FDG-PET imaging in a child with Kawasaki disease: systemic and coronary artery inflammation without dilatation
Bibliographic record
Abstract
Background Multiple sclerosis (MS) is estimated to affect 2.8 million people worldwide, with increasing prevalence in all world regions (Walton et al). While there is no cure for MS, medication and lifestyle modifications can slow disease progression and enhance patients’ quality of life. The biopsychosocial model of health recognises important interactions among biological, psychological and social factors in illness, including those relating to illness management, which contribute to the experience of those diagnosed with MS. Objective This qualitative, idiographic study aimed to explore the lived experiences of patients in the United Arab Emirates (UAE) diagnosed with MS. Methods Semistructured interviews were conducted with a purposive sample of eight patients with MS ranging in age from 25 to 56 years. All participants were residing in the UAE at the time of data collection. Interpretative phenomenological analysis was used to analyse the data. Results Three superordinate themes were identified from patients’ candid accounts of their lives with MS, highlighting issues of illness management, acceptance and gratitude, and adaptive coping. These themes broadly illustrate biological, psychological and social aspects of patients’ MS experiences. Conclusion The study emphasised the importance of adopting the biopsychosocial model to treat and manage MS. Additionally, it highlights the need for routine assessment and early, multidimensional approach with multidisciplinary team efforts to improve patients’ quality of life.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".