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Patients who restart antiretroviral medication after interruption remain at high risk of unfavorable outcomes in Ethiopia


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Background Achieving optimal adherence to highly active antiretroviral therapy (HAART) is necessary to attain viral suppression and hence optimal clinical outcome. Interruptions in antiretroviral therapy medication often occur, but a substantial proportion restart treatment. Long-term care engagement practices and clinical outcomes have not been described among cohorts of individuals on HAART in Ethiopia. Methods In this study we describe treatment interruption patterns over time among clients who interrupt and subsequently resume HAART, and those who are continuously engaged in treatment, and determine clinical factors associated with loss to engagement.An observational, longitudinal, retrospective cohort design was engaged, using secondary treatment program data. We analyzed differences in treatment interruption among clients who were continuously active and those that interrupted and restarted treatment at months 6, 12, 18, and 24. Cox proportional hazards regression analysis was used to identify predictors of loss from treatment. We estimated time to first treatment interruption, time to restarting after interruption, and time to second interruption. Data from all clients registered to receive HAART in ten study health facilities, from 2005 to 2014, were used to study clinical and treatment outcomes up to 60 months or study end. ResultsIn this study, 39% (8,759/22,647) of clients interrupted treatment for more than 1 month at least at one point during follow-up. Of these, only 35% ever restarted treatment. At the end of follow-up, the hazard of unfavorable treatment outcome (dead, lost, stopped HAART) for clients who restarted treatment at months 6, 12, 18 and 24 was higher by a factor of 1.9, 2.4, 2.6 and 2.4, as compared to those who never discontinued treatment at those times. ConclusionHAART treatment interruption was common in the study population. In those with a history of treatment interruption, long term clinical outcomes were found to be suboptimal. Targeted interventions are required to address follow-up challenges and prevent treatment interruption.
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R E S E A R C H A R T I C L E Open Access
Patients who restart antiretroviral
medication after interruption remain at
high risk of unfavorable outcomes in
Alula M. Teklu
and Kesetebirhan D. Yirdaw
Background: Achieving optimal adherence to highly active antiretroviral therapy (HAART) is necessary to attain
viral suppression and hence optimal clinical outcome. Interruptions in antiretroviral therapy medication often occur,
but a substantial proportion restart treatment. Long-term care engagement practices and clinical outcomes have
not been described among cohorts of individuals on HAART in Ethiopia.
Methods: In this study we describe treatment interruption patterns over time among clients who interrupt and
subsequently resume HAART, and those who are continuously engaged in treatment, and determine clinical factors
associated with loss to engagement.
An observational, longitudinal, retrospective cohort design was engaged, using secondary treatment program data.
We analyzed differences in treatment interruption among clients who were continuously active and those that
interrupted and restarted treatment at months 6, 12, 18, and 24. Cox proportional hazards regression analysis was
used to identify predictors of loss from treatment. We estimated time to first treatment interruption, time to
restarting after interruption, and time to second interruption. Data from all clients registered to receive HAART in
ten study health facilities, from 2005 to 2014, were used to study clinical and treatment outcomes up to 60 months
or study end.
Results: In this study, 39% (8,759/22,647) of clients interrupted treatment for more than 1 month at least at one
point during follow-up. Of these, only 35% ever restarted treatment. At the end of follow-up, the hazard of
unfavorable treatment outcome (dead, lost, stopped HAART) for clients who restarted treatment at months 6, 12, 18
and 24 was higher by a factor of 1.9, 2.4, 2.6 and 2.4, as compared to those who never discontinued treatment at
those times.
Conclusion: HAART treatment interruption was common in the study population. In those with a history of
treatment interruption, long term clinical outcomes were found to be suboptimal. Targeted interventions are
required to address follow-up challenges and prevent treatment interruption.
Keywords: Treatment interruption, Antiretroviral medication, Lost, Tracking, Treatment Outcome, Ethiopia
* Correspondence:
St. Pauls Hospital Millennium Medical College, Addis Ababa, Ethiopia
MERQ Consultancy Services PLC, Addis Ababa, Ethiopia, Addis Ababa,
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (, which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
( applies to the data made available in this article, unless otherwise stated.
Teklu and Yirdaw BMC Health Services Research (2017) 17:247
DOI 10.1186/s12913-017-2172-9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Since the initiation of programs to provide free Highly
Active Antiretroviral Therapy (HAART) in many low-
and middle-income countries worldwide, the number of
people living with HIV/AIDS who are receiving treat-
ment has been increasing; reaching 17 million in 2015
[1]. Such programs have helped prevent mortality and
new HIV infection among people irrespective of gender,
age, race or economic status. The UNAIDS reports a
decline in HIV/AIDS-associated mortality and in the
rate of new HIV infection globally; an indication of both
the success of HAART treatment programs and other
methods to prevent disease transmission. Progress is
specifically pronounced in sub-Saharan African coun-
tries, where AIDS-associated mortality and new infec-
tion have declined by 29% and 12%, respectively, since
2010 [2].
Many people who start HAART discontinue treat-
ment, undermining the morbidity, mortality and pre-
vention benefits of therapy. Stigma and discrimination,
lack of psychosocial support, inaccessibility to services,
opportunistic infections, and drug side effects are all
commonly-sited reasons for discontinuing therapy [3].
Attrition varies at different times since initiation of
therapy. A multi-site assessment conducted in low- and
middle- income countries estimated average retention
at 12, 24, and 60 months post-initiation was 81%, 75%,
and 67%, respectively [4]. Attrition in HAART in
Ethiopia appears to vary similarly, but data are limited.
In four health centers in Tigray region, retention was 92%
and 85% at 6 and 12 months, respectively. Variation was
also present between facilities; in the sites evaluated, 12-
month retention ranged from 78 to 92% [5].
Many clients restart treatment on their own after an
initial episode of discontinuation. But for those who do
not reinitiate treatment independently, supportive ser-
vices including phone-based patient tracking and home
visits from peer supporters or health care workers may
be conducted to encourage re-engagement. Even with
supportive mechanisms such as patient tracking, not all
clients re-engage in care, and those who re-engage may
subsequently exit treatment again. Treatment interrup-
tion practices among those who reinitiate therapy after
discontinuation were described in a study in Uganda,
where 43% of re-starters were lost to follow-up (LTFU)
within 18 months of reinitiating treatment [6]. Although
its possible similar trends may be present in chronic
HIV care settings in Ethiopia, treatment discontinuation
and attrition patterns have not been described in this
setting. The objective of this study is to describe treat-
ment interruption among HAART re-starters, to exam-
ine longer-term trends in engagement and loss from
care among re-starters, as well as to determine clinical
factors associated with treatment interruption.
Study setting
This study is conducted in ten randomly selected hospi-
tals from among 38 hospitals in Ethiopia located in
Addis Ababa, Benishangul Gumuz, Gambella, and
Southern Nations Nationalities and Peoples Region
(SNNP). The cumulative total of unique patients who
had ever started HAART in the selected facilities com-
bined was over 22,700 in 2014. Fee-based HAART was
available before 2005, when free HAART services be-
came available nationwide [7]. Follow-up services were
customized to clients according to their need, ranging
from every month to every 3 months. Follow-up was
made by doctors, health officers or nurses trained in
management of chronic HIV care, treatment and sup-
port. Starting in 2007, peer educators or adherence
supporterswere available to assist medical providers
with providing adherence counseling to patients and
conducting patient tracking following missed appoint-
was updated in registers, medical records, and elec-
tronic databases, kept in secure and confidential locations.
The most common antiretroviral medications used were
as follows: First-line HAART was a combination of stavu-
dine, zidovudine, abacavir or tenofovir plus lamivudine
plus neverapine or efavirenz; Second-line regimen
contained lopinavir/ritonavir in the place of neverapine or
efavirenz [9]. A nationally-standardized system for moni-
toring and evaluation was in place at every study site. At
the time of treatment, clinicians documented care and
therapy in personal medical records. Relevant data from
medical records were then transferred to facility registers
and electronic database by data clerks. Two data clerks
trained specifically in the management of HIV care and
treatment data were maintained at antiretroviral (ART)
treatment clinics to track and update records and docu-
mentation, to alleviate work load among clinicians. Data
quality assurance measures, supervision and mentorship
programs for clinicians and data clerks were in place to
ensure data was properly generated, recorded and used
onsite. Information with regard to patient tracking was re-
corded by peer educators, and was then reconciled with
individual medical records, facility registers and electronic
database at ART clinics. Pharmacy records at facilities
were also consulted to cross-check medication pick-up
data from medical records.
Study design
This is an observational retrospective cohort study,
using medical records documented as part of the routine
care from clients who started HAART in selected facil-
ities in Ethiopia from September 2005 to November
2013. Data was captured electronically from the patient
records. Clients who started treatment at other facilities
Teklu and Yirdaw BMC Health Services Research (2017) 17:247 Page 2 of 8
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but received follow-up at a study facility (transfers) were
excluded. From the full cohort, we evaluated the average
time to 1
episode of treatment interruption, average
time to restarting treatment after the 1
episode of treat-
ment interruption, and average time to 2
episode of
treatment interruption. We identified clients who had a
documented episode of treatment interruption followed
by restarting treatment (restarters, and compared them
with clients with un-interrupted treatment (continuous
treated), to compare longer-term outcomes over
specific comparable time periods in individual treatment
history. For example, all clients who discontinued treat-
ment before month six of HAART treatment but
restarted treatment by month six or before, were com-
pared with those who never discontinued treatment by
month six of follow-up. Subsequent treatment interrup-
tions were determined and compared among restarters
and continuously treated, for a maximum duration of 60
months of follow-up. In order to examine patterns of
treatment interruption for clients who restarted treat-
ment at different time periods in treatment history, the
same comparisons were made between restarters who
re-engaged in care matched with continuously-treated
individuals at months 12, 18 and 24. Finally, predictors
of retention in treatment were examined to identify dif-
ferentiating demographic and clinical characteristics
among restarters to identify those who were more likely
to remain in care.
Operational definitions
Treatment interruption was defined as having termi-
nated HAART treatment for more than 1 month. This
could be due to being lost from care at treatment
initiating health facility, decision to stop treatment, or
Loss was defined as failure to present for HAART
medication refill at the treatment-initiating health facil-
ity, with inability to be traced back by phone or home
visit for more than 1 month, without a documented rea-
son for failing to present (eg. no confirmed death nor
decision to stop treatment in agreement with health care
worker) [10].
Death was defined as a known client death from any
cause, confirmed by health care worker or post-loss
Stop was defined as discontinuation of HAART in
agreement with health care worker at treatment-initiating
health facility.
Restart was defined as resuming treatment at the
treatment-initiating health facility after treatment
Retention was defined as active antiretroviral treat-
ment therapy at the treatment- initiating health facility.
Favorable treatment outcome was defined as being
active in treatment up to 60 months post-HAART initi-
ation, or up until September 2014 (whichever came
first), at treatment- initiating health facility.
Unfavorable treatment outcome was defined as be-
ing classified as lost, dead, or stopped from treatment
following agreement with treating health care worker, at
the last contact visit prior to 60 months post-HAART
initiation at treatment-initiating health facility.
Transfer out: when a patient is referred from the fa-
cility where s/he started ART to another health facility.
Transfer in: when a patient is received from another
health facility after s/he is started on ART at that facility.
Variables and data collection
The following variables were abstracted from patient
medical records and included in study: age at treatment
initiation, gender, baseline WHO Stage, baseline CD4
cell count, HAART start date, date of each follow-up,
HAART treatment status (active, lost, dead, stop, trans-
fer out, transfer in). The primary outcomes of interest
were unfavorable treatment outcome on or before
month-60 of follow-up, from the date of re-initiation
among re-starters and the comparable date for the com-
parison group of continuously-treated. Patient medical
record data was ascertained from an MS Access elec-
tronic database kept at the health facilities selected as
study sites, for the purpose of generating routine
monthly reports. Data entry was made from paper based
medical records daily by trained data clerks. Data quality
assessment was made routinely onsite as well as by ex-
ternal mentors.
Statistical analysis
Data cleaning and analyses were conducted using
STATA version 11 (Stata Corp, College Station, TX,
USA) statistical software. Time to 1
episode of treat-
ment interruption, time to restart, and time to 2
sode of treatment interruption were described using
mean, median, and inter-quartile ranges, and were plot-
ted graphically using histograms. Survival analysis was
carried out to compare the retention experience between
re-starters and those that had not discontinued treat-
ment. Clients were uncensored at the time of loss, death
or stopped treatment (unfavorable treatment outcome).
Those remaining active in treatment engagement at
60 months of follow-up or at September 2014 (which-
ever came first) were considered to have had favorable
treatment outcome, and were censored at that time.
Regression analysis was made using Cox proportional
hazards model. Within-site correlation of patient
characteristics were controlled by stratification. αwas
Teklu and Yirdaw BMC Health Services Research (2017) 17:247 Page 3 of 8
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set to be 0.05 for all analyses [11, 12]. The dataset is
available as Additional file 1.
Baseline characteristics
The total study population included 22,647 unique individ-
uals. The median follow-up time was 2.7 years (inter-quar-
tile range (IQR): 8 months6 years). Most study
participants were adults (98%), and females accounted for
54%. The median age was 34 years (IQR: 2840 years).
Most clients, approximately 68%, started treatment in
WHO clinical stage III or IV. Median baseline CD4 cell
count was 148 (range: 65195/mm
). Additional baseline
characteristics are presented in Table 1 below.
Treatment interruption
Approximately 39% of clients had discontinued treatment
for a month or more at least once throughout the dur-
ation of follow up (8,759) (see Table 1). Among clients that
had discontinued at least once, the median time to first
discontinuance was one year (IQR: 0.32.6 years). Only
35% (n= 3,061) of clients restarted HAART after the first
interruption following enrollment. Among those who did
restart, median time to restarting treatment was 7 months
(IQR: 2.2 months1.7 years). Figure 1 depicts the distribu-
tion of time to 1
treatment interruption. A substantial
number of clients discontinued treatment in the first few
weeks after starting HAART. Similar trends are seen for
time to return to treatment (Fig. 2). Of those who
restarted treatment, 24% (735) discontinued treatment for
second time over follow-up. Half, or 50% of the cases who
discontinued a second time, had done so within
five months of follow-up (Fig. 3).
Follow-up outcome
Unfavorable treatment status at the end of observation
was observed for 28.5% (6,459) of the study population:
2,188 (34%) died, and 4,271 (66%) were lost to follow-
up. Compared to individuals that were active in treat-
ment at 6 months, those that had discontinued but
restarted treatment within the first 6 months were 1.9
times (95% confidence interval 1.52.4) more likely to
have an unfavorable outcome at the end of 5 years. One-
year retention in care was 83% for those that had discon-
tinued and re-started before six months, while it was
91% for those that had never discontinued. At the end of
follow-up, retention was 57% for restarters within 6
months, and 76% among comparable individuals who
had not discontinued by 6 months. Being adult, male,
having higher WHO stage (III or IV) and having lower
CD4 cell count at baseline were associated with higher
hazard of unfavorable treatment outcome at the end of
follow-up. Similar patterns were observed for assess-
ments at months 12, 18 and 24. For all time periods
assessed, re-starters experienced more than two-fold
excess hazard of unfavorable outcome (HR = 2.4 (95%
confidence interval 2.02.8), HR = 2.6 (95% confidence
interval 2.23.1), and HR = 2.4 (95% confidence inter-
val 2.02.8), respectively). (Tables 2 and 3) Among
Table 1 Baseline Characteristics (n= 22,647)
Variable Sub-category Number (%)
Age <15 513 (2)
15 22,134 (98)
Gender Female 12,226 (54)
Male 10,421 (46)
Baseline WHO Stage I or II 7,286 (32)
III or IV 15,361 (68)
Baseline CD4 <100 8,445 (37)
100349 12,384 (55)
350 1,818 (8)
Ever discontinued ART No 13,888 (61)
Yes 8,759 (39)
Fig 1 Time to 1
treatment interruption (years)
Fig 2 Time to treatment restart after 1
loss (years)
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those who discontinued and restarted treatment, be-
ing male, being WHO stage (III or IV), discontinuing
treatment for the first time before 6 months of
follow-up, and restarting treatment within 6 months
of interruption were associated with unfavorable treat-
ment outcome at the end of follow-up (Table 4).
Treatment interruptions were common in the study
population. A substantial proportion (39%), of clients
who started HAART in the study facilities discontinued
treatment at least once. Of these, 35% restarted treat-
ment, but approximately a quarter of those discontinued
treatment again. Among those who discontinued and re-
started, unfavorable outcomes at the end of follow-up
were at least twice as likely as among those who had
never discontinued treatment at months 6, 12, 18, and
Estimates of retention in care, or active engagement
on HAART among patients who have initiated therapy,
vary in different settings. In an observational,
prospective, multi-site cohort study of HIV-infected pa-
tients who initiated ART for the first time in Tigray,
Ethiopia, the 12 month retention was 85%. In a different
multi-clinic observational study in three regions in
Ethiopia, at 3 years, survival among 93,418 patients on
HAART was 70% [5, 13]. Estimates of survival from the
current study are comparable. But, only a few studies
have assessed long term treatment outcome among
those who interrupt and restart therapy. A study in
Uganda [6] found that of clients who interrupted but
subsequently resumed treatment, only 52% were active
in care after 18 months. This is similar with the current
studys estimate of 56%. In the Uganda study, those who
returned to care on their own were more likely to re-
sume care after second treatment interruption than were
those who were traced by health care workers and re-
engaged: 61% vs. 39%. In our study, analysis indicates
that those that discontinued and restarted again earlier
were more likely to have unfavorable outcomes in the
long term. It is possible that re-starters that were tem-
porarily lost from care may tend to have barriers to care
that remain unaddressed upon re-entry, undermining
subsequent adherence to treatment. These may be re-
lated to lack of access to care and support programs,
distance from treatment site, advanced disease stage, or
lack of proper adherence counseling [14, 15]. A study in
British Columbia [16] describes a slightly different trend
in treatment interruption experiences. In this setting,
only 29% of patients were active on treatment continu-
ously, though the follow-up period was longer than the
current study (19962012). However, in contrast to our
study, patients of younger age, higher CD4 count, and
earlier WHO clinical stages were more likely to be lost.
It may be that healthier patients may not feel the need
to adhere to treatment, as their present health status may
give them a false assurance of health. In our study, how-
ever, we found the reverse: sicker clients were more likely
Fig 3 Time to 2
interruption after restart (years)
Table 2 Determinants of unfavorable treatment outcome at 60 months among those active in treatment at month six
Variable Sub-category Hazard ratio, crude P- value Hazard ratio, adj P-value
Age <15 1 1
15 1.6 0.001 1.6 0.002
Gender Female 1 1
Male 1.3 <0.001 1.2 <0.001
Baseline WHO Stage I or II 1 1
III or IV 1.5 <0.001 1.4 <0.001
Baseline CD4 <100 1 1
100349 0.7 <0.001 0.8 <0.001
350 0.8 0.008 0.9 0.106
Ever discontinued HAART before 6 months No 1 1
Yes 1.8 0.000 1.9 0.000
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to discontinue follow-up. The explanation for this could
be that sicker people may be unable to ambulate easily
and struggle to travel to attend clinic and acquire medica-
tion [13].
This study clearly describes the distribution of time
between treatment initiation and interruption, among
treatment interrupters. Clients were generally more
likely to interrupt medication in early stages of treat-
ment than later stages. This may be due to drug side
effects, resurgence of opportunistic infections, non-
disclosure of status or fear of stigma and discrimination
[1720]. But, the time to the first occurrence of treat-
ment interruption was 1 year, as compared to an average
of 5 months to next occurrence after restarting. This re-
duction in time on treatment may be an indication of
adherence fatigue [21]. Or as explained earlier, recur-
rence of problems that were unaddressed the first time
treatment was interrupted. This points to the need for a
more targeted intervention to help clients achieve long-
term treatment goals, including viral suppression. In
most high burden facilities where providers are bur-
dened with a high work load, treatment supporters are
available to assist with counseling of patients. Counsel-
ing may be targeted to support those with a pattern of
poor adherence, by sharing personal experiences and
teaching ways to cope with challenges [2224]. Peer sup-
porters may also be able to reduce the length of inter-
ruption before restarting treatment.
The median time taken to restart treatment in this
study was seven months, although nearly a third of
those who restarted did so in the first few weeks.
Health care workers may be able to do more to reduce
this time by preparing patients before re-starting treat-
ment, and addressing emerging challenges as they ap-
pear. Improving accessibility of care is one important
approach to reducing loss from care. Bringing treat-
ment closer to patientsvicinity may alleviate barriers,
but such approaches may be complex to introduce, and
may not result in improvements in engagement in all
settings. In a study conducted by Médecins Sans
Table 4 Determinants of unfavorable treatment outcome at the end of follow-up among those who restarted treatment for HAART
after treatment interruption (n= 3,922)
Variable Sub-category Hazard ratio, crude P- value Hazard ratio, adj P-value
Age <15 1
15 1.4 0.300
Gender Female 1 1
Male 1.6 <0.001 1.6 <0.001
Baseline WHO Stage I or II 1 1
III or IV 1.2 0.061 1.3 0.014
Baseline CD4 <100 1
100349 0.8 0.049 0.9 0.138
350 0.8 0.112 0.8 0.178
Time to 1
interruption <6 months 1 1
6 months 0.4 <0.001 0.3 <0.001
Time to 1
restart < 6 months 1 1
6 months 0.3 <0.001 0.2 <0.001
Table 3 Hazard of unfavorable treatment outcome at the end of follow-up among those active in HAART care at months 6, 12, 18
and 24 months
Variable Sub-category Hazard ratio, adj P-value
Ever discontinued HAART before 6 months No 1
Yes 1.9 0.003
Ever discontinued HAART before 12 months No 1
Yes 2.4 <0.001
Ever discontinued HAART before 18 months No 1
Yes 2.6 <0.001
Ever discontinued ART before 24 months No 1
Yes 2.4 <0.001
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Frontières in 25 HAART treatment programs in mul-
tiple countries in Africa and Asia, program scale-up to
larger geographic coverage was associated with more
lost to follow-up, though it did result in improved mor-
tality. The reduction in mortality was comparable to
the incremental increase in loss rate. Further work may
need to be done to identify and re-engage clients that
are lost, which is more likely to happen with increased
frequency as more people are initiated on HAART. As
healthier patients are initiated earlier, it may be more
difficult to encourage adherence to treatment. For test-
and-treat strategy to result in mortality reduction, these
barriers will need to be addressed [1, 3, 25].
Among re-starters, male gender, being in advanced
WHO stage III or IV at baseline, history of treatment
interruption in the first 6 months after starting HAART,
and restarting treatment within 6 months of interruption
were significant predictors of subsequent loss from care.
We believe other factors may be helpful in identifying
those at risk of loss. This study used existing electronic
medical records and data, and therefore was limited to
the information that was previously collected. We were
therefore unable to explore other potential parameters
of interest. More studies are recommended, to inform
the development of a proper tool to help prioritize cli-
ents at risk, so that health care workers can target those
most in need of support.
Our analysis assumed that all lost patients interrupted
treatment, when in fact there is a possibility that some
restarted treatment at a different facility. This was dem-
onstrated in one study where nearly 20% of patients con-
sidered lost were found to be on treatment at a different
facility [26]. Therefore, our analysis represents the
worst case scenarioand may over-estimate loss from
treatment. The strength of this study comes from the
large number of clients followed over a long duration
of time, including from the beginning of free HAART
initiation in Ethiopia. This study relied on secondary
data collected for program purposes. Although the
original data may have had some errors or missing in-
formation, we took utmost precaution in our data ab-
straction to maintain accuracy as originally recorded.
This study indicates that treatment outcomes of
HAART defaulters are often unfavorable, and provides
evidence of the need for approaches to improve reten-
tion in care. Those who interrupt treatment follow-up
and then return to care experience less frequent re-
engagement upon subsequent interruptions from care.
Frequent delayed return to care and early relapse indi-
cate that there is much room for improvement in pa-
tient preparation and tracing as treatment coverage
expands further and healthier clients initiate treatment.
Additional file
Additional file 1: Excel file containing study dataset used for analysis.
(XLS 3617 kb)
CD4: Cluster differentiation 4; HAART: Highly active antiretroviral therapy;
HIV: Human-immune deficiency; LTFU: Lost to follow-up; WHO: World health
We would like to thank health care providers, data clerks and peer
supporters that contributed to the documentation of medical and electronic
records at facilities.
No funding.
Availability of data and material
All the data used in this study are included in this published article.
AMT participated in the conception of study, collection and analysis of the
quantitative data, compilation and review of documents, and drafting of the
manuscript. KD participated in the conception of study, collection and analysis
of the quantitative data, compilation and review of documents, and drafting of
the manuscript. Both authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
Existing data was used which was de-identified and de-linked before acquisition
and during analysis for which reason consent forms were not required.
Ethical approval was obtained from the National Research Ethics Review
Committee of Ethiopia.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
St. Pauls Hospital Millennium Medical College, Addis Ababa, Ethiopia.
MERQ Consultancy Services PLC, Addis Ababa, Ethiopia, Addis Ababa,
University of South Africa, Addis Ababa, Ethiopia.
Received: 9 August 2016 Accepted: 18 March 2017
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... Additionally, treatment interruption can diminish the internal connection patients feel towards HIV care [43]. Those who experience treatment interruption are more likely to have repeat interruptions over time and stop ART completely [50][51][52]. ...
Full-text available
Introduction: Mobility is common and an essential livelihood strategy in sub-Saharan Africa (SSA). Mobile people suffer worse outcomes at every stage of the HIV care cascade compared to non-mobile populations. Definitions of mobility vary widely, and research on the role of temporary mobility (as opposed to permanent migration) in HIV treatment outcomes is often lacking. In this article, we review the current landscape of mobility and HIV care research to identify what is already known, gaps in the literature, and recommendations for future research. Discussion: Mobility in SSA is closely linked to income generation, though caregiving, climate change and violence also contribute to the need to move. Mobility is likely to increase in the coming decades, both due to permanent migration and increased temporary mobility, which is likely much more common. We outline three central questions regarding mobility and HIV treatment outcomes in SSA. First, it is unclear what aspects of mobility matter most for HIV care outcomes and if high-risk mobility can be identified or predicted, which is necessary to facilitate targeted interventions for mobile populations. Second, it is unclear what groups are most vulnerable to mobility-associated treatment interruption and other adverse outcomes. And third, it is unclear what interventions can improve HIV treatment outcomes for mobile populations. Conclusions: Mobility is essential for people living with HIV in SSA. HIV treatment programmes and broader health systems must understand and adapt to human mobility, both to promote the rights and welfare of mobile people and to end the HIV pandemic.
... Retention measures are also limited as they are generally calculated retrospectively: data sources poorly distinguish between the loss to follow-up and death [158] and often miss "silent transfers" between different facilities [158]. This can be addressed by following patients to evaluate alternate outcomes and adjust estimates: either through tracing a sample [57], using weights from the literature [27,134] or using national/combined databases to follow patients who move between facilities [3,158]. However, all these approaches increase the burden of data collection, linkage and analysis, reducing their feasibility in practice. ...
Full-text available
Introduction: Engagement with HIV care is a multi-dimensional, dynamic process, critical to maintaining successful treatment outcomes. However, measures of engagement are not standardized nor comprehensive. This undermines our understanding of the scope of challenges with engagement and whether interventions have an impact, complicating patient and programme-level decision-making. This study identified and characterized measures of engagement to support more consistent and comprehensive evaluation. Methods: We conducted a scoping study to systematically categorize measures the health system could use to evaluate engagement with HIV care for those on antiretroviral treatment. Key terms were used to search literature databases (Embase, PsychINFO, Ovid Global-Health, PubMed, Scopus, CINAHL, Cochrane and the World Health Organization Index Medicus), Google Scholar and stakeholder-identified manuscripts, ultimately including English evidence published from sub-Saharan Africa from 2014 to 2021. Measures were extracted, organized, then reviewed with key stakeholders. Results and discussion: We screened 14,885 titles/abstracts, included 118 full-texts and identified 110 measures of engagement, categorized into three engagement dimensions ("retention," "adherence" and "active self-management"), a combination category ("multi-dimensional engagement") and "treatment outcomes" category (e.g. viral load as an end-result reflecting that engagement occurred). Retention reflected status in care, continuity of attendance and visit timing. Adherence was assessed by a variety of measures categorized into primary (prescription not filled) and secondary measures (medication not taken as directed). Active self-management reflected involvement in care and self-management. Three overarching use cases were identified: research to make recommendations, routine monitoring for quality improvement and strategic decision-making and assessment of individual patients. Conclusions: Heterogeneity in conceptualizing engagement with HIV care is reflected by the broad range of measures identified and the lack of consensus on "gold-standard" indicators. This review organized metrics into five categories based on the dimensions of engagement; further work could identify a standardized, minimum set of measures useful for comprehensive evaluation of engagement for different use cases. In the interim, measurement of engagement could be advanced through the assessment of multiple categories for a more thorough evaluation, conducting sensitivity analyses with commonly used measures for more comparable outputs and using longitudinal measures to evaluate engagement patterns. This could improve research, programme evaluation and nuanced assessment of individual patient engagement in HIV care.
... This study identified poor drug adherence tripled the chance of virological failure among patients with first-line HAART. This finding is consistent with multiple previous shreds of evidence (3,6,28,29). Those patients with poor drug adherence had no adequate drug concentration for sustained viral suppression. ...
Full-text available
Background: Virological failure remains a public health concern among patients with human immunodeficiency virus (HIV) after treatment initiation. Ethiopia is one of the countries that aims to achieve the global target of 90-90-90 that aims to achieve 90% virological suppression, but there is a paucity of evidence on the determinants of virological failure. Therefore, the study is intended to assess determinants of virological treatment failure among patients on first-line highly active antiretroviral therapy (HAART) at Mizan Tepi University Teaching Hospital (MTUTH), Southwest Ethiopia. Method: A hospital-based unmatched case-control study was conducted from 11 November to 23 December 2020, among 146 cases and 146 controls. All cases and controls were selected randomly using computer-generated random numbers based on their medical record numbers. During the document review, data were collected using checklists, entered into Epi-data version 4.0.2, and analyzed by SPSS version 25. A multivariable logistic regression analysis was done to identify the independent determinants of virological treatment failure. Results: In this study, being male (adjusted odds ratio (AOR) = 1.89, 95% CI: 1.04, 3.47), substance use (AOR = 2.67, 95% CI: 1.40, 4.95), baseline hemoglobin (Hgb) < 12 mg/dl (AOR = 3.22, 95% CI: 1.82, 5.99), poor drug adherence (AOR = 3.84, 95% CI: 1.77, 5.95), restart ART medication (AOR = 2.45, 95% CI: 1.69, 7.35), and opportunistic infection (OI) while on HAART (AOR = 4.73, 95% CI: 1.76, 12.11) were determinants of virological treatment failure. Conclusion: The study revealed that the sex of the patient, history of substance use, baseline Hgb < 12 mg/dl, poor drug adherence, restart after an interruption, and having OI through the follow-up period were determinants of virological failure. Therefore, program implementation should consider gender disparity while men are more prone to virological failure. It is also imperative to implement targeted interventions to improve drug adherence and interruption problems in follow-up care. Moreover, patients with opportunistic infections and restart HAART need special care and attention.
... In line with our findings, previous studies found that patients re-engaging in care, including those with prior ARV exposure [14,30], are likely to have poor outcomes, which may be linked to unaddressed factors associated with the initial default from care [31]. The increased risk of LTFU we observed among young patients may also be linked to a myriad of underlying complex factors such as medication adherence challenges [32][33][34]. ...
Objective: In a multicountry prospective cohort of persons with HIV from six countries between 2007 and 2015, we evaluated long-term outcomes of first-line non-nucleoside reverse-transcriptase inhibitor-based antiretroviral therapy (ART), and risk factors for loss-to-follow-up, mortality, virological failure, and incomplete CD4+ T-cell recovery. Methods: We calculated cumulative incidence of lost-to-follow-up, death, virological failure (VL ≥ 1000 cps/ml) and incomplete CD4+ T-cell recovery (<500 cells/μl) at successive years, using Kaplan-Meier and Cox regression. Results: Of 2735 participants, 58.0% were female, median age was 37 (interquartile range [IQR] 32-43) years, and median pre-ART CD4+ T-cell count was 135 (IQR 63-205)/μl. Total follow-up time was 7208 person-years (median 24.3 months, IQR 18.7-58.3). Deaths by any cause and loss to follow-up occurred mostly during the first year of ART (84%, 201/240 and 56%, 199/353, respectively). During their first 6 years of ART, 71% (95% confidence interval [CI] 69.0-73.7) were retained on first-line, and among those 90-93% sustained viral suppression (<1000 cps/ml); CD4+ T-cell recovery was incomplete in 60% (220/363) of participants. The risk factors associated with poor outcomes during long-term ART were: for loss-to-follow-up, recent VL ≥1000 cps/ml, recent CD4+ T-cell count ≤50 cells/μl, age <30 years, being underweight; for mortality, recent CD4+ T-cell count ≤50 cells/μl; and, for virological failure, age <40 years, recent CD4+ T-cell count ≤200 cells/μl, poor adherence, male sex, and low-level viremia. Conclusion: To achieve long-term ART success towards the UNAIDS targets, early ART initiation is crucial, coupled with careful monitoring and retention support, particularly in the first year of ART. Male and youth-centred care delivery models are needed to improve outcomes for those vulnerable groups.
... It has been reported that more that 75% of patient LTF could be traced and a good proportion return to ART and care at some point [14,15]. Regarding the determinants of ART retention, the observed higher retention in age group (31-40 years) is consistent with the findings from other studies, which have shown higher retention with older age groups compared with lower age groups [16,17]. ...
Full-text available
Introduction: retaining patients in antiretroviral treatment (ART) is essential for successful outcomes. Unfortunately, Cameroon continues to report suboptimal ART retention. This study focused on identifying determinants of ART retention in three HIV clinics in Cameroon within the HIV treat all context. Methods: a medical chart review of 423 subjects who initiated ART between July and September 2016 in the Limbe, Bamenda and Jamot Hospitals. Patients' sociodemographic and clinical characteristics and ART retention data were abstracted using structured paper forms. Chi square test was used to assess bivariate associations. Logistic regression was used to adjust for confounders. P-value was set at <0.05 at 95% confidence interval. Results: the mean age was 40±11 years, and 65.1% were females. Antiretroviral treatment retention after 24 months was 309/392 (78.83%) and 30/423 (7.1%) were transferred-out, 11/423 (2.6%) reported dead and 73/423 (17.3%) lost to follow-up. HIV status disclosure (AOR 0.16 95% CI: 0.05-0.51, p<0.01) and age group 31-50 years (AOR 3.63, 95% CI: 1.04-12.59, P= 0.04) were associated with lower and higher ART retention respectively. Conclusion: about a quarter of the participants were not retained in ART after 24 months. Patient-level factors determined ART retention. These factors should be considered in designing strategies to improve ART retention. More research is needed to identify other determinants of ART retention under the HIV treat all strategy.
... With very few exceptions, the consequence is a rapid increase in viral particle numbers, (Rothenberger et al., 2015). This immediate effect of treatment interruptions may result in serious implications for efficacy, making it necessary to treat with an alternative regimen, (Teklu and Yirdaw, 2017). Apart from this virological failure, less immediate effects, such as failure of the immune system to maintain an effective response, may follow treatment interruptions with detrimental effect to the immune system, (Imaz et al., 2013). ...
In the past 30 years, HIV infection made a transition from fatal to chronic disease due to the emergence of potent treatment largely suppressing viral replication. However, this medication must be administered life-long on a regular basis to maintain viral suppression and is not always well tolerated. Any interruption of treatment causes residual virus to be reactivated and infection to progress, where the underlying processes occurring and consequences for the immune system are still poorly understood. Nonetheless, treatment interruptions are common due to adherence issues or limited access to antiretroviral drugs. Early clinical studies, aiming at application of treatment interruptions in a structured way, gave contradictory results concerning patient safety, discouraging further trials. In-silico models potentially add to knowledge but a review of the Literature indicates most current models used for studying treatment interruptions (equation-based), neglect recent clinical findings of collagen formation in lymphatic tissue due to HIV and its crucial role in immune system stability and efficacy. The aim of this research is the construction and application of so-called ‘Bottom-Up’ models to allow improved assessment of these processes in relation to HIV treatment interruptions. In this regard, a novel computational model based on 2D Cellular Automata for lymphatic tissue depletion and associated damage to the immune system was developed. Hence, (i) using this model, the influence of spatial distribution of collagen formation on HIV infection progression speed was evaluated while discussing aspects of computational performance. Further, (ii) direct Monte Carlo simulations were employed to explore the accumulation of tissue impairment due to repeated treatment interruptions and consequences for long-term prognosis. Finally, (iii) an inverse Monte Carlo approach was used to reconstruct yet unknown characteristics of patient groups. This is based on sparse data from past clinical studies on treatment interruptions with the aim of explaining their contradictory results.
Early diagnosis of human immunodeficiency virus (HIV) and retention in care are cornerstones of better prognosis of people living with HIV (PLWH). The purpose of this study was to compare patients who discontinued antiretroviral treatment (ART) with those who were diagnosed late with HIV. In this retrospective analysis of PLWH under the care of one of the Infectious Diseases Clinics in Poland between 2020 and 2021, two sub-analyses were carried out. One comparing patients who relinked to care after treatment interruption ("Group A") with those who had late HIV diagnosis ("Group B"), another comparing group A to those who were adherent to ART ("Group C"). 215 patients were included in this study (Group A = 47, Group B = 53, Group C = 115). Those who discontinued ART more often used actively drugs (p = 0.001) in comparison to those with late HIV diagnosis. In both bivariate and multivariable analysis migrants were more often diagnosed late with HIV than interrupted ART (p = 0.004 and 0.015, respectively). In the second analysis, in the multivariable analysis female sex was not associated with treatment interruption, whereas active drug usage was. People using drugs have a higher risk of ART interruption. Migrants are more at risk of late HIV diagnosis. Adequate interventions should be made towards both groups.
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Introduction Men in sub-Saharan Africa are less likely than women to initiate antiretroviral therapy (ART) and more likely to have longer cycles of disengagement from ART programmes. Treatment interventions that meet the unique needs of men are needed, but they must be scalable. We will test the impact of various interventions on 6-month retention in ART programmes among men living with HIV who are not currently engaged in care (never initiated ART and ART clients with treatment interruption). Methods and analysis We will conduct a programmatic, individually randomised, non-blinded, controlled trial. ‘Non-engaged’ men will be randomised 1:1:1 to either a low-intensity, high-intensity or stepped arm. The low-intensity intervention includes one-time male-specific counseling+facility navigation only. The high-intensity intervention offers immediate outside-facility ART initiation+male-specific counselling+facility navigation for follow-up ART visits. In the stepped arm, intervention activities build in intensity over time for those who do not re-engage in care with the following steps: (1) one-time male-specific counselling+facility navigation→(2) ongoing male mentorship+facility navigation→(3) outside-facility ART initiation+male-specific counselling+facility navigation for follow-up ART visits. Our primary outcome is 6-month retention in care. Secondary outcomes include cost-effectiveness and rates of adverse events. The primary analysis will be intention to treat with all eligible men in the denominator and all men retained in care at 6 months in the numerator. The proportions achieving the primary outcome will be compared with a risk ratio, corresponding 95% CI and p value computed using binomial regression accounting for clustering at facility level. Ethics and dissemination The Institutional Review Board of the University of California, Los Angeles and the National Health Sciences Research Council in Malawi have approved the trial protocol. Findings will be disseminated rapidly in national and international forums and in peer-reviewed journals and are expected to provide urgently needed information to other countries and donors. Trial registration number NCT05137210 . Date and version 5 May 2023; version 3.
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Background: We conducted a nationwide cross-sectional study to estimate pretreatment drug resistance (PDR) prevalence in adults initiating ART in Sri Lanka following the WHO's recommendations. Methods: HIV drug resistance was determined on dried blood spots (DBSs) using population-based sequencing of the protease and reverse transcriptase genes and interpretation was based on Stanford HIVdb v9.0. Analyses were weighted to adjust for multistage sampling and genotypic failure rate. We used logistic regression to assess differences between groups. Results: Overall, in 10% (15 of 150) of patients initiating ART, HIV drug resistance mutations were detected. The prevalence of resistance to NNRTI drugs efavirenz/nevirapine was 8.4% (95% CI 4.6-15.0) but differed among those reporting having prior antiretroviral (ARV) exposure (24.4%, 95% CI 13.8-39.5) compared with 4.6% (95% CI 1.6-12.8) for those reporting as being ARV naive (OR 4.6, 95% CI 1.3-16.6, P = 0.021). PDR to efavirenz/nevirapine was also nearly twice as high among women (14.1%, 95% CI 6.1-29.4) compared with men (7.0%, 95% CI 3.1-14.7) (P = 0.340) and three times high among heterosexuals (10.4%, 95% CI 2.4-35.4) compared with MSM (3.8%, 95% CI 1.1-12.7) (P = 0.028). NRTI PDR prevalence was 3.8% (95% CI 1.1-12.1) and no PI PDR was observed in the study. Conclusions: A high prevalence of efavirenz/nevirapine PDR was reported, especially in patients with prior ARV exposure, in women and those reporting being heterosexual. These findings highlight the need to fast-track the transition to the WHO-recommended dolutegravir-based first-line ART.
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CD4 count recovery after antiretroviral treatment (ART) initiation has been thoroughly examined in HIV infection. However, immunologic response after ART restart following care interruption is less well studied. We compare the CD4 trends before disengagement from care and after ART re-initiation. Data were obtained from the East-Africa International epidemiology Databases to Evaluate AIDS (IeDEA) Collaboration (N= 62,534). CD4 trends before disengagement, during disengagement, and after ART re-initiation were simultaneously estimated through a linear mixed model with two subject-specific knots placed at the time of disengagement and treatment re-initiation. We also estimated CD4 trends conditional on the baseline CD4 value. 10,961 patients returned to care after disengagement from care, with the median (IQR) time of gap in care being 2.7 (2.1, 5.4) months. Our model showed that CD4 increases after ART re-initiation were much slower than those before disengagement. Assuming that disengagement from care occurs 12 months after ART initiation and a three-month treatment gap, CD4 counts at 3 years since ART initiation would be lower by 36.5 cells/$\mu L$ than those obtained under no disengagement. Given that poorer CD4 restoration is associated with increased mortality/morbidity, specific interventions targeting at better retention to care are urgently required.
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Introduction Studies have shown high initial mortality in Antiretroviral Therapy (ART) programs from resource-limited settings. However, there is dearth of evidence on treatment outcomes and associated determinant factors in public hospitals. Therefore, the objective of this study is to assess survival and identify predictors of death in adult HIV-infected patients initiating ART at a public hospital in Eastern Ethiopia. Methods A retrospective cohort study was conducted by reviewing baseline and follow-up records of patients who started ART between December 1, 2007 and December 31, 2011 at Kharamara hospital. Time to death was the main outcome measure. Kaplan-Meier models were used to estimate mortality and Cox proportional hazards models to identify predictors of mortality. Results A total of 784 patients (58.4% females) were followed for a median of 60 months. There were 87 (11.1%) deaths yielding an overall mortality rate of 5.15/100 PYO (95% CI: 4.73-6.37). The estimated mortality was 8.4%, 9.8%, 11.3%, 12.7% and 14.1% at 6, 12, 24, 36 and 48 months respectively. The independent predictors of death were single marital status (AHR: 2.31; 95%CI: 1.18-4.50), a bedridden functional status (AHR: 5.91; 95%CI: 2.87-12.16), advanced WHO stage (AHR: 7.36; 95%CI: 3.17-17.12), BMI < 18.5 Kg/m2 (AHR: 2.20; 95%CI: 1.18-4.09), CD4 count < 50 cells/µL (AHR: 2.70; 95%CI: 1.26-5.80), severe anemia (AHR: 4.57; 95%CI: 2.30-9.10), and TB co-infection (AHR: 2.30; 95%CI: 1.28-4.11). Conclusion Improved survival was observed in patients taking ART in Somali region of Ethiopia. The risk for death was higher in patients with advanced WHO stage, low CD4 count, low Hgb, low BMI, and concomitant TB infection. Intensive case management is recommended for patients with the prognostic factors. Optimal immunologic and weight recoveries in the first 6 months suggest increased effort to retain patients in care at this period.
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Introduction: Although Ethiopia has been scaling up the antiretroviral therapy (ART) services, low retention in care of patients remains one of the main obstacles to treatment success. We report data on retention in care and its associated determinants in Tigray, Ethiopia. Methods: We used data from the CASA project, a prospective observational and multi-site study of a cohort of HIV-infected patients who initiated ART for the first time in Tigray. Four participating health facilities (HFs) located in the South of Tigray were considered for this study. Patients were followed for one year after ART initiation. The main outcome measure was represented by the current retention in care, defined as the proportion of patients who were alive and receiving ART at the same HF one year after ART initiation. Patients who started ART between January 1, 2013 and December 31, 2013 were included in this analysis. Patients were followed for one year after ART initiation. The determinants of retention were analysed using univariate and multivariate Cox Proportional Hazards model with robust sandwich estimates to account for within HF correlation. Results: The four participating HFs in Tigray were able to retain overall 85.1% of their patients after one year from starting ART. Loss to follow-up (5.5%) and transfers to other HF (6.6) were the main determinant of attrition. A multivariate analysis shows that the factors significantly associated with retention were the type of HF, gender and active TB. Alamata health center was the HF with the highest attrition rate (HR 2.99, 95% CI: 2.77-3.23). Active TB (HR 1.72, 95% CI: 1.23-2.41) and gender (HR 1.64, 95% CI: 1.10-2.56) were also significantly associated with attrition. Conclusions: Although Ethiopia has significantly improved access to the ART program, achieving and maintaining a satisfactory long-term retention rate is a future goal. This is difficult because of different retention rates among HFs. Moreover specific interventions should be directed to people of different sex to improve retention in care in male population.
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L’objectif de cette étude est de décrire les caractéristiques des patients « perdus de vue » et les facteurs déterminant la perte de vue au cours du suivi de patients infectés par le VIH. Il s’agit d’une étude rétrospective, descriptive et analytique des patients, traités ou non par ARV, perdus de vue issus de la cohorte des patients suivis à l’Hôpital de jour (HDJ) de Ouagadougou. Au total, 402 patients sur 5 118 suivis dans la file active (7,9 %) ont été considérés perdus de vue. Parmi ces patients, 340 (84,5 %) avaient un statut vital inconnu, 28 (7 %) étaient vivants et 34 (8,5 %) décédés. L’âge moyen était de 37,5 ans. Deux cent cinquante et un (62,4 %) étaient de sexe féminin. La durée moyenne de suivi était de 2,9 ans. Après recherche active, 16 des 21 patients sous ARV étaient en arrêt thérapeutique. En analyse multivariée, les facteurs fortement associés à la perte de vue étaient la non scolarisation (p=0,008), la résidence hors de Ouagadougou (p=0,002) et le VIH2 (p
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High levels of adherence to antiretroviral therapy (ART) and retention in treatment programs are required for successful virologic suppression and treatment outcomes. While there have been numerous studies focusing on adherence and loss to follow-up (LTFU) in adults, studies in children and young adolescents are limited. For this study, we examined patterns of adherence and LTFU in HIV-infected pediatric patients receiving ART in PEPFAR-funded sites in Nigeria. We conducted a retrospective observational study utilizing data that had been collected during the course of care in a large pediatric ART program in Nigeria. A total of 3,513 children ages 0-14.9 years enrolled at 31 different sites between June 2005 and March 2011 were included in the study. Of the enrolled patients, 1,987 (56%) were LTFU by the end of the study period. LTFU was highest in those ages<2 years and those ≥13 years (versus aged 2-12.9 years). Year of ART initiation was a strong predictor of LTFU across all age groups. For those patients retained to 12 months, less than half showed optimal adherence (≥95%). While there were no differences in adherence rates at month 12 by age group, those aged 10 years and older did have declining adherence starting at 18 months. Adherence is critical for optimal ART patient outcomes. We found both low adherence and high LTFU rates in our study cohort. Additional studies focused on barriers to adherence and development of age-specific intervention programs are critical to improving overall pediatric outcomes.
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We describe trends in characteristics and outcomes among adults initiating HIV care and treatment in Ethiopia from 2006-2011. We conducted a retrospective longitudinal analysis of HIV-positive adults (≥15 years) enrolling at 56 Ethiopian health facilities from 2006-2011. We investigated trends over time in the proportion enrolling through provider-initiated counseling and testing (PITC), baseline CD4+ cell counts and WHO stage. Additionally, we assessed outcomes (recorded death, loss to follow-up (LTF), transfer, and total attrition (recorded death plus LTF)) before and after ART initiation. Kaplan-Meier techniques estimated cumulative incidence of these outcomes through 36 months after ART initiation. Factors associated with LTF and death after ART initiation were estimated using Hazard Ratios accounting for within-clinic correlation. 93,418 adults enrolled into HIV care; 53,300 (57%) initiated ART. The proportion enrolled through PITC increased from 27.6% (2006-2007) to 44.8% (2010-2011) (p < .0001). Concurrently, median enrollment CD4+ cell count increased from 158 to 208 cells/mm(3) (p < .0001), and patients initiating ART with advanced WHO stage decreased from 56.6% (stage III) and 15.0% (IV) in 2006-2007 to 47.6% (stage III) and 8.5% (IV) in 2010-2011. Median CD4+ cell count at ART initiation remained stable over time. 24% of patients were LTF before ART initiation. Among those initiating ART, attrition was 30% after 36 months, with most occurring within the first 6 months. Recorded death after ART initiation was 6.4% and 9.2% at 6 and 36 months, respectively, and decreased over time. Younger age, male gender, never being married, no formal education, low CD4+ cell count, and advanced WHO stage were associated with increased LTF. Recorded death was lower among younger adults, females, married individuals, those with higher CD4+ cell counts and lower WHO stage at ART initiation. Over time, enrollment in HIV care through outpatient PITC increased and patients enrolled into HIV care at earlier disease stages across all HIV testing points. However, median CD4+ cell count at ART initiation remained steady. Pre- and post-ART attrition (particularly in the first 6 months) have remained major challenges in ensuring prompt ART initiation and retention on ART.
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The National AIDS Control Organization (NACO) of India has been providing free ARV (antiretroviral) drugs since 2004. b0 y 2012, 486,173 patients had received treatment through the antiretroviral therapy (ART) centres. The objective of this observational study was to assess the factors determining survival of patients on ART under routine programme conditions in an ART centre in north India five years after its inception. Treatment naive HIV positive patients who were enrolled in the ART centre between May 2009 and May 2010 and started on ART as per the Revised NACO guidelines 2009, were included in the study and outcome was assessed after two years of follow up. A total of 1689 patients were included in the analysis, of whom 272 (16.10%) expired, 205 (12.13%) were lost to follow up (LFU), 526 (31.14%) were transferred out to other facilities and 686 (40.63%) were alive at the end of two years. Majority (92%) of the deaths occurred in the first six months of therapy. Age >30 yr, male gender, poor functional status, haemoglobin level <11 g/dl, body weight <45 kg and CD4 count <100/μl at baseline had significantly higher relative hazard of death. Most LFU also occurred in the first six months and these patients had significantly low CD4 count, weight, haemoglobin level and higher number of patients in Stages III and IV as compared to those who survived. The study findings revealed poor survival in the first six months of therapy especially in those with severe immunosuppression. This emphasizes the need for early enrolment into the programme. The high LFU occurring early after initiation of therapy suggests the urgent need to build an efficient patient retrieval system in the programme.
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HIV treatment requires lifelong adherence to medication regimens that comprise inconvenient scheduling, adverse side effects, and lifestyle changes. Antiretroviral adherence and treatment fatigue have been inextricably linked. Adherence in HIV-infected populations has been well investigated; however, little is known about treatment fatigue. This review examines the current state of the literature on treatment fatigue among HIV populations and provides an overview of its etiology and potential consequences. Standard systematic research methods were used to gather published papers on treatment fatigue and HIV. Five databases were searched using PRISMA criteria. Of 1557 studies identified, 21 met the following inclusion criteria: (a) study participants were HIV-infected; (b) participants were prescribed antiretroviral medication; (c) the article referenced treatment fatigue; (d) the article was published in a peer-reviewed journal; and (e) text was available in English. Only seven articles operationally defined treatment fatigue, with three themes emerging throughout the definitions: (1) pill burden; (2) loss of desire to adhere to the regimen; and (3) nonadherence to regimens as a consequence of treatment fatigue. Based on these studies, treatment fatigue may be defined as "decreased desire and motivation to maintain vigilance in adhering to a treatment regimen among patients prescribed long-term protocols." The cause and course of treatment fatigue appear to vary by developmental stage. To date, only structured treatment interruptions have been examined as an intervention to reduce treatment fatigue in children and adults. No behavioral interventions have been developed to reduce treatment fatigue. Further, only qualitative studies have examined treatment fatigue conceptually. Studies designed to systematically assess treatment fatigue are needed. Increased understanding of the course and duration of treatment fatigue is expected to improve adherence interventions, thereby improving clinical outcomes for individuals living with HIV.
Background: Few interventions have been shown to improve retention in HIV care, and none have targeted the hospitalized patient. Peer mentoring has not been rigorously tested. Methods: We conducted a randomized, controlled clinical trial of a peer mentor intervention. Eligible adults were hospitalized, and were either newly diagnosed with HIV infection or were out of care. The intervention, based on the information, motivation, and behavioral skills model, included two in-person sessions with a volunteer peer mentor while hospitalized, followed by 5 phone calls in the 10 weeks after discharge. The control intervention provided didactic sessions on avoiding HIV transmission on the same schedule. The primary outcome was a composite of retention in care (completed HIV primary care visits within 30 days and between 31 and 180 days after discharge) and VL improvement (≥1 log10 decline) 6 months after discharge. Results: We enrolled 460 participants in 3 years; 417 were in the modified intent-to-treat analysis. The median age was 42 years; 74% were male; and 67% non-Hispanic black. Baseline characteristics did not differ between the randomized groups. Twenty-eight percent of the participants in both arms met the primary outcome (P=0.94). There were no differences in pre-specified secondary outcomes, including retention in care and VL change. Post-hoc analyses indicated interactions between the intervention and length of hospitalization and between the intervention and receipt of linkage services before discharge. Conclusions: Peer mentoring did not increase re-engagement in outpatient HIV care among hospitalized, out-of-care persons. Enhanced interventions that address systemic barriers warrant further study.
Objective: Disclosure may affect adherence to antiretroviral treatment. In a medication adherence program, this cross-sectional study describes disclosure, perceived reaction after disclosure, living situations, and the relationship of disclosure with antiretroviral adherence. Methods: A combination of a questionnaire to measure disclosure and longitudinal electronic monitoring of medication adherence was used. Results: A total of 103 out of 159 eligible patients gave informed consent. The characteristics differed between participants and nonparticipants (race, education, sexual orientation, medication adherence). Thirteen participants did not disclose their HIV status. Seventy-three (81%) participants judged the reaction after disclosure positive. Among the 62 participants cohabiting, 52% disclosed to all co-residents. Adherence was high (median 100%). HIV disclosure was negatively associated with adherence, when disclosing to the mother (OR=2.46, p-value=0.086) and to siblings (OR=2.89, p-value=0.029). Living alone was associated to a lower adherence than cohabitation (Rate Ratio=1.42, p-value=0.007). Conclusion: HIV disclosure and adherence are sensitive issues, which may explain the reason for refusal. Nonparticipants may be those with the most difficulties disclosing. Practice implications: An unbiased collection of sensitive information, as HIV disclosure, is a difficult task. A cohort design, with research data collected systematically by a trusted healthcare provider, may better describe the association between adherence and disclosure.
Objective: The benefits of HAART rely on continuous lifelong treatment retention. We used linked population-level health administrative data to characterize durations of HAART retention and nonretention. Design: This is a retrospective cohort study. Methods: We considered individuals initiating HAART in British Columbia (1996-2012). An HAART episode was considered discontinued if individuals had a gap of at least 30 days between days in which medication was prescribed. We considered durations of HAART retention and nonretention separately, and used Cox proportional hazards frailty models to identify demographic and treatment-related factors associated with durations of HAART retention and nonretention. Results: Six thousand one hundred fifty-two individuals were included in the analysis; 81.2% were male, 40.6% were people who inject drugs, and 42.8% initiated treatment with CD4 cell count less than 200 cells/μl. Overall, 29% were continuously retained on HAART through the end of follow-up. HAART episodes were a median 6.8 months (25th, 75th percentile: 2.3, 19.5), whereas off-HAART episodes lasted a median 1.9 months (1.2, 4.5). In Cox proportional hazards frailty models, durations of HAART retention improved over time. Successive treatment episodes tended to decrease in duration among those with multiple attempts, whereas off-HAART episodes remained relatively stable. Younger age, earlier stages of disease progression, and injection drug use were all associated with shorter durations of HAART retention and longer off-HAART durations. Conclusion: Metrics to monitor HAART retention, dropout, and reentry should be prioritized for HIV surveillance. Clinical strategies and public health policies are urgently needed to improve HAART retention, particularly among those at earlier stages of disease progression, the young, and people who inject drugs.