Abstract 206: Cerebrovascular Events In Patients With Chronic Kidney Disease On Erythropoiesis Stimulating Agent
Bibliographic record
Abstract
Title: Cerebrovascular Events in Patients with Chronic Kidney Disease on Erythropoiesis Stimulating Authors: Ali M Rad, MD, MPH; Shubham Misra,MD;Rajan Garg, MD;Karine Karapetyan, MD;Sheila Roxana Safar, MD; Daniel Goldsmith, MD Background: Anemia is associated with an increased risk of cardiovascular events among patients with Chronic Kidney Disease (CKD). Guidelines have been developed for hemoglobin (Hgb) targets. Erythropoietin Stimulating Agents (ESA) are commonly used to increase hemoglobin level in CKD patients. The recent TREAT study found an increased incidence of stroke and cancer when maintaining the Hgb level at 12.5 g/dl. In the opposite, Watanabe et al showed no significant increase in risk of developing stroke in a Japanese population. Methods: All patients with chronic kidney disease who admitted between Jan 2009 till June 2011 were selected. Patients are categorized to 2 groups, CKD patients with cerebravascular events and CKD with no cerebrovascular events. Binary logistic regression was used for analysis. All results were adjusted for age and gender. Results: A total of 4926 patients were recognized. 348 out of 4926 had cerebrovascular events in their admissions between Jan 2009 till June 2011. 241/341 had ischemic cerebrovascular events, and the remainder had hemorrhagic events. Using binary logistic regression, our study shows a significant association between ESA injections and cerebrovascular events after adjusting for age, sex and Hgb level (p < 0.001). Conclusions: We showed there is significant association between ESA use and cerebrovascular events adjusting for hemoglobin level, age and sex. Even though there was association between Hgb level and cerebrovascular events in our preliminary data, after adjusting for ESA injections, there was no association between Hgb level and cerebrovascular events. This suggests less of an association between Hgb level and stroke than use of an ESA and stroke. Based on these results, we recommend considering iron replacement and blood transfusion in the treatment of anemia and CKD. More studies should be done to establish possible causation and pathophysiology between ESA injections and cerebrovascular agents which may include evaluating for any dose related association.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".