Clinical Predictors of Successful and Earlier Removal of Indwelling Pleural Catheters in Benign Pleural Effusions
Bibliographic record
Abstract
BACKGROUND: Indwelling pleural catheters (IPCs) are an emerging therapy for persistent benign pleural effusions. IPCs may achieve pleurodesis and be removed. OBJECTIVES: We aimed to identify factors associated with higher pleurodesis rates and earlier IPC removal in benign pleural effusions. METHODS: We reviewed a database of IPCs inserted for nonmalignant pleural effusions in the period August 2007 to June 2017 in patients who underwent medical thoracoscopy (MT). Clinical, radiologic, and pleural fluid data were recorded. Logistic regression and Cox proportional hazards were used to assess the rate of and time to pleurodesis. RESULTS: 304 IPCs were reviewed. 52 were excluded from the pleurodesis analysis due to removal for another reason, or because of an eventual diagnosis of malignant disease. The overall pleurodesis rate was 74%, and median time to pleurodesis was 42 (IQR 18-93) days. Variables with increased pleurodesis rates in multivariate analysis include Eastern Cooperative Oncology Group performance status score of ≤2 (odds ratio [OR] 4.22, 95% confidence interval [CI] 1.75-10.16) and MT (OR 5.27, 95% CI 2.74-10.11). No variables were associated with reduced pleurodesis rates in multivariate analysis. Variables that predicted earlier removal in multivariate analysis included secondary pleural infection (hazard ratio [HR] 14.19, 95% CI 4.11-48.91), % eosinophils (HR 1.03, 95% CI 1.01-1.05), and connective tissue disease (HR 2.59, 95% CI 1.20-5.57). Variables that predicted delayed removal include pleural effusion above the hilum (HR 0.54, 95% CI 0.34-0.85), liver failure (HR 0.31, 95% CI 0.16-0.60), and heart failure (HR 0.32, 95% CI 0.20-0.52). CONCLUSIONS: IPCs are safe in benign effusions. Clinicians should consider numerous factors when predicting the rate of and time to pleurodesis.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".