Craniofacial characteristics in Crouzon's syndrome: A systematic review and meta-analysis
Bibliographic record
Abstract
The purpose of this meta-analysis was to strengthen the credibility of primary research results by combining open-source scientific material, namely a comparison of craniofacial features (Cfc) between Crouzon's syndrome (CS) patients and non-CS populations. All articles published up to October 7, 2021, were included in the search of PubMed, Google Scholar, Scopus, Medline, and Web of Science. The PRISMA guidelines were followed to conduct this study. PECO framework was applied in the following ways: Those who have CS are denoted by the letter P, those who have been diagnosed with CS via clinical or genetic means by the letter E, those who do not have CS by the letter C, and those who have a Cfc of CS by the letter O. Independent reviewers collected the data and ranked the publications based on their adherence to the Newcastle-Ottawa Quality Assessment Scale. A total of six case-control studies were reviewed for this meta-analysis. Due to the large variation in cephalometric measures, only those published in at least two previous studies were included. This analysis found that CS patients had a smaller skull and mandible volumes than those without CS.in terms of SNA° (MD = −2.33, p = <0.001, I 2 = 83.6%) and ANB°(MD = −1.89, p = <0.005, I 2 = 93.1%)), as well as ANS (MD = −1.87, p = 0.001, I 2 = 96.5%)) and SN/PP (MD = −1.99, p = 0.036, I 2 = 77.3%)). In comparison to the general population, people with CS tend to have shorter and flatter cranial bases, smaller orbital volumes, and cleft palates. They differ from the general population in having a shorter skull base and more V-shaped maxillary arches.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".