Feasibility of a cluster-randomized influenza vaccination trial in U.S. nursing homes: Lessons learned
Bibliographic record
Abstract
Influenza severity increases and vaccine effectiveness decreases with age. High-dose influenza vaccine (HD) with quadruple the antigen of standard-dose (SD) vaccine is more efficacious in community-dwelling persons 65 years and older. We evaluated the feasibility of recruiting and randomizing Medicare certified nursing homes (NHs) for a pragmatic cluster-randomized trial comparing HD vs. SD (NCT1720277). Residents were long-stay and at least 65 years old. NH leadership agreed to standard of care random assignment with HD (Fluzone® High-Dose) or SD (Fluzone®) influenza vaccine for their facility for the 2012-2013 influenza season. We used Minimum Data Set (MDS) 3.0 and Vital Status records for pre-specified clinical outcomes: 1) all-cause hospitalization, 2) NH mortality, and 3) functional decline. Intent-to-treat analyses were performed at the resident-level using Cox proportional hazards, multivariable Poisson, and logistic regression models accounting for clustering by facility. We randomized 39 NHs (19 SD and 20 HD), coordinated vaccine delivery, implemented web-based data collection, and accessed MDS data, demonstrating feasibility. There were 2,957 eligible residents (SD 1496; HD 1461); characteristics were similar between groups. A total of 301 (20.1%) of SD and 197 (13.5%) of HD allocated residents were ever hospitalized, (adjusted relative risk 0.680; 95% CI: 0.537, 0.862; p = 0.001). NH mortality was 274 (18.3%) SD vs. 249 (17.1%) HD, adjusted relative risk 0.834; 95% CI: 0.678, 1.027; p = 0.087). There were no differences in decline in functional status (13.4 vs. 13.8%, adjusted relative risk 0.994; 95% CI: 0.774,1.278; p = 0.965). We demonstrate that a pragmatic large-scale trial is feasible in a NH setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".