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Record W2586892442 · doi:10.1186/s12906-017-1595-5

Medication use by middle-aged and older participants of an exercise study: results from the Brain in Motion study

2017· article· en· W2586892442 on OpenAlexafffundabout
Tania Pannu, Sarah Sharkey, Grazyna M Burek, Daniela Creţu, Michael D. Hill, David B. Hogan, Marc J. Poulin

Bibliographic record

VenueBMC Complementary and Alternative Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsLibin Cardiovascular Institute of AlbertaFoothills Medical CentreUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlberta InnovatesCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaAlberta Innovates - Health Solutions
KeywordsMedicineOver-the-counterPopulationInternal medicinePhysical therapyMedical prescriptionPharmacologyEnvironmental health

Abstract

fetched live from OpenAlex

Over the past 50 years, there has been an increase in the utilization of prescribed, over-the-counter (OTC) medications, and natural health products. Although it is known that medication use is common among older persons, accurate data on the patterns of use, including the quantity and type of medications consumed in a generally healthy older population from a Canadian perspective are lacking. In this study, we study the pattern of medication use in a sedentary but otherwise healthy older persons use and determined if there was an association between medication use and aerobic fitness level. All participants enrolled in the Brain in Motion study provided the name, formulation, dosage and frequency of any medications they were consuming at the time of their baseline assessment. Maximal aerobic capacity (VO 2 max) was determined on each participant. Two hundred seventy one participants (mean age 65.9 ± 6.5 years; range 55–92; 54.6% females) were enrolled. Most were taking one or more (1+) prescribed medication ( n = 204, 75.3%), 1+ natural health product ( n = 221, 81.5%) and/or 1+ over-the-counter (OTC) drug ( n = 174, 64.2%). The most commonly used prescribed medications were HMG-CoA reductase inhibitors (statins) ( n = 52, 19.2%). The most common natural health product was vitamin D ( n = 201, 74.2%). For OTC drugs, non-steroidal anti-inflammatories ( n = 82, 30.3%) were the most common. Females were more likely than males to take 1+ OTC medications, as well as supplements. Those over 65 years of age were more likely to consume prescription drugs than their counterparts ( p ≤ 0.05). Subjects taking more than two prescribed or OTC medications were less physically fit as determined by their VO 2 max. The average daily Vitamin D intake was 1896.3 IU per participant. Medication use was common in otherwise healthy older individuals. Consumption was higher among females and those older than 65 years. Vitamin D intake was over two-fold higher than the recommended 800 IU/day for older persons, but within the tolerable upper intake of 4,000 IU/day. The appropriateness of the high rate of medication use in this generally healthy population deserves further investigation.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.267
GPT teacher head0.415
Teacher spread0.148 · 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 teacher head, 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

Citations9
Published2017
Admission routes3
Has abstractyes

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