Middle Turbinate Evacuation Conchoplasty in Management of Contact-Point Rhinogenic Headache in Children
Bibliographic record
Abstract
Background: Our objective is to evaluate the efficacy and outcomes of endoscopic evacuation of middle turbinate "concha bullosa" compared with lateral partial turbinectomy, in children with chronic contact-point headaches. For the research, this study is using prospective clinical trial and setting in Otolaryngology department, Tanta University Hospital, Egypt. Methods: Over three years, 60 children underwent surgery for management of contact-point rhinogenic chronic headache resulting from middle turbinate concha bullosa, using either an evacuation technique (30 children) or lateral partial turbinectomy (lamellectomy technique, 30 children) with at least 12 months' follow up. Post-operative adhesions, olfactory disorders, pain intensity, and frequency and duration of headache attacks were monitored. Results: None of the children of the evacuation group developed post-operative synechia or olfactory disorders. In the lamellectomy group, two children reported reduced olfactory capacity and an additional four children had developed adhesions. Pain intensity and frequency and duration of headache attacks improved significantly in both groups (pre- vs post-operative results), but significantly more so in the evacuation group. Conclusion: The evacuation technique may be superior to the lamellectomy technique in preventing post-operative synechia and olfactory disorders, as well as better relieving of pain intensity and frequency and duration of headache attacks. doi: http://dx.doi.org/10.4021/ijcp53w
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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".