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Estimation of Primary Prevention of Gout in Men Through Modification of Obesity and Other Key Lifestyle Factors

2020· article· en· W3108832682 on OpenAlex
Natalie McCormick, Na Lu, Chio Yokose, Gary C. Curhan, Hyon K. Choi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsResearch Canada
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteCanadian Institutes of Health Research
KeywordsLifestyle modificationPrimary preventionGoutObesityKey (lock)MedicineGerontologyPhysical therapyEnvironmental healthInternal medicineComputer science

Abstract

fetched live from OpenAlex

Importance: The population impact of modifying obesity and other key risk factors for hyperuricemia has been estimated in cross-sectional studies; however, the proportion of incident gout cases (a clinical end point) that could be prevented by modifying such factors has not been evaluated. Objective: To estimate the proportion of incident gout cases that could be avoided through simultaneous modification of obesity and other key risk factors. Design, Setting, and Participants: The Health Professionals Follow-up Study is a US prospective cohort study of 51 529 male health professionals enrolled in 1986 and followed up through questionnaires every 2 years through 2012. Self-reported gout cases were confirmed through June 2015. Clean and complete data used for this analysis were available in June 2016, with statistical analyses performed from July 2016 to July 2019. Exposures: From data collected in the validated questionnaires, men were categorized to low-risk groups according to combinations of the following 4 factors: normal body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]; <25), no alcohol intake, adherence to Dietary Approaches to Stop Hypertension (DASH)-style diet (highest quintile of DASH diet score), and no diuretic use. Main Outcomes and Measures: Population attributable risks (PARs) for incident gout meeting the preliminary American College of Rheumatology survey criteria, overall and stratified by BMI. Results: We analyzed 44 654 men (mean [SD] age, 54.0 [9.8] years) with no history of gout at baseline. During 26 years of follow-up, 1741 (3.9%) developed incident gout. Among all participants, PAR for the 4 risk factors combined (BMI, diet, alcohol use, and diuretic use) was 77% (95% CI, 56%-88%). Among men with normal weight (BMI <25.0) and overweight (BMI 25.0-29.9), we estimated that more than half of incident gout cases (69% [95% CI, 42%-83%] and 59% [95% CI, 30%-75%], respectively) may have been prevented by the combination of DASH-style diet, no alcohol intake, and no diuretic use. However, among men with obesity (BMI ≥30), PAR was substantially lower and not significant (5% [95% CI, 0%-47%]). Conclusions and Relevance: The findings of this cohort study suggest that addressing excess adiposity and other key modifiable factors has the potential to prevent the majority of incident gout cases among men. Men with obesity may not benefit from other modifications unless weight loss is addressed.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.052
GPT teacher head0.308
Teacher spread0.256 · 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