Effects of Intermittent Fasting on Serum Lipid Levels, Coagulation Status and Plasma Homocysteine Levels
Bibliographic record
Abstract
BACKGROUND: During Ramadan, Muslims fast during the daylight hours for a month. The duration of restricted food and beverage intake is approximately 12 h/day which makes Ramadan a unique model of intermittent fasting. Many physiological and psychological changes are observed during Ramadan that are probably due to the changes in eating and sleeping patterns. METHODS: Serum total cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), prothrombin time, activated partial thromboplastin time (aPTT), plasma fibrinogen, D-dimer and homocysteine levels were measured in 24 healthy fasting volunteers (12 females, 12 males) aged 21-35 years. Venous blood samples were taken 1 week before Ramadan, on the 21st day of Ramadan and 20 days after Ramadan. RESULTS: No significant changes were observed on serum total cholesterol, triglycerides and LDL levels. HDL levels were significantly elevated during Ramadan (p < 0.001) and 20 days after Ramadan (p < 0.05). Prothrombin time, aPTT, fibrinogen and D-dimer levels were in the physiologic limits in all samples but D-dimer levels were significantly low at the end of Ramadan in comparison to pre- and post-fasting levels (p < 0.001). Homocysteine levels, being still in reference ranges, were low during Ramadan (p < 0.05) and reached the pre-fasting levels after Ramadan. CONCLUSION: Our results demonstrate that intermittent fasting led to some beneficial changes in serum HDL and plasma homocysteine levels, and the coagulation status. These changes may be due to omitting at least one meal when the body was particularly metabolically active and possibly had a low blood viscosity level at the same time. We conclude that intermittent fasting may have beneficial effects on hemostatic risk markers for cardiovascular diseases.
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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 | 0.000 |
| 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".