Clinical and socioeconomic characteristics of older adults with COVID-19: A protocol for a rapid systematic review
Bibliographic record
Abstract
SUMMARY The aim of this rapid systematic review is to analyze the prevalence of clinical, socioeconomic, and demographic characteristics, laboratory and imaging findings, diagnostic tests, and treatment information of older adults with COVID-19. To conduct this systematic review, the Cochrane Handbook recommendations will be followed. Patients aged 60 years or older with a confirmed diagnosis of SARS-CoV-2 infection will be included. A comprehensive literature search will be performed in the following databases: MEDLINE via PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Latin American and Caribbean Health Sciences Literature (LILACS), Spanish Bibliographic Index on Health Sciences (IBECS) and Epistemonikos COVID-19 L·OVE platform. No language restrictions will be applied. To assess the methodological quality of the included studies and the certainty of the evidence, the Newcastle-Ottawa Scale, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used. The meta-analysis will be performed using R software. We believe this rapid systematic review will be able to summarize the currently available evidence on clinical, socioeconomic characteristics, and management of COVID-19 in older adults. Therefore, it will help implement adequate strategies to fight the pandemic and assist in understanding the clinical profile of older patients with COVID-19, providing data with due scientific support upon which to base future choices of procedures and interventions.
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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 | 0.063 | 0.082 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.069 | 0.009 |
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".