Quality of Life in Patients with Urinary Incontinence: A Cross Sectional Study - Juniper Publishers

 Global Journal of Reproductive Medicine - Juniper Publishers

Abstract

Background: Urinary incontinence in women severely affects the physical, social and psychological aspects of life. Objectives: To find out the Quality of Life in female patients with urinary incontinence in a tertiary care hospital.

Materials and Methods: A cross-sectional, observational study was conducted in the Gynecology out-patient department. All non-pregnant women ≥21 years of age, attending the Gynecology OPD of tertiary care hospital for various complaints were included in the study. After obtaining written informed consent, demographics, relevant medical and surgical history was noted, and they were then administered two validated questionnaire 'Incontinence Quality of Life Questionnaire' (IQOL) and SF-36.

Result: The overall incidence of incontinence in this population was 17.0%, with a steadily rising incidence by age. The incidence was more in postmenopausal than premenopausal women. Menopausal women compared to non-menopausal women also had significantly higher incontinence QOL scores (median of 5 vs. 3; p=0.001). Avoidance and limiting behavior (ALB), Psychosocial impact (PSI) and social embarrassment (SE) scores were studied improved after 24 weeks. Items determining ALB had high correlation coefficient with total ALB and all of them were statistically significant. Items determining PSI had statistically significant correlation with mean PSI with all the items except two items. But among the items

Keywords: Female urinary incontinence; Incontinence quality of life questionnaire; SF36; Quality of life

Introduction

Process of urination is adapted in early childhood as an essential social behavior. Social and cultural norms demand that the act of urination be performed in private. Any degree of urine leakage or incontinence that compromises these norms results in discomfiture and initiates a social problem, as urine leakage may be associated with severe consequences on the mental wellbeing of the patient, feeling of alienation, depression or isolation, and may also adversely affect the personal and professional relations of patients. The International Continence Society (ICS) in the year 1976 defined incontinence as “the involuntary loss of urine that is a social hygienic problem”. To be termed as incontinence, the urine leakage must typically occur in the absence of urinary tract infection. The terms ‘social’ and ‘problem’ in the definition highlight the compromise in quality of life that individuals who suffer from this problem must make. To facilitate survey, the ICS has provided a simpler definition of incontinence i.e., “the complaint of any involuntary loss of urine”. As per this definition, more than half the women above 20 years of age have reported one or more episodes of incontinence [1]. The four main types of urinary incontinence are urge, stress, mixed, and functional incontinence. The clinical features the various types of incontinences somewhat overlap, but each type has certain discrete features. Urge incontinence is characterized by the involuntary leakage of urine accompanied by or immediately preceded by urgency. Stress incontinence is associated with urine leakage that occurs because of increased abdominal pressure from laughing, sneezing, coughing, climbing stairs, or other physical stressors on the abdominal cavity and, thus, the bladder. It is the most common type of urinary incontinence in younger women, but the incidence is highest in women between 45 and 49 years old. Mixed incontinence is a Urinary Incontinence combination of urge and stress incontinence, marked by involuntary leakage associated with urgency and with exertion, effort, sneezing, or coughing. Functional incontinence is the inability to hold urine due to reasons other than neuro-urologic and lower urinary tract dysfunction (eg, delirium, psychiatric disorders, urinary infection, reduced mobility) [2].

Because of anatomical difference like short urethra, more chances of recurrent UTI and because of pregnancy-childbirth or hysterectomy related injuries; urinary incontinence is more prevalent in women. Urinary incontinence is estimated to affect 200 million people worldwide. The exact prevalence of urinary incontinence in women is not available because of underreporting. But it is estimated to be as high as 55%.3 Urinary incontinence is associated with disturbance in day-to-day activities, sleep, sexual functions and causes psychological problems. There are multiple facets of urinary incontinence that have the potential to affect health-related quality of life, because both evaluation and treatment may alter quality of life. The disorder may affect emotional and social facets and may also have an impact on activities of daily living and role fulfillment. Because there is a lack of data on exact prevalence and quality of life in female patients with urinary incontinence, we decided to conduct a cross sectional survey about Quality of life in female patients with urinary incontinence in a tertiary care hospital.

Urinary Incontinence

Ethics

Ethics Committee permission was obtained prior to commencement of the study. Written informed consent was obtained from all the women prior to their inclusion in the study.

Study population

All non-pregnant women ≥21 years of age, attending the Gynecology OPD of King Abdullah University Hospital for various complaints were included in the study. After obtaining written informed consent, demographics, relevant medical and surgical history was noted. They were then administered a validated questionnaire ‘Incontinence Quality of Life Questionnaire’ (IQOL) by the same medical person. SF-36, a commonly used general QOL questionnaire was also administered to the patients concurrently with IQOL.

IQOL Questionnaire

The IQOL was a patient reported questionnaire. It was divided into 3 subscales with a total of 22 items pertaining to the symptoms of urinary incontinence:

a) Avoidance and limiting behavior (ALB)

b) Psychosocial impact (PSI)

c) Social embarrassment (SE)

Scoring by IQOL

Each item was to be scored on a 5-point Likert scale of 0 (not at all) to 4 (extremely). A mean score for each subscale is calculated (averaging the scores for the items in each subscale) as well as a total score for all 22 items (sum of all subscale scores). The scores were then transformed to a ‘Scale score’ ranging from 0-100 points for ease of interpretation: Scale score = (sum of the items – lowest possible score)/possible raw score range X 100 Urinary Incontinence.

Interpretation of IQOL

For all items, higher scores indicated less impact of urinary incontinence on quality of life. MCID: MID (Minimally Important Difference) was approximately 4 points when defined as that corresponding to a small effect size (0.2 SD at baseline) and approximately 11 points when defined as corresponding to a medium effect size (0.5 SD at baseline). SEM: ranged from 8-11 points. The IQOL questionnaire was translated into Arabic language and depending upon the language that the woman was best comfortable with, either English or Arabic questionnaire was provided.

Statistical analysis

Categorical variables were described using frequencies and percentages; continuous variables were described using range, mean and standard deviation (SD) if normal, and range, median, and inter-quartile range (IQR) if non-normal. Comparison of groups and categorical variables (cross127 tabulation) was conducted using chi square if the variable was binomial or multinomial and gamma/Kendall’s tau b if ordinal. Comparison of continuous variables (non-normal) was conducted using Mann-Whitney U test. An α of 0.05 was considered statistically significant. All statistical analysis was conducted using IBM SPSS Statistics 19.0 (IBM, Chicago, IL) using 2- tailed tests. Sample size No formal sample size was calculated for this study. All non-pregnant women visiting the Gynecology OPD were sequentially enrolled in the study.

Result

The overall incidence of incontinence in this population was 17.0%, with a steadily rising incidence by age. The differences are statistically significant (Kendall’s tau b: 0.264; gamma=0.546; p=4.1 x 10-12 139). The incidence of incontinence was more than twice as much in menopausal women compared to non-menopausal women (27.2% vs. 12%; p=8.0 x 10-6 140). patients out of 555 were postmenopausal .49patients out of the 180 had urinary incontinence (27.2%) 375 patients were still menstruating; 45 patient only complained of urinary incontinence (12%). Total QOL incontinence score for all subjects (excluding “how do you feel about yourself” and patient reporting of QOL because these are reverse scales compared to all other questions) was a non-normal variable: median: 3.0; range: 0-66 (maximum possible score=76); IQR (inter-quartile range): 10. There was a highly statistically significant difference between incontinence QOL score depending on whether subjects had incontinence or not: median: 22 vs. 2 (n=90 and 446); p=4.6 x 10-32. Although there was a trend toward a lower incontinence QOL score for those subjects aged 30 years or less, the differences between groups were not significant. Menopausal women compared to non-menopausal women also had significantly higher IQOL scores (median of 5 vs. 3; p=0.001). However, when analysis was restricted to those subjects with incontinence, there was no difference in IQOL score (median=22) for those women who were menopausal versus non-menopausal. Patient reported QOL score was not statistically different regarding presence or absence of incontinence: median=2, mean=2.17; no incontinence: median=2, mean=2.35). Likewise, there was even less difference by menopause status (data not shown).

However, respondents scored quite differently when they were asked whether they felt good about themselves; for incontinent subjects their mean/median scores were 1.87/2.0 compared to non-incontinent subjects whose scores were 2.31/3.0. This difference was statistically significant (p=0.003). Fifty two out of 94 women who had urinary incontinence were assessed for the ALB, PSI and SE due to urinary incontinence. The results are provided respectively. When ALB due to urinary incontinence was assessed, the item ‘I have difficulty getting a good night’s sleep because of my incontinence’ had the maximum mean of 1.79, with SD of 1.14 and the item ‘I worry about coughing/sneezing because of my incontinence’ had the least mean of 1.5 with SD of 0.828. When PSI due to urinary incontinence was assessed, the item ‘My incontinence makes me feel helpless’ had the maximum mean of 1.83 with SD of 1.279 and item ‘I get less enjoyment out of life because of my incontinence’ had the least mean of 1.42 with SD of 0.801. When SE due to urinary incontinence was assessed, it was observed that the item ‘I worry about being embarrassed or humiliated by my incontinence’ had the highest mean of 1.96 with SD of 1.427 and item ‘I feel I have no control over my bladder’ had the least mean of 1.6 with SD of 0.934. Correlation between individual items and total scores of ALB, PSI, SE and total QOL) the items determining ALB had high correlation coefficient with total ALB and all of them were statistically significant. Among the items determining PSI, all the items except two items had statistically significant correlation with mean PSI. But among the items determining SE, two items had no significant relationship with SE. Total QOL had significant relationship with all the items except one item of PSI and one item of SE. On comparison of IQOL mean scores with different domains of SF36 questionnaire, role physical had significantly positive relation with ALB, role emotional had significantly negative relation with PSI and SE had a significant and positive relation with bodily pain but negative and significant relationship with general health and vitality.

Discussion

There is an increasing prevalence of bladder control problems as the world population ages. Simultaneously, there is increasing attention to maintaining an active lifestyle. Treatment of urinary incontinence includes options such as pelvic floor exercises, vaginal devices, oral medications, peri-urethral bulking agents, botox injections into the bladder, and surgery. The medical and surgical management available for the treatment of urinary incontinence poses an economic burden, with poor patient satisfaction [3,4]. This further adds to the poor quality of life in patients. The Fourth ICI has stressed the importance of initial assessment of quality of life in patients of urinary incontinence [5]. Most patients with urinary incontinence decide to seek treatment due to the adverse impact of incontinence on the QOL. Disease specific QOL questionnaires provide a standard method of assessing the impact of symptoms of urinary incontinence on QOL of patients. Urinary incontinence is more common in women than in men, due to more exposure to pelvic trauma during childbirth. It is two times more common in women than in men [2]. Age is the single largest risk factor for urinary incontinence. An important finding of this study is that the incidence of incontinence showed a steady rise with age and was higher in menopausal women. This corroborates with the epidemiology of urine where the prevalence is reported to be 6.9% in women aged 20-39 years, 17.2% in those aged 40-59 years, 23.3% in those aged 60-79 years, and 31.7% in women older than 80 years of age.6The results of patient reported QOL suggest that while subjects may not feel that their quality of life is impacted by incontinence when asked to assess quality of life, but it does nevertheless affect them in terms of how good they feel about themselves. The IQOL is a highly used and widely recommended scale. Among other populations, the scale has been shown to be reliable, valid, and responsive to change. No ceiling effects have been reported. The questionnaire is easy to understand and poses little respondent burden. However, the assessment cannot be completed by proxy [4].

Our study provides symptom specific quality of life outcomes for urinary incontinence. The 3 domains of IQOL viz. ALB, PSI and SE showed that urinary incontinence affects the QOL of patients [6]. These effects could be especially bothersome in younger patients where incontinence has been shown to severely affect the emotional behavior and recreation and pastimes in younger women [7]. Moreover, it has been found that women with moderate to severe urinary incontinence may develop clinical depression requiring drug treatment [8]. In our study, we found that, barring a few, most items of IQOL individually correlated with the total subscale/domain scores, and with the overall QOL. The items of SF-36 correlated poorly with the domains of IQOL, indicating that a disease specific questionnaire must be used to assess the health related QOL in patients with symptoms of urinary incontinence. Also, IQOL may be used in future to measure the care provided to women with urinary incontinence and to assess treatment satisfaction. Our study assessed the women patients at a single center, whereas larger multicentric studies would provide substantial evidence of the impact of incontinence on QOL. To conclude, urinary incontinence affects many women and adversely affects the quality of life. Because of the lack of self-reporting, detection is inadequate. Disease specific self-reported questionnaires can help assess the impact of symptoms of urinary incontinence on QOL.

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Utilization of Conjoint Analysis in Understanding Consumer Preferences for Footwear - Juniper Publishers

Fashion Technology & Textile Engineering - Juniper Publishers

Abstract

This study was carried out to analyze the importance of using consumer preferences while stocking footwear by the retailer. Consumer stated preference data was collected in five footwear retail stores. A saturated sampling method was followed. A total of 425 data was collected. The collected consumer preference data was analyzed using conjoint analysis. This resulted in the importance score and utility score for various features of footwear. These scores are useful in estimating the consumer preferences in footwear. The results are estimated using a maximum utility model. The footwear retailers can make use these results in forecasting and stocking decisions for footwear.

Keywords: Fashion product; Footwear; Consumer preferences; Maximum utility model; Forecasting; Stoking decisions

Introduction

Footwear is the outer covering for the feet that gives protection and is in use since the earliest human history. Different cultures have different customs regarding footwear. Retailers and designers, design footwear by analyzing the trend, culture, experiences, intuitions, past sales data Franses & Verhoef [1] expert opinion data Normand, McNeil, Peterson & Palmer [2] consumer preferences data Darby, Batte, Ernst & Roe [3]; Wu, Liao & Chatwuthikrai [4]. While selecting footwear consumers select it based on their preference for a combination of attributes. Consumer preference can be measured in terms of utility that they derive from each attribute which make a product. The Utility can also be defined as the satisfaction that a consumer derives from the consumption of goods. Consumer value for different products is measured in terms of comparing utilities between them. Therefore, consumer preference can be considered as they express major factors such as fit, comfort, price, etc. Consumer preferences can be analysed using many methods like Functional measurement, Trade off analysis, Conjoint analysis etc., Eric P Kroes & Robert J Sheldon [5]. Conjoint analysis was initially originated in mathematical psychology, it is a statistical technique which determines how consumer value different attributes that make up an individual product or service. The objective of the conjoint analysis is to determine what combination of an attribute is more influential on the respondent choice of decision-making Francesco Marangon et al. [6] and was first introduced in marketing research to evaluate consumer preferences Kuzmanovic, Savic, Andric Gusavac, Makajic-Nikolic & Panic [7].

The basic principle underlying conjoint analysis is that a product is composed of attributes (example: comfort) and that each attribute may have two or more levels (example: less, medium, more) Manalo [8]. For example, while purchasing footwear, style and fit is majorly noticed by consumers along with price R Venkata Rao [9]. A combination of these different levels is known as a profile. The profiles can be either hypothetical or realistic. Respondents give their preference for a product in terms of ranking or rating. A profile is the more realistic context of asking respondents to evaluate potential product. They can be either given to respondents as a full profile or trade off method. Full profile is used in conjoint analysis in which the respondents prioritize the full range of the attributes of services J Douglous carroll & Paul E Green [10]. Using an experimental design called orthogonal array a total of a large combinations can be presented in as low as 6-20 combinations Manalo [8]. There are major steps for conjoint analysis as shown in Table 1 Paul E Green & Srinivasan [11].

First step in conjoint analysis is to select hypothetical scenarios for survey, to do this a preference model is selected. From Table 1, any method like vector model or ideal point model etc., can be chosen based on the attributes the product comprises of. The second step is to choose the data collection method. The third step is to use any of the stimulus set construction method and reduce the number of profiles to show to the respondents. Then by selecting a stimulus presentation method, description of the product can be given as pictorial or verbal Holbrook & Moore [12] or pictorial verbal Wu, Liao & Chatwuthikrai [4]. Pictorialverbal representation can be adopted because the information overload is reduced and the respondents take less time and it could be made realistic and interesting Paul E Green, V Srinivasan [13]. Pictorial representations can be used to overcome language barriers. These cards are evaluated by the respondents in the form of ranking or rating them Rada Mihalcea [14]. Ranking is sorting the profiles in terms of preferences from 1 to n. No equal ranks are allowed. It needs more explanations and preparations Jordan J Louviere [15]. Rating is assigning a preference score to each card. It expresses intensity of preferences but without comparison between products Rao [16]. In rating, Likert scale, numeric rating scale, graphic rating scale etc. are used. Likert scale is a scaling method, measuring the positive or negative response of a statement.

It is the most widely used in survey Rohit Verma, Madeline E Pullman [17]. These evaluations are analyzed using part worth, vector model, and ideal point Paul E Green & Srinivasan [11]. Analysis of collected data, results in a utility score, Known as a part worth. Part worth represents attributes utilities by a piece wise linear curve. This curve is formed by a set of straight lines that connect the point estimates of the utilities for the attribute levels Paul E Green, V Srinivasan [13]. These utility scores provide a quantitative measure of the preferences for each factor level and the larger value has the greater preferences. Apart from part worth scores, importance scores can also be estimated. A measure of relative importance of each factor known as an Importance score or value. The importance scores are computed by taking the range of utility score of each factor separately and dividing by the sum of utility ranges of all factors. Importance score also results in profile preferences. Profile preference is done using conjoint simulators. Conjoint simulators transform part worth utility data into a useful and appealing model. Simulators allow research and managers to analyze potential demand in a competitive market context and see how various changes to competing product profiles might impact demand.

This can be used for new product developments Orme B [18]. Conjoint analysis is important in the new product development and understanding preference for non-existing product. Conjoint analysis is used to understand consumer preferences, it has various applications, it is used in new product development of subcompact cars Wu [4] and according to Pentus, Mehine & Kuusik [19] package design can be altered by conjoint analysis as per the consumer’s preference, consumers’ preferences for attributes is demonstrated with the apple as an example Manalo [8] used to evaluate consumer preferences in mobile phones, also in Japanese telecommunication N Takano [20] also to study tourist preferences and in sports apparel because it is more comfort oriented hence it definitely needs the preference of the consumer Fowler [21] young fashion retail buyer’s attribute selection is done using conjoint analysis which helps to redefine or define a new product in fashion Burger [22] etc. Conjoint Analysis is hence proved to be a versatile tool to identify consumer preferences, but there are scarce resources in apparel as well as footwear that uses conjoint analysis in understanding consumer preferences and utilizing results in product designing, stocking decisions etc. Thus, in this study, an attempt is made to use conjoint analysis in understanding consumer preferences in women’s footwear.

Methodology

For understanding important score and utility score, the conjoint analysis was performed by using the following steps. To perform conjoint analysis, the attributes influencing consumer preferences was to be identified [23-25].

Attribute identification

To understand the attributes which influence the consumer preference in footwear, the expert opinion data was collected. Expert opinion data was conducted in 2 rounds. In the first round, the experts gave the important attributes and levels. Then in the second round, a consensus was brought in identifying the important attributes and levels.

Card design

From the expert opinion data, 6 attributes viz. heel, model, comfort, durability, price, material. And their levels are heel – pointed, flat and wedges, model – party wear and casual wear, comfort – less, medium and more, durability – 3 to 6 months, 6 months and 6 months & above, price – 250 to 500, 501 to 1000 and 1001 & above and material – leather, rexin and plastic were identified influencing footwear preferences. A combination of five attributes at three levels and one attribute at two levels (3^5*2^1 =486) resulted in 486 hypothetical profiles. Respondents will not be able to evaluate all the 486 profile, so to reduce the number of profiles, an orthogonal array was performed using SPSS. Here a fractional factorial design was followed to reduce 486 profiles to 20 profiles including 2 holdouts. Based on the orthogonal array, the cards were designed. To make it more interesting and easy way to evaluate, these cards were designed with both verbal and pictorial representation.

Questionnaire preparation

The attributes and various levels of the attributes were explained to the respondents. The evaluations were in the form of rating method. The questionnaire contains 5 - 1 Rating scale in which 5 represent most likely to purchase, 4 – likely to purchase, 3 – may or may not purchase, 2 – less interested and 1 – not at all interested. It also includes 4 open-ended questions about the respondents such as locality, color preferences, age and the brand preferences.

Data collection

The survey was done in Coimbatore, a city in India, for one month. For conducting the survey, a stratified sampling method was used. For this survey, 5 retail stores had been selected which had similar product such as women’s footwear, price such as Rs.250 – Rs.2000, target customers mainly were women, and weekend and week days’ walk-in were also similar in these stores. The retail stores also cater to kids and men’s footwear. The survey was a face– to –face survey.

Utility score

From the data, utility score can also be calculated, using part worth method. These utility scores indicate the perceived value of the variable and how sensitive consumer perceptions and preferences are to changes in product features. The combination of the overall part worth gives the total utility score. According to Kuzmanovic [7] to calculate respondents’ utility, linear additive utility model as in Eq. (1) is used.

Where j is the number of profiles, K is the number of attributes, Lk is the number of levels of attribute k, and βikl is respondent i’s part-worth utility with respect to level l of the attribute k. Xjkl is such a {0,1} variable that equals 1 if profile j has attribute k at level l, otherwise it equals 0. εij is a stochastic error term.

Important score

Attribute selected were price, model, heel, comfort, material and durability. The attributes selected were discrete that means they were individual, separate, distinct, unattached from each other. To understand which attribute the respondents value the most, important score was analyzed using the collected data using the represented in Eq. (2). For this SPSS software version – 17 was used. The importance of an attribute depends on the attribute levels chosen for the study. The importance is calculated based on the range of utility in each attribute.

Preference score

Using the data, the important score and utility score were calculated. The preference scores were also calculated using conjoint simulators. There are various conjoint simulation methods: max utility, Bradley-Terry-Luce (BTL) and logit. Each method has its pro and cons, the share of utility rule suffers from IIA property, and the weight age is based on utility scores. This study aims to give weight age based on preference order and not on the utility score. Maximum utility rule is a simple method and is used for high involvement products to estimate demand for an SKU, the number of respondents for whom this SKU offers highest utility is counted and is divided by a total number of respondents Rao [16]. Maximum utility rule assumes the respondents will buy the product for which he or she has the maximum preference with a probability of 1.

Results and Discussion

Attributes influencing consumer preferences were selected from different sources such as retailers’ interview, journal etc. The final attributes and levels were selected by conducting expert opinion data in two rounds. The selected attributes are heel, material, durability, comfort, ornamentation and price. Experts suggested retaining these six attributes because they felt their customers are more particular about heels, price and material. They also suggested including comfort. Durability because they felt, many customers look for durability, that value for money they pay. They felt customers rarely ask about ornamentation, so that attribute was removed.

Orthogonal array

By doing fractional factorial design twenty hypothetical profiles were derived. This includes two holdouts. This is shown in Table 2.

Design-pictorial/verbal

With the twenty profiles arrived the profile cards were designed. After using fraction factorial method to reduce the profiles from 486 the result came out with 18 cards and 2 holdouts. Hence, we got 20 cards as the final cards. These are pictorial-verbal cards.

Questionnaire design

Respondents evaluated the cards using rating method. The questionnaire contained 5-1 rating scale and questions pertaining to four demographic questions like color preference, age, brand.

Data collection

The survey was done in Coimbatore. This resulted in 425 usable responses. The respondents ensured a good representation of the population based on age. From the collected data, important score is analyzed. The result for important score is given in Table 3. Heel is given highest importance because our respondents were mostly college going girls who gives higher importance only for the heel. Secondly the respondents prefer comfort which gives them free movement. Next to the comfort the customers give more importance to material, price and only minimum importance was given to durability. Finally, model has been chosen as a least attribute as the respondents mostly feel price, durability, material as more important than the model.

Utility score

From the data, the utility score is calculated using part worth method. This utility score indicates the perceived value and the preference of a product. Shown in Figure 1. The results shows, in the attribute “price” lower price i.e. Rs.250 to Rs.500 has gained the highest utility score of 0.40 because the respondents who were visiting these stores are interested to buy the footwear at lower price. The result shows, in the attribute, “model” casual wear has got the highest utility score of 0.17 and party wear has got the lowest utility. The attribute “comfort” has gained the highest utility score of 0.90 than the others. In the attribute” material”, rubber has gained the highest utility score of 0.137.In the attribute “durability” that is 6months & above has gained the highest utility score of 0.083.In the attribute “heel”, flat has gained higher utility.

Simulation

From the utility scores it is noted that the profile which contains Rs.501 to 1000, casual wear, flat, more, comfort rubber and 6 months & above is highly preferred profile among the 27 existing / new profiles and it has gained preference share of 11.6%. Followed by Rs.1001 & above, party wear, pointed, more, leather, 6 months & above gained 10.6% and Rs.250 to 500, casual wear, wedges, less, rubber, 6 months has gained 7.1% and 250 – 500, casual wear, wedges, less, rexin, 3 months has gained 7.0%. From the Table 4 it can be noted that highly preferred SKU’s contains attributes like low price, casual wear, and pointed heel because most of the respondents are under the age of 30 and resides within 10kms from the city.

Reliability

The Pearson correlation coefficient R can take a range of values from +1 to -1. Here the value is greater than 0 i.e. 0.811 indicates a positive association. This value indicates the high linear correlation between the variables. The results show the value of Kendall’s tau is 0.525. This value indicates the moderate relationship between the columns of the rated data. Thus, the maximum utility model is validated in products like footwear. As fashion related products preferences is highly volatile and consumers easily substitute one style for another.

Conclusion

Result of utility score calculation shows, among price, Rs. 250 – 500 is highly preferred and Rs. 1001 & above has low preference. Among Model, casual wear has high preferences and party wear has low preference. Among Heel, pointed heel has high preference and flat has low preference. Among attributes pertaining comfort, more comfort is highly preferred than medium comfort. Among material rubber has high preference than leather. Among Durability attribute- 6 month and above has high preference and whereas, attribute 6 month has low preference. Result of the simulation shows that the combination of attributes which contains 501-1000, casual wear, flat, more comfort, rubber, 6 months & above gained the highest score of 11.6%. Thus, in this study, conjoint analysis is used to find the attributes required for the footwear according to consumer preferences.

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Addiction Medicine Needs Scientific Evidence-Based Interventions to Improve Patient Outcomes. A Model Related to the City of Hope is Proposed as a Step towards Improving Addiction Outcomes Worldwide - Juniper Publishers

 Addiction & Rehabilitation Medicine - Juniper Publishers

Opinion

The National Institute of Health (NIH) is a $37 Billion campus dedicated to finding new and improved treatments for all diseases in the USA. In the USA the National Institute of Drug Abuse (NIDA) a branch of NIH has dedicated $3 Billion to address the opioid crisis within its HEAL Initiative (Help Eliminate Addiction Long Term). The focus of this work is to fund research on ways to lower Opioid deaths, train nurses, doctors, family members and First Responders on ways to prevent overdoses using Narcan administered intra-nasally. Includes an effort to also introduce patients to Medication Assisted Treatment. That is using a drug that is an agonist to dopamine to reduce the euphoric effect of say heroin or Opioid legal drugs on dopamine receptors thereby blocking the euphoric effect of these drugs. It’s not too dissimilar to give Type1 Diabetes needles filled with insulin to keep diabetics alive with daily injections before meals. An estimated 77,000 people will die in The USA in 2019 from Opioid Overdoses. Many became addicted to legal pain medication after an injury, operation or other medical procedure. Additionally, family, friends, nurses and doctors can be trained to administer a medicine that could save an overdose victim with a squirt into the victim’s nose. Most people see addiction as a moral weakness or lack of willpower. However, Addiction is a complex brain disorder with a genetic predisposition. This longstanding stigma attached to addiction is now nearly 100 years old. People born with a certain set of 78 genes have a greater euphoric effect in their brain when using than most people. Regardless of their home life Identical twins raised apart with these genes have higher probability of becoming addicted than other people. Lifestyle of your parents or adoptive parents have little impact good or bad on whether a twin gets addicted, but genes do.

Addiction takes over the brain by activating the primal midbrain which focuses on Fight, Flight, Euphoria and Reproduction. Over time the dopamine receptors (which cause a euphoric effect) require more of the drug to reach the same effect. This then largely reduces the cerebral cortex’s rational thinking in the brain causing self-destructive out of control behavior. Unlike most all diseases only 10% of addicted patients ever get help for their addiction per se. Think about that for a moment, can you name any other disease in which so few are diagnosed and referred to a specialist soon after symptoms show up. Yet, the stigma around this killer disease is powerful. Most MDs do not diagnose and refer these patients. From 1934 until 1979 addiction was excluded from payment by Blue Cross-Blue Shield as a non-covered benefit. I helped get the American Medical Association to pass a resolution in the House of Delegates that it must be covered same as any other killer disease. Then the AMA President and I got the Health Insurance Association to do the same resolution demanding coverage from all other insurance carriers. Lastly, we got the World Health Association to require addiction coverage too. MD training and diagnosing addiction is way behind most diseases. MDs rarely diagnose addiction and refer and if they do refer are not given feedback by addiction treatment centers even if they do refer. This is unlike any other disease. General Practitioners are the gatekeepers of referral for all diagnoses. Yet, society, families and individuals with addiction tend to deny its existence often with tragic consequences.

The cost of all addiction to America is huge in comparison to most diseases. More is spent on the judicial system than on treatment centers. Jail cells don’t cure addiction. Substance abuse costs our Nation over $600 billion annually and treatment can help reduce these costs. Addicted people cause accidents in cars, trucks, trains, and get arrested or cause major lawsuits. It is estimated that the majority of the costs of addiction goes to the judicial system, for judges, juries, jails and parole officers not to mention drug smuggling prosecutions. According to several conservative estimates, every dollar invested in addiction treatment programs yields a return of between $4 and $7 in reduced drug-related crime, criminal justice costs, theft and other medical care of all kinds. When savings related to healthcare are included, total savings can exceed costs by a ratio of 12 to 1. Major savings to the individual and to society also stem from fewer interpersonal conflicts; greater workplace productivity; and fewer drug-related accidents, including overdoses and deaths.

In the US and worldwide addiction medicine has some major challenges ahead. Last year an estimated 77,000 opioid overdoses occurred nationwide. And these senseless deaths continue despite the $3B being spent to stem this tide. Part of the challenge we have in addiction is that we are dealing with a complex brain disorder. And science has not yet resolved how the brain is impacted by drugs of all kinds. The brain itself has more dopamine connections than the Milky Way galaxy by far the most complex organ on earth. And we do not yet fully understand how it works completely. Identical twins raised apart have a high probability of being addicts despite their adoptive parents or family life. We also know that the single most important trait to being successful in life is the ability to delay gratification. Such a trait is often woefully missing in people who become addicts, alcoholics, gamblers, smokers, sexually hyperactive, etc.

We know that home and family life play a role in the spread of addiction as do biological and genetic factors. All drugs of abuse affect the brain pleasure and reward systems in different ways. Growing evidence points to structural brain changes that drugs of abuse can trigger depression, and genetic factors which impact dopamine receptors along with those impacting Serotonin. Reductions in Serotonin has been associated with Depression and relapses. We still don’t understand the human brain fully. And that barrier is rendering our existing treatment regimens inadequate in improving outcomes. Today, patients once discharged from a random treatment center in the US will show 60% of patients will relapse within 6 months. Sometimes with little to no means to track these patients going forward. However, there is a new company seeking to address this inadequacy with a sophisticated system that tracks patients thru treatment from the perspective of clinicians treating them; family members; discharge planners and other patients as well. This data is collected and can be shared (with confidentiality of patient names) with third party payors.

Is it time for addiction treatment to be more like other diseases such as cancer where a large campus is created by a nonprofit 501C3 Foundation (tax deductible) that co shares newly developed innovations resulting from a collaborations of treatment centers internationally that have collaborations with medical device, biotech, Pharmaceutical, Imaging, and genetic companies whose research collaborations can obtain patents on new innovative diagnostic and treatment new discoveries that can be reviewed by a heterogeneous Medical Advisory Commission. This would not be an echo chamber with only recovering addicts and alcoholics along with Board Certified Addiction Medicine Medical Doctors. It would include perhaps geneticists, oncologists (who understand how cancer spreads with the help of genetics), Nobel Laureates in Brain neuroscience, geneticists, detoxification experts, etc. Such a freestanding nonprofit organization would be in a position to look more objectively at the science of the brain and its impact on the rest of the body. And in turn focus on a cure for addiction in a way that a for profit entity might be hampered by as well as an aggregation of Universities competing for grant money and not as much focus on a cure.

The creation of the Addiction Medicine Institute was inspired by the above model that resembles the City of Hope for Cancer in Duarte California. My goal was to catalyze a private nonprofit entity that is focused on the discovery of new and better treatments for addiction. Such an entity is generally lacking worldwide. I would be interested in hearing from other addiction clinicians, researchers and innovators who might want to collaborate with such an entity on behalf of addicts and alcoholics worldwide.

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Oxidative Stress and Inflammatory Biomarkers Analysis of Biofield Treated Proprietary Test Formulation in Heart Tissues in Cecal Slurry, LPS and E. Coli-induced Systemic Inflammatory Response Syndrome (SIRS) in Sprague Dawley Rats - Juniper Publishers

 Annals of Reviews and Research - Juniper Publishers

Abstract

The study was aimed to evaluate the antioxidant and anti-inflammatory biomarkers in heart tissues after treatment with the Biofield Energy Treated Proprietary Test Formulation and Biofield Energy Treatment per se to the animals on Cecal Slurry, LPS and E. coli-induced systemic inflammatory response syndrome (SIRS) model in Sprague Dawley rats. In this experiment, different antioxidants biomarkers such as myeloperoxidase (MPO), superoxide dismutase (SOD), lipid peroxidase (LPO) and proinflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), macrophage inflammatory protein-2 (MIP-2), and matrix metallopeptidase 9 (MMP-9) were analysed using ELISA assay in heart homogenate. A proprietary test formulation was formulated including minerals (magnesium, zinc, calcium, selenium, and iron), vitamins (ascorbic acid, pyridoxine HCl, vitamin E, cyanocobalamin, and cholecalciferol), Panax ginseng extract, β-carotene, and cannabidiol isolate. The constituents of the test formulation were divided into two parts; one section was defined as the untreated test formulation, while the other portion of the test formulation and the animals received Biofield Energy Healing Treatment remotely for about 3 minutes by a renowned Biofield Energy Healer, Mr. Mahendra Kumar Trivedi.

The level of MPO was reduced by 12.07% in the G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15) group as compared to the untreated test formulation (G4) group. Moreover, the level of SOD was significantly (p≤0.05) increased by 19.03%, 17.26%, and 11.81% in the G6, G7, and G9 groups, respectively as compared to the G4 group. The level of TNF-α was significantly decreased by 25.97%, 40.28% (p≤0.01), 24.86%, 36.54% (p≤0.01), and 34.30% in the G5, G6, G7, G8, and G9 groups, respectively as compared to the disease control (G2) group. Moreover, the level of IL-6 was significantly (p≤0.001) decreased by 23.5%, 31.0%, 26.3%, and 39.8% in the G5, G6, G8, and G9 groups, respectively as compared to the G2 group. Additionally, the level of MIP-2 was reduced by 26.7% and 19.5% in the G6 and G8 groups, respectively as compared to the G4 group.

Besides, the level of MMP-9 was significantly (p≤0.001) reduced by 15.1%, 21.5%, and 34% in the G6, G8, and G9 groups, respectively as compared to the G4 group. Altogether, the data imply the antioxidant and anti-inflammatory potential of the Biofield Energy Treated test formulation and Biofield Energy Treatment per se along with preventive measure on the animal with respect to various inflammatory conditions that might be beneficial various types of systemic inflammatory disorders specially sepsis, trauma, septic shock or any types of cardiac injuries. Therefore, the results showed the significant slowdown the inflammation-related disease progression and its complications/symptoms in the preventive Biofield Energy Treatment group per se and/or Biofield Energy Treated Test formulation groups (viz. G6, G7, G8, and G9) comparatively with the disease control group.

Keywords: Biofield Treatment; Inflammatory cytokines; The Trivedi Effect®; ELISA; SIRS; Antioxidant; Heart biomarker

Abbreviations: SIRS: Systemic inflammatory response syndrome; MPO: Myeloperoxidase; SOD: superoxide dismutase; LPO: Lipid peroxidase; CAD: Coronary artery disease; LDL: Low-density lipoprotein; CAM: Complementary and Alternative Medicine; NCCAM: National Center for Complementary/Alternative Medicine; NCCIH: National Centre of Complementary and Integrative Health; SD: Sprague Dawley; LPS: Lipopolysaccharide; SEM: Standard error of mean; RA: Rheumatoid arthritis; AD: Addison disease

Introduction

Cardiovascular diseases are very common cause of health burden worldwide [1]. Heart disease is the leading cause of death for all age’s population in the United States. In 2010, coronary artery disease (CAD) accounted for one in six deaths in the United States [2]. However, in 2020, one person dies every 36 seconds that’s one in every four deaths in the United States from cardiovascular disease [3,4]. Oxygen free radicals promote low-density lipoprotein (LDL) peroxidation, and increase the number of foam cells, that causes vascular endothelial cell injury, and induce expression of proinflammatory cytokines [5]. Cytokines (TNF-α, TGF-β) and interleukins (IL-1, IL-4, IL-6, IL-8, and IL-18) are responsible for the development of various inflammatory pathologies of various vital systems such as cardiac, brain, renal, lymphatic, etc. [6]. MIP-2 is produced by a variety of cells in response to infection or injury. It is regulated by multiple factors like by signalling through Toll-like receptor 2 (TLR2), TLR3, and TLR4 in response to diverse pathogens [7]. Superoxide dismutases (SODs) an antioxidant enzyme and also acts as a good therapeutic agent against reactive oxygen species-mediated diseases [8]. Thus, in order to study the change in heart cytokines in presence of Cecal Slurry, LPS and E. coli-induced systemic inflammatory response syndrome model in Sprague Dawley rats, a novel test formulation was designed with the combination of vital minerals (selenium, zinc, iron, calcium, and magnesium), essential vitamins (cyanocobalamin, ascorbic acid, pyridoxine HCl, vitamin E, and cholecalciferol), and nutraceuticals (β-carotene, Ginseng, cannabidiol isolate (CBD)). All the minerals and vitamins used in the test formulation have significant functional role to provide vital physiological responses [9,10]. Besides, cannabidiol itself has wide range of pharmacological profile and has been reported to role in different disorders [11,12], while ginseng extract is regarded as the one of the best immune booster for overall immunity [13]. The present study was aimed to evaluate the antioxidant and anti-inflammatory potential of the Biofield Energy Treated Proprietary Test Formulation and Biofield Energy Treatment per se to the animals on Cecal Slurry, LPS and E. coli-induced systemic inflammatory response syndrome model in Sprague Dawley rats.

Biofield Energy Healing Treatment has been reported with significant effects against various disorders and defined as one of the best Complementary and Alternative Medicine (CAM) treatment approach [14-16]. National Center for Complementary/Alternative Medicine (NCCAM) recommended CAM with several clinical benefits as compared with the conventional treatment approach [17]. National Centre of Complementary and Integrative Health (NCCIH) accepted Biofield Energy Healing as a CAM health care approach in addition to other therapies such as deep breathing, natural products, Tai Chi, yoga, therapeutic touch, Johrei, Reiki, pranic healing, chiropractic/osteopathic manipulation, guided imagery, meditation, massage, homeopathy, hypnotherapy, special diets, relaxation techniques, movement therapy, mindfulness, Ayurvedic medicine, traditional Chinese herbs and medicines in biological systems [18,19]. The Trivedi Effect®-Consciousness Energy Healing Treatment was scientifically reported on various disciplines such as in the materials science [20,21], agriculture science [22], antiaging [23], gut health [24], nutraceuticals [25], pharmaceuticals [26], overall human health and wellness. In this study, the authors want to evaluate the effect of the Biofield Energy Treatment (the Trivedi Effect®) on the given novel test formulation and Biofield Energy Treatment per se to the animals on heart biomarkers in presence of Cecal Slurry, LPS and E. coli-induced systemic inflammatory response syndrome model in in Sprague Dawley rats using standard ELISA assay.

Material and Methods

Chemicals and Reagents

Pyridoxine hydrochloride (vitamin B6), zinc chloride, magnesium (II) gluconate, and β-carotene (retinol, provit A) were purchased from TCI, Japan. Cyanocobalamin (vitamin B12), calcium chloride, vitamin E (Alpha-Tocopherol), cholecalciferol (vitamin D3), iron (II) sulfate, and carboxymethyl cellulose sodium were procured from Sigma-Aldrich, USA. Ascorbic acid (vitamin C) and sodium selenate were obtained from Alfa Aesar, India. Panax ginseng extract and cannabidiol isolate were obtained from Panacea Phytoextracts, India and Standard Hemp Company, USA, respectively. Dexamethasone was obtained from Clear synth, India. For the estimation of heart antioxidant and inflammatory biomarker panels, such as myeloperoxidase (MPO), superoxide dismutase (SOD), lipid peroxidation (LPO), tumour necrosis factor alpha (TNF-α), interleukin-6 (IL-6), macrophage inflammatory protein-2 (MIP-2), and matrix metallopeptidase 9 (MMP-9) were procured from CUSABIO, USA using specific ELISA kits.

Maintenance of Animal

Randomly breed male Sprague Dawley (SD) rats with body weight ranges from 200 to 300 gm were used in this study. The animals were purchased from M/s. Vivo Bio Tech, Hyderabad, India. Animals were randomly divided into nine groups based on their body weights consist of 10-12 animals of each group. They were kept individually in sterilized polypropylene cages with stainless steel top grill having provision for holding pellet feed and drinking water bottle fitted with stainless steel sipper tube. The animals were maintained as per standard protocol throughout the experiment.

Consciousness Energy Healing Strategies

Each ingredient of the novel test formulation was divided into two parts. One part of the test compound did not receive any sort of treatment and were defined as the untreated or control sample. The second part of the test formulation was treated with the Trivedi Effect® - Energy of Consciousness Healing Treatment (Biofield Energy Treatment) by a renowned Biofield Energy Healer, Mr. Mahendra Kumar Trivedi under laboratory conditions for ~3 minutes. Besides, three group of animals also received Biofield Energy Healing Treatment (known as the Trivedi Effect®) by Mr. Mahendra Kumar Trivedi under similar laboratory conditions for ~3 minutes. The Blessing (prayer)/Treatment was given to the test items/animals (present in the laboratory of Dabur Research Foundation, near New Delhi, India), remotely from USA for about 3 minutes via online web-conferencing platform. After that, the Biofield Energy Treated samples was kept in the similar sealed condition and used as per the study plan. In the same manner, the control test formulation group was subjected to “sham” healer for ~3 minutes treatment, under the same laboratory conditions. The “sham” healer did not have any knowledge about the Biofield Energy Treatment. The Biofield Energy Treated animals were also taken back to experimental room for further proceedings.

Experimental Procedure

Seven days after acclimatization, animals were randomized and grouped based on the body weight. The test formulation was prepared freshly prior to dosing and administered to the animals using an oral intubation needle attached to an appropriately graduated disposable syringe. The dose volume was 10 mL/kg in morning and evening based on body weight. The experimental groups were divided as G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Dosing for groups G7 and G8 were started on Day -15 and continued till end of the experiment. However, Group G1 to G5 and G9 animals were dosed with respective formulations from Day 1 and continued till the end of the experiment. Group G6 animals received Biofield Energy Treatment on Day-15 and were not dosed throughout the experimental period. At the end of the experimental period (8 weeks treatment), the animals were sacrifice and heart were collected, homogenised, and the supernatant subjected for estimation of antioxidants (MPO, SOD, and LPO) and cytokines (TNF alpha, IL-6, MIP-2, and MMP-9).

Induction of Systemic Inflammatory Response Syndrome (SIRS) Model

A combination model of sepsis was developed in SD rats by administering Cecal slurry (from donor animals, intraperitoneally, at the dose of 400 mg/kg) in combination with LPS (at the dose of 100 µg/animal) and E. coli [Escherichia coli; 0.2 mL (2M CFU)/animal]). The animals were monitored for various parameters for up to 56 days after disease (SIRS) induction. Ten Donor (~20 weeks old) rats were anesthetized. A midline laparotomy was performed on them and the cecum was extruded. A 0.5 cm incision was made on the anti-mesenteric surface of the cecum, and the cecum was squeezed to expel the feces. The feces from different donor animals was collected and weighed. Immediately after collection, the feces were pooled, diluted 1:3 with 5% dextrose solution and filtered to get a homogeneous suspension. Bacterial viability in the cecal slurry was analyzed. Cecal slurry prepared from donor rats was injected intraperitoneally into experimental rats (G2 to G9) at the dose of 400 mg/kg within 2 hours of preparation. After 3 hours, lipopolysaccharide (LPS) at the dose of 100 µg/animal, and gram-negative viable bacteria such as E. coli [0.2 mL (2M CFU)/animal] were injected, intraperitoneally (G2 to G9).

Preparation of Sample for the Estimation of Antioxidant and Cytokines

With the continued treatment to the respective groups of 8th week of the experimental period, all the animals were sacrificed, heart were collected, homogenized and subjected for the estimation of antioxidants and cytokines. The tissue from all the groups was stored at -20°C for further estimation. Alternatively, aliquot all the samples and store samples at -20°C or -80°C. Avoid repeated freeze-thaw cycles, which may alter the level of cytokines during final calculations.

Estimation of Antioxidants and Cytokine Levels

The heart from all the groups was subjected for the estimation of level of antioxidants such as MPO (CSB-E08722r), SOD (706002), and LPO (700870) and cytokines such as TNF-α (CSB-E11987r), IL-6 (CSB-E04640r), MIP-2 (CSB-E07419r), and MMP-9 (CSB-E08008r). All the biomarker panel was estimation using ELISA method as per manufacturer’s recommended standard procedure. This was a quantitative method and the principle was based on the binding of antigen and antibody in sandwich manner assay.

Statistical Analysis

The data were represented as mean ± standard error of mean (SEM) and subjected to statistical analysis using Sigma-Plot statistical software (Version 11.0). For multiple comparison One-way analysis of variance (ANOVA) followed by post-hoc analysis by Dunnett’s test and for between two groups comparison Student’s t-test was performed. The p≤0.05 was considered as statistically significant.

Results and Discussion

Assessment of Antioxidants in Heart Homogenate

Estimation of Myeloperoxidase (MPO): Myeloperoxidase (MPO) was estimated in the presence of the test formulation and the data are graphically shown in Figure 1. The data suggested that the disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) + 0.5% CMC) group (G2) showed value of MPO as 2.41 ± 0.0.28 ng/mL, which was increased by 0.45% as compared with the normal control (G1, 2.40 ± 0.1 ng/mL). However, positive control (Dexamethasone) treatment (G3) showed the level of MPO in heart i.e., 2.80 ± 0.14 ng/mL.

The level of MPO in heart tissues was decreased by 9.98% and 12.07% in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation) and G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15) groups, respectively as compared to the untreated test formulation (G4) group. High expression of MPO level in circulation are associated with inflammation and increased oxidative stress that leads to cardiovascular disease (CVDs) like coronary artery disease, congestive heart failure, arterial hypertension, pulmonary arterial hypertension, myocardial ischemia, stroke, cardiac arrhythmia and venous thrombosis [27]. Multiple lines of evidence suggested that MPO may play a role in atherogenesis in humans. However, MPO has little role as atheroprotective in the murine atherosclerosis model [28]. MPO plays an important role in the host defense against different types of bacteria and viruses. MPO is also an important enzyme in the inflammatory process, and inflammation is a key component in the development and progression of atherosclerotic and other forms of cardiovascular disease [29]. Overall, in this experiment the Biofield Energy Treated test formulation and Biofield Energy Healing Treatment per se reduced the level of MPO in the heart tissues, which could be helpful for the management of oxidative stress and inflammatory conditions related to cardiovascular disorders.

Figure 1 The effect of the test formulation on the level of heart myeloperoxidase (MPO) in Sprague Dawley rats. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9).

Estimation of Superoxide Dismutase (SOD): The effect of the test formulation and Biofield Energy Treatment per se was assessed by estimating the level of heart superoxide dismutase (SOD), and the results are graphically presented in the Figure 2. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) + 0.5% CMC) group (G2) showed value of SOD as 3.79 ± 0.13 U/mL, which was decreased by 3.2% as compared to the normal control group i.e., 4.10 ± 0.18 U/mL. However, positive control (Dexamethasone) treatment (G3) showed the level of SOD in heart i.e., 4.49 ± 0.22 U/mL, which was increased by 13.3% as compared to G2.

The level of SOD was increased significantly by 1.27%, 19.03% (p≤0.05), 17.26% (p≤0.05), 6.15%, and 11.81% (p≤0.05) in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation); G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15), G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15), and G9 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation) groups, respectively with reference to disease control group (G2). Further, the level of SOD was significantly increased by 3.8%, 22.01% (p≤0.05), 20.19% (p≤0.05), 8.80%, and 14.6% in the G5, G6, G7, G8, and G9 groups, respectively with reference to untreated test formulation group (G4). Studies in the heart suggest that extra-cellular SOD is important for preventing oxidative injury after myocardial infarction and may contribute to cardiac remodeling [30]. SOD is one of the main intracellular antioxidant defence mechanisms is associated with cardiac and vascular defects leads to hypertension and atherosclerosis. It is also protecting thermogenesis [31]. Therefore, in this experiment the Biofield Energy Treated test formulation significantly increased the level of heart SOD, which could be beneficial inflammation and oxidative damage.

Figure 2: The level of superoxide dismutase (SOD) measured in heart tissue in Sprague Dawley rats after administration with Biofield Treated test formulation and Biofield Treatment per se. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se + Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9). *p≤0.05 vs. G2 and #p≤0.05 vs. G4.

Estimation of Lipid Peroxidation (LPO): The level of lipid peroxidation (LPO) end product in terms of malondialdehyde (MDA) was detected in all the experimental groups and the data are presented in Figure 3. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) group (G2) and positive control (Dexamethasone) treatment (G3) groups showed value of MDA as 4.20 ± 0.48 µM and 4.33 ± 0.37 µM, respectively.

The level of MDA was decreased by 5.6%, 2.9%, and 18% in the G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15), and G9 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation) groups, respectively with reference to disease control group (G2). Additionally, the level of MDA was significantly reduced by 4.1%, 11.1%, 8.5%, and 22.8% (p≤0.05) in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation), G7, G8, and G9 groups, respectively as compared to the untreated test formulation group (G4). Oxidative stress and inflammation are two major mechanisms leading to atherosclerosis. Under oxidative stress, phospholipids and cholesterol esters can readily oxidized through a free radical-induced lipid peroxidation (LPO) process to form a complex mixture of oxidation products. These oxidized lipids are responsible for inflammatory responses in atherosclerosis by interacting with immune cells (macrophages) and endothelial cells [32]. The LPO products are highly reactive and causes selective alterations in cell signaling, protein and DNA damage, and cytotoxicity [33]. In this experiment, the Biofield Energy Treated preventive groups significantly reduced the level of LPO in heart tissues, which could be beneficial inflammation and oxidative damage in heart.

Figure 3: The level of heart lipid peroxidation (LPO) in Sprague Dawley rats after dosed with the Biofield Treated test formulation and Biofield Energy Healing per se. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9). *p≤0.05 vs. G4.

Assessment of Cytokines in Heart Homogenate

Estimation of Tumour Necrosis Factor Alpha (TNF-α): The expression of heart tumour necrosis factor alpha (TNF-α) in Sprague Dawley rats after administration of Biofield Treated test formulation and exposure of Biofield Treatment to the animals per se, and the results are shown in Figure 4. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) group (G2) showed value of TNF-α as 204.12 ± 46.49 pg/mL, which was significantly (p≤0.01) increased by 399% as compared with the normal control (G1, 40.91 ± 3.85 pg/mL).

Further, the positive control (Dexamethasone) treatment (G3) showed significant (p≤0.01) decreased TNF-α level by 66% i.e., 69.31 ± 8.52 pg/mL as compared to the G2 group. TNF-α level was decreased significantly by 25.97%, 40.28% (p≤0.01), 24.86%, 36.54% (p≤0.01), and 34.30% in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation); G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15), G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 (Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se + Biofield Energy Treated test formulation from day -15), and G9 (Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se animals + untreated test formulation) groups, respectively as compared to the disease control group (G2). Further, the expression of TNF-α was reduced by 16.2%, 10.9%, and 7.8% in the G6, G8, and G9 groups, respectively as compared to the untreated test formulation group (G4). Pro-inflammatory cytokines are consistently increased in congestive heart failure. In the cardiovascular system, TNF-α activate signal transduction pathways may causes vascular dysfunction, development, and progression of atherosclerosis, and thus ultimately leads to myocardial infarction and heart failure [34]. Another, study reported that TNFα is responsible for the progression of heart failure as a mediator of myocardial dysfunction and adverse remodeling, that leads to elevated levels of circulating TNFα in heart failure patients as compared with the control [35]. Moreover, TNF modulates both cardiac contractility and peripheral resistance, the two most important haemodynamic determinants of cardiac function [36]. Therefore, here the Biofield Energy Treated test formulation and Biofield Energy Treatment per se significantly reduced the level of TNF-α, which could be beneficial in the cardiovascular disorders.

Figure 4: The expression of heart tumour necrosis factor alpha (TNF-α) in Sprague Dawley rats after administration of Biofield Treated test formulation and exposure of Biofield Treatment to the animals per se. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9). ##p≤0.01 vs. G1 and **p≤0.01 vs. G2.

Estimation of Interleukin-6 (IL-6)

The expression of heart interleukin-6 (IL-6) in Sprague Dawley rats after administration of Biofield Treated test formulation and exposure of Biofield Treatment to the animals per se, and the results are graphically shown in Figure 5. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) group (G2) showed value of IL-6 as 19.05 ± 2.29 pg/mL, which was significantly (p≤0.001) increased by 98.7% as compared with the normal control (G1, 9.59 ± 0.44 pg/mL). Further, the positive control (Dexamethasone) treatment (G3) showed the level of IL-6 i.e., 10.46 ± 0.71 pg/mL, which was decreased by 45.1% as compared to the G2 group. The level of IL-6 was significantly decreased by 23.5% (p≤0.001), 31.0% (p≤0.001), 19.5%, 26.3% (p≤0.001), and 39.8% (p≤0.001) in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation); G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15), G7 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15; G8 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15), and G9 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation) groups, respectively, as compared to the disease control group (G2).

Further, the expression of IL-6 was decreased by 3.2%, 12.7%, 6.7%, and 23.9% in G5, G6, G8, and G9 groups, correspondingly with reference to untreated test formulation (G4) group. Based on the one of the studies from myocardial infarction which shows that IL-6 signaling plays a causal role in cardiovascular disease [37]. The patients with high titre of circulating inflammatory biomarkers get more susceptible to cardiovascular events. It is more common in patients with high IL-6, associated with an increased incidence of myocardial infarction and mortality among patients with acute coronary syndromes [38]. There is an extensive body of the literature that supports that an increased level of inflammatory cytokine like IL-6 is associated with acute ischemic conditions and predictor of coronary artery disease [39]. Overall, in this experiment the Biofield Energy Treated test formulation and Biofield Energy Treatment per se significantly reduced the level of IL-6, which could be reduce the risks of inflammatory diseases specially in the heart.

Figure 5: The expression of heart interleukin-6 (IL-6) in Sprague Dawley rats after administration of Biofield Treated test formulation and exposure of Biofield Treatment to the animals per se. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9). ###p≤0.001 vs. G1 and ***p≤0.001 vs. G2.

Estimation of Macrophage Inflammatory Protein-2 (MIP-2): The expression of macrophage inflammatory protein-2 (MIP-2) in heart tissue after administration of the Biofield Treated/Blessed proprietary test formulation and Biofield Energy Healing Treatment per se to the animals was estimated, and the results are graphically shown in Figure 6. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) group (G2) showed value of MIP-2 as 1734.78 ± 237.57 pg/mL, which was decreased by 51.8% as compared with the normal control (G1, 3598.50 ± 395.77 pg/mL).

Further, the positive control (Dexamethasone) treatment (G3) showed increased heart MIP-2 level by 40.6% i.e., 2438.50 ± 255.71 pg/mL as compared to the G2 group. The level of MIP-2 was decreased by 26.7% and 19.5% in the G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15) and G8 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15) groups, respectively as compared to the untreated test formulation group (G4). The MIP-2 is a murine counterpart of IL-8. MIP-2 is a naturally occurring inflammatory cytokine biomarker in myocardium and its expression is increased during myocarditis. Study reported that plasma MIP-2 levels are significantly elevated in mice on days 7 and 14 of post-infection with encephalomyocarditis (EMC) virus [40]. Taken together, our data suggest that the Biofield Energy Treated test formulation and Biofield Energy Treatment per se reduced the level of MIP-2 in heart tissues, which could prevent the cardiovascular-inflammation.

Figure 6: The expression of heart macrophage inflammatory protein-2 (MIP-2) in Sprague Dawley rats after treatment with Biofield Treated test formulation and Biofield Energy treatment per se to the animals. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation. Values are presented as mean ± SEM (n=6-9).

Estimation of Matrix Metallopeptidase-9 (MMP-9): The expression of matrix metallopeptidase-9 (MMP-9) in heart tissue after administration of the Biofield Treated/Blessed proprietary test formulation and Biofield Energy Healing Treatment per se to the animals was estimated, and the results are graphically presented in Figure 7. The disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na) group (G2) showed value of MMP-9 as 155.85 ± 12.62 pg/mL, which was increased by 13.8% as compared with the normal control (G1, 136.96 ± 4.68 pg/mL). Further, the positive control (Dexamethasone) treatment (G3) group decreased MMP-9 level by 8.1% i.e., 143.28 ± 7.66 pg/mL as compared to the G2 group.

The level of MMP-9 was decreased by 6.4%, 9%, 2%, 15.8%, and 29.3% in the G5 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation); G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15); G7 (Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation from day -15); G8 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se plus the Biofield Energy Treated test formulation from day -15), and G9 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se animals plus the untreated test formulation) groups, respectively, as compared to the disease control group (G2).

Besides, the level of MMP-9 was significantly reduced by 12.6%, 15.1% (p≤0.001), 8.6%, 21.5% (p≤0.001), and 34% (p≤0.001) in the G5, G6, G7, G8, and G9 groups, respectively with reference to untreated test formulation (G4) group. MMP-9 is one of the most widely investigated MMPs. MMP-9 expression has increases during cardiovascular disorders like hypertension, atherosclerosis, and myocardial infarction. MMP-9 degrades extracellular matrix proteins and activates cytokines and chemokines to regulate pathological remodeling processes that involve inflammation and fibrosis in cardiovascular disease [41]. According to one of the extensive research work done by Swedish researchers, they found the high level of MMP-9 in coronary artery disease (coronary artery ectasia) patients and a predictor of increased mortality in that patients [42]. In this study, the Biofield Energy Treated test formulation and Biofield Energy Treatment per se significantly reduced the level of MMP-9, which could be beneficial to combat inflammatory disease conditions in the cardiovascular patients.

Figure 7: The effect of the test formulation on the level of heart macrophage inflammatory protein-2 (MIP-2) in Sprague Dawley rats. G1 as normal control (vehicle, 0.5% w/v CMC-Na); G2 as disease control (Cecal Slurry, LPS and E. coli + 0.5% CMC-Na); G3 as reference item (Cecal Slurry, LPS and E. coli + Dexamethasone); G4 includes Cecal Slurry, LPS and E. coli along with untreated test formulation; G5 as Cecal Slurry, LPS and E. coli along with the Biofield Energy Treated test formulation; G6 group includes Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15; G7 as Cecal Slurry, LPS and E. coli + Biofield Energy Treated test formulation from day -15; G8 group includes Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se + Biofield Energy Treated test formulation from day -15, and G9 group denoted Cecal Slurry, LPS and E. coli + Biofield Energy Treatment per se animals + untreated test formulation. Values are presented as mean ± SEM (n=6-9). ***p≤0.001 vs. G4. Experiment includes four preventive maintenance groups (G6, G7, G8 and G9). The findings showed the significant slowdown of inflammation-related symptoms and also reduced the chances of disease susceptibility. All-inclusive, it indicate that the Trivedi Effect® was found to be most effective and benefited to protect different kinds of diseases and also improve the overall health and quality of life.

Conclusion

Based on the study outcome it was found that the level of MPO was decreased by 12% in the G6 (Cecal Slurry, LPS and E. coli along with Biofield Energy Treatment per se to animals from day -15) group as compared to the untreated test formulation (G4) group. Expression of SOD was significantly (p≤0.05) increased by 19.03%, 17.26%, and 11.81% in the G6, G7, and G9 groups, respectively as compared to the G4 group. Moreover, the level of TNF-α was significantly reduced by 25.97%, 40.28% (p≤0.01), 24.86%, 36.54% (p≤0.01), and 34.30% in the G6, G7, G8, and G9 groups, respectively with reference to disease control (G2) group. Additionally, IL-6 was significantly (p≤0.001) decreased by 23.5%, 31.0%, 26.3%, and 39.8% in the G5, G6, G8, and G9 groups, respectively as compared to the G2 group. Further, MIP-2 was decreased by 26.7% and 19.5% in the G6 and G8 groups, respectively as compared to the G4 group. Besides, the level of MMP-9 was significantly (p≤0.001) reduced by 15.1%, 21.5%, and 34% in the G6, G8, and G9 groups, respectively as compared to the G4 group.

Altogether, the Biofield Energy Treated test formulation and Biofield Energy Healing Treatment (the Trivedi Effect®) per se showed significant results with respect to different inflammatory biomarkers (cytokines) in the preventive maintenance group, G6 as well as other preventive maintenance groups (G7, G8, and G9) in Cecal Slurry, LPS and E. coli-induced systemic inflammatory response syndrome model rat model study. It also helped to slowdown the inflammatory disease progression and disease-related complications. The study data showed that Biofield Energy Treated Test formulation and Biofield Energy Treatment per se would be one of the best treatment strategies to prevent the manifestation of diseases. Thus, the Biofield Energy Treatment might act as a preventive maintenance therapy to maintain and improve the overall health and quality of life and simultaneously reduce the severity of acute/chronic diseases. The test formulation can also be used against rheumatoid arthritis (RA), fibromyalgia, aplastic anaemia, Addison disease (AD), multiple sclerosis, myasthenia gravis, psoriasis, Crohn’s disease, ulcerative colitis, dermatitis, hepatitis, Parkinson’s, stroke, etc.

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