Three Predicted HbA1C Equations and Results in Comparison with Lab-Tested A1C from 12 Discrete Lab-Tested Dates over a 3-Year Period Based on GHMethod: Math-Physical Medicine (No. 467)
Abstract
Gerald C Hsu
The author has utilized his collected data of finger pierced glucose readings 4x daily, carbs-sugar intake amount and postmeal walking steps for each meal over a 4-year period, from 2017 to 2020, to calculate the predicted HbA1C values (daily finger A1C). His previously predicted A1C values were conducted 10x close to 10 different lab-tested dates over 5 months for each period. During the 10 continuous 5-month periods, he achieved a 100% prediction accuracy using the daily finger A1C model. Starting from 5/5/2018, along with the finger glucoses, he collected 96 glucose data per day for 1,127 days using a continuous glucose monitoring (CGM) sensor device for a total of ~105,120 glucose data. He noticed that from 5/5/2018 through 6/5/2019, his average daily sensor glucose (123.96 mg/dL) is 12% higher than his average daily finger glucose (110.72 mg/ dL); therefore, if he uses the same formula for predicting HbA1C, it will result in a 12% higher Sensor A1C (7.39%) than his finger A1C (6.60%). In order to match his predicted sensor A1C with the lab A1C, he must multiply the average sensor glucose with a conversion factor to obtain the HbA1C value. In this article, he uses the 90-days moving average daily glucose data, eAG as his calculation base, which applies to the following three different equations as his predicted HbA1C formula with a conversion factor (CF):
(a) Daily A1C = (finger eAG) / 16.84
(b) New A1C-1 = (29% * sensor eAG +71% * GF) / 15.75
(c) New A1C-2 = (sensor eAG) / 18.86
The 3 conversion factors, 16.84, 15,75, 18.86, are the best-fitted CF values via a trial-and-error approach in order to make his predicted-A1C as close to the lab-A1C as possible. It should be noted that the New A1C-1 includes the influences from the glucose fluctuation (GF) factor. The GF influenced the outcomes of diabetes complications such as Stroke, Atherosclerosis, and cardiovascular disease. Furthermore, by choosing a high weighting factor of 71% for GF, it would modify the basic characteristics of the traditionally defined HbA1C. For example, the New A1C-1 has a different waveform shape from the daily finger A1C and New A1C-2 (daily sensor A1C) under the influences of eAG only.