Recurrent Pericarditis in a Woman With Acromegaly Responding Favorably to Transsphenoidal Surgery
Bibliographic record
Abstract
Objective: Acromegaly is associated with increased insulin-like growth factor 1 (IGF-1), promoting systemic inflammation and cardiovascular complications. We present a patient with acromegaly who developed recurrent pericarditis, resolving soon after somatotroph pituitary adenoma resection. The objective of this report is to describe a case of uncontrolled acromegaly with recurrent, unexplained pericarditis. Case Report: A 46-year-old woman was referred after a neurologist identified a 9 mm pituitary lesion on magnetic resonance imaging. Laboratory tests showed elevated IGF-1 of 52.3 nmol/mL (12.3-32.9 nmol/L), a nonsuppressible growth hormone (GH) level of 3.8 mcg/L (<0.4 mcg/L) after a 75 g oral glucose tolerance test, confirming acromegaly. One-year postdiagnosis, the patient developed pleuritic chest pain from pericarditis with moderate-to-severe pericardial effusion. Symptoms resolved with nonsteroidal antiinflammatory drugs, colchicine and pericardiocentesis. Over 3 years she experienced multiple episodes of recurrent pericarditis. A comprehensive diagnostic workup, including rheumatologic and infectious evaluations, was negative. After transsphenoidal adenoma resection, IGF-1 normalized, and medical therapy was discontinued. Pericarditis recurred 2 months postoperatively but has not occurred again over 12 years of acromegaly remission. Discussion: Hypersecretion of GH in acromegaly leads to elevated IGF-1 levels, which affect inflammatory responses. IGF-1 can promote systemic inflammation through proinflammatory cytokines, its effects may vary depending on tissue type. In this case, resolution of pericarditis following IGF-1 normalization suggests that elevated IGF-1 levels may mediate the inflammatory process in the pericardium. Conclusion: The case suggests that acromegaly may predispose some patients to pericarditis, but its frequency and underlying pathogenesis remain unclear.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".