Emerging trends in the diagnosis and treatment of acromegaly in Canada
Bibliographic record
Abstract
OBJECTIVE: To evaluate demographic data and quality of care of patients with acromegaly in Canada and their evolution over time and secondly, to evaluate predictors of co-morbidities and treatment outcomes. DESIGN AND PATIENTS: Retrospective analyses of clinical, biochemical and treatment outcome data of 649 patients with acromegaly (males: 50·7%) followed from 1980 to 2010 (mean 10·2 years, SD 13·7) in eight tertiary care centres from six Canadian provinces. RESULTS: In comparison to 1980-1994, the number of patients referred with acromegaly in the last 15 years was higher with female preponderance (52·8% vs 41·4%, P = 0·01) and an older age at diagnosis (46·4 ± 14 vs 41·3 ± 12 years, P < 0·0001). Diabetes was present in 28%, hypertension in 37% and sleep apnoea in 33% of cases. Pretreatment IGF-1 levels, but not GH levels were significant predictors of diabetes (P = 0·0002) and hypertension (P < 0·0001). Eighty-nine per cent of patients underwent pituitary surgery, 64·5% had medical therapy and 22% received radiotherapy. Radiotherapy was less utilized in the past 15 years (16% vs 45%, P < 0·0001). Multimodal therapy achieved remission or control of acromegaly in 70% of patients. Patients in remission or disease control had lower initial random GH (P = 0·04) and IGF-1 levels (P < 0·0001). Hypopituitarism was present in 23% of patients and cancer in 8·5%. CONCLUSIONS: There was an increase over time of referral for acromegaly management with female predilection. Initial higher IGF-1, but not GH levels, were predictive of co-morbidities and persistent active disease after treatment. Disease remission or control was attained in 70% of patients utilizing multimodal therapy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".