Cognitive impairment and neurocognitive profiles among people living with HIV and HIV- negative individuals older over 50 years: a comparison of IHDS, MMSE and MoCA

Cognitive impairment and neurocognitive profiles among people living with HIV and HIV- negative individuals older over 50 years: a comparison of IHDS, MMSE and MoCA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cognitive impairment and neurocognitive profiles among people living with HIV and HIV- negative individuals older over 50 years: a comparison of IHDS, MMSE and MoCA Panpan Chen, Xin Xin, Shaotan Xiao, Hantao Liu, Xin Liu, Na He, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3932903/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 May, 2024 Read the published version in Journal of NeuroVirology → Version 1 posted 7 You are reading this latest preprint version Abstract Background The aim of our study was to examine potential differences in the assessment of neurocognitive impairment (NCI) using cognitive screening tools between PLWH and HIV-negative individuals, as well as to compare the neurocognitive profiles. Methods This was baseline evaluation of Pudong HIV Aging Cohort, including 465 people living with HIV (PLWH) and 465 HIV-negative individuals aged over 50 years matched by age (± 3 years), sex and education. NCI was assessed using the Chinese version of Mini-mental State Examination (MMSE), the International HIV Dementia Scale (IHDS) and Beijing version of Montreal Cognitive Assessment (MoCA). Results In total, 258 (55.5%), 91 (19.6%), and 273 (58.7%) of PLWH were classified as having NCI by the IHDS, MMSE, and MoCA, compared to 90 (19.4%), 25 (5.4%), 135 (29.0%) of HIV-negative individuals, respectively (all p < 0.05); such associations Only MMSE revealed sex difference in NCI prevalence among PLWH. PLWH showed a larger overlap of NCI detected by IHDS, MMSE, and MoCA than HIV-negative people. Regarding cognitive domains, IHDS-motor and psychomotor speeds and MoCA-executive function showed the greatest disparities between two groups. In multivariable analysis, older age and more depressive symptoms were positively associated with NCI regardless of the screening tools or HIV serostatus. Conclusion PLWH display a higher prevalence of NCI and distinct neurocognitive profiles compared to HIV-negative individuals, despite viral suppression. Our data support that older PLWH tend to have deficits in multiple cognitive domains simultaneously. It is advisable to utilize the cognitive screening tools in conjunction to reveal complex patterns of cognitive deficits among PLWH, especially older PLWH. HIV cognitive impairment neurocognitive profile cognitive screening tools Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Despite the effective suppression of HIV replication and the subsequent improvement in life expectancy among people living with HIV (PLWH) through the use of combined antiretroviral therapy (cART), studies indicate that a considerable proportion, ranging from 19–67%, still experience varied degree of neurocognitive impairment (NCI) (Kellett-Wright et al.2021; Joska et al.2019; Makinson et al.2020; Lam et al.2021). This condition is commonly referred to as HIV-associated neurocognitive disorders (HAND). The HAND can be classified into three categories based on the severity of cognitive impairment and functional limitations: asymptomatic neurocognitive impairment (ANI), moderate neurocognitive disorder (MND), and HIV-associated dementia (HAD)( McArthur et al. 2010 ). The prevalence of NCI demonstrates notable disparities among several studies, potentially due to variations in demographic characteristics, comorbidity burdens and specific neurocognitive tools and classifications utilized(Joska et al.2019; Montanucci et al.2021; Pinto et al.2019; de Souza et al.2016; Omeragic et al.2020; Rubin et al.2019) In the cART era, cognitive impairment is frequently multifactorial, including direct effect of HIV on the brain as well as medication effects and various comorbidities(Rubin et al.2019; Saloner et al.2019; Giacometti et al.2019; Aung et al.2023). The neuropsychological profile of HAND in the post-cART era is becoming increasingly complex as a result of the combined effects of aging process and HIV infection(Ciccarelli 2020 ;Chiao et al.2013; Sacktor 2018 ). Prior to cART, individuals in advanced HIV often encountered a rapid progression of subcortical dementia, commonly referred to as HAD. Prior research has demonstrated that cART leads to in a less severe but more extensive clinical manifestation of cognitive impairment in PLWH, characterized by a mixed pattern of cortical and subcortical features, including greater deficits in executive functioning and working memory(Sacktor 2014 ). Neuropsychological testing batteries(Chiao et al.2013), encompassing a range of tests, is deemed the “gold standard” for diagnose HAND; however, this is time consuming and costly. Several authors have argued that this approach overestimates disease burden(Paul 2019 ). Cognitive screening tools is necessary in resource-limited settings or busy situations that are commonly seen among PLWH and aid in determining which individuals should be referred for additional neuropsychological assessment( Antinori et al.2007; Lyon et al.2009; Skinner et al.2009). NCI screening measures such as the International HIV dementia Scale (IHDS), Mini-mental state examination (MMSE) ,the Montreal cognitive assessment (MoCA),have become widely utilized due to their accessibility, brevity, sensitivity, and reliability(Joska et al.2016). These tools possess distinct characteristics that enable the evaluation of various cognitive domains. The IHDS demonstrates a notable degree of sensitivity in detecting sub-cortical dysfunction, like HAND(Lopardo et al.2009). In contrast, MMSE prioritizes the assessment of motor skills and timed tasks. It serves as a broad tool for detecting dementia and delirium( Trzepacz et al.2015). Moreover, MoCA exhibits greater sensitivity in PLWH who are experiencing MCI(Pinto et al.2019; Lopardo et al.2009). Numerous discussions have posited that the utilization of a composite of cognitive assessments may present a viable alternative to the exclusive reliance on a solitary screening instrument(Trunfio et al.2018; Underwoodet al.2019). In this study, we conducted a comparison of the three brief screening tools among virally suppressive PLWH aged over 50 years and age-, sex- and education-frequency matched HIV-negative individuals in a metropolitan region of China. The aim of our study was to examine potential differences in the assessment of cognitive impairment between these screening tools between PLWH and HIV-negative individuals, as well as to compare the neurocognitive profiles between the two groups. Methods Study Design This study included 465 PLWH and 465 HIV-negative individuals, who were frequency-matched in a 1:1 ratio considering factors such as age (± 3 years), sex, and education level. This was a baseline evaluation of the Pudong HIV Aging Cohort (PHAC), an ongoing prospective cohort focused on HIV and aging, initiated in 2017 and conducted in Pudong New Area, shanghai, which is one of the most developed districts in China. The cohort was structured to carry out parallel observations of PLWH and HIV-negative control individuals, with comparable age and sex. The PLWH who registered with the HIV/AIDS Comprehensive Response Information Management System (CRIMS)(Chen et al.2023; Shi et al.2022) were consecutively enrolled, and the HIV-negative control individuals were sourced from the same neighborhoods where the enlisted PLWH reside. PLWH in this study were consecutively recruited by their HIV care providers if met the inclusion criteria: aged over 50 years, initiated cART at least 6 months and HIV viral load < 40 copies/mL. Exclusion criteria included: they were confused; hearing loss; had an ongoing or past history of brain disease with clinical sequelae; had major psychiatric syndromes, sensorial loss, or co-infection with virus that may cause neurological abnormalities. The HIV-negative individuals who were recruited had similar inclusion and exclusion criteria as the PLWH except for the criteria related to HIV. The study was reviewed and approved by the Ethics Committee of Pudong New Area Center for Disease Control and Prevention. Written informed consent was required for this study in accordance with the national legislation and the institutional requirements. Data Collection Standardized structured questionnaire was administered to collect information on demographic characteristics, lifestyle behaviors and history of chronic conditions. Depressive symptoms were assessed by the Center for Epidemiologic Studies-Depression scale (CES-D) with cutoff score ≥ 16 (Santos et al.2021; Frain et al.2018). Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI), which global score ranges from 0 to 21 and > 5 indicating poor sleep quality( Frain et al.2018; Buysse et al.1989). Regular daily activities was defined as regular participation (at least twice a week, with each session lasting more than half an hour) in any one of the following five types of daily leisure activities: playing poker, mahjong or chess; calligraphy, painting, singing, or playing musical instruments; reading books or newspapers; doing handicrafts; practicing Tai Chi or square dance. Hypertension, diabetes and cardiovascular disease (CVD) was defined as previous diagnosis by physicians. HIV-related characteristics were extracted from CNISAPC. Nadir CD4 count was defined as the lowest CD4 count ever measured since HIV diagnosis. Current CD4 count was defined as the most recent CD4 count (within 2 months prior to survey or within 1 month after survey). Neurocognitive Assessment The IHDS, Chinese MMSE, and MoCA were administered by healthcare professionals who had completed their medical degrees and were employed as a health service provider. These professionals underwent a standardized training program for one week, which was provided by neurologists specializing in neurological and psychotic diseases at the Shanghai Pudong New Area Mental Health Center. The main reasons for using these three tools: First, all scales are brief and straightforward to administer. Second, aging PLWH have complex NCI symptoms that include cortical and subcortical dysfunctions. Finally, the cognitive tools were initially developed to evaluate various cognitive impairments. IHDS covers 3 domains including memory registration and recall, motor speed, psychomotor speed. The cut-off value for defining NCI was 10 (Yingying et al.2017). The cut-off value of ≤ 9 for defining NCI was also assessed( Molinaro et al.2020) that may be more appropriate for identifying NCI in those with low education level. MMSE covers 5 domains including orientation of place and time, memory registration, attention and calculation, memory recall, language. NCI was defined if MMSE ≤ 19 for those with no formal education; MMSE ≤ 22 for those with primary school education (≤ 6 years); MMSE ≤ 26 for those with junior school education or above (≥ 7 years) (Yingying et al.2017). MoCA covers visuospatial abilities, executive function, language, attention, concentration and working memory, short-term memory, orientation to time and place. NCI was defined if MoCA ≤ 26 for with junior school education or above (≥ 7 years) and ≤ 25 for the others(Pinto et al.2019). Statistical Analysis Analysis were performed using SAS software (version 9.11). Group differences were compared using Chi-square, Fisher’s exact, Student’s t-test, ANOVA, or Kruskal-Wallis tests. Generalized Linear Model (GLM) was utilized to examine the intertwined cognitive domains of HIV serostatus and sex. Pairwise comparisons were subsequently adjusted with Benjamini Hochberg. Multivariable logistic regressions were performed to identify the determinants of NCI. Results Participant characteristics A total of 465 PLWH and 465 HIV-negative individuals were included. As shown in Table 1, PLWH were more likely to be active smokers, had more depressive symptoms, and displayed greater physical activity. Alcohol use, hypertension, diabetes, and CVD events were comparable between both groups. Cognitive impairment between PLWH and HIV-negative individuals Overall, 258 (55.5%), 91 (19.6%), and 273 (58.7%) of PLWH were classified as NCI by IHDS, MMSE, and MoCA, compared to 90 (19.4%), 25 (5.4%), 135(29.0%) of HIV-negative individuals, respectively (all p <0.05) (Figure 1). Nearly all of NCI detected by MMSE were detected by IHDS or MoCA among PLWH, but about half of NCI detected by MMSE were detected by IHDS or MoCA among HIV-negative individuals. In general, the overlap of NCI detected by IHDS, MMSE, and MoCA was greater in PLWH than in HIV-negative individuals (22.1% vs 7.4%) (Figure 2). In multivariable analysis adjusting for potential confounders, HIV infection was independently associated with NCI using IHDS (≤ 10) (OR 5.10, 95% CI 3.68‒7.07), IHDS (≤ 9) (OR 7.20, 95% CI 4.97‒8.66), MMSE (OR 3.55, 95% CI 2.14‒5.91), and MoCA (OR 3.70, 95%CI 2.69‒5.08)), respectively (Supplementary Table 1). Table 1. Characteristics of PLWH and HIV-negative individuals Characteristics PLWH ( n = 465) HIV-negative individuals ( n = 465) p value Age, yr 60 (55‒65) 60 (55‒65) 0.856 Male 390 (83.9) 390 (83.9) 1.000 Education Primary or below 54 (11.6) 54 (11.6) 1.000 Middle school 188 (40.4) 188 (40.4) High school or above 223 (48.0) 223 (48.0) Marital status Never married 30 (6.5) 17 (3.7) 0.116 Married 332 (71.4) 351 (75.5) Divorced or widowed 103 (22.2) 97 (20.9) Current alcohol use 78 (16.8) 91 (19.6) 0.269 Current smoker 156 (33.6) 128 (27.7) 0.046 Regular daily activities 227 (48.8) 158 (34.0) <.001 Comorbid conditions History of hypertension 153 (32.9) 127 (27.3) 0.063 History of diabetes 47 (10.1) 49 (10.5) 0.914 History of CVD events 54 (11.6) 38 (8.2) 0.078 CES-D score 9 (3-18) 5 (0-16) <.001 Depression symptoms 154 (33.1) 92 (19.8) <.001 PSQI score 5 (2‒7) 4 (2‒6) 0.008 Poor sleep quality 199 (42.8) 159 (34.2) 0.007 Neurocognitive impairment NCI using IHDS ≤ 10 258 (55.5) 93 (20.0) <.001 ≤ 9 227 (48.8) 62 (13.3) <.001 NCI using MMSE 91 (19.6) 26 (5.6) <.001 NCI using MoCA 273 (58.7) 135 (29.0) <.001 HIV-related characteristics Nadir CD4 count <200 cells/μL 298 (64.1) Current CD4 count <350 cells/μL 148 (31.8) Time since HIV diagnosis ≥3 y 368 (79.1) Ever 2NRTI + EFV 352 (75.7) Data are presented as n (%) or median (IQR). Abbreviations: CVD, cardiovascular disease; EFV, efavirenz; NRTI, nucleotide reverse transcriptase inhibitors. After stratified by sex, using the IHDS (≤ 10), no significant difference was observed between female and male HIV-negative individuals (65.3% vs 53.1%, p =0.051), but significantly higher prevalence of NCI was observed among female than male HIV-negative individuals (29.3% vs 17.4%, p =0.017). In contrast, using the MMSE, significantly higher prevalence of NCI was observed among female than male PLWH (30.7% vs 17.4%, p =0.008), but no significant difference was observed among female and male HIV-negative individuals (8.0% vs 5.1%, p =0.322). Using the MoCA, no significant sex difference was observed in the prevalence of NCI, irrespective of HIV serostatus. Further stratified by age groups, prevalence of NCI increased with age regardless of screening tools and sex except that similar prevalence of NCI using IHDS were observed among female PLWH aged 50‒59years and 60‒69 years. Furthermore, the differences in NCI prevalence between PLWH and HIV-negative individuals were most pronounced for the youngest age group (ie, 50‒59 years), regardless of screening tools (Figure 1). Neurocognitive profiles between PLWH and HIV-negative individual s Next, we compared the mean IHDS, MMSE and MoCA composite scores and their domain subscores between PLWH and HIV-negative individuals and further stratified by sex (Table 2) and age groups (Figure 3). The composite scores and each domain subscore of IHDS, MMSE and MoCA were markedly lower in PLWH vs HIV-negative individuals except for the IHDS-memory registration and recall, MMSE-orientation, MoCA-orientation subscores (Table 2). The most notable differences between the two groups in the domain subscores were IHDS-motor and psychomotor speeds followed by MoCA-executive function (Table 2 and Figure 2). After stratified by sex and across the four groups, subsequent pairwise comparisons indicated that sex differences were observed in IHDS-motor speed, MoCA-executive function, attention, concentration and working memory, and language as well as composite scores of IHDS, MoCA among both PLWH and HIV-negative individuals. Sex difference in the MMSE composite score and MMSE-language subscore were only observed among PLWH (Table 2). After further stratified by age groups, female PLWH and HIV-negative individuals at the oldest age group tended to have notable lowest subscores in most of domains of IHDS, MMSE and MoCA except for memory registration, orientation,, suggesting a combined effects of HIV infection, aging and sex (Figure 3). Factors associated with NCI by HIV serostatus Multivariable logistic analysis of factors associated with NCI using IHDS, MMSE and MoCA stratified by HIV serostatus were shown in Figure 4, respectively. In multivariable analysis, only older age and more depressive symptoms were positively associated with NCI regardless of the screening tools or HIV serostatus. For the NCI using IHDS, higher education level and regular daily activities were negatively associated n with NCI regardless HIV serostatus. Active smokers was positively associated with NCI (OR 1.75; 95% CI 1.12‒2.73) among PLWH, whereas poor sleep quality was positively associated NCI among HIV-negative individuals (OR 1.79; 95% CI 1.06‒3.03) (Figure 4). Table 2. Neurocognitive domains compared by HIV serostatus and sex Neurocognitive domains HIV serostatus* PLWH HIV-negative individuals p value Group contrasts b PLWH HIV-negative individuals F value p value Female (1) Male (2) Female (3) Male (4) HIV status a Sex a HIV status ×sex a IHDS /score Memory registration and recall/4 3.28 3.34 1.24 0.266 3.19 3.23 3.30 3.36 0.271 0.128 0.930 No diff Motor speed/4 2.37 3.56 570.7 <.001 2.13 2.41 3.32 3.61 <.001 <.001 0.845 1<2,3;2,3<4 Psychomotor speed/4 2.54 3.54 308.4 <.001 2.30 2.59 3.38 3.57 <.001 0.003 0.608 1<3;2<4 Total/12 8.27 10.43 380.0 <.001 7.71 8.38 9.88 10.54 <.001 <.001 0.903 1<2,3;2,3<4 MMSE /score Orientation/10 9.83 9.82 0.04 0.848 9.82 9.83 9.77 9.83 <.001 0.001 0.991 No diff Memory registration/3 2.78 2.87 7.9 0.005 2.76 2.82 2.93 2.86 0.005 0.624 0.257 No diff Attention and calculation/5 4.07 4.42 25.9 <.001 3.80 4.12 4.17 4.47 <.001 0.001 0.991 2<4 Memory recall/3 2.41 2.71 44.4 <.001 2.32 2.43 2.69 2.72 <.001 0.255 0.539 1<3;2<4 Language/9 8.38 8.71 31.5 <.001 7.92 8.47 8.54 8.74 <.001 <.001 0.034 1<2,3;2<4 Total/30 27.49 28.50 47.4 <.001 26.62 27.65 28.12 28.64 <.001 0.005 0.287 1<2,3;2<4 MoCA /score Visuospatial abilities/4 2.73 3.14 35.6 <.001 2.69 2.74 2.80 3.20 0.003 0.041 0.040 2,3<4 Executive functions/4 2.43 3.15 106.1 <.001 1.99 2.51 2.75 3.23 <.001 <.001 0.989 1<2,3;2,3<4 Attention, concentration, and working memory/6 5.14 5.55 46.1 <.001 4.83 5.21 5.29 5.60 <.001 0.000 0.801 1<2,3;2,3<4 Language/5 3.76 4.09 19.9 <.001 3.04 3.90 3.80 4.14 <.001 <.001 0.014 1<2,3;2,3<4 Short-term memory/5 2.71 3.48 69.0 <.001 2.45 2.76 3.48 3.48 <.001 <.001 0.843 1<3;2<4 Orientation to time and place/6 5.86 5.88 0.2 0.638 5.73 5.88 5.83 5.89 0.337 0.039 0.364 No diff Total /30 23.50 26.1 116.6 <.001 21.72 23.85 24.93 26.38 <.001 <.001 0.432 1<2,3;2,3<4 *Multivariate analysis was performed on the scores by HIV serostatus, adjusting by age, sex and education. GLM was utilized to examine the intertwined cognitive domains of HIV serostatus. a GLM was utilized to examine the intertwined cognitive domains of HIV serostatus and sex. b Four pairwise comparisons (1 vs 2, 1 vs 3, 2 vs 4 and 3 vs 4) were performed and subsequently adjusted using the Benjamini Hochberg procedure. No diff=no difference. For the NCI using MMSE, female (OR 2.27; 95% CI 1.12‒4.62), active alcohol users (OR 2.27; 95% CI 1.17‒4.43), diabetes (OR 2.84; 95% CI 1.29‒6.27) and undergoing efavirenz (EFV) treatment (OR 2.2; 95% CI 1.11‒4.69) were positively associated with NCI among PLWH, whereas, higher education level was negatively associated with NCI (OR 0.19; 95% CI 0.05‒0.69) and hypertension was positively associated with NCI (OR 3.52; 95% CI 1.25‒5.88) among HIV-negatively individuals (Figure 4). For the NCI using MoCA, higher education level (OR 0.26; 95% CI 0.15‒0.45) and regular daily activities (OR 0.26; 95% CI, 0.14‒0.47) were negatively associated with NCI, and poor sleep quality were positively associated with NCI (OR 3.08; 95% CI 1.79‒5.28) among HIV-negative individuals. In contrast, none of the aforementioned factors were significantly associated with NCI among PLWH (Figure 4). Discussion The findings of our study demonstrate a distinct prevalence of NCI as assessed by the IHDS, MMSE and MoCA. The IHDS and MoCA tools identified a greater prevalence of NCI in PLWH as compared to MMSE. This tendency can be attributed to the fact that these tools are specifically developed to identify various forms of cognitive impairment. The MMSE is primarily designed to assess cognitive impairment associated with dementia. On the other hand, the MoCA has been specifically designed to identify mild cognitive impairments(Pinto et al.2019; Lopardo et al.2009). Conversely, the IHDS is developed to identify minor cognitive deficits in sub-cortical areas among PLWH, comprising impairments that occur in the early stages as well as those of lesser severity(Montanuccet al.2021). The prevalence of NCI among our PLWH, as assessed by IHDS and MMSE, were similar to previous reports from developing counties(Kellett-Wright et al.2021;Yingying et al.2017; Qiao et al.2019). However, MoCA detected a lower prevalence among PLWH in our study compared to early investigations( Milanini et al.2016; Selvaraj et al.2023). Such discrepancy may be partly explained by the difference in timing of ART initiation. It’s interesting to note that PLWH showed a larger overlap of NCI detected by IHDS, MMSE, and MoCA than HIV-negative people, indicating that aged PLWH are more likely to have deficits in multiple cognitive domains simultaneously( Sacktor et al.2014). Subsequent comparisons of all cognitive domains covered the IHDS, MMSE, and MoCA tools revealed distinct neurocognitive profiles between PLWH and HIV-negative individuals. The most prominent disparities observed between the two identified groups were in terms of IHDS-motor speed and psychomotor speed, as well as MoCA-executive function. It has been demonstrated that during the pre-ART era, HIV infection could exert a detrimental impact on both motor and psychomotor speeds, primarily targeting the subcortical regions of the brain(Lam et al.2021). Our results suggest that treated PLWH continued to experience cognitive impairment in subcortical regions despite viral suppression. This highlights the importance of using the IHDS evaluate the cognitive dysfunction in the post-ART era. Our finding also revealed sex difference in the prevalence of NCI. Specifically, it was seen that females had a higher prevalence of NCI than males; however, this disparity depends on the screening tools used and HIV serostatus. The MMSE was the only tool that revealed significant sex difference among PLWH, which is consistent with previous reports using MMSE(Qiao et al.2019;Sundermanet al.2018; Burlacu et al.2018). In contrast, the MoCA was the only tool demonstrating sex difference among HIV-negative individuals, whereas IHDS did not detect any sex difference in the both groups. The lack of sex difference in NCI prevalence by MoCA among PLWH is likely attributable to the floor effect( Pinto et al.2019; Dang et al.2015) as both groups had higher prevalence of NCI. As our data further indicated, sex differences were observed in the composite scores of IHDS and MoCA, as well as subscores of IHDS-motor speed, MoCA-executive function, attention, concentration and working memory, and language among both PLWH and HIV-negative individuals; however, sex difference in the MMSE composite score and MMSE-language subscore were only observed among PLWH. Collectively, these findings imply that HIV infection and sex may have distinct effects on cognitive domains, and thus there is a sex difference in NCI prevalence as assessed by various screening tools. Moreover, our data reinforce the evidence that the IHDS predominantly reflects the cognitive impairment associated with HIV, and additionally indicate that the MMSE reflects the cognitive impairment due to combined effects of HIV infection and sex. These emphasize the need to employ a combination of neurocognitive screening tools to provide a comprehensive assessment of cognitive impairment in PLWH, thereby facilitate early detection and intervention. In addition, consistent with previous studies(Saloner et al.2019;Aung et al.2023), we found that older age and depressive symptoms were consistently associated with NCI, regardless of HIV serostatus and the screening tools, suggesting that aging and depression play an important role in various cognitive impairments. Given the high prevalence of depression in PLWH( Joska et al.2016) and their robust link to cognitive impairment, a deeper understanding of whether treating or alleviating depressive symptoms can improve cognitive health among PLWH and its underlying mechanism are warranted(Williams et al.2020; Mudraet al.2022;Rubin et al.2019) . Consistent with previous findings( Qiao et al.2019; Burlacu et al.2018), female PLWH were more likely to have NCI than male PLWH, as assessed by MMSE, indicating a synergistic effect of HIV infection and female on specific cognitive domains(Qiao et al.2019) such as language as our data indicated. Current alcohol use was also associated with NCI using MMSE. Long-term alcohol use may cause immunological damage, which may cause neuropsychological deficits that eventually lead to dementia( Rianawati et al.2021). Alcohol use has been found to interact with HIV infection to worsen cognitive impairment(Green et al.2004). Our investigation also revealed that EFV use was associated with NCI using MMSE. However, this association was not observed when NCI was evaluated using either IHDS or MoCA. Animal studies have revealed CNS toxicity related to EFV use(Borrajo et al.2021). In conjunction with our findings, these data suggest that EFV could potentially add the risk of NCI. Our study additionally indicates that a greater level of education and regular daily activities, may exert a protective effect against NCI, as evaluated by the IHDS. Several limitations should be noted. First, this was cross-sectional design, hence could not assess temporal or causal relationship between factors of interest and the development of NCI. Second, all subjects were only recruited from Shanghai, China, which may could potentially restrict the generalizability of our findings to other geographic areas. Third, the lack of neurocognitive testing battery limits hinders the ability to evaluate the accuracy of these screening tools in identifying NCI. In summary, PLWH exhibit a higher prevalence of NCI and distinct neurocognitive profiles compared to comparable HIV-negative individuals, despite viral suppression. The cognitive screening tools show variations in the detection of NCI prevalence which is also depending on age, sex and HIV serostatus. Our data support the notion that older PLWH tend to have deficits in multiple cognitive domains simultaneously. Given that various diverse screening tools can identify distinct aspects of cognitive dysfunction, it is advisable to utilize these screening tools in conjunction to uncover complex patterns of cognitive impairment among PLWH, especially older PLWH, and thereby promote early detection and intervention. Declarations Ethics statement The studies involving Human participants had been carried out in accordance with the Declaration Helsinki. The studies were reviewed and approved by the Ethics Committee of Pudong New Area Center for Disease Control and Prevention. Written informed consent was obtained from the individual(s). Author contributions Panpan Chen, Yingying Ding and Na He contributed to the conception or design of the work. Panpan Chen, Xin Xin, Shaotan Xiao contributed to supervising subject enrollment and data collection. Panpan Chen and Xin Xin contributed to data analysis and manuscript draft. Hantao Liu, Xin Liu contributed to the data collection. Yingying Ding critically revised the manuscript. All authors critically reviewed and edited the manuscript and consented to final publication. Panpan Chen and Xin Xin conceived the study and contributed equally to this study and should be considered co-first authors. Yingying Ding and Na He should be considered co-corresponding authors. Conflicts of interest The authors declare that they have no conflict of interest. Data Availability The data which support the conclusions of our study is included within the article. Acknowledgments The authors wish to thank all study participants. Funding This research was supported by Research Grant for Health Science and Technology of Pudong New Area Health Commission of Shanghai (No. PW2020A-10), Pudong New Area Science and Technology Development Innovation fund (No. PKJ2023-Y71), Academic Leaders Training Program of Pudong Health Commission of Shanghai (No. PWRd2022-01), Medical discipline Construction Project of Pudong Health Committee of Shanghai(No. PWYgts2021-04), National Natural Science Foundation of China (No. 82173579), and Shanghai three-year (No. 2023-2025) action plan to strengthen the public health system (No. GWVI-11.1-05). References Antinori A, Arendt G, Becker JT, Brew BJ, Byrd DA, Cherner M, Clifford DB, Cinque P, Epstein LG, Goodkin K, Gisslen M, Grant I, Heaton RK, Joseph J, Marder K, Marra CM, McArthur JC, Nunn M, Price RW, Pulliam L, Robertson KR, Sacktor N, Valcour V, Wojna VE. Updated research nosology for HIV-associated neurocognitive disorders. Neurology, 2007. 69(18): p. 1789-1799. 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Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res, 1989. 28(2): p. 193-213. Chen PP, Wei XY, Tao L, Xin X, Xiao ST, He N. Cerebral abnormalities in HIV-infected individuals with neurocognitive impairment revealed by fMRI. Scientific Reports, 2023. 13(1). Chiao S, Rosen HJ, Nicolas K, Wendelken LA, Alcantar O, Rankin KP, Miller B, Valcour V. Deficits in Self-Awareness Impact the Diagnosis of Asymptomatic Neurocognitive Impairment in HIV. AIDS Research and Human Retroviruses, 2013. 29(6): p. 949-956. Ciccarelli N., Considerations on nosology for HIV-associated neurocognitive disorders: it is time to update? Infection, 2020. 48(1): p. 37-42. Dang C, Wei B, Long J, Zhou M, Han X, Zhao T. Validity of the International HIV Dementia Scale as Assessed in a Socioeconomically Underdeveloped Region of Southern China: Assessing the Influence of Educational Attainment. International Journal of Infection Disease, 2015 Apr:33:56-61. de Souza EM, Buoniconti CS, Valim FC, Moura AS. Risk factors for neurocognitive impairment in HIV-infected patients and comparison of different screening tools. Dement Neuropsychol, 2016. 10(1): p. 42-46. Frain JA, Chen L. Examining the effectiveness of a cognitive intervention to improve cognitive function in a population of older adults living with HIV: a pilot study. Therapeutic Advances in Infectious Disease, 2018. 5(1): p. 19-28. Giacometti LL, Barker JM. Comorbid HIV infection and alcohol use disorders: Converging glutamatergic and dopaminergic mechanisms underlying neurocognitive dysfunction. Brain Research, 2019. 1723: p. 146390. Green JE, Saveanu RV, Bornstein RA. Bornstein, The effect of previous alcohol abuse on cognitive function in HIV infection. Am J Psychiatry, 2004. 161(2): p. 249-54. Joska JA, Witten J, Thomas KG, Robertson C, Casson-Crook M, Roosa H, Creighton J, Lyons J, McArthur J, Sacktor NC. A Comparison of Five Brief Screening Tools for HIV-Associated Neurocognitive Disorders in the USA and South Africa. AIDS and Behavior, 2016. 20(8): p. 1621-1631. Joska JA, Dreyer AJ, Nightingale S, Combrinck MI, De Jager CA. Prevalence of HIV-1 Infection in an elderly rural population and associations with neurocognitive impairment. AIDS, 2019. 33(11): p. 1765-1771. Lam JO, Hou CE, Hojilla JC, Anderson AN, Gilsanz P, Alexeeff SE, Levine-Hall T, Hood N, Lee C, Satre DD, Silverberg MJ. Comparison of dementia risk after age 50 between individuals with and without HIV infection. AIDS, 2021. 35(5): p. 821-828. Lopardo GD, Bissio E, Iannella Mdel C, Crespo AD, Garone DB, Cassetti LI. Good neurocognitive performance measured by the international HIV dementia scale in early HIV-1 infection. J Acquir Immune Defic Syndr, 2009. 52(4): p. 488-92. Lyon ME, McCarter R, D'Angelo LJ. Detecting HIV Associated Neurocognitive Disorders in Adolescents: What Is the Best Screening Tool? Journal of Adolescent Health, 2009. 44(2): p. 133-135. Makinson A, Dubois J, Eymard-Duvernay S, Leclercq P, Zaegel-Faucher O, Bernard L, Vassallo M, Barbuat C, Gény C, Thouvenot E, Costagliola D, Ozguler A, Zins M, Simony M, Reynes J, Berr C. Increased Prevalence of Neurocognitive Impairment in Aging People Living With Human Immunodeficiency Virus: The ANRS EP58 HAND 55-70 Study. Clinical Infectious Diseases, 2020. 70(12): p. 2641-264 McArthur JC, Steiner J, Sacktor N, Nath A. Human immunodeficiency virus-associated neurocognitive disorders: Mind the gap. Annals of Neurology, 2010: p. NA-NA. Molinaro M, Sacktor N, Nakigozi G, Anok A, Batte J, Kisakye A, Myanja R, Nakasujja N, Robertson KR, Gray RH, Wawer MJ, Saylor D. Utility of the International HIV Dementia Scale for HIV-Associated Neurocognitive Disorder. JAIDS Journal of Acquired Immune Deficiency Syndromes, 2020. 83(3): p. 278-283. Montanucci C, Chipi E, Salvadori N, Rinaldi R, Eusebi P, Parnetti L. HIV-Dementia Scale as a screening tool for the detection of subcortical cognitive deficits: validation of the Italian version. Journal of Neurology, 2021. 268(12): p. 4789-4795. Mudra, R.A., et al., Neuroinflammation in HIV-associated depression: evidence and future perspectives. Mol Psychiatry, 2022. 27(9): p. 3619-3632. Mudra Rakshasa-Loots A, Whalley HC, Vera JH, Cox SR. Potential pharmacological approaches for the treatment of HIV-1 associated neurocognitive disorders. Fluids and Barriers of the CNS, 2020. 17(1). Paul R. Neurocognitive Phenotyping of HIV in the Era of Antiretroviral Therapy. Current HIV/AIDS Reports, 2019. 16(3): p. 230-235. Qiao X, Lin H, Chen X, Ning C, Wang K, Shen W, Xu X, Xu X, Liu X, He N, Ding Y. Sex differences in neurocognitive screening among adults living with HIV in China. Journal of NeuroVirology, 2019. 25(3): p. 363-371. Rianawati S, Andriani N, Munir B, Raisa N. Serial case of HIV associated neurocognitive disorder. Journal of the Neurological Sciences, 2021. 429: p. 117683. Rubin LH, Maki PM. HIV, Depression, and Cognitive Impairment in the Era of Effective Antiretroviral Therapy. Current HIV/AIDS Reports, 2019. 16(1): p. 82-95. Rubin LH, Gustafson D, Hawkins KL, Zhang L, Jacobson LP, Becker JT, Munro CA, Lake JE, Martin E, Levine A, Brown TT, Sacktor N, Erlandson KM. Midlife adiposity predicts cognitive decline in the prospective Multicenter AIDS Cohort Study. Neurology, 2019. 93(3): p. e261-e271. Sacktor N, Robertson K. Evolving clinical phenotypes in HIV-associated neurocognitive disorders. Current Opinion in HIV and AIDS, 2014. 9(6): p. 517-520. Sacktor N. Changing clinical phenotypes of HIV-associated neurocognitive disorders. Journal of NeuroVirology, 2018. 24(2): p. 141-145. Saloner R, Campbell LM, Serrano V, Montoya JL, Pasipanodya E, Paolillo EW, Franklin D, Ellis RJ, Letendre SL, Collier AC, Clifford DB, Gelman BB, Marra CM, McCutchan JA, Morgello S, Sacktor N, Jeste DV, Grant I, Heaton RK, Moore DJ. Neurocognitive SuperAging in Older Adults Living With HIV: Demographic, Neuromedical and Everyday Functioning Correlates. Journal of the International Neuropsychological Society, 2019. 25(05): p. 5 Santos G, Locatelli I, Métral M, Berney A, Nadin I, Calmy A, Tarr P, Gutbrod K, Hauser C, Brugger P, Kovari H, Kunze U, Stoeckle M, Früh S, Schmid P, Rossi S, Di Benedetto C, Du Pasquier R, Darling K, Cavassini M. The association between depressive symptoms and neurocognitive impairment in people with well-treated HIV in Switzerland. International Journal of STD & AIDS, 2021. 32(8): p. 729-739. Shi R, Chen X, Lin H, Shen W, Xu X, Zhu B, Xu X, Ding Y, He N. Interaction of sex and HIV infection on renal impairment: baseline evidence from the CHART cohort. International Journal of Infectious Diseases, 2022. 116: p. 182-188. Skinner S, Adewale AJ, DeBlock L, Gill MJ, Power C. Neurocognitive screening tools in HIV/AIDS: comparative performance among patients exposed to antiretroviral therapy. HIV Medicine, 2009. 10(4): p. 246-252. Sundermann EE, Heaton RK, Pasipanodya E, Moore RC, Paolillo EW, Rubin LH, Ellis R, Moore DJ. Sex differences in HIV-associated cognitive impairment. AIDS, 2018. 32(18): p. 2719-2726. Trunfio M, Vai D, Montrucchio C, Alcantarini C, Livelli A, Tettoni MC, Orofino G, Audagnotto S, Imperiale D, Bonora S, Di Perri G, Calcagno A. Diagnostic accuracy of new and old cognitive screening tools for HIV-associated neurocognitive disorders. HIV Medicine, 2018. 19(7): p. 455-464. Trzepacz PT, Hochstetler H, Wang S, Walker B, Saykin AJ. Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults. BMC Geriatrics, 2015. 15(1). Underwood J, De Francesco D, Cole JH, Caan MWA, van Zoest RA, Schmand BA, Sharp DJ, Sabin CA, Reiss P, Winston A. Validation of a Novel Multivariate Method of Defining HIV-Associated Cognitive Impairment. Open Forum Infectious Diseases, 2019. 6(6). Williams ME, Joska JA, Amod AR, Paul RH, Stein DJ, Ipser JC, Naudé PJW. The association of peripheral immune markers with brain cortical thickness and surface area in South African people living with HIV. Journal of NeuroVirology, 2020. 26(6): p. 908-919. Ding Y, Lin H, Shen W, Wu Q, Gao M, He N. Interaction Effects between HIV and Aging on Selective Neurocognitive Impairment. Journal of Neuroimmune Pharmacology, 2017(12): p. 661-669. Kellett-Wright J, Flatt A, Eaton P, Urasa S, Howlett W, Dekker M, Kisoli A, Duijinmaijer A, Thornton J, McCartney J, Yarwood V, Irwin C, Mukaetova-Ladinska E, Akinyemi R, Lwezuala B, Gray WK, Walker RW, Dotchin CL, Makupa P, Paddick SM. Screening for HIV-Associated Neurocognitive Disorder (HAND) in Adults Aged 50 and Over Attending a Government HIV Clinic in Kilimanjaro, Tanzania. Comparison of the International HIV Dementia Scale (IHDS) and IDEA Six Item Dementia Screen. AIDS and Behavior, 2021. 25(2): p. 542-553. Milanini B, Ciccarelli N, Fabbiani M, Baldonero E, Limiti S, Gagliardini R, Borghetti A, D'Avino A, Mondi A, Colafigli M, Cauda R, Di Giambenedetto S. Neuropsychological screening tools in Italian HIV+ patients: a comparison of Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE). Clin Neuropsychol, 2016. 30(sup1): p. 1457-1468. Pinto TCC, Machado L, Bulgacov TM, Rodrigues-Júnior AL, Costa MLG, Ximenes RCC, Sougey EB. Is the Montreal Cognitive Assessment (MoCA) screening superior to the Mini-Mental State Examination (MMSE) in the detection of mild cognitive impairment (MCI) and Alzheimer's Disease (AD) in the elderly? International Psychogeriatrics, 2019. 31(04): p. 491-504. Selvaraj N, Chidambaram Y, Dhas CPCJ, Nekkanti A, Velammal P, Kumar B, Alagesan M. Prevalence of Asymptomatic HIV Associated Neurocognitive Disorder in a Tertiary Care Hospital in South India: A Single Centre Observational Study. Mediterranean Journal of Infection Microbes and Antimicrobials, 2023. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 May, 2024 Read the published version in Journal of NeuroVirology → Version 1 posted Editorial decision: Revision requested 13 Mar, 2024 Reviews received at journal 10 Mar, 2024 Reviewers agreed at journal 07 Feb, 2024 Reviewers invited by journal 07 Feb, 2024 Editor assigned by journal 06 Feb, 2024 Submission checks completed at journal 06 Feb, 2024 First submitted to journal 06 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3932903","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271646971,"identity":"bc497120-2b55-4869-a65b-2cb44085e757","order_by":0,"name":"Panpan Chen","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Panpan","middleName":"","lastName":"Chen","suffix":""},{"id":271646972,"identity":"3acf84d0-5cee-4f1d-9bb6-b640b121f7e0","order_by":1,"name":"Xin Xin","email":"","orcid":"","institution":"Fudan 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University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Ding","suffix":""}],"badges":[],"createdAt":"2024-02-06 05:36:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3932903/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3932903/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13365-024-01205-y","type":"published","date":"2024-05-06T16:52:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50877313,"identity":"d1776df6-7111-441b-b91c-c0901dbc15fe","added_by":"auto","created_at":"2024-02-08 19:18:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20966,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of neurocognitive impairment using IHDS, MMSE and MoCA tools: Stratification by HIV serostatus, Sex and Age Groups.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3932903/v1/b1e96b191907aff01f8fd6ab.png"},{"id":50877317,"identity":"43aa97b8-cf39-489e-8f6e-80f0cf033647","added_by":"auto","created_at":"2024-02-08 19:18:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24716,"visible":true,"origin":"","legend":"\u003cp\u003eThe overlap of NCI detected by IHDS, MMSE, and MoCA screening tools by HIV serostatus.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3932903/v1/82c99651c195678c9d506971.png"},{"id":50877314,"identity":"e376678a-d5f0-4af2-a27f-1dfc8af1effb","added_by":"auto","created_at":"2024-02-08 19:18:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":97541,"visible":true,"origin":"","legend":"\u003cp\u003eNeurocognitive profiles among PLWH and HIV-negative individuals, stratified by sex and age groups.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3932903/v1/aeed788aaae0a76533e33f4f.png"},{"id":50877316,"identity":"dfb56b56-5148-430f-8502-195365d4dc95","added_by":"auto","created_at":"2024-02-08 19:18:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56004,"visible":true,"origin":"","legend":"\u003cp\u003eLogistic regression models on factors associated with NCI using the IHDS MMSE,and MoCA by HIV serostatus.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3932903/v1/b43401e4c7a6294a609a3b83.png"},{"id":50877558,"identity":"54fb5cc0-3fb6-4164-8e04-575bd8d5ef0d","added_by":"auto","created_at":"2024-02-08 19:26:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1248868,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3932903/v1/a1c251e2-1cb7-4ce0-be28-c28488946999.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cognitive impairment and neurocognitive profiles among people living with HIV and HIV- negative individuals older over 50 years: a comparison of IHDS, MMSE and MoCA","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDespite the effective suppression of HIV replication and the subsequent improvement in life expectancy among people living with HIV (PLWH) through the use of combined antiretroviral therapy (cART), studies indicate that a considerable proportion, ranging from 19\u0026ndash;67%, still experience varied degree of neurocognitive impairment (NCI) (Kellett-Wright et al.2021; Joska et al.2019; Makinson et al.2020; Lam et al.2021). This condition is commonly referred to as HIV-associated neurocognitive disorders (HAND). The HAND can be classified into three categories based on the severity of cognitive impairment and functional limitations: asymptomatic neurocognitive impairment (ANI), moderate neurocognitive disorder (MND), and HIV-associated dementia (HAD)( McArthur et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The prevalence of NCI demonstrates notable disparities among several studies, potentially due to variations in demographic characteristics, comorbidity burdens and specific neurocognitive tools and classifications utilized(Joska et al.2019; Montanucci et al.2021; Pinto et al.2019; de Souza et al.2016; Omeragic et al.2020; Rubin et al.2019) In the cART era, cognitive impairment is frequently multifactorial, including direct effect of HIV on the brain as well as medication effects and various comorbidities(Rubin et al.2019; Saloner et al.2019; Giacometti et al.2019; Aung et al.2023).\u003c/p\u003e \u003cp\u003eThe neuropsychological profile of HAND in the post-cART era is becoming increasingly complex as a result of the combined effects of aging process and HIV infection(Ciccarelli \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e;Chiao et al.2013; Sacktor \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Prior to cART, individuals in advanced HIV often encountered a rapid progression of subcortical dementia, commonly referred to as HAD. Prior research has demonstrated that cART leads to in a less severe but more extensive clinical manifestation of cognitive impairment in PLWH, characterized by a mixed pattern of cortical and subcortical features, including greater deficits in executive functioning and working memory(Sacktor \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Neuropsychological testing batteries(Chiao et al.2013), encompassing a range of tests, is deemed the \u0026ldquo;gold standard\u0026rdquo; for diagnose HAND; however, this is time consuming and costly. Several authors have argued that this approach overestimates disease burden(Paul \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Cognitive screening tools is necessary in resource-limited settings or busy situations that are commonly seen among PLWH and aid in determining which individuals should be referred for additional neuropsychological assessment( Antinori et al.2007; Lyon et al.2009; Skinner et al.2009).\u003c/p\u003e \u003cp\u003eNCI screening measures such as the International HIV dementia Scale (IHDS), Mini-mental state examination (MMSE) ,the Montreal cognitive assessment (MoCA),have become widely utilized due to their accessibility, brevity, sensitivity, and reliability(Joska et al.2016). These tools possess distinct characteristics that enable the evaluation of various cognitive domains. The IHDS demonstrates a notable degree of sensitivity in detecting sub-cortical dysfunction, like HAND(Lopardo et al.2009). In contrast, MMSE prioritizes the assessment of motor skills and timed tasks. It serves as a broad tool for detecting dementia and delirium( Trzepacz et al.2015). Moreover, MoCA exhibits greater sensitivity in PLWH who are experiencing MCI(Pinto et al.2019; Lopardo et al.2009). Numerous discussions have posited that the utilization of a composite of cognitive assessments may present a viable alternative to the exclusive reliance on a solitary screening instrument(Trunfio et al.2018; Underwoodet al.2019).\u003c/p\u003e \u003cp\u003eIn this study, we conducted a comparison of the three brief screening tools among virally suppressive PLWH aged over 50 years and age-, sex- and education-frequency matched HIV-negative individuals in a metropolitan region of China. The aim of our study was to examine potential differences in the assessment of cognitive impairment between these screening tools between PLWH and HIV-negative individuals, as well as to compare the neurocognitive profiles between the two groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study included 465 PLWH and 465 HIV-negative individuals, who were frequency-matched in a 1:1 ratio considering factors such as age (\u0026plusmn;\u0026thinsp;3 years), sex, and education level. This was a baseline evaluation of the Pudong HIV Aging Cohort (PHAC), an ongoing prospective cohort focused on HIV and aging, initiated in 2017 and conducted in Pudong New Area, shanghai, which is one of the most developed districts in China. The cohort was structured to carry out parallel observations of PLWH and HIV-negative control individuals, with comparable age and sex. The PLWH who registered with the HIV/AIDS Comprehensive Response Information Management System (CRIMS)(Chen et al.2023; Shi et al.2022) were consecutively enrolled, and the HIV-negative control individuals were sourced from the same neighborhoods where the enlisted PLWH reside. PLWH in this study were consecutively recruited by their HIV care providers if met the inclusion criteria: aged over 50 years, initiated cART at least 6 months and HIV viral load\u0026thinsp;\u0026lt;\u0026thinsp;40 copies/mL. Exclusion criteria included: they were confused; hearing loss; had an ongoing or past history of brain disease with clinical sequelae; had major psychiatric syndromes, sensorial loss, or co-infection with virus that may cause neurological abnormalities. The HIV-negative individuals who were recruited had similar inclusion and exclusion criteria as the PLWH except for the criteria related to HIV.\u003c/p\u003e \u003cp\u003e The study was reviewed and approved by the Ethics Committee of Pudong New Area Center for Disease Control and Prevention. Written informed consent was required for this study in accordance with the national legislation and the institutional requirements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eStandardized structured questionnaire was administered to collect information on demographic characteristics, lifestyle behaviors and history of chronic conditions. Depressive symptoms were assessed by the Center for Epidemiologic Studies-Depression scale (CES-D) with cutoff score\u0026thinsp;\u0026ge;\u0026thinsp;16 (Santos et al.2021; Frain et al.2018). Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI), which global score ranges from 0 to 21 and \u0026gt;\u0026thinsp;5 indicating poor sleep quality( Frain et al.2018; Buysse et al.1989). Regular daily activities was defined as regular participation (at least twice a week, with each session lasting more than half an hour) in any one of the following five types of daily leisure activities: playing poker, mahjong or chess; calligraphy, painting, singing, or playing musical instruments; reading books or newspapers; doing handicrafts; practicing Tai Chi or square dance. Hypertension, diabetes and cardiovascular disease (CVD) was defined as previous diagnosis by physicians. HIV-related characteristics were extracted from CNISAPC. Nadir CD4 count was defined as the lowest CD4 count ever measured since HIV diagnosis. Current CD4 count was defined as the most recent CD4 count (within 2 months prior to survey or within 1 month after survey).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eNeurocognitive Assessment\u003c/h2\u003e \u003cp\u003eThe IHDS, Chinese MMSE, and MoCA were administered by healthcare professionals who had completed their medical degrees and were employed as a health service provider. These professionals underwent a standardized training program for one week, which was provided by neurologists specializing in neurological and psychotic diseases at the Shanghai Pudong New Area Mental Health Center. The main reasons for using these three tools: First, all scales are brief and straightforward to administer. Second, aging PLWH have complex NCI symptoms that include cortical and subcortical dysfunctions. Finally, the cognitive tools were initially developed to evaluate various cognitive impairments.\u003c/p\u003e \u003cp\u003eIHDS covers 3 domains including memory registration and recall, motor speed, psychomotor speed. The cut-off value for defining NCI was 10 (Yingying et al.2017). The cut-off value of \u0026le;\u0026thinsp;9 for defining NCI was also assessed( Molinaro et al.2020) that may be more appropriate for identifying NCI in those with low education level. MMSE covers 5 domains including orientation of place and time, memory registration, attention and calculation, memory recall, language. NCI was defined if MMSE\u0026thinsp;\u0026le;\u0026thinsp;19 for those with no formal education; MMSE\u0026thinsp;\u0026le;\u0026thinsp;22 for those with primary school education (\u0026le;\u0026thinsp;6 years); MMSE\u0026thinsp;\u0026le;\u0026thinsp;26 for those with junior school education or above (\u0026ge;\u0026thinsp;7 years) (Yingying et al.2017). MoCA covers visuospatial abilities, executive function, language, attention, concentration and working memory, short-term memory, orientation to time and place. NCI was defined if MoCA\u0026thinsp;\u0026le;\u0026thinsp;26 for with junior school education or above (\u0026ge;\u0026thinsp;7 years) and \u0026le;\u0026thinsp;25 for the others(Pinto et al.2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAnalysis were performed using SAS software (version 9.11). Group differences were compared using Chi-square, Fisher\u0026rsquo;s exact, Student\u0026rsquo;s t-test, ANOVA, or Kruskal-Wallis tests. Generalized Linear Model (GLM) was utilized to examine the intertwined cognitive domains of HIV serostatus and sex. Pairwise comparisons were subsequently adjusted with Benjamini Hochberg. Multivariable logistic regressions were performed to identify the determinants of NCI.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 465 PLWH and 465 HIV-negative\u0026nbsp;individuals\u0026nbsp;were\u0026nbsp;included. As shown in Table 1, PLWH were more likely to be active smokers, had more depressive symptoms, and displayed greater physical activity. Alcohol use, hypertension, diabetes, and CVD events were comparable between both groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognitive impairment between PLWH and HIV-negative individuals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 258 (55.5%), 91 (19.6%), and 273 (58.7%) of PLWH were classified as NCI by IHDS, MMSE, and MoCA, compared to 90 (19.4%), 25 (5.4%), 135(29.0%) of HIV-negative individuals, respectively (all \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05) (Figure 1).\u0026nbsp;Nearly all of NCI detected by MMSE were detected by IHDS or MoCA among PLWH, but about half of NCI detected by MMSE were detected by IHDS or MoCA among HIV-negative individuals. In general, the overlap of NCI detected by IHDS, MMSE, and MoCA was greater in PLWH than in HIV-negative individuals (22.1%\u003cem\u003e\u0026nbsp;vs\u0026nbsp;\u003c/em\u003e7.4%) (Figure 2).\u0026nbsp;In multivariable analysis adjusting for potential confounders, HIV infection was independently associated with NCI using IHDS (\u0026le; 10) (OR 5.10, 95% CI 3.68‒7.07), IHDS (\u0026le; 9) (OR\u0026nbsp;7.20, 95% CI\u0026nbsp;4.97‒8.66),\u0026nbsp;MMSE (OR 3.55, 95% CI 2.14‒5.91), and MoCA (OR\u0026nbsp;3.70, 95%CI\u0026nbsp;2.69‒5.08)), respectively (Supplementary Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003e Characteristics of PLWH and HIV-negative individuals\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003e\u003cem\u003eCharacteristics\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003ePLWH\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 465)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003eHIV-negative individuals\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003en\u003c/em\u003e = 465)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eAge, yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e60 (55‒65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e60 (55‒65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e390 (83.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e390 (83.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003ePrimary or below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e54 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e54 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e188 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e188 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eHigh school or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e223 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e223 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e30 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e17 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e332 (71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e351 (75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eDivorced or widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e103 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e97 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eCurrent alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e78 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e91 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e156 (33.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e128 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eRegular daily activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e227 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e158 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eComorbid conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eHistory of hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e153 (32.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e127 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eHistory of diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e47 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e49 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eHistory of CVD events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e54 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e38 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eCES-D score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e9 (3-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e5 (0-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eDepression symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e154 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e92 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003ePSQI score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e5 (2‒7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e4 (2‒6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003ePoor sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e199 (42.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e159 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNeurocognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNCI using IHDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003e\u0026le; 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e258 (55.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e93 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003e\u0026le; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e227 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e62 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNCI using MMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e91 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e26 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNCI using MoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e273 (58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e135 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHIV-related characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eNadir CD4 count \u0026lt;200 cells/\u0026mu;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e298 (64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eCurrent CD4 count \u0026lt;350 cells/\u0026mu;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e148 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eTime since HIV diagnosis \u0026ge;3 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e368 (79.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.09803921568628%\"\u003e\n \u003cp\u003eEver 2NRTI + EFV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.71657754010695%\"\u003e\n \u003cp\u003e352 (75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.033868092691623%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.151515151515152%\"\u003e\n \u003cp\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as n (%) or median (IQR).\u003c/p\u003e\n\u003cp\u003eAbbreviations: CVD, cardiovascular disease; EFV, efavirenz; NRTI, nucleotide reverse transcriptase inhibitors.\u003c/p\u003e\n\u003cp\u003eAfter stratified by sex, using the IHDS (\u0026le; 10), no significant difference was observed between female and male HIV-negative individuals (65.3% \u003cem\u003evs\u0026nbsp;\u003c/em\u003e53.1%, \u003cem\u003ep\u003c/em\u003e=0.051), but significantly higher prevalence of NCI was observed among female than male HIV-negative individuals (29.3% \u003cem\u003evs\u003c/em\u003e 17.4%, \u003cem\u003ep\u003c/em\u003e=0.017). In contrast, using the MMSE, significantly higher prevalence of NCI was observed among female than male PLWH (30.7% \u003cem\u003evs\u0026nbsp;\u003c/em\u003e17.4%, \u003cem\u003ep\u003c/em\u003e=0.008), but no significant difference was observed \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eamong female and male HIV-negative individuals (8.0% \u003cem\u003evs\u003c/em\u003e 5.1%, \u003cem\u003ep\u003c/em\u003e=0.322). Using the MoCA, no significant sex difference was observed in the prevalence of NCI, irrespective of HIV serostatus. Further stratified by age groups, prevalence of NCI increased with age regardless of screening tools and sex except that similar prevalence of NCI using IHDS were observed among female PLWH aged 50‒59years and 60‒69 years. Furthermore, the differences in NCI prevalence between PLWH and HIV-negative individuals were most pronounced for the youngest age group (ie, 50‒59 years), regardless of screening tools (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeurocognitive profiles\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ebetween PLWH and HIV-negative individual\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we compared the mean IHDS, MMSE and MoCA composite scores and their domain subscores between PLWH and HIV-negative individuals and further stratified by sex (Table 2) and age groups (Figure 3). The composite scores and each domain subscore of IHDS, MMSE and MoCA were markedly lower in PLWH \u003cem\u003evs\u003c/em\u003e HIV-negative individuals except for the IHDS-memory registration and recall, MMSE-orientation, MoCA-orientation subscores (Table 2). The most notable differences between the two groups in the domain subscores were IHDS-motor and psychomotor speeds followed by MoCA-executive function (Table 2 and Figure 2).\u003c/p\u003e\n\u003cp\u003eAfter stratified by sex and across the four groups, subsequent pairwise comparisons indicated that sex differences were observed in IHDS-motor speed, MoCA-executive function, attention, concentration and working memory, and language as well as composite scores of IHDS, MoCA among both PLWH and HIV-negative individuals. Sex difference in the MMSE composite score and MMSE-language subscore were only observed among PLWH (Table 2).\u003c/p\u003e\n\u003cp\u003eAfter further stratified by age groups, female PLWH and HIV-negative individuals at the oldest age group tended to have notable lowest subscores in most of domains of IHDS, MMSE and MoCA except for memory registration, orientation,, suggesting a combined effects of HIV infection, aging and sex (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with NCI by HIV serostatus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariable logistic analysis of factors associated with NCI using IHDS, MMSE and MoCA stratified by HIV serostatus were shown in Figure 4, respectively. In multivariable analysis, only older age and more depressive symptoms were positively associated with NCI regardless of the screening tools or HIV serostatus. For the NCI using IHDS, higher education level and regular daily activities were negatively associated n with NCI regardless HIV serostatus. Active smokers was positively associated with NCI (OR 1.75; 95% CI 1.12‒2.73) among PLWH, whereas poor sleep quality was positively associated NCI among HIV-negative individuals (OR 1.79; 95% CI 1.06‒3.03) (Figure 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eNeurocognitive domains compared by HIV serostatus and sex\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1023\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.27956989247312%\" rowspan=\"2\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeurocognitive domains\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.881720430107528%\" colspan=\"4\" style=\"width: 24.2669%;\"\u003e\n \u003cp\u003eHIV serostatus*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.436950146627566%\" colspan=\"2\" style=\"width: 10.1803%;\"\u003e\n \u003cp\u003ePLWH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.730205278592376%\" colspan=\"2\" style=\"width: 15.6255%;\"\u003e\n \u003cp\u003eHIV-negative\u0026nbsp;individuals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.52003910068426%\" colspan=\"3\" style=\"width: 18.1114%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.459433040078201%\" rowspan=\"2\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003eGroup\u0026nbsp;contrasts\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.653846153846153%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003ePLWH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.873626373626374%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003eHIV-negative individuals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.142857142857143%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003eF value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.104395604395604%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.516483516483516%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.554945054945055%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.791208791208792%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.6923076923076925%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.967032967032967%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003eHIV\u003c/p\u003e\n \u003cp\u003estatus\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.829670329670329%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003eSex\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.28021978021978%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003eHIV\u0026nbsp;status\u003c/p\u003e\n \u003cp\u003e\u0026times;sex\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHDS\u003c/strong\u003e\u003cstrong\u003e/score\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eMemory registration and recall/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003eNo diff\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eMotor speed/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e570.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003ePsychomotor speed/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e308.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;3;2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eTotal/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e8.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e10.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e380.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e7.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e8.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e9.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e10.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMMSE\u003c/strong\u003e\u003cstrong\u003e/score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eOrientation/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e9.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e9.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e9.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e9.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e9.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e9.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003eNo diff\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eMemory registration/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003eNo diff\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eAttention and calculation/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e4.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eMemory recall/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e44.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;3;2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eLanguage/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e8.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e8.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e31.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e7.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e8.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eTotal/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e27.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e28.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e26.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e28.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e28.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMoCA\u003c/strong\u003e\u003cstrong\u003e/score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eVisuospatial abilities/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.040\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eExecutive functions/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e106.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eAttention, concentration, and working memory/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e5.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e46.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e5.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e5.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eLanguage/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e19.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eShort-term memory/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e69.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;3;2\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003eOrientation\u0026nbsp;to time and place/6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e5.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e5.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e5.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e5.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e5.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e5.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003eNo diff\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.297455968688844%\" style=\"width: 12.5478%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e/30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.164383561643835%\" style=\"width: 5.4453%;\"\u003e\n \u003cp\u003e23.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.882583170254403%\" style=\"width: 8.6414%;\"\u003e\n \u003cp\u003e26.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.088062622309198%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e116.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.772994129158513%\" style=\"width: 5.682%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.066536203522505%\" style=\"width: 5.8004%;\"\u003e\n \u003cp\u003e21.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.38160469667319%\" style=\"width: 4.3799%;\"\u003e\n \u003cp\u003e23.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.262230919765166%\" style=\"width: 8.8781%;\"\u003e\n \u003cp\u003e24.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.47945205479452%\" style=\"width: 6.7474%;\"\u003e\n \u003cp\u003e26.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.675146771037182%\" style=\"width: 5.2085%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.577299412915851%\" style=\"width: 4.6166%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.185909980430528%\" style=\"width: 8.4046%;\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.469667318982388%\" style=\"width: 13.1396%;\"\u003e\n \u003cp\u003e1\u0026lt;2,3;2,3\u0026lt;4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Multivariate analysis was performed on the scores by HIV serostatus, adjusting\u0026nbsp;by age, sex and education.\u0026nbsp;GLM\u0026nbsp;was\u0026nbsp;utilized to examine the intertwined cognitive domains of HIV serostatus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e GLM was utilized to examine the intertwined cognitive domains of HIV serostatus and sex.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Four pairwise comparisons (1\u003cem\u003e\u0026nbsp;vs\u003c/em\u003e 2, 1 \u003cem\u003evs\u003c/em\u003e 3, 2 \u003cem\u003evs\u003c/em\u003e 4 and 3 \u003cem\u003evs\u003c/em\u003e 4) were performed and subsequently adjusted using the Benjamini Hochberg procedure. No diff=no difference.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the NCI using MMSE, female (OR 2.27; 95% CI 1.12‒4.62), active alcohol users (OR 2.27; 95% CI 1.17‒4.43), diabetes (OR 2.84; 95% CI 1.29‒6.27) and undergoing efavirenz (EFV) treatment (OR 2.2; 95% CI 1.11‒4.69) were positively associated with NCI among PLWH, whereas, higher education level was negatively associated with NCI (OR 0.19; 95% CI 0.05‒0.69) and hypertension was positively associated with NCI (OR 3.52; 95% CI 1.25‒5.88) among HIV-negatively individuals (Figure 4).\u003c/p\u003e\n\u003cp\u003eFor the NCI using MoCA, higher education level (OR 0.26; 95% CI 0.15‒0.45) and regular daily activities (OR 0.26; 95% CI, 0.14‒0.47) were negatively associated with NCI, and poor sleep quality were positively associated with NCI (OR 3.08; 95% CI 1.79‒5.28) among HIV-negative individuals. In contrast, none of the aforementioned factors were significantly associated with NCI among PLWH (Figure 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of our study demonstrate a distinct prevalence of NCI as assessed by the IHDS, MMSE and MoCA. The IHDS and MoCA tools identified a greater prevalence of NCI in PLWH as compared to MMSE. This tendency can be attributed to the fact that these tools are specifically developed to identify various forms of cognitive impairment. The MMSE is primarily designed to assess cognitive impairment associated with dementia. On the other hand, the MoCA has been specifically designed to identify mild cognitive impairments(Pinto et al.2019;\u0026nbsp;Lopardo \u0026nbsp; et al.2009). Conversely, the IHDS is developed to identify minor cognitive deficits in sub-cortical areas among PLWH, comprising impairments that occur in the early stages as well as those of lesser severity(Montanuccet al.2021).\u0026nbsp;The prevalence of NCI among our PLWH, as assessed by IHDS and MMSE, were similar to previous reports from developing counties(Kellett-Wright et al.2021;Yingying et al.2017;\u0026nbsp; \u0026nbsp;Qiao et al.2019). However, MoCA detected a lower prevalence among PLWH in our study compared to early investigations(\u0026nbsp; \u0026nbsp;Milanini et al.2016;\u0026nbsp; \u0026nbsp; \u0026nbsp;Selvaraj et al.2023). Such discrepancy may be partly explained by the difference in timing of ART initiation.\u0026nbsp;It\u0026rsquo;s interesting to note that PLWH showed a larger overlap of NCI detected by IHDS, MMSE, and MoCA than HIV-negative people, indicating that aged PLWH are more likely to have deficits in multiple cognitive domains simultaneously(\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sacktor \u0026nbsp;et al.2014).\u003c/p\u003e\n\u003cp\u003eSubsequent comparisons of all cognitive domains covered the IHDS, MMSE, and MoCA tools revealed distinct neurocognitive profiles between PLWH and HIV-negative individuals. The most prominent disparities observed between the two identified groups were in terms of IHDS-motor speed and psychomotor speed, as well as MoCA-executive function. It has been demonstrated that during the pre-ART era, HIV infection could exert a detrimental impact on both motor and psychomotor speeds, primarily targeting the subcortical regions of the brain(Lam et al.2021). Our results suggest that treated PLWH continued to experience cognitive impairment in subcortical regions despite viral suppression. This highlights the importance of using the IHDS evaluate the cognitive dysfunction in the post-ART era.\u003c/p\u003e\n\u003cp\u003eOur finding also revealed sex difference in the prevalence of NCI. Specifically, it was seen that females had a higher prevalence of NCI than males; however, this disparity depends on the screening tools used and HIV serostatus. The MMSE was the only tool that revealed significant sex difference among PLWH, which is consistent with previous reports using MMSE(Qiao et al.2019;Sundermanet al.2018; Burlacu \u0026nbsp;et al.2018). In contrast, the MoCA was the only tool demonstrating sex difference among HIV-negative individuals, whereas IHDS did not detect any sex difference in the both groups. The lack of sex difference in NCI prevalence by MoCA among PLWH is likely attributable to the floor effect(\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pinto et al.2019;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Dang \u0026nbsp; et al.2015) as both groups had higher prevalence of NCI. As our data further indicated, sex differences were observed in the composite scores of IHDS and MoCA, as well as subscores of IHDS-motor speed, MoCA-executive function, attention, concentration and working memory, and language among both PLWH and HIV-negative individuals; however, sex difference in the MMSE composite score and MMSE-language subscore were only observed among PLWH. Collectively, these findings imply that HIV infection and sex may have distinct effects on cognitive domains, and thus there is a sex difference in NCI prevalence as assessed by various screening tools. Moreover, our data reinforce the evidence that the IHDS predominantly reflects the cognitive impairment associated with HIV, and additionally indicate that the MMSE reflects the cognitive impairment due to combined effects of HIV infection and sex. These emphasize the need to employ a combination of neurocognitive screening tools to provide a comprehensive assessment of cognitive impairment in PLWH, thereby facilitate early detection and intervention.\u003c/p\u003e\n\u003cp\u003eIn addition, consistent with previous studies(Saloner \u0026nbsp;et al.2019;Aung et al.2023), we found that older age and depressive symptoms were consistently associated with NCI, regardless of HIV serostatus and the screening tools, suggesting that aging and depression play an important role in various cognitive impairments. Given the high prevalence of depression in PLWH(\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Joska et al.2016) and their robust link to cognitive impairment, a deeper understanding of whether treating or alleviating depressive symptoms can improve cognitive health among PLWH and its underlying mechanism are warranted(Williams et al.2020;\u0026nbsp; \u0026nbsp;\u0026nbsp;Mudraet al.2022;Rubin et al.2019) . Consistent with previous findings(\u0026nbsp;Qiao et al.2019;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Burlacu \u0026nbsp;et al.2018), female PLWH were more likely to have NCI than male PLWH, as assessed by MMSE, indicating a synergistic effect of HIV infection and female on specific cognitive domains(Qiao et al.2019) such as language as our data indicated. Current alcohol use was also associated with NCI using MMSE. Long-term alcohol use may cause immunological damage, which may cause neuropsychological deficits that eventually lead to dementia(\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Rianawati et al.2021). Alcohol use has been found to interact with HIV infection to worsen cognitive impairment(Green et al.2004). Our investigation also revealed that EFV use was associated with NCI using MMSE. However, this association was not observed when NCI was evaluated using either IHDS or MoCA. Animal studies have revealed CNS toxicity related to EFV use(Borrajo \u0026nbsp;et al.2021). In conjunction with our findings, these data suggest that EFV could potentially add the risk of NCI. Our study additionally indicates that a greater level of education and regular daily activities, may exert a protective effect against NCI, as evaluated by the IHDS.\u003c/p\u003e\n\u003cp\u003eSeveral limitations should be noted. First, this was cross-sectional design, hence could not assess temporal or causal relationship between factors of interest and the development of NCI. Second, all subjects were only recruited from Shanghai, China, which may could potentially restrict the generalizability of our findings to other geographic areas. Third, the lack of neurocognitive testing battery limits hinders the ability to evaluate the accuracy of these screening tools in identifying NCI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, PLWH exhibit a higher prevalence of NCI and distinct neurocognitive profiles compared to comparable HIV-negative individuals, despite viral suppression. The cognitive screening tools show variations in the detection of NCI prevalence which is also depending on age, sex and HIV serostatus. Our data support the notion that older PLWH tend to have deficits in multiple cognitive domains simultaneously. Given that various diverse screening tools can identify distinct aspects of cognitive dysfunction, it is advisable to utilize these screening tools in conjunction to uncover complex patterns of cognitive impairment among PLWH, especially older PLWH, and thereby promote early detection and intervention.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving Human participants had been carried out in accordance with the Declaration Helsinki. The studies were reviewed and approved by the Ethics Committee of Pudong New Area Center for Disease Control and Prevention. Written informed consent was obtained from the individual(s).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePanpan Chen, Yingying Ding and Na He contributed to the conception or design of the work. Panpan Chen, Xin Xin, Shaotan Xiao contributed to supervising subject enrollment and data collection. Panpan Chen and Xin Xin contributed to data analysis and manuscript draft. Hantao Liu, Xin Liu contributed to the data collection. Yingying Ding critically revised the manuscript. All authors critically reviewed and edited the manuscript and consented to final publication. Panpan Chen and Xin Xin conceived the study and contributed\u0026ensp;equally\u0026ensp;to\u0026ensp;this study\u0026ensp;and\u0026ensp;should\u0026ensp;be\u0026ensp;considered\u0026ensp;co-first\u0026ensp;authors. Yingying Ding and Na He should be considered co-corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data which support the conclusions of our study is included within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank all study participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Research Grant for Health Science and Technology of Pudong New Area Health Commission of Shanghai (No. PW2020A-10), Pudong New Area Science and Technology Development Innovation fund (No. PKJ2023-Y71), Academic Leaders Training Program of Pudong Health Commission of Shanghai (No. PWRd2022-01), Medical discipline Construction Project of Pudong Health Committee of Shanghai(No. PWYgts2021-04), National Natural Science Foundation of China (No. 82173579), and Shanghai three-year (No. 2023-2025) action plan to strengthen the public health system (No. GWVI-11.1-05).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAntinori A, Arendt G, Becker JT, Brew BJ, Byrd DA, Cherner M, Clifford DB, Cinque P, Epstein LG, Goodkin K, Gisslen M, Grant I, Heaton RK, Joseph J, Marder K, Marra CM, McArthur JC, Nunn M, Price RW, Pulliam L, Robertson KR, Sacktor N, Valcour V, Wojna VE. 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Is the Montreal Cognitive Assessment (MoCA) screening superior to the Mini-Mental State Examination (MMSE) in the detection of mild cognitive impairment (MCI) and Alzheimer\u0026apos;s Disease (AD) in the elderly? International Psychogeriatrics, 2019. 31(04): p. 491-504.\u003c/li\u003e\n\u003cli\u003eSelvaraj N, Chidambaram Y, Dhas CPCJ, Nekkanti A, Velammal P, Kumar B, Alagesan M. Prevalence of Asymptomatic HIV Associated Neurocognitive Disorder in a Tertiary Care Hospital in South India: A Single Centre Observational Study. Mediterranean Journal of Infection Microbes and Antimicrobials, 2023.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neurovirology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"njiv","sideBox":"Learn more about [Journal of NeuroVirology](http://link.springer.com/journal/13365)","snPcode":"13365","submissionUrl":"https://submission.nature.com/new-submission/13365/3","title":"Journal of NeuroVirology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HIV, cognitive impairment, neurocognitive profile, cognitive screening tools","lastPublishedDoi":"10.21203/rs.3.rs-3932903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3932903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe aim of our study was to examine potential differences in the assessment of neurocognitive impairment (NCI) using cognitive screening tools between PLWH and HIV-negative individuals, as well as to compare the neurocognitive profiles.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was baseline evaluation of Pudong HIV Aging Cohort, including 465 people living with HIV (PLWH) and 465 HIV-negative individuals aged over 50 years matched by age (\u0026plusmn;\u0026thinsp;3 years), sex and education. NCI was assessed using the Chinese version of Mini-mental State Examination (MMSE), the International HIV Dementia Scale (IHDS) and Beijing version of Montreal Cognitive Assessment (MoCA).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn total, 258 (55.5%), 91 (19.6%), and 273 (58.7%) of PLWH were classified as having NCI by the IHDS, MMSE, and MoCA, compared to 90 (19.4%), 25 (5.4%), 135 (29.0%) of HIV-negative individuals, respectively (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05); such associations Only MMSE revealed sex difference in NCI prevalence among PLWH. PLWH showed a larger overlap of NCI detected by IHDS, MMSE, and MoCA than HIV-negative people. Regarding cognitive domains, IHDS-motor and psychomotor speeds and MoCA-executive function showed the greatest disparities between two groups. In multivariable analysis, older age and more depressive symptoms were positively associated with NCI regardless of the screening tools or HIV serostatus.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePLWH display a higher prevalence of NCI and distinct neurocognitive profiles compared to HIV-negative individuals, despite viral suppression. Our data support that older PLWH tend to have deficits in multiple cognitive domains simultaneously. It is advisable to utilize the cognitive screening tools in conjunction to reveal complex patterns of cognitive deficits among PLWH, especially older PLWH.\u003c/p\u003e","manuscriptTitle":"Cognitive impairment and neurocognitive profiles among people living with HIV and HIV- negative individuals older over 50 years: a comparison of IHDS, MMSE and MoCA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-08 19:18:17","doi":"10.21203/rs.3.rs-3932903/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-13T17:13:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-10T22:05:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3e99404a-4f1a-450f-b240-fd2cdf214a1e","date":"2024-02-07T21:58:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-07T19:47:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-06T14:53:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-06T14:53:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroVirology","date":"2024-02-06T05:33:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neurovirology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"njiv","sideBox":"Learn more about [Journal of NeuroVirology](http://link.springer.com/journal/13365)","snPcode":"13365","submissionUrl":"https://submission.nature.com/new-submission/13365/3","title":"Journal of NeuroVirology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a598f5c0-8703-43f9-9070-ff9ed2baaa3f","owner":[],"postedDate":"February 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-09T16:52:03+00:00","versionOfRecord":{"articleIdentity":"rs-3932903","link":"https://doi.org/10.1007/s13365-024-01205-y","journal":{"identity":"journal-of-neurovirology","isVorOnly":false,"title":"Journal of NeuroVirology"},"publishedOn":"2024-05-06 16:52:03","publishedOnDateReadable":"May 6th, 2024"},"versionCreatedAt":"2024-02-08 19:18:17","video":"","vorDoi":"10.1007/s13365-024-01205-y","vorDoiUrl":"https://doi.org/10.1007/s13365-024-01205-y","workflowStages":[]},"version":"v1","identity":"rs-3932903","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3932903","identity":"rs-3932903","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}