International Travel Patterns and Travel Risks for Stem Cell Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Stem cell transplantation (SCT) is being increasingly utilized for multiple medical illnesses. However, there is limited knowledge about international travel patterns and travel-related illnesses of stem cell transplant recipients (SCTRs). METHODS: An observational cross-sectional study was conducted among 979 SCTRs at Memorial Sloan Kettering Cancer Center using a previously standardized and validated questionnaire. International travel post SCT, pre-travel health advice, exposure risks, and travel-related illnesses were queried. RESULTS: A total of 516 SCTRs completed the survey (55% response rate); of these, 40% were allogeneic SCTRs. A total of 229 (44.3%) respondents reported international travel outside the United States and Canada post SCT. The international travel incidence was 32% [95% confidence interval CI 28-36] within 2 years after SCT. Using multivariable Cox regression analysis, variables significantly associated with international travel within first 2 years after SCT were history of international travel prior to SCT [hazard ratio (HR) = 5.3, 95% CI 2.3-12.0], autologous SCT (HR = 2.6, 95% CI 1.6-2.8), foreign birth (HR = 2.3, 95% CI 1.5-3.3), and high income (HR = 2.0, 95% CI 1.8-3.7). During their first trip, 64 travelers (28%) had traveled to destinations that may have required vaccination or malaria chemoprophylaxis. Only 56% reported seeking pre-travel health advice. Of those who traveled, 16 travelers (7%) became ill enough to require medical attention during their first trip after SCT. Ill travelers were more likely to have visited high-risk areas (60 vs 26%, p = 0.005), to have had a longer mean trip duration (24 vs 12 days, p = 0.0002), and to have visited friends and relatives (69 vs 21%, p < 0.0001). CONCLUSIONS: International travel was common among SCTRs within 2 years after SCT and was mainly to low-risk destinations. Although the overall incidence of travel-related illnesses was low, certain subgroups of travelers were at a significantly higher risk. Pre-travel health counseling and interventions were suboptimal.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".