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Record W2002125254 · doi:10.1136/gut.2004.057976

The lighter side of myeloma: an easily overlooked diagnosis

2005· article· en· W2002125254 on OpenAlexaff
Jordan J. Feld

Bibliographic record

VenueGut · 2005
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMultiple myelomaMedicineInternal medicine

Abstract

fetched live from OpenAlex

Aim: A subset of functional dyspepsia patients respond to acid suppressive therapy, but the prevalence of non-erosive reflux disease in functional dyspepsia and its relevance to symptoms have never been established. The aim of the present study was to study 24 hour pH monitoring in consecutive functional dyspepsia patients. Methods: A total of 247 patients with dyspeptic symptoms (166 women, mean age 44 (SEM 1) year), with a negative upper gastrointestinal endoscopy and without dominant symptoms of heartburn participated in the study. In all patients, the severity of dyspeptic symptoms and the presence of heartburn was assessed by a questionnaire and a 24 hour oesophageal pH monitoring study was performed. All patients underwent a gastric emptying breath test and in 113 a gastric barostat study was performed. Results: Abnormal pH monitoring (acid exposure .5% of time) was found in 58 patients (23%). Of 21 patients with a positive heartburn questionnaire, 76% had pathological pH monitoring, while this was the case in only 18.5% of patients with a negative heartburn questionnaire. Demographic characteristics and the prevalence of other pathophysiological mechanisms did not differ between heartburn negative patients with normal or abnormal acid exposure. Pathological acid exposure in heartburn negative patients was associated with the presence of epigastric pain (65 v 84%, p,0.005) and of moderate or severe pain (48 v 69%, p = 0.005). Conclusion: Pathological oesophageal acid exposure is only present in a subset of heartburn negative functional dyspepsia patients, which are characterised by a higher prevalence of epigastric pain.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.316

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 head0.027
GPT teacher head0.320
Teacher spread0.293 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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