- Email: [email protected]
Screening HIV-associated neurocognitive disorders (HAND) among HIV positive patients attending antiretroviral therapy in South Wollo, Ethiopia
Accepted Manuscript Screening HIV-associated neurocognitive disorders (HAND) among HIV positive patients attending antiretroviral therapy in South Wollo, Ethiopia Million Tsegaw, Gashaw Andargie, Getnet Alem, Minale Tareke PII:
S0022-3956(16)30537-4
DOI:
10.1016/j.jpsychires.2016.10.016
Reference:
PIAT 2993
To appear in:
Journal of Psychiatric Research
Received Date: 21 June 2016 Revised Date:
15 October 2016
Accepted Date: 20 October 2016
Please cite this article as: Tsegaw M, Andargie G, Alem G, Tareke M, Screening HIV-associated neurocognitive disorders (HAND) among HIV positive patients attending antiretroviral therapy in South Wollo, Ethiopia, Journal of Psychiatric Research (2016), doi: 10.1016/j.jpsychires.2016.10.016. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
1
Screening HIV-associated neurocognitive disorders (HAND) among HIV positive
2
patients attending antiretroviral therapy in South Wollo, Ethiopia
RI PT
3
Million Tsegaw 1, Gashaw Andargie2, Getnet Alem3, *Minale Tareke4
5
1
Department of Psychiatry, Dessie Referral Hospital, Dessie, Ethiopia
6
2
Institute of Public Health, College of Medicine and Health Science, University of Gondar,
7
Gondar, Ethiopia
8
3
9
Ethiopia. 4
Research and Training directorate, Amanuel Mental Specialized Hospital, Addis Ababa,
M AN U
10
SC
4
Bahir Dar University, College of Medicine and Health science, Bahir Dar, Ethiopia,
11
* Corresponding author
13
P.O. Box +251 79, Bahir Dar, Ethiopia
14
TE D
12
Email addresses: [email protected], [email protected] ,[email protected],
16
[email protected]
18 19 20
AC C
17
EP
15
21 22 23
1
ACCEPTED MANUSCRIPT
ABSTRACT
25
Background: The vast majority of people living with HIV/AIDS reside in low and middle
26
income countries, particularly in Sub-Saharan Africa, including Ethiopia. Despite the huge
27
number of service users in the local area, cognitive disorder among HIV patients has not been
28
extensively studied and there is a dearth of knowledge on the subject. The objective of this study
29
was to assess the prevalence and associated factors of HIV-associated neurocognitive disorder
30
among people living with HIV/AIDS in antiretroviral therapy (ART) clinics. Methods:
31
Institution based cross sectional study was conducted from April to May, 2015 at Dessie Referral
32
Hospital & Kombolcha Health Center. International HIV Dementia Scale was used to screen
33
HIV associated neurocognitive deficits. Logistic regression analysis was used to assess
34
predictors of neurocognitive disorders. Result: The risk of HIV associated neurocognitive
35
disorder was 36.4%. Those who had CD4 count of 500 cells/dl or less (AOR =2.368(1.524,
36
3.680)), no formal education (AOR =4.287(2.619, 7.016)), poor medication adherence (AOR =
37
1.487(1.010, 2.180)) and older age (AOR =3.309(1.259, 8.701)) were found to be significantly
38
associated with HIV associated neurocognitive disorders. Conclusion: The risk of HIV-
39
associated neurocognitive disorder was found to be high among people living with HIV/AIDS.
40
This emphasizes the need of regular cognitive screening for early identification and appropriate
41
intervention.
43
SC
M AN U
TE D
EP
AC C
42
RI PT
24
Key words: HIV, people living with HIV/AIDS, HIV-associated neurocognitive disorder
44 45 46 47 2
ACCEPTED MANUSCRIPT
48
Introduction
49
Global statistics estimated that 35 million people were living with Human Immunodeficiency
51
Virus/Acquired Immuno Deficiency Syndrome (HIV/AIDS) in 2013, of which 24.7 million live
52
in Sub-Sahara Africa/resource limited settings/ where little HIV neurology research is conducted
53
(Meyer AC, 2014).
54
In Ethiopia, according to 2007 single point estimate, about 1.12 million people were living with
55
HIV in 2009, of which 336,160 were eligible for Highly Active Anti-retroviral Therapy
56
(HAART). There were an estimated of 131145 new infections and 44751 AIDS related
57
deaths(Hapco, 2010).
58
The human immunodeficiency virus (HIV) can cause a spectrum of neuropsychological
59
impairment known collectively as HIV-associated neurocognitive disorder (HAND).Though the
60
incidence of HIV-associated dementia has reduced in the HAART era; the prevalence of milder
61
forms of HAND has increased(Cross et al., 2013a, Nabha et al., 2013, Woods et al., 2009).
62
HIV-associated neurocognitive disorders (HAND) is used to describe a spectrum of disorders
63
that range from asymptomatic neurocognitive impairment to minor neurocognitive disorder to
64
clinically severe dementia. The most severe form HIV-associated dementia also referred to as the
65
AIDS dementia complex or HIV encephalopathy is considered an AIDS-defining illness(Fauci et
66
al., 2015).
67
HAND is characterized by impaired cognitive functioning and reduced mental activity that
68
interferes with work, domestic and social functioning. HAND and HIV/AIDS have complex and
69
bidirectional relationship, with reported neurocognitive impairment/cognitive deficits up to 99%
AC C
EP
TE D
M AN U
SC
RI PT
50
3
ACCEPTED MANUSCRIPT
in symptomatic patients and 33% in non-symptomatic cases. This dramatic impact of HIV/AIDS
71
left untreated; leading to decreased patient’s quality of life, reduced ability to perform daily
72
activities, poor medication adherence and shorter survival time(Larsson et al., 2009, Breuer et
73
al., 2011).
74
A population-based longitudinal cohort study conducted to determine the risk factors of HAND
75
among HIV-infected patients revealed that increased age, increased length of survival with
76
diagnose of HIV-1infection, low Cluster of Differentiation(CD4) cell counts, and high viral load
77
(>100,000copies/ml) had strong association with HAND(McCombe et al., 2013).
78
There are limited studies which showed the magnitude of HIV associated neurocognitive
79
disorders and associated factors among people living with HIV/AIDS (PLHA) in Sub-Saharan
80
region(Nakku et al., 2013), particularly in Ethiopia. The aim of this study was to determine the
81
magnitude and associated factors of HAND among PLHA. Hence, the findings might have
82
importance to stakeholders and policy makers working in neuro- psychiatric areas by showing its
83
prevalence and the factors associated with it.
84
METHODS
85
Study Settings and Population
86
A cross sectional study was conducted at Dessie Referral Hospital (DRH) and Kombolcha
87
Health Center (KHC) HIV care clinic. Dessie is located in South Wollo administrative zone,
88
Amhara, National Regional state, North East Ethiopia. Dessie is the capital town of South Wollo
89
zone, which is located 401 km Northeast of Addis Ababa (the capital city of Ethiopia). The town
90
has an estimated population of 279,423(2012) and has one public referral hospital, three general
91
private hospitals, and four government health centers, all are providing antiretroviral therapy
AC C
EP
TE D
M AN U
SC
RI PT
70
4
ACCEPTED MANUSCRIPT
(ART) services. Dessie Referral Hospital is the only referral hospital which serves for more than
93
five million people of the South Wollo zone and neighboring zones. Dessie Referral Hospital and
94
Kombolcha Health Center give service on average for 5100 and 3000 attendants monthly with
95
four delivery units, respectively.
96
The study population was PLHA aged between 18 to 65 years who had treatment follow up at
97
DRH and KHC ART clinic during study period. Those with severe medical illness related
98
/unrelated to HIV disease at the time of data collection, severe psychiatric disorders (e.g.,
99
schizophrenia), intellectual disability and physical disabilities (upper limb amputation/defect)
M AN U
SC
RI PT
92
were excluded from the study.
101
Sample size and Sampling procedures
102
The sample size was calculated using the formula [n = ((zα/2)2 p (1-p))/ d2] for estimating a
103
single population proportion at 95% confidence interval (CI) (Zα/2 = 1.96), 5% margin of error.
104
Proportion of population living with HIV and who had HAND was taken as 38%,(Lawler et al.,
105
2010a) and by adding 10% contingency for non response rate, a total of 595 study populations
106
were involved.
107
Data Collection and quality control
108
A structured questionnaire was used to collect data on socio-demographic characteristics and
109
clinical factors of HIV/AIDS. The International HIV Dementia Scale (IHDS) was used as a
110
screening tool to identify individuals who are at risk of HAND. The presence of HAND was
111
screened by the sum of a 3 item IHDS score of ≤9.5 in this study.
AC C
EP
TE D
100
112
5
ACCEPTED MANUSCRIPT
113
The IHDS consists of three subtests:
114
A. Timed finger tapping test: The number of finger taps of the first two fingers of the non-dominant hand is measured
116
by instructing the participant to open and close the fingers as widely and as quickly as
117
possible over a 5-second period.
RI PT
115
The finger tapping test is scored as follows :( 4 = 15 in 5 seconds, 3 = 11-14 in 5 seconds,
119
2 = 7-10 in 5 seconds, 1= 3-6 in 5 seconds, 0= 0-2 in 5 seconds)
SC
118
B. The alternating hand sequence test: Individual was asked to perform the following
121
movement with the non-dominant hand as quickly as possible over a 10s period;
M AN U
120
122
clench the hand in a fist on a flat surface;
123
put the hand flat on the surface with the palm down; and
124
Put the hand perpendicular to the flat surface on the side of the fifth digit. The three hand positions are demonstrated to the participant by the examiner, and the participant
126
was allowed to perform the sequence correctly twice for practice before the 10 second subtest is
127
performed. The number of sequences correctly performed within 10seconds up to a maximum
128
number of 4 is scored. A participant unable to perform the alternating hand sequence was
129
assigned a score of 0.
130
C. The verbal recall subset (Registration):
131
Registration (new learning) was also measured by reciting four words to the subject and then
132
asking him/her to repeat them immediately. The words are repeated by the examiner until the
133
subject can repeat all four words correctly. The subject was asked to recall the four words after
134
the timed finger tapping and alternating hand sequence tests.
AC C
EP
TE D
125
6
ACCEPTED MANUSCRIPT
The number of items recalled was scored out of 4. For words not recalled, the subject was
136
prompted with a ‘semantic’ clue as follows: Animal (dog), piece of clothing (hat), vegetable
137
(bean), and color (red).A half-point is assigned for each correct word recalled after prompting. A
138
total score out of 12 is calculated for each participant, with each of the three subtests contributing
139
4 points to the total score. Any participant with a score 9.5 or less was screened as risk for
140
HAND.
141
Adherence was assessed using Morsiky-8 item scale. The presence of poor adherence was
142
explained by sum of Morisky 8- item medication adherence scale score of 3-8.
143
Pre-coded and pre-tested Amharic version questionnaires were used to collect data by face to
144
face interviewing the participants. Three trained clinical nurses were recruited from Dessie
145
Health center for data collection and screening of people living with HIV/AIDS for HAND.
146
Data quality control issues were insured by conducting pre- test on 5% of the study participants.
147
Training was given for data collectors and supervisor on the questionnaire, how to screen HAND
148
using IHDS, the purpose of the study and how to approach respondents and obtain consent.
149
Filled questionnaires were checked daily for their completeness and consistency by the principal
150
investigator and supervisor.
SC
M AN U
TE D
EP
AC C
151
RI PT
135
152
Data management and analysis
153
The data was coded, checked, cleaned and entered into computers using software
154
epidemiological information (Epi- info) and then exported into statistical package for social
155
sciences (SPSS version 20) for analysis. The data was presented by mean, frequency, percentage
156
and odds ratio for different variables using descriptive statistics. Bivariate analysis was used to 7
ACCEPTED MANUSCRIPT
assess the relationship between each independent variables and outcome variable. Variables that
158
met p-value < 0.2 were selected for further analysis using multivariate logistic regression
159
analysis in order to control confounding effects.
160
RI PT
157
Ethical considerations
Ethical clearance was obtained from University of Gondar and Amanuel Mental Specialized
162
Hospital. A formal letter of permission was obtained from Amanuel Mental Specialized Hospital
163
and was submitted to Dessie Referral Hospital and Kombolcha Health Center. Each participant
164
was informed about the purpose of study. Confidentiality of respondents was maintained. An
165
informed consent was obtained from each respondent, following patient willingness data was
166
collected and any one not willing to take part in the study was not obliged at time of data
167
collection.
168
Results
169 170
Socio-demographic characteristics
171
Five hundred ninety three (593) people living with HIV/AIDS were involved in the study,
172
making the response rate of 99%. The mean age of the respondents were 38.6 ± 10.6 years.
173
Among the study participants 309(52.1%) were females and 377(63.6%) were married (table1).
174 175
HIV Associated Neurocognitive disorder (HAND)
176
Among the study participants who screened for HAND, 216(36.4%) of them had scored 9.5 or
177
less on IHDS. Procedural implementation of international HIV dementia scale (IHDS) was as
178
follows: The first measurement on IHDS was timed finger tapping, on this part motor speed was
179
assessed, 184(30.7%) were did very well scoring 4 out of 4. On the second part psychomotor
AC C
EP
TE D
M AN U
SC
161
8
ACCEPTED MANUSCRIPT
speed measurement was assessed, of whom 310 (52.3%) had performed the sequential procedure
181
scoring 4 out of 4.Thirdly, memory recall was assessed and was found as 368 (62.1%) had
182
recalled all the four items without any clue scoring 4 out of 4.
183 184
HAND and Clinical factors
185
Duration of being on HAART were also assessed, and was found that about 580(97.8%) had
186
been on HAART for more than 2 years (Table 2).
187 188
Factors associated with HAND
189
Bivariate and multivariate analysis showed that the association between HAND and age,
190
educational status, medication adherence and CD4 count were statistically significant. After
191
adjusting other variables(sex, ethnicity, religion, marital status, occupational status and clinical
192
factors like duration of taking HAART, clinical stage), the chance of having HAND among age
193
group 56-65(AOR=(3.309 CI(1.259,8.701)) was more likely as compared to age group 18-25
194
years. The multivariate analysis indicates that the risk of HAND was 3.3 times higher in those
195
participants having increased age.
196
This study also revealed that the likelihood of having the risk of HAND among PLHA was twice
197
in primarily educated participants (AOR= 2.005 CI (1.343, 2.994)) and/ or was around four times
198
in those who cannot read & write (AOR= 4.287 CI (2.619, 7.016)) as compared to those
199
educated secondary and above.
200
Participants who had poor medication adherence to ART, the odds of developing the risk of
201
HAND was 1.48 times higher (AOR = 1.487 CI (1.010, 2.180)). Similarly, having CD4 count of
RI PT
180
AC C
EP
TE D
M AN U
SC
The clinical data reviewed during the time of study showed that 411 (69.3%) had HIV stage T1.
9
ACCEPTED MANUSCRIPT
<= 500cells/µl were around twice more likely to have the risk of HAND (AOR =2.368 CI
203
(1.524, 3.680)) when compared to those with CD4 count of >500cells/µl (Table 3).
204 205
Discussion
206
In this study, the risk of HAND among people living with HIV/AIDS was 36.4% by using
207
international HIV dementia scale (IHDS) as screening tool and IHDS performance was greatly
208
influenced by increased age, no or low level of education, lower CD4 count and poor medication
209
adherence.
SC
RI PT
202
M AN U
210
The finding of this study was in line with the study done in Botswana (38%)(Chibanda et al.,
212
2014), in Thailand (37.5%) (Heaps et al., 2013), and in China (37.31%) (Zhang et al., 2012) were
213
found to have HAND. In all cases, the common predictors explained were older age, no or low
214
level of education, lower CD4 count and poor medication adherence.
215
However, the risk of HAND in the current study was higher than a cross-sectional study done in
216
Singapore (22.7%)(Chan et al., 2012), in Malawi (15%)(Kelly et al., 2014), in Cameroon
217
(21.1%) (Njamnshi
218
(24.8%)(Mossie TB et al., 2014).The differences might be accounted to the neurovirulence strain
219
differences, older age, being unable to read and write notified as a more powerful predictors.
220
On the other hand, this study was lower than study done in United State (52%), a prospective
221
cross-sectional study at Washington University Hospital (41%) (Cross et al., 2013b), in Uganda
222
(64.4%)(Nakku et al., 2013), and in Switzerland (83%) (Fasel et al., 2014). The discrepancy in
223
the prevalence rate might be accounted to the neurovirulence strain/clade/ differences, the
224
differences in the common predictors for the development of HAND as stated by lower CD4
TE D
211
AC C
EP
et al., 2008) ,and at Debre markos Hospital, Northwest Ethiopia
10
ACCEPTED MANUSCRIPT
count ,no or low level of education, and poor medication adherence. Other possible reasons for
226
the differences between the present study and other studies were mainly due to differences in the
227
method, using different cut-off points, consequences of unappreciated cultural nuances,
228
differences in the sample size used and certain environmental factors. The discrepancies might
229
also be explained from the difference in study population and demographic characteristics which
230
play a great role in the development of HAND
231
In this study, HAND was significantly associated with age group ranged 56-65 years which was
232
nearly consistent with the study done in Kenya and Botswana(Lawler et al., 2010b, Chibanda et
233
al., 2014).
234
Regarding educational level, being unable to read and write was significantly associated with
235
higher risk of developing HAND which was in line with the Sub-Saharan countries findings
236
(Breuer et al., 2011, Cross et al., 2013b).This might be because of better neuropsychological
237
test performance; better awareness about the chronic course of the illness and good follow-up
238
resulted in good medication (ART) adherence.
239
In the present study, there was statistically significant association between the clinical factors
240
like low CD4 count and poor medication adherence. This finding is supported by other studies,
241
as studies demonstrate that these factors, were the predictive variables in the development of
242
HAND in the setting where universal access to care and treatment available(McCombe et al.,
243
2013, Fasel et al., 2014).
244
Overall; the results of the present study provides additional information to assist with screening
245
of HAND to local area. The finding also gives key information about the impact of HAND on
246
socio-demographic variables, clinical and other related factors. Collectively, this work facilitates
AC C
EP
TE D
M AN U
SC
RI PT
225
11
ACCEPTED MANUSCRIPT
efforts to understand the neurological complications of HIV infection, which remains a global
248
concern.
249
Strengths and limitations of this study
250
The strength of this study is the first on HAND in a representative sample in Ethiopia and used a
251
method of screening that is applicable to local clinical practice. Although we used standard
252
morsiky-8 item scale for assessing adherence, we didn’t measure plasma drug concentrations.
253
Even if International HIV Dementia Scale is suited for screening HAND in resource limited
254
settings or in low- and middle income countries independent of language and culture, it is not
255
validated in Ethiopia
SC
M AN U
256
RI PT
247
Conclusion
The risk of HAND was found to be high among PLHA at Dessie Referral Hospital and
258
Kombolcha Health Center. Increased age, no or low level of education, lower CD4 count and
259
poor medication adherence were significantly associated with HAND. Screening of HIV
260
associated Neurocognitive disorders for all PLHA should be done for early diagnosis and
261
treatment in order to decrease/delay/ neurocognitive dysfunctions. This finding will provide a
262
foundation for future neurocognitive studies and clinical neurocognitive outcomes in HIV
263
clinics. In order to improve the detection of patients with clinically significant HAND in study
264
area, future research should address the wider impact of HAND using cohort study.
265
References
266 267 268 269
BREUER , E., MYER , L., STRUTHERS , H. & JOSKA , J. A. 2011. HIV/AIDS and mental health research in subSaharan Africa: a systematic review. . African Journal of AIDS Research. , 10, 101-122. CHAN , L. G., KANDIAH, N. & CHUA, A. 2012. HIV-associated neurocognitive disorders in a South Asian population:contextual application of the 2007 criteria. . BMJ open.
AC C
EP
TE D
257
12
ACCEPTED MANUSCRIPT
EP
TE D
M AN U
SC
RI PT
CHIBANDA, D., BENJAMIN , L., WEISS, H. A. & ABAS , M. 2014. Mental, neurological, and substance use disorders in people living with HIV/AIDS in low-and middle-income countries. JAIDS, 67, 554567. CROSS , H. M., COMBRINCK, M. I. & JOSKA, J. A. 2013a. HIV-associated neurocognitive disorders: Antiretroviral regimen, central nervous system penetration effectiveness, and cognitive outcomes. South African Medical Journal., 103, 758-762. CROSS , S., ÖNEN , N., GASE , A., OVERTON , E. T. & ANCES, B. M. 2013b. Identifying Risk Factors for HIVAssociated Neurocognitive Disorders Using the International HIV Dementia Scale. . J Neuroimmune Pharmacol, 8, 1114-22. FASEL , D., KUNZE, U., ELZI , L., WERDER , V., NIEPMANN , S. & MONSCH , A. U. E. A. 2014. A short tool to screen HIV-infected patients for mild neurocognitive disorders-a pilot study. BMC Psychology, 2. FAUCI, K., LONGO, H. & LOSCALZO, J. 2015. Harrison’s Principles of Internal Medicine, United States, McGraw-Hill Education. HAPCO, F. 2010. Report on Progress towards Implementation of the UN Declaration of Commitment on HIV/AIDS. AA: Federal ministry of health., 6-14. HEAPS, J., VALCOUR , V., CHALERMCHAI, T., PAUL, R., RATTANAMANEE, S. & SIANGPHOE , U., ET AL 2013. Development of normative neuropsychological performance inThailand for the assessment of HIV-associated neurocognitive disorders. . J Clin Exp Neuropsychol., 35, 1-8. KELLY , C. M., VAN OOSTERHOUT, J. J., NGWALO, C., STEWART, R. C. & BENJAMIN, L. E. A. 2014. HIV Associated Neurocognitive Disorders (HAND) in Malawian Adults and Effect on Adherence to Combination Anti-Retroviral Therapy. PLoS ONE., 9. LARSSON , B. O., SÄLL, L., SALAMON, E. & ALLGULANDER, C. 2009. HIV infection and psychiatric illness. . Afr J Psychiatry, 12, 115-128. LAWLER, K., MOSEPELE, M., RATCLIFFE, S., SELOILWE, E., STEELE, K., NTHOBATSANG, R. & STEENHOFF, A. 2010a. Neurocognitive impairment among HIV-positive individuals in Botswana: a pilot study. Journal of the International AIDS Society, 13. LAWLER, K., MOSEPELE , M., RATCLIFFE , S., SELOILWE, E., STEELE, K. & NTHOBATSANG† R, E. A. 2010b. Neurocognitive impairment among HIV-positive individuals in Botswana: a pilot study. Journal of the International AIDS Society, 13. MCCOMBE, J. A., VIVITHANAPORN, P., GILL , M. & POWER , C. 2013. Predictors of symptomatic HIVassociated neurocognitive disorders in universal health care. . HIV medicine, 14, 99-107. MEYER AC 2014. Neurology and the Global HIV Epidemic. Semin Neurol, 34, 70-77. MOSSIE TB, KASSA AW & TEGEGNE MT 2014. HIV dementia among HIV positive people at Debre markos hospital, Northwest Ethiopia. . American Journal of Psychiatry and Neuroscience, 2, 18-24. NABHA, L., DUONG, L. & TIMPONE , J. 2013. HIV-associated neurocognitive disorders: perspective on management strategies. . Drugs., 73, 893-905. NAKKU , J., KINYANDA , E. & HOSKINS , S. 2013. Prevalence and factors associated with probable HIV dementia in an African population : A cross-sectional study of an HIV / AIDS clinic population. BMC Psychiatry, 13, 126. NJAMNSHI , A. K., DJIENTCHEU VDE, P., FONSAH, J. Y., YEPNJIO, F. N., NJAMNSHI, D. M. & MUNA, W. E. 2008. The International HIV Dementia Scale is a useful screening tool for HIV-associated dementia/cognitive impairment in HIV-infected adults in Yaoundé-Cameroon. . J Acquir Immune Defic Syndr, 49, 393-7. WOODS , S. P., MOORE, D. J., WEBER , E. & GRANT, I. 2009. Cognitive neuropsychology of HIV-associated neurocognitive. disorders. . Neuropsychology review., 19, 152-168. ZHANG, Y., QIAO, L., DING , W., WEI , F., ZHAO, Q. & WANG, X. E. A. 2012. An initial screening for HIVassociated neurocognitive disorders of HIV-1 infected patients in China. . J Neurovirol. , 1-12.
AC C
270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316
13
ACCEPTED MANUSCRIPT
317
AC C
EP
TE D
M AN U
SC
RI PT
318
14
ACCEPTED MANUSCRIPT
Acknowledgements This study received financial support from University of Gondar and AMSH. We would like to thank Dessie Referral Hospital and Kombolcha health Center administrative and technical staffs
RI PT
for their indispensible co-operations before & during data collection. We are also grateful to the study participants without whom the current study would not have been realized. Finally, we
AC C
EP
TE D
M AN U
SC
would like to thank Bahir Dar University for facility to write up in appropriate manner.
1
ACCEPTED MANUSCRIPT
Table 1: Distribution of PLHA by their socio-demographic characteristics, DRRH & KHC, ART clinic, July 2015(n= 593).
Male
Frequency 284
Age
Female 18-25
309 40
26-35 36-45 46-55 56-65 Married Not married
237 167 82 67 377 216
Religion
Occupation
SC
40.0 28.2 13.8 11.3 63.6 36.4
No education Primary Secondary and above Orthodox Muslim Protestant Others Employed Unemployed
102 197 294 298 279 12 4 166 427
17.2 33.2 49.6 50.3 47.0 2.0 .7 28.0 72.0
Amhara Oromo Tigray Others
524 42 20 7
88.4 7.1 3.4 1.2
AC C
EP
Ethnicity
52.1 6.7
M AN U
Educational status
TE D
Marital status
Percent (%) 47.9
RI PT
Variables Sex
1
ACCEPTED MANUSCRIPT
Table 2: Distribution of PLHA by their clinical status at DRH & KHC, ART clinic, July 2015 (n=593).
T1
Percent (%)
411
69.3
58 116 8
CD4 count(cell/dl)
<=500 >500
361 232
Duration of taking HAART
<= 2years > 2years
13 580
Treatment by regimen
First line Second line
9.8 19.6 1.3 60.9 39.1
M AN U
Stage I Stage II Stage III
RI PT
Clinical stage
Frequency
SC
Variables
562 31
2.2 97.8
94.8 5.2
TE D
Table 3: Bivarate and multivariate analysis to show the association between socio-demographic and clinical factors with HAND among PLHA in DRH & KHC ART clinic, 2015 Variables
HAND
Yes No
1.00
9
31
1.00
26-35
88
149
2.077(0.915, 4.715)
36-45
78
89
2.073(0.896, 4.792)
46-55
45
37
2.979(1.223,7.252)
56-65
41
26
4.375(1.759,10.880)
3.309(1.259,8.701)*
71
31
4.171(2.598,6.598)
4.287(2.619,7.016)*
81
116
2.039(1.385,3.001)
2.005(1.343,2.994)
Secondary &above >500cell/µl
109
185
1.00
1.00
44
123
1.00
1.00
<=500cell/µl
217
209
0.447(0.299,0.670)
2.368(1.524,3.680)*
AC C
Educational Unable to read &write status Primary
CD4 count
AOR(95%CI)
18-25
EP
Age
COR(95%CI)
2
ACCEPTED MANUSCRIPT
Medication
Good
70
152
1.00
1.00
adherence
Poor
191
180
1.771(1.239,2.533)
1.487(1.010,2.180)*
RI PT
Note: * =p<0.05, 1.00 = Reference, COR = Crude odd ratio at 95 % CI, AOR =Adjusted odd
AC C
EP
TE D
M AN U
SC
ratio at 95 % CI.
3
S0022-3956(16)30537-4
DOI:
10.1016/j.jpsychires.2016.10.016
Reference:
PIAT 2993
To appear in:
Journal of Psychiatric Research
Received Date: 21 June 2016 Revised Date:
15 October 2016
Accepted Date: 20 October 2016
Please cite this article as: Tsegaw M, Andargie G, Alem G, Tareke M, Screening HIV-associated neurocognitive disorders (HAND) among HIV positive patients attending antiretroviral therapy in South Wollo, Ethiopia, Journal of Psychiatric Research (2016), doi: 10.1016/j.jpsychires.2016.10.016. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
1
Screening HIV-associated neurocognitive disorders (HAND) among HIV positive
2
patients attending antiretroviral therapy in South Wollo, Ethiopia
RI PT
3
Million Tsegaw 1, Gashaw Andargie2, Getnet Alem3, *Minale Tareke4
5
1
Department of Psychiatry, Dessie Referral Hospital, Dessie, Ethiopia
6
2
Institute of Public Health, College of Medicine and Health Science, University of Gondar,
7
Gondar, Ethiopia
8
3
9
Ethiopia. 4
Research and Training directorate, Amanuel Mental Specialized Hospital, Addis Ababa,
M AN U
10
SC
4
Bahir Dar University, College of Medicine and Health science, Bahir Dar, Ethiopia,
11
* Corresponding author
13
P.O. Box +251 79, Bahir Dar, Ethiopia
14
TE D
12
Email addresses: [email protected], [email protected] ,[email protected],
16
[email protected]
18 19 20
AC C
17
EP
15
21 22 23
1
ACCEPTED MANUSCRIPT
ABSTRACT
25
Background: The vast majority of people living with HIV/AIDS reside in low and middle
26
income countries, particularly in Sub-Saharan Africa, including Ethiopia. Despite the huge
27
number of service users in the local area, cognitive disorder among HIV patients has not been
28
extensively studied and there is a dearth of knowledge on the subject. The objective of this study
29
was to assess the prevalence and associated factors of HIV-associated neurocognitive disorder
30
among people living with HIV/AIDS in antiretroviral therapy (ART) clinics. Methods:
31
Institution based cross sectional study was conducted from April to May, 2015 at Dessie Referral
32
Hospital & Kombolcha Health Center. International HIV Dementia Scale was used to screen
33
HIV associated neurocognitive deficits. Logistic regression analysis was used to assess
34
predictors of neurocognitive disorders. Result: The risk of HIV associated neurocognitive
35
disorder was 36.4%. Those who had CD4 count of 500 cells/dl or less (AOR =2.368(1.524,
36
3.680)), no formal education (AOR =4.287(2.619, 7.016)), poor medication adherence (AOR =
37
1.487(1.010, 2.180)) and older age (AOR =3.309(1.259, 8.701)) were found to be significantly
38
associated with HIV associated neurocognitive disorders. Conclusion: The risk of HIV-
39
associated neurocognitive disorder was found to be high among people living with HIV/AIDS.
40
This emphasizes the need of regular cognitive screening for early identification and appropriate
41
intervention.
43
SC
M AN U
TE D
EP
AC C
42
RI PT
24
Key words: HIV, people living with HIV/AIDS, HIV-associated neurocognitive disorder
44 45 46 47 2
ACCEPTED MANUSCRIPT
48
Introduction
49
Global statistics estimated that 35 million people were living with Human Immunodeficiency
51
Virus/Acquired Immuno Deficiency Syndrome (HIV/AIDS) in 2013, of which 24.7 million live
52
in Sub-Sahara Africa/resource limited settings/ where little HIV neurology research is conducted
53
(Meyer AC, 2014).
54
In Ethiopia, according to 2007 single point estimate, about 1.12 million people were living with
55
HIV in 2009, of which 336,160 were eligible for Highly Active Anti-retroviral Therapy
56
(HAART). There were an estimated of 131145 new infections and 44751 AIDS related
57
deaths(Hapco, 2010).
58
The human immunodeficiency virus (HIV) can cause a spectrum of neuropsychological
59
impairment known collectively as HIV-associated neurocognitive disorder (HAND).Though the
60
incidence of HIV-associated dementia has reduced in the HAART era; the prevalence of milder
61
forms of HAND has increased(Cross et al., 2013a, Nabha et al., 2013, Woods et al., 2009).
62
HIV-associated neurocognitive disorders (HAND) is used to describe a spectrum of disorders
63
that range from asymptomatic neurocognitive impairment to minor neurocognitive disorder to
64
clinically severe dementia. The most severe form HIV-associated dementia also referred to as the
65
AIDS dementia complex or HIV encephalopathy is considered an AIDS-defining illness(Fauci et
66
al., 2015).
67
HAND is characterized by impaired cognitive functioning and reduced mental activity that
68
interferes with work, domestic and social functioning. HAND and HIV/AIDS have complex and
69
bidirectional relationship, with reported neurocognitive impairment/cognitive deficits up to 99%
AC C
EP
TE D
M AN U
SC
RI PT
50
3
ACCEPTED MANUSCRIPT
in symptomatic patients and 33% in non-symptomatic cases. This dramatic impact of HIV/AIDS
71
left untreated; leading to decreased patient’s quality of life, reduced ability to perform daily
72
activities, poor medication adherence and shorter survival time(Larsson et al., 2009, Breuer et
73
al., 2011).
74
A population-based longitudinal cohort study conducted to determine the risk factors of HAND
75
among HIV-infected patients revealed that increased age, increased length of survival with
76
diagnose of HIV-1infection, low Cluster of Differentiation(CD4) cell counts, and high viral load
77
(>100,000copies/ml) had strong association with HAND(McCombe et al., 2013).
78
There are limited studies which showed the magnitude of HIV associated neurocognitive
79
disorders and associated factors among people living with HIV/AIDS (PLHA) in Sub-Saharan
80
region(Nakku et al., 2013), particularly in Ethiopia. The aim of this study was to determine the
81
magnitude and associated factors of HAND among PLHA. Hence, the findings might have
82
importance to stakeholders and policy makers working in neuro- psychiatric areas by showing its
83
prevalence and the factors associated with it.
84
METHODS
85
Study Settings and Population
86
A cross sectional study was conducted at Dessie Referral Hospital (DRH) and Kombolcha
87
Health Center (KHC) HIV care clinic. Dessie is located in South Wollo administrative zone,
88
Amhara, National Regional state, North East Ethiopia. Dessie is the capital town of South Wollo
89
zone, which is located 401 km Northeast of Addis Ababa (the capital city of Ethiopia). The town
90
has an estimated population of 279,423(2012) and has one public referral hospital, three general
91
private hospitals, and four government health centers, all are providing antiretroviral therapy
AC C
EP
TE D
M AN U
SC
RI PT
70
4
ACCEPTED MANUSCRIPT
(ART) services. Dessie Referral Hospital is the only referral hospital which serves for more than
93
five million people of the South Wollo zone and neighboring zones. Dessie Referral Hospital and
94
Kombolcha Health Center give service on average for 5100 and 3000 attendants monthly with
95
four delivery units, respectively.
96
The study population was PLHA aged between 18 to 65 years who had treatment follow up at
97
DRH and KHC ART clinic during study period. Those with severe medical illness related
98
/unrelated to HIV disease at the time of data collection, severe psychiatric disorders (e.g.,
99
schizophrenia), intellectual disability and physical disabilities (upper limb amputation/defect)
M AN U
SC
RI PT
92
were excluded from the study.
101
Sample size and Sampling procedures
102
The sample size was calculated using the formula [n = ((zα/2)2 p (1-p))/ d2] for estimating a
103
single population proportion at 95% confidence interval (CI) (Zα/2 = 1.96), 5% margin of error.
104
Proportion of population living with HIV and who had HAND was taken as 38%,(Lawler et al.,
105
2010a) and by adding 10% contingency for non response rate, a total of 595 study populations
106
were involved.
107
Data Collection and quality control
108
A structured questionnaire was used to collect data on socio-demographic characteristics and
109
clinical factors of HIV/AIDS. The International HIV Dementia Scale (IHDS) was used as a
110
screening tool to identify individuals who are at risk of HAND. The presence of HAND was
111
screened by the sum of a 3 item IHDS score of ≤9.5 in this study.
AC C
EP
TE D
100
112
5
ACCEPTED MANUSCRIPT
113
The IHDS consists of three subtests:
114
A. Timed finger tapping test: The number of finger taps of the first two fingers of the non-dominant hand is measured
116
by instructing the participant to open and close the fingers as widely and as quickly as
117
possible over a 5-second period.
RI PT
115
The finger tapping test is scored as follows :( 4 = 15 in 5 seconds, 3 = 11-14 in 5 seconds,
119
2 = 7-10 in 5 seconds, 1= 3-6 in 5 seconds, 0= 0-2 in 5 seconds)
SC
118
B. The alternating hand sequence test: Individual was asked to perform the following
121
movement with the non-dominant hand as quickly as possible over a 10s period;
M AN U
120
122
clench the hand in a fist on a flat surface;
123
put the hand flat on the surface with the palm down; and
124
Put the hand perpendicular to the flat surface on the side of the fifth digit. The three hand positions are demonstrated to the participant by the examiner, and the participant
126
was allowed to perform the sequence correctly twice for practice before the 10 second subtest is
127
performed. The number of sequences correctly performed within 10seconds up to a maximum
128
number of 4 is scored. A participant unable to perform the alternating hand sequence was
129
assigned a score of 0.
130
C. The verbal recall subset (Registration):
131
Registration (new learning) was also measured by reciting four words to the subject and then
132
asking him/her to repeat them immediately. The words are repeated by the examiner until the
133
subject can repeat all four words correctly. The subject was asked to recall the four words after
134
the timed finger tapping and alternating hand sequence tests.
AC C
EP
TE D
125
6
ACCEPTED MANUSCRIPT
The number of items recalled was scored out of 4. For words not recalled, the subject was
136
prompted with a ‘semantic’ clue as follows: Animal (dog), piece of clothing (hat), vegetable
137
(bean), and color (red).A half-point is assigned for each correct word recalled after prompting. A
138
total score out of 12 is calculated for each participant, with each of the three subtests contributing
139
4 points to the total score. Any participant with a score 9.5 or less was screened as risk for
140
HAND.
141
Adherence was assessed using Morsiky-8 item scale. The presence of poor adherence was
142
explained by sum of Morisky 8- item medication adherence scale score of 3-8.
143
Pre-coded and pre-tested Amharic version questionnaires were used to collect data by face to
144
face interviewing the participants. Three trained clinical nurses were recruited from Dessie
145
Health center for data collection and screening of people living with HIV/AIDS for HAND.
146
Data quality control issues were insured by conducting pre- test on 5% of the study participants.
147
Training was given for data collectors and supervisor on the questionnaire, how to screen HAND
148
using IHDS, the purpose of the study and how to approach respondents and obtain consent.
149
Filled questionnaires were checked daily for their completeness and consistency by the principal
150
investigator and supervisor.
SC
M AN U
TE D
EP
AC C
151
RI PT
135
152
Data management and analysis
153
The data was coded, checked, cleaned and entered into computers using software
154
epidemiological information (Epi- info) and then exported into statistical package for social
155
sciences (SPSS version 20) for analysis. The data was presented by mean, frequency, percentage
156
and odds ratio for different variables using descriptive statistics. Bivariate analysis was used to 7
ACCEPTED MANUSCRIPT
assess the relationship between each independent variables and outcome variable. Variables that
158
met p-value < 0.2 were selected for further analysis using multivariate logistic regression
159
analysis in order to control confounding effects.
160
RI PT
157
Ethical considerations
Ethical clearance was obtained from University of Gondar and Amanuel Mental Specialized
162
Hospital. A formal letter of permission was obtained from Amanuel Mental Specialized Hospital
163
and was submitted to Dessie Referral Hospital and Kombolcha Health Center. Each participant
164
was informed about the purpose of study. Confidentiality of respondents was maintained. An
165
informed consent was obtained from each respondent, following patient willingness data was
166
collected and any one not willing to take part in the study was not obliged at time of data
167
collection.
168
Results
169 170
Socio-demographic characteristics
171
Five hundred ninety three (593) people living with HIV/AIDS were involved in the study,
172
making the response rate of 99%. The mean age of the respondents were 38.6 ± 10.6 years.
173
Among the study participants 309(52.1%) were females and 377(63.6%) were married (table1).
174 175
HIV Associated Neurocognitive disorder (HAND)
176
Among the study participants who screened for HAND, 216(36.4%) of them had scored 9.5 or
177
less on IHDS. Procedural implementation of international HIV dementia scale (IHDS) was as
178
follows: The first measurement on IHDS was timed finger tapping, on this part motor speed was
179
assessed, 184(30.7%) were did very well scoring 4 out of 4. On the second part psychomotor
AC C
EP
TE D
M AN U
SC
161
8
ACCEPTED MANUSCRIPT
speed measurement was assessed, of whom 310 (52.3%) had performed the sequential procedure
181
scoring 4 out of 4.Thirdly, memory recall was assessed and was found as 368 (62.1%) had
182
recalled all the four items without any clue scoring 4 out of 4.
183 184
HAND and Clinical factors
185
Duration of being on HAART were also assessed, and was found that about 580(97.8%) had
186
been on HAART for more than 2 years (Table 2).
187 188
Factors associated with HAND
189
Bivariate and multivariate analysis showed that the association between HAND and age,
190
educational status, medication adherence and CD4 count were statistically significant. After
191
adjusting other variables(sex, ethnicity, religion, marital status, occupational status and clinical
192
factors like duration of taking HAART, clinical stage), the chance of having HAND among age
193
group 56-65(AOR=(3.309 CI(1.259,8.701)) was more likely as compared to age group 18-25
194
years. The multivariate analysis indicates that the risk of HAND was 3.3 times higher in those
195
participants having increased age.
196
This study also revealed that the likelihood of having the risk of HAND among PLHA was twice
197
in primarily educated participants (AOR= 2.005 CI (1.343, 2.994)) and/ or was around four times
198
in those who cannot read & write (AOR= 4.287 CI (2.619, 7.016)) as compared to those
199
educated secondary and above.
200
Participants who had poor medication adherence to ART, the odds of developing the risk of
201
HAND was 1.48 times higher (AOR = 1.487 CI (1.010, 2.180)). Similarly, having CD4 count of
RI PT
180
AC C
EP
TE D
M AN U
SC
The clinical data reviewed during the time of study showed that 411 (69.3%) had HIV stage T1.
9
ACCEPTED MANUSCRIPT
<= 500cells/µl were around twice more likely to have the risk of HAND (AOR =2.368 CI
203
(1.524, 3.680)) when compared to those with CD4 count of >500cells/µl (Table 3).
204 205
Discussion
206
In this study, the risk of HAND among people living with HIV/AIDS was 36.4% by using
207
international HIV dementia scale (IHDS) as screening tool and IHDS performance was greatly
208
influenced by increased age, no or low level of education, lower CD4 count and poor medication
209
adherence.
SC
RI PT
202
M AN U
210
The finding of this study was in line with the study done in Botswana (38%)(Chibanda et al.,
212
2014), in Thailand (37.5%) (Heaps et al., 2013), and in China (37.31%) (Zhang et al., 2012) were
213
found to have HAND. In all cases, the common predictors explained were older age, no or low
214
level of education, lower CD4 count and poor medication adherence.
215
However, the risk of HAND in the current study was higher than a cross-sectional study done in
216
Singapore (22.7%)(Chan et al., 2012), in Malawi (15%)(Kelly et al., 2014), in Cameroon
217
(21.1%) (Njamnshi
218
(24.8%)(Mossie TB et al., 2014).The differences might be accounted to the neurovirulence strain
219
differences, older age, being unable to read and write notified as a more powerful predictors.
220
On the other hand, this study was lower than study done in United State (52%), a prospective
221
cross-sectional study at Washington University Hospital (41%) (Cross et al., 2013b), in Uganda
222
(64.4%)(Nakku et al., 2013), and in Switzerland (83%) (Fasel et al., 2014). The discrepancy in
223
the prevalence rate might be accounted to the neurovirulence strain/clade/ differences, the
224
differences in the common predictors for the development of HAND as stated by lower CD4
TE D
211
AC C
EP
et al., 2008) ,and at Debre markos Hospital, Northwest Ethiopia
10
ACCEPTED MANUSCRIPT
count ,no or low level of education, and poor medication adherence. Other possible reasons for
226
the differences between the present study and other studies were mainly due to differences in the
227
method, using different cut-off points, consequences of unappreciated cultural nuances,
228
differences in the sample size used and certain environmental factors. The discrepancies might
229
also be explained from the difference in study population and demographic characteristics which
230
play a great role in the development of HAND
231
In this study, HAND was significantly associated with age group ranged 56-65 years which was
232
nearly consistent with the study done in Kenya and Botswana(Lawler et al., 2010b, Chibanda et
233
al., 2014).
234
Regarding educational level, being unable to read and write was significantly associated with
235
higher risk of developing HAND which was in line with the Sub-Saharan countries findings
236
(Breuer et al., 2011, Cross et al., 2013b).This might be because of better neuropsychological
237
test performance; better awareness about the chronic course of the illness and good follow-up
238
resulted in good medication (ART) adherence.
239
In the present study, there was statistically significant association between the clinical factors
240
like low CD4 count and poor medication adherence. This finding is supported by other studies,
241
as studies demonstrate that these factors, were the predictive variables in the development of
242
HAND in the setting where universal access to care and treatment available(McCombe et al.,
243
2013, Fasel et al., 2014).
244
Overall; the results of the present study provides additional information to assist with screening
245
of HAND to local area. The finding also gives key information about the impact of HAND on
246
socio-demographic variables, clinical and other related factors. Collectively, this work facilitates
AC C
EP
TE D
M AN U
SC
RI PT
225
11
ACCEPTED MANUSCRIPT
efforts to understand the neurological complications of HIV infection, which remains a global
248
concern.
249
Strengths and limitations of this study
250
The strength of this study is the first on HAND in a representative sample in Ethiopia and used a
251
method of screening that is applicable to local clinical practice. Although we used standard
252
morsiky-8 item scale for assessing adherence, we didn’t measure plasma drug concentrations.
253
Even if International HIV Dementia Scale is suited for screening HAND in resource limited
254
settings or in low- and middle income countries independent of language and culture, it is not
255
validated in Ethiopia
SC
M AN U
256
RI PT
247
Conclusion
The risk of HAND was found to be high among PLHA at Dessie Referral Hospital and
258
Kombolcha Health Center. Increased age, no or low level of education, lower CD4 count and
259
poor medication adherence were significantly associated with HAND. Screening of HIV
260
associated Neurocognitive disorders for all PLHA should be done for early diagnosis and
261
treatment in order to decrease/delay/ neurocognitive dysfunctions. This finding will provide a
262
foundation for future neurocognitive studies and clinical neurocognitive outcomes in HIV
263
clinics. In order to improve the detection of patients with clinically significant HAND in study
264
area, future research should address the wider impact of HAND using cohort study.
265
References
266 267 268 269
BREUER , E., MYER , L., STRUTHERS , H. & JOSKA , J. A. 2011. HIV/AIDS and mental health research in subSaharan Africa: a systematic review. . African Journal of AIDS Research. , 10, 101-122. CHAN , L. G., KANDIAH, N. & CHUA, A. 2012. HIV-associated neurocognitive disorders in a South Asian population:contextual application of the 2007 criteria. . BMJ open.
AC C
EP
TE D
257
12
ACCEPTED MANUSCRIPT
EP
TE D
M AN U
SC
RI PT
CHIBANDA, D., BENJAMIN , L., WEISS, H. A. & ABAS , M. 2014. Mental, neurological, and substance use disorders in people living with HIV/AIDS in low-and middle-income countries. JAIDS, 67, 554567. CROSS , H. M., COMBRINCK, M. I. & JOSKA, J. A. 2013a. HIV-associated neurocognitive disorders: Antiretroviral regimen, central nervous system penetration effectiveness, and cognitive outcomes. South African Medical Journal., 103, 758-762. CROSS , S., ÖNEN , N., GASE , A., OVERTON , E. T. & ANCES, B. M. 2013b. Identifying Risk Factors for HIVAssociated Neurocognitive Disorders Using the International HIV Dementia Scale. . J Neuroimmune Pharmacol, 8, 1114-22. FASEL , D., KUNZE, U., ELZI , L., WERDER , V., NIEPMANN , S. & MONSCH , A. U. E. A. 2014. A short tool to screen HIV-infected patients for mild neurocognitive disorders-a pilot study. BMC Psychology, 2. FAUCI, K., LONGO, H. & LOSCALZO, J. 2015. Harrison’s Principles of Internal Medicine, United States, McGraw-Hill Education. HAPCO, F. 2010. Report on Progress towards Implementation of the UN Declaration of Commitment on HIV/AIDS. AA: Federal ministry of health., 6-14. HEAPS, J., VALCOUR , V., CHALERMCHAI, T., PAUL, R., RATTANAMANEE, S. & SIANGPHOE , U., ET AL 2013. Development of normative neuropsychological performance inThailand for the assessment of HIV-associated neurocognitive disorders. . J Clin Exp Neuropsychol., 35, 1-8. KELLY , C. M., VAN OOSTERHOUT, J. J., NGWALO, C., STEWART, R. C. & BENJAMIN, L. E. A. 2014. HIV Associated Neurocognitive Disorders (HAND) in Malawian Adults and Effect on Adherence to Combination Anti-Retroviral Therapy. PLoS ONE., 9. LARSSON , B. O., SÄLL, L., SALAMON, E. & ALLGULANDER, C. 2009. HIV infection and psychiatric illness. . Afr J Psychiatry, 12, 115-128. LAWLER, K., MOSEPELE, M., RATCLIFFE, S., SELOILWE, E., STEELE, K., NTHOBATSANG, R. & STEENHOFF, A. 2010a. Neurocognitive impairment among HIV-positive individuals in Botswana: a pilot study. Journal of the International AIDS Society, 13. LAWLER, K., MOSEPELE , M., RATCLIFFE , S., SELOILWE, E., STEELE, K. & NTHOBATSANG† R, E. A. 2010b. Neurocognitive impairment among HIV-positive individuals in Botswana: a pilot study. Journal of the International AIDS Society, 13. MCCOMBE, J. A., VIVITHANAPORN, P., GILL , M. & POWER , C. 2013. Predictors of symptomatic HIVassociated neurocognitive disorders in universal health care. . HIV medicine, 14, 99-107. MEYER AC 2014. Neurology and the Global HIV Epidemic. Semin Neurol, 34, 70-77. MOSSIE TB, KASSA AW & TEGEGNE MT 2014. HIV dementia among HIV positive people at Debre markos hospital, Northwest Ethiopia. . American Journal of Psychiatry and Neuroscience, 2, 18-24. NABHA, L., DUONG, L. & TIMPONE , J. 2013. HIV-associated neurocognitive disorders: perspective on management strategies. . Drugs., 73, 893-905. NAKKU , J., KINYANDA , E. & HOSKINS , S. 2013. Prevalence and factors associated with probable HIV dementia in an African population : A cross-sectional study of an HIV / AIDS clinic population. BMC Psychiatry, 13, 126. NJAMNSHI , A. K., DJIENTCHEU VDE, P., FONSAH, J. Y., YEPNJIO, F. N., NJAMNSHI, D. M. & MUNA, W. E. 2008. The International HIV Dementia Scale is a useful screening tool for HIV-associated dementia/cognitive impairment in HIV-infected adults in Yaoundé-Cameroon. . J Acquir Immune Defic Syndr, 49, 393-7. WOODS , S. P., MOORE, D. J., WEBER , E. & GRANT, I. 2009. Cognitive neuropsychology of HIV-associated neurocognitive. disorders. . Neuropsychology review., 19, 152-168. ZHANG, Y., QIAO, L., DING , W., WEI , F., ZHAO, Q. & WANG, X. E. A. 2012. An initial screening for HIVassociated neurocognitive disorders of HIV-1 infected patients in China. . J Neurovirol. , 1-12.
AC C
270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316
13
ACCEPTED MANUSCRIPT
317
AC C
EP
TE D
M AN U
SC
RI PT
318
14
ACCEPTED MANUSCRIPT
Acknowledgements This study received financial support from University of Gondar and AMSH. We would like to thank Dessie Referral Hospital and Kombolcha health Center administrative and technical staffs
RI PT
for their indispensible co-operations before & during data collection. We are also grateful to the study participants without whom the current study would not have been realized. Finally, we
AC C
EP
TE D
M AN U
SC
would like to thank Bahir Dar University for facility to write up in appropriate manner.
1
ACCEPTED MANUSCRIPT
Table 1: Distribution of PLHA by their socio-demographic characteristics, DRRH & KHC, ART clinic, July 2015(n= 593).
Male
Frequency 284
Age
Female 18-25
309 40
26-35 36-45 46-55 56-65 Married Not married
237 167 82 67 377 216
Religion
Occupation
SC
40.0 28.2 13.8 11.3 63.6 36.4
No education Primary Secondary and above Orthodox Muslim Protestant Others Employed Unemployed
102 197 294 298 279 12 4 166 427
17.2 33.2 49.6 50.3 47.0 2.0 .7 28.0 72.0
Amhara Oromo Tigray Others
524 42 20 7
88.4 7.1 3.4 1.2
AC C
EP
Ethnicity
52.1 6.7
M AN U
Educational status
TE D
Marital status
Percent (%) 47.9
RI PT
Variables Sex
1
ACCEPTED MANUSCRIPT
Table 2: Distribution of PLHA by their clinical status at DRH & KHC, ART clinic, July 2015 (n=593).
T1
Percent (%)
411
69.3
58 116 8
CD4 count(cell/dl)
<=500 >500
361 232
Duration of taking HAART
<= 2years > 2years
13 580
Treatment by regimen
First line Second line
9.8 19.6 1.3 60.9 39.1
M AN U
Stage I Stage II Stage III
RI PT
Clinical stage
Frequency
SC
Variables
562 31
2.2 97.8
94.8 5.2
TE D
Table 3: Bivarate and multivariate analysis to show the association between socio-demographic and clinical factors with HAND among PLHA in DRH & KHC ART clinic, 2015 Variables
HAND
Yes No
1.00
9
31
1.00
26-35
88
149
2.077(0.915, 4.715)
36-45
78
89
2.073(0.896, 4.792)
46-55
45
37
2.979(1.223,7.252)
56-65
41
26
4.375(1.759,10.880)
3.309(1.259,8.701)*
71
31
4.171(2.598,6.598)
4.287(2.619,7.016)*
81
116
2.039(1.385,3.001)
2.005(1.343,2.994)
Secondary &above >500cell/µl
109
185
1.00
1.00
44
123
1.00
1.00
<=500cell/µl
217
209
0.447(0.299,0.670)
2.368(1.524,3.680)*
AC C
Educational Unable to read &write status Primary
CD4 count
AOR(95%CI)
18-25
EP
Age
COR(95%CI)
2
ACCEPTED MANUSCRIPT
Medication
Good
70
152
1.00
1.00
adherence
Poor
191
180
1.771(1.239,2.533)
1.487(1.010,2.180)*
RI PT
Note: * =p<0.05, 1.00 = Reference, COR = Crude odd ratio at 95 % CI, AOR =Adjusted odd
AC C
EP
TE D
M AN U
SC
ratio at 95 % CI.
3