MétaCan
Menu
Back to cohort
Record W1986034672 · doi:10.1002/mus.21787

Bacterial overgrowth syndrome in myotonic muscular dystrophy is potentially treatable

2010· article· en· W1986034672 on OpenAlexaff
Mark A. Tarnopolsky, Erin Pearce, Andre Matteliano, Cindy James, David Armstrong

Bibliographic record

VenueMuscle & Nerve · 2010
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineSmall intestinal bacterial overgrowthMyotonic dystrophyAntibioticsDiarrheaInternal medicineGastroenterologyRifaximinIrritable bowel syndrome

Abstract

fetched live from OpenAlex

Over one third of patients with myotonic muscular dystrophy type 1 (DM1) have gastrointestinal complaints. The cause is multifactorial, and treatment options are limited. Twenty DM1 patients with gastrointestinal symptoms were screened over a 2-year period using glucose breath hydrogen testing (GBHT) to evaluate the prevalence of small intestinal bacterial overgrowth (SIBO). Sixty-five percent of patients had a positive GBHT, and diarrhea was the most common presenting symptom. Ciprofloxacin was the most common antibiotic used for treatment, and 70% of patients reported a good response to the initial course of treatment. Although the causes of gastrointestinal symptoms in patients with DM1 are multifactorial, small intestinal bacterial overgrowth is an important diagnostic consideration that is easily diagnosed using glucose breath hydrogen testing and often shows a good response to treatment with common antibiotics.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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

Citations44
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueMuscle & NerveSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207