Regional differences in aortic valve replacements: Atlantic Canadian experience
Bibliographic record
Abstract
BACKGROUND: Transcatheter aortic valve implantation (TAVI) is evolving rapidly and is increasingly being adopted in the treatment of aortic valve disease. The goal of this study was to examine regional differences in surgical aortic valve replacement (SAVR) and TAVI across Atlantic Canada. METHODS: We identified all patients who underwent SAVR or TAVI between Jan. 1, 2010, and Dec. 31, 2014, in New Brunswick, Nova Scotia and Newfoundland and Labrador. Data obtained included patient demographic characteristics and surgical procedure details. We performed univariate descriptive analyses and calculated crude and age- and sex-adjusted incidence rates. RESULTS: A total of 3042 patients underwent SAVR or TAVI during the study period, 1491 in Nova Scotia, 1042 in New Brunswick and 509 in Newfoundland and Labrador. Patient demographic characteristics were similar across regions. A much higher proportion of patients in Newfoundland and Labrador (43.6%) than in Nova Scotia (4.2%) or New Brunswick (13.6%) received a mechanical versus a bioprosthetic valve. Rates of TAVI increased over the study period, with New Brunswick adopting their program before Nova Scotia (144 v. 74 procedures). Adjusted rates of all AVR procedures remained stable in Nova Scotia (40-50 per 100 000 people). Adjusted rates were lower in New Brunswick and Newfoundland and Labrador than in Nova Scotia; they increased slowly in New Brunswick over the study period. CONCLUSION: Despite geographical proximity and similar patient demographic characteristics, there existed regional differences in the management of aortic valve disease within Atlantic Canada. Further study is required to determine whether the observed differences in age- and sex-adjusted rates of AVR may be explained by geographical disease-related differences, varying practice patterns or barriers in access to care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".