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Record W2164447433 · doi:10.1177/1076029608326166

Lessons From Ximelagatran: Issues for Future Studies Evaluating New Oral Direct Thrombin Inhibitors for Venous Thromboembolism Prophylaxis in Orthopedic Surgery

2008· review· en· W2164447433 on OpenAlexaff
Alejandro Lazo‐Langner, Marc Rodger, Philip S. Wells

Bibliographic record

VenueClinical and Applied Thrombosis/Hemostasis · 2008
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of OttawaWestern University
FundersAmerican Society of Hematology
KeywordsXimelagatranMedicineDirect thrombin inhibitorVenous thromboembolismWarfarinCochrane LibraryMeta-analysisOrthopedic surgeryRandomized controlled trialLow molecular weight heparinKnee replacementMEDLINEIntensive care medicineAnesthesiaHeparinSurgeryInternal medicineDabigatranThrombosisAtrial fibrillation

Abstract

fetched live from OpenAlex

Venous thromboembolism is a frequent complication of total hip and knee replacement requiring prophylaxis with anticoagulants. A direct thrombin inhibitor-ximelagatran-did not show advantages over other anticoagulants and it was withdrawn from the market; however, new drugs are being developed. We conducted a systematic review and meta-analysis to identify conditions under which ximelagatran might potentially be superior to current standards. Medline, EMBASE, the Cochrane Library, and grey literature were screened for randomized trials comparing ximelagatran with warfarin or low-molecular-weight heparin for thromboprophylaxis in total hip or knee replacement. Two reviewers independently assessed and extracted data. A meta-analysis with especial attention to statistical heterogeneity was conducted. This study suggested that the risk-benefit profile of ximelagatran-and probably other similar agents-depends on the type of surgery, the initial timing of administration, and probably the dose. These issues should be explicitly explored in future trials evaluating new direct thrombin inhibitors.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
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 head0.342
GPT teacher head0.508
Teacher spread0.166 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations12
Published2008
Admission routes1
Has abstractyes

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