P.142 Characteristics of a large cohort of patients with acromegaly with surgical outcome by geographic living location
Bibliographic record
Abstract
Background: Acromegaly is a rare disease caused by a growth hormone-secreting pituitary adenoma which results in potentially debilitating skeletal, cardiac and gastrointestinal disease. Surgical resection can be curative, but in Southern Alberta, skull base surgeons and multi-disciplinary pituitary teams work at a single centre, raising the question of whether rurally-dwelling patients experience worse outcomes. We aim to characterize post-surgical remission rates by living location in acromegaly patients at our institution. Methods: A retrospective chart review supplemented a single surgeon database of patients with acromegaly treated at our centre (February 2011-April 2022) with demographic, endocrinological, and surgical variables. Statistical analysis was performed using Stata Version 17. Results: Our cohort included 47 cases of acromegaly (53% male), all treated with endoscopic transsphenoidal surgery. The average age at first operation was 46.7 years (20-69 years), 77% were macroadenomas, and the average adenoma size at initial MRI was 16mm. 54.55% of the urban cohort achieved immediate post-surgical remission, versus 28.57% of the rural cohort (OR:3.0(95%CI:0.67,15.51)). Conclusions: The characteristics of our cohort agree with the literature. The odds of immediate post-surgical remission in urban-dwelling patients was 3.0 times that of rurally-dwelling patients. Our results failed to meet statistical significance likely due to lack of power secondary to sample size.
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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 | 0.000 | 0.002 |
| 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) | 0.005 | 0.001 |
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".