TONSILLECTOMY IN PAEDIATRIC POPULATION
Bibliographic record
Abstract
Objectives: To compare mean operative time and Intra operative blood lossbetween bipolar electro dissection and cold dissection tonsillectomy in paediatric population.Study Design: Randomized controlled trial. Place and Duration: Department of ENT and Headand Neck Surgery, Continental Medical College, Hospital Lahore, from 1 January 2015 to 30September 2015. Materials and Methods: This study included 164 patients of age group 4 to12 years of either gender undergoing tonsillectomy. The patients were divided into two equalgroups designated as A and B each having 82 patients using simple random sampling. Patientsin group A were operated for tonsillectomy by bipolar electrocautry while group B underwenttonsillectomy by cold steel dissection method. All patients in both groups were assessed foroperating time and intra-operative blood loss. Results: Out of 82 cases of Bipolar DissectionGroup 49(60%) patients were male and 33(40%) patients were female. Whereas in 82 casesof Cold Dissection Group 51(62%) patients were male and 31(38%) patients were female.Mean age of patients was 7.2(SD ± 1.97) years. Mean operation time was 15 minutes withstandard deviation ± 1.21 in group A as compared to group B where mean operation time was20 minutes with standard deviation ± 1.87. Mean blood loss was 7 ml with standard deviation± 2.53 in patients of group A as compared to Patients in group B who mean blood loss of 30ml with standard deviation ± 3.46. Group A had statistically significant lower operative time andblood loss than group B. Conclusion: Tonsillectomy with bipolar electro dissection method ismuch better than cold steel dissection method. It has an advantage of less blood loss duringsurgery. It significantly reduces intra operative time.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".