Influence of Prednisone on Inflammatory Biomarkers in Community‐Acquired Pneumonia: Secondary Analysis of a Randomized Trial
Bibliographic record
Abstract
Glucocorticoids are frequently prescribed in inflammatory diseases and have recently experienced a boom in the treatment of COVID-19. Small studies have shown an effect of glucocorticoids on inflammatory marker levels, but definitive proof is lacking. We investigated the influence of prednisone on inflammatory biomarkers in a previous multicenter, randomized, placebo-controlled trial that compared a 7-day treatment course of 50-mg prednisone to placebo in patients hospitalized with community-acquired pneumonia. We compared levels of C-reactive protein (CRP), procalcitonin (PCT), leukocyte and neutrophil count between patients with and without glucocorticoid treatment at baseline and on days 3, 5, and 7 and at discharge by Wilcoxon tests and analysis of variance. A total of 356 patient data sets in the prednisone group and 355 in the placebo group were available for analysis. Compared to placebo, use of prednisone was associated with reductions in levels of CRP on days 3, 5, and 7 (mean difference of 46%, P < .001 for each time point). For PCT, no such difference was observed. Leukocyte and neutrophil count were higher in the prednisone group at all time points (mean difference of 27% for leukocytes and 33% for neutrophils, P <.001 for all time points). We conclude that after administration of glucocorticoids in community-acquired pneumonia, patients had lower CRP levels and increased leukocyte and neutrophil count as compared to the placebo group. PCT levels were not different between treatment groups. PCT levels thus may more appropriately mirror the resolution of infection compared to more traditional inflammatory markers.
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How this classification was reachedexpand
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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".