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Record W2258387567 · doi:10.2196/resprot.4467

A Multicenter Prospective Study to Investigate the Diagnostic Accuracy of the SeHCAT Test in Measuring Bile Acid Malabsorption: Research Protocol

2016· article· en· W2258387567 on OpenAlexvenueno aff
Fiona Reid, Janet L. Peacock, Bola Coker, Viktoria McMillan, Cornelius Lewis, Stephen Keevil, Roy Sherwood, G. Vivian, Robert A. Logan, Jennifer Summers

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsBile acid malabsorptionProtocol (science)MedicineTest (biology)MalabsorptionBile acidInternal medicineComputer scienceAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Bile acid malabsorption (BAM) is one possible explanation for chronic diarrhea. BAM may be idiopathic, or result from ileal resection or inflammation including Crohn's disease, or may be secondary to other conditions, including cholecystectomy, peptic ulcer surgery, and chronic pancreatitis. No "gold standard" exists for clinical diagnosis of BAM, but response to treatment with a bile acid sequestrant (BAS) is often accepted as confirmation. The SeHCAT (tauroselcholic [selenium-75] acid) test uses a radiolabeled synthetic bile acid and provides a diagnostic test for BAM, but its performance against "trial of treatment" is unknown. Fibroblast growth factor 19 (FGF-19) and 7-alpha-hydroxy-4-cholesten-3-one (C4) also offer potential new biomarkers of BAM. OBJECTIVE: This protocol describes a multicenter prospective study to evaluate the diagnostic accuracy of SeHCAT and 2 biomarkers in predicting BAM as assessed by trial of treatment. METHODS: Participating gastroenterology centers should have a minimum workload of 30 SeHCAT patients per annum. Patients should not be pregnant, on medication that could confound follow-up, or have any severe comorbidity. All eligible patients attending a gastrointestinal appointment will be invited to participate. On attending the SeHCAT test, blood and fecal samples will be collected for analysis of FGF-19 by enzyme-linked immunosorbent assay and for C4 and fractionated bile acids by liquid chromatography-mass spectrometry. A capsule containing radiolabeled SeHCAT will be administered orally and a scan performed to measure SeHCAT activity. Patients will return on day 7 to undergo a second scan to measure percentage SeHCAT retention. The test result will be concealed from clinicians and patients. BAS will be dispensed to all patients, with a follow-up gastroenterologist appointment at 2 weeks for clinical assessment of treatment response and adherence. Patients responding positively will continue treatment for a further 2 weeks and all patients will have a final follow-up at 8 weeks. The diagnostic accuracy of the SeHCAT test and biomarkers will be analyzed at different thresholds using sensitivity, specificity, positive and negative predictive value, likelihood ratios, and area under the curve in a sample of 600 patients. Multivariable logistic regression models will be used to assess the association between presence of BAM and continuous SeHCAT retention levels after adjustment for confounders. RESULTS: Funding is being sought to conduct this research. CONCLUSIONS: The SeHCAT test for diagnosis of BAM has been in common use in the United Kingdom for more than 30 years and an evidence-based assessment of its accuracy is overdue. The proposed study has some challenges. Some forms of BAS treatment are unpleasant due to the texture and taste of the resin powder, which may negatively affect recruitment and treatment adherence. Trial of treatment is not as "golden" a standard as would be ideal, and itself warrants further study.

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)0.037
metaresearch head score (Gemma)0.028
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.037
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.028
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.003
Science and technology studies0.0040.003
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0160.006

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 head0.296
GPT teacher head0.533
Teacher spread0.238 · 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
GenreProtocol

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

Citations11
Published2016
Admission routes1
Has abstractyes

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