## GH-METHODS

Math-Physical Medicine

### NO. 267

Investigation on the impact of different glucose ranges and the damage on human internal organs using frequency domain analyses (GH-Method: math-physical medicine)

Corresponding Author: Gerald C. Hsu, eclaireMD Foundation, USA.

Introduction
In this paper, the author describes his research results on the impact of different glucose ranges and the damage on human internal organs using the frequency domain analysis technique.

Methods
He has collected his glucose data via a continuous glucose monitor (CGM) sensor device from 5/5/2018 through 6/1/2020 at ~76.5 glucose data per day.  For the ~2-year period (758 days), he collected a total of 57,987 glucose data. As a reference, he also listed his average glucose values from his 3,032 finger-pierced glucose data at 4-data points per day.  In this particular analysis, he did not distinguish the differences between FPG versus PPG, but instead used his daily average glucose values to conduct his mathematical analysis.

Initially, he collected and displayed his “time-domain” data result, which represents the horizontal x-axis as time (day) and the vertical y-axis as glucose (mg/dL) – similar to an EKG chart for heart.  Next, he utilized a mathematical algorithm based on “Fourier Transform” technique to convert these time domain data into frequency domain data.  In the frequency domain chart, the x-axis becomes frequency scale, instead of time scale, and the y-axis becomes the amplitude scale associated with each distinctive frequency value, instead of glucose scale.  In one of his earlier published article (Reference 1), he proved this y-axis value in the frequency domain, which actually indicates the “relative” energy level associated with that particular frequency on x-axis.  Based on this frequency domain data chart, he could then segregate the total frequency range into several different sub-ranges of frequency.  As shown in Figure 1, it depicts an example of the process mentioned above.

In the glucose frequency domain diagram, we can see that the waveform (or curve) pattern is a symmetric salad bowl shape with the high edge on each rim.  Let us focus on the left-half of this chart.  The far left side indicates the lower-frequency range, those higher glucose values associated with lower frequency between 0 and 16; with higher amplitude, more individual energy; while the center specifies the higher-frequency range, those lower glucose values associated with higher frequency above 16, with lower amplitude or less individual energy.

The above applications are directly applied from both physics and mathematics. Now, let us discuss the biomedical side.

• Pre-diabetes condition (between 120 mg/dL and 140 mg/dL)  versus diabetes condition (> 140 mg/dL)
• TAR (glucose > B = 180), TIR (A < glucose < B = 180), TBR (glucose < A); where value A is defined by the author for the specific purpose of his analysis (Reference 2).

Here, the author wants to focus on the glucose range between 120 and 140, i.e. the “grey area” between pre-diabetes conditions and diabetes conditions.  Therefore, he has chosen two values for A, 120 mg/dL and 140 mg/dL, instead of 70 mg/dL for TBR as suggested by ADA guidance (Reference 2).  Besides, his glucose records indicate his ADA defined TBR (< 70 mg/dL) is only 5% which means his risk of insulin shock is extremely low.  His purpose is to identify how much relative damage on the internal organs due to energy associated with this grey area between the pre-diabetes and full diabetes conditions, i.e. within the range of 120 mg/dL and 140 mg/dL.

Glucose value is associated with certain frequency range.  Each frequency range is associated with certain energy level that creates a level of damage on the internal organs.  Therefore, in order to accomplish his research objectives, he has to modify and enhance his software programs in order to be able to calculate the relative energy level of any user-defined frequency range.

Results
Figure 2 shows his summarized analysis data table.  Figures 3 through 6 illustrate graphic presentations of the data table in Figure 2.  Figures 3 and 4 depict diabetes case, i.e. TIR is within 140 mg/dL and 180 mg/dL, TBR is less than 140 mg/dL.  Figures 5 and 6 represent pre-diabetes case, i.e. TIR is within 120 mg/dL and 180 mg/dL, TBR is less than 120 mg/dL.  For both diabetes and pre-diabetes cases, TAR is defined as greater than 180 mg/dL, in order to investigate the energy generated from those extremely high glucose components (180 mg/dL was chosen for this research work).

Figure 1 is merely displaying certain prominent features of both time-domain and frequency-domain.  Readers can delve deeper into Figures 2 through 6 to find out more detailed information.

Figure 4, the conclusive figure for diabetes case, shows:

• Energy of TAR (> 180):  13%
• Energy of TIR (140 – 180):  60%
• Energy of TBR (< 140):  27%

Figure 6, the conclusive figure for pre-diabetes case, shows:

• Energy of TAR (> 180):  13%
• Energy of TIR (120 – 180):  35%
• Energy of TBR (< 120):  52%

When we subtract the pre-diabetes TIR % from the diabetes TIR %, we get a 25% of associated energy difference which belongs to the glucose range of 120 mg/dL to 140 mg/dL.

Another observation is that the subtotal energy associated with glucoses above 140 mg/dL causes 48% of organ damage; however, the glucose range between 120 and 140 also contributes another 25% of damage. This means that all of his glucose components above 120 mg/dL would contribute a 73% of total impact on his internal organs.

###### Figure 6: Pre-Diabetes glucose range’s energy contribution %

Conclusions
In general, diabetes patients who are disciplined would focus on their daily glucose level and try to maintain a value below 140 mg/dL.  It is a good practice for this diabetes conditions.  However, this article provides another message that even the glucoses in the range between 120 mg/dL and 140 mg/dL can contribute 25% of the associated energy to impact their internal organs.

The research work illustrated in this article is to better understand glucose situations better and deeper.  It also proves that GH-Method: math-physical medicine is a powerful methodology to discover more hidden truths regarding diseases and health matters.

References

1. Hsu, Gerald C., eclaireMD Foundation, USA. October 2019. No. 120: “The study on the damage to internal organs and the pancreatic beta cells health state due to excessive energy associated with high PPG components and distinctive waveforms using GH-Method: math-physical medicine.”
2. Hsu, Gerald C., eclaireMD Foundation, USA. March 2020. No. 238: “The influences of medication on diabetes control using TIR analysis (GH-Method: Math-physical medicine).”
3. Hsu, Gerald C., eclaireMD Foundation, USA. April 200. No. 246: “Segmentation analysis of sensor glucoses and their associated energy (GH-Method: math-physical medicine).”