Consumption of caffeinated coffee and a high carbohydrate meal affects postprandial metabolism of a subsequent oral glucose tolerance test in young, healthy males
Bibliographic record
Abstract
Caffeine and caffeinated coffee (CC) elicit acute insulin insensitivity when ingested before a carbohydrate load. The effects of CC on glucose tolerance and insulin sensitivity when co-ingested with a high carbohydrate meal and on postprandial metabolism of a subsequent (second) carbohydrate load have not been studied. In a randomised, crossover design, ten healthy males ingested either CC (5 mg caffeine/kg body weight), decaffeinated coffee (DC) or water (W; equal volume) co-ingested with a high glycaemic index cereal followed 3 h later by a 75 g oral glucose tolerance test. After the initial meal, insulin area under the curve (AUC) and insulin sensitivity index did not differ between treatments, although glucose AUC for CC (107 (sem 18) mmol/l x 3 h) and DC (74 (sem 15) mmol/l x 3 h) was greater than W ( - 0.2 (sem 29) mmol/l x 3 h, P < 0.05). After the second carbohydrate load, insulin AUC for CC was 49 % and 57 % greater (P < 0.01) than for DC and W, respectively. Despite the greater insulin response, glucose AUC for CC (217 (sem 24) mmol/l x 2 h) was greater than both DC (126 (sem 11) mmol/l x 2 h, P = 0.01) and W (55 (sem 34) mmol/l x 2 h, P < 0.001). Insulin sensitivity index after the second meal was lower after CC (8.2 (sem 0.9)) compared with both DC (12.4 (sem 1.2), P < 0.01) and W (13.4 (sem 1.4), P < 0.001). Co-ingestion of CC with one meal resulted in insulin insensitivity during the postprandial phase of a second meal in the absence of further CC ingestion. Thus, CC may play a role in daily glycaemic management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".