Changes in Circulating Monocyte Subsets (CD16 Expression) and Neutrophil-to-Lymphocyte Ratio Observed in Patients Undergoing Cardiac Surgery
Bibliographic record
Abstract
BACKGROUND: The characteristics of circulating inflammatory cells (leukocytes) in patients undergoing heart surgery remains poorly understood. Recently, neutrophil-to-lymphocyte ratio (NLR) and specific monocyte subsets (based on CD14/CD16 expression) have been suggested as markers of inflammation and predictors of outcomes. The present study aims to characterize the influence cardiac surgery with cardiopulmonary bypass (CPB) has on specific circulating leukocytes. METHODS: All consecutively enrolled patients had blood samples taken pre (0d), early post, (5d), and late post (90d) surgery. Complete blood counts were performed and whole leukocyte isolations were obtained from blood samples and analyzed with flow cytometry. Fluorophore-linked antibodies (CD45, CD11b, CD14, CD16) were added to the blood cell isolations and later assessed by flow cytometry. RESULTS: 17 patients were enrolled and samples obtained at 0d, 5d and 90d. We demonstrated a significant increase in NLR (2.2-fold; p=0.0028) and CD16-MFI (Mean Fluorescence Index-measure fluorescence intensity shift of CD16 in a gated cell population) early at d5 (2.0–fold; p=0.0051). Both NLR and CD16-MFI levels generally returned to normal by d90. There was a significant positive correlation between NLR and CD16-MFI (r2=0.29; p=0.0064). Adverse cardiovascular event (AE) was defined as prolonged length of hospitalization or readmission to hospital for cardiac reasons after discharge, were seen in 59% of patients (no deaths occurred). In an unadjusted analysis of AE we identified NLR as a likely predictor of AE, which meant that patients developing AE had a significantly higher baseline NLR (p=0.0065) something that was not observed with CD16-MFI (p=0.2541). CONCLUSION: Cardiac surgery is associated with a significant increase in NLR and CD16-MFI (non-classical monocytes) early after surgery corresponding to the early inflammatory phase after surgery. Furthermore, we have for the first time identified a significant correlation between NLR and CD16-MFI. While the mechanism for this relationship remains unclear, our findings support the use of a simple test of NLR as a biomarker of inflammation for predicting outcomes in cardiac surgery patients.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 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".