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Record W2084875667 · doi:10.1097/fjc.0b013e31821533cc

Short-term Aerobic Exercise Reduces Nitroglycerin-induced Orthostatic Intolerance in Older Adults With Type 2 Diabetes

2011· article· en· W2084875667 on OpenAlexafffund
Kenneth Madden, Chris Lockhart, Tiffany Potter, D. Cuff, Graydon S. Meneilly

Bibliographic record

VenueJournal of Cardiovascular Pharmacology · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMedicineAerobic exerciseOrthostatic intoleranceType 2 diabetesPhysical therapyDiabetes mellitusOrthostatic vital signsInternal medicineBlood pressureEndocrinology

Abstract

fetched live from OpenAlex

AIMS/HYPOTHESIS: Older adults are at a high risk for syncope due to orthostatic intolerance (OI), and this risk increases with comorbid type 2 diabetes and vasoactive medications. Despite many benefits, previous investigations have shown worsening OI with aerobic training. We examined whether aerobic exercise reduced OI in older adults with type 2 diabetes who were given a short-acting vasoactive agent (nitroglycerin). METHODS: Forty older adults (25 males and 15 females, mean age 71.4 ± 0.7 years, ranging in age from 65 to 83 years) with type 2 diabetes were recruited. Subjects were randomized to each of 2 groups: an aerobic group (3 months of vigorous aerobic exercise) and a nonaerobic (no aerobic exercise) group. Exercise sessions were supervised by a certified exercise trainer 3 times per week. After being given 400 μg of sublingual nitroglycerin, each subject was placed in a 70° head-up tilt for 30 minutes. RESULTS: When the 2 groups were compared using a Cox proportional hazards model, tilt table tolerance was significantly better in the aerobic group as compared to in the nonaerobic group (χ(2)(MC) = 7.271, P = 0.007). CONCLUSIONS: Our findings indicate that a relatively short aerobic exercise intervention can improve postnitroglycerin orthostatic tolerance in older adults with type 2 diabetes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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 designOther design
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

Citations8
Published2011
Admission routes2
Has abstractyes

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