Pericardiocentesis versus Pericardiotomy for Malignant Pericardial Effusion: A Retrospective Comparison
Bibliographic record
Abstract
BACKGROUND: Treatment of malignant pericardial effusion remains controversial, because no randomized controlled trials have been conducted to determine the best approach, and results of retrospective studies have been inconsistent. The objective of the present study was to compare pericardiocentesis and pericardiotomy with respect to efficacy for preventing recurrence, and to determine, for those two procedures, diagnostic yields, complication rates, and effects on survival. We also aimed to identify clinical and procedural factors that could predict effusion recurrence. METHODS: We retrospectively assessed 61 patients who underwent a procedure for treatment of a malignant pericardial effusion at the Institut universitaire de cardiologie et de pneumologie de Québec between February 2004 and September 2013. RESULTS: Pericardiocentesis was performed in 42 patients, and pericardiotomy, in 19 patients. The effusion recurrence rate was significantly higher in patients treated with pericardiocentesis than with pericardiotomy (31.0% vs. 5.3%, p = 0.046). The diagnostic yield of the procedures was not significantly different (92.9% vs. 86.7%, p = 0.6). The overall rate of complications was similar in the two groups, as was the median overall survival (2.4 months vs. 2.6 months, p = 0.5). In univariate analyses, the procedure type was the only predictor of recurrence that approached statistical significance. Age, sex, type of cancer, presence of effusion at the time of cancer diagnosis, prior chest irradiation, tamponade upon presentation, and total volume of fluid removed did not influence the recurrence rate. CONCLUSIONS: Compared with pericardiocentesis, pericardiotomy had higher success rate in preventing recurrence of malignant pericardial effusion, with similar diagnostic yields, complication rates, and overall survival.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".