Unlike MWH, WWH demonstrated a global impairment profile with spared verbal recognition. Consistently, previous findings regarding memory impairment among PWH found this impairment to be more dependent on frontal and subcortical structures with relatively normal memory retention but impaired memory retrieval . Even in the female-specific profile of relative weakness in learning and memory, recognition was less impaired compared to learning and recall. We can only speculate as to why the sparing of recognition in the global impairment profile was specific to WWH and to verbal vs. visual memory. It is possible that, in the context of cognitive impairment in HIV, the female advantage in verbal memory may be most salient for the least cognitively taxing memory component, recognition performance, and this advantage is not fully adjusted for in our demographically corrected T-scores. Despite the heterogeneity in cognitive profiles by sex, the sociodemographic/clinical/biological factors associated with these cognitive profiles were similar for MWH and WWH suggesting that, although the same factors confer increased vulnerability to cognitive dysfunction, the adverse effects of these factors impact brain function differently in men and women. In both MWH and WWH, WRAT-4 had the greatest discriminative value of profile class followed by HIV disease variables , depressive symptoms, age, race/ethnicity and years of education. WRAT-4 scores have been consistently identified as an important determinant of cognitive function among PWH, with lower WRAT-4 scores conferring risk for cognitive impairment . WRAT-4 performance may be particularly salient in this population, given that reading level may reflect education quality, above and beyond years of education, especially in lower socioeconomic populations because of the many factors impacting education quality . Additionally,vertical farming systems reading level is associated with health outcomes including hospitalizations and outpatient doctor visits and, thus, may be a proxy for bio-psychosocial factors underlying general health . HIV disease variables were also strong determinants of cognitive profiles in both men and women.

Aside from some instances of a shorter duration of HIV disease relating to more cognitive impairment in WWH and in the total sample, the more biologically-based HIV disease variables were associated with cognitive impairment in the expected direction; higher current and nadir CD4 count and lower viral load were protective against cognitive impairment. It is curious that the global weakness with spared verbal recognition profile in women was associated with more severe HIV-related variables yet with shorter duration of HIV infection. We speculate that the shorter HIV infection in WWH may reflect CNS effects of untreated and/or early course HIV infection. Alternatively, the self-reported shorter duration of infection may not have been accurate, to the extent that WWH lived longer with untested/undetected infections. Findings are consistent with a wealth of literature relating proxies of HIV disease burden and severity to cognitive function and suggests that, even in the era of effective ART when viral suppression is common, HIV disease burden can have adverse effects on the brain possibly due to poor penetration of ARTs into the CNS, ART resistance, poor medication adherence , and/or the establishment of viral reservoirs in the CNS reservoir . In line with hypotheses of mental health factors relating to cognitive impairment profiles more strongly in women, current diagnosis of MDD was a predictor of cognitive profiles only among WWH. 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 recognitioncompared to the profile demonstrating only Weakness in motor function . 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, 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 multi-collinearity 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,cannabis grow room 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 areneeded 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. Traumatic brain injury is a significant public health concern as it is a leading cause of mortality, morbidity and disability in the United States. According to the World Health Organization, TBI is expected to become the third leading cause of death and disability in the world by 2020. In the United States TBI contributes to a third of all injury-related deaths. The leading causes of injuries resulting in TBI prevalence are traffic related, such as motor vehicle crashes, or non-traffic related, such as falls. Notably, up to 51% of all TBI patients have substance use exposure at the time of injury. Substance use includes alcohol and drugs such as marijuana. Current existing research suggest that in general, substance-exposed patients may have worse TBI outcomes, including greater rates of mortality and severity of injury. Research has also shown that substance use exposed TBI patients suffer worse functional outcomes, which can result in socioeconomic burden to patients and the nation at large. This healthcare burden has been calculated to be approximately $76.5 billion in 2010 alone. There is a substantial body of research elucidating the role alcohol plays in injuries that lead to TBI prevalence and outcomes. Specifically, alcohol use results in impairments such as diminished motor control, blurred vision, and poor decision making, which has been shown to increase the risk of traffic related injury.

This research has been used to create public health policies and prevention programs that have made a significant health impact, such as reducing the number of alcohol-impaired drivers. Other substances have not been as well studied. For example, marijuana is a drug that despite being federally and legally regulated, remains the most widely used drug in the U.S. Marijuana use has been shown to result in similar cognitive impairments as alcohol use, such as lack of coordination, inability to pay attention, and decision-making abilities, suggesting marijuana users are similarly at increased risk for TBI. There is some indirect evidence of this, in that it has been shown that marijuana users in general are about 25% more likely to be involved in a motor vehicle crash and that the older adult marijuana users have a greater risk for falls. However, concrete data linking marijuana exposure at time of injury and TBI prevalence and severity is scarce. Adding to the concern, national surveys on drug use and health have documented an increase in individual daily marijuana use over the last 5 years. As the number of states legalizing marijuana for both medical and recreational use increases, it is imperative to resolve the ambiguity within the research available regarding the relationships between marijuana exposure at time of injury, mechanism of injury, and TBI prevalence and severity. This study found that the presence of THC was significantly associated with lower GCS scores and a potentially more severe TBI, but this relationship was significant without controlling for other predicting variables. Furthermore, a significant relationship was found between GCS scores, age, and blood alcohol levels at the time of presentation in the ED. Older participants were found to have higher GCS scores, indicating a less serious brain injury. Study participants who had higher blood alcohol levels were found to have lower GCS scores, indicating a more serious brain injury. Age and higher blood alcohol levels were found to be associated, with higher blood alcohol levels noted in younger patients. A linear regression showed different results when examining the relationship between the presence of THC and GCS scores, hence TBI severity. When controlling for all other variables, the presence of THC was not found to be an independent predictor of TBI severity.