Bibliographic record
Abstract
Abstract This review examines the evolving landscape of constrictive pericarditis (CP) through analysis of literature spanning 1932 to 2025, sourced from PubMed, Scopus, and Google Scholar using key terms related to the etiology, clinical features, diagnosis, and treatment of CP. Eligible literature included original research articles, systematic and narrative reviews, case reports, expert consensus statements, and guidelines from professional societies. CP is a chronic pericardial disease resulting in impaired ventricular filling and heart failure symptoms. While previously dominated by tuberculosis and idiopathic cases, its modern etiological profile has shifted significantly. This review explores the evolving causes, clinical features, diagnostic advances, and treatment strategies of CP in the current medical practice. Modern causes of CP include prior cardiac surgery/percutaneous intervention, radiation therapy, autoimmune diseases, viral pericarditis, and uremia associated with end-stage renal disease. Modern imaging modalities—particularly echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging—have improved diagnostic accuracy and helped differentiate CP from other causes of heart failure. Features such as pericardial late gadolinium enhancement and elevated inflammatory markers help identifying reversible subset of the disease, which may respond to anti-inflammatory therapy. In chronic, fibrotic cases, surgical pericardiectomy remains the definitive therapy, with outcomes improved by early diagnosis and appropriate timing of surgery. CP is no longer a relic of the past, but a dynamic condition shaped by modern medicine. Recognizing its evolving etiologies is critical for timely diagnosis and individualized treatment. With advances in imaging and inflammation-targeted therapies, opportunities exist to improve outcomes and reduce reliance on surgery in selected cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".