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Record W2989764195 · doi:10.1093/jtm/taz091

The risk and prevention of venous thromboembolism in the pregnant traveller

2019· review· en· W2989764195 on OpenAlexafffund
Divya J. Karsanji, Shannon M. Bates, Leslie Skeith

Bibliographic record

VenueJournal of Travel Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsMcMaster UniversityUniversity of Calgary
FundersEli Lilly CanadaEli Lilly and Company
KeywordsMedicineVenous thromboembolismThrombophiliaCompression stockingsPregnancyObstetricsRisk assessmentRisk factorFamily historyDeep veinThrombosisIntensive care medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The average risk of venous thromboembolism (VTE) in long haul travellers is approximately 2.8 per 1000 travellers, which is increased in the presence of other VTE risk factors. In pregnant long-haul travellers, little is known in terms of the absolute risk of VTE in these women and, therefore, there is limited consensus on appropriate thromboprophylaxis in this setting. OBJECTIVE: This review will provide guidance to allow practitioners to safely minimize the risk of travel-related VTE in pregnant women. The suggestions provided are based on limited data, extrapolated risk estimates of VTE in pregnant travellers and recommendations from published guidelines. RESULTS: We found that the absolute VTE risk per flight appears to be <1% for the average pregnant or postpartum traveller. In pregnant travellers with a prior history of VTE, a potent thrombophilia or strong antepartum risk factors (e.g. combination of obesity and immobility), the risk of VTE with travel appears to be >1%. Postpartum, the risk of VTE with travel may be >1% for women with thrombophilias (particularly in those with a family history) and other transient risk factors and in women with a prior VTE. CONCLUSIONS: Based on our findings, we recommend simple measures be taken by all pregnant travellers, such as frequent ambulation, hydration and calf exercises. In those at an intermediate risk, we suggest a consideration of 20-30 mmHg compression stockings. In the highest risk group, we suggest careful consideration for low-molecular-weight heparin thromboprophylaxis. If there are specific concerns, we advise consultation with a thrombosis expert at the nearest local centre.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.404
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2019
Admission routes2
Has abstractyes

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