Effect of No-Reflow During Primary Percutaneous Coronary Intervention for Acute Myocardial Infarction on Six-Month Mortality
Bibliographic record
Abstract
Background: No-reflow is a serious complication that can occur during primary percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI). No-reflow is a frequent event during percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI), and it may affect cardiac prognosis. Objectives: The main objective of the study is to find the effect of no-reflow during primary percutaneous coronary intervention for acute myocardial infarction on six-month mortality. Methods: This study was conducted at Ayub Teaching Hospital Abbottabad over a period of six months (1st January 2022 to 30th June 2022). A total of 130 patients who underwent primary PCI for AMI were included. The occurrence of no-reflow during the procedure was noted, and six-month mortality was recorded. Results: Of the 130 patients included in the study, 34 (26.2%) developed no-reflow during PPCI. The mean age of the patients was 58.5 ± 9.6 years, and 73.8% were male. The most common risk factors for AMI were hypertension (52.3%), smoking (45.4%), and diabetes (36.2%). There were no significant differences in baseline clinical and angiographic characteristics between patients with and without no-reflow. Conclusions: The occurrence of no-reflow during primary PCI for AMI is associated with a higher six-month mortality rate. Further research is needed to explore strategies to prevent or mitigate the occurrence of no-reflow during primary PCI for AMI. Keywords: AMI, No-reflow, Mortality, percutaneous coronary intervention (PCI)
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".