Risk factors for 30-day COVID-19 mortality among people living with dementia in Alberta, Canada: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: People living with dementia (PLWD) were disproportionately impacted by the COVID-19 pandemic, experiencing high mortality rates in the initial waves. However, factors contributing to their increased risk of death following COVID-19 infection remain unclear. Given that PLWD are a heterogenous population with varying susceptibility to negative health outcomes, this study aimed to identify independent factors associated with 30-day COVID-19 mortality among PLWD and vulnerable subgroups of PLWD. METHODS: We conducted a retrospective cohort analysis using administrative data from March 1st 2020 to December 1st 2020, in Alberta, Canada. We examined the association between an outcome variable created to examine mortality in the 30-days following COVID-19 infection and factors related to the demographics and health (e.g., age, comorbidities), health service use (e.g., past physician utilization), and environment (e.g., community or long-term care) of PLWD in our study cohort and subgroups of our study cohort based on age, sex, and living setting (community, long-term care). RESULTS: Among our study cohort of PLWD (N = 1526), 28% of individuals died within 30 days following COVID-19 infection. After adjusting for confounders, increasing age (AOR = 2.38, 95% CI: 1.12-5.06), male sex (AOR = 2.30, 95% CI: 1.76-3.01), and living in long-term care (AOR = 5.91, 95% CI: 4.49-7.79) were associated with a higher risk of 30-day COVID-19 mortality. Additionally, congestive heart failure, diabetes with complications, and renal failure were linked to mortality among certain subgroups of PLWD. CONCLUSIONS: The 30-day COVID-19 case fatality rate was high among PLWD. PLWD who were older, male, and living in long-term care were at the greatest risk. The findings of this study demonstrate that specific groups of PLWD, based on both demographic and site-of-care-related factors, would benefit most from improved attention in future infectious disease public health planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".