Abstract 11695: The Kinetics of Circulating Monocyte Subsets and Microbial Translocation in the Acute Phase of ST-Elevation Myocardial Infarction Reveals Prognostic Values for Cardiovascular Outcomes
Bibliographic record
Abstract
Introduction: In experimental myocardial infarction (MI), a rise in cell counts of circulating monocyte subsets contributes to impaired myocardial healing, and to atherosclerotic plaque destabilization.The underlying pathophysiological mechanisms for the post-MI monocytosis and the prognostic role of monocyte subsets in patients suffering ST-elevation MI (STEMI) are still unclear. Hypothesis: The kinetics of the three monocyte subsets (classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes) and gut microbial translocation are associated with cardiovascular outcomes after STEMI. Methods: In 100 STEMI patients treated with primary percutaneous coronary intervention (PCI), monocyte subsets and microbial translocation markers (lipopolysaccharide [LPS] and D-lactate) were measured on Days 1, 2, 3, 5 and 7 of STEMI onset, compared with 35 stable coronary heart disease patients and 35 healthy volunteers. All STEMI patients were prospectively followed for the first occurrence of an adverse cardiovascular event. Results: From Day 1 to Day 7, a parallel increase in CD14++CD16- cell counts, CD14++CD16+ cell counts, and gut permeability markers was observed, with peak levels on Day 2. During a median follow-up of 1.5 years, 25 events were recorded. Univariate Kaplan-Meier analysis revealed that Day 2 CD14++CD16- cell counts ( P =0.022), CD14++CD16+ cell counts ( P =0.024) and Δ LPS (Day 2 – Day 1; P =0.027) each predicted the primary endpoint when stratified by median values. After adjustment for confounders, Day 2 CD14++CD16+ monocyte counts showed the strongest predictive value (per SD increase: hazard ratio [HR]: 2.127; 95% CI 1.313 to 3.446; P =0.002) for cardiovascular events. Conclusions: The expansion of the CD14++CD16+ monocyte subset on Day 2, which is associated a transient increase in microbial translocation, independently predicts adverse cardiovascular outcome in STEMI patients treated with primary PCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".