Abstract WP420: Incidence of Contrast Induced Nephropathy Among Different Stroke Subtypes After Adoption of New Emergency Brain Imaging Protocol for Acute Stroke - A Single Center Perspective
Bibliographic record
Abstract
Introduction: Studies demonstrating benefits of mechanical thrombectomy for large vessel occlusion (LVO) in acute ischemic stroke (AIS) has led to increased use of CT angiogram (CTA). Similarly, CTA is frequently performed to diagnose cerebrovascular pathology after intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH). Such contrast-enhanced CT (CECT) studies in stroke population are often associated with contrast induced nephropathy (CIN). However, incidence of CIN after adoption of increased use of CTA to diagnose LVO for possible mechanical thrombectomy is largely unknown. Hypothesis: We investigated the incidence of CIN in acute stroke population after adoption of CECT protocol to diagnose LVO and compared it to patients undergoing CECT study for other indications. Methods: Single-center retrospective chart review of patients presenting to the emergency room and investigated with CECT between January 2015 and December 2017. A rise in serum creatinine (SCr) 1.5 times the presenting SCr within first 72 hours of CECT defined CIN. Non-parametric Chi-squared tests were used to make intergroup comparison and a p-value of <0.05 was considered significant. Results: Nine hundred and forty-seven charts of patients undergoing CECT were reviewed. Patients with ICH [30/132 (22.7%)] and SAH [17/126 (13.5%)] had significantly higher incidence of CIN as compared to those with AIS [11/150 (7.3%)] and non-stroke [36/494 (6.8%)] etiologies. Patients developing CIN had increased length of stay in all groups with it being statistically significant in non-stroke (p<0.0001) and ICH (p<0.004). Diabetes mellitus was identified as a significant risk factor for CIN in AIS (p=0.0094) and non-stroke population (p=0.0002). Use of antihypertensives during the first 72 hours of admission was significantly associated with CIN (p=0.0025) among non-stroke patients whereas it was not identified to be a risk factor for CIN in stroke cohort. Intravenous hydration was not associated with prevention of CIN in any of the study groups. Conclusion: Our study results demonstrate higher incidence of CIN among patients with hemorrhagic stroke and reports risk for developing CIN in AIS is comparable to non-stroke population undergoing CECT in emergency circumstances.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".