Prevalence of bruising at the vascular access site one week after elective cardiac catheterisation or percutaneous coronary intervention
Bibliographic record
Abstract
AIM: To identify the prevalence and predictors of VAS bruising in the 5-7 days following cardiac catheterisation or percutaneous coronary intervention. BACKGROUND: Complication(s) of cardiac catheterisation and/or percutaneous coronary intervention (PCI) occur commonly at the vascular access site (VAS). While major complications, such as retroperitoneal bleeding, are evident before hospital discharge, the prevalence of VAS bruising in the early post-discharge period is undocumented. DESIGN: Prospective observational study. METHOD: Data were collected on 172 patients following cardiac catheterisation and/or PCI through (1) chart review, (2) pre-discharge assessment and (3) telephone follow up 5-7 days post-discharge. RESULTS: At the time of telephone follow up bruising was reported in 68.6% of all patients (n = 118), with 47% of those patients (n = 56) reporting bruises larger than 7.5 cm (3 inches). Incidence of bruising varied by access site; 73% of patients (n = 86) who had femoral access, 83% (n = 5) with femoral access plus closure device and 60% (n = 17) of patients with radial access reported bruising 5-7 days post-discharge. Bivariate analysis revealed a significant association between female sex and post discharge bruising (χ(2) 10.490, p = 0.001), with a likelihood ratio of 11.20. Abciximab use during the procedure was associated with post discharge bruising (Fisher's exact test, p = 0.045). Logistic regression analysis revealed female sex as a significant predictor of bruising after discharge (p = 0.001). CONCLUSION: This study suggests that the majority of patients will experience significant bruising at the VAS following discharge and that women may be more at risk. RELEVANCE TO CLINICAL PRACTICE: The high prevalence of post-discharge bruising after cardiac catheterisation and/or PCI has important implications for nursing education and preparation of patients prior to hospital discharge.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".