MétaCan
Menu
← Back to cohort
Record W2322664613 · doi:10.1249/mss.0b013e318267aa6b

Fitness, Fatness, and Metformin

2012· letter· en· W2322664613 on OpenAlexaffabout
Bareket Falk, Raffy Dotan

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2012
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsBrock University
Fundersnot available
KeywordsCardiorespiratory fitnessMetforminMedicineVO2 maxLean body massBody weightPopulationObesityFat massPhysical fitnessEndocrinologyInternal medicinePhysiologyAnimal sciencePhysical therapyBlood pressureDiabetes mellitusEnvironmental healthBiologyHeart rate

Abstract

fetched live from OpenAlex

Dear Editor-in-Chief: In a recent study, Rynders et al. (4). came to a potentially significant conclusion that the antidiabetic drug metformin provides no added benefit to 6 months of lifestyle modifications among obese adolescents. The authors reported improvements in body composition, inflammatory factors, and cardiorespiratory fitness (CRF) in a group of obese adolescents, whether or not they used metformin. This conclusion certainly strengthens the importance of and promotes proper nutrition and physical activity in that population. The authors further observed that the improvements in body composition and inflammatory factors were much more pronounced in those participants who had demonstrated an improvement in CRF, as reflected by increased maximal oxygen consumption (V˙O2max). They thus concluded that future intervention programs should be designed to increase V˙O2max. Although we generally agree with such recommendations, the authors’ conclusion is not borne out by their reported data. V˙O2 and V˙O2max are measured in absolute terms of liters of O2 per minute. When training effects are assessed in adults, these absolute values are the yardsticks for changes in CRF. In such individuals, body weight–normalized values may reflect weight loss or gain due to training, diet, or other factors. However, when children or adolescents are assessed, increases in absolute V˙O2max may reflect growth-related gains in muscle mass (2). To take into account both the training and growth factors, one should normalize V˙O2max to fat-free mass rather than to total body mass. When a 4.1 mL O2·kg−1·min−1 improvement in V˙O2max is observed in conjunction with a 4.3-kg weight loss, as was reported in the present study, one should be hard pressed to assign the improvement to fitness gain rather than to weight loss. We suggest that the observed V˙O2max increase reflects weight reduction rather than increased CRF. The authors note that “these favorable changes occurred with an average of only one supervised exercise setting per week” (4, p. 790). Indeed, the 12.5% V˙O2max improvement after a single weekly session contradicts previous findings in youths (1,3). Although the data provided in the article do not allow us to examine the effect of weight reduction on V˙O2max, the data in Table 2 (4) can easily be interpreted to mean that favorable changes in inflammatory factors and CRF were more pronounced in participants with greater reductions in body weight and fat percentage. The authors have the data (absolute V˙O2max, body mass, and fat percentage) and may be interested in verifying our suggestion. Moreover, the reported maximal test values (heart rates <160 beats·min−1, low RERs that diminished posttraining, and V˙O2max <21 mL O2·kg−1·min−1) suggest that the incremental test performed by the participants resulted in peak rather than maximal V˙O2max values. We propose that the observed postintervention augmentation of cardiovascular values could also reflect the participants’ habituation to the testing environment. Thus, the study certainly supports the importance of lifestyle modifications in obese adolescents. It also demonstrates an association between weight reduction and improvement in V˙O2max. However, it neither proves nor disproves the significance of exercise training in improving cardiorespiratory fitness. The training load was simply insufficient. Bareket Falk, PhD Department of Kinesiology Brock University, St. Catharines, ON, Canada Raffy Dotan, MSc Faculty of Applied Health Sciences Brock University, St. Catharines, ON, Canada The authors declare no conflicts of interest.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0080.004

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 head0.013
GPT teacher head0.260
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & Exercise→Same topicMuscle metabolism and nutrition→French-language works237,207→