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Record W3009852707 · doi:10.1503/cjs.006318

Venous thromboembolism in emergency general surgery patients: a single-centre retrospective cohort study

2020· article· en· W3009852707 on OpenAlexaffvenue
Mei Yang, Patrick Murphy, Laura Allen, Nathalie Sela, Shaylan K. Govind, Ken Leslie, Kelly Vogt

Bibliographic record

VenueCanadian Journal of Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineVenous thromboembolismRetrospective cohort studyCohortDemographicsCohort studyEmergency medicineSurgeryInternal medicineThrombosis

Abstract

fetched live from OpenAlex

Background: There is limited literature on the risk of venous thromboembolism (VTE) in emergency general surgery (EGS) patients. We undertook this study to identify the rate of symptomatic VTE for patients undergoing EGS operations. Methods: We conducted a retrospective cohort study evaluating EGS patients who underwent operative intervention between March and December 2014. Data collected included patient demographics, type of procedure, risk of VTE, VTE prophylaxis, development of symptomatic VTE, and mortality. Results: We included 767 patients in our analysis. The mean age was 53 ± 19.7 years, and 52.2% of patients were female. Eighteen patients (2.3%) experienced VTE in hospital and 12 (1.6%) experienced VTE after discharge. Only 66% of patients received appropriate VTE prophylaxis. High-risk patients had a higher VTE rate (7.4% v. 2.3%, p < 0.001) and higher mortality (17.6% v. 4.0%, p < 0.001) than lowto moderate-risk patients. Conclusion: The risk of VTE in patients requiring EGS is significant and persists after hospital discharge. Further studies on quality improvement with VTE prophylaxis are warranted.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.239
Teacher spread0.202 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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