Concomitant symptomatic cardiac sarcoidosis and systemic sclerosis with cardiac involvement: a case report.
Bibliographic record
Abstract
Sarcoidosis and systemic sclerosis are two inflammatory multisystemic disorders of unknown etiology that may be life-threatening especially when there is cardiac involvement. Both diseases may coexist, however, there are very few case reports of patients with both cardiac sarcoidosis and systemic sclerosis in the literature. We report the case of a 72-year-old female who was initially referred for dyspnea. A chest computed tomography scan showed multiple hilar and mediastinal adenopathy with a non-specific opacity in the middle pulmonary lobe. FDG-PET-scan showed increased FDG uptake in the adenopathy, the middle lobe and the right ventricular free wall. Sarcoidosis was confirmed with a lung biopsy. Both electrocardiogram and echocardiogram were normal. Four months later, the patient developed a high-grade atrioventricular block deemed secondary to her cardiac sarcoidosis. Two years later, the patient was referred to a rheumatologist for severe Raynaud's symptoms, sclerodactyly and acrocyanosis. After thorough investigations, a diagnosis of limited cutaneous systemic sclerosis with systemic and cardiac sarcoidosis was made. This case demonstrates that both cardiac sarcoidosis and systemic sclerosis may coexist. In the literature, either disease may come first. In cases where cardiac symptoms appear after the diagnosis of concomitant sarcoidosis and systemic sclerosis, it might be difficult for clinicians to confirm which disease is responsible for the heart involvement. This is important since early cardiac sarcoidosis treatment should be done to prevent major complications and may well differ from systemic sclerosis treatment. In this review, we discuss the main clinical manifestations and imaging findings seen with cardiac disease secondary to sarcoidosis and systemic sclerosis.
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) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".