Lack of independent effect of type 2 diabetes beyond characteristic comorbidities and medications on small muscle mass exercising muscle blood flow and exercise tolerance
Bibliographic record
Abstract
Persons with type 2 diabetes (T2D) are believed to have reduced exercise tolerance; this may be partly due to impaired exercising muscle blood flow (MBF). Whether there is an impact of T2D on exercising MBF within the typical constellation of comorbidities (hypertension, dyslipidemia, obesity) and their associated medications has not been investigated. We tested the hypothesis that small muscle mass exercise tolerance is reduced in persons with T2D versus Controls (matched for age, body mass index, fitness, comorbidities, non-T2D medications) and that this is related to blunted MBF. Eight persons with T2D and eight controls completed a forearm critical force (fCFimpulse) test as a measure of exercise tolerance (10-min intermittent maximal effort forearm contractions; the average contraction impulse in the last 30 sec quantified fCFimpulse). Forearm blood flow (FBF; ultrasound) and mean arterial pressure (MAP; finger photoplethysmography) were measured; forearm vascular conductance (FVK) was calculated. Data are means ± SD, T2D versus Control. fCFimpulse was not different between groups (136.9 ± 47.3 N·sec vs. 163.1 ± 49.7 N·sec, P = 0.371) nor was the ∆FBF from rest to during exercise at fCFimpulse (502.9 ± 144.6 vs. 709.1 ± 289.2 mL/min, P = 0.092), or its determinants ∆FVK and ∆MAP (both P > 0.05), although there was considerable interindividual variability. ∆FBF was strongly related to fCFimpulse (r = 0.727, P = 0.002), providing support for the relationship between oxygen delivery and exercise tolerance. We conclude that small muscle mass exercising MBF and exercise tolerance are not impaired in representative persons with T2D versus appropriately matched controls. This suggests that peripheral vascular control impairment does not contribute to reduced exercise tolerance in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".