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Record W4380991429 · doi:10.3390/nu15122763

Real-World Management of High Stool Output in Patients with Short Bowel Syndrome: An International Multicenter Survey

2023· article· en· W4380991429 on OpenAlexaff
Narisorn Lakananurak, Elizabeth Wall, Hilary Catron, Adela Delgado, Sophie Greif, Jean Herlitz, Lisa Moccia, David F. Mercer, Tim Vanuytsel, Vanessa J. Kumpf, Mark Berner‐Hansen, Leah Gramlich

Bibliographic record

VenueNutrients · 2023
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsUniversity of AlbertaRoyal Alexandra HospitalAlberta Health Services
Fundersnot available
KeywordsShort bowel syndromeMulticenter studyMedicineInternal medicineGastroenterologyRandomized controlled trialParenteral nutrition

Abstract

fetched live from OpenAlex

BACKGROUND: International practice guidelines for high-stool-output (HSO) management in short bowel syndrome (SBS) are available, but data on implementation are lacking. This study describes the approach used to manage HSO in SBS patients across different global regions. METHODS: This is an international multicenter study evaluating medical management of HSO in SBS patients using a questionnaire survey. Thirty-three intestinal-failure centers were invited to complete the survey as one multidisciplinary team. RESULTS: Survey response rate was 91%. Dietary recommendations varied based on anatomy and geographic region. For patients without colon-in-continuity (CiC), clinical practices were generally consistent with ESPEN guidelines, including separation of fluid from solid food (90%), a high-sodium diet (90%), and a low-simple-sugar diet (75%). For CiC patients, practices less closely followed guidelines, such as a low-fat diet (35%) or a high-sodium diet (50%). First-line antimotility and antisecretory medications were loperamide and proton-pump inhibitors. Other therapeutic agents (e.g., pancreatic enzymes and bile acid binders) were utilized in real-world practices, and usage varied based on intestinal anatomy. CONCLUSION: Expert centers largely followed published HSO-management guidelines for SBS patients without CiC, but clinical practices deviated substantially for CiC patients. Determining the reasons for this discrepancy might inform future development of practice guidelines.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.030
GPT teacher head0.315
Teacher spread0.285 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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