35: Examining the Evidence and Strength of Recommendations Behind the 2014 Rourke Baby Record Preventive Care Guide
Bibliographic record
Abstract
Recommendations for preventive care in children, including screening maneuvers, anticipatory guidance and specific interventions, should be based on sound evidence. The health maintenance recommendations should be effective if applied, should not cause unintended consequences (harm), and should optimize the time spent in clinic between the primary care provider and family. The Rourke Baby Record (RBR) is a tool for primary care providers, which includes preventive care recommendations based on available evidence. We sought to rank recommendations for preventive care in the most recent iteration of the RBR by order of priority based on level of evidence and strength of recommendation. We also highlighted advantages and drawbacks to assigning a priority value to preventive services in children based on the current classification system. We assigned a level of evidence (low, moderate, or high) using the GRADE system and a strength of recommendation (weak or strong) for each of the recommendations in the 2014 RBR. We gave the highest values to strong recommendations supported by high quality evidence, and the lowest values to weak recommendations supported by low quality evidence. We re-examined the evidence base for strong recommendations and ranked them according to 1) importance of outcomes, 2) uncertainty and magnitude of estimates of benefits or harms, and 3) feasibility for implementation during well-baby and well-child visits. The number of preventive care recommendations in children supported by high quality studies is limited. A large majority of recommendations are based on expert consensus. Recommendations that ranked high in priority had a large potential for health improvement, including immunizations, growth monitoring, breastfeeding counseling, vehicle safety and counseling to prevent sudden infant death syndrome. We highlight some of the difficulties encountered in developing an evidence base for pediatric preventive care, including the lack of evidence for long-term health benefits and the poor methodological quality of studies. Evidence of benefits and harms from randomized controlled trials is often lacking for ethical or feasibility reasons. Except for maneuvers with a clear potential for health improvement such as immunizations, the evidence is limited for preventive care recommendations, leaving clinicians with little empirical guidance on how to implement them. While evidence of causality between preventive care and better health outcomes should be established, estimates of benefits from randomized trials should not always be sought. Observational study designs or quasi-experimental designs of high quality can make a large contribution to the evidence base in this field and should be considered in future research.
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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 | 0.147 | 0.543 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.034 | 0.018 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".