The Epidemiology of Endocarditis in Manitoba: A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Recently, anecdotal evidence suggested an increase in infective endocarditis (IE) in Manitoba driven by an increasing proportion of patients with intravenous drug use (IVDU)-associated endocarditis. This study aimed to characterize the observed changing incidence and epidemiology of IE. METHODS: This retrospective study evaluated consecutive patients >18 years old with an International Classification of Disease-10 diagnosis of IE who presented to a tertiary referral center in Winnipeg, Manitoba between January 1, 2004 and December 31, 2018. Data were obtained by individual review of paper and electronic medical records and entered into the Research Electronic Data Capture database. Mortality and hospital readmission data were acquired by linking Research Electronic Data Capture data to the Manitoba Centre for Health Policy, which prospectively maintains a comprehensive population-based health database. RESULTS: A total of 612 cases of IE were identified. The incidence of IE increased from 2.03 per 100,000 in 2004 to 5.16 per 100,000 in 2018, with IVDU-associated cases increasing from 0.11 to 2.87 per 100,000. Left heart vegetations were most common in the non-IVDU group, whereas right-sided vegetations dominated in the IVDU group. All-cause mortality did not differ between IVDU and non-IVDU IE, despite a significantly younger age in patients with IVDU. The IVDU group showed a higher rate of endocarditis recurrence. CONCLUSIONS: In this first study to examine the longitudinal incidence of IE in Manitoba, we showed that the incidence of IE has significantly increased over the last 15 years, with a contribution of IVDU-associated IE that has a high rate of mortality and disease recurrence.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".