Acute Ischemic Stroke Risk Following Cardiac Interventions in the United States From 2016 to 2021
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Ischemic stroke following cardiac intervention is a serious complication. However, there are limited data comparing stroke risk and severity among patients undergoing different types of cardiac interventions. We examined the incidence of ischemic stroke among patients undergoing cardiac interventions and identified variables associated with risk and severity of ischemic stroke. METHODS: We included cardiac intervention hospitalizations for adults within the United States from 2016 to 2021 in the National Inpatient Sample. We constructed a cross-sectional cohort of cardiac intervention hospitalizations comprising all hospitalizations within a Centers for Medicare & Medicaid Services-defined "Cardiac Surgery" Diagnosis-Related Group. The exposure was category of cardiac intervention, and primary outcome was ischemic stroke in any coding position. After survey weighting, we examined the frequency and factors associated with ischemic stroke, stroke severity, and inpatient mortality. A secondary analysis was performed in a subset of patients with documented NIH Stroke Scale (NIHSS). RESULTS: < 0.001) and ischemic stroke increased the risk of in-hospital death 5-fold (OR 5.07, 95% CI 4.77-5.39). DISCUSSION: Ischemic stroke during hospitalizations for cardiac interventions in the United States varies by type of intervention and shows an increasing trend from 2016 to 2021. Cardiac intervention patients sustaining an ischemic stroke are 5 times as likely to have in-hospital death as those without stroke. Further research is needed to identify high-risk populations that could benefit from specific postoperative monitoring strategies and/or specific therapeutic interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".