Living with Trimethylaminuria (TMAU) from an adult viewpoint
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".