A Case-Control Study of Repeated Adenoidectomy in Children
Bibliographic record
Abstract
OBJECTIVES: To determine the rate of repeated adenoidectomy in children and examine the risk factors associated with this condition. DESIGN A retrospective nested case-control study was performed. All cases of adenoidectomy performed at a single pediatric institution between 1990 and 2010 were examined. A total of 168 children who had undergone a repeated adenoidectomy were identified. A 1:1 matched case-control study was performed. The data were analyzed using a conditional logistic analysis. SETTING: Single tertiary pediatric institution. PATIENTS: Children aged 0 to 18 years having undergone at least 1 adenoidectomy. MAIN OUTCOME MEASURES: Risk factors associated with repeated adenoidectomy. RESULTS: A total of 10 948 adenoidectomies were performed in the study period. The rate of repeated adenoidectomy was 1.5% (168 cases). The mean age at first adenoidectomy was significantly lower in the repeated adenoidectomy group (P < .001), and children younger than 5 years at the time of adenoidectomy were 2.5 times more likely to require a repeated procedure. The case-control study identified a strong association between adenoidectomy without tonsillectomy and repeated adenoidectomy, with children who had undergone a repeated adenoidectomy having a 3.68-times higher odds (95% CI, 2.10-6.45) of having an adenoidectomy alone. CONCLUSIONS: Age younger than 5 years and adenoidectomy without tonsillectomy were identified as important risk factors for repeated adenoidectomy in children. Parents should be made aware of the increased risk of adenoid regrowth if surgery is performed at a young age. Children undergoing adenoidectomy alone should be followed up carefully to monitor for symptom recurrence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".