Diagnostic Utility of Pleural C-Reactive Protein and Procalcitonin for Parapneumonic Pleural Effusion: A Head-to-Head Comparison Study
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Bibliographic record
Abstract
Introduction: The diagnostic utility of pleural fluid C-reactive protein (CRP) and procalcitonin (PCT) for parapneumonic pleural effusion (PPE) is a subject of ongoing investigation. There remains lack studies comparing their diagnostic accuracy in a head-to-head manner. Furthermore, the incremental diagnostic value of their combination over a single marker and the net benefit of them remains unknown. Methods: This prospective study enrolled participants presenting with undiagnosed pleural effusion, subsequently measuring their pleural levels of CRP and PCT. A diagnostic model that integrated both biomarkers was constructed using logistic regression analysis. The diagnostic performance and net benefit of CRP, PCT, and the composite model were assessed through receiver-operating characteristic (ROC) curve analysis and decision curve analysis (DCA). Results: The study included 32 PPE patients and 121 patients without PPE. The area under the ROC curve (AUC) for CRP was 0.73 (95% confidence interval [CI]: 0.63-0.83), with a sensitivity of 0.71 (95% CI: 0.55-0.87) and a specificity of 0.68 (95% CI: 0.59-0.77) at a threshold of 10 mg/L. In contrast, the AUC for PCT was 0.58 (95% CI: 0.46-0.69), with sensitivity and specificity rates of 0.50 (95% CI: 0.33-0.67) and 0.65 (95% CI: 0.56-0.74) at a threshold of 0.1 ng/mL, respectively. Notably, the AUC for the diagnostic model was comparable to that of CRP alone at 0.73 (95% CI: 0.63-0.82). DCA showed that applying CRP provided a net clinical benefit, while PCT did not. Conclusion: Pleural fluid CRP possesses moderate diagnostic capability for PPE, while PCT exhibits limited diagnostic utility. Additionally, the combined application of CRP and PCT does not confer any significant enhancement in diagnostic accuracy over the use of CRP alone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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