Effect of Exercise on Glycemic Status of Patients Suffering from type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: The number of people with diabetes is now considered to have reached epidemic proportions. Globally the incidence rate of type 1 and particularly type 2 diabetes are increasing in all societies. Type 2 diabetes is highly prevalent in elderly and is now emerging in childhood and accounts for more than 95% of all diabetes. Due to the rising tide of type 2 diabetes, it is a major international challenge for optimal intervention and prevention strategies. Objective: To see the effectiveness of exercise in type to diabetic patient . Materials and Methods: The study was carried out in the department of physiology of Mymensingh Medical College from July 2007 to June 2008. To assess glycemic status we estimate pre and post exercise blood glucose and glycated hemoglobin level of 101 study group whose age ranged from 38-70 years. Result: During the study time in this group of population pre and post exercise blood glucose level was respectively 9.18 mmoI/L and 8.05 mmoI/L, P vale ˂ 0.001,indicate the significance of exercise. Regular exercise for a period of 30 to 40 minutes in the form of walking seems to improve the glycemic status in type 2 diabetes mellitus. Conclusion: It can be concluded that regular exercise for a period of 30 to 40 munites in the form of walking seems to control blood glucose level within normal range in type 2 diabetes mellitus. So, health care professionals must address exercise in those patients as a part of treatment. J. Dhaka National Med. Coll. Hos. 2013;19 (01): 6-10
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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 | 0.002 |
| 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 | 0.001 |
| 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".