Management of Malignant Pleural Effusion with ASEPT® Pleural Catheter: Quality of Life, Feasibility, and Patient Satisfaction
Bibliographic record
Abstract
Objective. The PleurX® IPC system has been used extensively in the past. Over time, management of MPE with the PleurX system can be costly. The new ASEPT pleural catheter, through advantages in design, may ultimately show cost savings. The primary outcome of this study was to evaluate safety and efficacy of the ASEPT system.Method. This single centre, prospective study enrolled 50 patients with MPE, who were followed for as long as they were alive with a catheter. Quality of Life (QoL) was assessed before, at 2 weeks, and 6 weeks after ASEPT catheter insertion using the EORTC QLQ-C30 and LC13 questionnaires. Ease of catheter use and complications were reported by physician and community nurses.Results. 50 patients with MPE with a mean age of 64.5±1.9 , BDI of 2.8±0.9 , and ECOG score of 3.0±0.7 were recruited. No immediate or long-term complications were reported during the study period. Compared to precatheter insertion, global health status (−18, p<0.001 ), QLQ-C30 dyspnea (−39, p<0.00001 ), and LC13 dyspnea (−11, p<0.0005 ) significantly improved at 2 and 6 weeks after intervention. Provider surveys indicated favourable ease of use.Conclusion. The new ASEPT catheter offers a safe and effective option for the management of MPE.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".