Prevalence, characteristics and mortality of cancer patients undergoing pericardiocentesis in the United States between 2004 and 2017
Bibliographic record
Abstract
BACKGROUND: Pericardiocentesis is undertaken in patients with cancer for diagnostic and therapeutic purposes. However, there are limited data on the frequency, characteristics and mortality of patients with different cancers undergoing pericardiocentesis. METHODS: All hospitalisations of adult cancer patients (≥18 years) in the US National Inpatient Sample between January 2004 and December 2017 were included. The cohort was stratified by discharge code of pericardiocentesis and cancer, using the International Classification of Diseases. The prevalence of pericardiocentesis, patient characteristics, cancer types and in-hospital all-cause mortality were analysed between cancer patients undergoing pericardiocentesis versus not. RESULTS: A total of 19,773,597 weighted cancer discharges were analysed, out of which 18,847 (0.1%) underwent pericardiocentesis. The most common cancer types amongst the patients receiving pericardiocentesis were lung (51.3%), haematological (15.9%), breast (5.4%), mediastinum/heart (3.2%), gastroesophageal (2.2%) and female genital cancer (1.8%), whilst 'other' cancer types were present in 20.2% patients. Patients undergoing pericardiocentesis had significantly higher mortality (15.6% vs. 4.2%, p < 0.001) compared to their counterparts. The presence of metastatic disease (aOR 2.67 95% CI 1.79-3.97), weight loss (aOR 1.48 95% CI 1.33-1.65) and coagulopathy (aOR 3.22 95% CI 1.63-6.37) were each independently associated with higher mortality in patients who underwent pericardiocentesis. CONCLUSION: Pericardiocentesis is an infrequent procedure in cancer patients and is most commonly performed in patients with lung, haematological and breast cancer. Cancer patients undergoing pericardiocentesis have increased mortality, irrespective of the underlying cancer type.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".