Comparison of Post-Tonsillectomy Hemorrhage rate in patients undergoing two commonly used Tonsillectomy Methods.
Bibliographic record
Abstract
Objective: To compare the cold steel method and bipolar diathermy in tonsillectomies in terms of post-tonsillectomy hemorrhage. Study Design: Randomized Controlled Trial. Setting: Department of ENT, Head & Neck Surgery, Ayub Teaching Hospital, Abbottabad. Period: 29th October 2020 to 1st June 2022. Methods: A total of 102 patients of both genders with ages 3 to 59 years undergoing tonsillectomy were included. Patients undergoing antiplatelet therapy, experiencing bleeding diathesis, possessing a high anesthetic risk, having uncontrolled medical conditions, suffering from anemia, or currently dealing with acute infections were not included in the study. Patients were divided into two groups A & B. Group A patients were operated by the Cold steel method and Group B were operated by Bipolar diathermy. All the surgeries were performed by the same surgical team. Both tonsils were fully exposed by Boyl Devi's mouth gag under general anesthesia. Complete removal of both tonsils was done with the Cold steel method in group A and by using Bipolar diathermy in group B. Post-operative hemorrhage (occurring 24 hours after surgery) without the necessity to return to the operation theatre for intervention was assessed. Results: The mean age of patients in group A was 20.0 ± 13.83 years and in group B was 19.12 ± 13.17 years. The majority of the patients 79 (77.45%) were between 3 to 30 years of age. Out of 102 patients, 63 (61.76%) were males and 39 (38.24%) were females with male to female ratio of 1.6:1. Frequency of secondary hemorrhage in Group A (cold steel method) was found in 01 (1.96%) while in Group B (bipolar diathermy) was 06 (11.76%) (p-value = 0.050). Conclusion: This study concluded that the frequency of post-tonsillectomy hemorrhage is higher in patients operated by bipolar diathermy as compared to the cold steel method.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".