Periodontal status and IOTN interventions among young hemophiliacs
Bibliographic record
Abstract
Fifty-two young individuals suffering from severe haemophilia A and B volunteered to be compared with school- and college-going students for oral health status description and subsequent management. A total of 244 students (84.42% boys and 15.58% girls) with the age group of 13-23 years were divided into two groups, A and B (controls). The purpose of this study was to increase awareness about evidence-based dental practices by oral examinations followed by comparisons of periodontal health and prevalence of malocclusions among medically compromised students and healthy controls. Results described the oral health in severe haemophilic population to be compromised with combined simplified health index score of 0.50 and Decayed/Modified/Filled Teeth (DMFT) index score of 2.07 when compared with 0.42 and 0.95, respectively, among group B. Although prevalence of malocclusion and orthodontic treatment needs among group A were higher, yet it was not confirmed as a reason for degraded dental and periodontal status. However, spontaneous and/or toothbrush (trauma)-induced gingival bleeding episodes among group A could be explained as factors discouraging oral hygiene maintenance, particularly self-administered measures. Four haemophiliacs presented with symptoms of Temporomandibular Joint Dysfunction Syndrome (TMPDS). Evidence-based oral medicine and clinical practices need to be encouraged and applied to enhance the quality of life among haemophiliacs, particularly in developing world. Dental treatment needs of haemophilic population appear to be greater and maybe incorporated in routine dental practices, at institutional and individual levels.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".