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Hpathy Ezine - November, 2006

The Monster With A Thousand Heads:

The Organon and Statistics

-- Remus Mihaila, MD

 

“It is easy to doubt matters which cannot be laid before our ocular vision, but in itself this doubt proves nothing at all, for according to the old rule of logic: negantis est probare”

from The Chronic Diseases ( I:79)

Based on the 6th edition of The Organon of the Medical Art and The Chronic Diseases Their Peculiar Nature and Their Homeopathic Cure 1, 2, two most important books written by the founder of Homeopathy Dr. Samuel Hahnemann, I have decided to further show the links between the superior philosophical concepts regarding disease and treatment in Homeopathy on one side, and their consequences for the future, and on the other side. I have also tried to show the usefulness, actually the necessity, of mathematics as a tool when applied correctly, in describing such concepts at the level of biological sciences, with its most common application - the bio statistics.3

The simple statistical model that I want to present here, through its incontestable recognized validity,3 has many usages and consequences, in particular on the correct understanding of the relation between health and disease, disease definition and levels, and the correct level where the treatment of chronic diseases in particular should be calibrated on objective facts, in accord with the original ideas that we can find in the founding homeopathic books.1, 2

To further illustrate the above ideas, I would first of all like to present the set of concepts as they are described by Dr. Samuel Hahnemann, that would lead to the idea of making such a model, in their original presentation as they are described in The Organon of the Medical Art the 6th Edition1 and in The Chronic Diseases Their Peculiar Nature and Their Homeopathic Cure.2

1.The Organon

Aphorism 103 – “ I had to investigate the chronic wasting sickness (namely and principally Psora) much more exactly than ever before. I had to do this because of the extent of the symptoms in these chronic diseases and also because one patient carries only a part of the symptoms in himself, while a second or third patient, etc suffers from some other befallments which likewise as it were, are only a part torn off from the totality of the symptoms that make up the entire extent of one and the same disease. Therefore, the complex of all the symptoms belonging to such a miasmtic wasting sickness (in particular psora) can only be ascertained from very many such individual chronic patients. Without such a complete overview and total image, the medicines that are homeopathically curative for the whole wasting sickness (namely the antipsorics) cannot be searched out. These medicines are at the same time, the true remedies for the individual patients that are suffering from these chronic maladies

2.      The Chronic Diseases

But usually, after repeated attempts to conquer the disease which appeared in a form always somewhat changed, residual complaints appeared which Homeopathic medicines hitherto proved, though not few, had to leave uneradicated, yea often undiminished”. (I:4)

“What was the reason of the thousands of unsuccessful endeavours to heal the other diseases of a chronic nature so that lasting health might result? Might this be caused, perhaps by the still too small number of Homeopathic remedial means that have so far been proved as to their pure action?, The followers of Homeopathy have hitherto thus consoled themselves; but this excuse, or so called consolation, never satisfied the founder of Homeopathy particularly because even the new additions of proved valuable medicines, increasing from year to year, have not advanced the healing of chronic (non venereal) diseases by a single step…” (I:4; emphasis added)

“…What is there to prevent this? The answer to this question which is so natural, inevitably led me to discover the nature of these chronic diseases…. The Giver of all good things permitted me within this space of time to gradually solve this sublime problem through unremitting thought, indefatigable inquiry, faithful observation and the most accurate experiments made for the welfare of Humanity”. (I:5)

“ These are the characteristic secondary symptoms of the long unacknowledged, thousand-headed monster, pregnant with disease, the Psora, the original miasmtic malady which now makes its manifest appearance”. (I:78; emphasis added)

And also below, one of the most peculiar and hidden paragraphs, in an explicative note: 

“To prove the psoric nature of these chronic diseases without acknowledged infection, we do not even need the fact that the anti psoric remedies prove effectual therein; this serves only like the proof to a correctly solved mathematical problem” (I:79; emphasis added).

I consider the above paragraphs of greatest relevance for my demonstration as they are at its base. They indicate a statistical model which I consider to be a necessary reality, starting right from the beginning, with my lectures on homeopathic texts and in particular on The Organon of the Medical Art.

Although I make below a presentation for the theoretical model and its collateral ideas, a few years ago I used the same principle which I describe today, and the results were surprising and a real proof for the validity of the model itself that anybody can try any time. At that time, using the results only for justifying economical needs, I did not know that a wonderful science has already founded a whole system on such observations, and that this validates its usefulness and truth.

Samuel Hahnemann observed from clinical experience that in chronic diseases, although he and those that followed the homeopathic principles correctly, have applied the treatment as indicated by these principles in counting the totality of the individual signs and symptoms, there were patients with relapses and for them the disease did not stop in its progress.1,2

Through careful observation, he could see at some point the cause of these failures was the impossibility of treating some patients with chronic diseases. These belong to a disease that is at another logical level than the combination of individual signs and symptoms, and is invisible to the eye in its totality. It is a collective statistical disease that makes the remedy almost impossible to find if we start at the individual level.

I will show below that the collective statistical disease does exist indeed.

Samuel Hahnemann made the connection with the ways of transmission and origins of such disease, and he showed the links of the statistical disease with certain origins and ways of transmission, in particular parasites and micro organisms. He also discovered there is not only one such collective disease. During his life, he proved three of them which have origins in infectious diseases. He called them Miasm and they were Psora, Syphilis, and Sycosis; of which Psora is the oldest and the most widespread amongst the patients with chronic diseases. To avoid their transmission, the treatment of the miasms must always be homeopathic from the start, from the moment of infection to avoid the contamination of the new subject with the disease, and to further avoid the spread of such a disease in ways that may not necessarily be via infection.

Based on the above, I would like to show that in fact miasms are statistical diseases in the common sense.

Following Samuel Hahnemann, through the work of other homeopaths, other major miasms have been discovered and connected with their ways of transmission

However, there is another homeopathic principle which states that for homeopathy it is not necessarily important which types of stressors are involved in the development of a disease. We may never have complete access to the full possible variations in the type of stressors or their strength. Combined with a logically possible internal susceptibility, and based on the above as a principle of incontestable validity, I have started in the search of mathematical functions that would best describe such an idea.

Searching for possible models, I have first realized that Homeopathy does not use any quantitative concepts in the description of the disease parameter. It operates with perceptible signs and symptoms which statistically speaking are qualitative variables, and not quantitative or numeric variables.

Inside the science of statistics, I have found a few mathematical functions or tests belonging to inductive statistics, which are used in data correlation, and when applied these will show if there is a mathematical correlation between variables. Amongst them, there is a specific statistical function, the Chi square test that can in particular be used to show and certify such correlations between variables.

This is exactly our case and I believe is a clarifying answer.

As we want to find valid correlations between signs and symptoms, as qualitative variables, and Chi square is more permeable to errors in introducing these variables, it is without doubts that this function is suitable for our purpose.3

At the same time, being permeable to certain errors in introducing the qualitative data to be processed, Chi square is also indicated by the fact that it would be impossible to accept that any symptom which at any point in time is similar at the conceptual level to the same symptom in another patient, can at the same time be fully similar to the same symptom in another patient in reality, in its objective expression.

For that reason, as we are starting from homeopathic principles which indicate such a study, we need to further expand the study with the aid of and inside homeopathy. It is a necessity that in performing the study, the best description of qualitative data (symptoms and signs) will find their expression in the homeopathic Materia Medica, as the place we can find maximum degrees of expressing the perceptible signs and symptoms we see in patients with chronic diseases suitable for our study.

The Chi square function

The Chi square test is a statistical function that shows if 2 qualitative variables are independent in a random population and it has a wide range of applications in research within biological sciences.3

It can only test if the two variables are independent without indicating, which is smaller of greater. It does not express quantitative differences between variables, it just express if the variables are independent or correlated.

The first step in applying the chi square test is to establish the correct hypothesis. The null hypothesis is indicating that the two variables are not correlated and they are independent.

There are many tutorials on the web for the Chi square function and its applications and is not the purpose of this communication to be a Chi square tutorial which is a clear mathematical function with well defined characteristics and very simple to use and calculate.

Our hypothesis is that in a 2x2 table, in the 2 rows present or not present are variables indicating the patients that have a specific symptom and the patients that do not have it. In the columns are the symptoms to be checked for the null hypothesis (for independence). Symptom 1 is tested against all other symptoms until we finish the testing of it with the symptom 1 with all the others we have found in the randomly chosen patients.

The Chi square shortcut function for 2x2 tables is:

       
 

A

B

A + B

 

C

D

C + D

 

A + C

B + D

A + B + C + D = N

X2 =                 N (AD – BC)2        

           __________________________     

           (A + C) (B + D) (A + B) (C + D)

Theoretical examples:

 

Present

Not present

Total

Symptom 1

67

34

101

Symptom 2

36

15

51

Total

103

49

152

Chi Square 0.2804

For significance at .05 level Chi Square should be >/= 3.84 which is the minimum level where we can accept or reject the null hypothesis using the Chi square function.

The distribution is not significant

 

Present

Not present

Total

Symptom 1

23

55

78

Symptom 3

36

22

58

Total

59

77

136

Chi Square 14.377

P </= 0.01

The distribution is significant

The degrees of freedom for the 2x2 table are 1.

If we would have for example 30 symptoms as a total after introducing random data from individual patients, S1 to S30, then, as shown before we will test S1 with all the other 29 independent symptoms in 2x2 tables, and for example we find that S1 has a statistical correlation with S5, S6, S9, and S22; then if from the practical result we cannot reject the null hypothesis for S1 being associated with the variables mentioned, then we cannot reject that they are all associated with each other as well.

We do the same with each one of the symptoms until we have tested them all against possible correlations and we have finished all the possible combinations, and then we connect the correlative chains together. As they all are independent, they will join in an imaginary root at the source that has produced the qualitative variables.

In such a way we have built a three-dimensional inductive statistical disease, impossible to see in any of the individuals who belong to it. It is a reality that cannot be seen but it is as real as anything we can see with the open eyes.

Conditions in using Chi square function:

  1. The sample must be randomly drawn from the population.
  1. Data must be reported in raw frequencies (not percentages);
  1. Measured variables must be independent;
  1. Values/categories on independent and dependent variables must be mutually exclusive and exhaustive;
  1. Observed frequencies cannot be too small.


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