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Record W4391873471 · doi:10.1093/jcag/gwad061.284

A284 EVALUATING THE INCIDENCE OF MAJOR GASTROINTESTINAL BLEEDING IN PATIENTS WITH CIRRHOSIS ON ANTICOAGULATION THERAPY: A TERTIARY SINGLE CENTRE EXPERIENCE

2024· article· en· W4391873471 on OpenAlexaff
Hasan Bualbanat, Anouar Teriaky, Darren Hudson, Karim Qumosani

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineCirrhosisIncidence (geometry)Tertiary careGastrointestinal bleedingIntensive care medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Patients with chronic liver disease, especially those with cirrhosis, face an increased risk of bleeding and thrombosis due to hemostasis dysregulation. In such cases, prescribing anticoagulation therapy requires a cautious approach, given the inherent risk-reduction in thrombosis alongside a suspected elevated bleeding risk. Aims Perform a retrospective study to evaluate anticoagulation safety and gastrointestinal bleeding incidence in cirrhotic patients. Methods A retrospective study was conducted at the University Hospital of London Health Sciences Centre, involving patients who attended outpatient hepatology clinics between 2010 and 2022. To be eligible, patients had to be 18 years or older and have confirmed cirrhosis through imaging, radiology, or pathology. They were monitored for up to 5 years for the primary outcome, which was major gastrointestinal bleeding requiring hospitalization. Exclusions included patients with underlying hematologic or thrombotic conditions contributing to abnormal hemostasis beyond cirrhosis and those who underwent liver transplantation. Descriptive statistics were provided, such as means and standard deviations for continuous variables, and proportions/percentages for categorical ones. Group comparisons utilized the Student's t-test for continuous variables and chi-squared tests for categorical variables. Univariate and multivariate logistic regression were employed to calculate odds ratios and their associated 95% confidence intervals for the primary outcome Results We retrospectively enrolled 300 patients, with 34.0% having cirrhosis and anticoagulation history. The average age was 63.1 years [95% CI 61.7 – 64.6], and 43.7% were female. Atrial fibrillation was the primary reason for anticoagulation (53.9%). Cirrhotic patients on anticoagulation had a 13.1% bleeding rate, while those without had 18.6% (p-value = 0.207, not significant). Univariate analysis suggested a possible link between anticoagulation and bleeding risk (OR 1.51 [95% CI 0.79 – 2.89]). No covariates predicted bleeding in univariate logistic regression. In multivariate analysis adjusting for age and sex, the odds ratio remained at 1.50 [95% CI 0.78 – 2.88]. The study hints at a higher bleeding risk in cirrhotic patients on anticoagulation, but more statistical power is needed, either through a larger sample or a multicenter approach. Conclusions To further investigate the association between anticoagulation and bleeding risk in cirrhotic patients, a larger multicentre study with increased enrollment is required. Nonetheless, interim findings do suggest the potential existence of an associated bleeding risk in cirrhotic patients undergoing anticoagulation therapy, albeit with a small observed effect size and uncertain clinical significance. Funding Agencies None

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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