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Record W2970588274 · doi:10.1055/s-0039-1696639

Management of Lifestyle Factors in Individuals with Cirrhosis: A Pragmatic Review

2019· review· en· W2970588274 on OpenAlexaff
Puneeta Tandon, Annalisa Berzigotti

Bibliographic record

VenueSeminars in Liver Disease · 2019
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCirrhosisLifestyle modificationSedentary lifestyleEtiologyMalnutritionDiseaseObesityPopulationHepatocellular carcinomaPhysical activityIntensive care medicineGerontologyPhysical therapyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Lifestyle-related factors are major determinants/modifiers of prognosis in patients with cirrhosis. Accumulating evidence indicates that malnutrition, obesity, sedentary lifestyle, alcohol and smoking habits, and likely poor oral hygiene can increase the risk of progression of the disease, and some of them are linked to higher risk of hepatocellular carcinoma. Importantly, lifestyle-related factors can be largely corrected, and as such they represent an attractive approach to be added to etiological and pharmacological therapy in patients with cirrhosis. Nonetheless, lifestyle is often neglected in this population. In this concise review, the authors present evidence supporting lifestyle changes in patients with cirrhosis-including, but not limited to, nutrition and physical activity in malnourished and obese patients. They also discuss some elements of motivational interviews as a tool to support a better interaction between hepatologists and patients in this field.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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)0.0030.000

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 head0.025
GPT teacher head0.314
Teacher spread0.289 · 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 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

Citations21
Published2019
Admission routes1
Has abstractyes

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