Social Deprivation and Post‐TAVR Outcomes in Ontario, Canada: A Population‐Based Study
Bibliographic record
Abstract
Background Transcatheter aortic valve replacement (TAVR)/intervention has become the standard of care for treatment of severe aortic stenosis across the spectrum of risk. There are socioeconomic disparities in access to TAVR. The impact of these disparities on postprocedural outcomes remains unknown. Our objective was to examine the association between neighborhood-level social deprivation and post-TAVR mortality and hospital readmission. Methods and Results We conducted a population-based retrospective cohort study of all 4145 patients in Ontario, Canada, who received TAVR from April 1, 2017, to March 31, 2020. Our co-primary outcomes were 1-year postprocedure mortality and 1-year postprocedure readmission. Using Cox proportional hazards models for mortality and cause-specific competing risk hazard models for readmission, we evaluated the relationship between neighborhood-level measures of residential instability, material deprivation, and concentration of racial and ethnic groups with post-TAVR outcomes. After multivariable adjustment, we found a statistically significant relationship between residential instability and postprocedural 1-year mortality, ranging from a hazard ratio of 1.64 to a hazard ratio of 2.05. There was a significant association between the highest degree of residential instability and 1-year readmission (hazard ratio, 1.23 [95% CI, 1.01-1.49]). There was no association between material deprivation and concentration of racial and ethnic groups with post-TAVR outcomes. Conclusions Residential instability was associated with increased risk for post-TAVR mortality, and the highest quintile of residential instability was associated with increased post-TAVR readmission. To reduce health disparities and promote an equitable health care system, further research and policy interventions will be required to identify and support economically and socially minoritized patients undergoing TAVR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".