Although the prevalence of a current or lifetime diagnosis of MDD did not differ between WWH and MWH, MDD was an important risk factor of demonstrating Global weaknesses with spared verbal recognition compared to the profile demonstrating only Weakness in motor function. This finding aligns with our work demonstrating that MDD may have a greater impact in women compared to men. Our work indicates that HIV comorbid with depression affects certain cognitive domains including cognitive control, and that these effects are largest in women. specifically, WWH with elevated depressive symptoms had 5 times the odds of impairment on Stroop Trial 3, a measure of behavioral inhibition, compared to HIV-uninfected depressed women, and 3 times the odds of impairment on that test compared to depressed MWH. In a recent meta-analysis, small to moderate deficits in declarative memory and cognitive control were documented not only in individuals with current MDD but also in individuals with remitted MDD, leading to the conclusion that these deficits occur independently of episodes of low mood in individuals with “active” MDD. Together these lines of work suggest that MDD would exacerbate cognitive difficulties in PWH, particularly in the cognitive domains of declarative memory and cognitive control in WWH. Our study has limitations. Although we were adequately powered within both WWH and MWH , the magnitude of power was discrepant by sex considering that women represented 20% of our sample. Larger-scale studies in WWH only are currently underway. The generalizability of our findings also warrant additional study as the profiles identified here may not represent the profiles among all PWH. Due to the unavailability of data, we were unable to explore certain psychosocial factors as potential determinants of cognitive profiles. Our analyses were cross-sectional which allows us to identify determinants associated with cognitive profiles but precludes us from determining the temporal relationships between these factors and cognitive function. Although many of the related factors may be risk factors for cognitive impairment, reverse causality is possible with some of the factors resulting from cognitive impairment. Additionally,cannabis grow system interpretation of the machine learning results should be done with care as RF is an ensemble model that is inherently non-linear in nature.
This means that the importance and predictive power of every variable is specified in the context of other variables. This can lead to situations where an important predictive variable in the RF model has no significant difference in the overall comparison but has dramatic differences when included with other variables in the model. As such, this model should be interpreted as hypothesis-generating and identifies variables in need of further investigation. Lastly, because our study was focused on sex differences in cognitive profiles within PWH, we did not include a HIV-seronegative comparison group. Thus, we cannot determine the degree to which HIV contributes to sex differences in cognitive profiles. However, the independent HIV-related predictors does suggest that HIV has a role. Despite these limitations, we selected RF over linear models such as lasso and ridge regression because RF models had more predictive power and higher accuracy in this data compared to the linear models, even linear models with tuning parameters such as ridge and lasso that can used for feature selection. The results from these models mirror the P-values for the univariate comparisons , which is expected since analysis of variance and t-tests are also linear models. Moreover, RF models are more optimal for handling missing data, the inclusion of categorical predictor variables, and the use of categorical outcome measures which was the case in the present study. RF models also account for the complexity in the data that can arise from multicollinearity often seen in large feature sets. In conclusion, our results also suggest that sex is a contributor to the heterogeneity in cognitive profiles among PWH and that cognitive findings from MWH or male-dominant samples cannot be wholly generalized to WWH. Whereas, MWH showed an unimpaired profile and even a cognitively advantageous profile, WWH only showed impairment profiles that included global and more domain-specific impairment, which supports previous findings of greater cognitive impairment in WWH than in MWH. Although the strongest determinants of cognitive profiles were similar in MWH and WWH including WRAT- 4, HIV disease characteristics, age and depressive symptoms, the direction of these associations sometimes differed.
This suggests that the effects of certain biological, clinical, or demographic factors on the brain and cognition may manifest differently in MWH and WWH and that sex may contribute to heterogeneity not only in cognitive profiles but in their determinants although studies with larger numbers of WWH are needed to more definitively test these hypotheses. It is important to detect these differing cognitive profiles and their associated risk/protective factors as this information can help to identify differing mechanisms contributing to cognitive impairment and whether these mechanisms are related to HIV disease, neurotoxic effects of ART medications, and/or comorbidities that are highly prevalent among PWH. Given the longer lifespan of PWH in the era of effective antiretroviral therapy, cognitive profiling will also inform aging-related effects on cognition in the context of HIV and perhaps early clinical indicators of age-related neurodegenerative disease. By identifying cognitive profiles and their underlying mechanisms, we can ultimately improve our ability to treat by tailoring and directing intervention strategies to those most likely to benefit. Overall, our results stress the importance of considering sex differences in studies of the pathogenesis, clinical presentation, and treatment of cognitive dysfunction in HIV.Older persons living with HIV , often defined as age 50 years, represent a rapidly growing population. More than 50% of PLWH in the U.S. are 50 years,. Furthermore, older PWLH have high rates of multi-morbidity. Chronic pain and substance use occur commonly in this population and are associated with poor health outcomes and increased use of healthcare services. PLWH are also at risk for declining physical functioning and reduced physical performance. Given the high prevalence of co-morbid pain, substance use, and reduced physical functioning in older PLWH, multi-component interventions targeting all three are needed. Cognitive behavioral therapy is an evidence-based approach for managing both pain and substance use. According to the Infectious Diseases Society of America guidelines, CBT is a recommended first line non-pharmacologic treatment for chronic pain management among PLWH. In addition, exercise therapies reduce pain, reverse muscle atrophy, and decrease fall risk among older adults with chronic pain. Tai chi is a mind-body exercise that combines gentle movement, meditation and deep breathing. Tai chi can be feasibly administered to diverse groups of older adults and is associated with reduced pain,marijuana grow system risk of falling and depressive symptomatology. Given high rates of physical deconditioning in PLWH , tai chi constitutes a particularly appealing movement-based therapy due to its use of low impact, graded, weight bearing exercises.
Finally, text messaging has recently demonstrated efficacy in reinforcing elements of behavioral interventions, including those directed at changing addictive behaviors and managing chronic pain. Text messaging may also be an acceptable continuing care strategy following intensive treatment for a substance use disorder and in reducing problem drinking. We conducted a pilot randomized controlled trial to assess the feasibility, acceptability and preliminary efficacy of a multi-component behavioral intervention—a combined CBT and tai chi protocol reinforced with text messaging—to reduce levels of pain and substance use, and improve physical performance among older PLWH. We hypothesized that participants randomized to the intervention arm would demonstrate reductions in substance use, pain-related disability and pain intensity along with improvements in physical performance.Prior to the RCT, we conducted focus groups with prospective end users of the intervention to ascertain their preferences regarding behavioral treatments for pain ; developed the integrated intervention and trained APAIT staff to deliver it; and conducted a small pilot study, using the results to refine study materials and procedures prior to the current trial. We also obtained supplemental funding to conduct daily diary assessments of overall health, pain, behavioral responses to pain, mood, sleep, exercise, drinking and drug use, and social contact among all study participants via their cell phones. These data are reported in a separate paper. The Institutional Review Boards of all participating institutions approved the study. All participants provided written informed consent and participants assigned to the CBT/TC/TXT arm granted permission for the CBT sessions to be audiotaped. Study investigators developed an eight session, manualized treatment protocol to be delivered once weekly over 60 minutes in a group format by behavioral health counselors. The eight week, open-group program was adapted from three manualized interventions: 1) Manage Your Pain ; 2) Integrated CBT ; and 3) Mindfulness Based Relapse Prevention. All CBT sessions began with homework review, followed by delivery of didactic materials, coping skills, rehearsal exercises, and a new homework assignment. Therapy content focused on a different theme each week including 1) coping with chronic pain, 2) using mindfulness to cope with pain, 3) understanding and changing problematic patterns of substance use, 4) building motivation for change, 5) stress management and problem solving, 6) coping with negative thoughts and emotions, 7) improving sleep, and 8) building social support. Participants were given a copy of the client manual to facilitate between-session homework practice of coping skills presented in the weekly sessions. Three behavioral health counselors, including two members of APAIT’s staff, participated in a day-long training led by a Master’s level clinician experienced in administering manualized CBT interventions. To maintain fidelity during the trial, a clinical psychologist provided monthly supervision with review of audiotaped CBT sessions and feedback to counselors. Ongoing fidelity monitoring was conducted on all CBT sessions using a previously developed fidelity rating scale that assessed the extent of study therapists’ use of CBT-specific skills.These showed acceptable to excellent fidelity on all domains.The study employed a Yang-style tai chi delivered weekly for one hour following each CBT session. Each session started with a 10-minute warm-up, stretching and review of tai chi principles followed by 30 minutes of tai chi exercises, including five animal forms, a walking meditation, and a partnered activity known as push hands. Each class ended with a 10-minute cool down and a 5-minute closing that included a review of the material presented. A tai chi instructor with 18 years of experience trained two APAIT exercise program staff to lead the tai chi exercises. The staff underwent training for 1 hour weekly for 3 months before they began to lead tai chi sessions in the study. The trainer also attended four tai chi study sessions with each of the study instructors during the trial to monitor staff members’ instruction and provide feedback and adjustments as needed. Between November 2015 and April 2016, participants were recruited by a research assistant who distributed flyers at venues serving PLWH, including APAIT, gave presentations at nearby health agencies, and approached potential participants at health centers. A flow diagram shows the number of individuals approached, screened, and recruited, as well as losses to follow-up. Randomization was conducted by research staff who used consecutively numbered, sealed envelopes containing assignment information using a computer-generated set of random numbers to select permutated blocks of six. Within each block, equal numbers were assigned to each of the three groups. Participant follow-up concluded in July, 2016. Participants were compensated for their time via gift cards. Participants in the CBT/TC/TXT arm could be compensated up to $280, those in the SG arm could be compensated up to $200, while subjects in the AO arm could be compensated up to $120. Compensation included $10 for attending each CBT, TC or SG session.Demographic and health-related data included date of birth, gender, race/ethnicity, education, marital status, housing arrangement, employment status, number of years living with HIV, most recent CD4+ T lymphocyte count and HIV-1 RNA [detectable or undetectable ] and number of non-HIV chronic medical conditions. Participants also completed mental and physical health measures. Substance use data included most often used substance and the total number of substances used. Substances included both drugs and alcohol. Substance use measures included the WHO ASSIST-Version 3 and the Timeline Follow back. The TLFB was used to determine the number of days in the past 30 days of a) using a preferred substance; b) using any substance; c) using any drugs; and d) heavy drinking. Pain data included number of years of chronic pain, and medications used to treat pain.