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Record W7071011654

A Profile of Physical Fitness Variables in an Out-Patient Adult Population with Narcolepsy

2021· dissertation· en· W7071011654 on OpenAlexaff

Bibliographic record

VenueArrow@dit (Dublin Institute of Technology) · 2021
Typedissertation
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsTrinity College
Fundersnot available
KeywordsNarcolepsyEpworth Sleepiness ScalePhysical fitnessQuality of life (healthcare)Test (biology)Vitality
DOInot available

Abstract

fetched live from OpenAlex

Background: Narcolepsy is a disabling lifelong condition that impacts an individuals ability to regulate sleep-wake patterns. Narcolepsy can significantly impact the physical and mental wellbeing of people with narcolepsy, and has been associated with significant reductions in quality of life and physical performance. Despite physical functioning and vitality being the most affected domains of health-related quality of life in this cohort, more accurate measurements of physical performance using a suitable physical test battery have not yet been conducted.\n\nMethods: A systematic review and meta-analysis was conducted to explore health-related quality of life in adults with narcolepsy. A cross-sectional study was conducted to assess the physical performance of adults with narcolepsy who attended the Narcolepsy Clinic in St. James s Hospital between October 2019 and March 2020. A comprehensive battery was designed to assess physical performance variables. The following variables were objectively assessed; cardiopulmonary fitness (YMCA Submaximal Bike Test), muscle strength (Dynamometry and Countermovement Jump Test), muscle endurance (ACSM Push Up Test and Wall Squat Test) and physical activity (Actigraphy). A number of questionnaires were utilised to assess health-related quality of life (Short Form 36 and Functional Outcomes of Sleep Questionnaire), symptom severity (Narcolepsy Severity Scale and Epworth Sleepiness Scale) and physical activity (Physical Activity Vital Sign) and sedentary behaviour (Sedentary Behaviour Questionnaire) of this sample. Several open-ended questions were asked to ascertain participants attitudes towards exercise and their physical performance. \n\nResults: In total, 23 participants completed the test battery. The majority of participants were female (n=13, 56.52%). The mean age (± SD) was 31.53 (13.17) years with a range of 20-63 years observed. The majority of participants were concentrated in the 20-29 age group (n=14, 60.87%). Physical performance was generally found to be lower than age-and-gender matched normative values for cardiopulmonary fitness, physical activity and muscle strength and endurance. Symptom severity was high as measured by the Narcolepsy Severity Scale and Epworth Sleepiness Scale, and participants reported significantly reduced quality of life when compared to general population norms. Analysis of the open-ended questions provided valuable insights into the difficulties experienced with exercising in people with narcolepsy. Furthermore, an interrelationship was identified between participants physical performance, health-related quality of life and symptom severity.\n\nConclusion: In this sample of people with narcolepsy, physical performance was found to be markedly reduced than normative values, irrespective of participant age, gender and BMI. The chosen test battery employed in this study was largely feasible, and participants were enthusiastic and receptive towards the study. The interrelationship identified between physical performance, symptom severity and quality of life warrants further exploration of the role of physical activity and exercise in improving the physical performance in people with narcolepsy, and the influence of exercise on health-related quality of life and symptom severity in this cohort.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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