American Society of Anesthesiology Classification May Predict Severe Post-Tonsillectomy Haemorrhage in Children
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to identify pre- or intraoperative markers for post-tonsillectomy haemorrhage (PTH) that may help to define in-/outpatient tonsillectomy. DESIGN: A retrospective case-control study of tonsillectomized patients. SETTING: A tertiary referral university hospital. METHODS: Twenty-three children with PTH were compared with 69 tonsillectomized age- and sex-matched children without bleeding. The cohort consisted of 559 individuals under 18 years old who were scheduled for tonsillectomy or adenotonsillectomy between 1996 and 2000. MAIN OUTCOME MEASURES: Physical and analytical variables were investigated, including blood pressure, haemoglobin and haematocrit levels, coagulation profile, American Society of Anesthesiology (ASA) physical status classification, indications for surgery, obstructive sleep apnea and snoring, surgical experience, addition of adenoidectomy, method of tonsillectomy, type of anaesthesia, method of haemostasis, and total surgical time. Statistical significance was calculated by the Mann-Whitney U test and Fisher's exact test. RESULTS: The incidence of PTH was 4.11%, and all but one case were primary bleedings. Nineteen cases occurred within the first 8 hours. A possible risk marker identified was ASA class 2 (odds ratio = 5.69, p = .04). Other investigated factors were not significant. CONCLUSIONS: The ASA classification may be a predictor for PTH and could be used to select outpatients before tonsillectomy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".