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Record W2461690387 · doi:10.1182/blood.v124.21.592.592

Antithrombotic Treatment and Outcomes of Splanchnic Vein Thrombosis in an International Prospective Registry: Results of 2-Year Follow-up

2014· article· en· W2461690387 on OpenAlexaffabout
Walter Ageno, Nicoletta Riva, Sam Schulman, Jan Beyer‐Westendorf, Soo‐Mee Bang, Marco Senzolo, Elvira Grandone, Giovanni Barillari, Matteo Nicola Dario Di Minno, R. Duce, Alessandra Malato, Rita Santoro, Daniela Poli, Peter Verhamme, Ida Martinelli, Pieter W. Kamphuisen, Francesco Dentali

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsMedicineThrombosisProspective cohort studyPortal vein thrombosisClinical endpointSurgeryInternal medicineInterquartile rangeClinical trial

Abstract

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Abstract Background: Little information is available on the long-term clinical outcome of patients with splanchnic vein thrombosis (SVT). We aimed to assess incidence rates of bleeding, recurrence, and mortality in a large prospective cohort of SVT patients after a 2-year follow-up. Methods: Consecutive SVT patients were enrolled in a multicenter international registry, from 2008 to 2012. Information was gathered on baseline characteristics, risk factors and therapeutic strategies. Clinical outcomes (major bleeding; vascular events, defined as venous or arterial thrombosis, and mortality) during follow-up were collected and reviewed by a Central Adjudication Committee. Major bleeding was defined using the ISTH definition plus the need for hospitalization. The primary analysis was performed up to the first adjudicated major bleeding or thrombotic event. Results: 604 patients from 31 centers were enrolled in this study, 21 (3.5%) were lost to follow-up. Median follow-up duration was 2 years (IQR 1-2). Median age was 54 years (range 16-85); 62.6% were males. Most common risk factors were liver cirrhosis in 27.8% of patients and solid cancer in 22.3%. Portal vein was the most common site of thrombosis. 139 patients were not anticoagulated; 175 received parenteral anticoagulants only (median duration 5.8 months, IQR 3-12) and 290 were started on vitamin K antagonists (median duration 24 months, IQR 7-24). According to the primary analysis, 103 events occurred during follow-up: 35 major bleeding events (3.8/100 patient-years [pt-y]; 95%CI, 2.7-5.2), 2 of which were fatal bleeding, and 68 thrombotic events (7.3/100 pt-y; 95%CI 5.8-9.3), 9 of which were vascular deaths. All-cause mortality occurred in 106 patients (10.3/100 pt-y; 95% CI 8.5-12.5). The incidence of major bleeding events was 4.0/100 pt-y in patients on anticoagulant drugs and 3.4/100 pt-y in patients not receiving anticoagulants. The incidence of vascular events was 5.6/100 pt-y and 9.7/100 pt-y, respectively. Major bleeding and vascular event rates were highest in cirrhotic patients (10.0/100 pt-y and 11.3/100 pt-y, respectively), and lowest in the subgroup of non-malignant non-cirrhotic patients (1.8/100 pt-y and 5.6/100 pt-y, respectively). Conclusions: SVT patients have a non-negligible long-term risk of both bleeding and thrombotic events, but this risk varies according to the pathogenesis of SVT. Anticoagulant treatment is associated with a reduced incidence of thrombotic events without apparently resulting in an increased risk of bleeding. Funding: The study was funded by a grant from Pfizer Canada to ISTH Disclosures Ageno: Bayer Healthcare: Research Funding. Schulman:Bayer HealthCare: Consultancy, Honoraria, Research Funding; Boehringer Ingelheim: Consultancy, Honoraria, Research Funding. Beyer-Westendorf:Bayer: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Boehringer: Honoraria, Research Funding.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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
Published2014
Admission routes2
Has abstractyes

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