Restricting Indications for Sinonasal Computed Tomography in Children With Cystic Fibrosis
Bibliographic record
Abstract
OBJECTIVES To evaluate whether a low rate of exposure to sinonasal computed tomographic (CT) scans can be achieved when strict criteria are applied for their use in children with cystic fibrosis (CF) and to emphasize the importance of limiting radiation exposure in the context of the current longer life expectancy in this group of patients. DESIGN Retrospective chart review. SETTING Tertiary care children's hospital. PATIENTS The study included 277 children who were regularly followed up in the CF clinic in the last 11 years (mean duration of follow up, 7.87 years), 33 of whom underwent sinonasal CT. MAIN OUTCOME MEASURES Indications used for scanning, health professional (ear, nose, and throat specialist or pulmonologist) ordering the test, eventual modifications of ongoing treatment according to CT results, and time lapse between CT scanning and surgery. RESULTS Of 277 children with CF, 33 (12%) underwent a total of 39 sinonasal CT scans during the follow-up period (0.018 scans per patient per year of follow-up). Twenty-nine of the CT scans (74% of all cases, 90% of CT scans ordered by the ear, nose, and throat surgeon) were performed in the preoperative context and demonstrated the extent of the polypoid disease whenever present (26 cases [90%]) and the cause of nasal obstruction (20 cases [69%]). The mean period between the scanning and the surgery was 57 days (range, 0.10-173 days). Computed tomographic scans that were not meant for preoperative planning were performed in 10 cases (26%). The indications were disease evaluation (10%), ruling out a mucocele (5%); pre-lung transplantation status (5%), ruling out an intraorbital complication (3%); and headache investigation (3%). The results of the scans did not modify the management of the disease in those patients. CONCLUSIONS With the use of stringent criteria, it is possible to achieve a low rate of exposure to sinonasal CT scans in the population of children with CF. The main indication should be the preoperative planning regarding anatomy, extent of disease, and sites of nasal obstruction. The use of CT scans for disease evaluation does not seem to appreciably modify the treatment course and could be avoided.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".