A case series of infectious complications in medical tourists requiring hospital admission or outpatient home parenteral therapy
Bibliographic record
Abstract
BACKGROUND: Travelling for medical care is increasing, and this medical tourism (MT) may have complications, notably infectious diseases (ID). We sought to identify MT-related infections (MTRIs) in a large Canadian health region and estimate resulting costs. METHODS: Retrospective and prospective capture of post-MT cases requiring hospital admission or outpatient parenteral antimicrobial therapy was completed by canvassing ID physicians practising in Calgary, Alberta, from January 2017 to July 2019. Cost estimates for management were made with the Canadian Institute for Health Information’s (CIHI’s) patient cost estimator database tool applied to estimated rates of Canadians engaging in MT from a 2017 Fraser Institute report. RESULTS: We identified 12 cases of MT-related infectious syndromes. Eight had microbial etiologies identified. MTs were young (mean 40.3 [SD 12.2] y) and female ( n = 11) and pursued surgical treatment ( n = 11). Destination countries and surgical procedures varied but were largely cosmetic ( n = 5) and orthopaedic ( n = 3). Duration to organism identification (mean 5.3 wk) and treatment courses (mean 19 wk) appeared lengthy. CIHI cost estimates for management of relevant infectious complications of our cases ranged from $6,288 to $20,741, with total cost for cases with matching codes ( n = 8) totalling $94,290. CONCLUSIONS: In our series of MTRIs, etiologic organisms often found in Canadian-performed post-procedural infections were identified, and prolonged treatment durations were noted. Young women pursuing cosmetic surgery may be a population to target with public health measures to reduce the incidence of MTRIs and burden of disease.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".