{"title":"基于5640餐数据的餐后血糖预测的简单公式-方法:数学-物理医学(No. 301)","authors":"","doi":"10.33140/jcei.05.05.004","DOIUrl":null,"url":null,"abstract":"This article is based on the continuation of the author’s research work, a simple and practical, yet highly accurate\npostprandial plasma glucose (PPG) prediction formula for type 2 diabetes (T2D) patients. His methodology is the\ndeveloped GH-Method: math-physical medicine (MPM) which has been utilized repeatedly in the past decade.\nThe predicted PPG formula-based on the status of fasting plasma glucose (FPG), carbs/sugar intake amount, and postmeal walking steps are as follows:\nPredicted PPG\n= 0.97 * FPG + (carbs/sugar grams * 1.8) - (post-meal walking steps in thousand * 5)\nThe conclusive results have the order of values m1 / m2 /m3 / prediction accuracy %.\nCase A: 1.8 / 5.0 / 0.97 / 99.8%\nCase B: 2.0 / 5.0 / 0.945 / 99.9%\nCase C: 2.2 / 5.0 / 0.92 / 99.9%\nExercise is important, contributing ~3% higher than food, is easily achieved compared to the required knowledge of\ndiet. As a result, the author spent four years to study food nutrition. Most T2D patients are seniors; therefore, he\nsuggests that walking is the best form of exercise. However, the most difficult part of exercise is the behavior psychology\nrelated to the issue of “discipline and persistence”. T2D patients need to walk between 2,000 to 4,000 steps after each\nmeal. The author walks an average of 4,300 steps after each meal. On the other hand, diet (carbs/sugar amount and\nnutritional balance) requires much more and deeper knowledge of food nutrition in order to control diabetes. Therefore,\nthe author developed an AI-based tool to assist T2D patients.\nFor non-tech patients, the following simple guidelines can assist with meal intake:\nStarchy food:\nEat an amount half of your fist or hand at most\nColorful vegetables:\nEat an amount limited to one fist or hand.\nGreen vegetables:\nEat an amount limited to 2.5 fists or hands.\nPlease note: you must combine two types of vegetable together in order to get the total intake limitation.\nThe author highly recommends the patients to measure their FPG at least several times a quarter, in order to get a\nquarterly average FPG value. The other three PPG values can then utilize the formula-based predicted PPG to control\ntheir overall diabetes conditions.\nThe described method mentioned above in regard to the predicted PPG formula along with the post-meal walking\nexercise and carbs/sugar intake amount can help patients control their diabetes without painful and troublesome fingerpiercing glucose measurements. The author has been measuring his glucoses for 8.5 years (3,126 days) with fingerpiercing glucose testing combined with his 10-years of diabetes research work. He hopes this article can provide useful\nguidelines to other diabetes patients to take back their lives from this dreadful chronic disease.","PeriodicalId":73657,"journal":{"name":"Journal of clinical & experimental immunology","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A simple formula based on postprandial plasma glucose prediction using 5,640\\nmeals data via GH-Method: math-physical medicine (No. 301)\",\"authors\":\"\",\"doi\":\"10.33140/jcei.05.05.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article is based on the continuation of the author’s research work, a simple and practical, yet highly accurate\\npostprandial plasma glucose (PPG) prediction formula for type 2 diabetes (T2D) patients. His methodology is the\\ndeveloped GH-Method: math-physical medicine (MPM) which has been utilized repeatedly in the past decade.\\nThe predicted PPG formula-based on the status of fasting plasma glucose (FPG), carbs/sugar intake amount, and postmeal walking steps are as follows:\\nPredicted PPG\\n= 0.97 * FPG + (carbs/sugar grams * 1.8) - (post-meal walking steps in thousand * 5)\\nThe conclusive results have the order of values m1 / m2 /m3 / prediction accuracy %.\\nCase A: 1.8 / 5.0 / 0.97 / 99.8%\\nCase B: 2.0 / 5.0 / 0.945 / 99.9%\\nCase C: 2.2 / 5.0 / 0.92 / 99.9%\\nExercise is important, contributing ~3% higher than food, is easily achieved compared to the required knowledge of\\ndiet. As a result, the author spent four years to study food nutrition. Most T2D patients are seniors; therefore, he\\nsuggests that walking is the best form of exercise. However, the most difficult part of exercise is the behavior psychology\\nrelated to the issue of “discipline and persistence”. T2D patients need to walk between 2,000 to 4,000 steps after each\\nmeal. The author walks an average of 4,300 steps after each meal. On the other hand, diet (carbs/sugar amount and\\nnutritional balance) requires much more and deeper knowledge of food nutrition in order to control diabetes. Therefore,\\nthe author developed an AI-based tool to assist T2D patients.\\nFor non-tech patients, the following simple guidelines can assist with meal intake:\\nStarchy food:\\nEat an amount half of your fist or hand at most\\nColorful vegetables:\\nEat an amount limited to one fist or hand.\\nGreen vegetables:\\nEat an amount limited to 2.5 fists or hands.\\nPlease note: you must combine two types of vegetable together in order to get the total intake limitation.\\nThe author highly recommends the patients to measure their FPG at least several times a quarter, in order to get a\\nquarterly average FPG value. The other three PPG values can then utilize the formula-based predicted PPG to control\\ntheir overall diabetes conditions.\\nThe described method mentioned above in regard to the predicted PPG formula along with the post-meal walking\\nexercise and carbs/sugar intake amount can help patients control their diabetes without painful and troublesome fingerpiercing glucose measurements. The author has been measuring his glucoses for 8.5 years (3,126 days) with fingerpiercing glucose testing combined with his 10-years of diabetes research work. He hopes this article can provide useful\\nguidelines to other diabetes patients to take back their lives from this dreadful chronic disease.\",\"PeriodicalId\":73657,\"journal\":{\"name\":\"Journal of clinical & experimental immunology\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of clinical & experimental immunology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33140/jcei.05.05.004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of clinical & experimental immunology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33140/jcei.05.05.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A simple formula based on postprandial plasma glucose prediction using 5,640
meals data via GH-Method: math-physical medicine (No. 301)
This article is based on the continuation of the author’s research work, a simple and practical, yet highly accurate
postprandial plasma glucose (PPG) prediction formula for type 2 diabetes (T2D) patients. His methodology is the
developed GH-Method: math-physical medicine (MPM) which has been utilized repeatedly in the past decade.
The predicted PPG formula-based on the status of fasting plasma glucose (FPG), carbs/sugar intake amount, and postmeal walking steps are as follows:
Predicted PPG
= 0.97 * FPG + (carbs/sugar grams * 1.8) - (post-meal walking steps in thousand * 5)
The conclusive results have the order of values m1 / m2 /m3 / prediction accuracy %.
Case A: 1.8 / 5.0 / 0.97 / 99.8%
Case B: 2.0 / 5.0 / 0.945 / 99.9%
Case C: 2.2 / 5.0 / 0.92 / 99.9%
Exercise is important, contributing ~3% higher than food, is easily achieved compared to the required knowledge of
diet. As a result, the author spent four years to study food nutrition. Most T2D patients are seniors; therefore, he
suggests that walking is the best form of exercise. However, the most difficult part of exercise is the behavior psychology
related to the issue of “discipline and persistence”. T2D patients need to walk between 2,000 to 4,000 steps after each
meal. The author walks an average of 4,300 steps after each meal. On the other hand, diet (carbs/sugar amount and
nutritional balance) requires much more and deeper knowledge of food nutrition in order to control diabetes. Therefore,
the author developed an AI-based tool to assist T2D patients.
For non-tech patients, the following simple guidelines can assist with meal intake:
Starchy food:
Eat an amount half of your fist or hand at most
Colorful vegetables:
Eat an amount limited to one fist or hand.
Green vegetables:
Eat an amount limited to 2.5 fists or hands.
Please note: you must combine two types of vegetable together in order to get the total intake limitation.
The author highly recommends the patients to measure their FPG at least several times a quarter, in order to get a
quarterly average FPG value. The other three PPG values can then utilize the formula-based predicted PPG to control
their overall diabetes conditions.
The described method mentioned above in regard to the predicted PPG formula along with the post-meal walking
exercise and carbs/sugar intake amount can help patients control their diabetes without painful and troublesome fingerpiercing glucose measurements. The author has been measuring his glucoses for 8.5 years (3,126 days) with fingerpiercing glucose testing combined with his 10-years of diabetes research work. He hopes this article can provide useful
guidelines to other diabetes patients to take back their lives from this dreadful chronic disease.