Millions of Dollars Wasted on Preventable Hospital Readmissions in Older Adults with Chronic Lung Disease
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) exacerbations costs millions of dollars to healthcare systems, largely due to the cost of multiple hospital admissions. We analyzed multiple studies related to the impact of influenza vaccine on COPD exacerbations. We found that receiving the yearly influenza vaccine reduces the number of COPD exacerbations requiring hospital admissions in older adults. However, there are an alarming number of subjects who indicate that physicians rarely recommend influenza vaccine until later stages of disease. The Ontario Health Technology Advisory Committee recommends influenza vaccination for those with COPD during an acute episode of care and post acute episodes of care. Vaccinations would be appropriate for those without any pre-existing contraindications including those with allergies to the vaccination and history of Guillain-Barre syndrome. Careful consideration would have to be given to individuals meeting the following criteria when choosing the type of influenza vaccination: those with egg allergies, asthma, aged >50 years old, immunocompromised patients, or those in contact with immunocompromised individuals.In addition, previous studies demonstrate a surprising lack of methodological and statistical rigour. To our knowledge, our study is the first investigation of statistical methods within studies of the impact of influenza vaccine on COPD exacerbations. We will present crucial information for healthcare providers and caregivers in order to create a healthier community of elders.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".