Cardiac Sarcoidosis Diagnostic Challenges and Management: A Case Report and Literature Review
Bibliographic record
Abstract
Sarcoidosis can be presented as cardiac sarcoidosis (CS), which is challenging to diagnose due to its clinical silence. Ventricular arrhythmias and atrioventricular blocks can be fatal and cause sudden death in patients with cardiac sarcoidosis. Five percent of sarcoidosis patients have clinically evident cardiac sarcoidosis. However, autopsy reports and imaging studies have shown a higher prevalence of cardiac involvement. Early recognition is important to prevent such detrimental consequences. Cardiac sarcoidosis is increasingly being diagnosed owing to increased awareness among physicians and new diagnostic tools like MRI and positron emission tomography (PET) scan replacing traditional endomyocardial biopsy. A definitive diagnosis of CS remains challenging due to the non-specific clinical findings that can present similar symptoms of common cardiac disease; therefore, the imaging and biopsies are substantial for diagnosis confirmation. Pharmacological and Implantable devices are two main therapeutic approaches in cardiac sarcoidosis, in which steroids and pacemaker therapy have shown better outcomes. This review summarizes the available data related to the prevalence, prognosis, diagnosis, and management of cardiac sarcoidosis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".