The role of tonsillectomy in reducing recurrent pharyngitis: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To determine the evidence for efficacy of tonsillectomy in reducing the incidence of recurrent pharyngitis. DATA SOURCES: Literature databases consisting of PUBMED, SCOPUS, CINHAL AND OVID EMBASE including all languages. REVIEW METHODS: Literature search of database by 2 authors with structured criteria using an online database. Selected studies evaluated with meta-analysis. RESULTS: In four randomized, controlled trials tonsillectomy was favored over medical therapy in reducing pharyngitis. The difference was statistically significant in only one study. Overall meta-analysis results were significant, indicating that tonsillectomy results in a reduction of about 43% in the incidence of pharyngitis. The number needed to treat with tonsillectomy to prevent one sore throat per month for the first year after surgery was 11 (95% CI; 7-23). CONCLUSION: Tonsillectomy reduces the incidence of recurrent pharyngitis to a modest degree.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".