Diagnostic accuracy of pleural fluid NT-pro-BNP for pleural effusions of cardiac origin: a systematic review and meta-analysis
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Bibliographic record
Abstract
BACKGROUND: Several studies have been published in the literature on the diagnostic accuracy of NT-pro-BNP for pleural effusions from heart failure in the last decade. The purpose of our study was to perform a systematic review and meta-analysis on the diagnostic accuracy of pleural fluid NT-pro-BNP for pleural effusions of cardiac origin. METHODS: MEDLINE, EMBASE, PapersFirst, and the Cochrane collaboration and the Cochrane Register of controlled trials were searched. All searches were inclusive as of March 2010. Studies were only included if the absolute number of true-positive, false-negative, true-negative, and false-positive observations were available, and the "reference standards" were described clearly. Two investigators independently reviewed articles and extracted data. Quality was assessed with the Quality Assessment for Diagnostic Accuracy Studies (QUADAS). The bivariate model for diagnostic meta-analysis was used to obtain a pooled sensitivity and a pooled specificity. RESULTS: Ten studies (total number of patients 1120) were included in the meta-analysis. The average pleural fluid NT-pro-BNP level in effusions of cardiac origin was 6140 pg/mL. The pooled sensitivity and specificity of all studies combined was 94% (95% CI: 90-97) and 94% (95% CI: 89-97) respectively. The pooled positive likelihood ratio was 15.2 (95% CI: 8.1-28.7) and the pooled negative likelihood ratio was 0.06 (95% CI: 0.03-0.11). The area under the ROC curve was 0.98 (95% CI: 0.96-0.99) and the diagnostic odds ratio was 246 (95% CI: 81-745). CONCLUSIONS: Pleural fluid NT-pro-BNP is a very useful biomarker with high diagnostic accuracy for distinguishing pleural effusions of cardiac origin.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it