Mental health and substance use associated with hospitalization among people with laboratory confirmed diagnosis of COVID-19 in British Columbia: a population-based cohort study
Bibliographic record
Abstract
Abstract Background This study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. Methods This study was performed using the BC COVID-19 Cohort, which integrates data on all COVID-19 cases, hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia as of January 15 th , 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. Findings From 56,874 COVID-19 cases included in the analyses, 2,298 were hospitalized. Models showed significant association of the following factors with increased hospitalization risk: male sex (adjusted risk ratio (aRR)=1.27; 95%CI=1.17-1.37), older age (p-trend <0.0001 across age groups with a graded increase in hospitalization risk with increasing age [aRR 30-39 years=3.06; 95%CI=2.32-4.03, to aRR 80+years=43.68; 95%CI=33.41-57.10 compared to 20-29 years-old]), asthma (aRR=1.15; 95%CI=1.04-1.26), cancer (aRR=1.19; 95%CI=1.09-1.29), chronic kidney disease (aRR=1.32; 95%CI=1.19-1.47), diabetes (treated without insulin aRR=1.13; 95%CI=1.03-1.25, requiring insulin aRR=5.05; 95%CI=4.43-5.76), hypertension (aRR=1.19; 95%CI=1.08-1.31), injection drug use (aRR=2.51; 95%CI=2.14-2.95), intellectual and developmental disabilities (aRR=1.67; 95%CI=1.05-2.66), problematic alcohol use (aRR=1.63; 95%CI=1.43-1.85), immunosuppression (aRR=1.29; 95%CI=1.09-1.53), and schizophrenia and psychotic disorders (aRR=1.49; 95%CI=1.23-1.82). Among women of reproductive age, in addition to age and comorbidities, pregnancy (aRR=2.69; 95%CI=1.42-5.07) was associated with increased risk of hospital admission. Interpretation Older age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization. Funding BC Centre for Disease Control, Canadian Institutes of Health Research. Research in context Evidence before this study Factors such as older age, social inequities and chronic health conditions have been associated to severe COVID-19 illness. Most of the evidence comes from studies that don’t include all COVID-19 diagnoses in a jurisdiction), focusing on in-hospital mortality. In addition, mental illness and substance use were not evaluated in these studies. This study assessed factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. Added value of this study In this population-based cohort study that included 56,874 laboratory-confirmed COVID-19 cases, older age, male sex, injection drug use, problematic alcohol use, intellectual and developmental disability, schizophrenia and psychotic disorders, chronic comorbidities and pregnancy were associated with the risk of hospitalization. Insulin-dependent diabetes was associated with higher risk of hospitalization, especially in the subpopulation younger than 40 years. To the best of our knowledge this is the first study reporting this finding, (insulin use and increased risk of COVID-19-related death has been described previously). Implications of all the available evidence Prioritization of vaccination in population groups with the above mentioned risk factors could reduce COVID-19 serious outcomes. The findings indicate the presence of the syndemic of substance use, mental illness and COVID-19, which deserve special public health considerations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".