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Effects of ascites resolution after successful TIPS on nutrition in cirrhotic patients with refractory ascites

2001· article· en· W2036774791 on OpenAlexaff
Johane P. Allard, Jenny Chau, Karim Sandokji, Laurie Blendis, Florence Wong

Bibliographic record

VenueThe American Journal of Gastroenterology · 2001
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of TorontoToronto General Hospital
Fundersnot available
KeywordsMedicineAscitesCirrhosisGastroenterologyInternal medicineRefractory (planetary science)Resting energy expenditureTransjugular intrahepatic portosystemic shuntPortal hypertensionBody weight

Abstract

fetched live from OpenAlex

OBJECTIVE: Malnutrition is common in patients with decompensated cirrhosis and refractory ascites. The use of transjugular intrahepatic portosystemic stent shunt (TIPS) is effective in eliminating ascites. The purpose of this study was to investigate the effect of TIPS and resolution of refractory ascites on the nutritional status of patients with decompensated cirrhosis. METHODS: Fourteen consecutive patients with refractory ascites and a Pugh score of 9.0+/-0.5 had a TIPS insertion. Biochemical data, resting energy expenditure (REE), total body nitrogen (TBN), body potassium (TBK), body fat (TBF), muscle force (MF), and food intake were recorded before TIPS, and at 3 and 12 months after the procedure. RESULTS: Ten patients completed the study. Baseline values for REE, TBN, TBF, MF, and energy intake were below normal at baseline. There was a significant increase in dry weight, TBN, and REE at 3 and 12 months compared with baseline. TBF improved significantly at 12 months. There was a trend toward an increase in energy intake (p = 0.072). There was no change in protein intake, TBK, MF, and Pugh score. CONCLUSION: In cirrhotic patients with refractory ascites, resolution of the ascites after TIPS placement resulted in improvement of several nutritional parameters, especially for body composition.

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 score0.077
Threshold uncertainty score0.238

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)0.0000.000

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 head0.003
GPT teacher head0.208
Teacher spread0.206 · 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

Citations97
Published2001
Admission routes1
Has abstractyes

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