MétaCan
Menu
Back to cohort
Record W2983767055 · doi:10.14740/gr1179

Elevated International Normalized Ratio: A Risk Factor for Portal Vein Thrombosis in Cirrhotic Patients

2019· article· en· W2983767055 on OpenAlexvenueno aff
Eric O. Then, Vijay S. Are, Michell Lopez-Luciano, Andrew Ofosu, Andrea Culliford, Vinaya Gaduputi

Bibliographic record

VenueGastroenterology Research · 2019
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePortal vein thrombosisCirrhosisInternal medicineLiver transplantationGastroenterologyThrombosisBilirubinMedical recordComplicationSurgeryTransplantation

Abstract

fetched live from OpenAlex

BACKGROUND: Portal vein thrombosis (PVT) is a complication that is commonly seen in patients with cirrhosis and an entity that leads to increased mortality in patients who undergo liver transplantation. This study aims to establish a link between an elevated international normalized ratio (INR) and the presence of PVT in a cohort of cirrhotic patients. METHODS: We retrospectively reviewed the electronic medical records of all patients diagnosed with cirrhosis in SBH Health System from 2013 to 2018. Among these patients we extracted baseline demographic data, laboratory results, co-morbidities and the presence of PVT. RESULTS: In total there were 268 patients who met our inclusion criteria. Twenty-two patients had PVT, while 246 patients did not. Of the 22 patients with PVT there was a statistically significant increase in INR when compared to patients without PVT. There was also a statistically significant increase in total bilirubin, alkaline phosphatase and platelet count. CONCLUSIONS: Elevated INR levels are associated with the presence of PVT in patients with cirrhosis. These findings suggest a hypercoagulable state and could assist clinicians in risk-stratifying patients when making the decision to initiate anti-coagulation therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.355
Teacher spread0.319 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGastroenterology ResearchSame topicLiver Disease and TransplantationFrench-language works237,207