India stands third with respect to HIV epidemic in the world. About 2.1 million people are estimated to be living with HIV in India. The number of deaths due to AIDS related illnesses in India was estimated to be around 62,000 people in the year 2016 [
Free antiretroviral therapy (ART) is being provided by National AIDS Control Organization (NACO) of India since 2004. With the introduction of Highly Active Antiretroviral Therapy (HAART), there has been a sizable reduction of HIV associated mortality in developing countries [
Mortality at an early stage has been reported among patients soon after initiation of ART which is unlikely to be related to drug efficacy [
Identification and rectification of these modifiable factors during routine clinical care might help in prolonging survival thereby preventing more deaths among PLHIV. This study therefore aims to identify prognostic factors influencing mortality among a cohort of HIV infected adult patients on ART.
This retrospective cohort study was conducted in May 2017 in a major tertiary care hospital affiliated to a medical college in the city of Mangalore of Karnataka state in southern India. The approval to do this study was obtained from the Institutional Ethics Committee. Then, the permission to do the study at the setting was taken from the medical superintendent of the respective hospital.
The secondary data of all confirmed patients of HIV started on ART over a seven year follow-up period from January 2010 till December 2016 was collected by the investigators. The information regarding sociodemographic details of the patients, age at diagnosis of HIV, age at starting ART, functional status of patients, substance usage, associated OIs, WHO clinical staging of the patient, haematological reports, height, weight of the patient, and health status of the spouse were noted down in a predesigned content validated pro forma. The number of follow-up visits to the treatment centre, type of ART regimen, adherence to treatment, chemoprophylaxis regimen, and outcome of management whether survived or died was also recorded. No personal identifier was stated on the data collection form.
The cohort constituted patients aged above 14 years and who underwent at least two visits to the treatment centre.
Transferred out patients and lost to follow-up patients whose outcome following treatment was not known were censored. Patients who did not return for follow-up visits for more than three consecutive months were considered as lost to follow-up [
Patients who had already started treatment with ART before the period of observation of this study and those aged below 15 years were excluded.
The most recent laboratory results before starting ART was used as a base line value. In patients where this information was unavailable, the results obtained within a month of ART initiation were recorded as baseline values [
Body mass Index (BMI) was categorized as per Asian classification. Adherence to ART more than 95% was considered good, between 85 and 94% as average and less than 85% as poor adherence with treatment [
The survival time was calculated in days between the date of treatment initiation and the date of the event (death) or date of censoring [
Data were entered and analyzed using
Descriptive statistics were used to describe the characteristics of the cohort. Person years of observation (PYO) and incidence rates were also calculated for various periods. The Kaplan-Meier curves were generated to estimate life time survival probability of patients.
Univariate analysis was done using Chi square test, unpaired t test, and Analysis of Variance. All the risk factors significant at 0.15 level qualified entry in the multivariable model and were excluded using a backward stepwise elimination procedure to identify the true predictors. Cox proportional hazard regression model was used to calculate the adjusted hazard rate and to determine independent prognostic factors of mortality among patients after initiation of ART. p ≤ 0.05 was considered statistically significant association.
Mean age of the 285 patients enrolled in this study was 45.8±9.7 years with age ranging from 18 years to 76 years (Table
Demographic and clinical characteristics of HIV patients.
Demographic characteristics | Number | Percentage |
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Age group (years) | ||
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18-25 | 6 | 2.1 |
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26-35 | 28 | 9.8 |
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36-45 | 111 | 39.0 |
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46-55 | 94 | 33.0 |
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56-65 | 40 | 14.0 |
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>65 | 6 | 2.1 |
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Gender | ||
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Male | 176 | 61.8 |
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Female | 109 | 38.2 |
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Marital status | ||
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Unmarried | 46 | 16.1 |
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Married | 177 | 62.1 |
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Divorced | 9 | 3.2 |
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Widow/ widower | 53 | 18.6 |
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Educational status (n=278) | ||
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Illiterate | 25 | 9.0 |
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Primary school | 129 | 46.4 |
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Secondary school | 81 | 29.1 |
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College and above | 43 | 15.5 |
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Occupation (n=269) | ||
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Unemployed | 87 | 32.3 |
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Unskilled | 54 | 20.1 |
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Semi-skilled | 70 | 26.0 |
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Skilled | 32 | 11.9 |
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Semi-professional | 7 | 2.6 |
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Professional | 19 | 7.1 |
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Monthly income (n=239) | Median INR 5000 (IQR 3000- 8000) | |
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Health condition of the spouse (n=203) | ||
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Healthy | 102 | 50.2 |
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Chronically ill | 61 | 30.1 |
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Died | 40 | 19.7 |
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Place | ||
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Urban | 243 | 85.3 |
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Rural | 42 | 14.7 |
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Clinical characteristics | Number | Percentage |
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Type of ART | ||
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First line | 266 | 93.3 |
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Second line | 19 | 6.7 |
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Mean age at diagnosis of HIV (years) | 41.1±10.3 | |
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Age at starting ART (years) | ||
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≤20 | 4 | 1.4 |
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21-30 | 20 | 7.0 |
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31-40 | 91 | 31.9 |
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41-50 | 112 | 39.3 |
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51-60 | 51 | 17.9 |
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>60 | 7 | 2.5 |
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Time between diagnosis and initiation of ART (days) | Median 55 (IQR 7 - 910) | |
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Duration of taking ART (days) | Mean 1127.0±611.8 | |
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Time between initiation of ART and death (days) (n=44) | Median 110 (IQR 25.2 - 780) | |
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Cotrimoxazole prophylaxis | ||
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Yes | 73 | 25.6 |
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No | 212 | 74.4 |
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Isoniazid prophylaxis | ||
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Yes | 43 | 15.1 |
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No | 242 | 84.9 |
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Adherence to ART | ||
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Good | 267 | 93.7 |
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Average | 14 | 4.9 |
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Poor | 4 | 1.4 |
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Side effects of ART | ||
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Present | 35 | 12.3 |
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Absent | 250 | 87.7 |
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Mean number of visits to ART centre | 30.4±16.5 | |
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Outcome of treatment | ||
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Survived | 241 | 84.6 |
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Died | 44 | 15.4 |
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Total | 285 | 100.0 |
Median BMI (Kg per sq.mtrs) of patients was 20.1(IQR 17.7-22.9) before the start of ART (n=257), 20.7(IQR 18.4-23.6) after 6 months (n=249), 21.2(IQR 18.6-23.7) after 12 months (n=242), 21.1(IQR 18.6-23.1) after 24 months (n=178), 21.3(IQR 18.2-23.5) after 36 months (n=124), 21.4(IQR 18.3-23.2) after 48 months (n=105), and 21.5(IQR 18.2-23.6) after 60 months (n=67) of starting ART.
Around 3% and 7% increase of BMI from baseline median level was observed after 6 months and 60 months of ART, respectively.
Median CD4 count (cells per cu.mm) of patients was 364(IQR 201-498.5) before the start of ART (n=285), 410(IQR 314-574.5) after 6 months (n=254), 494(IQR 355-656.5) after 12 months (n=241), 562(IQR 401-728) after 24 months (n=175), 584.5(IQR 432-770) after 36 months (n=130), 575.5(IQR 418-754.5) after 48 months (n=106), and 563.5(IQR 450-722.5) after 60 months (n=62) of starting ART. The CD4 count before the start of ART was <200 cells per cu.mm of blood in 71(24.9%) patients.
13.6% and 59.4% increase of CD4 count from baseline median level were observed after 6 months and 48 months of ART, respectively.
The median CD4 count of patients (cells per cu.mm) at the time of death (n=44) was 210(IQR 128-375.5).
During the follow-up period, CD4 count remained the same or was less than the baseline values among 67(23.5%) patients, yielding an immunologic treatment failure rate of 41.5/100 person years of observation (PYO).
Death was reported among 6(85.7%) patients with CD4 count less than 100 cells per cu.mm of blood in comparison to 38(13.7%) patients with CD4 count ≥100 cells per cu.mm of blood (X2=27.1, p<0.001).
Mean haemoglobin values (gms per dl) before start of ART were 12.1±2.4 among patients.
Mean age of patients at the start of ART was 42.9±9.6 years (Table
Good adherence with ART was seen among 238(95.2%) patients without any side effects with ART compared to 29(82.9%) among those with side effects (X2=7.9, p=0.005).
Extra-pulmonary and pulmonary tuberculosis were the most common OI before and after starting ART, respectively (Table
Distribution of various characteristics before and after start of antiretroviral therapy (ART) among patients.
Characteristics before starting ART | Characteristics after starting ART | ||||
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Number | Percentage | Number | Percentage | ||
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Functional status (n=285) | Functional status (n=240) | ||||
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Ambulatory | 51 | 17.9 | Ambulatory | 1 | 0.4 |
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Bedridden | 6 | 2.1 | Bedridden | 1 | 0.4 |
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Working | 228 | 80.0 | Working | 238 | 99.2 |
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Pattern of substance usage (n=285) | Pattern of substance usage (n=285) | ||||
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Tobacco chewing | 13 | 4.6 | Tobacco chewing | 14 | 4.9 |
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Smoking | 32 | 11.2 | Smoking | 15 | 5.3 |
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Alcohol consumption | 62 | 21.7 | Alcohol consumption | 22 | 7.7 |
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Opportunistic infections present (n=285) | Opportunistic infections present (n=285) | ||||
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Extra pulmonary tuberculosis | 34 | 11.9 | Pulmonary tuberculosis | 15 | 5.3 |
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Pulmonary tuberculosis | 28 | 9.8 | Extra pulmonary tuberculosis | 9 | 3.2 |
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Candidiasis | 5 | 1.7 | Cytomegalovirus infection | 2 | 0.7 |
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Pneumocystis jiroveci pneumonia | 4 | 1.4 | Toxoplasmosis | 2 | 0.7 |
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Cryptococcal infections | 2 | 0.7 | Others | 2 | 0.7 |
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Toxoplasmosis | 2 | 0.7 | |||
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Others | 3 | 1.0 | |||
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BMI (Kg per sq.mtrs) of patients before starting ART (n=257) | BMI of patients after 60 months of starting ART (n=67) | ||||
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Under weight | 87 | 33.9 | Under weight | 19 | 28.4 |
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Normal weight | 112 | 43.6 | Normal weight | 23 | 34.3 |
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Over weight | 25 | 9.7 | Over weight | 16 | 23.9 |
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Obese | 33 | 12.8 | Obese | 9 | 13.4 |
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Clinical staging of HIV patients before starting ART (n=285) | Clinical staging of HIV patients after 60 months of starting ART (n=90) | ||||
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Stage 1 | 172 | 60.3 | Stage 1 | 75 | 83.3 |
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Stage 2 | 18 | 6.3 | Stage 2 | 6 | 6.7 |
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Stage 3 | 27 | 9.5 | Stage 3 | 5 | 5.6 |
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Stage 4 | 68 | 23.9 | Stage 4 | 4 | 4.4 |
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Mean CD4 count (cells/cu.mm) before starting ART (n=285) | 381.4±235.9 | Mean CD4 count (cells/cu.mm) after 60 months of starting ART (n=62) | 596±216.7 |
Cause of death was known in 13 patients. It is comprised of cardiac causes in 3, pneumonia in 6, and tuberculosis, and encephalitis in 2 patients each.
Majority of deaths, i.e., 21(47.7%), occurred within three months of starting ART. The proportion of patients who died was 7.4%, 1.1%, 1.1%, 1.9%, 2.4%, and 2.4% at <3 months, 3-6 months, 6 months to 1 year, 1-2 years, 2-3 years, and ≥3 years of treatment with ART, respectively. In terms of person years it was 3.2, 0.4, 0.2, 0.1, 0.1, and 0.1, respectively, during these periods of treatment with ART.
During the follow-up period, a total of 44/285(15.4%) patients died. The proportion of patients who died was 4.9%, 1.5%, 1.1%, 2.3%, 1.2%, 0%, and 5.5% at <3 months, 3-6 months, 6 months to 1 year, 1-2 years, 2-3 years, 3-4 years, and ≥4 years, respectively, following the diagnosis.
The death rate was 44 deaths/880.79 person years of treatment X 100 = 4.99 per 100 person years of treatment with ART. The death rate was 44/1407.8 person years since diagnosis X 100 = 3.12 per 100 person years.
The time between diagnosis of HIV and death was ≤100 days in 14(31.8%), 101 days to 1 year 8(18.2%), 1 year to 5 years in 12(27.3%), and more than 5 years in 10(22.7%) patients.
Out of the 44 deaths reported, the most recent CD4 count (cells per cu.mm) before death was <100, 100-199, 200-299, 300-399, 400-499, and ≥500 in 6(13.6%), 15(34.1%), 8(18.2%), 6(13.6%), 3(6.9%), and 6(13.6%), respectively.
The median duration of taking ART among the patients who died (n=44) was 110 (IQR 25.2-780) days.
The mean duration of taking ART (days) was 36.5, 335.3, 392.9, 490.2, 550, and 1207.5 among patients whose most recent CD4 count (cells per cu.mm) before death was <100, 100-199, 200-299, 300-399, 400-499, and ≥500, respectively (F=3.345, p=0.013).
Therefore patients who died with a low CD4 count were on ART for a much shorter time than those who died with a higher CD4 count. This implies that deaths at low CD4 count were caused by patients starting ART, too late to benefit.
The median survival time among the patients who died (n=44) was 380.5 (IQR 44-1756.2) days.
The mean survival time (days) following diagnosis with HIV was 401, 584.7, 1235.2, 757.8, 2719, and 1606.2 among patients whose most recent CD4 count (cells per cu.mm) before death was <100, 100-199, 200-299, 300-399, 400-499, and ≥500, respectively (F=2.494, p=0.048).
The mean survival time (days) following diagnosis with HIV was 1401±1393.8 days (or 46.7 months) and median survival time was 790 days (IQR 148-2667) for patients whose most recent CD4 count before death was ≥200 cells per cu.mm.
Univariate analysis found those patients whose baseline functional status was nonworking (p<0.001), those who were tobacco users before starting ART (p=0.019), those who were alcoholics before (p=0.003) and after (p=0.001) starting ART, those with OIs and tuberculosis before (p<0.001) and after starting ART (p<0.001), patients who were in WHO Clinical Stage 4 of HIV disease before initiation of ART (p<0.001), those who had ≤15 visits to treatment centre (p<0.001), those who took ART for ≤2 years (p<0.001), those whose adherence to ART was either average or poor (p=0.03), and patients from urban areas (p<0.001) were significantly associated with mortality status. There was no association between age (p=0.602), gender (p=0.537), marital status (p=0.287), educational status (p=0.598), occupation (p=0.06), history of smoking before starting ART (p=0.582), tobacco chewing after starting ART (p=0.903), smoking after starting ART (p=0.817), health status of the spouse (p=0.125), clinical staging of HIV at different intervals during the observation period after starting ART (p= ns), type of ART (p=0.54), age at starting ART (p=0.627), monthly income (p=0.588), BMI (p=0.624), and time since diagnosis to start of ART (p=0.133) with mortality status among patients in this study.
Mean CD4 count (cells per cu.mm) before the start of ART among patients who survived (n=241) was 402.5±235.3 in comparison to 266±206.1 among those who died (n=44). This difference in the mean CD4 counts was significant using unpaired t test, t=3.602, p<0.001.
There was no significant difference in the mean values of base line total leucocyte count (p=0.7) and base line haemoglobin levels (p=0.454) between patients who survived and died.
To calculate unadjusted hazard ratio, WHO clinical stage 1 of HIV was taken as reference value. Cox’s regression was applied to the mortality data using variables significantly associated with it and the output is presented as Table
Multivariable Cox regression analysis of prognostic factors of mortality among HIV patients after starting ART (n=285).
Characteristics | Unadjusted HR | 95% CI of unadjusted HR | P value | Adjusted HR | 95% CI of Adjusted HR | P value | ||
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Lower | Upper | Lower | Upper | |||||
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Presence of opportunistic infections before starting ART | 3.504 | 1.691 | 7.26 | <0.001 | 2.251 | 1.047 | 4.839 | 0.038 |
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Presence of tuberculosis before starting ART | 6.872 | 3.31 | 14.266 | <0.001 | 2.22 | 1.074 | 4.592 | 0.031 |
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Functional status at baseline | 4.06 | 2.037 | 8.093 | <0.001 | 0.644 | 0.442 | 0.936 | 0.021 |
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WHO clinical staging of HIV at baseline | 4.624 | 2.295 | 9.314 | <0.001 | 1.266 | 0.965 | 1.66 | 0.089 |
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Unsatisfactory adherence to treatment | 3.013 | 1.067 | 8.511 | 0.03 | 2.564 | 1.001 | 6.571 | 0.05 |
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History of alcohol usage after starting ART | 4.51 | 1.795 | 11.332 | 0.001 | 1.348 | 1.02 | 1.781 | 0.036 |
A patient with any OI before the start of treatment was 2.251 times more likely to die in comparison to patient without any OIs. Similarly, patients with tuberculosis before starting treatment, unsatisfactory (poor/average) adherence to ART, and those with history of alcohol usage during treatment were at 2.22, 2.564 and 1.348 times, respectively, at greater risk of dying when compared with the rest. The confidence interval of these observation does not contain 1, indicating statistical significance (Table
The cumulative proportion surviving was plotted against the survival times. This resulted in a stepped survival curve presented as Figure
Kaplan-Meier survival curves illustrating cumulative survival probability of people living with HIV after initiation of ART (n=285).
The mean survival time for patients after detection of HIV in this study was 5583.5±249.3 days (95% CI is 5094.8-6072.2).
The hazard function h(t) which is the conditional probability of dying at time t is shown in Figure
Cumulative hazard function of people living with HIV after starting ART (n=285).
This study was done to identify the prognostic factors influencing mortality among a cohort of HIV infected adult patients on ART. It was observed that the presence of OIs and tuberculosis before and poor/average adherence to ART and alcohol usage after starting ART were independent prognostic factors of mortality among these patients.
The incidence density of death rate in this study was 3.12 per 100 PYO compared to other studies, where it was 1.75 [
The proportion of patients who died in this study was 15.4% in comparison to two other studies done in Ethiopia, where it was reported as 9.4% [
This study observed that the mean survival time was 46.7 months, among patients with the most recent CD4 count before death, as ≥200 cells per cu.mm. This was more than 44.2 months reported in a study done in Hyderabad, India [
Majority of deaths in this study occurred within 3 months of starting ART, as also observed in previous studies [
In this study, good adherence to ART was reported in 93.7% patients in comparison to 27.4% [
In a study done in Ethiopia, an 8 percentage gain in weight was observed in the first 6 months of treatment [
Progressive change in CD4 count after initiation of ART was noticed in this study. However the increase in median CD4 count level from baseline values over the first 6 months of ART was lesser compared to 76.2% reported in an Ethiopian study [
Multivariable analysis in the present study showed that the presence of OIs, including tuberculosis before starting ART, to be associated with greater risk of mortality. Therefore, early identification of OIs will be helpful in identifying patients who need more intense follow-up for treatment of specific OI.
Similarly, the presence of tuberculosis infection as an independent prognostic factor of mortality was reported by previous studies [
Another important independent prognostic factor of mortality observed in this study was poor/average pattern of adherence to ART, which was also supported by other studies [
Further, history of usage of alcohol after starting ART was also an important prognostic factor of mortality. This was probably because it causes poor adherence with treatment. Another Ethiopian study too observed that patients reporting substance usage, with significant independent risk of mortality [
Previous studies using Cox regression analysis identified male gender [
The proportion of deaths was minimal 4 years after diagnosis of HIV in this study when compared with previous studies. Similarly, the survival probability of patients was better than that reported in other settings, probably due to acceptable level of adherence to treatment and good number of follow-up visits by the patients. The CD4 count and BMI were found to increase among them, as soon as 6 months of treatment. However, majority of deaths were reported within 3 months of starting ART. This could be due to delayed diagnosis of HIV and associated OIs. Added to this, side effects of ART need to be attended to during follow-up visits. Therefore intensive monitoring of HIV patients on ART with various factors identified in multivariable analysis such as presence of OIs before the start of treatment and counselling for the alcoholics and those with poor/average adherence to treatment (probably due to drug side effects) is a must for prolonging the survival of the HIV affected patients in this settings.
This study highlights the mortality statistics among PLHIV and the factors influencing it in an urban tertiary care setting of coastal India. It was observed that clinical and simple laboratory data available to health care providers can predict patients on treatment who are at higher risk of mortality. Screening efforts need to be intensified for early detection and management of OIs among HIV infected patients both before and after the start of ART. Other measures like good counselling and periodic monitoring would improve adherence and might also prevent alcohol consumption after treatment with ART. Monitoring and frequency of visits need to be more frequent in the first 3 months of starting ART, during which the proportion of deaths was found to be the most. These measures would help a long way in reducing mortality among PLHIV in the setting.
This being a record based study has the limitation of availability of information, as stated in the records. There is also a possibility of deaths in this study which may have occurred due to causes not directly related to HIV/AIDS. The retrospective study design which limits analysis of the role of social and psychological factors and a single centric study which limits generalizability of information are other shortcomings of this research study.
The data used to support the findings of this study are available from the corresponding author upon request.
This was a students’ research project conducted during their research postings in the Department of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education, Mangalore, India. It was a self-funded study. The investigators of this study did not receive any financial support from the employers. Further no funder was involved in the manuscript writing, editing, approval, or decision to publish this research work.
The authors declare that they have no conflicts of interest.
Nitin Joseph is guarantor of this research work, concept, design, literature search, tool preparation, and manuscript preparation. Ushasti Sinha contributed to data collection, data analysis, statistical analysis, and interpretation of data. Nishtha Tiwari contributed to data collection, data entry, literature search, manuscript preparation, and manuscript editing. Pritha Ghosh contributed to data collection, data entry, and manuscript editing. Patneedi Sindhu contributed to data collection and manuscript editing. All authors approved the final manuscript before submission.
The authors thank the medical superintendent of Kasturba Medical College Hospital, Attavar, Mangalore, and Dr. John T Ramapuram, Professor and HOD in Internal Medicine at Kasturba Medical College Hospital, Attavar, Mangalore, for their cooperation and help in the conduct of this study. We also thank Karnataka State AIDS Prevention Society, Bangalore, Government of India, for their guidance in this research work. Finally we wish to acknowledge the support provided by the Department of Community Medicine, Kasturba Medical College, Mangalore, and Manipal Academy of Higher Education, Manipal for encouraging research and its publication in international journals of repute.