Phytotherapy of cardiovascular diseases
INFORMATION ASPECT
Goroshetchenko A.V.1, Treskunov K.A.1, Martirosyan D.M.!
hospital of the Scientific Center at the Russian Academy of Sciences, Chernogolovka, Russia functional Foods Center at D&A Inc., Richardson, Texas, USA
RESUME
The future development of phytotherapy in the world medicine requires a new level of investigations aimed at the treatment of malignant formation, AIDS and cardiovascular diseases. With a view to including phytotherapy in the international system of public health, it is very significant to solve the problems regarding a creation of a unified standard for the application of plant-derived resources and methods of definition of their efficiency for the treatment of various diseases. The goal of this present work is to create a single automatized approach towards the treatment by means of herbs, specifically for the treatment of cardiovascular diseases.
Since 1972 up to present a group of researchers headed by an academician Treskunov, has succeeded in establishing and collecting a huge computer database with respect to the treatment of subjects by means of phytotherapy. Databases and a special software complex for a therapeutist were created. This allowed not only to conduct static and kinetic researches of a medical process but also to use the given researches in practice.
The data of phytotherapy efficiency of cardiovascular diseases were taken into account. It was proved that they average 70% for a static efficiency and 31 % for a kinetic efficiency. The investigations of temporal characteristics enabled us to speak about the speed of phytotherapy when treating cardiovascular diseases.
A typical symptomatology of every cardiovascular disease was defined based on the complete processing of the entire database. An efficiency of the action of a particular herb upon the particular parameter was defined by means of the kinetic efficiency for every symptom, syndrome and disease in the computer cartography. The theoretical researches conducted by us allowed us to increase the efficiency of phytotherapy of particular patients. A set of herbs for the given particular patients and their concentration in the collection were formulated by us based on the results of the array processing of the efficiency of all the sets of parameters.
INTRODUCTION
Botanical medicine, or phytotherapy, is the most widespread foim of medical treatment in the world (1). Estimated sales of herbal medicine in the U.S. reached $1.2 billion in 1996 (2). Treatment by phytotherapy is less costly as opposed to conventional medicine. Costeffectiveness studies are rare even in East Asia where the economic impact of herbs in the medical marketplace is greatest. Herbal medications are potentially effective for withdrawing patients from benzodiazepine drugs, at a significant savings in cost as well as in quality of life (3) Medical plants have also been tested for a variety of other complaints including nausea (4) hyperglycemia (5) circulation problems (6) hypercholesterolemia (7) and hormone regulation for disorders of climacteric (8). Thus there is tremendous potential to reduce health care costs by using herbal extracts and herbs. But there is a need for methods of testing appropriate to botanical medication. Ignoring the details of personal history and physical examination will neither validate the traditional uses of herbs nor develop their therapeutic potential. Regulating agencies in USA, Germany, France, the United Kingdom, Canada, and Japan enforce standards of herbal product quality and safety assessment of herbal product manufacturers (9, 10) There remain several uncertainties with regard to standards. Potency of substances is also affected by growing conditions, storage, handling, as well as subsequent methods of preparation. The complex properties of herbs must be studied and applied within the context of more complex "functional" whole-system models of physiology. As in French phytotherapy of the terrain, Ayurvedic and Chinese medical systems have long traditions of diagnosis that adjust treatment according to a complex interpretation of symptoms and signs. The goal of whole-system treatment is to seek the correct combination of herbs to balance out unwanted effects or onesided effects from individual herbs.
Since 1972, we have collected the phytotherapy database (11,12,13,14,15,16) of about 3000 patients. For each patient without selection, a Computer Card was set up. It includes all the necessary data about a patient and his/her treatment.
As a result, databases and a phytotherapeutist program complex were created. For the first time, it gave us an opportunity to perform not only the static and kinetic investigations of the treatment process, but also to use the investigation data in the practical treatment procedure.
The aim of this article is to show the potentials of the phytotherapy computer base when treating cardiovascular diseases.
PROBLEM DEFINITION
This scientific work consisted of six tasks.
First, we would like to define the phytotherapy effectiveness of main cardiovascular diseases (CVD) in view of their static and kinetic variants.
Second, the analysis of the temporary indices enables to compare various cases on how fast a patient recovers due to the phytotherapy treatment in various cardiovascular diseases.
Third, the full processing of the whole data basis allows us to define the typical symptoms of each CVD up to the average characteristics of each symptom. As a result, we can estimate the kinetic characteristics of a disease, which depend not only on the quantity and quality of parameter (symptom, syndrome and disease), but on the time of their development (kinetics). Only computers can perform it. Hereafter, the word "parameter" will mean the symptom, syndrome, and diseases as the investigation objects.
Fourth, when using the kinetic efficiency for each particular parameter in a Computer Card (CC) and knowing the concentration of herbs in species, one can estimate the action of the efficiency in each herb for the given parameter.
Fifth, the theoretical investigations performed by our group, allows us to use them in practice, mainly to increase phytotherapy efficiency in particular patients. We made a recipe taking into account that the species are made from herbs, which are most effective for the whole parameter complex relating to the particular patient. Based on the results of the matrix efficiency for all groups of parameters, we received not only the herb species for a particular patient, but also their concentration of herbs in the species.
Sixth, we would like to show how great the potentials of our "Phytotherapy Computer Basis" are. We performed an exotic investigation. We defined the presence of the predisposition to the CVD depending on the date of birth and sign of Zodiac. This is known as the "Astrology prognosis".
ESTIMATION OF THE PHYTOTHERAPY EFFICIENCY IN CARDIOVASCULAR DISEASES
When registering a patient, the following factors are included: gender, age (date of birth), weight, height, blood type and rhesus factor, allergy presence etc.
When making basic calculations the following factors are taken into account:
-
1. The disease symptom, syndrome, as they were manifested prior to the treatment according to the 1-3 Ws scale;
-
2. The disease symptom, syndrome, as they were manifested upon the completion of the treatment according to the 0-3 Wp scale;
-
3. The time interval within which the disease symptom, syndrome, are present according to the 1-3 Ts scale;
-
4. The treatment time interval according to the 1 -3 T1 scale.
The efficiency of the calculation is performed based on two algorithms: statistical and kinetic.
The statistical variant assumes the summary accounting of all CC in which the given disease is present and the summation of all the indices:
The kinetic variant assumed the time interval accounting. The phytotherapy efficiency of the symptom, syndrome, is calculated based on the formula below:
We must first receive the data, which should be subject to reliability qualification. We then use the mathematical, statistical, methods (15). The phytotherapy efficiency of the CVD is a series of values that can coincide (in this case, we state with confidence about the efficiency of the phytotherapy on the whole) or not coincide (in this case, the part of diseases, symptoms, syndromes) will deviate from the average values.
To check the coincidence hypotheses we use the following formulas:
- 1. The efficiency average index
-
2. Standard efficiency deviation
Commonly, the condition character variation is considered as the average if the quantity of the variation coefficient is between the limits 10 % to 25 %.
Finally, it is essential to determine the "doubtful" data, i.e. the data that goes beyond the data reliability.
4. According to the formula, the limits within which the reliable results lie
In the formula, ta is a Student's coefficient for the confidence interval 95 % obtained according to Table 1 (Formula 6).
Since the article covers a detailed description of the researches in comparison with the phytotherapy of various classes of disease, it should be pointed out that phytotherapy of respiratory apparatus diseases, gastrointestinal tract is the most effective one. The diseases are traditional for our civilization and their phytotherapy is developed and successfully applied long before the emergence of pharmaceutical medicine. Pharmaceutical medicine can concede the treatment of the above diseases to phytotherapy. Autoimmune and oncological diseases are hardly treated through phytotherapy. However, pharmaceutical medicine failed to achieve considerable success in this field. Nevertheless, as a result of long and persistent treatment, positive results can be evident when conducting a joint treatment with pharmaceutical medicine based on the developed methods.
Below are the diseases which pertain to the class of the disease of "group risk" when a lot depends not only on the knowledge and methods, but also their experience, skill, and intuition of a phytotherapeutist: cardiovascular diseases, skin diseases and the diseases of the nervous system. The main reasons of the above diseases are not the cause of the nature but the changes of the natural factors of the environment. The immune system is by no means in condition to find an adequate response to the new challenge. Therefore, it is unable to wipe out and change the reasons of disease, since phytotherapy can only eliminate their consequences.
To perform the detailed investigation of the CVD phytotherapy potentials, 15 diseases presented in the CVD Table 1 were selected. We determine the student's coefficient for the coefficient interval of 95 % according to Table 1 (Formula 6). It is equal to ta=2.14. Consequently, the mathematically reliable values of efficiency are between the limits (see Formula 6)
According to Table 1, the uncertain (going beyond the reliability limits) are the efficiency indices "Myocardosis" Ef = 82 % (over the upper permissible limit by 3, 2%) and "Myocardium infarct" Ef = 53 % (less than the low permissible limit by 8 %).
Table 1. Statistical CVD Phytotherapy Efficiency
| Disease | In total | PR | PI | IM | NC | i | W | Ef | ||||
| I | % | I | % | I | % | I | % | I | % | % | ||
| Hypertension | 486 | 189 | 39 | 20 4 |
42 | 32 | 7 | 55 | 11 | 6 | 1 | 70 |
| Hypotonia | 336 | 176 | 52 | 10 2 |
30 | 7 | 2 | 50 | 15 | 1 | 0 | 74 |
| Cardiac Insufficiency | 188 | 90 | 48 | 66 | 35 | 4 | 2 | 26 | 14 | 2 | 1 | 72 |
| Stenocardia Tension | 143 | 53 | 37 | 73 | 51 | 13 | 9 | 4 | 3 | 0 | 0 | 77 |
| Obesity | 66 | 12 | 18 | 21 | 32 | 26 | 39 | 6 | 9 | 1 | 2 | 59 |
| Myocardosis | 44 | 20 | 45 | 22 | 50 | 1 | 2 | 1 | 2 | 0 | 0 | 82 |
| Myocardium Infarct | 15 | 2 | 13 | 7 | 47 | 4 | 27 | 1 | 7 | 1 | 7 | 53 |
| Encephalopathy | 63 | 19 | 30 | 41 | 65 | 1 | 2 | 2 | 3 | 0 | 0 | 77 |
| Heart Disease | 23 | 4 | 17 | 15 | 65 | 0 | 0 | 4 | 17 | 0 | 0 | 63 |
| WD by Hypertension Type | 19 | 7 | 37 | 8 | 42 | 1 | 5 | 3 | 16 | 0 | 0 | 69 |
| WD by Hypotonia Type | 147 | 77 | 52 | 56 | 38 | 3 | 2 | 9 | 6 | 2 | 1 | 79 |
| Streptococcal Infection | 21 | 16 | 76 | 1 | 5 | 0 | 0 | 4 | 19 | 0 | 0 | 80 |
| Discirculatory Encephalopathy |
206 | 34 | 17 | 12 8 |
62 | 23 | 11 | 19 | 9 | 2 | 1 | 65 |
| Cardiosclerosis | 67 | 9 | 13 | 40 | 60 | 7 | 10 | 11 | 16 | 0 | 0 | 60 |
| Ciliary Arrhythmia | 59 | 20 | 34 | 25 | 42 | 7 | 12 | 6 | 10 | 1 | 2 | 68 |
Where PR - practically recovered, PI - significant improvement, IM - improvement, NCh - no changes, W - worsening
RATE ESTIMATION OF PHYTOTHERAPY IN CARDIOVASCULAR DISEASES
When using the CVD phytotherapy, it is of great interest to observe the process of the recovery rate in view of kinetics. Similar investigations were carried out and the data of the results are presented in Table 2.
To simplify the processing, it is essential to unite the "PR" (Practically Recovered) data and the "SI" (Significant Improvement) and calculate the phytotherapy rate for the case PR + PI. The obtained data is presented in Table 3.
For all this, the error of the variation coefficient is estimated according to the following formula:
In accordance with Table 3, the average value of the phytotherapy CVD rate is a part of the confidence interval (Cv ranges from 10% to 25 %) only for the third case. For the first case, it is a part of the confidence interval but relatively (in view of error Cv).
Table 2. Cardiovascular Phytotherapy Rate
| Disease | PR - TI (month) | PI - TI (month) | ||||||||||
| 1(<1 | 1 | 2(1-3) | 3(>3) | 1(<1) | 2(1-3) | 3(>3) | ||||||
| J | % | J | % | JL | % | I | % | I | % | J | % | |
| Hypertention | 66 | 14 | 42 | 9 | 81 | 17 | 65 | 13 | 38 | 8 | 10.1 | 21 |
| Hypotonia | 57 | 15 | 54 | 16 | 65 | 19 | 31 | 9 | 20 | 6 | 51 | 15 |
| Failing Heart | 30 | 16 | 24 | 13 | 36 | 19 | 15 | 8 | 21 | 11 | 30 | 16 |
| Stenocardia Tension | 23 | 16 | 6 | 4 | 24 | 17 | 22 | 15 | 20 | 14 | 31 | 22 |
| Obesity | 8 | 12 | 1 | 2 | 3 | 5 | 8 | 12 | 0 | 0 | 13 | 20 |
| Myocardosis | 7 | 16 | 5 | 11 | 8 | 18 | 7 | 16 | 5 | 11 | 10 | 23 |
| Myocardium Infarct | 1 | 7 | 0 | 0 | 1 | 7 | 4 | 27 | 0 | 0 | 3 | 20 |
| Encephalopathy | 11 | 17 | 5 | 8 | 3 | 5 | 21 | 33 | 4 | 6 | 16 | 25 |
| Heart Disease | 3 | 13 | 0 | 0 | 1 | 7 | 4 | 27 | 0 | 0 | 3 | 10 |
| VVD by Hypertension Type | 2 | 11 | 2 | 11 | 3 | 16 | 5 | 26 | 2 | 11 | 1 | 5 |
| VVD by Hypotonia Type | 21 | 14 | 30 | 20 | 26 | 18 | 26 | 18 | 8 | 5 | 22 | 15 |
| Cardiosclerosis | 3 | 4 | 3 | 4 | 3 | 4 | 9 | 13 | 13 | 19 | 18 | 27 |
| Ciliary Arrhythmia | 7 | 12 | 3 | 5 | 10 | 17 | 8 | 14 | 4 | 7 | 13 | 22 |
This is accounted for by the fact that the state estimate in the course of the treatment lasting from one to three months has an intermediate nature. Table 3 also indicates that the recovery process after receiving phytotherapy is protracted. At least one third of patients are treated for over three months.
Table 3. Statistical Estimation of the Cardiovascular Phytotherapy Rate
| Rate Indices | Practically Recovered + Significant Improvement | ||
| Upto 1 month rn=i) | From 1 to 3 months (TI = 2) | Over 3 months (Tl=3) | |
| Average Value Xav. | 30.7 | 16.5 | 33.3 |
| Standard Deviation Sx | 8.32 | 7.95 | 6.78 |
| Standard Error Ox | 2.31 | 2.21 | 1.88 |
| Variation Coefficient Cv | 27 | 48.2 | 20.4 |
| Error Cv | 5.67 | 11.4 | 4.16 |
ESTIMATION OF TYPICAL SYMPTOMATOLOGY OF CARDIOVASCULAR DISEASES
The available statistics enables us to merely evaluate the "Typical computer medical history". Based on the statistics, all symptoms, syndromes and diseases relating to the investigated disease are remembered. If they occur more than 30% of the time, they are considered related to the particular disease. All their characteristics (pronounced nature before and after phytotherapy - Ws, Wp, existence time and treatment - Ts, Tl) are remembered and summed up. In accordance with the results, Formula 1 - Ek, calculates the efficiency of the symptom, syndrome, and treatment. The given value, unlike the values presented in Table 1, has a dynamic character, since not only the final result but also all the treatment parameters are taken into account. The utmost possible value of efficiency (see Formula 1) is equal:
Therefore, one can estimate the kinetic efficiency not only based on absolute values but also on percentage and compare it with the value of static efficiency.
According to Table 1, the largest statistics are collected for five types of cardiovascular diseases:
-
1. Hypertension - 486
-
2. Hypotonia - 336
-
3. Cardiac Insufficiency -188
-
4. Exertional Angina (pectoris) - 143
-
5. Discirculatory Encephalopathy - 206
Based on these diseases, we will carry out further investigations.
Below are the results of the computer processing obtained in accordance with the program "Standard Medical history - HYPERTENSION."
Table 4. Standard Medical History - HYPERTENTION
| Name | In Total (486) | Ts | Ws | W1 | Tl | Ed | Ek% | R | |
| 1 | Giddiness | 204 | 2.90 | 2.25 | 0.68 | 2.15 | 0.94 | 31 | 4 |
| 2 | Depression | 197 | 2.80 | 2.23 | 0.73 | 2.05 | 0.73 | 24 | 6 |
| 3 | Aches | 198 | 2.85 | 2.14 | 0.65 | 1.98 | 1.00 | 33 | 1 |
| 4 | Headache | 238 | 2.87 | 2.24 | 0.74 | 2.02 | 0.95 | 32 | 3 |
| 5 | Insomnia | 169 | 2.90 | 2.14 | 0.66 | 2.02 | 0.99 | 33 | 2 |
| 6 | Life quality | 164 | 2.64 | 2.65 | 0.96 | 2.21 | 0.85 | 28 | 5 |
Notes:
-
1. For Ts, Tl, Ws and W1 their average values are taken.
-
2. R is a symptom (syndrome) range. The higher the efficiency is, the higher the range.
It is interesting to compare the values of the static and kinetic efficiency of phytotherapy symptom, syndrome of the diseases presented above. The list of symptoms, syndromes and also the efficiency compression are presented in Table 5.
At the bottom of the table the data of static processing of its columns are shown. Practically the coefficient of variation Cv is less than 25% for all the data. So the variation of the result is within the permissible limits. On making calculation for the permissible interval by formula 6 for each column at the confidence probability equal to 95%, we obtain the limits within which our data is included. The data being beyond the given limits (at least slightly) are displayed in bold print.
As shown in the table, the static efficiency values exceed the kinetic efficiency values by two or more times. It is explains that the efficiency is calculated without using the data concerning the severity of the initial and final symptoms, the correlation between the existence time and the treatment time. When calculating the phytotherapy efficiency as a dynamic process, the more precise but lower values are obtained.
However, according to the official medical statistics, the efficiency is determined by the static technique.
The official medical statistics determines the efficiency value based on the statistic technique. We can sort out the values of statistical and kinesthetic efficiency from large to small, and see that the class of each parameter in the disease doesn't always coincide. This shows that the researches of kinesthetic efficiency in "Standard Medical history" will allow us to disclose the dynamics of phytotherapy of a disease. Our article does not cover the comprehensive research in this field.
Table 5. Standard Medical Histories and the Efficiency of Treatment by Means of Phytotherapy (%)
| Symptom | Hypotonia | Hypertension | Lardiac Insntliciency | Stenocardia | Encephalopathy | ||||||
| Es | Ek | Es | Ek | Es | Ek | Es | Ek | Es | Ek | ||
| 1 | Headache | 72 | 32 | 70 | 31 | 58 | 26 | - | - | 74 | 34 |
| 2 | Giddiness | 76 | 31 | 76 | 32 | 71 | 28 | - | - | 77 | 37 |
| 3 | Depression | 74 | 24 | 68 | 27 | 69 | 26 | - | - | - | - |
| 4 | Insomnia | 74 | 33 | - | - | 79 | 30 | - | - | - | - |
| 5 | Aches | 76 | 33 | 76 | 32 | 76 | 30 | - | - | - | - |
| 6 | Life quality | 68 | 28 | 72 | 31 | - | - | 67 | 27 | 64 | 26 |
| 7 | Diastolic pressure | - | - | - | - | 79 | 28 | 73 | 30 | 71 | 30 |
| 8 | Stomachaches | - | - | 79 | 36 | 80 | 36 | - | - | - | - |
| 9 | Constipation | - | - | 74 | 33 | 76 | 32 | - | - | - | - |
| 10 | Infiltration | - | - | - | - | 77 | 28 | - | - | - | - |
| 11 | Cholecystitis | - | - | - | - | 71 | 26 | - | - | - | - |
| 12 | Gastroduodenum | - | - | - | - | 79 | 27 | - | - | - | - |
| 13 | Oedemata | - | - | - | 79 | 31 | - | - | - | - | |
| 14 | Tachycardia | - | - | - | - | 69 | 30 | - | - | - | - |
| 15 | Ischemia | - | - | - | - | - | - | 58 | 29 | - | - |
| 16 | Short breath | - | - | - | - | - | - | 71 | 35 | - | - |
| 17 | Atherosclerosis | - | 30 | 74 | 32 " | 74 | 29 | 68 | 27 | - | - |
| Xav. | 73 | 70 | 30 | 72 | 32 | ||||||
| Sx | 3.03 | 3.55 | 4.34 | 2.71 | 8.15 | 2.87 | 2.18 | 3.31 | 5.60 | 4.80 | |
| Cv | 4.16 | 1.18 | 6.03 | 8.75 | 11.0 | 9.90 | 3.14 | 11.1 | 7.80 | 15.0 | |
| Ox | 1.23 | 1.45 | 1.63 | 1.02 | 2.27 | 0.80 | 0.97 | 1.48 | 2.80 | 2.40 |
ESTIMATION OF ACTION EFFICIENCY IN THE HERBS EFFECTING THE SYMPTOMS, SYNDROMES AND DISEASES
We used Formula 1 to calculate the action efficiency of herbs effecting the symptoms, syndromes, and diseases. To perform it, we added the logarithm with a base 10 of the reverse herb concentration in species into the formula. The logarithm is taken to coordinate the dimensional representation of values, because the concentration, as a rule, is from a tenth to thousandth proportion out of the full compound. Therefore, the influence coefficient of herbs (its concentration) upon the efficiency of phytotherapy can be presented as follows:
The exceptions are the symptoms, syndromes, and diseases of adaptation decreasing (disadaptation), because of the herb - adaptogenes in the minimum amounts act as catalyst which are not included in the chemical reactions of the Krebs system - ATF synthesis and resynthesis. In these cases, use:
Taking Formula 1 into account, the action efficiency of herbs influencing the given symptom, syndrome, and the disease in i - medical history, can be estimated as follows: (Wsi-Wpi) Tsi
We defined the general action efficiency of the given herb influencing the given symptom, syndrome, of the disease as the arithmetic average throughout the base of all the medical histories.
Where S is a number of medical histories, where the combination of the given herb and the given disease are met (from 1 to N).
The acquired data is normalized on the 1-10 scale. Therefore, the tables in the action efficiency of the herbs upon the symptoms, syndromes, and diseases are derived. We use them in further practical and scientific work. Below are the tables of efficiency, which are obtained for five main diseases covered in the present article. As a rule, the first five herbs are taken at the beginning of the table and (if there is a negative effect) then the last five herbs are taken.
It is essential to sum up the herbs presented in the table. The herb which is in the first place acquires a class equal to 5, the one that is in the second place acquires a class equal to 4 and so on. Having summed up all the herbs above, we draw another table of herbs, which are considered to be more effective during cardiovascular diseases. There is a problem concerning the forming of the effective medicine species to treat the particular patient. The intuition of a doctor who treats the patient is a main factor. The available medicinal species don't take into account the individual symptoms of a patient and intended for an average statistical patient.
Table 6. Action Efficiency of Herbs upon Cardiovascular Diseases
| Hypertension | Hypotonia | Cardiac Insufficiency | Stenocardia Tension | Discirculatory Enccephalop. | |||||
| Herb | E | Herb | E | Herb | E | Herb | E | Herb | E |
| Hypericum perforatum | 8.1 | Matricaria chamomilla | 8.1 | Hypericum perforatum | 5.1 | Hypericum perforatum | 2.4 | Plantago | 2.3 |
| Matricaria chamomilla | 7.5 | Plantago | 4.5 | Taraxacum officinale wigg | 3.9 | Poligonum aviculare | 1.5 | Poligonum aviculare | 2.0 |
| Betula alba | 4.6 | Hypericum perforatum | 3.4 | Matricaria chamomilla | 3.7 | Plantago | 1.4 | Hypericum perforatum | 1.9 |
| Vaccinium vitis - idaea | 4.1 | Tussilado farfara | 3.0 | Achillea milleforum | 3.7 | Melilotus | 1.1 | Melilotus | 15 |
| PMentha piperita | 4.0 | Achillea milleforum | 3.0 | Melilotus | 2.6 | Mentha piperita | 0.8 | Mentha piperita | 1.1 |
| Agrimonia Eupatoria | -1 | Melilotus* | -1 | Urtica mens | -2 | ||||
| Tryfolium pratense | -1 | Origanum vulgare | -1 | Alchimilla vulgaris | -2 | ||||
| Glechoma hederacea | -1 | Crataecus | -1 | Sanguisorba officinalis | -2 | ||||
| Hypericum perforatum | -2 | Leonurus Cichorium intybus | -2 |
* Not all herbs having a negative action on hypotonia are presented due to the lack of space
Table 7. Herbs More Effective During Cardiovascular Diseases
| Herb | Class | Herb | Class |
| Taraxacum | 17 | Millefolium | 3 |
| Matricaria | 12 | Betula pendula | 3 |
| Plantago | 12 | Mentha piperita | 3 |
| Hypericum | 8 | Vaccinium vitis-idaea L. | 2 |
| Polygonum aequale Lindm. | 8 | Farfara | 2 |
| Melilotus | 5 |
ESTIMATION OF THE SPECIES COMPOUND IN VIEW OF HERB EFFICIENCY
As a result, the action efficiency is often rather lower than expected. Since 1990, the authors have carried out the tedious work regarding the computer accounting and statistical processing of the medical histories of patients. As a result, two tables of herb action efficiency upon the symptoms, syndromes, and disease of a patient (hereinafter referred to as "symptoms") have been obtained.
Having solved this problem, we could precede to a new stage of joint work, namely, to develop the calculation of algorithm for the computer species - ARKOS.
-
1. The initial data for calculation
-
B. Tables of efficiency that include the symptom number, herb number and action efficiency (from - 1 0 up to +10) arranged in descending order, according to the action efficiency.
-
C. Numbers and names of herbs
-
D. Numbers and names of symptoms
The initial information for the preparation of the species include:
-
a) Address information of a patient
-
b) Symptoms list
The symptoms that a patient has are marked in the list. As a result, the initial table of a patient's symptomatology is obtained. It is put into the computer. After a doctor questions a patient, the doctor enters the following additional information referring to each symptom into the acquired table.
| Patient m | Symptom, syndrome, diseases 1-700 | Existence time Ts 1 - 3 | Pronounced WR 1-3 | Influence on general state WL 1 - 100 | Complex index Kp |
| i | 2 | 3 | 4 | 5 | 6 |
-
2. Information processing and making up the species for treatment.
-
A. According to the efficiency obtained on the basis of symptoms, the medicinal herbs are selected to treat the patient. The principal Symptom —> the most effective medicinal herb is used to treat the patient. The complex index of significance is assigned to each symptom (and to the medicinal herb which corresponds to it). It,is calculated by the following formula:
- I.e. we acquire 3 indices S-symptom, Nt - herb number, Kp - complex index of further processing for each symptom.
In fact, not a single herb from the efficiency table corresponds to the symptom but several depend on the index Kpsi. However, to simplify the statement, it is advisable to use one herb for each symptom. The further calculations would be elementary if the plant producing maximal effect upon one of the symptom did not have a positive (or negative) effect upon other symptoms, including the ones, which have been selected. This is the reason why in the calculations, the indices of the total effect of the given plant based on all the symptoms of the species Eti and the total effect of the plants based on the given symptom Eti are taken into account. During the calculations the indices in the given symptom having a relation of complex index in the given symptom towards the minimal complex index of the significance within the symptom.
It is assumed that in low herb quantities, the action efficiency influencing the symptom increase is directly proportional to the herb quantity.
Figure 1. Relation of the Herb Action Efficiency to its Concentration in the Species
Efficiency
- B. Calculation performed in accordance with the total herb effect based on the given Esi symptom.
Step 1. All indices referring to the herb efficiency based on the given Esi symptom are summed up.
Step 2. The highest is chosen and is taken as a normative part in the species.
Step 3. The normative amount of each herb species in a symptom is in reference to the chosen amount of herb species, which are calculated as a normalized herb species unit. The compound obtained in such a way that the action efficiency influencing each symptom would be similar.
Step 4. The normative amount of herbs in species for each symptom is calculated. The presented importance of the symptom:
-
3. The example of the species composition calculation.
Below is the example of the species composition calculation for the patients suffering from cardiovascular diseases (five principal symptoms were taken for the sake of the simplicity of the example). As a result, the following data was obtained.
A. Initial data:
An expert doctor filled out the data presented in columns 1-5. The data presented in columns 6 and 7 were calculated based on Formulas 1 and 2 in reference to the symptoms having the lowest complex index Kp (0078).
-
C. Intermediate calculation data:
As a result, the following table of the total influence in the herbs upon the mentioned symptoms (conformity of the herb numbers with their names) was obtained. The presented table indicates that the herb 002 Matricaria chamomilla and 024 Hypericum perforatum are the most active and effective on all the symptoms mentioned in Table 8 (Oil hypertension and 066 arteriosclerosis). Therefore, the subsequent calculation for the herbs 002 and 024 is performed by all the symptoms.
Table 8. Species Composition Calculations for Cardiovascular Patients
| Symptom JNs |
Symptom, syndrome, and disease S 1-700 |
Existence time Ts 1 - 3 | Intensity WR 1-3 |
Influence on the general state WL 1 -100 | Complex Index Kp | Presented Complex Index Kp,pr |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| 002 | Giddiness | 3 | 3 | 030 | 49 | 2.7 |
| Oil | Hypertension | 3 | 2 | 030 | 33 | 1.8 |
| 042 | Tachycardia | 3 | 3 | 050 | 64 | 3.6 |
| 060 | Arteriosclerosis | 3 | 2 | 070 | 50 | 2.8 |
| 078 | Cardiac insufficiency | 1 | 2 | 080 | 18 | 1.0 |
Table 9. Calculations for Herbs 002 and 024
| SYMPTOMS | Et | Nkr | ||||||
| 002 | Oil | 042 | 060 | 078 | ||||
| H | 002 | 8 | 7 | -2 | 2 | 4 | 19 | 1.00 |
| E | 024 | 6 | -2 | 5 | 1 | 5 | 15 | 1.27 |
| R | 029 | 7 | 4 | 2 | 2 | 15 | 2.27 | |
| В | 047 | 1 | 8 | 2 | 4 | 15 | 1.27 | |
| S | Es | 22 | 13 | 7 | 7 | 15 | ||
| Nk | 1.0 | 1.69 | 3.14 | 3.14 | 1.47 |
The normative coefficient Nkr is calculated with respect to the herb 002 having the highest efficiency, and the normative coefficient Nks is calculated with respect to the symptom, the action efficiency of the herb upon which is the largest (002 - Giddiness). The calculations in view of the symptom importance (Formula 13) are shown below.
Table 10. Step 1
| SYMPTOMS | Sdt | Nkr | ||||||
| 002 | Oil | 042 | 060 | 078 | ||||
| H | 002 | 8 | 11.8 | -6.3 | 6.3 | 5.9 | 25.7 | 1.12 |
| E | 024 | 6 | -3.4 | 15.7 | 3.1 | 7.3 | 28.7 | 1.00 |
| R | 029 | 7 | * | 12.6 | 6.3 | 2.9 | 28.8 | 1.00 |
| В | 047 | 1 | 13.6 | - | 6.3 | 5.9 | 26.8 | 1.07 |
| S | Sds | 22 | 22 | 22 | 22 | 22 | ||
| Nk | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Le. the normative coefficient Nks corresponds completely to Kp np. (Table 8) and the species efficiency action upon the symptoms corresponds completely to the presented importance of the symptoms
Table 10. Step 2
| Symptoms | Sdt | Nkr | ||||||
| H E R В S |
002 | Oil | 042 | 060 | 078 | |||
| 002 | 21.6 | 21.2 | -22.7 | 17.6 | 5.9 | 1.2 | 70.7 | |
| 024 | 16.2 | -6.1 | 56.5 | 8.7 | 7.3 | 82.6 | 1.02 | |
| 029 | 18.9 | - | 45.4 | 17.6 | 2.9 | 84.8 | 1.00 | |
| 047 | 2.7 | 24.5 | - | 17.6 | 5.9 | 50.7 | 1.67 | |
| Sds | 59.4 | 39.6 | 79.2 | 61.5 | 22 | |||
| Nks | 2.7 | IL | 3.6 | 2.8 | 1.0 |
D. Calculation results
As a result, the following species composition is obtained.
Table 11. Obtained Composition of Species
| Herb name | Sdt | Weight, g | |
| 002 | Metricaria chamomilla | 1.2 | 5 |
| 024 | Hypericum perforatum | 82.6 | 377 |
| 029 | Plantago | 84.8 | 387 |
| 047 | Taraxacum officinale | 50.7 | 231 |
| 219.3 | 1000 |
The obtained data has a demonstrative character because the algorithm is stated in a simplified manner, as followed:
-
1. In reality, not only one herb is taken from the table of efficiency, but several, for its total efficiency to correspond to the coefficient Kp.np.
-
2. As a result, the probable negative actions of the herbs are taken into account and compensation is made. For instance, most of the herbs cause blood coagulation. Melilotus is normally added for the compensation of this negative effect.
As a result, the complexity of the calculation and the volume of the initial matrix considerably increase, but this article does not cover the detailed explanations. In addition, the doctor is provided with the samples from archives "Computer medical histories", the so-called "Analogue", i.e. the variants which are similar by symptoms and which result in a successful treatment. Therefore, it is the doctor that selects the final variant.
ESTIMATION OF THE PREDISPOSITION TO THE CARDIOVASCULAR DISEASES IN RELATION TO ASTROLOGY
In conclusion of our extensive investigation, we present analysis data of the predisposition to the cardiovascular disease in view of astrology. For example, the curve of dependence in principal cardiovascular diseases is presented. The following graph shows the occurrence of hypertension for different zodiac signs.
Figure 2. Predisposition of Hypertension (HP) in View of Astrology
Zodiac Signs
Notes: 1. Capricorn 2. Aquarius 3. Pisces 4. Aries, 5. Taurus 6. Gemini 7. Cancer 8. Leo
9. Virgo 10. Libra 11. Scorpio 12. Sagittarius
In Table 12, the minimum and maximum of hypertension occurrence is shown.
Table 12. Predisposition in View of Astrology to Cardiovascular Diseases
| Disease | Max | Min | |||
| Sign | No | Sign | |||
| 1 | Hypertension | Libra | 10 | Pisces Scorpio | 3 11 |
| 2 | Hypotonia | Libra | 10 | Aquarius | 2 |
| 3 | Discirculatory Encephalopathy |
Cancer | 7 | Pisces Scorpio | 3 11 |
| 4 | Cardiac Insufficiency |
Taurus Virgo | 5 9 |
Pisces Scorpio | 3 11 |
| 5 | Stenocardia Tension | Virgo Libra Cancer |
9 10 7 |
Aries Scorpio | 4 11 |
The data given in the table correspond in general to the medical astrology data (16).
CONCLUSIONS
-
1. The data presented above shows a high efficiency in the proposed technique of recording, storage and processing information referring to various patient diseases treated by phytotherapy.
-
2. A typical symptomatology of every cardiovascular disease was defined based on the complete processing of the entire database. An efficiency of the action of a particular herb upon the particular parameter was defined by means of the kinetic efficiency for every symptom, syndrome and disease in the computer cartography.
-
3. The theoretical researches conducted by us allowed us to increase the efficiency of phytotherapy of particular patients. A set of herbs for the given particular patients and their concentration in the collection were formulated by us based on the results of the array processing of the efficiency of all the sets of parameters.
REFERENCES
-
1. Hasegawa, M., ed. Herbal Medicine: Kampo Past and Present. Tokyo: Tsumura Juntendo, 1985,52-66
-
2. Tyler, V. E., "What pharmacists should know about herbal remedies" Journal of the American Pharmacological Association, 1996, 36, 29-37
-
3. Rasmussen, P. "A role for phytotherapy in the treatment of benzodiazepine and opiate drag withdrawal (pail 1)" The European Journal of Herbal Medicine, 1997, 3 (1), 11-21
-
4. Bone, M. E., et al., "Ginger root: a new antiemetic: the effect of ginger root on postoperative nausea and vomiting after major gynecological surgery" Anesthesia, 1990, 45, 669-671
-
5. Yokozawa, T. et al., "Studies on the mechanism of the hypoglycemic activity of ginsenoside-Rb2 in streptozotocin-diabetic rats" Chem Phaim Bull. 1985, 14, 255-259
-
6. Bauer, U. "Six-month double-blind randomized clinical trial of Ginkgo biloba extract versus placebo in two parallel groups in patients suffering from peripheral arterial insufficiency" Arzneim Forsch Drag Res. 1984, 34 (1), 716-720
-
7. Aue, W. et al., "Hypertension and hyperlipidemia: garlic helps in mild cases" Brit. J Clin Pract. 1990, 69, 3-6
-
8. Zava, D. et al., "Estrogen and progestin bioactivity of foods, herbs and spices" PSEBM, 1998,217, 369-378
-
9. Tyler, V. E., Herbs of Choice: The Therapeutic Use of Phytomedicinals. Binghamton, NY: Pharmaceuticals Products Press, 1994
-
10. Newall, C. A., Anderson, L. A., and Phillipson, J. D., Herbal Medicine: A Guide for Health Care Professionals. London: Pharmaceutical Press, 1996
-
11. K.A. Treskunov "Essays of phytotherapeutist" book 1, 2002
-
12. K.A. Treskunov "Essays of phytotherapeutist" book 2, 2003
-
13. K.A. Treskunov, N.S. Ignatieva, O.K. Treskunova, B.A. Komarov, A.V. Goroshetchenko in book "Significance of phytotherapy in modem medicine" Russian Academy of sciences, Chernogolovka, 1999: 88-96, 96-102
-
14. K.A. Treskunov, N.S. Ignatieva, O.K. Treskunova, B.A. Komarov, A.V. Goroshetchenko in book "Phytotherapy, laser therapy, natural biological active substances in XXI century" Medical Centre of Russian Academy of Science, Chernogolovka, 2000: 146-152
-
15. V.I. Sergienko, LB. Bondareva "Mathematical statistics in clinical investigations" M. "Geotar-Med" 2001
-
16. M.V. Bilipova "Medical astrology" 199B