patterns of co-occurrence of different clusters of mental disorders among the participants. We examined the association between preexisting mental disorders cluster and the clinical outcomes of COVID-19 disease using logistic regression or multinomial logistic regressions for COVID-19 severity, hospitalization, and death, as appropriate separately. Models were fully adjusted for age, gender, race, ethnicity, residence, and smoking status. The models for COVID-19 hospitalization and death were also adjusted for the COVID-19 severity. To investigate if co-occurrence of different cluster of mental disorders associated with COVID-19 clinical outcomes, we further investigate the three-way interactions among three clusters of mental disorders in the final regression models. Forest plots were created based on the final regression models to virtually present the impacts to COVID-19 clinical All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 25, 2021. ; https://doi.org/10.1101/2021.10.21.21265340 doi: medRxiv preprint outcomes by all the factors including pre-existing mental disorders, co-occurrence of different clusters of mental disorders, and other covariates. All the analyses were done with SAS, version 9.4. A p<0.05 was considered statistically significant for all 2-sided tests. Of the 476,775 adult COVID-19 patients included in the study, 421,475 patients had no recorded clinical diagnosis of a mental disorder and 55,300 patients who had at least one cluster of mental disorders before the COVID-19 diagnosis ( Table 2) . Among the overall sample, 58.3% were aged 18-49 years old (mean=45.7, SD=18.6), 52.9% were female, 47.6% were White, 20.4% were Black, 5.1% were Hispanic/Latino, and the majority were living in urban area (87.0%). Over half (54.0%) patients were identified as asymptomatic cases, 33.3% as mild cases, and 12.7% as moderate/severe cases. About 4.4% of all patients (n=20,995) were hospitalized and 1.9% (n=8,924) died due to COVID-19. Among the 55,300 patients who had at least one preexisting cluster of mental disorders, 8.8% (n=4,848) were hospitalized and 3.9% (n=2,163) died due to COVID-19. Of the 55,300 patients with pre-existing mental disorders, 23 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Generally, we observed significant differences in age, gender, race, ethnicity, residence, and smoking status between participants with and without pre-existing mental disorders (Table 2 ). For example, there was a higher proportion of non-Hispanic/Latino among participants with pre-existing mental disorders, compared with those without these conditions. However, the patterns of the socio-demographic difference between participants with and without pre-existing mental disorders varied by the cluster of mental disorders. Higher proportions of participants with internalizing disorders were older (≥50 years), female, White, non-smokers, and lived in rural areas. Higher proportions of participants with externalizing disorders were males, Black/African American, former/ current smokers, and lived in rural areas. We found higher proportions of participants with thought disorders were older (≥50 years), Black/African American, non-smokers, and lived in rural areas. Regarding the clinical outcomes of COVID-19, there was a higher proportion of hospitalization for COVID-19 among participants with pre-existing mental disorders, compared to those without respective cluster of mental disorders (Internalizing disorders: 10 (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The multivariate results suggest an elevated risk of COVID-19-related hospitalization and death among participants with pre-existing mental disorders adjusting for key socio-demographic covariates (i.e., age, gender, race, ethnicity, residence, smoking) ( Co-occurrence of any two clusters was positively associated with COVID-19 hospitalization and COVID-19-related death (See the forest plot in Figure 2 and Table 3 ). Specifically, compared to those with no pre-existing mental disorders, the odds of being All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Using a psychopathology structure model of mental disorders (i.e., the three-factor model) and leveraging the EHR data for state-level cohort of COVID-19 patients in SC, United States, we have explored the association between pre-existing mental disorders and severity of COVID-19 from a new perspective. That is, we examined how each cluster of mental disorders (i.e., internalizing disorders, externalizing disorders, and thought disorders) could affect COVID-19 clinical outcomes (i.e., severity, hospitalization, and death) and how the co-occurrence of multiple clusters of mental disorders associates with these clinical outcomes after controlling for other key sociodemographic confounders (e.g., age, race, ethnicity, urban/rural residence). Our findings are aligned with existing evidence of a positive association between preexisting mental disorders and COVID-19 related hospitalization and death. Several studies have posited potential reasons and interpretations regarding the underlying mechanism of pre-existing mental disorders as a risk factor of COVID-19 clinical outcomes, including immune dysregulation processes, genetic predisposition towards psychiatric disorders, and healthcompromising lifestyle (20) . The activation of the endocrine stress axis at different levels, such as hypothalamic-pituitary-adrenal (HPA) axis which can lead to altered glucocorticoids and suppressed cell-mediated and humoral immunity is widely reported among people with mental disorders (35) (36) (37) (38) . The immune dysfunction, subsequently, contributes to high risk of SARS-CoV-2 infection. The inflammatory cytokine overproduction induced by glucocorticoid receptor resistance may be responsible for the damage of the lungs and correlated with disease deterioration and fatal COVID-19 (39) (40) (41) . Recent studies also demonstrate a strong genetic link between psychiatric disorders and general infections including COVID-19. Health behavioral changes in response to stress (e.g., altered diet and exercise patterns, smoking and alcohol abuse) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 25, 2021. ; https://doi.org/10.1101/2021.10.21.21265340 doi: medRxiv preprint may also explain the observed associations between mental disorders and COVID-19 clinical outcomes (42) . In addition, we discovered that pre-existing thought disorders (e.g., mania, schizophrenia, obsessive-compulsive disorders [OCD]) may be related to COVID-19 hospitalization and death in the greatest magnitude. Thought disorders are usually considered as severe mental disorders. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. We found that people with 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 (either internalizing or externalizing disorder). Given that having pre-existing thought disorders is a high-risk factor of worse COVID-19 clinical outcomes, it is reasonable that cooccurrence of thought disorders and either internalizing disorders or externalizing disorders indicates more vulnerability compared to the single cluster of pre-existing mental disorders. Notably, the co-occurrence of internalizing and externalizing disorders has increased risk of hospitalization and death caused by COVID-19 compared to a single condition. Internalizing disorders, like depression and anxiety disorders have been found to be associated with immuneinflammatory disturbances, which may contribute to severe clinical outcomes of COVID-19 (49, 50) . The lifestyle changes following the occurrence of internalizing disorders, such as smoking and alcohol abuse, may also contribute to altered risk to COVID-19 infection and worse outcomes. Externalizing disorders, especially long-term use of tobacco, alcohol, and other drugs, are also closely related to cardiovascular, pulmonary, and metabolic diseases, which are highrisk preconditions for COVID-19 outcomes (51, 52) . In addition, some studies indicate a genetic association between psychiatric disorder and COVID-19 (53) . For example, one genome-wide association study suggests that genetic liability to depression and substance misuse is associated with severe COVID-19 outcomes (hospitalization or death) (54) . Although our results suggest that pre-existing mental disorders are risk factors of COVID-19-related hospitalization and death, it is interesting that pre-existing mental disorders may be associated with decreased risk of mild cases. Extant literature suggests that pre-existing All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 25, 2021. ; https://doi.org/10.1101/2021.10.21.21265340 doi: medRxiv preprint chronic illness and therapeutic options may affect the prognosis of COVID-19 and have a possible protective effect against COVID-19. For example, allergic sensitization in asthma is related to lower expression of angiotensin-converting enzyme (ACE)2 receptors showing a potential protective effect (55) . In addition, the use of inhaled corticosteroids is generally safe and associated with decreased risk of hospitalization (56) . However, there is a dearth of evidence regarding whether treatment for mental disorders affect prognosis of COVID-19. Given the high rate of comorbidity between mental disorders and chronic somatic disease, the pre-existing chronic conditions and the treatment among these patients could be complicated. Further studies are needed to identify potential confounders and explain the "protective effect" (56) . In addition, the high-risk drug-drug interactions (DDIs) that may occur in COVID-19 treatment accompanied by psychotropic drug prescription warrants multidisciplinary study engaging both psychiatrists and infectious disease physicians (57) . The strengths of the current study include categorizing mental disorders guided by a psychopathology structure model, a statewide cohort, being representative of both impatient and outpatient COIVD-19 cases and generating real-world evidence. Utilization of the statewide standardized case report form enables us to systematically collect comprehensive information on COVID-19 clinical outcomes. 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 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. settings. Rural areas persistently face a lack of mental health professionals and mental health service infrastructure (59). Compared to Whites, African Americans have less access to mental health services and less likely to utilize necessary mental healthcare. They are less satisfied with professional mental health services and have higher rates of dropout from these services (60). Furthermore, this group faces higher risk of COVID-19 infection, endures more barriers to access to health resources, and shows disproportionally high morbidity and mortality of COVID-19. More empirical evidence and policy studies are needed to illustrate and address the intersection between mental health, COVID-19, and social deprivation/vulnerability from the perspective of health equity and structural racism. In summary, the current study suggests that people with mental disorders, especially thought disorders and co-occurrence of multiple clusters should been identified as high-risk population for severe consequences of COVID-19, requiring enhanced preventive, triage, and treatment strategies. Future studies need to further differentiate the impacts of mental disorders on COVID-19 clinical outcomes by severity/stage of the illness (e.g., acute vs. stabilized); include a comprehensive set of social determinates of health in the analysis; and explore the interaction between different clusters of mental disorders and pre-existing somatic conditions. Summers-Gabr NM. 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Mental Illness: Prevalence of Any Mental Illness (AMI) Among U.S. Adults Overall population The results for Asian group were not reported due to policy. Chi-square tests for all the characteristics variables are all significant (i.e., P<.05). Note: Logarithm of odds ratio was used in developing the forest plots given large value of some odds ratios. We then use zero instead of one as the criteria of significance. (a) severity (mild vs asymp); (b) severity (severe vs asymp); (c) hospitalization (yes vs no); (d) death (yes vs no).