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Record W3093398832 · doi:10.1177/1076029620962226

Potential Risk Factors Contributing to Development of Venous Thromboembolism for Total Knee Replacements Patients Prophylaxed With Rivaroxaban: A Retrospective Case-Control Study

2020· article· en· W3093398832 on OpenAlexaff
Owais Mian, Davide Matino, Robin Roberts, Ellen McDonald, Anthony K.C. Chan, Howard H.W. Chan

Bibliographic record

VenueClinical and Applied Thrombosis/Hemostasis · 2020
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster UniversityMcMaster Children's HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineRivaroxabanTourniquetVenous thromboembolismRetrospective cohort studyBody mass indexTotal knee arthroplastyThrombosisAnesthesiaSurgeryUnivariate analysisInternal medicineMultivariate analysisWarfarin

Abstract

fetched live from OpenAlex

Rivaroxaban after total knee arthroplasty (TKA) is used to prevent postoperative venous thromboembolism (VTE); however, despite thromboprophylaxis, some patients still develop postoperative VTE. To determine whether tourniquet time, time to initiate rivaroxaban (TTI RIV ), or Body Mass Index (BMI) was associated with postoperative VTE. A retrospective case-control study was conducted. Those patients that developed VTE despite prophylaxis (cases) were compared to controls (no VTE). A univariate analysis was conducted (p < 0.05 statistically significant). Seven VTE cases were identified from 234 TKA-patients. Patients with and without VTE had BMI of 40.1 ± 9.1 and 32.8 ± 7.5, respectively (p = 0.064). TTI RIV in VTE and control group was 28.2 ± 4.7 hours and 26.4 ± 4.2 hours, respectively (p = 0.39). Mean tourniquet time in VTE and control group was 65.0 ± 8.7 minutes and 49 ± 8.8 minutes, respectively (p = 0.0007). Statistically significant differences in tourniquet times were noted between VTE and non-VTE group but not for TTI RIV and BMI. Prolonged tourniquet use could pose a potential risk factor for postoperative VTE. Thromboprophylaxis management may need to be adjusted, based on patient-specific factors that could include increasing doses of oral anticoagulants and/or mechanical prophylaxis. However, further large-scale studies are required to establish pathophysiology.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.304
Teacher spread0.273 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations4
Published2020
Admission routes1
Has abstractyes

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