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Record W2806358017 · doi:10.1186/s12916-018-1069-8

Transient portal vein thrombosis in liver cirrhosis

2018· review· en· W2806358017 on OpenAlexaff
Xingshun Qi, Xiaozhong Guo, Eric M. Yoshida, Nahúm Méndez‐Sánchez, Valerio De Stefano, Frank Tacke, Andrea Mancuso, Yasuhiko Sugawara, Sien‐Sing Yang, Rolf Teschke, Ankur Arora, Dominique Valla

Bibliographic record

VenueBMC Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsVancouver General Hospital
FundersNatural Science Foundation of Liaoning ProvinceChina Postdoctoral Science Foundation
KeywordsMedicineAntithromboticPortal vein thrombosisCirrhosisThrombosisNatural historyRisk stratificationPortal hypertensionIntensive care medicineClinical PracticeInternal medicineCardiologyPhysical therapy

Abstract

fetched live from OpenAlex

In real-world clinical practice, the acceptance of anticoagulation therapy in the management of portal vein thrombosis (PVT) in patients with cirrhosis is limited by the fear of an increased bleeding risk. Additionally, accumulating evidence indicates that spontaneous recanalization of PVT may occur in the absence of antithrombotic treatment. Therefore, risk stratification based on outcomes in such patients is crucial for determining a therapeutic strategy. In this paper, we draw attention to the distinct clinical entity, "transient PVT" by introducing two cases with PVT that spontaneously recanalized in the absence of antithrombotic treatment. We reviewed the available data regarding the probability of and predictors for spontaneous recanalization of PVT. Available data suggest singling out transient thrombosis in the natural history of PVT in patients with cirrhosis because of its prognostic and management implications.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.132
GPT teacher head0.379
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations70
Published2018
Admission routes1
Has abstractyes

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