Socioeconomic Barriers for Newly Transferred Young Adults With Congenital Heart Disease
Bibliographic record
Abstract
Background This study aimed to ascertain socioeconomic factors affecting successful transfer to adult congenital cardiology and cardiac surgical services in Ontario. Methods Patients with congenital heart disease (CHD) referred from a pediatric CHD program to an adult CHD (ACHD) center between January 1, 2004, and December 31, 2015, were identified. The prevalence of (1) failed transfer (FT), (2) lost to follow-up (LTFU), and (3) cardiac surgery (CS) during the extended study period of 2004-2018 was investigated. Socioeconomic variables associated with FT, LTFU, and CS were explored using Environics data associated with postal code at the time of transfer. Results A total of 2196 patients were referred from the pediatric to ACHD center between 2004 and 2015. Within this cohort, 11% had FT and 25% had LTFU; there was a 2% overlap between the FT and LTFU groups. A total of 106 patients (4.8%) underwent CS. Age at referral (odds ratio [OR]: 0.591, P < 0.001) and being unable to travel to work by car (OR: 0.986, P < 0.001) were both associated with FT, though the latter is not clinically relevant. Residential addresses with lower income (OR: 0.976, P = 0.016) were associated with LTFU. Factors associated with CS were higher household income ( P < 0.001), access to a car for travel to work ( P < 0.001), Canadian citizenship ( P = 0.041), and French or English as the primary language in the home ( P = 0.038). Conclusions Socioeconomic factors are associated with access to specialized ACHD services among young adults. Strategies to ensure equity in care should be explored.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".