Alterations in Cardiac Function Following Endurance Exercise Are Not Duration Dependent
Bibliographic record
Abstract
Cardiac function has been shown to transiently decrease following prolonged exercise, with greater durations related to increased impairment. However, the prospective assessment of exercise duration on cardiac performance is rare, and the influence of relative exercise intensity is typically not assessed in relation to these changes. The aim of this study was to determine whether progressively longer running distances over the same course would elicit greater cardiac impairment. The present investigation examined cardiac alterations in 49 athletes, following trail-running races of 25km, 50km, 80km, and 160km, performed on the same course on the same day. Echocardiography, including conventional and speckle tracking imaging, was performed with legs-raised to 60° to mitigate alterations in preload both pre-and-post race. Race-intensities were monitored via heart rate (HR). Following the races, mean arterial pressure (Δ-11±7mmHg, P<0.0001), and HR (Δ19±14bpm, P<0.0001) were altered independent of race distance. Both left and right ventricular (LV and RV) diastolic function were reduced (ΔLV E/A -0.54±0.49, P<0.0001; ΔRV A’ +0.02±0.04m/s, P=0.01) and RV systolic function decreased (ΔTAPSE -0.25±0.9cm, P=0.01), independent of race distance. Cardiac impairment was not apparent using speckle tracking analysis with cubic spline interpolation. While race duration was unrelated to cardiac alterations, increased racing HR was related to greater RV base dilation (r =-0.37, P=0.03). Increased time spent at higher exercise intensities was related to reduced LV ejection fraction following 25km (r=-0.81, P=0.03), LV systolic strain rate following 50km (r=0.59, P=0.04), and TAPSE (r=-0.81, P=0.03) following 80km races. Increased running duration did not affect the extent of exercise-induced cardiac fatigue, however, intensity may be a greater driver of cardiac alterations.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".