Neutrophil Counts Help Predict Free Wall Rupture Following St-elevation Myocardial Infarction
Bibliographic record
Abstract
PURPOSE: Free wall rupture (FWR) is a lethal complication after acute myocardial infarction; however, the un-derlying mechanisms of FWR are unclear. This study analyzes the relationship between neutrophil counts and FWR following ST-elevation myocardial infarction (STEMI). METHODS: The case group was STEMI patients with FWR and the control group was STEMI patients without FWR (case-control ratio was 1:4). The demographic data, clinical manifestation and laboratory test results were retrospectively collected and analyzed. RESULTS: Of a total of 6,712 consecutive STEMI patients, 78 patients (1.2%) had FWR. Compared with STEMI patients, patients with FWR were older and more likely to be female with an anterior infarct. White blood cell (WBC) counts were significantly higher in the FWR group. Moreover, we found that the elevated neutrophil counts mainly accounted for the elevated WBC counts. There was also a correlation between the age and neu-trophil counts (P=0.0109); as patient age increased, neutrophil counts decreased (P=0.0387). We also found no correlation between neutrophil counts and the time between myocardial infarction attack and FWR; however, when dividing these patients into FWR ≤48 h after admission to hospital for STEMI and FWR >48 h, there was a significant difference in neutrophil counts (P=0.0196). Furthermore, the results of logistic regression analy-sis showed that increased neutrophil was an independent risk factor for FWR (odds ratio: 2.404, confidence interval: 1.055-5.477). CONCLUSION: Elevated neutrophil counts were found to be the main cause of differences in WBC counts be-tween FWR and STEMI. Elevated neutrophil was an independent risk factor for FWR. This study provided clues for further research and development of therapeutics for the prevention of FWR.
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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 | 0.000 | 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 | 0.001 |
| 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".