Top studies relevant to primary care from 2018: From PEER.
Bibliographic record
Abstract
OBJECTIVE: To summarize high-quality studies for 10 topics from 2018 that have strong relevance to primary care practice. QUALITY OF EVIDENCE: . MAIN MESSAGE: Topics of the 2018 articles include whether low-dose acetylsalicylic acid improves health outcomes like cardiovascular disease (CVD); whether a low-carbohydrate diet is better than a low-fat diet for weight loss (and whether genetics matter); whether vaginal estradiol is superior to placebo for vulvovaginal symptoms of menopause; whether opioid management is better than nonopioid management for chronic back or osteoarthritis pain; whether additional water intake will decrease recurrent urinary tract infections; whether omega-3 fatty acids prevent CVD or reduce dry eyes; whether the new drug icosapent improves CVD; whether bath additives help eczema; whether acetaminophen can prevent recurrent febrile seizures; and recommendations for glycemic targets in diabetes based on reviews of evidence and other guidelines. Five "runner-up" studies are also briefly reviewed. CONCLUSION: Research from 2018 produced several high-quality studies in CVD but also spanned the breadth of primary care including pediatrics, women's health, and pain management, among other areas.
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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 | 0.026 | 0.170 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.047 | 0.008 |
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".