Clinical Outcomes of Older Persons and Persons with Dementia Admitted for Coronavirus Disease 2019: Findings from the Philippine CORONA Study
Bibliographic record
Abstract
INTRODUCTION: The Philippine CORONA Study was a multicenter, retrospective, cohort study of 10,881 coronavirus disease 2019 (COVID-19) admissions between February and December 2020. METHODS: Subgroup analysis was done on clinical outcomes of mortality, respiratory failure, duration of ventilator dependence, intensive care unit (ICU) admission, length of ICU stay, and length of hospital stay among older persons and persons with dementia. RESULTS: The adjusted hazard ratios for mortality among the mild and severe cases were significantly higher by 3.93, 95% CI [2.81, 5.50] and by 1.81, 95% CI [1.43, 2.93], respectively, in older persons compared to younger adults. The adjusted hazard ratios for respiratory failure in older persons were increased by 2.65, 95% CI [1.92, 3.68] and by 1.27, 95% CI [1.01, 1.59] among the mild and severe cases, respectively. The adjusted hazard ratio for ICU admission in older persons was higher by 1.95, 95% CI [1.47, 2.59] among the mild cases. The adjusted hazard ratios for mortality and ICU admission in persons with dementia were higher by 7.25, 95% CI [2.67, 19.68] and by 4.37, 95% CI [1.08, 17.63], respectively, compared to those without dementia. CONCLUSION: Older age and dementia significantly increased the risk of mortality, respiratory failure, and ICU admission among COVID-19 patients.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".