MétaCan
Menu
Back to cohort
Record W2750097320 · doi:10.12968/pnur.2017.28.8.344

Living with Trimethylaminuria (TMAU) from an adult viewpoint

2017· article· en· W2750097320 on OpenAlexaff
Abie Lateef, Sylvie Marshall−Lucette

Bibliographic record

VenuePractice Nursing · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineQuality of life (healthcare)PsychologyEmotiveDistressingGerontologyNursingSociology

Abstract

fetched live from OpenAlex

Using new case studies, Abie Lateef and Sylvie Marshall-Lucette examine the causes and consequences of ‘fish odour syndrome’, an under-researched and distressing condition that can have an often over-looked effect on quality of life Trimethylaminuria (TMAU) is an uncommon, inherited metabolic disease (IMD) characterised by an unpleasant rotting fish-like mouth or body odour. There does not seem to be any available study that addresses the psycho-social impact of this often missed and delayed diagnosed condition. Thus, this study explores adult patients' perspectives of living with TMAU, at one IMD department in the United Kingdom. A descriptive phenomenological approach was adopted to study 11 adult participants, selected from 19 eligible patients with TMAU. After gaining approval from a Local Research Ethics Committee, data from in-depth, semi-structured interviews were transcribed verbatim and inductively analysed. Four main themes were identified from the data: conceptualisation of TMAU; personal sensitivity in the conundrum of TMAU; life with TMAU; and moving forward with TMAU. The participants' highly emotive, insightful lived experiences suggest an overlooked and overdue need for awareness of TMAU among healthcare professionals and the public, as well as funded studies into appropriate treatment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.011
GPT teacher head0.325
Teacher spread0.314 · 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 designOther design
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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuePractice NursingSame topicMetabolism and Genetic DisordersFrench-language works237,207