Effects of Gender and Baseline CD4 Count on Post-Treatment CD4 Count Recovery and Outcomes in Patients with Advanced HIV Disease: A Retrospective Cohort Study

Abstract

Presentation to care with advanced HIV disease (AHD) is a significant problem in sub-Saharan Africa. We evaluated factors associated with immune recovery among individuals presenting to care with AHD in Zimbabwe. We conducted a retrospective evaluation of outcomes among adult (>18 years old) individuals with AHD (CD4 count ≤200 cells/mm³) receiving care at 18 outpatient primary care clinics in Harare, Zimbabwe. Baseline and 12-month CD4 count data were extracted from medical records. CD4 count recovery (defined as CD4 count >200 cells/mm³) after 12 months on non-nucleotide reverse transcriptase inhibitor (NNRTI)-based antiretroviral therapy (ART) regimen was determined and factors associated with CD4 count recovery were established using logistic regression. All statistical analysis was performed on SPSS v23. A total of 1,338 participant records were included in the analysis. The median interquartile range (IQR) age was 37 (30-43) years and 52% were females. The baseline median (IQR) CD4 count was 50 (28–75) cells/mm³ and was significantly lower among patients with history of cryptococcal meningitis compared to those without [25 (10–52) vs. 52 (32–77), respectively; p = .0009]. The median (IQR) CD4 count at 12 months after ART initiation increased from 50 (28–75) at baseline to 180 (92–290) cells/mm³. Immune recovery with a CD4 count >200 cells/mm³ was observed in 181/417 (43%). Male gender and low baseline CD4 count were strong predictors of poor immunological recovery on ART. Immunological recovery following ART initiation was 43% among individuals with AHD. Male patients are most vulnerable to persistent immunological failure.

Clinical Trial Registration number: NCT02434172.

Introduction

Despite the widespread availability of antiretroviral therapy (ART) in sub-Saharan Africa (SSA), up to half of people living with HIV (PLHIV) are still presenting to ART program with advanced HIV disease (AHD) defined as CD4 count ≤200 cells/mm³ or World Health Organization (WHO) clinical stage 3 or 4 disease for adults initiating on ART.¹ WHO clinical stage 3 encompasses a set of clinical manifestations that include weight loss of >10% of total body weight, prolonged unexplained diarrhea (>1 month), pulmonary tuberculosis (TB), and severe systemic bacterial infections. While stage 4 includes all of the AIDS-defining illnesses such as pneumocystis pneumonia, cryptococcal meningitis (CM) or other extra pulmonary, kaposi sarcoma, and chronic herpes simplex virus infection.

Many factors, including delay in HIV diagnosis and ART commencement, treatment failure, and disengagement from ART program, contribute to late presentation with AHD. Capacity for CD4 count recovery is reduced in individuals with AHD and opportunistic infections such as CM and TB remain the top two leading causes of morbidity and mortality.^2,3

Various factors influence the immune recovery following initiation of ART. These include CD4 count at the time of ART initiation, age, gender, and the ART regimen.^4
–6 Few studies have focused the analysis on CD4 count recovery in individuals with AHD that are receiving care in routine public health clinics in SSA. We sought to estimate the factors associated with CD4 count recovery among adults with AHD initiating ART before availability of integrase inhibitors and in very low resourced outpatient clinics in Harare, Zimbabwe.

Materials and Methods

Study design, setting, and population

The National ART program in Zimbabwe was initiated in April 2004 at specialist centers with subsequent decentralization to outpatient community-based clinics. In 2013, the criteria for ART initiation was a CD4 count ≤500 cells/mm³. Between January 26, 2013, and February 16, 2016, we conducted a retrospective analysis of outcomes (survival and retention to care) among individuals with AHD (CD4 count ≤200 cells/mm³) who enrolled into care at 18 outpatient clinics in Harare, Zimbabwe, between April 16, 2010 and October 2, 2015. Adults (>18 years old) with a documented HIV-positive test and a CD4 count ≤200 cells/mm³ and a medical chart at the clinic were included in the analysis. Participants could be ART naive or ART experienced and could be on any nationally approved ART regimens.

The National treatment regimens for adults and adolescents largely consisted of zidovudine (AZT), tenofovir disoproxil fumarate (TDF), and lamivudine (3TC) as the primary nucleotide reverse transcriptase inhibitors (NRTIs); with either efavirenz (EFV) or nevirapine (NVP) as the non-NRTIs (NNRTIs) in the first line treatment regimens. Stavudine (d4T)-based regimens were being phased out at the time of the study. The preferred second line ART regimens consisted of AZT/3TC/ritonavir-boosted atazanavir (ATV/r) or ritonavir-boosted lopinavir (LPV/r) if TDF was used in first line ART or TDF/3TC/ATV/r or LPV/r if AZT was used in first line ART.⁷ The study data were collected by chart review.

Treatment guidelines recommended CD4 count testing at 6-month intervals. CD4 count testing was often centralized with inconsistent reporting of results back to the clinic. Lack of completion or lack of availability of reported CD4 count results was common at that time. Viral load testing was not part of routine care at that time.

Data collection

A specific case reporting from a study was developed for data extraction. Data extraction was done by two independent extractors and entered into the electronic database. Any discrepancies were resolved by the data manager before finalization of the entry. The key variables extracted for analysis included sociodemographic data (age, sex, level of education, marital and employment status) and clinical data (WHO clinical stage, CD4 count, presence of key opportunistic infections, including TB and CM, ART initiation date, ART regimens, date of last visit, and clinical outcome at 6 and 12 months). Routine viral load was not available at that time, instead baseline CD4 count and follow-up CD4 count were collected.

Data analysis

Statistical analyses were performed on SPSS v23. Descriptive statistics were used to summarize the baseline demographic and clinical characteristics and were presented as frequencies and percentages for categorical data and medians interquartile range (IQR) for continuous data. Kruskal–Wallis test was used to compare median CD4 counts at baseline and 12 months after ART initiation. McNemar's test was used to compare the proportion of patients with CD4 counts ≤200 cells/mm³ at baseline and 12 months. Bivariate and multivariate Cox regression analyses were carried out to assess whether key variables were independently and jointly associated with the risk of attrition from care and treatment. The independent variables considered were gender, age, TB history, CM history, WHO clinical stage, and baseline CD4 count.

Ethical approval

The study was reviewed and approved by the local Institutional Review Board of the Joint Research and Ethics Committee of the University of Zimbabwe and the Parirenyatwa Group of Hospitals (JREC/01/13), the Medical Research Council of Zimbabwe (MRCZ/A1767) and the Research Council of Zimbabwe.

Results

Baseline participants characteristic

A total of 1,480 individuals were enrolled (Fig. 1) at the study clinics between April 16, 2010, and October 2, 2015, with a CD4 count ≤200 cells/mm³. Among the charts reviewed, 1,338 (90%) met the inclusion criteria for the study. The median (IQR) age was 37 (30–43) years. Slightly above half (52%) were females and WHO stages 3 and 4 were reported in 59%. Median age of males was significantly older than females [38 (IQR 33–44) vs. 34 (IQR:28–41), respectively, p < .00001]. More males were married compared with females (73% vs. 47.9%, respectively, p < .00001) and a higher proportion of females were widowed compared to males (23.7% vs. 5.5%, respectively, p < .00001). There were also significant gender differences in employment and education status (Table 1).

FIG. 1.

Consort diagram of the study.

Table 1.

Baseline Characteristics of the Participants

Characteristics	All, N (%)	Male, N (%)	Female, N (%)	p
Median (IQR) age in years (N = 1,336)	37 (30–43)	38 (33–44)	34 (28–41)	<.00001
<40	845 (63.5)	364 (56.4)	481 (70.1)	<.00001
≥40	486 (36.5)	281 (43.6)	205 (29.9)	<.00001
Marital status (N = 1,313)
Single	155 (11.8)	67 (10.6)	88 (13.0)	.171
Married	788 (60.0)	463 (73.0)	325 (47.9)	<.00001
Separated/Divorced	174 (13.3)	69 (10.9)	105 (15.5)	.013
Widowed	196 (14.9)	35 (5.5)	161 (23.7)	<.00001
Employment (N = 957)
Employed/Self and Part-time	608 (63.5)	377 (79.2)	231 (48.0)	<.00001
Unemployed	325 (34.0)	89 (18.7)	236 (49.1)	<.00001
Not stated	24 (2.5)	10 (2.1)	14 (2.9)	.582
Education (N = 1,102)
None	31 (2.7)	16 (2.8)	15 (2.6)	.834
Primary	154 (13.3)	52 (9.0)	102 (17.6)	<.00001
Secondary	805 (69.6)	405 (70.4)	400 (68.8)	.555
University	19 (1.6)	11 (1.9)	8 (1.4)	.503
Skilled job training	90 (7.8)	65 (11.3)	25 (4.3)	<.00001
Not indicated	57 (4.9)	26 (4.5)	31 (5.3)	.529
WHO Clinical Stage (N = 1,333)
WHO Stage 1 + 2	475 (35.6)	211 (32.7)	264 (38.4)	.032
WHO stage 3 + 4	781 (58.6)	396 (61.4)	385 (56.0)	.032
WHO stage not indicated	77 (5.8)	38 (5.9)	39 (5.7)	.881
History of opportunistic infections
History of tuberculosis (N = 1,090)	262 (24.0)	152 (28.9)	110 (19.5)	<.001
History of cryptococcal meningitis (N = 989)	23 (2.3)	15 (3.1)	8 (1.6)	.119
CD4 count, cells/mm³
Baseline median (IQR) CD4 count (N = 1,338)	50 (28–75)	50 (28–75)	50 (29.25–75)	.856
Initial ART regimen
Abacavir/Didanosine/Atazanavir/Rinonavir	1 (0.1)	0	1 (0.2)	.267
Tenofovir/Lamivudine/Atazanavir/Rinonavir	2 (0.2)	1 (0.2)	1 (0.2)	1
Abacavir/Lamivudine/Atazanavir/Rinonavir	1 (0.1)	1 (0.2)	0	.250
d4T/Lamivudine/NVP	416 (32.6)	194 (31.8)	222 (33.3)	.569
Tenofovir/Lamivudine/NVP	440 (34.5)	186 (30.5)	254 (38.2)	.004
d4T/Lamivudine/EFV	14 (1.1)	8 (1.3)	6 (0.9)	.490
Tenofovir/Lamivudine or Emtricitabine/EFV	379 (29.7)	204 (33.4)	175 (26.3)	.006
Zidovudine/Lamivudine/NVP	11 (0.9)	7 (1.1)	4 (0.6)	.327
Zidovudine/Lamivudine/EFV	9 (0.7)	8 (1.3)	1 (0.2)	.021
Abacavir/Lamivudine/EFV	1 (0.1)	1 (0.2)	0	.242
Duration on ART in months
12 to <24	577 (73.1)	269 (73.9)	308 (72.5)	.660
24 to <36	208 (26.4)	94 (25.8)	114 (26.8)	.749
≥36	4 (0.5)	1 (0.3)	3 (0.7)	.435

Bold text represents statistically significant values p < 0.05.

ART, antiretroviral therapy; d4T, stavudine; EFV, efavirenz; IQR, interquartile range; NVP, nevirapine; WHO, World Health Organization.

Advanced clinical disease defined by WHO stage 3 or 4 disease was more common in males than females (61.4% vs. 56%, respectively, p = .032). A history of TB was documented for 262 (24%) individuals and CM in 23 (2.3%). More males had a history of TB at the time of enrollment into care compared to females (28.9% vs. 19.5%, respectively, p < .001). The baseline median (IQR) CD4 count was 50 (28–75) cells/mm³ and was the same in males and females.

Baseline CD4 count was significantly lower among individuals with a history of CM compared to those without [25 (10–52) vs. 52 (32–77), respectively; p = .0009]. Individuals with a history of TB had a lower baseline median (IQR) CD4 count compared to those without [48 (27–69.5) vs. 53.5 (32–77), respectively, p = .001]. ART was initiated in 1,275 (95.3%). Of these 1,275 individuals, 416 (32.6%) were initiated on d4T/3TC/NVP, 440 (34.5%) were initiated on TDF/3TC/NVP, and 379 (29.7%) were initiated on TDF/3TC/EFV. A NVP-based regimen was initiated in 866 (67.9%).

More women were initiated on a NVP-based regimen than men (69.6% vs. 60%, respectively, p < .001) while men more frequently were initiated on an EFV-based regimen compared to women (34.1% vs. 26.3%, respectively, p = .002). Four participants were on second line therapy with a boosted protease inhibitor-based regimen (ATV/r). The duration on ART was <24 months for 577 (73.1%) individuals.

Outcomes of the participants at follow-up

The median (IQR) time of follow-up in the clinic was 12 (8–17) months. At follow-up, 981 (73%) individuals were still engaged into care, 750 (56%) remained at the clinic, and 231 (17%) were reported as having transferred out of the clinic. Among the study cohort, 313 (23%) were loss to follow-up and 44 (3%) were known to have deceased (Table 2). Retention in care (54.3% and 58%), loss to follow-up (25.6% and 21.2%), transfer out (15.5% and 17.2%), and death (3.7% and 2.8%) rates were similar between males and females, respectively. Follow-up CD4 counts were available for 417 (31%) individuals [181 (28.1%) men and 236 (34.3%) women, respectively, p = .015].

Table 2.

Outcomes of the Participants at Follow-Up

Characteristics	All, N (%)	Male, N (%)	Female, N (%)	p
Age in years, median (IQR)	37 (31–44)	40 (34–46)	34 (29–41)	<.00001
<40	253 (61.0)	86 (47.5)	167 (71.4)	<.00001
≥40	12 (39.0)	95 (52.5)	67 (28.6)	<.00001
Marital status (N = 415)
Single	50 (12.0)	18 (9.9)	32 (13.6)	.250
Married	232 (55.6)	128 (70.7)	104 (44.1)	<.00001
Separated/Divorced	66 (15.8)	24 (13.3)	42 (17.8)	.215
Widowed	66 (15.8)	11 (6.1)	55 (23.3)	<.00001
Employment (N = 304)
Employed/Self and Part-time	194 (63.8)	111 (84.7)	83 (48.0)	<.00001
Unemployed	104 (34.2)	18 (13.7)	86 (49.7)	<.00001
Not stated	6 (2.0)	2 (1.5)	4 (2.3)	.617
Education (N = 358)
None	9 (2.5)	6 (3.7)	3 (1.5)	.184
Primary	45 (12.6)	13 (8.1)	32 (16.2)	.021
Secondary	245 (68.4)	113 (70.2)	132 (67.0)	.052
University	9 (2.5)	5 (3.1)	4 (2.0)	.509
Skilled job training	23 (6.4)	16 (9.9)	7 (3.6)	.016
Not indicated	27 (7.5)	8 (5.0)	19 (9.6)	.101
WHO clinical stage (N = 1,333)
WHO Stage 1 + 2	167 (41.1)	71 (39.7)	96 (42.3)	.596
WHO stage 3 + 4	239 (58.9)	108 (60.3)	131 (57.7)	.596
WHO stage not indicated
History of opportunistic infections
History of tuberculosis (N = 368)	78 (21.2)	42 (26.1)	36 (17.4)	.424
History of cryptococcal meningitis (N = 337)	11 (3.3)	6 (4.0)	5 (2.7)	.503
Follow-up CD4 count ranges (N = 417)
No. with follow-up CD4 count	417 (31.3)	181 (28.1)	236 (34.3)	.015
<25	91 (21.8)	43 (23.8)	48 (20.3)	.390
25–49	112 (26.9)	47 (26.0)	65 (27.5)	.728
50–100	214 (51.3)	91 (50.3)	123 (52.1)	.719
Outcome categories (N = 417)
Deceased	14 (3.4)	10 (5.5)	4 (1.7)	.032
Loss to follow-up	37 (8.9)	15 (8.3)	22 (9.3)	.719
Still in care	337 (80.8)	144 (79.6)	193 (81.8)	.569
Transferred	25 (6.0)	10 (5.5)	15 (6.4)	.704
Unknown	4 (1.0)	2 (1.1)	2 (0.8)	.750
New/Switched Regimen (N = 404)
NVP-based regimens	109 (27.0)	42 (24.0)	67 (30.6)	.144
EFV-based regimens	261 (64.6)	117 (66.9)	144 (65.8)	.818
PI-based regimens	34 (8.4)	16 (9.1)	18 (8.2)	.749
Other	2 (0.7)	1 (0.6)	1 (0.4)	.772
Reasons for switching (N = 239)
Treatment failure	27 (6.5)	13 (7.2)	14 (5.9)	.596
Stock-outs	54 (12.9)	19 (10.5)	35 (14.8)	.201
Drug toxicity	19 (4.6)	6 (3.3)	13 (5.5)	.294
Change in National ART regimen	111 (26.6)	46 (25.4)	65 (27.5)	.638
Other	22 (5.3)	14 (7.7)	8 (3.4)	.055
Unknown	6 (1.4)	3 (1.7)	3 (1.3)	.741
Follow-up CD4, cells/mm³ (N = 417)
0–100	115 (27.6)	58 (32.0)	57 (24.2)	.077
101–200	121 (29.0)	63 (34.8)	58 (24.6)	.023
201–300	82 (19.7)	30 (16.6)	52 (22.0)	.168
301–400	44 (10.6)	16 (8.8)	28 (11.9)	.308
401–500	31 (7.4)	10 (5.5)	21 (8.9)	.190
500+	24 (5.8)	4 (2.2)	20 (8.5)	.006

Bold text represents statistically significant values p < 0.05.

PI, protease inhibitor.

The median (IQR) CD4 count after a median follow-up time of 12 months from ART initiation increased from 50 (28–75) at baseline to 180 (92–290) cells/mm³. Immune recovery with a CD4 count >200 cells/mm³ was observed in 181 (43%) participants who had a repeat CD4 count test available. Persistent low CD4 count ≤200 cells/mm³ was observed in 236 (57%) and severe immunosuppression (CD4 count ≤100 cells/mm³) in 115 (27.6%) participants. Women had a higher median (IQR) CD4 count increase from 50 (29–75) at baseline to 152 (60–269) after a median time of 12 months compared to men [from 50 (28–75) at baseline to 100 (19–188), p < .0001].

Most of the participants, 255 (61.2%), switched to a new regimen of TDF/3TC/EFV largely due to changes in the National treatment regimen, while 34 (8.4%) switched to a protease inhibitor (PI)-based regimen.

Factors associated with CD4 count recovery (CD4 count >200 cells/mm³)

The single most important determining factor for CD4 count recovery in individuals with severe AHD was gender. Women were twice as likely as men to achieve CD4 count recovery >200 cells/mm³ after a median follow-up time of 12 months compared with men (odds ratio = 1.9, 95% confidence interval: 1.218–2.964 p = .005). Having a baseline CD4 count ≥50 cells/mm³ and being employed were also associated with better immune response (p < .05) (Table 3).

Table 3.

Factors Associated with CD4 Recovery (CD4 > 200 cells/mm³)

Variable	Univariate				Multivariate
Variable	Proportion	OR	95% CI	p	Proportion	95% CI	p
Age (n = 403)
<40	0.29	1			1
≥40	0.30	1.05	0.68–1.62	.832	0.88	0.41–1.89	.746
Gender (n = 404)
Male	0.23	1			1
Female	0.36	1.9	1.22–2.96	.005	3.09	1.30–7.35	.011
Marital status (n = 403)
Married	0.30	1			1
Not married (Widowed, Separated/Divorced)	0.30	0.98	0.64–1.50	.923	1.28	0.59–2.80	.536
Employment (n = 295)
Employed/Self and Part-time	0.30	1			1
Unemployed/Unknown	0.26	0.80	0.47–1.37	.417	2.55	1.05–6.19	.039
Education (n = 321)
None+primary	0.31	1			1
Secondary	0.31	0.90	0.45–1.80	.76	2.09	0.76–5.73	.153
Tertiary+skilled job training	0.26	0.70	0.25–1.95	.489	2.04	0.48–8.76	.336
WHO Clinical Stage (n = 394)
WHO Stage 1 + 2	0.33	1			1
WHO stage 3 + 4	0.28	0.80	0.52–1.24	.32	0.78	0.35–1.73	.542
History of tuberculosis (n = 357)
No	0.31	1			1
Yes	0.23	0.65	0.36–1.18	.157	0.88	0.34–2.26	.792
History of cryptococcal meningitis (n = 328)
No	0.32	1			1
Yes	0.27	0.81	0.21–3.13	.764	3.56	0.25–51.25	.351
CD4 count ranges (n = 405)
<25	0.26	1			1
25–49	0.23	0.85	0.44–1.64	.629	1.10	0.38–3.23	.863
50–100	0.35	1.52	0.87–2.64	.140	3.12	1.15–8.42	.025
ART regimen analysis based on NRTI (n = 400)
d4T-based regimens	0.38	1			1
TDF-based regimens	0.26	0.56	0.36–0.88	.011	0.53	0.21–1.32	.174
Other	0.17	0.32	0.07–1.53	.155	0		1
ART regimen analysis based on NNRTI (n = 400)
EFV-based regimens	0.23	1			1
NVP-based regimens	0.33	1.57	0.97–2.54	.067	2.49	0.58–10.74	.221
Other	0.50	3.27	0.44–24.19	.247
Duration on ART (N = 339)
12 to <24 months	0.30	1			1
24 to <36 months	0.38	1.45	0.89–2.35	.138	0.71	0.30–1.66	.43
≥36 months	—
Switched regimen (n = 401)
No	0.29	1			1
Yes	0.31	1.11	0.72–1.72	.632	0.30	0.07–1.26	.1

Bold text represents statistically significant values p < 0.05.

CI, confidence interval; NNRTI, non-nucleotide reverse transcriptase inhibitor; NRTI, nucleotide reverse transcriptase inhibitor; OR, odds ratio; TDF, tenofovir disoproxil fumarate.

Characteristics of participants with a follow-up CD4 count

Females and particularly those who were married with a secondary education as well as those with an history of TB had higher median CD4 count changes compared to males (p < .05) at follow-up (Table 4). We also observed that females recovered better on TDF-based regimens compared to males. This observation was also true for those on EFV- or NVP-based regimens. Females that were still in care and on ART for <24 months had a higher CD4 count change compared to males in care (p < .05) (Table 4).

Table 4.

Characteristics of Participants with a Follow-Up CD4 Count

Characteristics	All	Median (IQR) CD4 among males	Median (IQR) CD4 among males female	p
Median (IQR) CD4 count	132 (38 to 234)	100 (19 to 188)	152 (60 to 269)	<.0001
Baseline CD4 (n = 418)
<25	124 (42 to 233)	101 (25 to 204)	168 (50 to 253)	.115
25–49	132 (19 to 224)	101 (0 to 147)	152 (39 to 266)	.01
≥50	132 (46 to 248)	97 (22 to 211)	152 (71 to 271)	.012
Marital status (n = 415)
Divorced	141 (3 to 277)	133 (1 to 203)	147 (35 to 295)	.364
Married/Living with partner	136 (44 to 237)	101 (27 to 194)	166 (78 to 333)	<.0001
Never married	126 (33 to 229)	85 (11 to 215)	153 (50 to 230)	.358
Widowed	120 (31 to 236)	76 (0 to 118)	140 (44 to 245)	.038
Education (n = 358)
None	141 (14 to 220)	145 (18 to 212)	49	.796
Primary	147 (74 to 256)	147 (78 to 237)	142 (72 to 315)	.698
Secondary	136 (38 to 230)	101 (17 to 196)	169 (65 to 258)	.003
University	208 (120 to 344)	147 (97 to 366)	268 (129 to 353)	.624
Skilled job training	44 (17 to 144)	41 (19 to 134)	50 (0 to 234)	.973
Not indicated	106 (0 to 248)	79 (0 to 178)	122 (0 to 341)	.567
History of opportunistic infections
History of tuberculosis (N = 369)	128 (42 to 212)	88 (18 to 146)	183 (104 to 247)	.001
History of cryptococcal meningitis (n = 338)	74 (19 to 233)	24 (5 to 247)	119 (94 to 241)	.068
ART regimen analysis based on NRTI (n = 401)
d4T-based regimens	146 (82 to 257)	130 (66 to 241)	163 (88 to 268)	.099
TDF-based regimens	120 (23 to 233)	87 (10 to 181)	145 (43 to 277)	.001
ART regimen analysis based on NNRTI (n = 409)
EFV-based regimens	118 (29 to 227)	87 (10 to 167)	157 (76 to 248)	.005
NVP-based regimens	136 (44 to 237)	106 (30 to 213)	149 (52 to 274)	.014
Outcome categories (n = 414)
Deceased	—	—	—	—
Loss to follow-up	103 (12 to 194)	29 (9 to 120)	125 (39.3 to 220.5)	.122
Still in care	136 (53 to 236)	106 (37 to 190)	152 (71 to 270)	.004
Transferred	213 (127 to 319)	195 (96 to 221)	268 (168 to 388)	.04
WHO Clinical Stage (n = 407)
WHO Stage 1 + 2	144 (68 to 226)	141 (76 to 211)	150 (60 to 233)	.463
WHO stage 3 + 4	120 (23 to 237)	77 (4 to 156)	152 (53 to 277)	0
12-Month CD4 (n = 418)
0–100	0 (−4 to 25)	0 (−6 to 18)	0 (−1 to 28)	.359
101–200	103 (82 to 136)	100 (76 to 136)	108 (87 to 135)	.271
201–300	190 (160 to 217)	188 (158 to 214)	196 (162 to 224)	.535
301–400	276 (250 to 310)	270 (250 to 299)	280 (250 to 311)	.617
401–500	388 (359 to 412)	404 (355 to 419)	379 (354 to 407)	.352
500+	574 (508 to 668)	638 (454 to 781)	577 (514 to 655)	.907
Duration on ART (n = 348)
12 to <24 months	138 (69 to 242)	117 (44 to 190)	152 (76 to 257)	.011
24 to <36 months	136 (17 to 249)	100 (0 to 209)	159 (30 to 295)	.1

Bold text represents statistically significant values p < 0.05.

Discussion

Although ART has been made widely available globally, a significant proportion of PLHIV in SSA still presents to care with AHD and many other comorbidities. CD4 count recovery after effective ART is a critical determinant of AIDS morbidity and mortality. We examined the determinants of CD4 count recovery among individuals with AHD initiating ART in Zimbabwe.

After a median follow-up time of 12 months from ART initiation, we observed a median (IQR) increase in CD4 count to 180 (92–290) from 50 (28–75) at baseline. These findings cement results from other studies, which showed that effective ART could improve levels of CD4 count and therefore decrease the proportion of immunocompromised patients.^8

–11 A study in South Africa which examined CD4 count recovery among HIV-infected patients starting ART with a very advanced immunodeficiency reported a much higher median increase in CD4 count, 261 cells/mm³ at 48 weeks from 97 at baseline.¹¹ Effective ART improves levels of CD4 count among patients with AHD. However, change in CD4 count remains lower in this vulnerable population when compared to those who start off ART with higher CD4 count.¹²

In most PLHIV, CD4 count recovery (a “safe” CD4 count threshold of 200 cells/mm³) is important on ART as this decreases the risk of development of HIV-related comorbidities.¹³ Previous studies have shown that CD4 count recovery among patients starting ART varied from 37% to 59%.^14,15 Similarly, in our study, 43% of the participants had recovered with CD4 counts >200 cells/mm³ at 12 months and up to 72.4% had a CD4 count >100 cells/mm³. Nevertheless, a substantial proportion (27.6%) of the patients failed to recover a CD4 count >100 cells/mm³ despite 1 year of ART, remaining susceptible to opportunistic infections and increased mortality. This result in severely immunocompromised individuals is comparable with previous studies that have also shown that initiating ART with a CD4 count <200 cells/mm³ is associated with poor CD4 count response.^16
–18

In our study, male gender was a strong predictor of immunological failure despite the same median baseline CD4 count (50 cells/mm³) in both groups. Men, however, had more clinically advanced disease characterized by the presence of TB and the WHO stage 3 and 4 diseases. A study in Nigeria assessing immunologic and virologic outcomes at 12 months among ART naive adults initiating ART also reported higher rates of CD4 count recovery among female patients than males.⁹ In South Africa, similar finding was observed.¹⁹ However, the study was part of a longitudinal population-based HIV and health surveillance conducted by the Africa Centre for Health and Population Studies in rural uMkhanyakude district of KwaZulu-Natal, South Africa.

A similar study in India on the impact on CD4 counts among newly diagnosed adult PLHIV who registered to receive HIV care and treatment in 12 ART centers, representatives of Karnataka, India, also found that females were more likely to recover their CD4 counts compared to males.¹⁹ This observation may be attributed to factors including the better and earlier health-seeking behavior of females compared to their counterpart males and the hormonal effect.^20,21 We also found that females and who were married with at least secondary education had higher median CD4 count changes at follow-up compared to males. The supportive socioeconomic environment appears to be advantageous to women on ART.

Previous studies have shown that younger age (<40 years) were significantly associated with CD4 count recovery.^4,22 In contrast to these studies, we found no association between younger age and better immune response.

WHO reported high levels of opportunistic infections among patients presenting to care with AHD, decreasing the rate of immune reconstitution and increasing the risk of mortality and AIDS acquisition. In our study, history of TB was present in almost one quarter of the patients (24%) at baseline, while CM was present in a small number (2%). However, these 2 opportunistic infections were not associated with CD4 count recovery.

Retention to care particularly among individuals with AHD is of paramount for the success of HIV treatment. In our study, up to 23% were loss to follow-up. This high rate may be attributed to several factors, including fear of stigma, disclosure of the HIV status to the family, and negative health care provider attitudes, as previously reported in African studies.^23
–25 However, the constant interaction with the health care system for monitoring and treatment of their comorbid conditions may be an important driver of retention into the care.

We aimed to provide key baseline data to enable clinicians and policy makers to better understand the burden of mortality among individuals with CD4 count ≤100 cells/mm³. Our findings had several important programmatic implications for the country. First, we found that among individuals presenting to care with AHD and initiating on ART, 43% had recovered with CD4 counts >200 cells/mm³, but up to 27.6% of the patients continued to have a CD4 count <100 cells/mm³ despite 1 year of ART. This high rate of persistent immunological failure on ART has programmatic implications. Implementation of Rapid start (same-day initiation of ART in patients newly diagnosed with HIV) and ‘Test and Treat’ (all people testing positive for HIV should start ART early regardless of WHO clinical stage or CD4 count) policies that were not present at that time will likely reduce the proportion presenting into care with AHD.

Our data also highlight the vulnerability of men living with HIV. Male participants are at increased risk of poor immunological response. Efforts to address the gender inequalities and delivering differentiated services that are male friendly should be prioritized.^26
–28 Men are often left behind as much global health programming on HIV is focused on women and girls.^29,30 Furthermore, Rapid start strategies in male supportive environments will be needed. These strategies will be particularly important in the post-COVID era where lockdowns decreased access to HIV services as previously reported,^31

–34 and it is anticipated that there will be higher rates of individuals presenting to care with AHD.

Study limitations

One of the limitations includes the fact that the study is a retrospective study, hence, other factors not described in this study and not available in the clinical records may have contributed to the immunological outcomes among these vulnerable participants. Viral load testing was not routinely available at that time, and persistent viremia, adherence concerns, and other factors may have contributed to some of the observed gender differences. Another limitation is the fact that the incomplete CD4 count data at 12 months' follow-up do not fully reflect the rate of CD4 count recovery in this study.

However, our findings provide real-world information on CD4 count recovery and determinants associated with CD4 count recovery. In the era of “Test and Treat” policy, CD4 count measurement remains an important tool for monitoring the immunological response of individuals living with HIV. The decentralization of POC CD4 count testing has since improved access to CD4 count testing services.^35
–37

Furthermore, the preferred ART regimen (NVP-based regimens) used during the study may have contributed to the low rate of CD4 count recovery reported in our study. Introduction of integrase inhibitor-based treatment regimens in SSA may contribute to improved CD4 count recovery. Studies have shown that integrase inhibitor-based regimens are associated with rapid and better CD4 count recovery compared to NNRTIs or PI-based ART.^38
–40 Further studies are needed to evaluate if the gender difference persists in the setting of ART initiation with integrase inhibitors.

Conclusion

We found that only 43% of patients presenting to care with AHD had recovered with CD4 counts >200 cells/mm³ after 1 year and males were less likely to recover. ART can improve immunologic status but significant proportion of individuals with AHD failed to achieve immunologic recovery. Minimizing the proportion of patients presenting with AHD is critical for improving clinical outcomes among those in care. Minimizing AHD in all but maybe specifically targeting men will be important.

Footnotes

Acknowledgments

We thank the participants and their families, and the clinics and staff. We also thank the CryptoART study team and CDC collaborators who made this study possible: Exavior Chivige, Edward Makaha, Taddy Mwarumba, Christine Ross, Snighdha Vallabhaneni, and Shirish Balachandra.

Authors' Contributions

A.T.M. and C.E.N. conceived the study. P.G. performed data analysis. V.K. wrote the first draft. A.T.M and V.K. critically reviewed and finalized the article. All authors contributed to subsequent drafts and reviewed and approved the final article.

Author Disclosure Statement

All authors have no reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest.

Funding Information

This work was supported by the Centers for Disease Control and Prevention (1U01GH000737).

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Effects of Gender and Baseline CD4 Count on Post-Treatment CD4 Count Recovery and Outcomes in Patients with Advanced HIV Disease: A Retrospective Cohort Study

Abstract

Introduction

Materials and Methods

Study design, setting, and population

Data collection

Data analysis

Ethical approval

Results

Baseline participants characteristic

Outcomes of the participants at follow-up

Factors associated with CD4 count recovery (CD4 count >200 cells/mm3)

Characteristics of participants with a follow-up CD4 count

Discussion

Study limitations

Conclusion

Footnotes

Acknowledgments

Authors' Contributions

Author Disclosure Statement

Funding Information

References

Factors associated with CD4 count recovery (CD4 count >200 cells/mm³)