Genotype and malocclusion in patients with osteogenesis imperfecta
Bibliographic record
Abstract
OBJECTS: To investigate the relationship between genotype and severity of malocclusion in osteogenesis imperfecta (OI). SETTING AND SAMPLE POPULATION: A total of 49 patients participated in this cross-sectional study (age range: 5-19 years; 28 females; diagnoses: OI type I, N = 7; OI type III, N = 11; OI type IV, N = 27; OI type V, N = 2; OI type VI, N = 2). MATERIALS AND METHODS: Sequence analysis of COL1A1/COL1A2 and other OI-related genes was compared to the Peer Assessment Rating (PAR), an index reflecting the severity of malocclusion. RESULTS: The mutation spectrum was as follows: COL1A1, N = 22; COL1A2, N = 22, IFITM5, N = 2; SERPINF1, N = 2; no mutation detected, N = 1). Compared to patients with COL1A1 mutations, patients with COL1A2 mutations had significantly higher scores for total PAR, anterior cross-bite, anterior open bite and anteroposterior buccal occlusion. Males with COL1A2 mutations had significantly higher total PAR scores than females (median 36 vs 30, P = .047, Mann-Whitney test). Exploratory correlation between age and buccal vertical occlusion was noted in patients with COL1A2 mutations (Spearman correlation: r = .46, P = .03, power = .50). Two patients with OI type V (caused by IFITM5 mutations) had total PAR scores of 44 and 21. Both patients scored high for "segment." Patients with OI type VI (due to SERPINF1 mutations) scored similar to OI type V for "centreline." Considerable difference was observed in the total PAR score between the 2 patients with OI type VI. They had total PAR of 43 and 2. CONCLUSION: Type of disease-causing mutation affects the severity of malocclusion in individuals with OI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".