The Glycemic Index, Postprandial Hypotension and Cardiovascular Disease
Bibliographic record
Abstract
High glycemic index diets have been associated with an increased risk of cardiovascular disease events and all-cause mortality. We suggest that part of the reason for this association is through the effect of the rapidly digested high glycemic index carbohydrate diets in promoting the effects of postprandial hypotension in vulnerable individuals. Postprandial hypotension has been recognized as a problem especially affecting the frail elderly. The phenomenon occurs earlier in the day and includes syncope and falls acutely and more serious cardiovascular events and increased all-cause mortality in the longer-term. The mechanism appears to relate to the rapid digestion of carbohydrates foods. Strategies that reduce the amount of meal carbohydrates and their rate of absorption by enzyme inhibition or by delaying gastric emptying and have proved helpful as has increased fluid intake, presumably due to dilution of small intestinal contents and a reduction in the tonicity, so reducing the need for intestinal fluid secretion to dilute osmotically active sugars and products of digestion. In this way the need for increased blood flow to the gut can be reduced, that would otherwise steal blood from the systemic circulation resulting in a drop in blood pressure and an increase in heart rate. Slowly absorbed or low glycemic index carbohydrates would therefore appear potentially useful as part of the dietary strategy for the treatment of postprandial hypotension and conversely postprandial hypotension could be one of the reasons why high glycemic index diets have been associated with increased CVD risk.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".