Electrocardiographic findings in athletes: the prevalence of left ventricular hypertrophy and conduction defects.
Bibliographic record
Abstract
OBJECTIVES: To determine whether there are electrocardiographic differences or distinctive abnormalities between athletes and sedentary subjects, and to verify the relationship between vagal activity measured by heart rate variability (SD of all normal-to-normal intervals [SDNN]) and possible electrocardiographic abnormalities. SUBJECTS AND METHODS: Resting electrocardiograms and heart rate variability measurements were performed separately during a single visit on 100 athletes and 50 nonathlete control subjects aged 18 to 55 years. The athletes were from the following various sports disciplines: long-distance running, mountain biking, cross-country skiing, biathlon, speed skating, swimming and triathlon. RESULTS AND CONCLUSIONS: There were significantly longer RR intervals, PR intervals and QT intervals in athletes than in control subjects (all P<0.05). The QRS complex and QTc did not show significant differences (both P>0.05). The prevalence of left ventricular hypertrophy (LVH) and incomplete right bundle branch block (IRBBB) was 10% and 7%, respectively, in athletes, but these conditions were absent in control subjects; among athletes, 2% presented with both conditions. LVH and IRBBB were more common among long-distance runners (six of 14 and four of 14, respectively) and could be attributed to normal, long term adaptation to intense, repeated exercise. LVH was related to age (P=0.04), whereas IRBBB was influenced by the number of years of training in the respective sports discipline (P=0.03). The mean SDNN value was significantly more elevated in athletes (P=0.0001), reflecting a higher parasympathetic tone than in sedentary control subjects. However, there was no relationship between vagal activity and LVH or IRBBB (both P>0.05).
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".