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Record W2225074001 · doi:10.1001/jamaneurol.2015.4265

Association Between Change in Body Mass Index, Unified Parkinson’s Disease Rating Scale Scores, and Survival Among Persons With Parkinson Disease

2016· article· en· W2225074001 on OpenAlexaboutno aff
Anne‐Marie Wills, Adriana Pérez, Jue Wang, Xiao Su, John C. Morgan, Suja S. Rajan, Maureen A. Leehey, Gregory M. Pontone, Kelvin L. Chou, Chizoba C. Umeh, Zoltán Mari, James T. Boyd

Bibliographic record

VenueJAMA Neurology · 2016
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and Stroke
KeywordsParkinson's diseaseRating scaleBody mass indexDiseaseAssociation (psychology)MedicineGerontologyPsychologyInternal medicineDevelopmental psychology

Abstract

fetched live from OpenAlex

IMPORTANCE: Greater body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) is associated with improved survival among persons with Huntington disease or amyotrophic lateral sclerosis. Weight loss is common among persons with Parkinson disease (PD) and is associated with worse quality of life. OBJECTIVE: To explore the association between change in BMI, Unified Parkinson's Disease Rating Scale (UPDRS) motor and total scores, and survival among persons with PD and to test whether there is a positive association between BMI at randomization and survival. DESIGN, SETTING, AND PARTICIPANTS: Secondary analysis (from May 27, 2014, to October 13, 2015) of longitudinal data (3-6 years) from 1673 participants who started the National Institute of Neurological Disorders and Stroke Exploratory Trials in PD Long-term Study-1 (NET-PD LS-1). This was a double-blind randomized placebo-controlled clinical trial of creatine monohydrate (10 g/d) that was performed at 45 sites throughout the United States and Canada. Participants with early (within 5 years of diagnosis) and treated (receiving dopaminergic therapy) PD were enrolled from March 2007 to May 2010 and followed up until September 2013. MAIN OUTCOMES AND MEASURES: Change across time in motor UPDRS score, change across time in total UPDRS score, and time to death. Generalized linear mixed models were used to estimate the effect of BMI on the change in motor and total UPDRS scores after controlling for covariates. Survival was analyzed using Cox proportional hazards models of time to death. A participant's BMI was measured at randomization, and BMI trajectory groups were classified according to whether participants experienced weight loss ("decreasing BMI"), weight stability ("stable BMI"), or weight gain ("increasing BMI") during the study. RESULTS: Of the 1673 participants (mean [SD] age, 61.7 [9.6] years; 1074 [64.2%] were male), 158 (9.4%) experienced weight loss (decreasing BMI), whereas 233 (13.9%) experienced weight gain (increasing BMI). After adjusting for covariates, we found that the weight-loss group's mean (SE) motor UPDRS score increased by 1.48 (0.28) (P < .001) more points per visit than the weight-stable group's mean (SE) motor UPDRS score. The weight-gain group's mean (SE) motor UPDRS score decreased by -0.51 (0.24) (P = .03) points per visit, relative to the weight-stable group. While there was an unadjusted difference in survival between the 3 BMI trajectory groups (log-rank P < .001), this was not significant after adjusting for covariates. CONCLUSIONS AND RELEVANCE: Change in BMI was inversely associated with change in motor and total UPDRS scores in the NET-PD LS-1. Change in BMI was not associated with survival; however, these results were limited by the low number of deaths in the NET-PD LS-1. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00449865.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.248
Teacher spread0.231 · 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".

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Citations95
Published2016
Admission routes1
Has abstractyes

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