Inflammatory Response to Ultramarathon Running: A Review of IL-6, CRP, and TNF-α
Bibliographic record
Abstract
Ultramarathon running elicits a profound inflammatory response, characterized by significant increases in interleukin-6 (IL-6) and C-reactive protein (CRP), with comparatively modest changes in tumor necrosis factor-alpha (TNF-α). We reviewed approximately 80 field studies of ultramarathon events (distances >42.2 km) that measured IL-6, CRP, and TNF-α before and after races. IL-6 typically spiked immediately post-race-often rising dozens or even thousands of times above baseline-then rapidly declined, usually returning to near baseline within 24-48 h. CRP, an acute-phase protein, exhibited a slower, sustained elevation, peaking 24-72 h after race completion and remaining above baseline for 2-3 days before gradually returning to normal. TNF-α responses were variable: some studies reported small but significant post-race increases (roughly 1.2-1.7-fold above baseline), while others found no significant change in circulating TNF-α despite the extreme effort. Longer race durations and distances generally correlated with higher peak IL-6 and CRP levels. Experienced ultramarathon runners tended to exhibit attenuated inflammatory responses compared with less-trained individuals, and anti-inflammatory cytokines (e.g., IL-10) increased in tandem with IL-6 in well-trained athletes, helping to mitigate TNF-α elevations. In total, 28 studies were included in the final synthesis, and their quality was assessed using the Newcastle-Ottawa Scale. Visual synthesis tools, including a PRISMA flowchart and time course plots, are provided to enhance the narrative's interpretability. In summary, ultramarathon running elicits a robust systemic inflammatory response with distinct temporal patterns for IL-6, CRP, and TNF-α. These findings have important implications for athlete recovery, monitoring, and understanding the physiological limits of the inflammatory response to extreme endurance stress.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".