key: cord-0834763-ltqnj6w0
authors: Clouston, S.; Luft, B. J.; Sun, E.
title: History of premorbid depression is a risk factor for COVID-related mortality: Analysis of a retrospective cohort of 1,387 COVID+ patients
date: 2020-12-19
journal: nan
DOI: 10.1101/2020.12.17.20248362
sha: 2eb8ea9561bb9a41986fe0c7740fe776a8a5c7d5
doc_id: 834763
cord_uid: ltqnj6w0

Background: The goal of the present work was to examine risk factors for mortality in a 1,387 COVID+ patients admitted to a hospital in Suffolk County, NY. Methods: Data were collated by the hospital epidemiological service for patients admitted from 3/7/2020-9/1/2020. Time until final discharge or death was the outcome. Cox proportional hazards models were used to estimate time until death among admitted patients. Findings: In total, 99.06% of cases had resolved leading to 1,179 discharges and 211 deaths. Length of stay was significantly longer in those who died as compared to those who did not p=0.007). Of patients who had been discharged (n=1,179), 54 were readmitted and 9 subsequently died. Multivariable-adjusted Cox proportional hazards regression revealed that in addition to older age, male sex, and heart failure, a history of premorbid depression was a risk factor for COVI-19 mortality. Interpretation: While an increasing number of studies have shown effects linking cardiovascular risk factors with increased risk of mortality in COVID+ patients, this study reports that history of depression is a risk factor for COVID mortality.

The outcome was days until death due among inpatients admitted for COVID-19 care. Preexisting conditions were recorded at intake. Only comorbidities that occurred frequently enough to identify statistically significant relationships were examined. Conditions examined included previously diagnosed chronic heart failure, chronic obstructive pulmonary disease, depression, diabetes mellitus, or stroke. Demographic variables included age in years, and sex. We also examined inclusion of additional comorbidities including asthma, atrial fibrillation, anxiety, cancer, cardio-arterial disease, chronic kidney disease, dementia, and obesity. We identified patients with no premorbid conditions. Sensitivity analyses additionally considered accounting for the number of comorbid conditions, which in this population ranged from 0-19 (mean = 3.13 [2.82] ) but since these analyses did not identify significant correlations, this variable was dropped from models presented.

Age in years and patient sex were also considered; age was entered in years because categorization of age usually results in substantial loss of information with the additional result being attribution of variance due to older age to aging-related conditions.

While the goal of the present study was not to study the effects of in-hospital treatments, some have noted that intubated patients were at increased risk of mortality (18). Yet, mechanical ventilation was most likely to be used among individuals with the most severe disease in the early weeks of disease management. To examine the importance of adjusting for intubation, we conducted multivariable analyses adjusting for whether an individual had been intubated at all during their inpatient stay.

The guidance regarding ventilator use to treat COVID-19 changed in April 2020. Since then, intubation rates have fallen drastically. Since mortality rates, and vulnerability to COVID-related mortality, may differ in intubated patients, we examined risk factors in intubated and non-. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint intubated patients, and also compared risk factors in patients who had been admitted prior to April 15 th when ventilation was still being used regularly versus thereafter when ventilation was much less common.

Ethics: The Internal Review Board at Stony Brook University approved this study (IRB#1586703).

Patient characteristics were reported using means and standard deviations or percentages (%).

Student's t-tests and χ 2 were used to complete unadjusted analyses. Multivariable-adjusted analyses relied on Cox proportional survival modeling was used to estimate time until death among all admitted patients when adjusting for age (19); the exact method was used to account for ties (20) . To reduce the number of predictors in the multivariable-adjusted analyses, only variables that had p-values < 0.10 were retained for multivariable-adjusted analyses. Power simulations determined that at least 1,300 patients were required to achieve multivariableadjusted power estimates (α=0.05, power=0.80); a priori projections completed in April indicated May 15 th as study closing date. Follow-up was allowed for at least twice the expected mean length of hospital stay until at least 99% of cases had resolved. Proportional hazards assumptions were tested. Model concordance (C) was reported to determine predictive accuracy; C ranges from 0.50 (poor predictor) through 0.70-0.80 (very good accuracy) to 1.00 (perfect prediction). All analyses were completed using Stata 15.1/SE [StataCorp] .

The current study examined outcomes among COVID+ patients (N=1,387; 211 deaths) admitted from 3/7-5/15/2020 (mean length of stay=13.00 [SD = 18.04] days). Outcomes were censored at death or on 9/1/2020 to allow time for patients to resolve. At time of analysis, . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint [3.57-5.53 ] increase in the risk of mortality in these models. Notably, age alone was a very good predictor of the risk of mortality in this population (C = 0.74). The predictive power was similarly good in females (C=0.77) and males (C=0.72), and in both individuals with any comorbidities (C=0.72) and among those with without any comorbidities (C=0.84).

Length of stay was significantly longer in those who died (16.08 days) as compared to those who did not (12.43 days; difference=3.65 days, p=0.007). Of patients who had been discharged . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint Age/sex-adjusted models identified intubation, chronic obstructive pulmonary disease, depression, and stroke as possible risk factors for COVID-19 mortality ( Table 2) . Diabetes and anxiety showed trends potentially indicative of risk factors. Additionally, analyses suggested that lacking any comorbidities was not associated with reduced risk of COVID-19 mortality.

Multivariable-adjusted models ( Table 3) revealed that in addition to previously described physical conditions (i.e., older age, male sex, and heart failure) a history of depression was a significant risk factor for COVID+ mortality. The proportional hazards assumption was met (χ 2(9) =10.24, P=0.332); the final model had very good accuracy (C=0.79). Table 4 ) in older (≤65 years) versus younger patients (<65 years) were substantively similar showing, for example, that depression was a risk factors for mortality in older patients though due to small numbers showed only a trend in younger patients.

Subgroup analyses suggested that the association between depression and mortality was stronger in males than females.

Sensitivity analyses did not identify factors that differed between intubated and nonintubated patients, and risk factors did not differ in the era of ventilation as compared to postventilation (after April 15 th ). Additionally, models considering the number of comorbid conditions did not change interpretation as compared to the model presented in Tables 3 or 4 .

This study sought to examine correlates of COVID-19 mortality. In the present study, we relied on a large cohort of patients admitted for COVID-19 in New York to determine that in addition to older age and male sex, a history of premorbid depression and heart failure were risk factors for COVID-19 mortality. Additionally, we determined that depression was a risk factor . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint for COVID mortality in older patients, but that depression was more predictive in men as compared to women. COVID-19 is an age-related disease that causes older infected individuals to experience more severe disease and large increases in risk of mortality (5) . Vulnerability to COVID-19 is a topic of intense interest that is important to individuals who may have an array of premorbid conditions and who may be making efforts to avoid infection. Prior work has highlighted a relatively large array of aging-related conditions such as diabetes and hypertension as potential risk factors for COVID-19. The current study supports earlier work suggesting that age is a substantively important risk factor for COVID-related mortality.

Individuals are increasingly being asked to return to work or else to justify staying home with many workers relying on comorbid conditions as a reason to justify working from home. The current study suggested that not all comorbidities confer increased vulnerability to COVID-19 mortality. However, we also found that lacking any comorbidities was not associated with reduced hazards of mortality among COVID+ patients. The present data suggest that while a number of comorbid conditions were associated with increased risk of COVID-related mortality in a medium-sized hospital in a large suburban community, that more research is warranted to better understand the mechanisms linking these risk factors to increased risk of mortality in these patients.

Our finding that depression is a risk factor for mortality in COVID+ patients supports prior analyses in a large population database (21). Mechanisms for such a relationship may include the potential for neuro-and systemic immune dysfunction that is common among individuals with depression (17). Indeed, patients with depressive symptoms have heightened levels of circulating proinflammatory cytokines including interleukin-6 (22), and heightened production of pro-. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint 1 0 inflammatory cytokines in response to stressors (23). This may be particularly important in the pathogenesis of COVID-19 given the purported crucial role that interleukin-6 plays in some initial reports of adverse outcomes related to COVID-19.

We did not find that hypertension was a risk factor for COVID-19 mortality, despite some reports to the contrary (24). Prior reports have suggested that there is some data to suggest that hypertension and diabetes both be risk factors because of their high prevalence in hospitals caring for COVID-19 (25). For example, in the largest such study (n=140), hypertension was described as being the most common comorbidity with a prevalence of 30% (26). Hypertension and diabetes are both high-prevalence age-related conditions, making them highly likely to present in a population of older adults. For example, the Centers for Disease Control and Prevention (27) estimate the prevalence of diabetes and hypertension in New York State to be 11.0% and 29.4% respectively, with estimates increasing to 24.1% and 55.6% respectively in respondents aged 65 and older. In the currently study (mean age 59.78), COVID+ patients had diabetes and hypertension at prevalence rates in this cohort that closely matched prevalence in the population, potentially highlighting the need for age-adjustment in research on studies examining predictors of COVID-19 severity and mortality.

Heart failure is a complex aging-related condition characterized by reduced functional capacity that carries reduced quality of life, increased healthcare usage, and high risk of mortality (28). Individuals with heart failure are at increased risk of dying from a range of conditions including from stroke and anemia, as well as from lung, liver, and kidney diseases (29). Heart failure is a common comorbidity in atrial fibrillation, a condition that often causes heart failure and also carries high risk of stroke (30). Together, these analyses support the increasingly . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint 1 1 common view that COVID-19 may cause a clotting disorder that accelerates mortality due to cardiovascular and cerebrovascular causes.

Though being among the earliest studies to identify pre-existing conditions that increase risk of mortality in COVID+ patients, this study is also limited in focusing on patients admitted to a single hospital on Long Island, NY. Information about race/ethnicity and socioeconomic status were not recorded. A number of studies have noted neuropsychiatric changes among COVID+ patients (12). NY. The current study did not seek to determine indicators of cardiovascular, pulmonary, or cerebrovascular indicators of COVID-19 severity but instead sought simply to identify patients for whom exposure to SARS-CoV-2 may be more deadly. Analyses did not identify dementia as a risk factor for mortality despite the fact that Alzheimer's disease, a main cause of dementia, is a neuroinflammatory condition that causes elevated levels of c-reactive protein and cytokines commonly related to COVID-19. However, since individuals with Alzheimer's disease and vascular dementia are most commonly cared for in nursing homes, where a large number of outpatient deaths are known to have occurred, this effect may be underestimated in studies such as this one that rely on inpatient samples. In the case that encephalopathy is present, but may not always become severe, future research is warranted to examine the potential for a lasting post-COVID encephalopathy among survivors. Major depression is a heterogeneous condition with a range of potential etiologies; we were unable here to examine whether subsyndromal depression or specific depressive symptoms were attributable for the increased risk identified herein. Due to limitations in the available data, we could not adjust for socioeconomic or racial/ethnic disadvantage here. Prior work suggests that these may . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint 1 2 play a significant role both in the risk of infection and in the risk of mortality. Further efforts are needed to characterize these risk factors for disease.

There is increasing agreement that COVID-19 causes changes in the central nervous system (11) and that neuropsychiatric effects may be important when characterizing COVID-19 severity (31). There is also increasing recognition that these changes may carry long-term behavioral and functional consequences (32). The current study additionally suggests that those with preexisting depression may also be at higher risk of experiencing the most severe forms of the disease.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint 1 3

Author contributions: SC completed the analyses and drafted the paper. BL provided topical expertise and edited the manuscript. ES developed the hypotheses and provided scientific oversight.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint Brain, Behavior, and Immunity 2020;

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint Table 2 ) were retained in analyses in Model 1. Model 2 incorporated all prior covariates as well as intubation experience.

. CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint 1 . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

The copyright holder for this this version posted December 19, 2020. ; https://doi.org/10.1101/2020.12.17.20248362 doi: medRxiv preprint

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