A case report of capillary leak syndrome with recurrent pericardial and pleural effusions
Bibliographic record
Abstract
BACKGROUND: Capillary leak syndrome (CLS) is a rare connective tissue disease, triggered by the leak of serous fluid into the interstitial spaces, characterized by a hallmark of oedema and effusions in confined spaces. The limiting factor in CLS management appears to be its diagnosis rather than treatment, which is usually to contain the disease progression rather than a cure. CASE SUMMARY: We report a case of a 51-year-old woman with recurrent life-threatening presentations of pericardial effusions, pleural effusions, and generalized swelling of face and extremities. The only notable past medical history was of Type 1 diabetes. Numerous investigations did not lead to specific disease accounting for pericardial effusions and pleural effusions. Eventually, the diagnosis of CLS was made based on hypovolaemic shock, hypoalbuminaemia, and haemoconcentration without the presence of albuminuria. She was managed with steroids to reduce system inflammation and later with immunoglobulins and tumour necrosis factor to contain the disease process. Since her diagnosis and subsequent appropriate management, she has not had further admissions with cardiac tamponade 16 months of follow-up. DISCUSSION: The diagnosis of CLS is difficult to make unless there is a high degree of suspicion and until other causes have been ruled out. It remains a challenging condition to manage as the treatment options are limited and patients recurrently present with emergencies until the correct diagnosis is made and the optimal treatment is provided.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| 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".