Abstract
Detailed neuropsychological testing was performed on 134 HIV seropositive (SP) and 77 HIV seronegative (SN) individuals, 86% with early stage HIV infection in Nigeria, to determine the frequency of HIV-related neurocognitive impairment among the HIV-infected group. Twenty-two tests were administered to assess the following seven ability domains: speed of information processing (SIP); attention/working memory (AWM); executive functioning (EF); learning (LN); memory (MEM); verbal fluency (VF); and motor speed/dexterity (MSD). Demographically corrected individual test scores and scores for each domain or reflecting a global deficit (a global deficit score, or GDS) were compared for the SP and SN groups. SP participants were older, had fewer years of education, were more likely to be married, differed in ethnicity and had higher depression scores than SN individuals. On the testing, SP performed worse than SN on four tests that individually assessed LN, VF and MSD (the timed gait). SP subjects, however, performed better than SN on the finger-tapping test, also a motor task. Within the seven ability domains, SP performed worse than SN with respect to SIP, EF, LN, MEM and VF and also on the global measure. SP were also more frequently impaired on tests of SIP, and there was a borderline increase in the frequency of global impairment. Performance by SP subjects was not associated with CD4 counts. However, there were significant correlations between viral load measurements and individual tests of SIP, EF, LN and VF and with overall EF and a borderline correlation with the GDS. Depression scores for SP were associated with impairment on only a single test of EF. These results demonstrate that the ability of these assessments to identify areas of impairment that may be specifically linked to a history of HIV infection among individuals in Nigeria. Confirmation of these findings awaits analyses using data from a larger number of control subjects.
Keywords: neuropsychological, AIDS, Africa
Introduction
At the end of 2011, 34.0 million people globally were reported to be living with the human immunodeficiency virus (HIV) infection (UNAIDS, 2012). Among adults aged 15–49 years worldwide, an estimated 0.8% is living with HIV infection, with the numbers of infected individuals showing considerable variation between countries and regions. Africa currently accounts for 69.0% of people living with HIV infection worldwide (UNAIDS, 2012). In Nigeria, the number of people living with the infection increased over the twenty six year period beginning in 1986, when the first case of AIDS was reported in the country, through December 2011 to about 3.4 million ((NACA), 2012).
HIV affects virtually all body systems, and the nervous system is a frequent target of infection (Berger et al., 1987; Grant et al., 1987; Grant et al., 1995; McArthur, 1987; Snider et al., 1983). Involvement of the nervous system by HIV infection is associated with an increased risk for the development of neurocognitive impairment (NCI) that occurs in the context of HIV associated neurocognitive disorders (HAND) (Antinori et al., 2007). The occurrence of NCI in HIV infection can result from either direct mechanisms, for example, neurotoxicity induced by HIV proteins, or due to indirect involvement of the brain, as occurs with bystander damage induced by inflammatory mediators released by activated immune cells or astrocytes (Anderson et al., 2002; Nath, 2002). The impact of NCI on the ability of an individual to function can be severe and, untreated, is associated with an increased mortality (Ellis et al., 1997; Mayeux et al., 1993; McArthur et al., 1993). Therefore, NCI ranks as potentially one of the most devastating manifestations of HIV infection. With the introduction of effective combination antiretroviral therapy, the overall incidence on the most severe forms of NCI has decreased, an effect from treatment that has been observed worldwide, including in Sub-Saharan Africa (Joska JA, 2010). However, such treatment typically results in an incomplete clinical response, and this fact combined with the improved overall survival from HIV infection, has resulted in an increased overall prevalence of NCI (Dore et al., 1999; Dore et al., 2003; Heaton et al., 2011; Sacktor et al., 2001).
There is paucity information regarding the frequency of HIV-associated NCI in Nigeria, where there is a high burden of HIV infection. In this report are described the results of an analysis of neuropsychological test data from individuals in Abuja, Nigeria who were recruited into a longitudinal study that will examine factors that are associated with risk for developing neurocognitive impairment as a result of HIV infection.
Results
Demographic, Clinical, and Laboratory Characteristics of Study Participants
Baseline data available on 210 participants (133 SP and 77 SN) were analyzed. SP participants were overall older and had fewer years of education than SN individuals (table 1). SP participants were also more likely to be married, to be from different ethnic groups in Nigeria and to have higher depression scores than SN individuals. SP individuals had lower CD4+ T cell counts than SN, and approximately 86% of HIV infected individuals were asymptomatic for their HIV infection. The mean plasma viral load among the 117 SP subjects who were tested was approximately 27,000 copies/ml, and plasma virus was undetectable (<20 copies/ml) in three individuals.
Table 1.
Demographic Characteristics, WHO Stage and CD4 count for the HIV Seropositive and Seronegative Subjects
| Group | HIV SN | HIV SP | P values |
|---|---|---|---|
|
| |||
| Number of subjects | 77 | 133 | |
|
| |||
| Age (years) | |||
| Mean (SD) | 29.48 (6.72) | 33.59 (7.28) | <0.0001 |
|
| |||
| Gender (%) | |||
| Female | 48 (62.34) | 77 (57.89) | 0.5 |
|
| |||
| Mean years of education (SD) | 14.32 (1.74) | 12.39 (3.06) | <0.0001 |
|
| |||
| Number of participants by | |||
| Ethnicity (%) | |||
| Hausa | 1 (1.30) | 9 (6.77) | |
| Ibo | 11 (14.29) | 34 (25.56) | 0.01 |
| Yoruba | 16 (20.78) | 12 (9.02) | |
| Others | 49 (63.64)) | 78 (58.65) | |
| Marital status (%) | |||
| Married | 27 (35.06) | 68 (51.13) | |
| Single/widowed/divorced | 50 (64.94) | 66 (48.87) | 0.024 |
|
| |||
| WHO Stage (%) | |||
| Stage 1 | - | 86.47 | |
| Stage 4 | 8.27 | ||
| Stage 3 | 3.76 | ||
| Stage 4 | 1.50 | ||
| Median CD4 count (IQR) | 754 [IQR 545–883] | 348 (217–496.5) | <0.0001 |
| CD4 group (%) | |||
| ≤350/μl | 3 (3.90) | 69 (51.88) | |
| 350 – 500/μl | 13 (16.88) | 32 (24.06) | <0.0001 |
| ≥ 500/μl | 61 (79.22) | 32 (24.06) | |
| Log HIV viral load (N=117) | 4.43 (0.98) | ||
| Median HIV viral load (IQR) | 4.56 (3.96–5.08) | ||
| BDI | 4.06 (4.42) | 7.02 (7.37) | 0.0004 |
SD = Standard Deviation; IQR = Interquartile Range
This category includes a total of 61 ethnic groups, 29 among SN and 32 among SP participants. Eight of the ethnic groups included both SN and SP individuals.
Median [Interquartile Range]
Comparison of Domain-Specific and Overall Performance by SP and SN Participants on the Neuropsychological Tests
In order to link neuropsychological test performance to deficit, age and education-adjusted standardized T scores were converted to clinical deficit scores. The mean deficit scores for the seven ability domains and the GDS were then compared for the SP and SN participants (table 2). This analysis showed that mean scores for SIP, EF, LN, MEM and VF were higher for SP than for SN participants. Also, mean GDS was higher for SP than for SN participants.
Table 2.
Comparison of Mean Ability Doman and Global Deficit Scores for HIV-1 Seropositive and Seronegative Subjects
| HIV SN | HIV SP | P-Value | |
|---|---|---|---|
| Ability Domain Deficit Scores | |||
| Speed of Information Processing | 0.26 (0.39)1 | 0.47 (0.54) | 0.0008 |
| Attention/Working Memory | 0.26 (0.52) | 0.26 (0.48) | 1.0 |
| Executive Functions | 0.27 (0.46) | 0.55 (0.79) | 0.0014 |
| Learning | 0.25 (0.50) | 0.47 (0.71) | 0.0082 |
| Memory | 0.29 (0.48) | 0.45 (0.71) | 0.056 |
| Verbal Fluency | 0.25 (0.44) | 0.40 (0.58) | 0.029 |
| Motor Function | 0.25 (0.37) | 0.26 (0.37) | 0.85 |
| Global Deficit Score | 0.26 (0.23) | 0.40 (0.35) | 0.0007 |
Mean (SD)
Analysis of the Percentage of Individuals with Specific Ability Domain and with Global Impairment
The percentage individuals who showed evidence of impairment in any of the seven ability domains, indicated by a deficit score >0.5, and the presence of NCI, indicated by a GDS ≥0.5, was compared for the SP and SN groups (table 3). This analysis showed a statistically significant difference only with respect to speed of information processing, with a higher percentage of SP individuals demonstrating impairment than SN subjects. There was also a borderline increase in the frequency of global impairment among SP participants.
Table 3.
Frequency of Impairment in the Individual Ability Domains and Globally Among Study Participants
| HIV SN | HIV SP | P-Value | |
|---|---|---|---|
| Ability Domain Deficit Scores | |||
| Verbal Fluency | 19 (24.68)1 | 44 (33.08) | 0.20 |
| Speed of Information Processing | 13 (16.88) | 52 (39.10) | 0.0008 |
| Delayed Recall | 25 (32.47) | 50 (37.59) | 0.46 |
| Attention/Working Memory | 22 (28.57) | 41 (30.83) | 0.73 |
| Executive Function | 26 (33.77) | 60 (45.11) | 0.11 |
| Learning | 22 (28.57) | 54 (40.60) | 0.08 |
| Motor Function | 15 (19.48) | 24 (1805) | 0.80 |
| Global Deficit Score | 15 (19.48) | 41 (30.83) | 0.073 |
Number impaired (percent)
Comparison of SP and SN Participant Performance on the Individual Neuropsychological Tests
The means of the standardized T scores for the individual neuropsychological tests were compared for SP and SN participants (table 4). Analysis of the means of the demographically adjusted scores showed that SP participants performed worse on tests of learning (the Hopkins Total Learning Test and the Hopkins Verbal Learning Test), verbal fluency (the Letter (Word Sound) Fluency Test) and with motor speed and dexterity (the Timed Gait Test). SN participants performed worse than SP on the Finger-tapping Test, a test of motor speed and dexterity.
Table 4.
Neuropsychological Performance for HIV-1 SP Participants
| Mean T Score* | SD | P-value | Cohen’s d | |
|---|---|---|---|---|
| Speed of Information Processing | ||||
| WAIS-III Digit Symbol | 47.99 | 10.80 | 0.18 | 0.19 |
| WAIS-III Symbol Search | 47.74 | 11.96 | 0.16 | 0.21 |
| Color Trails Test 1 Trial | 49.80 | 13.24 | 0.90 | 0.02 |
| Trail Making Test A | 48.80 | 14.02 | 0.47 | 0.10 |
| Attention/Working Memory | ||||
| Paced Auditory Serial Addition Task | 48.64 | 10.01 | 0.35 | 0.14 |
| WMS-III Spatial Span | 50.76 | 10.86 | 0.61 | −0.07 |
| Executive Functions | ||||
| Color Trails Test 2 | 49.44 | 12.20 | 0.73 | 0.05 |
| Stroop Color and Word Test | 48.18 | 11.07 | 0.24 | 0.17 |
| Learning | ||||
| HVLT-R total learning | 45.08 | 9.73 | 0.0006 | 0.50 |
| BVMT-R total learning | 49.82 | 12.04 | 0.91 | 0.02 |
| Memory | ||||
| HVLT-R delayed recall | 45.46 | 9.63 | 0.001 | 0.46 |
| BVMT-R delayed recall | 49.23 | 13.22 | 0.96 | 0.07 |
| Verbal Fluency | ||||
| Letter (Word Sound) Fluency | 45.43 | 10.26 | 0.001 | 0.45 |
| Category Fluency: Nouns (animals) | 48.40 | 10.23 | 0.28 | 0.16 |
| Category Fluency: Verbs (actions) | 48.71 | 10.54 | 0.38 | 0.13 |
| Motor Speed and Dexterity | ||||
| Grooved Pegboard Test | 51.92 | 11.01 | 0.21 | −0.18 |
| Finger tapping test | 54.98 | 13.42 | 0.0025 | −0.42 |
| Timed gait | 46.73 | 10.43 | 0.027 | 0.32 |
All T scores are demographically corrected. T scores were also scaled to yield, for all tests for SN controls, a mean = 50 and a standard deviation (SD) = 10. A T score <50 indicates worse performance on the testing
HVLT-R: Hopkins Verbal Learning Test-Revised; BVMT-R: Brief Visuospatial Memory Test – Revised
Neuropsychological Test Result Associations with HIV Infection Parameters and with Depression
Correlations analyses were performed to determine whether performance on the neuropsychological assessments were associated with CD4+ T cell counts (<200, 200–500 or >500 μl/dl), HIV clinical status or with depression. For CD4+ T cell counts, a correlation was observed only with the timed gait and the correlation was only at a borderline level (Table 4). Viral load measures, however, inversely correlated with individual tests of speed of information processing (WAIS-III Digit Symbol and WAIS-III Symbol Search) and verbal fluency (Category Fluency: Nouns (animals) and Category Fluency: Verbs (actions)), whereas correlations of borderline significance were observed with Hopkins Verbal Total Learning and the Grooved Pegboard Test. Viral load measurements also showed a significant direct correlation with overall executive function and a borderline significant correlation with overall verbal fluency. There was a significant direct correlation between GDS and viral load measurements.
Correlations with depression scores were determined for both SN and SP individuals. Scores for SN showed a significant correlation only with the Timed Gait test. Depression scores for SP correlated inversely with performance on the Stroop Color and Word Test and, at a borderline level of significance, with overall motor function.
Discussion
This is one of several stidoes that have examined the frequency of neurocognitive impairment among HIV infected individuals in Nigeria. Previously, such studies have utilized either the Community Screening Interview for Dementia (CSI ‘D’) or, in studies that we previously reported, the International HIV Dementia Scale (IHDS) (Hall et al., 2000; Odiase et al., 2006; Royal, III et al., 2012; Salawu et al., 2008). Infected individuals studied using both approaches showed evidence of worse cognitive status as compared to SN subjects. However, these screens, though useful for identifying abnormalities that occur commonly in HIV infection and take relatively little time to administer, are less sensitive and specific then more detailed neuropsychological testing for detecting HIV-related cognitive impairment.
Preliminary studies performed on small numbers of patients established the feasibility of using for the studies that is described in this report (Royal, III et al., 2012). In the study reported here, we found that SP participants performed worse on the Hopkins Verbal Learning Total Learning, the Hopkins Verbal Learning Test-Revised, the Letter (Word-Sound) Fluency tests and the Timed Gait. Averaging the results of the individual test scores showed that the SP participants performed worse that SN in all of the associated domains, with the exception of that for motor function. Motor impairment can occur in the context of HIV-related cognitive impairment, and such impairment tends to be a later manifestation of HIV nervous system involvement (Antinori et al., 2007; Report of a Working Group of the American Academy of Neurology AIDS Task Force, 1991). The reason why SP would perform better on this test is unclear. Perhaps their performance may reflect an ability that is linked to an occupation or other activity that is more typical of individuals in the SP group.
In contrast to the relatively low frequency of impairment on the individual tests, a difference in mean disability scores was noted for five of the seven ability domains, and a significant difference was also noted for the mean GDS (table 3). In addition, there were increased frequencies of impairment in one domain and with respect to the GDS. Similar domain-specific and overall differences have been previously reported when comparing SP and SN subjects in both African and Western cohorts (Heaton et al., 2011; Kanmogne et al., 2010). However, it is notable in our data that few individuals scored beyond the defined cut-offs for impairment for the domain scores and for the GDS. This is consistent with the fact that the SP participants were overall in the early stages of their HIV disease.
To determine whether measures of HIV disease status might have impacted performance of the testing, correlations between CD4+ T cell counts (<200, 200–500 or >500 cells per μl) and viral load with individual neuropsychological test, domain and global scores were examined. The level of immunosuppression as indicated by the CD4+ T cell count appeared to have little impact on performance on the outcome of the testing. However, a higher viral load was associated with impaired performance on multiple tests, within several domains and with respect to global neurocognitive functioning. These findings suggest that more subtle viral effects on test performance may be observed even where there may be few individuals who perform in a range where they would be considered to be impaired. Such associations may in some individuals be potentially linked to the milder forms of HAND (i.e., asymptomatic neurocognitive impairment or minor neurocognitive disorder). Which SP individuals in the study met criteria for the various subtypes of HAND were not determined for this report; however, this will be the focus of future analyses. Of note is the fact that the presence of depressive symptoms among members of the cohort did not appear to have an impact on how well individuals performed in the testing.
Despite the several interesting observations described above, there are several limitations to our study. A significant limitation is the fact that, although scores were adjusted for age and education, the number of individuals in the control group is less than what is generally considered ideal to be able to adequately control for these factors. With respect to the reported number of years of education, it is the case that in some African communities much education occurs in the home with the elderly teaching the young. Therefore, the number of years of formal education may not accurately reflect the level of education that is actually achieved by an individual (Paddick et al., 2013). In addition, the education background of the participant will, to some extent, reflect the population of patients that seek care at the health care centers where the recruitment for the study took place. To some degree, the same limitation can be also stated for other participant demographic factors. However, regardless of the reasons for the differences noted, it is important to control for age an education in analyses such as those presented here. One approach to addressing this issue would have been to match the groups on these variables. While this can also be considered for future analyses, recruitment of SN subjects into the study has continued and repeat analyses are planned that will utilize a larger number of controls. Such studies should provide even more reliable normative data. Future studies using such norms may, indeed, yield findings that are different from what is reported here. However, the fact that our overall results are consistent with what has been previously reported gives confidence that it is unlikely that major differences from what we present here will emerge. It is also not always possible to control for certain factors that may be important, which is the case for the differences noted in the ethnicity of the SP and SN subjects. The major groups are represented in the categorization that is presented; however, a significant percentage falls outside of these groups. That reflects the fact that a large number of ethnic groups exist in Nigeria. To try to place each person in our study in a separate group would have yielded only one or two individuals in some groups, and to exclude such individuals from the study would have resulted in the cohort not being reflective of the ethnic diversity of the general population. Other important issues that were not addressed in this report are the likely role of strains of HIV that are present in Nigeria and possible host factors may influence the expression and course of disease. Such information, combined with those from the studies described here, is likely to be valuable for understanding patterns of treatment responses and the overall effectiveness of such approaches as there continues to be a rapid scale up of treatment with antiretroviral agents in Nigeria.
Materials and methods
Study recruitment and participants
Study participants were recruited from two clinical sites, the National Hospital (NH) and the University of Abuja Teaching Hospital (UATH), in Abuja, the capital city of Nigeria. These hospitals are within a network of sites supported by the Institute of Human Virology, Nigeria (IHVN) with funds from the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) program. SP subjects were recruited at the time of a regular clinical visit. SN controls were recruited from the HIV voluntary counseling and testing centers located at the clinical sites where HIV patients are recruited. At the time of standard posttest counseling, HIV negative subjects were individually and privately invited to speak with a study staff member who performed screening for eligibility employing the process described above. All individuals were ≥18 years of age, able to converse in English and antiretroviral naïe with no history of active tuberculosis, syphilis or other infections. The participants also had no evidence of the presence of a clinical problem that could impair their ability to participate in the testing, including active CNS or systemic disease, a history of significant head trauma, a history or alcohol abuse, use of other mind-altering substances, or if there was evidence of substance use on urine toxicology screening, a previous diagnosis of a learning disability or psychiatric disorder, or other disorders associated with the presence of focal neurological signs or deficits. Demographic information was obtained, and participants were administered standardized questionnaires, a thorough general medical assessment and neuropsychological testing (described below). Volunteers underwent phlebotomy and subsequent determination of HIV-1 serological status and measurement of CD4+ T cell count performed at the IHVN-supported Research Laboratory located in Asokoro, Abuja. Viral load measurements were performed using the Roche Amplicor Monitor Test v.1.5 (Roche; detection range = 400–750,000 copies/ml, or the COBAS® AmpliPrep/COBAS TaqMan HIV-1 Test (Roche; detection range = 20–10,000,000 copies/ml). Informed consent was obtained from the study participants independently or with the assistance of a family member. All study procedures were approved by the University of Maryland Baltimore, NH, and UATH Institutional Review Boards and by the Nigerian National Health Research Ethics Committee. The enrollment target for the study has been set at 100 SN and 200 SP individuals.
Neuropsychological testing
A detailed standardized neuropsychological battery was administered to all study participants in order to identify possible impairment within specific cognitive domains of interest. The testing was administered at each of the testing site by either of two nurses who underwent training in Nigeria administered in-person by a University of California, San Diego (UCSD) neuropsychological testing technician. For quality control, the tests were double-scored, and completed forms on randomly-selected participants were assessed for accuracy and discussed at a monthly teleconference. The ability domains tested (followed by the individual tests within the domains in parentheses), were: Speed of Information Processing (WAIS-III Digit Symbol, WAIS-III Symbol Search, Color Trails Test 1 and Trail Making Test A); Attention/Working Memory (Paced Auditory Serial Addition Task, and WMS-III Spatial Span); Abstraction/Executive Functioning (Color Trails Test 2 and Stroop Color and Word Test), Learning and Delayed Recall (Hopkins Verbal Learning Test – Revised and Brief Visuospatial Memory Test – Revised); Verbal Fluency (Letter (Word Sound, Category Fluency: Nouns (animals) and Category Fluency: Verbs (actions)); Motor Speed and Dexterity (Grooved Pegboard Test, Finger Tapping Test and Timed Gait), and Screening for Effort (Hiscock Digit Memory Test). Raw scores from the neuropsychological tests were converted to standardized scores (T scores) that were adjusted for age, gender and education based on the SN sample. T-scores were then used to calculate a global deficit score (GDS), reflecting performance across the test battery, with a score ≥0.5 indicating NCI (Carey et al., 2004). In addition to recruiting only English speakers, to minimize the potential impact of language of cultural differences on performance on the testing, words were eliminated from verbal tests that were likely to be unfamiliar to individuals from the region and, after appropriate pilot testing, were replaced by more familiar terms.
Statistical Analysis
Demographic data and neuropsychological T scores and global deficit scores were compared for SP and SN participants using t-tests or the Mann-Whitney U test, as appropriate. The frequency of impairment and select categorical demographic and clinical data were compared for the two groups using the chi-square test. Neuropsychological test score associations with CD4+ T cell counts viral load and depression scores and GDS were examined using regression analysis. Correlations were examined by calculating the Pearson’s correlation coefficient or Spearman’s rank correlation coefficient, as appropriate.
Table 5a.
Correlations for HIV Disease Parameters and Depression Scores with Neuropsychological Test Scores
| I. Individual Neuropsychological Test T Scores | CD4 | Viral Load | BDI | |
|---|---|---|---|---|
| Speed of Information Processing | SP | SP | SN | SP |
| WAIS-III Digit Symbol | 0.03, 0.7 | −0.203, 0.03 | 0.15, 0.2 | 0.06, 0.5 |
| WAIS-III Symbol Search | −0.02, 0.8 | −0.157, 0.10 | 0.03, 0.8 | −0.12, 0.17 |
| Color Trails Test 1 Trial | 0.06, 0.5 | −0.034, 0.72 | 0.219, 0.54 | −0.02, 0.8 |
| Trail Making Test A | 0.06, 0.5 | −0.062, 0.51 | 0.03, 0.8 | −0.07, 0.4 |
| Attention/Working Memory | ||||
| Paced Auditory Serial Addition Task | 0.03, 0.8 | −0.125, 0.19 | −0.16, 0.15 | −0.03, 0.7 |
| WMS-III Spatial Span | 0.03,0.7 | 0.0003, 1.0 | −0.04, 0.8 | 0.02, 0.8 |
| Executive Functions | ||||
| Color Trails Test 2 | −0.04, 0.7 | −0.053, 0.58 | 0.15, 0.2 | 0.005, 0.95 |
| Stroop Color and Word Test | −0.02, 0.8 | −0.199, 0.03 | −0.05, 0.6 | −0.207, 0.017 |
| Learning | ||||
| HVLT-R total learning | −0.01, 0.9 | −0.212, 0.024 | 0.04, 0.7 | −0.09, 0.3 |
| BVMT-R total learning | −0.02, 0.8 | −0.084, 38 | −0.02, 0.9 | −0.1, 0.3 |
| Memory | ||||
| HVLT-R delayed recall | 0.06, 0.5 | −0.119, 0.21 | −0.008, 0.9 | 0.09, 0.3 |
| BVMT-R delayed recall | 0.008, 0.9 | −0.090, 0.34 | 0.04, 0.8 | −0.05, 0.6 |
| Verbal Fluency | ||||
| Letter (Word Sound) Fluency | 0.13, 0.14 | −0.204, 0.029 | 0.03, 0.8 | 0.07, 0.4 |
| Category Fluency: Nouns (animals) | 0.04, 0.7 | −0.163, 0.08 | 0.06, 0.6 | −0.09, 0.3 |
| Category Fluency: Verbs (actions) | 0.17, 0.2 | −0.234, 0.012 | −0.07, 0.5 | −0.04, 0.6 |
| Motor Speed and Dexterity | ||||
| Grooved Pegboard Test | −0.06, 0.5 | −0.079, 0.40 | 0.20, 0.09 | −0.14, 0.1 |
| Finger tapping test | 0.06, 0.5 | −0.026, 0.78 | −0.10, 0.4 | −0.04, 0.6 |
| Timed gait | 0.162, 0.06 | −0.113, 0.3 | −0.367, 0.0013 | −0.1, 0.3 |
Correlation coefficient, p-value; HVLT-R: Hopkins Verbal Learning Test-Revised; BVMT-R: Brief Visuospatial Memory Test – Revised
Table 5b.
Correlations for HIV Disease Parameters and Depression Scores with Neuropsychological Test Scores
| CD4 | Viral Load | BDI | ||
|---|---|---|---|---|
| I. Ability Domain Deficit Scores1 | SP | SP | SN | SP |
| Speed of Information Processing | −0.02, 0.8 | 0.114, 0.23 | −0.19, 1.0 | 0.1, 0.3 |
| Attention/Working Memory | −0.02, 0.8 | 0.073, 0.44 | 0.08, 0.5 | 0.004, 0.97 |
| Executive Functions | 0.03, 0.7 | 0.247, 0.008 | 0.08, 0.5 | 0.09, 0.3 |
| Learning | −0.01, 0.9 | 0.84, 0.37 | 0.09, 0.4 | 0.12, 0.2 |
| Memory | −0.05, 0.6 | 0.015, 0.88 | −0.15, 0.2 | 0.08, 0.4 |
| Verbal Fluency | −0.15, 0.08 | 0.137, 0.15 | −0.20, 0.08 | 0.02, 0.8 |
| Motor Function | −0.09, 0.3 | 0.062, 0.51 | 0.12, 0.3 | 0.156, 0.073 |
| II. Global Deficit Score | −0.08, 0.3 | 0.172, 0.067 | −0.05, 0.6 | 0.14, 0.11 |
Correlation coefficient, p-value
Acknowledgments
Supported by: R01MH086356 NIMH/NIH (W. Royal and W.A. Blattner)
Footnotes
Conflict of Interest Statement:
Christopher Akolo, MBBS: no conflict of interest to declare.
Walter Royal, III, MD: no conflict of interest to declare.
Mariana Cherner, PhD: no conflict of interest to declare.
Kanayo Okwuasaba, MBBS: no conflict of interest to declare.
Lindsay Eyzaguirre, MS: no conflict of interest to declare.
Ruxton Adebiyi, BS: no conflict of interest to declare.
Anya Umlauf, PhD: no conflict of interest to declare.
Terence Hendrix, BS: no conflict of interest to declare.
Alashl’e Abimiku, PhD: no conflict of interest to declare.
Joyce Johnson, MS: no conflict of interest to declare.
William A. Blattner, MD, MPH: no conflict of interest to declare.
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