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[An Official Publication of ISF College of Pharmacy, Moga]



Original Article
Year : 2018   |  Volume : 10   |  Issue : 4   |  Page : 158-161  

Correlation of demographics profile of patients with genital herpes at a tertiary care hospital in Punjab

Davinder Singh, Amit Sharma, Sumir Kumar, Ashish Baldi, Dinesh Kumar Sharma

Correspondence Address:Department of Pharmacy Practice, ISF College of Pharmacy, Moga, Punjab, India. Department of Pharmacy, Uttarakhand Technical University, Dehradun, Uttarakhand. Department of Pharmacy Practice, ISF College of Pharmacy, Moga, Punjab, India. Department of Skin and VD, Guru Gobind Singh Medical College and Hospital and RC, Baba Farid University of Health Sciences, Faridkot, Punjab, India. Department of Pharmaceutical Science and Technology, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, India. Department of Pharmacy, Roorkee College of Pharmacy, Roorkee, Uttarakhand, India

Source of Support: Nil, Conflict of Interest: None declared


DOI: 10.4103/2231-4040.197331

Abstract  

Introduction: Genital herpes is a sexually transmitted infection (STI). This STI causes herpetic sores, which are painful blisters (fluid-filled bumps) that can break open and ooze fluid. Objective: The present study was designed to investigate the correlation of genital herpes at a tertiary care teaching hospital. Methodology: The prospective study was conducted over a period of 8 months. This included 220 genital herpes patients of age between 31 and 40 years who fulfilled the inclusion criteria that were recruited in the study. Result: Of 220 cases, 153 were male and 67 were female. Mean of the age of male patients was found to be 35.23 and female was 33.34. The value of age variable, i.e., R2 = 0.367 was weak as it found to be <0.4. Hence, correlation was found to be weak. A positive coefficient indicates that the association is positive, that is, if weight increases, body mass index of the patient also increases. Conclusion: Our study showed that the maximum patients were male and they were from 31 to 40 age category, most of the patients were belong to a rural area and they were married and they were doing the private job, most common presenting complaint of patients was genital herpes.

Keywords: Genital herpes simplex virus, body mass index, sexually transmitted disease

How to cite this article:
Singh D, Sharma A, Kumar S, Baldi A, Sharma DK. Correlation of demographics profile of patients with genital herpes at a tertiary care hospital in Punjab. Pharmaspire 2018;10(4):158-161.

Introduction

Genital herpes is a sexually transmitted infection (STI). This STI causes herpetic sores, which are painful blisters (fluid-filled bumps) that can break open and ooze fluid. It is caused by either of the two herpes simplex viruses (HSV), HSV type 1 (cold sores) or HSV type 2 (genital herpes); this type of the HSV that enters your body through small breaks in the skin or mucous membranes. The mucous membranes are the thin layers of tissue that lines the openings of your body. They can be found in your nose, mouth, and genitals. Once the viruses are inside your body, they incorporate themselves into your cells and then stay in the nerve cells of your pelvis when the sores are not present Sharma6virus can also spread. Infants can also infect from infected mother.[1] According to the WHO, approximately 60% of worldwide HSV-2 infections are among women. For 2003, it was estimated that there were 23.6 million new HSV-2 infections among 15–49 years old globally, with 12.8 million of those infections among reproductive-age females.

Methodology

The prospective study was conducted over a period of 8 months in the Department of Dermatology, Guru Gobind Singh Medical College and Hospital, Faridkot. This included 220 genital herpes patients of age between 31 and 40 years who fulfilled the inclusion criteria that were recruited in the study. Diseases were diagnosed on the basis of detailed history, demographic data, and age of sexual debut, lifetime number of sexual partners, clinical examination, and relevant investigations. The data were analyzed by significant statistically analysis that is SPSS ver. 16. The human immunodeficiency virus (HIV) status of all the patients was established with enzyme-linked immunosorbent assay test done as per the NACO guidelines.[4] Clinical examination along with all relevant investigations such as complete hemogram, serum biochemistry profile, and complete urine examination. Venereal disease research laboratory test was also done in all patients and controls.

It can be diagnosed by the following tests:

  • Viral culture: This test involves taking a tissue sample or scraping of the sores for examination in the laboratory.[5]
  • Polymerase chain reaction (PCR) test: PCR is used to copy your DNA from a sample of your blood, tissue from a sore, or spinal fluid. The DNA can then be tested to establish the presence of HSV and determine which type of HSV you have.[5,6]
  • Blood test: This test analyses a sample of your blood for the presence of HSV antibodies to detect a past herpes infection.

The test done with this kit, as compared to the western blot for HSV-2, is 98% specific and 100% sensitive. Linear regression was calculated to know the association between variable coefficients and whether the residuals were positive or negative.

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Results

Of 220 cases, 153 were male and 67 were female. The age of the cases varied from 31 to 40 years, with a mean age of 34.65 years as shown in Table 1. Mean of the age of male patients was found to be 35.23 and female was 33.34. Of 220 cases, 158 were married and 62 were unmarried. History of exposure to multiple partners was obtained from all the males. Of 220 cases, 45 patients gave a positive history of genital herpes. Of these 220 cases, 42 patients had active genital pain at the time of the examination. The mode of transmission in most cases was heterosexual 206 (96%) followed by bisexual 14 (6.4%). Patient was sex with 1–5 partner and contact with partner more than 5 times; a history of unprotected sexual contact with partner was elicited in 156 (70.9%) patients. It was observed that 52 (23.6%) partners were having genital ulcer, 148 (67.3%) having extramarital contact and type of partner were maximum friends and relatives, and 135 (61.4%) patients doing sex for fun.

A linear regression was performed to predict relationship of body mass index (BMI) with age of the patient. A significant regression equation was found F (1,218) = 1.638 P = 0.001 with an R-value is 0.18 and R2 is 0.001. Relationship of age of the patient was significant predictors with BMI.

Coefficients table is the main table for linear regression. Table 3 or Figure 1 shows BMI = 29.84–0.01 for age. A negative coefficient shows that the association is negative. The value of age variable, i.e., R2 = 0.367 was weak as it found to be <0.4. Hence, correlation was found to be weak. From residuals, statistics discovers the residuals. The mean (standard deviation [SD]) for predicted values (BMI) is 30.23 (0.86%) as shown in Table 2. In a good model, there should be very few residual and our residual here is ranging from −11.393 to 12.408 and the maximum Cook’s distance is 0.001–0.056. A linear regression was performed to predict relationship of BMI with weight. A significant regression equation was found F (1,218) = 3952.90 P = 0.001 with an R2 of 0.73 and R is 860. Relationship of weight was significant predictors with BMI. Coefficients table is the main table for linear regression, Table 3 or Figure 1 shows BMI = −3.201–0.443 for weight, the value of R2 for weight variable, i.e., 0.739. Hence, it was found that correlation was moderate and positive. From residuals, statistics discover the residuals. The mean (SD) for predicted values (BMI) is 30.23 (4.24%). In a good model, there should be very few residual and our residual here is ranging from −2.60 to 2.91 and the maximum Cook’s distance is 0.001–043, as shown in Table 2.

A linear regression was performed to predict relationship of BMI with height. A significant regression equation was found F (1,218) = 1834.07 P = 0.001 with an R2 of 0.343 and R is 0.586. Relationship of height was significant predictors with BMI. Coefficients table is the main table for linear regression. This is shown in Table 3 and Figure 1 shows BMI = 100.7–6.6 for height. The value of R2 for height variable was 0.343. Hence, the correlation was weak and negative coefficient due to R-value in between 0.1 and 0.3, i.e. weak. From residuals, statistics discover the residuals. The mean (SD) for predicted values (BMI) is 30.23 (2.894%) as shown in Table 2. In a good model, there should be very few residual and our residual here is ranging from −10.96 to 12.285 and the maximum Cook’s distance is 0.001–049. No outliers were found during this test.

Discussion

Genital ulcerative disease is a potential risk factor for acquiring HIV infection. Few studies revealed that genital herpes is currently the most common genital ulcerative disease. More recently, several groups have reported that serological evidence of HSV type 2 infections is associated with increased HIV-1 infection.[5-7] Due to the sample size, it was not possible to determine the correlates of each STI within the different sites which could be different due to heterogeneity in behavior patterns and historical trajectory of infections.[15-20] Face-to-face interviews could lead to misreporting due to social desirability bias. Finally, we were able to explore the impact of people who were missed in the survey on study outcomes as the demographic variables between those who migrated out, were present but refused to participate and participate demographic variables to differ between those who were missed from the survey and those who participated.[8,21-25] Our study revealed that male patient was 153 (69.5%) and a female patient was 67 (30.5%), the study was opposed from Mohanty et al. (1995),[9-13,26] it was found to be 407 (78.8%) was male and 109 (21.13%) were female; a linear regression was performed to predict relationship of BMI with age. Relationship of age weight height of the patient was significant predictors with BMI.

A positive coefficient indicates that the association is positive, that is, if weight increases, BMI of the patient also increases a negative coefficient indicates that the association is negative, that is, if height decreases BMI of the patient also decreases. The residuals statistics tell us about the residuals.

Conclusion

Genital herpes was the most common ulcerative STI, while genital wart was the most common non-ulcerative STI and estimates of the linear relationship between age, weight, and height with BMI. The estimates highlight the urgent need for the public health community to ensure that well-recognized effective interventions for STI prevention, screening, diagnosis, and treatment should be more widely available. Improved estimation methods are needed.[9-14] The effectiveness of antiviral treatment for genital herpes should be investigated in core groups at high risk of HIV/STD.[14,26,27,30,31] Our study showed that the maximum patients were male and they were from 31 to 40 age category; most of the patients were belong to a rural area and they were married and they were doing the private job and maximum patients were educated with the 12th class, the most common presenting complaint of patients was genital herpes.[27-35] Health programs should be still more focused on creating awareness of the minor STIs and to remove the stigma from the society so that the patients attend the proper health-care facilities in the early stage itself for treatment thereby and as a result complications and further transmission of the STIs can be avoided.

Ethical approval

The study was conducted after approved by the Institutional Ethics Committee of Indo Soviet Friendship College of Pharmacy, Moga, India.

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