The association between gastrointestinal injury, complaints, and food intake in 60-km ultramarathon runners
Bibliographic record
Abstract
We aimed to assess the association between gastrointestinal (GI) injury, complaints, and food intake in 60-km ultramarathon runners. Thirty-three ultramarathon runners provided pre- and post-race blood samples for assessment of GI injury by intestinal fatty-acid binding protein (I-FABP), and inflammatory response by interleukin (IL)-6, IL-8, tumour necrosis factor alpha (TNF-α), and C-reactive protein (CRP). GI complaints and nutritional intake were reported by a post-race questionnaire. GI complaints were reported by 73% of the runners, of which 20% reported 1 or 2 severe complaints. IL-6, IL8, TNF-α, and CRP increased significantly from pre- to post-race (P < 0.001 for all biomarkers), while I-FABP did not (1375 [IQR: 1264–2073] to 1726 [IQR: 985–3287] pg/mL; P = 0.330). The ‘GI complaints score’, as the integral of the number and severity of GI complaints, did not correlate with ΔI-FABP (rs: –0.050, P = 0.790) or energy intake (rs: 0.211, P = 0.260). However, there was a significant negative correlation between energy intake and ΔI-FABP (rs: –0.388, P = 0.031). In conclusion, GI complaints were neither associated with food intake nor GI injury as assessed by plasma I-FABP response. Energy intake, however, was inversely related to the I-FABP response to exercise. This finding suggests that substantial energy intakes during exercise may prevent exercise-induced GI injury as assessed by the I-FABP response. Novelty: No association between gastrointestinal complaints and gastrointestinal injury (I-FABP response) or food intake was present. There was an inverse correlation between energy intake and plasma I-FABP response, suggesting that higher energy intakes may prevent gastrointestinal injury as assessed by the I-FABP response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".