Abstract
Introduction: Patients with human immunodeficiency virus and acquired
immunodeficiency syndrome (HIV/AIDS) are prone to opportunistic infections
(OIs) given their immunosuppressed state. OIs continue to cause morbidity and
mortality in HIV/AIDS patients even after highly-active antiretroviral therapy
(HAART); hence, attainment of the goals on health care programs, particularly
in resource-poor countries, is hard to achieve. The prevalence of specific OIs
varies in different countries and even in different areas within the same
country. Little information is available about the prevalence of OI in HIV
patients from developing countries, especially India. Early diagnosis and
prompt treatment contribute to increased life expectancy among infected
patients delaying progression to AIDS. Hence, the present study was carried out
to elucidate current frequencies and spectrum of OIs in HIV seropositive adult
patients in Haryana and to evaluate the associated risk factors for OIs. Materials
and methods: This was a cross-sectional study carried out at the Dept. of
General Medicine in a tertiary care hospital in North India. Basic demographic
details, anthropometric measurements, symptoms of HIV/OI, clinical examination,
biochemical investigations, and treatment details were recorded. Patients aged
18 to 70 years and HIV seropositive subjects were included in the study. Results:
The study found that about 53.21% of HIV/AIDS patients on ART had one or more
OIs. Tuberculosis (TB) was the predominant OI identified, with a prevalence of
25.71%. Candidiasis and herpes zoster were the second and the third most
prevalent OIs at 13.8% (101/731) and 7.25% (53/731), respectively. Age
(43.4 ± 10.7 years), low-income, illiteracy, low socioeconomic status,
initial 4 months since initiation of ART, CD4 count <200/mm3,
body mass index of <18.5 kg/m², poor ART adherence, hemoglobin, albumin were
strongly associated with OIs. Conclusion: The present study shows that
TB is the commonest OI in adults and the overall population of people living
with HIV (PLHIV) in Haryana and proves that OIs across different patient groups
vary significantly. Various factors like adherence to HAART, socioeconomic and
education status of patients can influence the occurrence and outcome of these
deadly infections.
Keywords: Spectrum,
opportunistic infections, PLHIV
Human immunodeficiency virus (HIV)
infection is one of most studied infectious diseases since it was first
recognized clinically in 1981 in the United States of America. HIV-related
opportunistic infections (OIs) have been defined as infections that are more
frequent or more severe because of HIV-mediated immunosuppression1.
OIs are the first clinical manifestations that alert clinicians to the
occurrence of the acquired immunodeficiency syndrome (AIDS). These OIs occurs
on average 7 to 10 years after infection with HIV2,3. Until
effective antiretroviral therapy (ART) was developed, patients generally
survived for only 1 to 2 years after the initial manifestation of AIDS4.
However, OIs continue to cause morbidity and mortality in HIV/AIDS patients
even after highly-active antiretroviral therapy (HAART); hence, the attainment
of the goals on health care programs, particularly in resource-poor countries,
is hard to achieve. OIs shorten the life span of people with HIV infection and
require expensive treatments, which carry a substantial financial burden,
especially for a developing country like India. Timely intervention helps
HIV-positive persons live longer and also helps to prevent transmission in the
community5.
Estimating the cost of necessary health care as
accurately as possible must be the first step in planning specialized health
services, which is only possible if we know how the OIs are distributed in a
given place. Also, there is no denying that HIV-related OIs affect a person’s
quality of life and contributes to the overall disability-adjusted life years
(DALY) caused by AIDS. The prevalence of specific OIs varies in different
countries and even in other areas within the same country. Identifying such OIs
is especially important for HIV and AIDS case management. Little information is
available about the prevalence of OI in HIV patients from developing countries,
especially India. Early diagnosis of OIs and prompt treatment contribute to
increased life expectancy among infected patients delaying progression to AIDS.
Hence, this study was carried out to elucidate current prevalence and spectrum
of OIs infecting HIV-seropositive adult patients in Haryana, a northern state
in India, and to evaluate the associated risk factors of OIs. Identifying such
pathogens is very important for clinicians and health planners to tackle the
AIDS epidemic more effectively.
MATERIALS AND METHODS
This was a cross-sectional study carried out at
a tertiary care center in North India. Adult patients between 18 to 70
years attending the Nodal ART Centre, admitted under Dept. of Medicine PGIMS,
Rohtak, Haryana, and admitted under clinics were enrolled in this study.Patients
who did not consent to participate in the study, those with psychiatric illness
taking regular medications, pregnant and lactating mothers, those with
non-HIV/AIDS-related malignancy, known cases of chronic kidney and liver
disease prior to diagnosis of HIV and patients with an altered sensorium or cognitive
impairment severely affecting communication were excluded from the
study. Our Nodal ART Centre has all the adequate facilities and
investigations for detecting the OI before commencing ART.
Detailed information of all enrolled patients
was filled in a proforma designed for the study purpose. This included basic
demographic details, anthropometric measurements, symptoms of HIV/OI, clinical
examination and treatment. At baseline, each patient underwent hematological
and biochemical investigations. Patients were assessed for OI risk factors.
These included age, weight at last visit, serum albumin at diagnosis of OI,
World Health Organization (WHO) clinical stage III and IV, CD4 count at
the time of diagnosis of OI, initiation of ART since diagnosis of HIV and
adherence to ART. The Center for Adherence Support Evaluation (CASE)
Adherence Index, a simple composite measure of self-reported ART adherence, was
utilized to assess adherence to ART6.Informed consent
was taken from all participants and study was approved from ethical committee
of the institute and Haryana state division of National AIDS Control Society.
The diagnosis of OI was made following standard
guidelines where possible, and facilities available. Where diagnosis was based
on clinical grounds alone, the opinion of two independent physicians involved
in enrolled patient care and management was required before such diagnosis was
accepted.
Statistical Analysis
Statistical Package for Social Sciences (SPSS)
Version 23 was used for all descriptive and statistical analysis. Association of OIs was done by subgroup analysis
of WHO staging, CD4 count, demographic and biochemical/hematological profile,
and treatment adherence. The distribution of data was analyzed and appropriate parametric/nonparametric tests were used for statistical analysis. Continuous data were expressed as means ± standard deviation (SD), and the means were compared using
a t-test. Nominal data were expressed as frequencies or proportions, and the Chi-square test and Fisher’s exact test were used to compare the differences in frequency. For all tests, a p-value of <0.05 will be considered significant, and
the confidence interval will be kept at 95%.
RESULTS AND OBSERVATIONS
The study was conducted in the Dept. of General
Medicine, PGIMS, Rohtak, Haryana, India. A total of 731 patients aged 18 to 70
years and HIV seropositive subjects were included in the study. The baseline
characteristic of the study participants is presented in Table 1.
Table
1. Distribution of Demographic Characteristics of Study Subjects
|
Demographic characteristics
|
Frequency
|
Percentage
(%)
|
Gender
Female
Male
Transgender
|
284
438
9
|
38.85
59.92
1.23
|
Area of residence
Rural
Urban
|
534
197
|
73.05
26.95
|
Religion
Christian
Hindu
Muslim
Sikh
|
3
717
10
1
|
0.41
98.08
1.37
0.14
|
Income
<2,000
2,000-5,000
5,001-20,000
>20,000
|
135
232
298
66
|
18.47
31.74
40.77
9.03
|
Socioeconomic status
Lower
Upper lower
Lower middle
Upper middle
Upper
|
51
113
377
120
70
|
6.98
15.46
51.57
16.42
9.58
|
Education
Illiterate
Primary school
Secondary school
College and Above
|
172
271
208
80
|
23.53
37.07
28.45
10.94
|
Marital status
Married
Unmarried
Widow/Widower
|
655
23
53
|
89.60
3.15
7.25
|
Spouse
Expired
Nonreactive
Reactive
|
52
289
198
|
9.65
53.62
36.73
|
Age (years)
Mean ± SD
Median (25th-75th percentile)
Range
|
40.02
± 11.17
38
(32-48)
19-70
|
The study found that about 53.21% of HIV/AIDS
patients had one or more OIs compared to 46.79% who had no
OI. Tuberculosis (TB) (48.32% of total OIs) was the predominant OI
identified, with a prevalence of 25.71% (200/731). Of these, 71.80% (n = 135/188)
were pulmonary TB and 31.3% were extrapulmonary TB (n = 59/188). Among the
extrapulmonary TB cases, 35 were abdominal TB and 24 were TB
meningitis. Candidiasis and herpes zoster were the second and the third
most prevalent OIs in the present study, at 13.8% (101/731) and 7.25% (53/731),
respectively (Table 2).
Table 2. Distribution of Opportunistic Infections
of Study Subjects
|
Opportunistic
infections
|
Frequency
|
Percentage (%)
|
Percentage (%) from
total OI
|
No OI
|
342
|
46.79
|
-
|
Skin
Herpes zoster
Kaposi sarcoma
|
73
53
20
|
9.99
7.25
2.74
|
18.77
13.62
5.14
|
CNS
TBM
Primary CNS lymphoma
PMLE
Cryptococcal
meningitis
Cerebral
toxoplasmosis
|
56
24
3
2
15
12
|
7.66
3.28
0.41
0.27
2.05
1.64
|
14.40
6.17
0.77
0.51
3.86
3.08
|
GIT
Abdominal TB
Chronic mucocutaneous
candidiasis
Candidal esophagitis
HSV oral ulcers
|
166
35
100
1
16
|
22.71
4.79
13.68
0.14
2.19
|
42.67
9.00
25.71
0.26
4.11
|
Chronic diarrhea
Cryptosporidiosis
Giardiasis
Isosporiasis
Schistosomiasis
|
20
14
1
2
3
|
2.74
1.92
0.14
0.27
0.41
|
5.14
3.60
0.26
0.51
0.77
|
Respiratory
Pulmonary TB
|
161
135
|
22.02
18.47
|
41.39
34.70
|
Other bacterial
Klebsiella
pneumoniae
Pseudomonas
aeruginosa pneumonia
Streptococcus
pneumoniae
|
12
3
1
8
|
1.64
0.41
0.14
1.09
|
3.08
0.77
0.26
2.06
|
Fungal
Aspergillus fumigatus pneumonia
Histoplasma
capsulatum pneumonia
Cryptococcus
neoformans pneumonia
Pneumocystis
jirovecii pneumonia
|
8
1
1
1
5
|
1.09
0.14
0.14
0.14
0.68
|
2.06
0.26
0.26
0.26
1.29
|
Hematology
Diffuse large B-cell
lymphoma
|
10
10
|
1.37
1.37
|
2.57
2.57
|
Eye
CMV retinitis
|
1
1
|
0.14
0.14
|
0.26
0.26
|
Total pulmonary and
extrapulmonary
|
188
|
25.71
|
48.32
|
OI
= Opportunistic infection; TB = Tuberculosis; CNS = Central nervous system;
TBM = Tuberculosis meningitis; PMLE = Polymorphous light eruption; GIT =
Gastrointestinal tract; HSV = Herpes simplex virus; CMV = Cytomegalovirus.
There were 63 co-infections of different OIs
observed in the current study. Of these, 55 had 2 co-infections, 7 had 3
co-infections, and 1 patient had 4 co-infections. TB with candidiasis were the
most common co-infection (32 cases) followed
by TB with cryptosporidiosis (4 cases).
The mean ± SD of age (years) in patients with OI
was 43.4 ± 10.7, which was significantly higher than patients without OI (36.18
± 10.43). The proportion of patients with OI was significantly higher in
patients with income (in Rupees) (<2,000 [68.15.52%] and 2,000-5,000
[60.34%]) as compared to 5,000-20,000 (45.97%) and >20,000 (30.30%). OIs
were significantly higher in illiterate people (66.86%) as compared to those
with primary school education (52.40%), secondary school education (54.33%) and
college and higher education (23.75%) with a p-value of <0.0001. It was
found that 90.20% of patients in the lower Kuppuswamy class had OIs as compared
to upper-lower (57.52%), lower-middle (52.25%), upper-middle (41.67%), and
upper class (44.29%) with a p-value <0.0001. OIs were significantly higher
in patients with body mass index (BMI) (kg/m²) of <18.5 (underweight; 83.94%) as compared to 18.5-24.99 (normal BMI;
44.23%), 25-29.99 (overweight; 3.85%), =30 (obese; 0%) with p value of
<0.0001. Significant association was seen between weight (kg) and OIs. Mean ± SD of weight (kg) in patients without OI was 58.7 ± 9.17, which was significantly higher as compared to patients with OI (52.72 ± 7.21) with p value of <0.0001.
The proportion of patients with OI was
significantly higher in time since ART initiation (months)=12 months
(71.84%) as compared to 13 to 24 months (30.19%), 25 to 36 months
(26.67%), 37 to 48 months (57.64%), 49 to 60 months (53.33%), 61 to 72
months (55.56%), and =73 months (52.21%) (p < 0.0001). The
proportion of patients with OI was significantly higher within 1 to 4
months (83.33%) as compared to 5 to 8 months (66.67%), 9 to 12 months (50%)
after HAART initiation with p value of 0.011. This signifies that as the viral
load decreases and CD4 count improves, the risk of OIs reduces significantly.
The highest prevalence was seen in patients
categorized as WHO clinical stage IV and III (n = 135/135, 100%) and (n =
193/193, 100%), respectively, while the lowest prevalence was observed among
clinical stage I patients (n = 1/342, 0.29%). Statistically, a significant
association was depicted between the prevalence of OIs and WHO clinical stages
II, III, and IV.
The prevalence of
OIs was found to be highest (n = 225/225, 100%)
among HIV-infected patients with CD4 count <200/mm3 followed by
CD4 count 200-349/mm3 and 350-499/mm3 with a prevalence
of (n = 122/157, 77.71%) and (n = 30/127, 23.62%), respectively
whereas, the prevalence was significantly lower in patients with CD4 count more
than 500/mm3 with a prevalence of only 5.41% (Fig. 1). The mean
± SD CD4 count/mm³ in patients without OI was 600.37 ± 246.8, which was
significantly higher than patients with OI (199.07 ± 116.88).

Good adherence to ART was seen in 503 (68.81%)
patients, and poor adherence was present in 228 patients (31.19%). OIs were
significantly higher in patients with poor ART adherence (99.12%) as compared
to good adherence (32.41%).
A significant
association was seen between low hemoglobin, protein (g/dL), albumin (g/dL)
and OI. Mean ± SD protein (g/dL) and albumin (g/dL) in patients without OI
was 7.51 ± 0.86, 3.9 ± 0.51, respectively, which was significantly higher as
compared to patients with OI (7.29 ± 0.88 (p = 0.0006), 3.63 ± 0.6 (p
< 0.0001)), respectively.
On univariate
analysis, co-factors that had significant association with OIs were low-income
education/socioeconomic status, age, weight/BMI, hemoglobin, albumin, CD4
count, WHO staging, adherence to ART (Table 3).
On performing multivariate regression, CD4
count, low case adherence index score (poor adherence) and WHO staging (stage
II, stage III and stage IV) were significant independent risk factors of OI
after adjusting for confounding factors. Patients with low case adherence index
score (poor adherence), WHO staging (stage II, stage III, stage IV) had
significantly high risk of OI with adjusted odds ratio (OR) of 913.992
(21.282-39,252.803), 20.188.208 (678.408-60, 0764.698), 26.264.032
(640.880-1076331.334), respectively. With the increase in CD4, risk of OI
significantly decreased with adjusted OR of 0.989 (0.98-0.999) (Table 3).
Table 4. Comparison Between Different Studies
Vis-a-Vis Present Study
|
Study
|
Prevalence of OIs
|
Most common OIs
|
Most common
|
2nd most common
|
3rd most common
|
Our study (2022)
|
53.21%
|
Tuberculosis (48.32%)
|
Candidiasis (25.7%)
|
Herpes zoster (13.6%)
|
International studies
Mitiku et al7
(2015)
Solomon et al13
(2018)
Balkhair et al9 (2012)
Iroezindu et al10
(2013)
Chanie et al (in
children)17 (2021)
|
48%
88.4%
58%
22.4% (76/339)
5.53%
|
Tuberculosis (21.23%)
Tuberculosis (18%)
Pneumocystis
jirovecii pneumonia (25%)
Candidiasis (8.6%)
Pneumonia (35.63%)
|
Herpes zoster (11.2%)
Community-acquired
pneumonia (16.3%)
Cryptococcal
meningitis (22%)
Tuberculosis (7.7%)
Tuberculosis (28.74%)
|
Oral candidiasis
(9.5%)
Oral candidiasis
(15.3%)
CMV retinitis (17%)
Dermatitis (5.6%)
Oral Candidiasis
(10.34%)
|
Indian studies
Vinod et al15
(2018)
Ghate et al11 (2009)
Srirangaraj et al12
(2011)
Singh et al16 (2003)
Bariha et al18
(2018)
Saldanha et al19
(2008)
Sharma20
(2004)
|
23.5%
35.7%
8.3%
|
Candidiasis (52%)
Tuberculosis (15.4%)
Tuberculosis (53.4%)
Oral candidiasis
(59%)
Tuberculosis (51%)
Tuberculosis (45.3%)
Tuberculosis (71%)
|
Tuberculosis (50%)
Oral Candidiasis (11.3%)
Oral Candidiasis
(27.2%)
Tuberculosis (56%)
Oral Candidiasis
(43%)
Candidiasis (34.5%)
Candidiasis (39.3%)
|
Herpes zoster (10.1%)
Herpes zoster (14.7%)
Cryptosporidiosis
(47%)
Cryptosporidiosis
(6.8%)
Cryptosporidiosis
(17.5%)
Pneumocystis
jirovecii pneumonia (7.4%)
|
DISCUSSION
HIV is a major global public health issue, which
has claimed more than 40 million lives so far with ongoing transmission
globally. Despite the availability of ART, it is not a 100% curable disease.
OIs and associated complications account for considerable morbidity and
mortality in people living with HIV (PLHIV). The present study involving 731
patients on ART was carried out to elucidate current frequencies and spectrum
of OIs infecting HIV seropositive adult patients in Haryana and to evaluate the
associated risk factors of OIs.
The most common self-reported risk factor for
the occurrence of HIV was the heterosexual route of transmission (94.53%),
followed by unsafe sex with high-risk partners 6.16% and men who have sex with
men (MSM) 3.01%. This can be explained by the mode of sexual activity practiced
in the population. The study found that about 53.21% of HIV/AIDS patients
on ART had one or more OIs compared to 46.79% who had no OI. This agrees with
the prevalence of 48%, 46.7% and 58% documented by Mitiku et al, Sun et al, and
Balkhair et al, respectively7-9. However, prevalence in the present
study is higher than various studies conducted in Nigeria and Southern India,
which documented 22.4%, 35.7%, and 8.3% prevalence, respectively10-12.
This might be due to methodological differences in selecting study subjects.
Moreover, South India’s literacy rate is comparatively higher as compared to
Haryana’s; the present study found a significant association between education
and OIs. This may explain the lower prevalence of OIs in the South. Also, it
was lower as compared to the South Ethiopia study with a prevalence of 88.4%13.
This could be due to differences in availability and duration of HAART, the
difference in CD4 level, clinical staging and the difference in host immunity
of study subjects.
The present study revealed that TB (48.32% of
total OIs) is the predominant OI identified, with a prevalence of 25.71%
(188/731). Other studies done worldwide also had the same observation and TB
was the most common OI found in PLHIV7,13,14. TB enhances the
progression of HIV infection by inducing immune activation. Candidiasis and
herpes zoster were the second and the third most prevalent OIs in the present
study, at 13.8% (101/731) and 7.25% (53/731), respectively. However, in many
other studies, Candidiasis was found to be the most common OI as summarized in
Table 47,9-13,15-20.
Table 4. Comparison Between Different Studies
Vis-a-Vis Present Study
|
Study
|
Prevalence of OIs
|
Most common OIs
|
Most common
|
2nd most common
|
3rd most common
|
Our study (2022)
|
53.21%
|
Tuberculosis (48.32%)
|
Candidiasis (25.7%)
|
Herpes zoster (13.6%)
|
International studies
Mitiku et al7
(2015)
Solomon et al13
(2018)
Balkhair et al9 (2012)
Iroezindu et al10
(2013)
Chanie et al (in
children)17 (2021)
|
48%
88.4%
58%
22.4% (76/339)
5.53%
|
Tuberculosis (21.23%)
Tuberculosis (18%)
Pneumocystis
jirovecii pneumonia (25%)
Candidiasis (8.6%)
Pneumonia (35.63%)
|
Herpes zoster (11.2%)
Community-acquired
pneumonia (16.3%)
Cryptococcal
meningitis (22%)
Tuberculosis (7.7%)
Tuberculosis (28.74%)
|
Oral candidiasis
(9.5%)
Oral candidiasis
(15.3%)
CMV retinitis (17%)
Dermatitis (5.6%)
Oral Candidiasis
(10.34%)
|
Indian studies
Vinod et al15
(2018)
Ghate et al11 (2009)
Srirangaraj et al12
(2011)
Singh et al16 (2003)
Bariha et al18
(2018)
Saldanha et al19
(2008)
Sharma20
(2004)
|
23.5%
35.7%
8.3%
|
Candidiasis (52%)
Tuberculosis (15.4%)
Tuberculosis (53.4%)
Oral candidiasis
(59%)
Tuberculosis (51%)
Tuberculosis (45.3%)
Tuberculosis (71%)
|
Tuberculosis (50%)
Oral Candidiasis (11.3%)
Oral Candidiasis
(27.2%)
Tuberculosis (56%)
Oral Candidiasis
(43%)
Candidiasis (34.5%)
Candidiasis (39.3%)
|
Herpes zoster (10.1%)
Herpes zoster (14.7%)
Cryptosporidiosis
(47%)
Cryptosporidiosis
(6.8%)
Cryptosporidiosis
(17.5%)
Pneumocystis
jirovecii pneumonia (7.4%)
|
In the present study, the prevalence of
cryptococcal meningitis was 2.05%, significantly higher than in the study
conducted by Mitiku, with a prevalence of 0.28%7. This could be due
to increasing diagnostic availability
(radiological and serology) and high suspicion of disease. There were 63 co-infections of different OIs observed in the present study. Of these, 55 had 2 co-infections, 7 had 3 co-infections, and 1 patient had 4 co-infections. Also, TB with candidiasis
was the most common co-infection (32 cases), followed by TB with cryptosporidiosis (4 cases). This was similar to studies conducted in Eastern Ethiopia and Northwest Ethiopia7,21.
A higher
proportion of TB and candidiasis co-infection in the present study may be
explained by a higher prevalence of these two OIs among the study participants.
Double and triple OIs have also been reported from studies in India and Nigeria5,10.
Prevalence of OIs among patients with comorbid viral hepatitis was comparable.
No statistically significant association was observed (p = 0.053).
This could be due to the small sample size of hepatitis B virus (HBV) and
hepatitis C virus (HCV) reactive patients. However, the highest prevalence of
OIs was depicted among hepatitis B surface antigen (HBsAg) reactive patients (n
= 14/18, 77.78%).
The present study was conducted among HIV
patients taking ART for 1 month or more. The prevalence of OIs was
significantly higher in patients on ART for <4 months (83.33%), and the
prevalence decreased in the subsequent months. This was similar to various
previous studies and may be because HAART improves patient’s CD4 count and
therefore the prevalence of OIs decreases overtime22,23.
HIV-associated OIs and other related infections continue to occur in
HIV-positive patients, but since the introduction of HAART, most infections
occur at rates that are substantially lower than those seen in the pre-HAART
era.
WHO clinical stage IV and III showed highest
prevalence while least prevalence was observed among clinical stage I
patients. This was similar to study in Northwest Ethiopia21. In WHO
stages II, III and IV, there is marked reduction in CD4 count, which may be the
reason for the increased prevalence of OIs as in our study. The prevalence of
OIs was highest (n = 225/225, 100%) among HIV-infected patients with CD4 count
<200/mm3. In contrast, the prevalence was significantly lower in
patients with a CD4 count of >500/mm3, with a prevalence of only
5.41%. Other studies from India have also reported a high risk of developing
OIs such as TB, Pneumocystis jirovecii pneumonia and cryptococcal
meningitis among patients with CD4 counts <200 cells/mm3 23.
This finding appears accurate since CD4 cells play a central role in the
activation of humoral and cellular immune response in the fight against
infection. Hence, low CD4 count increases susceptibility to OIs21.
In the present
study, OI was significantly higher in patients with BMI (kg/m²) of <18.5
(underweight; 83.94%). BMI is an important indicator of nutritional status in
patients with HIV infection. Emaciation is a common condition during the early
period of HIV, and there is some evidence that higher BMI is associated with
more robust CD4+ T-cell recovery in HAART-treated patients24. Li et
al demonstrated that HIV-infected patients with higher BMI at pre-treatment
exhibit better immune reconstitution overtime after HAART initiation25.
Also, patients with body weight <52.72 ± 7.21 kg were more prone to develop
OIs. This finding was similar to a study conducted by Inamdar et al14.
Opportunistic infections were significantly
higher in patients with poor adherence to ART (99.12%). This was similar to the
findings in the study conducted by Iroezindu et al10. Fonsah et al
conducted a study where subjects with CD4 cell counts <200 cells/µL had a
lower proportion of good adherence than subjects with CD4 cell counts =200
cells/µL26. Therefore, people with poor adherence have a low CD4
count that translates to an increased incidence of OIs. Poor adherence to ART
also causes progression of HIV, decreased CD4 count and hence can result in
more OIs as already discussed.
Significant association was seen between
hemoglobin (g/dL) and patients with OI with
mean ± SD of hemoglobin (g/dL) <9.87 ± 1.83 g/dL. This was similar to a study by Iroezindu et al10. Srikantia et al demonstrated that both the cell-mediated immune response and bactericidal capacity of leukocytes in children with
hemoglobin levels below 10 g/dL were significantly depressed.27
Significant
association was seen between protein, albumin and OIs. Studies in the past
decade have suggested that low albumin levels in HIV-infected patients are associated with rapid progression to AIDS and may
account for increased mortality. Studies have suggested baseline albumin levels
to be a good predictor of survival in patients with low CD4 count28-30.
This may be attributable to nutritional factors, enteropathy and acute phase
reactant proteins. Hence, the National AIDS Control Organization (NACO) in
India provides nutritional supplements to those HIV-infected cases inducted for
ART and nutritional counseling for others as a part of a national policy31.In developing countries where many people live below the poverty
line, serum albumin would be a useful surrogate test for predicting the
severity of HIV infection and the clinical monitoring of response to ART.
There were some limitations of the present
study. As a cross-sectional study, cause-effect relationships cannot be
assessed. Therefore, the data on the natural history pattern of disease and
survival of hospitalized patients with HIV/AIDS could not be established. The
study’s endpoint is restricted to the in-hospital period; hence, the full
access to patient’s follow-up clinical data after being discharged was not
always available.
The present study shows TB as the commonest OI
in overall population of PLHIVs in Haryana followed by candidiasis and herpes
zoster. Baseline CD4 cell count <200 cells/mm3, baseline WHO
clinical stages III and IV and ART nonadherence were strongly associated with
the prevalence of OIs. Lower income, education and socioeconomic status were
also associated with a higher prevalence of OIs. Weight, BMI, albumin,
hemoglobin level are strong predictors for the occurrence of OIs.
CONCLUSION
Presently, India
has the third-largest population of HIV-infected individuals after South Africa
and Nigeria. HIV patients are susceptible to a variety of OIs depending upon
clinical status, WHO grading and CD4 count. It is noteworthy that OIs can have
atypical presentations and multisystem involvement. Various factors like
adherence to ART, socioeconomic and education status of patients can influence
the occurrence and outcome of these deadly infections. Hence, there is a need
for surveillance and a high degree of suspicion of these infections in HIV
patients to ensure early diagnosis and intervention. Moreover, interventions
need to be designed to promote easy and early access to HIV testing and early
enrollment of HIV-infected individuals into ART services seeing that the use of
ART was found to reduce the prevalence of OIs by 4th month. Individuals who
continue to have low CD4 cell counts while on ART should be aggressively
evaluated for OIs and practical efforts to optimize their immunological recovery
should be made.
Conflict of Interest: Nil.
External Funding
Support: Nil.
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