Risk factors associated with restenosis in patients with percutaneous coronary intervention
Bibliographic record
Abstract
ABSTRACT Objective: The objective of this study was to assess the risk factors associated with residual stenosis in patients with percutaneous transluminal coronary angioplasty (PTCA). Materials and Methods: A cross-sectional survey was conducted at a single health-care center among coronary artery disease patients who have undergone PTCA. Primary information including demographics and clinical characteristics, groups of pre- and postdilation balloons, and characteristics of culprits’ vessel flow were retrieved from medical records of each patient. Data were analyzed using descriptive and appropriate comparative statistics. Results: A total of 1000 patients were included in this study. The majority of patients were men (67.0%). Hypertension (HTN) and diabetes were the most common comorbid condition. Yukon Choice phosphorylcholine (PC)-elite (86.2%) was the most common stent used in patients with PTCA followed by Endeavor Sprint (12.7%). All of the patients (100%) underwent PTCA for single culprit vessel disease (SVD) while 30.2% of the patients underwent PTCA for two-vessel disease (2VD). The incidence of residual stenosis was 0.5% for SVD PTCA and 0.3% for 2VD PTCA. The 2VD group achieved thrombolysis in myocardial infarction flow Grade II postrevascularization in 98.6% of patients. Significant associations were observed between residual stenosis and various factors. HTN (odds ratio [OR]: 38.79, 95% confidence interval [CI]: 3.260-461.688; P = 0.004), diabetes mellitus (OR: 4.548, 95% CI: 0.036-63.948; P < 0.001), the use of a 0.014” × 190 cm guide (OR: 185.0, 95% CI: 25.922-1320.294; P < 0.001), and the presence of two-vessel disease (OR: 6.698, 95% CI: 1.221-36.749; P = 0.029) were found to be significantly associated with residual stenosis. Conclusion: Residual stenosis was observed in both SVD and 2VD PTCA however, presence of HTN and DM, and 2VD were identified as pronounced risk factors for residual stenosis.
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 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 | 0.000 |
| 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) | 0.000 | 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".