Hispanic Secondary Stroke Prevention Initiative Design: Study Protocol and Rationale for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Hispanic-Latino populations face a disproportionate stroke burden and are less likely to have sufficient control over stroke risk factors in comparison with other ethnic populations. A promising approach to improving chronic health outcomes has been the use of community health workers (CHWs). OBJECTIVE: The objective of this randomized controlled trial is to evaluate the effectiveness of a CHW intervention among Latino patients at risk of recurrent stroke. METHODS: The Hispanic Secondary Stroke Prevention Initiative (HiSSPI) is a randomized clinical trial of 300 Latino participants from South Florida who have experienced a stroke within the last 5 years. Participants randomized into the CHW intervention arm receive health education and assistance with health care navigation and social services through home visits and phone calls. The intervention also includes a mHealth component in which participants also receive daily text messages (short message service). The primary outcome is change in systolic blood pressure at 12 months. Other secondary outcomes include changes in low-density lipoprotein, glycated hemoglobin, and medication adherence. RESULTS: Study enrollment began in 2015 and will be completed by the end of 2018. The first results are expected to be submitted for publication in 2020. CONCLUSIONS: HiSSPI is one of the first randomized controlled trials to examine CHW-facilitated stroke prevention and will provide rigorous evidence on the impact of CHWs on secondary stroke risk factors among Latino individuals who have had a stroke. TRIAL REGISTRATION: ClinicalTrials.gov NCT02251834; https://clinicaltrials.gov/ct2/show/NCT02251834 (Archived by WebCite at http://www.webcitation.org/72DgMqftq). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/11083.
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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 | 0.066 | 0.076 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.099 | 0.019 |
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".