Role of C-reactive Protein and Tumor Necrosis Factor-Alpha in Differentiating between Ventilator-Associated Pneumonia and Systemic Inflammatory Response Syndrome without Infectious Etiology.
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Differential diagnosis of systemic inflammatory response syndrome (SIRS) with or without infectious cause is critically important in terms of initiating antimicrobial agents in case of infectious etiology such as ventilator-associated pneumonia (VAP). The aim of this study was to determine the diagnostic and prognostic roles of C-reactive protein (CRP) and tumor necrosis factor-alpha (TNF-α) in differentiating between ventilator-associated pneumonia and SIRS without infectious etiology. MATERIALS AND METHODS: In this prospective observational study, 91 adult intensive care unit (ICU) patients were enrolled. According to established diagnostic criteria, they were classified into three groups of "non-SIRS non-VAP", "SIRS non-VAP" and "SIRS-VAP". Serum CRP and TNF-α were measured on days 1, 3 and 7 of the study and compared using repeated measures ANOVA. RESULTS: With respect to diagnosis, there was no significant difference in the values of these biomarkers between groups (P>0.05). There was no statistically significant "time trend" for C-reactive protein and TNF-α (P>0.05). Considering both group effect and Time effect, the changes were not significantly different for CRP (P= 0.86) and TNF-α (P=0.69). In contrast, the clinical score and the clinical pulmonary infection score (CPIS) ≥ 6, had 100% specificity for diagnosing VAP. With respect to prognosis, only an unchanged or decreasing TNF-α from day 1 to day 3 was marginally associated with 28-day survival. However, day 1 and day 3 acute physiology and chronic health evaluation II (APACHE II) scores were highly associated with 28-day survival. CONCLUSION: Unlike clinical scoring system including CPIS and APACHE II, TNF-α and CRP levels were not useful as diagnostic or prognostic biomarkers for differentiating between SIRS with VAP etiology and SIRS without infectious etiology.
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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 | 0.001 | 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