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Open Access

Peer-reviewed

Research Article

Correlates of the HIV-associated neurocognitive disorders among adults living with HIV in Dodoma region, central Tanzania: A cross-sectional study

Abstract

Background

HIV-associated neurocognitive disorders (HAND) continue to manifest despite advancements and improved antiretroviral therapy coverage. Neurocognitive impairment is a significant predictor of poor prognosis related to poor antiretroviral therapy adherence and retention in HIV care.

Methods

This cross-sectional study examined 397 participants attending cared for and treatment at Dodoma Regional Referral Hospital (DRRH) and selected by systematic sampling. The combination of Montreal Cognitive Assessment (MoCA), International HIV Dementia Scale (IHDS), and The Lawton Instrumental Activity of Daily Living (IADL) were used to assess HIV-associated neurocognitive disorders. Factors associated with HAND were determined using univariate and multivariable logistic regression.

Results

Of 397 participants, 234(59.1%) met the criteria for HAND with 231(58.2%) comprising asymptomatic neurocognitive disorder (ANI) or mild neurocognitive disorders (MND), and 3 (0.76%) HIV- associated dementia (HAD). Participants with HAND had significantly poorer performance in each cognitive domain on both MoCA and IHDS. Under multivariable regression, age of 55 years or above with Adjusted Odds Ratio (AOR): 3.5 (95%CI: 1.1, 11.6), p = 0.041 and female gender (AOR): 2.7 (95%CI: 1, 6, 4.5), p<0.001 were significantly associated with HAND. Adherence to antiretroviral therapy AOR: 0.4(95%CI: 0.2, 1.0), p = 0.044, and attaining primary education AOR: 0.3(95%CI: 0.1, 0.8), p = 0.01 or secondary education AOR: 0.1(95%CI: 0.03, 0.2), p<0.001 compared to having no formal education showed good cognitive performance.

Conclusion

HIV-associated neurocognitive disorders are common in HIV, especially ANI and MND, are common in HIV infected Tanzanians. Both socio-demographic and clinical variables influence neurocognitive functioning in this population. Screening for mild neurocognitive disorders may be indicated if effective treatment becomes available.

Citation: Nyundo AA (2023) Correlates of the HIV-associated neurocognitive disorders among adults living with HIV in Dodoma region, central Tanzania: A cross-sectional study. PLoS ONE 18(5): e0285761. https://doi.org/10.1371/journal.pone.0285761

Editor: Dured Dardari, Centre Hospitalier Sud Francilien, FRANCE

Received: July 12, 2022; Accepted: May 2, 2023; Published: May 25, 2023

Copyright: © 2023 Azan A. Nyundo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: Yes- The author A.A.N received funding for data collection process for the study from Fogarty International Center of the National Institutes of Health "https://www.fic.nih.gov/" under award number D43TW009775. The funders played no role in the study design, data collection and analysis, decision to publish, preparation of the manuscript or supporting for publication processing charges.

Competing interests: No-authors have no competing interests

Introduction

HIV-associated neurocognitive disorders (HAND) is a neurological complication attributable to HIV in the central nervous system (CNS), manifesting with deficits in memory, concentration, attention, and motor skills [1, 2]. For clinical and research purposes, FRASCATI criteria are widely used to categorize HAND into Asymptomatic Neurocognitive Impairment (ANI), Mild Neurocognitive Disorders (MND), and a more severe form called HIV-associated disorders (HAD) [3, 4].

Over three decades, the lifespan of people living with HIV (PLWH) has significantly improved with highly active antiretroviral therapy (HAART).

Furthermore, incidence of severe HAD has been reduced by ART; however, nearly half the population continues to present with some form of cognitive impairment within the spectrum of HAND [5].

The brain is the second most affected organ in HIV infection after the lungs; the cascade of events related to the pathogenesis of cognitive impairment commences during the early phases of HIV infection. The virus enters the brain parenchyma [6, 7] through the infected macrophages and lymphocytes or by the passage of cell-free virus and virus release from the infected endothelial cells [8]. The absence of overt neuropathologies that were common before the cART era suggests clinical presentation of HAND is attributed to functional alteration of neuronal connectivity as opposed to gross neuronal loss or encephalitis [9, 10].

HAND remains prevalent in the cART era, albeit with less advanced stages of HIV infection or severe neurocognitive impairment. Currently, the less severe ANI and MND are observed even among patients with high CD4+ count and undetectable viral load as opposed to pre- ART era, where low CD4+ count, low weight, and anemia were the significant risks for HAND [11]. Nadir CD4+ count, advanced age, hypertension, and dyslipidemia, hepatitis C co-infection (HCV), type of ART used, and psychosocial factors including depression, anxiety, and stigma also remain risk factors for HAND [12–15].

The interaction of sociodemographic and clinical factors adds to the complexity of understanding the course of HAND and offers challenges in diagnostic and designing intervention. This study therefore, examines with standard quantitative methods the prevalence of and risk factors for HAND among adult patients on ART attending an HIV specialty care clinic in the Dodoma region of Tanzania.

Materials and methods

Study design

This is a hospital clinic-based prospective observational cross-sectional, single site study.

Study settings

Dodoma is the capital of Tanzania, located in the central part of the country, with about 410,956 people as per the 2012 census [16]. The study was conducted in the Dodoma region’s main referral hospital, "Dodoma Regional and Referral Hospital" (DRRH). Care and treatment clinic (CTC) services are also conducted in the hospital five days a week, covering up to 100 patients a day coming mostly from Dodoma, and few come outside of Dodoma. Other services provided at the CTC include ART medications, HIV-related counseling services, routine investigations such as CD4+ count, viral load, general medical care, and medical referrals in case of need.

Study population and sampling

During the study period from March to June 2020, the CTC had enrolled10, 288 patients on ART, of whom 3,708 were available for participation. Using a Kish Leslie formula n = Z2p (1-p) /d2 for a single proportion, a sample size (n) of 384 was calculated, P estimated at 0.5. Z = 1.96, d = 0.05. A final sample size of 397 was attained through a systematic sampling procedure whereby attendance was used to identify and direct every third participant for an interview after inclusion and exclusion criteria were applied.

Inclusion/Exclusion criteria

We included all patients at least 18 years of age and being on ART for a minimum of six months. The participants must be able to provide informed consent with adequate vision, hearing, articulation, and without disability of any of the upper limbs for neurocognitive assessment. Those who could not read and write in English and Swahili were excluded from the study. We also excluded those with active CNS infection, known complications of previous CNS infection, neurological disorders, in active phase of a psychotic episode and also those with comorbid cardiometabolic conditions including hypertensive disorders, diabetes mellitus.

Data collection, variables, and measurements

Outcome variable.

HIV-associated neurocognitive disorders. The neurocognitive assessment was determined using the Swahili-translated Montreal Cognitive Assessment (MoCA) and International HIV dementia scale (IHDS).

A meta-analysis found that a cutoff point of 23/30 on MoCA has better diagnostic accuracy across all domains than the routinely used 26/30 cutoff score, especially in a population with less education [17]. The Swahili version of MoCA has acceptable reliability, a sensitivity of 70% and specificity of 60% for MCI and sensitivity of 72% and specificity for dementia in the rural Dodoma older adult population [18]. Since the population used was homogeneously made of older adults from the rural population without HIV, the results from this study were not used as comparative or control group for our relatively younger HIV population (mean age + 41 years). Nonetheless, the population could still demonstrate the effectiveness of the tools in an African population with low education. The instrument also has a receiver operating characteristic curve with an area under the curve of 0.71; MoCA has been widely used worldwide among people with or without symptomatic HAND [19] and is considered a practical screening tool for cognitive assessment in HIV-population [20].

HIV-associated neurocognitive impairment (HAND) was assessed using the combination of the score of Montreal Cognitive Assessment (MoCA), the International HIV-associated dementia scale (IHDS), and The Lawton Instrumental Activity of Daily Living (IADL). The combination of scores from each instrument provides the following categories.

No neurocognitive impairment.

Based on MoCA score ≥ 23 or IHDS score ≥ 10 and IADL score of ≥ 8.

Asymptomatic neurocognitive impairment (ANI) or Mild neurocognitive disorder (MND) is considered positive if the patient scores < 23 in MoCA and a score of <10 on IHDS and IADL score of ≥ 8.

HIV- Associated Dementia (HAD).

The patient had to score < 23 on MoCA, a score of < 10 on IHDS <10, and an IADL score of < 8.

MoCA assesses six key neurocognitive domains;1) visuospatial-executive with a total of five points comprising of clock drawing, trail making B task, and three-dimension cube copy; 2) naming of unfamiliar animals for a maximum of three points for accurate naming of each animal, language with the maximum of three points attained from sentence repetition for two points and a phonemic fluency task for one point: 3) short-term memory assessing delayed recall of words for a maximum of 5 points; 4) abstraction (verbal abstraction) for a maximum of 2 points; 5) attention and calculation assessing digits forward and backward, target detection using tapping and serial 7s subtraction for a maximum of 6 points; 6) and orientation of time and space for a maximum of 6 points [21].

As for IHDS, three main cognitive domains are assessed; memory recall, motor speed, and psychomotor speeds, each with a maximum score of four points, making a total score of twelve. IHDS has demonstrated its utility in screening for cognitive impairment screening in HIV, with good test-retest reliability and capacity to discriminate between the presence or absence of cognitive impairment 90% of the time [22]. This screening tool has gained a reputation for its good pooled sensitivity of 0.90 [95% confidence interval (CI), 0.88–0.91] and overall specificity of 0.96 (95% CI, 0.95–0.97) under summary receiver operation [23]. Compared to MoCA, which is more sensitive in screening milder forms of HAND, IHDS is more sensitive in screening for severe form of HAND [24].

The Lawton Instrumental activity of daily living (IADL) assessed the functional status of the patient’s capacity for self-care, which is usually impaired among patients diagnosed with HIV-associated dementia.

The scale assesses one’s ability for daily tasks such as laundry, handling finances, and using a telephone. Measuring eight domains of functioning provides early warning signs of functional decline and can be administered in 10 to 15 minutes. The good performance of IADLs is used as an indicator of corresponding cognitive health status with reliable integrity [25].

Independent variables.

Major depressive disorders and substance use and related disorders. The standardized instrument MINI International Neuropsychiatry Interview Schedule (MINI) was used to assess these variables. MINI has acceptably high validation and reliability scores. It can also be administered much shorter (mean 18.7 + 11.6 min, median 15 min) after a brief training session, clinicians can use it, and lay interviewers require more extensive training [26]. We only used the sub-scale of MDD and substance use disorders in the M.I.N.I because of their direct influence on neurocognitive performance in the HIV population [27–30].

Socio-demographic and clinical profiles were also included as explanatory variables; these include age (in years), marital status, gender, occupation (formal employment or no formal employment), years of formal education, living arrangement, most recent CD4+ count (cells/mm3), current viral load (detectable at ≥ 40 copies/ml), Hepatitis C virus (HCV) infection screening and Hepatitis B virus (HBV), type of ART regimen, HIV/AIDS clinical staging as per WHO criteria, duration of ART use (in years), Hemoglobin (HB) concentration in (mmol/L) and body mass index (BMI measured in Kg/m2.

Data collection and analysis.

The evidence-based researcher-designed questionnaire collected sociodemographic and clinical information of interest, while psychiatric diagnoses were assessed using MINI. Two bilingual groups were consulted to translate MoCA to Swahili and then back-translated to English while maintaining a similar meaning. Interviews were conducted by trained research assistants who took over forty-five working days to complete the assessment of 397 participants. The research assistants (RAs) were Medical Doctors by profession working as registrars at a referral psychiatric hospital. The RAs were trained for seven days on how to do the interview, administer and rating the study instruments including MINI, MoCA and IHDS. Pre and post training assessment of RAs was done to assess the level of knowledge and skills gained. Under observed setting, the trained assistants had to demonstrate their competency by correctly interviewing and administer study tools on at least ten HIV patients before commencing the actual data collection. Data were analyzed using SAS version 9.4. Descriptive statistics such as frequency and percentage to describe the categorical variables, while mean and standard deviation (SD) or median and interquartile ranges (IQR) were used for continuous variables and presented using tables and figures where appropriate. Frequencies and proportions were summarized in one decimal place while p-values were summarized into three decimal places (a p-value of <0.001 indicated values reaching this point or below).

A Chi-square test was computed to determine the association between socio-demographic, clinical variables, and neurocognitive impairment. At the same time, a t-test was used to determine the mean difference in neurocognitive scores between participants with HAND versus those without HAND across all cognitive domains for both MoCA and IHDS (See Table 3). Unadjusted binary logistic regression was done for preliminary analysis of factors associated with HAND, Thereafter; variables that reached an overall significance level of < 20% (p-value < 0.2) were computed under multivariable model to adjust for confounders. As most participants were negative for HBV/HCV and used only one type of ART regimen {Tenofovir (TDF) +Lamivudine (3TC) +Dolutegravir (DTG)}, these variables were not included in the logistic regression.

Ethical considerations and concerns.

The study was approved by the local IRB of the Dodoma University Ethical and Research Committee with reference UDOM/ DRP/134/VOL V/91 once the proposal was fully established and merited approval. Trained research assistants who are medical doctors at the level of registrar provided participants with accurate, detailed information regarding the study. If a participant suffered from a neurological, psychiatric, or any other medical disorder needing urgent treatments, they were referred to specialized care based on the locally agreed protocols. Written informed consent forms were provided for those who could read and write; otherwise witnessed verbal informed consent was to be used as an alternative. No minor was included in the study, if a participant could not consent due to medical or any other reason, a custodian or close relative provided the consent.

Results

Socio-demographic and clinical characteristics of the study population by HAND

Out of 397 participants, the majority (69.5%) were females, significantly more males were neurocognitively impairment compared to females (p<0.001). The mean age of the study population was 41.9(12.6) years compared to 43.8(11.8) and 38.8(13.4) years for those with and without HAND, respectively (p<0.001). Other factors significantly associated with HAND included occupation, marital status, and education level (p<0.001). As for the clinical profile, only non-adherence to ART had significantly higher proportions of HAND compared to those with good adherence (p = 0.050), refer (Tables 1 and 2).

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Table 1. Socio-demographic characteristics by HAND status of the study population (N = 397).

https://doi.org/10.1371/journal.pone.0285761.t001

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Table 2. Baseline clinical profile and major depressive disorders of the study participants, N(397).

https://doi.org/10.1371/journal.pone.0285761.t002

Prevalence of HIV-associated neurocognitive disorders by severity.

Out of three hundred and ninety-seven participants, 59.0% met the criteria for HAND on both MoCA and IHDS, of which 58.2% had either asymptomatic neurocognitive impairment (ANI) or mild neurocognitive impairment (MNI). In contrast, 0.8% had a severe form known as HIV-associated dementia (HAD), see Fig 1. Furthermore, there were 315(79.4%) and 266(67%) participants who met exclusive criteria of neurocognitive impairment for HIDS and MoCA, respectively, refer (Fig 1).

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Fig 1. Prevalence of HAND.

https://doi.org/10.1371/journal.pone.0285761.g001

The mean neurocognitive performance based on MoCA was 19.7 for the study population, while the participants with HAND had significantly lower scores of 16.7 compared to those without HAND, 24.0, p<0.001. The mean neurocognitive performance based on IHDS was 7.9 for the study population, while the participants with HAND had significantly lower scores of 6.9 compared to those without HAND, 9.3, p<0.001. Furthermore, participants with HAND have significantly poorer performance in each cognitive domain on both MoCA and IHDS, refer (Table 3).

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Table 3. Pattern of neurocognitive performance by cognitive domain based on MoCA and IHDS, N(397).

https://doi.org/10.1371/journal.pone.0285761.t003

Under logistic regression, being female AOR: 2.7(95%CI: 4.5, 1.9), p<0.001 was associated with poor cognitive functioning, while every higher increment in age category was significantly associated with neurocognitive impairment under unadjusted analysis although the association remained significant only for those with 55+ years and above AOR:3.5(95%CI:1.0,11.6), p = 0.04 under adjusted analysis. Adherence to ART AOR: 0.4(95%CI: 0.2, 1.0), p = 0.04, having attained primary education AOR: 0.3(95%CI: 0.1, 0.8), p = 0.01 or secondary education AOR: 0.09(95%CI: 0.03, 0.2), p<0.001 compared to having no formal education were all significantly associated with favorable cognitive performance, refer (Table 4).

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Table 4. Logistic regression for factors associated with HAND.

https://doi.org/10.1371/journal.pone.0285761.t004

Discussion

The high prevalence (58.2%) of either asymptomatic or mild neurocognitive impairment that we found in our HIV+ population was associated with advanced age, female sex, less education and ART adherence. With just about 1% met the criteria for HIV-associated dementia; this pattern reflects the effectiveness of HAART in reducing the severe forms of HAND while the prevalence of milder forms remain high, ranging between 21% to 81% [31, 32]. A higher prevalence of neurocognitive disorders in HIV has been reported elsewhere in sub-Saharan Africa. For example, a prevalence of 81.1% was reported from Eldoret, Kenya [24], 68.4% in Dar es Salaam Tanzania [33], and 68.6% in Kampala Uganda [34]. The use of a single screening instrument for neurocognitive function in most of these studies compared to the requirement to meet the criteria on both MoCA and IHDS in our study could explain the difference in prevalence rates. Conversely, a lower prevalence of HAND is reported when a comprehensive neuropsychological battery based on Frascati criteria is used; a meta-analysis shows a global prevalence of HAND to be 44.9%, with the specific a distribution of 26.2%, 8.5%, and 2.1% for ANI, MND and HAD, respectively [35].

Although 41% of the population did not meet the criteria for HAND, the overall mean neurocognitive scores of the whole population were below the cutoff point for IHDS (9.3) but not on MoCA (24.0). Furthermore, the participants with HAND had significantly lower scores than those without HAND across all cognitive domains on both tools, suggesting diffuse brain involvement related to global cognitive impairment. In HIV infection, subcortical brain structures are particularly vulnerable, especially at the early stages [36]; however, the cortical areas are also not spared as the infection progresses and may be linked with motor decline and subsequent cognitive dysfunction [37].

The mean scores of the study population were below the set cut-off point on both IHDS and MoCA; also, more participants (79%) met the criteria for neurocognitive impairment on IHDS compared to 67% on MoCA. This observation may imply the distinct capacity of IHDS to assess specific cognitive domains such as the motor and psychomotor speed that were poorly performed by our participants in general but are not assessed in the MoCA. These specific deficits may suggest an involvement in subcortical structures which are particularly vulnerable in HIV infection and may indicate severe cognitive impairment. Higher proportion of positive screening on IHDS than MoCA may also suggests that the cognitive scores were skewed towards a more severe cognitive impairment within the spectrum of ANI to MND regardless of just about 1% meeting the criteria for most severe form of HAND known as HIV associated Dementia [24].

Regression analyses found that being female and older were significantly associated with neurocognitive impairment. Women had poor cognitive functioning compared to male, especially in speed of information processing (SIP), memory, and motor functions [38]. The sex difference in neurocognitive impairment is attributed to cognitive reserve, mental health, and other comorbidities and biological factors [38].

The cognitive reserve is a factor in determining neurocognitive impairment when the brain is traumatized [39, 40]; compared to men, women living with HIV tend to have lower cognitive reserve that is influenced by a sex difference in psychological risk factors which are synergistically or additive to low cognitive reserve prior to HIV infection and set precedence for neurocognitive impairment after the infection [41, 42]. These factors include low education, poverty, depression, barriers to healthcare and early life trauma which are more common among women than men [43, 44].

Stress and early life trauma as well as mental health disorders tend to affect neurocognitive functioning more in women living with HIV than in men; evidence supports that anxiety, depression, PTSD, and perceived stress are all associated with deficits in memory, learning, and attention [45–48].

The gender differences in neurocognitive performance in HIV could also be linked to endocrinological and immunological factors. Generally, sex steroids, including estradiol, progesterone, and testosterone can influence neurocognitive performance in a healthy population and their optimal levels are linked to good verbal performance in females and visual-spatial performance in males [38]. Specific female-related factors, including menstrual cycle, menopause, and pregnancy, bring complex dynamics that influence neurocognitive performance [49] even more. In HIV, through viral suppression and replications, estradiol is directly linked to transcriptional activities that affect neurocognitive activities [50, 51]. Indeed, both progesterone and estradiol impact immunomodulatory mechanisms through chemokine and cytokines, which also influence neurocognitive functioning [52]. Emerging evidence highlights sex differences in immune function and sex-specific genetic determinants of immune response to HIV infection [53] with variation in pathogenesis-related to chronic immune activation linked to HIV-induced neurotoxicity and eventual neurocognitive decline [54, 55]. Although evidence is not well established, the sex difference in monocyte-associated inflammatory biomarkers has been observed. For example, females have higher levels of sCD163 than males [56, 57]. Also, Neopterine, a marker of cellular immune activation whose CSF levels are generally associated with NCI, their plasma concentration appears to be associated with NCI only in WLWH but not in MLWH [58–61].

In this study, age was also significantly associated with poor neurocognitive deficits. While the overall age group was associated with poor cognitive performance at univariate analysis, only those above the age of 55 years were significantly associated with neurocognitive impairment when adjusted for confounding variables. As HIV/AIDS is now considered a chronic disease, the interaction between HIV and aging affects the brain, and neurocognitive functions become more apparent [62]. Our findings support the previous observation that advanced age is among the factors associated with reduced neurocognitive impairment and vulnerability to HAND in the HIV population [63–66]. The pathogenesis of neurocognitive decline could partly be due to the additive impact of aging and HIV [67, 68]. Emerging evidence also supports the synergistic effect of the two factors: eg, acceleration memory deficits over one year are found among older but not younger population with HIV [69, 70].

The two factors that appeared protective against neurocognitive impairment are higher educational achievement and adherence to ART. Similar to previous studies, a higher level of education was associated with better cognitive performance. Although there were fewer participants with an advanced level of education, it was still evident that the higher a person had, the better the cognitive performance. Advanced education is thought to improve cognitive reserve and delay neurocognitive decline and functional expression of HIV-related neurodegenerative processes [71–73]. Furthermore, the effect of education is reflected when using cognitive screening tools, including MoCA and MMSE, which are sensitive to educational and socioeconomic factors; for this reason, lower cut-off points or the addition of a point is recommended for those patients with less than twelve years of formal education.

As of recent, the relationship between neurocognitive functioning and adherence to ART is increasingly becoming an area of interest for intervention. Given that the ART adherence rate in sub-Saharan Africa is below the recommended 95%, the reciprocal relation between neurocognitive impairment and ART adherence becomes a significant issue of concern. Our study showed that suboptimal adherence was significantly associated with neurocognitive impairment. Other studies have also shown that neurocognitive impairment is a major predictor of poor adherence to ART [74]. However, the temporal relationship between poor adherence and poor cognitive functioning is unclear.

People living with major depression (MDD) had 35% more odds of neurocognitive impairment that those without MDD. Depression is considered an independent risk for cognitive impairment, indeed, the analysis of the same data to determine the influence of MDD on cognition showed depression negatively influences neurocognitive functioning [75].

The study had several limitations; first, being a cross-sectional study limits its capacity to delineate the temporal relationship between HAND and the explanatory variables. Secondly, using MoCA and IHDS instead of the gold standard comprehensive neuropsychological assessment lowers the diagnostic accuracy and ability to fully categorize HAND into ANI, MND, and HAD. However, both MoCA and IHDS are recommended instruments in settings where the use of ideal gold standard assessment is not feasible. Furthermore, to improve the sensitivity and specificity, the HAND diagnosis was only met if both MoCA and IHDS scores were below the set cutoff points. Also, using IADL improved the ability to identify HAD, albeit the inability to distinguish ANI from MND remained a limitation.

Acknowledgments

The author acknowledges the Dodoma regional Referral Hospital for the permission to conduct the study in the hospital premises. Sincere gratitude goes to Dr Sadiki Mandari, Dr Maseto Galikunga, Dr Amina Ally and Dr Joshua John for their impressive work as research assistants. Last but not least, special appreciation to the clients attending the CTC clinic for their corporation and willingness to participate.

References

  1. 1. Shapshak P, Kangueane P, Fujimura RK, Commins D, Chiappelli F, Singer E, et al. Editorial neuroAIDS review. AIDS Lond Engl. 2011 Jan 14;25(2):123–41. pmid:21076277
  2. 2. Price RW. Neurological complications of HIV infection. Lancet Lond Engl. 1996 Aug 17;348(9025):445–52.
  3. 3. Antinori A, Arendt G, Becker JT, Brew BJ, Byrd DA, Cherner M, et al. Updated research nosology for HIV-associated neurocognitive disorders. Neurology. 2007 Oct 30;69(18):1789–99. pmid:17914061
  4. 4. Gisslén M, Price RW, Nilsson S. The definition of HIV-associated neurocognitive disorders: are we overestimating the real prevalence? BMC Infect Dis. 2011 Dec 28;11:356. pmid:22204557
  5. 5. Wang Y, Liu M, Lu Q, Farrell M, Lappin JM, Shi J, et al. Global prevalence and burden of HIV-associated neurocognitive disorder: A meta-analysis. Neurology. 2020 Nov 10;95(19):e2610–21. pmid:32887786
  6. 6. Masliah E, DeTeresa RM, Mallory ME, Hansen LA. Changes in pathological findings at autopsy in AIDS cases for the last 15 years. AIDS [Internet]. 2000 Jan 7 [cited 2022 Apr 13];14(1):69–74. Available from: https://journals.lww.com/aidsonline/Fulltext/2000/01070/Changes_in_pathological_findings_at_autopsy_in.8.aspx pmid:10714569
  7. 7. Gannon P, Khan MZ, Kolson DL. Current understanding of HIV-associated neurocognitive disorders pathogenesis. Curr Opin Neurol [Internet]. 2011 Jun [cited 2022 Apr 13];24(3):275–83. Available from: https://journals.lww.com/co-neurology/Abstract/2011/06000/Current_understanding_of_HIV_associated.15.aspx pmid:21467932
  8. 8. Kramer-Hämmerle S, Rothenaigner I, Wolff H, Bell JE, Brack-Werner R. Cells of the central nervous system as targets and reservoirs of the human immunodeficiency virus. Virus Res. 2005 Aug;111(2):194–213. pmid:15885841
  9. 9. Saylor D, Dickens AM, Sacktor N, Haughey N, Slusher B, Pletnikov M, et al. HIV-associated neurocognitive disorder—pathogenesis and prospects for treatment. Nat Rev Neurol [Internet]. 2016 Apr [cited 2022 Jun 26];12(4):234–48. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937456/ pmid:26965674
  10. 10. Gelman BB. Neuropathology of HAND With Suppressive Antiretroviral Therapy: Encephalitis and Neurodegeneration Reconsidered. Curr HIV/AIDS Rep. 2015 Jun;12(2):272–9. pmid:25860316
  11. 11. Cysique LA, Brew BJ. Vascular cognitive impairment and HIV-associated neurocognitive disorder: a new paradigm. J Neurovirol [Internet]. 2019 Oct 1 [cited 2022 Jun 28];25(5):710–21. Available from: pmid:30635846
  12. 12. Sacktor N, Skolasky RL, Seaberg E, Munro C, Becker JT, Martin E, et al. Prevalence of HIV-associated neurocognitive disorders in the Multicenter AIDS Cohort Study. Neurology. 2016 Jan 26;86(4):334–40. pmid:26718568
  13. 13. Bloch M, Kamminga J, Jayewardene A, Bailey M, Carberry A, Vincent T, et al. A Screening Strategy for HIV-Associated Neurocognitive Disorders That Accurately Identifies Patients Requiring Neurological Review. Clin Infect Dis Off Publ Infect Dis Soc Am. 2016 Sep 1;63(5):687–93. pmid:27325690
  14. 14. Lj H, R L, M D, J M, Fc L, R G, et al. Multicenter European Prevalence Study of Neurocognitive Impairment and Associated Factors in HIV Positive Patients. AIDS Behav [Internet]. 2018 May [cited 2022 Jun 28];22(5). Available from: https://pubmed.ncbi.nlm.nih.gov/28144792/
  15. 15. Ellis RJ, Badiee J, Vaida F, Letendre S, Heaton RK, Clifford D, et al. CD4 nadir is a predictor of HIV neurocognitive impairment in the era of combination antiretroviral therapy. AIDS Lond Engl. 2011 Sep 10;25(14):1747–51.
  16. 16. Census General Report-2012PHC.pdf [Internet]. [cited 2022 Apr 7]. Available from: http://tanzania.countrystat.org/fileadmin/user_upload/countrystat_fenix/congo/docs/Census%20General%20Report-2012PHC.pdf
    • 17. Carson N, Leach L, Murphy KJ. A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. Int J Geriatr Psychiatry. 2018;33(2):379–88. pmid:28731508
    • 18. Masika GM, Yu DSF, Li PWC. Accuracy of the Montreal Cognitive Assessment in Detecting Mild Cognitive Impairment and Dementia in the Rural African Population. Arch Clin Neuropsychol Off J Natl Acad Neuropsychol. 2021 Apr 21;36(3):371–80. pmid:31942599
    • 19. Koenig N, Fujiwara E, Gill MJ, Power C. Montreal Cognitive Assessment Performance in HIV/AIDS: Impact of Systemic Factors. Can J Neurol Sci J Can Sci Neurol. 2015 Dec 4;1–6. pmid:26635008
    • 20. Rosca EC, Albarqouni L, Simu M. Montreal Cognitive Assessment (MoCA) for HIV-Associated Neurocognitive Disorders. Neuropsychol Rev [Internet]. 2019 Sep 1 [cited 2021 Aug 22];29(3):313–27. Available from: pmid:31440882
    • 21. Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005 Apr;53(4):695–9. pmid:15817019
    • 22. Utility of the HIV Dementia Scale (HDS) in identifying HIV dementia in a South African sample. J Neurol Sci [Internet]. 2008 Jun 15 [cited 2022 Apr 11];269(1–2):62–4. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0022510X0700812X pmid:18237748
    • 23. Hu X, Zhou Y, Long J, Feng Q, Wang R, Su L, et al. Diagnostic accuracy of the International HIV Dementia Scale and HIV Dementia Scale: A meta-analysis. Exp Ther Med. 2012 Oct;4(4):665–8. pmid:23170123
    • 24. Mohamed AA, Oduor C, Kinyanjui D. HIV-associated neurocognitive disorders at Moi teaching and referral hospital, Eldoret, Kenya. BMC Neurol [Internet]. 2020 Jul 14 [cited 2022 Apr 11];20(1):280. Available from: pmid:32664858
    • 25. Gold DA. An examination of instrumental activities of daily living assessment in older adults and mild cognitive impairment. J Clin Exp Neuropsychol. 2012;34(1):11–34. pmid:22053873
    • 26. Amorim P. Mini International Neuropsychiatric Interview (MINI): validação de entrevista breve para diagnóstico de transtornos mentais. Braz J Psychiatry [Internet]. 2000 Sep [cited 2020 Jun 21];22(3):106–15. Available from: http://www.scielo.br/scielo.php?script=sci_abstract&pid=S1516-44462000000300003&lng=en&nrm=iso&tlng=pt
    • 27. Moore DJ, Blackstone K, Woods SP, Ellis RJ, Atkinson JH, Heaton RK, et al. Methamphetamine use and neuropsychiatric factors are associated with antiretroviral non-adherence. AIDS Care [Internet]. 2012 Dec 1 [cited 2020 Jun 20];24(12):1504–13. Available from: pmid:22530794
    • 28. Hendershot CS, Stoner SA, Pantalone DW, Simoni JM. Alcohol Use and Antiretroviral Adherence: Review and Meta-Analysis. JAIDS J Acquir Immune Defic Syndr [Internet]. 2009 Oct [cited 2020 Jun 20];52(2):180–202. Available from: https://journals.lww.com/jaids/Fulltext/2009/10010/Alcohol_Use_and_Antiretroviral_Adherence__Review.5.aspx pmid:19668086
    • 29. Thaler NS, Sayegh P, Kim MS, Castellon SA, Hinkin CH. Interactive Effects of Neurocognitive Impairment and Substance Use on Antiretroviral Non-adherence in HIV Disease. Arch Clin Neuropsychol [Internet]. 2015 Mar 1 [cited 2021 Dec 13];30(2):114–21. Available from: pmid:25589442
    • 30. Hinkin CH, Castellon SA, Durvasula RS, Hardy DJ, Lam MN, Mason KI, et al. Medication adherence among HIV+ adults. Neurology [Internet]. 2002 Dec 24 [cited 2021 Nov 21];59(12):1944–50. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871670/
    • 31. McDonnell J, Haddow L, Daskalopoulou M, Lampe F, Speakman A, Gilson R, et al. Minimal cognitive impairment in UK HIV-positive men who have sex with men: effect of case definitions and comparison with the general population and HIV-negative men. J Acquir Immune Defic Syndr 1999. 2014 Oct 1;67(2):120–7. pmid:24991974
    • 32. Rosenthal LS, Skolasky RL, Moxley RT, Roosa HV, Selnes OA, Eschman A, et al. A novel computerized functional assessment for human immunodeficiency virus-associated neurocognitive disorder. J Neurovirol. 2013 Oct;19(5):432–41. pmid:24081883
    • 33. Nyundo AA, Ndetei DM, Othieno CJ, Mathai AM. Neurocognitive correlates of the use of combined Antiretroviral Therapy among HIV-infected adults attending care and treatment center at Muhimbili National Hospital, Dar es Salaam, Tanzania: An analytical crosssectional study. Tanzan Med J [Internet]. 2015 [cited 2022 May 28];27(1). Available from: https://www.ajol.info/index.php/tmj/article/view/129268
    • 34. Nakasujja N, L Skolasky R, Musisi S, Allebeck P, Robertson K, Ronald A, et al. Depression symptoms and cognitive function among individuals with advanced HIV infection initiating HAART in Uganda. BMC Psychiatry [Internet]. 2010 Jun 10 [cited 2022 May 28];10(1):44. Available from: pmid:20537129
    • 35. Wei J, Hou J, Su B, Jiang T, Guo C, Wang W, et al. The Prevalence of Frascati-Criteria-Based HIV-Associated Neurocognitive Disorder (HAND) in HIV-Infected Adults: A Systematic Review and Meta-Analysis. Front Neurol [Internet]. 2020 [cited 2022 May 28];11. Available from: https://www.frontiersin.org/article/10.3389/fneur.2020.581346 pmid:33335509
    • 36. Küper M, Rabe K, Esser S, Gizewski ER, Husstedt IW, Maschke M, et al. Structural gray and white matter changes in patients with HIV. J Neurol [Internet]. 2011 Jun 1 [cited 2022 Jun 6];258(6):1066–75. Available from: pmid:21207051
    • 37. Zhou Y, Li R, Wang X, Miao H, Wei Y, Ali R, et al. Motor-related brain abnormalities in HIV-infected patients: a multimodal MRI study. Neuroradiology [Internet]. 2017 Nov 1 [cited 2022 Jun 6];59(11):1133–42. Available from: pmid:28889255
    • 38. Rubin LH, Neigh GN, Sundermann EE, Xu Y, Scully EP, Maki PM. Sex Differences in Neurocognitive Function in Adults with HIV: Patterns, Predictors, and Mechanisms. Curr Psychiatry Rep [Internet]. 2019 Sep 14 [cited 2022 Jun 6];21(10):94. Available from: pmid:31522330
    • 39. Y S. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc JINS [Internet]. 2002 Mar [cited 2022 Jun 7];8(3). Available from: https://pubmed.ncbi.nlm.nih.gov/11939702/?dopt=Abstract pmid:11939702
    • 40. Stern Y, Gurland B, Tatemichi TK, Tang MX, Wilder D, Mayeux R. Influence of education and occupation on the incidence of Alzheimer’s disease. JAMA. 1994 Apr 6;271(13):1004–10. pmid:8139057
    • 41. Tsai AC, Burns BFO. Syndemics of psychosocial problems and HIV risk: A systematic review of empirical tests of the disease interaction concept. Soc Sci Med 1982. 2015 Aug;139:26–35.
    • 42. Singer M. AIDS and the health crisis of the U.S. urban poor; the perspective of critical medical anthropology. Soc Sci Med 1982. 1994 Oct;39(7):931–48.
    • 43. Basso MR, Bornstein RA. Estimated premorbid intelligence mediates neurobehavioral change in individuals infected with HIV across 12 months. J Clin Exp Neuropsychol. 2000 Apr;22(2):208–18. pmid:10779835
    • 44. R F, En M, P S, Oa S, Ba C, Jt B, et al. Psychosocial risk factors of HIV morbidity and mortality: findings from the Multicenter AIDS Cohort Study (MACS). J Clin Exp Neuropsychol [Internet]. 2003 Aug [cited 2022 Jun 7];25(5). Available from: https://pubmed.ncbi.nlm.nih.gov/12815503/?dopt=Abstract
    • 45. Maki PM, Rubin LH, Valcour V, Martin E, Crystal H, Young M, et al. Cognitive function in women with HIV: findings from the Women’s Interagency HIV Study. Neurology. 2015 Jan 20;84(3):231–40. pmid:25540304
    • 46. Rubin LH, Pyra M, Cook JA, Weber KM, Cohen MH, Martin E, et al. Post-traumatic stress is associated with verbal learning, memory, and psychomotor speed in HIV-infected and HIV-uninfected women. J Neurovirol [Internet]. 2016 Apr 1 [cited 2022 Jun 7];22(2):159–69. Available from: pmid:26404435
    • 47. Rubin LH, Cook JA, Weber KM, Cohen MH, Martin E, Valcour V, et al. The association of perceived stress and verbal memory is greater in HIV-infected versus HIV-uninfected women. J Neurovirol [Internet]. 2015 Aug 1 [cited 2022 Jun 7];21(4):422–32. Available from: pmid:25791344
    • 48. Rubin LH, Sundermann EE, Cook JA, Martin EM, Golub ET, Weber KM, et al. Investigation of menopausal stage and symptoms on cognition in human immunodeficiency virus-infected women. Menopause N Y N. 2014 Sep;21(9):997–1006. pmid:24496085
    • 49. Sherwin BB. Estrogen and cognitive functioning in women: lessons we have learned. Behav Neurosci. 2012 Feb;126(1):123–7. pmid:22004260
    • 50. Das B, Dobrowolski C, Luttge B, Valadkhan S, Chomont N, Johnston R, et al. Estrogen receptor-1 is a key regulator of HIV-1 latency that imparts gender-specific restrictions on the latent reservoir. Proc Natl Acad Sci U S A. 2018 Aug 14;115(33):E7795–804. pmid:30061382
    • 51. Szotek EL, Narasipura SD, Al-Harthi L. 17β-Estradiol inhibits HIV-1 by inducing a complex formation between β-catenin and estrogen receptor α on the HIV promoter to suppress HIV transcription. Virology. 2013 Sep 1;443(2):375–83.
    • 52. Devadas K, Biswas S, Ragupathy V, Lee S, Dayton A, Hewlett I. Modulation of HIV replication in monocyte derived macrophages (MDM) by steroid hormones. PloS One. 2018;13(1):e0191916. pmid:29373606
    • 53. Schmiedel BJ, Singh D, Madrigal A, Valdovino-Gonzalez AG, White BM, Zapardiel-Gonzalo J, et al. Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression. Cell. 2018 Nov 29;175(6):1701–1715.e16. pmid:30449622
    • 54. Raghavan A, Rimmelin DE, Fitch KV, Zanni MV. Sex Differences in Select Non-communicable HIV-Associated Comorbidities: Exploring the Role of Systemic Immune Activation/Inflammation. Curr HIV/AIDS Rep. 2017 Dec;14(6):220–8. pmid:29080122
    • 55. Lipton SA. Requirement for macrophages in neuronal injury induced by HIV envelope protein gp120. Neuroreport. 1992 Oct;3(10):913–5. pmid:1421098
    • 56. Ticona E, Bull ME, Soria J, Tapia K, Legard J, Styrchak SM, et al. Biomarkers of inflammation in HIV-infected Peruvian men and women before and during suppressive antiretroviral therapy. AIDS Lond Engl. 2015 Aug 24;29(13):1617–22.
    • 57. Martin GE, Gouillou M, Hearps AC, Angelovich TA, Cheng AC, Lynch F, et al. Age-associated changes in monocyte and innate immune activation markers occur more rapidly in HIV infected women. PloS One. 2013;8(1):e55279. pmid:23365694
    • 58. Burdo TH, Weiffenbach A, Woods SP, Letendre S, Ellis RJ, Williams KC. Elevated sCD163 in plasma but not cerebrospinal fluid is a marker of neurocognitive impairment in HIV infection. AIDS Lond Engl. 2013 Jun 1;27(9):1387–95.
    • 59. Krebs SJ, Slike BM, Sithinamsuwan P, Allen IE, Chalermchai T, Tipsuk S, et al. Sex differences in soluble markers vary before and after the initiation of antiretroviral therapy in chronically HIV-infected individuals. AIDS Lond Engl. 2016 Jun 19;30(10):1533–42.
    • 60. Hagberg L, Cinque P, Gisslen M, Brew BJ, Spudich S, Bestetti A, et al. Cerebrospinal fluid neopterin: an informative biomarker of central nervous system immune activation in HIV-1 infection. AIDS Res Ther. 2010 Jun 3;7:15. pmid:20525234
    • 61. Dunbar N, Pemberton L, Perdices M, Brew BJ. Clinical Markers of the Presence of Dementia and Neuropsychological Impairment in HIV Infection. J Neuro-AIDS. 1996;1(4):31–48. pmid:16873177
    • 62. Cohen RA, Seider TR, Navia B. HIV effects on age-associated neurocognitive dysfunction: premature cognitive aging or neurodegenerative disease? Alzheimers Res Ther [Internet]. 2015 Apr 6 [cited 2022 Jun 15];7(1):37. Available from: pmid:25848401
    • 63. Wendelken LA, Valcour V. Impact of HIV and aging on neuropsychological function. J Neurovirol. 2012 Aug;18(4):256–63. pmid:22528478
    • 64. Valcour VG, Shikuma CM, Watters MR, Sacktor NC. Cognitive impairment in older HIV-1-seropositive individuals: prevalence and potential mechanisms. AIDS Lond Engl. 2004 Jan 1;18 Suppl 1:S79–86. pmid:15075502
    • 65. Becker JT, Lopez OL, Dew MA, Aizenstein HJ. Prevalence of cognitive disorders differs as a function of age in HIV virus infection. AIDS Lond Engl. 2004 Jan 1;18 Suppl 1:S11–18. pmid:15075493
    • 66. Wilkie FL, Goodkin K, Khamis I, van Zuilen MH, Lee D, Lecusay R, et al. Cognitive functioning in younger and older HIV-1-infected adults. J Acquir Immune Defic Syndr 1999. 2003 Jun 1;33 Suppl 2:S93–105. pmid:12853858
    • 67. Becker JT, Maruca V, Kingsley LA, Sanders JM, Alger JR, Barker PB, et al. Factors affecting brain structure in men with HIV disease in the post-HAART era. Neuroradiology. 2012 Feb;54(2):113–21. pmid:21424708
    • 68. Ances BM, Ortega M, Vaida F, Heaps J, Paul R. Independent effects of HIV, aging, and HAART on brain volumetric measures. J Acquir Immune Defic Syndr 1999. 2012 Apr 15;59(5):469–77. pmid:22269799
    • 69. Seider TR, Luo X, Gongvatana A, Devlin KN, de la Monte SM, Chasman JD, et al. Verbal memory declines more rapidly with age in HIV infected versus uninfected adults. J Clin Exp Neuropsychol. 2014;36(4):356–67. pmid:24645772
    • 70. Morgan EE, Woods SP, Smith C, Weber E, Scott JC, Grant I, et al. Lower cognitive reserve among individuals with syndromic HIV-associated neurocognitive disorders (HAND). AIDS Behav. 2012 Nov;16(8):2279–85. pmid:22677976
    • 71. Kabuba N, Menon JA, Franklin DR, Lydersen S, Heaton RK, Hestad KA. Effect of Age and Level of Education on Neurocognitive Impairment in HIV Positive Zambian Adults. Neuropsychology [Internet]. 2018 Jul [cited 2022 Jun 15];32(5):519–28. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296371/ pmid:29504779
    • 72. Le Carret N, Lafont S, Mayo W, Fabrigoule C. The effect of education on cognitive performances and its implication for the constitution of the cognitive reserve. Dev Neuropsychol. 2003;23(3):317–37. pmid:12740188
    • 73. Ostrosky-Solis F, Ardila A, Rosselli M, Lopez-Arango G, Uriel-Mendoza V. Neuropsychological test performance in illiterate subjects. Arch Clin Neuropsychol Off J Natl Acad Neuropsychol. 1998 Oct;13(7):645–60. pmid:14590626
    • 74. Nyundo AA. Neurocognitive decline as a major predictor of nonadherence to antiretroviral therapy among adults living with HIV in Dodoma region, central Tanzania. Health Sci Rep [Internet]. 2022 [cited 2022 Jun 16];5(4):e669. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/hsr2.669 pmid:35686198
    • 75. Nyundo AA, Ismail A. The influence of major depressive disorders on neurocognitive function among adults living with HIV/AIDS in a regional referral hospital in Dodoma, Tanzania. Trop Med Int Health [Internet]. 2022 [cited 2022 Jun 16];27(1):58–67. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/tmi.13699 pmid:34743393