Quality of Reporting and Evidence in American Academy of Pediatrics Guidelines
Bibliographic record
Abstract
OBJECTIVES: The primary objectives were to evaluate the quality of development and reporting of American Academy of Pediatrics (AAP) guidelines and to determine the level of evidence underlying the recommendations. METHODS: Two reviewers scored each guideline by using the Appraisal of Guidelines for Research and Evaluation II (AGREE-II) instrument and determined the level of evidence for each recommendation in each guideline. Subgroup analyses compared AAP guidelines published before and after key changes in AAP guideline development policy and compared internal with endorsed guidelines. RESULTS: For the 28 current guidelines, the highest average scores on AGREE-II were in scope and purpose (75%) and clarity of presentation (73%). The lowest average scores were in editorial independence (17%) and applicability (30%). The only domain that improved after AAP policy updates was editorial independence (P = .01). Of the 190 treatment recommendations, 43% were based on experimental studies, 30% on observational studies, and 27% on expert opinion or no reference. Compared with early guidelines, late guidelines included a higher proportion of treatment recommendations based on experimental studies (P = .05). CONCLUSIONS: There was no clear improvement in the quality of development and reporting of AAP clinical practice guidelines over time. Routine application of AGREE-II to guideline development could enhance guideline quality. The proportion of guideline recommendations based on experimental evidence has increased slightly over time. Pediatric research agendas should be matched to vital gaps in the evidence underlying pediatric guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.538 | 0.870 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.028 | 0.030 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".