Does the Application of X-Ray Contrast Agents Impair the Clinical Effect of Intravenous Recombinant Tissue-Type Plasminogen Activator in Acute Ischemic Stroke Patients?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Experimental data suggest a negative interaction between x-ray contrast agents and fibrinolytic efficacy of recombinant tissue-type plasminogen activator (rtPA). We hypothesized that the application of a contrast agent before intravenous thrombolysis with rtPA reduces its clinical efficacy in acute ischemic stroke. METHODS: We retrospectively studied consecutive ischemic stroke patients receiving contrast agents for computed tomography angiography before intravenous treatment with rtPA. We compared functional outcomes with an historical control group from the Canadian Alteplase for Stroke Effectiveness Study who did not receive contrast agents before thrombolysis with rtPA. Primary end point was favorable functional outcome at 90 days defined as modified Rankin Scale scores 0 to 2. We performed logistic regression analysis and a propensity score matching analysis to estimate the effect size of contrast agent use as a negative predictor of outcome. RESULTS: We identified 111 patients for the computed tomography angiography and 1119 patients for the control group. Proportions of favorable functional outcome were 47.7% (53/111 patients) for the computed tomography angiography group and 49.5% (542/1094 patients) for the control group (P=0.77). Adjusted probabilities for favorable outcome were 0.48 (95% CI, 0.37-0.58) and 0.51 (95% CI, 0.47-0.54), respectively. Contrast use was associated with reduced odds of favorable outcome (OR, 0.62(;) 95% CI, 0.38-0.99). Propensity score matching suggested a larger effect size (OR, 10.0%; 95% CI, 0.5%-19.3%). CONCLUSIONS: Our study did not show a significant negative clinical effect of x-ray contrast agents applied before intravenous thrombolysis with rtPA. However, to confirm a possible small negative interaction between contrast agents and rtPA, additional experimental and prospective clinical studies are needed.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".