Clinical characteristics of chylothorax: results from the International Collaborative Effusion database
Bibliographic record
Abstract
Background Chylothorax is an uncommon medical condition for which limited data are available regarding the contemporary aetiology, management and outcomes. The goal of this study was to better define these poorly characterised features. Methods The medical records of adult patients diagnosed with chylothorax at 12 centres across Europe, America and South Africa from 2009–2021 were retrospectively reviewed. Descriptive and inferential statistics were performed. Results 77 patients (median age 69 years, male to female ratio 1.5) were included. Subacute dyspnoea was the most typical presenting symptom (66%). The commonest cause of chylothorax was malignancy (68.8%), with lymphoma accounting for 62% of these cases. Other aetiologies were trauma (13%), inflammatory/miscellaneous conditions (11.7%) and idiopathic cases (6.5%). At the initial thoracentesis, the pleural fluid appeared milky in 73%, was exudative in 89% and exhibited triglyceride concentrations >100 mg·dL −1 in 88%. Lymphangiography/lymphoscintigraphy were rarely ordered (3%), and demonstration of chylomicrons in pleural fluid was never ascertained. 67% of patients required interventional pleural procedures. Dietary measures were infrequently followed (36%). No patient underwent thoracic duct ligation or embolisation. Morbidity included infections (18%), and thrombosis in malignant aetiologies (16%). The 1-year mortality was 47%. Pleural fluid protein >3.5 mg·dL −1 (sub-distribution hazard ratio (SHR) 4.346) or lactate dehydrogenase <500 U·L −1 (SHR 10.21) increased the likelihood of effusion resolution. Pleural fluid protein ≤3.5 mg·dL −1 (HR 4.047), bilateral effusions (HR 2.749) and a history of respiratory disease (HR 2.428) negatively influenced survival. Conclusion Chylothoraces have a poor prognosis and most require pleural interventions. Despite the standard recommendations, lymphatic imaging is seldom used, nor are dietary restrictions followed.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".