Guidelines for the diagnosis and treatment of acromegaly: a Canadian perspective.
Bibliographic record
Abstract
Acromegaly is a chronic, debilitating condition caused by excessive secretion of growth hormone (GH). In the majority of cases the condition results from benign pituitary adenomas or, rarely, from ectopic production of GH-releasing hormone. Regardless of the cause, excess GH results in physical disfigurement associated with arthropathy, diabetes, hypertension, cardiac dysfunction, obstructive sleep apnea and colonic neoplasia. The death rate for acromegalic patients is 2 to 3 times higher than that of the general population, but with appropriate reduction of GH hypersecretion it tends to shift into the normal range. Treatment is thus aimed at normalizing GH secretion; eradicating or stabilizing the pituitary tumour while preserving normal pituitary function, and managing the associated complications. The treatment modalities available to achieve these objectives include transsphenoidal surgery, pharmacotherapy and radiation, or various combinations of these. This review provides an update on our current understanding of the pathophysiology of GH hypersecretion in acromegaly, the newly defined diagnostic criteria and the end point for a cure for acromegaly, and on new developments in drug treatment with the advent of slow-release forms of somatostatin analogues and the longer-acting dopamine receptor agonists, as well as in the area of radiotherapy. Its main purpose is to guide any physician involved in the diagnosis and management of patients with acromegaly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.010 |
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".