Malignant pleural effusions in lymphoproliferative disorders
Bibliographic record
Abstract
In order to determine variables that correlate with malignant pleural effusion and mortality in patients with lymphoproliferative disorders and pleural effusion, a retrospective study was performed. Clinical data of hospitalized patients with a lymphoid malignancy and pleural effusion who underwent thoracentesis from January 1993 to December 2002 were collected. A logistic regression analysis was carried out to determine prognostic variables that predict malignant pleural effusion and hospital mortality. There were 86 patients who were admitted on 91 occasions. The median age was 70 years (range 4 - 92) and the male:female ratio was 44:42. Sixty-four patients (74%) had advanced disease, 43 (50%) had received prior chemotherapy and 9 (10%) were in remission. Of 91 cases of pleural effusions, 44 (48%) were bilateral, 80 (88%) were exudates and 48 (53%) were due to malignant involvement of pleura. In multivariate analysis, symptomatic pleural effusion (odds ratio 10.3, 95% confidence interval 1.7 - 98.3), pleural fluid mesothelial cell count < 5% (odds ratio 8.0, 95% confidence interval 1.4 - 58.2), pleural fluid:serum lactate dehydrogenase (LDH) > or =1 (odds ratio 6.4, 95% confidence interval 1.2 - 45.6) and pleural fluid lymphocyte percentage > or =50 (odds ratio 6.4, 95% confidence interval 1.2 - 50) were significantly correlated with malignant effusion. A secondary cancer (odds ratio 11.9, 95% confidence interval 2.3 - 88.8), pleural fluid:serum LDH > or =1 (odds ratio 10.9, 95% confidence interval 2.6 - 64.9), and pneumonia (odds ratio 6.4, 95% confidence interval 1.7 - 28.6) were significantly correlated with hospital mortality. In conclusion, malignant pleural effusion is the common etiology of pleural effusion in patients with lymphoid malignancy. Many clinical and cytochemical markers have discriminatory values in identifying malignant effusion. A high pleural fluid to serum LDH level correlates with malignant pleural involvement and hospital mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".