Sickle cell disease in Ontario, Canada: an epidemiologic profile based on health administrative data
Bibliographic record
Abstract
BACKGROUND: The number of patients with sickle cell disease in Ontario, Canada, is unknown. In the absence of a formal registry, we performed a study to determine an approximate census via analysis of health administrative databases. METHODS: We identified Ontario patients with a diagnosis of sickle cell disease through queries of the Discharge Abstract Database, National Ambulatory Care Reporting System and Newborn Screening Ontario database. The period of inquiry was Apr. 1, 2007, through Mar. 31, 2017. We identified repeat interactions by the same patient by cross-referencing provincial health insurance plan numbers. RESULTS: We documented health care system interactions for 3418 unique patients (1912 [55.9%] female, median age at the time of identification 24 yr). Over the 10-year study period, patients visited the emergency department a median of 2 (interquartile range [IQR] 1-7) times and an average of 6.69 (standard deviation [SD] 26.71) times, and were admitted to hospital a median of 1 (IQR 1-5) time and an average of 4.38 (SD 8.53) times for treatment related to sickle cell disease. A total of 229 patients (6.7%) died during the study period, with an average age at death of 55 years. Even without accounting for the effects of immigration, the rate of natural increase slowed slightly over the study period owing to a decrease in the annual number of affected births. INTERPRETATION: The estimated prevalence of patients with sickle cell disease in Ontario in 2007/08-2016/17 was 1 in 4200, and affected patients' need for hospital-based care was substantial, although highly variable. Similar queries of health administrative databases may be feasible in other Canadian provinces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".