Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 European Journal https://doi.org/10.1186/s40001-022-00639-6 of Medical Research RESEARCH Open Access Factors associated to neurocognitive impairment in older adults living with HIV Júlia Gutierrez‑San‑Juan1,5, Itziar Arrieta‑Aldea3, Isabel Arnau‑Barrés2, Greta García‑Escobar4, Elisabet Lerma‑Chipirraz3, Paula Pérez‑García2, Agustin Marcos3, Fabiola Blasco‑Hernando3, Alicia Gonzalez‑Mena3, Esperanza Cañas3, Hernando Knobel3 and Robert Güerri‑Fernández1,3,5,6* Abstract Objective: The HIV infection is a chronic disease that causes neurocognitive impairment (NI) and has been related with early development of frailty. We aimed to study the main risk factors for neurocognitive disorders and frailty in HIV older adults. Materials and methods: Cross-sectional study with 40 HIV individuals older than 65 years under antiretroviral ther‑ apy in Hospital del Mar (Barcelona) recruited between November 2019 and October 2020. Data has been obtained through clinical scores and a blood sample to evaluate NI and frailty and has been analyzed with non-parametric tests and a multivariate logistic regression model. Results: Among the 40 patients admitted for the study, 14 (35%) had positive screening for NI. We found that HIV individuals with nadir CD4+ T-cell count lower than 350 cells/mm3 had 39.7 more risk for NI (95% CI 2.49–632.10; p = 0.009). Those with a lower education level had 22.78 more risk for neurocognitive disorders (95% CI 2.13–242.71; p = 0.01) and suffering any comorbidity with a punctuation ≥ 1 in the Charlson Comorbidity index had an increased risk of 18.26 of developing NI and frailty (95% CI 1.30–256.33; p = 0.031), among them diabetes was significantly more frequent in NI. Conclusion: We observed that the main risk factors for a positive NI screening in HIV older adults were low education level, a nadir CD4+ T-cell count < 350 cells/mm3 and the presence of any comorbidity, highlighting diabetes among them. Keywords: HIV, Aging, Neurocognitive disorder, Frailty, Antiretroviral therapy Keypoints Message:Low nadir CD4+ T-cell count and low school- Aim: Which HIV older adults should be mandatory ing are associated with higher risk of positive screening screened for neurocognitive impairment for neurocognitive disorder in HIV older adults Findings:We found in a small very well characterized Introduction cohort that individuals with lower nadir CD4+ T-cell The human immunodeficiency virus (HIV) infection is a count, meaning advanced HIV infection at any time and chronic disease suffered by 38 million people in the world lower schooling are associated with higher probability of in 2019 [1]. HIV is a neurotropic virus which causes positive neurocognitive impairment test. central nervous system (CNS) damage and neurocogni- *Correspondence: rguerri@psmar.cat tive impairment (NI). This is found in 10–20% in early 6 Hospital del Mar Institute of Medical Research, Passeig Doctor Aiguader HIV stages and in 30–40% in advanced disease [2, 3]. 88, 08003 Barcelona, Spain Although the clinical range of NI associated with HIV is Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 2 of 7 wide, the more severe forms have dramatically decreased these conditions, 40 participants were randomly selected due to the use of antiretroviral treatment (ART) [4, 5]. for the study and were visited at the same day by different However, the milder forms continue to concern in people specialists (infectious diseases, geriatrics and neuropsy- living with HIV (PLWH) [5–7], especially now that life chology). We excluded any patients who had a severe expectancy is significantly longer [8, 9]. NI plays a pre- intellectual disability from other causes than HIV. ponderant role in the deterioration of the quality of life Demographic and clinical data were extracted from and functionality, carrying an accelerated appearance of electronic medical records and clinical scores. Laboratory frailty [10–12]. Many mechanisms for NI such as CNS workups included a fasting blood draw with metabolic virus persistence despite suppressed peripheral viral load, markers such as total cholesterol, LDL–HDL cholesterol, continuous activation of monocytes in the CNS [13–15], triglycerides, and HIV markers including CD4+ , CD8+ HIV-specific persistent inflammatory response or poten- T-cell count and viral load. tial ART CNS toxicities [5, 16] have been proposed. All MOCA score lower than 25/30 was considered a posi- of these seem to be keystone in the pathophysiology of tive screening for NI as analysis consideration. neurocognitive deterioration. Schooling was categorized into three groups, lower HIV-associated dementia (HAD) and HIV-associated education level including elementary school and illiterate neurocognitive disorders (HAND) have declined in the individuals, and high school education and professional era of ART. However, the ageing of the HIV population degree and university. is impacting significantly in the neurocognitive status of An integral geriatric evaluation was performed to ana- PLWH overlapping both conditions and posing a poten- lyze sensory impairment, sleep disorders, polypharmacy tial risk for frailty [10, 17, 18]. It is believed that nowa- (considered as taking ≥ 5 drugs), urine and fecal inconti- days, the NI found in HIV is linked to HIV itself but also nence, constipation, falls (≥ 2 in the last year), depressive aging-associated comorbidities such as cardiovascular syndrome, dementia, delirium, malnutrition and pres- disease, metabolic disorders, osteoporosis, obesity, can- sure ulcers. Daily life activities were assessed using Bar- cer, Alzheimer disease or other types of dementias [5, 14, thel and Lawton–Brody index, and nutritional status was 19]. analyzed by Mini Nutritional Assessment (MNA) screen- Neurocognitive disorders are screened using scores as ing test. Frailty was valuated with the Clinical Frailty the Brief Neurocognitive (BNC) or the HIV Neurobe- scale and comorbidity was assessed using the Charlson havioral Research Center (HNRC) [20]. Among them, Comorbidity index, which was also categorized in no MOCA score has traditionally been used to the screening comorbidities, medium–low (1–2 comorbidities) or high of NI, showing a high sensitivity (90%) but low specificity (≥ 3 comorbidities). All included individuals had a VACS (45%). At the same time extensive tests are used to con- index at baseline [15]. firm those positive cases evaluating different capacities such as motor skills with Dominant hand time (GPT) or Statistics Non-dominant hand time (GPT), executive functioning Continuous variables were expressed as medians and with Total time (TMT-B) or verbal fluency with Phone- interquartile range (IQRs) and were compared using mic (COWAT) [21]. The importance of an early diagnosis Mann–Whitney U test. Categorical variables were and a multidisciplinary care has been previously demon- expressed as frequencies (percentages) and were com- strated [10]. However, the factors associated with NI and pared with the χ2 test. A multivariable logistic regression ageing nowadays in the HIV pandemic remain unveiled. model was fitted to analyze the positive screening for NI The aim of our study was to describe a cohort of PLWH adjusting by age, nadir CD4+ T-cell count, educational older than 65 years under ART to determine the preva- level and comorbidity, to determine odds ratios (ORs) lence of a positive screening for NI associated with HIV and 95% confidence intervals (CI) for covariates. Those and to analyze the risk factors for a positive result. As variables with p value < 0.05 in univariate analysis were secondary objectives to study other components of cog- included into the multivariate logistic regression model. nition and functionality. STATA/MP V.14.2 software. Materials and methods Results Cross-sectional study conducted in Hospital del Mar Among 40 patients recruited for the study, 14 (35%) had in Barcelona, Spain. From November 2019 to October positive screening for NI. Table 1 shows the cohort’s 2020 HIV participants were selected from a clinical HIV baseline characteristics (overall), and the comparison cohort with 2094 patients followed-up by the Infectious between positive and negative screening in the MOCA Disease Department. Eligible participants included peo- test. Individuals testing positive in the NI screening had ple over 65 years under ART. Of the 147 who reached lower educational level (21.43% vs 73.08%; p = 0.002), Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 3 of 7 Table 1 Baseline characteristics of the cohort Overall Negative screening Positive screening P value n (%) 40 26 (65) 14 (35) – Age 0.472 Median age (IQR) 70 (68–75) 71 [67.5–77.3] 70 [68.5–75]   < 70 years (n, %) 17 (42.5) 6 (42.86) 11 (42.31) 70–80 years (n, %) 19 (47.5) 6 (42.86) 13 (50)   > 80 years (n, %) 4 (10) 2 (14.29) 2 (7.69) Gender 0.178 Men (n, %) 34 (85) 14 (100) 20 (76.92) Women (n, %) 4 (10) 0 4 (15.38) Transsexual (n, %) 2 (5) 0 2 (7.68) Schooling 0.002 Elementary school (n, %) 24 (60) 3 (21.43) 21 (80) High school/professional (n, %) 8 (20) 5 (35.72) 3 (12) University (n, %) 8 (20) 6 (42.86) 2 (8) Home 0.471 Alone (n, %) 16 (40) 6 (42.86) 10 (38.46) Partnered (n, %) 17 (42.5) 7 (50) 10 (38.46) Sharing room (n, %) 7 (17.5) 1 (7.14) 6 (23.08) Toxic habits 0.534 Smoking (n, %) 9 (22.5) 3 (21.43) 6 (23.08) Ex-smoking (n, %) 16 (40) 6 (42.86) 10 (34.46) Alcohol (n, %) 18 (45) 6 (42.86) 12 (46.15) Recreation drugs (n, %) 6 (15) 3 (21.43) 3 (11.54) Comorbidities Hyper blood pressure (n, %) 20 (50) 8 (40) 12 (60) 0.507 Dyslipidemia (n, %) 24 (60) 10 (41.67) 14 (15.6) 0.279 Diabetes mellitus (n, %) 7 (17.5) 0 7 (26.92) 0.033 Chronic kidney disease (n, %) 3 (7.5) 2 (66.67) 1 (33.33) 0.232 Stroke (n, %) 3 (7.5) 2 (14.29) 1 (3.85) 0.232 Overweight (BMI 25–30) (n, %) 19 (47.5) 7/50) 12 (46.15) 0.816 Obesity (BMI ≥ 30) (n, %) 10 (25) 3 (27.27) 8 (72.73) 0.528 Liver cirrhosis (n, %) 1 (2.5) 1 (7.14) 0 0.168 Vitamin D deficiency (n, %) 15 (37.5) 5 (35.71) 10 (38.46) 0.864 Osteoporosis (n, %) 2 (5) 0 2 (7.69) 0.287 Pulmonary disease (n, %) 5 (12.5) 0 5 (19.23) 0.079 Cancer active (n, %) 2 (22.22) 1 (25) 1 (20) 0.858 Cancer cured (n, %) 7 (77.78) 3 (75) 4 (80) 0.858 Neurocognitive impairment (n, %) 1 (2.70) 0 1 (4.17) 0.456 Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 4 of 7 Table 1 (continued) Overall Negative screening Positive screening P value Co-infections 0.634 Toxoplasma (n, %) 1 (2.5) 0 1 (3.85) Atypical mycobacteria (n, %) 1 (2.5) 0 1 (3.85) Varicella-zoster virus (n, %) 2 (5) 2 (14.29) 0 Herpesvirus (n, %) 2 (5) 1 (7.14) 1 (3.85) Hepatitis C virus (SVR) (n, %) 4 (100) 1 (100) 3 (100) Hepatitis B virus (n, %)   Active 1 (12.5) 0 1 (14.29)   Controlled 4 (50) 1 (100) 3 (42.86)   Past 3 (37.5) 0 3 (42.86) Invasive CMV (n, %) 1 (2.5) 0 1 (3.85) Kaposi’s sarcoma (n, %) 2 (5) 1 1 Tuberculosis (n, %) 5 (12.5) 1 (7.14) 4 (15.38) HIV data CD4+ T-cell count nadir (IQR) 352 [163–520] 526.5 [352–603] 334 [150–400] 0.01 CD4/CD8 at diagnosis (IQR) 0.34 [0.27–0.59] 0.5 [0.29–0.65] 0.32 [0.19–0.48] 0.18 CD8+ count at diagnosis (IQR) 770 [661–1197.5] 1027.5 [800–1198] 731 [526–1197] 0.160 Zenit viral load (IQR) 33,765 [8900–90434] 55,048.5 [6050–174354] 33,000 [11000–84248] 0.632 Time since diagnosis (years) (IQR) 22 [14–27.5] 23.5 [15–29] 21.5 [13–27] 0.560 Time under ART (years) (IQR) 19 [9–22.5] 19.5 [8–24] 19 [10–22] 0.638 Time undetectable (months) (IQR) 163 [60–228] 79 [71–207] 171.5 [60–228] 0.601 Geriatric evaluation Barthel index (IQR) 100 [100–100] 100 [100–100] 100 [100–100] 0.768 Lawton and Brody index (IQR) 8 [8–8] 8 [7, 8] 8 [8–8] 0.479 Charlson comorbidity index (n, %) 0.031   No comorbidity (0) 25 (62.5) 12 (85.71) 13 (50)   Medium–low (1–2) 10 (25) 1 (7.14) 9 (34.62)   High (> 3) 5 (12.5) 1 (7.14) 4 (15.38) MNA screening (IQR) 14 [12–14] 14 [12.5–14] 13 [12–14] 0.188 Sensory impairment (n, %) 17 (45.95) 6 (46.15) 11 (45.83] 0.985 Sleep disorder (n, %) 4 (10.81) 2 (15.38) 2 (8.33) 0.510 Polypharmacy (n, %) 24 (64.86) 10 (76.92) 14 (58.33) 0.258 Urine incontinence (n, %) 4 (10.81) 1 (7.69) 3 (12.5) 0.653 Fecal incontinence (n, %) 2 (5.41) 0 2 (8.33) 0.285 Constipation (n, %) 3 (8.11) 1 (7.69) 2 (8.33) 0.946 Falls (n, %) 5 (13.51) 4 (30.77) 1 (4.17) 0.024 Depressive syndrome (n, %) 4 (10.81) 2 (15.38) 2 (8.33) 0.510 Clinical frailty scale (IQR) 2 [2–2] 2 [1, 2] 2 [2–2.5] 0.241 SPPB total (IQR) 10 [9–11] 9 [8–10] 11 [9–11] 0.400 VACS index points (IQR) 35 [33–43] 33 [33–37] 43 [33–49] 0.029 Neurological evaluation MOCA test (IQR) 22.37 [20–26.5] 27 [26–28] 20 [18–22] 0.000 Blood test Total cholesterol (IQR) 165.5 [144–188.5] 177 [150–189] 164.5 [142–186] 0.954 LDL cholesterol (IQR) 105.5 [90.5–117] 100 [78–110] 106 [95–118] 0.410 HDL cholesterol (IQR) 44.2 [34.55–55.2] 45.7 [37.7–55] 43.4 [32.8–55.4] 0.798 Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 5 of 7 Table 1 (continued) Overall Negative screening Positive screening P value Triglycerides (IQR) 133.5 [96.5–183] 128 [82–188] 138 [98–169] 0.887 CD4+ T-cell count (IQR) 636.5 [477–783.5] 758 [547–958] 584.5 [459–721] 0.088 CD8+ T-cell count (IQR) 798 [579–1058.5] 968 [795–1128] 721 [561–999] 0.083 CD4/CD8 (IQR) 0.76 [0.59–1.05] 0.76 [0.58–1.03] 0.77 [0.6–1.09] 0.186 Undetectable (%) 100 100 100 – Differences between older adults with positive and negative screening for neurocognitive impairment BMI body mass index; SVR sustained viral response Table 2 Logistic multivariable regression (95% CI 2.49–632.10; p = 0.009), the OR for lower educa- Odds-ratio 95% CI tion level was 22.78 (95% CI 2.13–242.71; p = 0.01) and the OR for any comorbidity (≥ 1 in Charlson Comorbid- Age 0.91 0.75–1.11 ity index) was 18.26 (95% CI 1.30–256.33; p = 0.031). Nadir CD4+ T-cell count (< 350 cells/mm3) 39.70 2.49–632.10 Education level (lowest level) 55.28 1.34–452.71 Charlson index (≥ 1 comorbidity) 18.26 1.30–256.33 Discussion Predictors of neurocognitive disorders We report a significant association between having a positive screening for NI and nadir CD4+ T-cell count, lower education level and having any comorbidity among HIV+ older adults. These results, although expected, while individuals with university studies or a profes- help to understand the potential underlying causes of sional degree were less likely to test positive in the NI NI among HIV individuals. Moreover, we found that the screening (42.86% vs 7.69%; p = 0.008) and (14.29% vs 0%; frailty phenotype was not directly associated with NI. p = 0.048), respectively. Likewise, individuals with diabe- In our series, a third of the individuals had a posi- tes mellitus tested positive to NI screening (26.92% vs 0%; tive screening for NI. This proportion is similar to prior p = 0.033). Interestingly, we found no differences between reported studies, where 30–50% of older adults living groups with respect to age, gender, toxic habits or hous- with HIV had HAND [21]. Usually, the onset of this con- ing status (Table 1). dition consists on subacute neurological symptoms such When focusing on HIV characteristics there were no as lack of focus or impaired motor fine skills [6, 22]. This differences in time to exposure to HIV, nor in time unde- NI might be associated with poorer quality of life and tectable (with no viral load detectable in blood) (Table 1). shorter life expectancy [5, 9, 23, 24]. An early diagnosis Those individuals testing positive for NI had significantly is keystone to identify subjects at risk and to plan appro- lower nadir CD4+ T-cell count [(526.5 cells/mm3 (352– priate management strategies. In this scenario screening 603) vs 334 (150–400); p = 0.001)] and a trend to lower tests such as MOCA might help to identify individuals actual CD4+ T-cell count [(758 cells/mm3 (547–958) that could need further studies [25, 26]. vs 584.5 (459–721); p = 0.088)]. Moreover, VACS index We found that HIV status at diagnosis, schooling revealed statistically significant results according to NI, degree and comorbidities are determinants in the odds detecting higher scores in those patients with positive of testing positive in the NI screening. However, we also screening (33 vs 43; p = 0.029). expected to report an association between aging and NI, One patient was detected with neurocognitive impair- but we did not find it. One potential explanation might ment prior to the start of the study. Regarding to geriat- be the small sample size of this cohort. But also that there ric syndrome results are shown in Table 1. Twenty-five might be a selection bias. Individuals who were able to individuals (62.5%) had no comorbidity according to participate into the study were in a good health condi- the Charlson Comorbidity index and the median punc- tion, at least enough to come to the clinic and participate tuation in the Clinical Frailty scale was 2 (2–2). Only five in the study. However, prior studies have widely demon- patients referred having suffered ≥ 2 falls in the last year. strated the association between age and NI [9, 11, 12, 16, Those who tested positive for NI were more likely to have 24, 27]. any comorbidity (12 (85.71%) vs 13 (50%); p = 0.026). The association found between NI and low CD4+ In a multivariate logistic regression model to predict T-cell nadir seems to be associated with some character- a positive screening for NI (Table 2), the OR for nadir istics of the HIV infection and how it affects the immune CD4+ T-cell count less than 350 cells/mm3 was 39.7 system. Chronic HIV infection and aging are related in a Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 6 of 7 state of immunosenescence which contributes to earlier with medium–low comorbidity levels in the Charlson appearance of comorbidities among HIV individuals [2, Comorbidity index, where higher scores were related to 3, 9, 11, 12, 17]. However, there is a subpopulation of indi- positive screening in the MOCA test. Among comorbidi- viduals among people living with HIV known as late pre- ties, diabetes was found to be more represented in the senters with particularly low nadir CD4+ T-cell count. positive NI screening group [19]. As previously reported, We found that individuals with a CD4+ T-cell nadir several studies revealed that sustained levels of hyper- lower than 350 cells/mm3 had 39.7 more risk for NI. Low glycemia, poor glycemia controls and insulin resistance CD4+ T-cell nadir has been shown to be a relevant to a could influence the development of neurocognitive disor- worse prognostic for other HIV but also for other non- ders [19, 32, 33]. AIDS comorbidities [2, 7, 9]. Nadir CD4+ T-cell count Our study has some limitations, since this is a reduced is associated with a greater destruction of the immune sample size single center study. Moreover, the COVID-19 system by the HIV itself. Therefore, a low CD4+ T-cell pandemic made us cancel the activity of the HIV-frailty count may lead to a higher viral replication, and subse- clinic. However, this study has also some strengths, quently to an increased inflammatory response, who has because all individuals included are well characterized been claimed as responsible for many comorbidities asso- with a multidisciplinary approach, where different spe- ciated to HIV. The HIV infection impairs the homeostasis cialists assessed all the included individuals. of CD4 lymphocytes leading to a CD4+ destruction by direct cytopathic effect, and hyperactivation and deple- Conclusions tion of the immune system that has been associated with One third of individuals tested positive for the NI screen- multiple effects such as NI [2, 6, 9, 14]. However, likely ing in our cohort. According to our results, those indi- the viral replication in reservoirs, as the brain, might viduals with a nadir CD4+ T-cell count < 350 cells/mm3, have a role in the progressive deterioration observed in lower education level and the presence of comorbidities individuals prior to the appearance of the highly effective such as diabetes mellitus had an increased risk of devel- antiretroviral therapy [2]. The late diagnosis of the HIV oping NI and should be prioritized in neurocognitive infection implies low CD4+ T-cell count and, at the same assessment among HIV older adults. time, more time of exposure to a highly replicant virus. Acknowledgements The long term impact of this period regardless of the later We want to thank to our patients time undetectable might be a potential explanation to the association observed between nadir CD4+ and neuro- Authors’ contributions Concept and design: RGF, IAB, IAA. Data collection or processing: IAA, IAB, JGS, cognitive impairment. GGE, PPG, RGF. Analysis or interpretation: RGF, IAA, JGS. Literature search: RGF, In the same line, schooling has also an impact in NI. IAB, IAA, JGS, GGE, PPG, ELC, DCL. Writing: RGF, JGS, IAA, IAB. All authors read Moreover, HIV patients who have low education attain- and approved the final manuscript. ment carry higher risk of developing HAND compared Funding with HIV patients with university studies or profes- The authors declared that this study received no financial support. sional degrees [28–30]. This could be related to a greater Availability of data and materials development of neuronal capacity during childhood and Data of this study are not public, but are available under reasonable request to greater neurological training throughout life, which could the corresponding author. act as a protective factor against the development of neu- rocognitive disorders [13, 28, 31]. Besides, the exposure Declarations to HIV might have impaired the normal development Ethics approval and consent to participate of the neuronal capacity. These individuals have been The Institutional Ethics Committee of Parc de Salut Mar of Barcelona approved exposed to HIV for a long time, and most of them have the study (CEIm 2018/8186/I) and all participants have signed the informed also been exposed to no therapy or to more toxic therapy consent. The study was carried out in accordance with the Declaration of Helsinki of 2013 and the data was analyzed maintaining the privacy rights and than the used nowadays. anonymity of the participants according to the Organic Law on Data Protec‑ Likely the cause of the NI in HIV individuals is not tion of 2018. monocausal and the accumulation of several facts Consent for publication occurred during the lifetime might be impacting in the All authors have reviewed the manuscript and share consent for publication. neurocognitive function. However, the immune damage induced by HIV and its consequences seems to be rele- Competing interests The authors have declared that no competing interest exists. vant among these potential causes. We also performed a geriatric assessment and we Author details observed how comorbidity is associated with positive 1 Department de Medicina, Universitat Autònoma de Barcelona and Univer‑ sitat, Barcelona, Spain. 2 Department of Geriatrics, Hospital del Mar, Barce‑ screening for NI. A trend was observed in those patients lona, Spain. 3 Department of Infectious Diseases, Hospital del Mar Institute Gutierrez‑San‑Juan et al. European Journal of Medical Research (2022) 27:15 Page 7 of 7 of Medical Research, Barcelona, Spain. 4 Department of Neurology, Hospital del 20. Fazeli PL, Casaletto KB, Paolillo E, Moore RC, Moore DJ. 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