Implementing a package of noncommunicable disease interventions in the Republic of Moldova: two-year follow-up data
Bibliographic record
Abstract
Noncommunicable diseases (NCDs) are a growing challenge in the Republic of Moldova. A previously reported pilot cluster randomized controlled trial aimed to determine the feasibility of implementing and evaluating essential interventions for NCDs (e.g. cardiovascular risk scoring, hypertension management, statin treatment, etc.) in primary health care in the Republic of Moldova, with a view toward national scale up. One-year follow-up data (previously published) demonstrated modest improvements in NCD risk factor identification and management could be achieved. Herein, we report the second-year follow-up data and conclude that sustainable improvements in NCD risk factor control (e.g. hypertension control) can be achieved in primary health care in low resource settings by adapting existing resources (e.g. WHO PEN) and conducting focused clinical training and support. If scaled to a national level, these improvements in risk factor control could significantly translate to reductions in premature mortality from NCDs.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".