Raised blood sugar: Diabetes mellitus – autoimmune diabetes

Irene Kolbe, Naturopath, Hanover, Germany

Dear Colleagues and Senior Management, Mr Sinn and all colleagues at Regumed

How a working hypothesis became a certainty

I began my lecture last year with these words and presented you with the changes in blood seen in dark field using bioresonance.

I also made further comparisons in order to show in images how different influences over months and years can produce new results.

You were shown images before and after therapy. Here is one of the images again as a , which I presented last time.

reminder of the case of Mr A

The above picture is now over three years old.

A proportion of the patients, whose images I looked at and in which a change became visible, are patients who also developed type 1 diabetes from viral stresses. It is often only at this stage, however, that they come to my practice.

Autoimmune diabetes – DISCOURSE
Pathomechanism

We now believe that type 1 diabetes is caused by both an interaction between genetic predisposition and external factors

(e.g. certain viral infections such as the EpsteinBarr virus, Cytomegalovirus and other slow virus infections) and by immune dysregulation. Certain T lymphocytes have been described that specifically target the beta cells in the pancreas. Likewise antibodies against beta cells have been found and against glutamate decarboxylase or directly against insulin. As a result of immunological dysfunction, the insulinproducing cells are destroyed causing a total deficiency in insulin.

The term glutamate decarboxylase (GAD) is a generic name for enzymes acting as catalysts in the reaction of glutamate to gamma aminobutyric acid (GABA) and to carbon dioxide. From a chemical perspective, this is decarboxylation, reflecting the name of the enzyme group.

The peak ages for the disease are in childhood and adolescence, however it can affect virtually anyone at any age.

Not every patient is immediately given an insulin pump or sensor for tissue measurement. Certain criteria have to be met.

Blood sugar and tissue glucose

Continuous glucose monitoring systems (CGMS) are officially only approved as a supplement to conventional blood sugar selfmonitoring and not as a replacement. The reason lies in the measuring principle used in CGM systems.

CGM systems do not monitor blood sugar but tissue glucose values. To measure blood sugar levels the sensor (sensing applicator) would need to be located in a blood vessel. The CGM system sensor is in fact located in subcutaneous fatty tissue, more exactly in the interstitium, and measures the glucose there. Studies have shown that in principle blood sugar and tissue glucose concur well. This only applies however as long as blood sugar levels are stable.

If blood sugar changes quickly i.e. rises or falls suddenly, then it takes a certain length of time for the tissue glucose level to adjust accordingly. This means that the values displayed are timedelayed. A CGM system therefore does not display in real time the current blood sugar value, rather a timedelayed glucose value as measured in the intestitial fluid. This has to be taken into account when interpreting the trend arrows in the CGM system which show which direction values will move in the next few minutes.

The value displayed in the CGM system is not a “realtime value” based on blood sugar. In particular, in phases of rapid blood sugar change, for example after a meal or during exercise, it “lags” behind the blood sugar value (“physiological time lag”). This time lag can be anywhere between five and 25 minutes.

No more measurements? People with diabetes value continuous measurement in terms of being able to monitor their metabolism round the clock and being able to make better decisions about therapy. Diabetics also hope in this way to avoid the “finger prick”. This is only sometimes the case. All CGM systems must be calibrated regularly in order to function correctly. Depending on the model, this means measuring sugar levels once to three times a day and feeding the CGM system with the ‘real’ value in order to obtain reliable data (for the trend arrows).

Patient Case Study

Review
Mr A., born 1951, farmer

Mr A. suffers from muscular dystrophy due to a chromosome defect. Two years before we met he had suffered, linked to his illness, an episode of transient vasculitis of the heart with pronounced posterior wall infarction associated with a viral infection.

His blood values did not recover after cortisone therapy and he continued to display pronounced leukopenia. His work meant he spent a lot of time outdoors in all weathers and as a result he remained very susceptible to infections and developed type 1 diabetes.

Therapy at the time with the following programs Treatment with the BICOM BICOM optima®:

  1. Basic therapy
  2. Eliminating program (based on testing) liver, kidney
  3. Strain, exposure to pathogens (viruses, fungi, bacteria) 978.1 and viruses 996.0 and clearing blockages 3017.0
  4. In the honeycomb (Channel 2): Quentakehl
  5. Oral: 4step therapy according to Dr Werthmann as maintenance dose
  6. Chip

Mr A., of solid North German stock and a farmer to boot, said at the time: “What must be must be and now all is well” meaning he felt well again and the objective and subjective evaluable data backed this up, and so we said goodbye.

I had not heard anything from him for a long time and I had another case in mind which I was intending to present to you as an example of Autoimmune Diabetes. Then Mr A. reappeared. His wife called and said “He’s not at all well!” Up to that point he had not been ill with any further infections.

On 14/11/2015 Mr A. had been admitted to hospital with severe hyperglycaemia and quantitative disturbances of consciousness. What had happened? His wife reported he had previously had an infection which just wouldn’t go away and when he had started to feel better then he became ill again one week later. Once again with flulike symptoms. Sometime later his diabetes became severely out of control. Ketoacidosis developed in the form of diabetic precoma and admission to hospital was necessary.

Sensor data (mg dl)-1

Sensor data (mg dl)-2

On 20/11/2015 after Mr A. had been discharged and the administration of antibiotics had finished (after five days), we produced the following dark field image:

Mr A. had been discharged

The following image was made at the , which took place weekly:

conclusion of therapy

Treatment

The treatments were tested out with respect to autoimmune diabetes. This was always preceded by testing of the underlying stress.

I have listed for you below the programs and the variations which I have used in this area:

1.Basic program
2.Programs after testing:
280.4 (alternatively 380.4) Influenza
281.4 Auto-regulation
301.8 Spleen/pancreas stress
450.0 Diabetes mellitus
996.0 (alternatively 978.1) Viral stress

3. The following low deep frequency programs after testing:
3117.0 Viral infection
3017.0 Clear blocks (tissue)
3036.0 Detoxification
3037.0 Inflammation
3109.0 Acidosis
3013.0 Stress from pathogens

4. Via the honeycomb:
Notakehl: bacterial stress
Grifola frondosa: viral stress
Pleo Pin (Pinikehl): Spleen/liver
regulation

The stresses which we discover from testing and then treat can appear in a changed form at a later time or recur. We can reduce these stresses using bioresonance and its testing options, plus the respective programs and the honeycomb.

I hope that with this example I have been able to show you how we can use new measuring techniques for assessment, patient history and subsequent treatment.

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