Laparoscopic compared with open adrenalectomy for resection of pheochromocytoma: a review of 47 cases.
Bibliographic record
Abstract
OBJECTIVE: We conducted a retrospective cohort study to determine whether laparoscopic adrenalectomy (LA) is a safe and effective therapy for the management of pheochromocytoma, as compared with open adrenalectomy (OA). METHODS: We collected pertinent data on 47 pheochromocytoma resections from 44 patient charts. Perioperative outcomes of 30 LAs were compared with 14 OAs. RESULTS: Median (and standard deviation [SD]) length of postoperative stay was shorter in the laparoscopic group (3.0, SD 3.3 d v. 6.0, SD 1.1 d; p < 0.05), and tumour size was smaller (3.9, SD 2.7 cm v. 5.0, SD 2.9 cm; p < 0.05). No statistically significant differences were found for operative time or rate of postoperative complications. There were no statistically significant between-group differences in intraoperative hypertensive episodes (systolic blood pressure > 180 and/or diastolic blood pressure > 90) or hypotensive episodes (systolic blood pressure < 100 and/or diastolic blood pressure < 60) or in the need for antihypertensive or vasopressive agents. There were no intraoperative complications related to extremes of blood pressure. There were no perioperative mortalities in this series, nor was there an increased risk of recurrent disease with the laparoscopic technique. CONCLUSION: LA is safe and effective for the management of pheochromocytoma.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".