Factors partitioning physical frailty in people aging with HIV: A classification and regression tree approach

Disentangling the Effects of Comorbidity and Polypharmacy on Cognitive Function and Physical Frailty in Individuals With HIV

OBJECTIVE

To estimate the extent to which comorbidity, polypharmacy, and anticholinergic/sedative burden interrelate to influence cognitive ability, perceived cognitive deficits (PCD), and physical frailty in people living with HIV.

DESIGN

Cross-sectional Structural Equation Modeling of data from 824 older people living with HIV in Canada, participating in the Positive Brain Health Now study.

METHOD

Structural Equation Modeling was used to link observed variables, including comorbidity, polypharmacy, anticholinergic, and sedative burden, to cognitive ability and 2 latent constructs-physical frailty and PCD. The model was adjusted for age, sex, education, nadir CD4, duration of HIV, and symptoms of anxiety/depression. Maximum Likelihood with Robust standard errors and bootstrapping were used to test the robustness and significance of the model's indirect effects.

RESULTS

Anticholinergic burden had a direct significant negative relationship with cognitive ability (βstd = -0.21, P < 0.05) and indirect effect on PCD (βstd = 0.16, P < 0.01) and frailty (βstd = 0.06, P < 0.01) through sedative burden. Sedative burden was directly associated with PCD (βstd = 0.18, P < 0.01) and indirectly with frailty through PCD (βstd = 0.07, P < 0.01). Comorbidity and polypharmacy exerted indirect effects on PCD and physical frailty through anticholinergic and sedative burden. The model fits the data well (CFI: 0.97, TLI: 0.94, RMSEA: 0.05, SRMR: 0.04).

CONCLUSIONS

Anticholinergic and sedative burden function as a pathway through which polypharmacy and comorbidities influence physical frailty and PCD. Reducing the use of anticholinergic and sedative medications could help prevent and manage cognitive impairment and frailty in older people living with HIV.

Prevalence and Correlates of Frailty Among Older Adults Living With HIV in the CHANGE HIV Cohort

BACKGROUND

Advancements in treatment have resulted in improved survival among people living with HIV. However, additional years of life are not necessarily spent in good health, as frailty tends to develop at a younger age among people living with HIV. We set out to examine the prevalence of frailty and its correlates among older adults living with HIV in Canada, with a primary interest in nadir CD4 count.

METHODS

We performed a cross-sectional analysis of the Correlates of Healthy Aging in Geriatric HIV (CHANGE HIV) study, a Canadian cohort of people living with HIV aged 65 years or older. Participants were assessed using the Fried Frailty Phenotype at cohort entry, and those meeting ≥3 criteria were characterized as frail. We used Poisson regression with robust standard errors to estimate the association between nadir CD4 count and frailty, as well as age, gender, time since HIV diagnosis, comorbidities, marital status, and loneliness.

RESULTS

Among 439 participants included in this analysis (median age 69 years, interquartile ranges 67-73), prevalence of frailty was 16.6%. Frailty was not associated with nadir CD4 count. Not being in a relationship (aRR 2.09, 95% CI 1.01 to 4.30) and greater degree of loneliness (aRR 1.25 per 10 point increase on UCLA loneliness scale, 95% CI 1.09 to 1.44) were associated with frailty.

CONCLUSIONS

Frailty occurred in 16.6% of older adults living with HIV in this cohort. While nadir CD4 count did not correlate with frailty, being single and lonely did, highlighting the importance of recognizing and addressing these social vulnerabilities among people aging with HIV.

Health-related quality of life measures provide information on the contributors, components, and consequences of frailty in HIV: a systematic mapping review

PURPOSE

Frailty in HIV is extensively explored in epidemiological and clinical studies; it is infrequently assessed as an outcome in routine care. The focus on health-related quality of life (HRQL) measures in HIV presents a unique opportunity to understand frailty at a larger scale. The objective was to identify the extent to which generic and HIV-related HRQL measures capture information relevant to frailty.

METHODS

A systematic mapping review using directed and summative content analyses was conducted. An online search in PubMed/Medline identified publications on frailty indices and generic and HIV-related HRQL measures. Directed content analysis involved identifying contributors, components, and consequences of frailty from the frailty indices based on the International Classification of Functioning, Disability, and Health framework. Summative content analysis summarized the results numerically.

RESULTS

Electronic and hand search identified 447 review publications for frailty indices; nine reviews that included a total of 135 unique frailty indices. The search for generic and HIV-related HRQL measures identified 2008 records; five reviews that identified 35 HRQL measures (HIV-specific: 17; generic: 18). Of the 135 frailty indices, 88 cover more than one frailty dimension and 47 cover only physical frailty. Contributors to frailty, like sensory symptoms and nutrition, are extensively covered. Components of frailty such as physical capacity, cognitive ability, and mood are also extensively covered. Consequences of frailty namely self-rated health, falls, hospitalization, and health services utilization are incomprehensively covered. HRQL measures are informative for contributing factors, components of frailty, and a consequence of frailty.

CONCLUSION

HRQL items and measures show a strong potential to operationalize multidimensional frailty and physical frailty. The study suggests that these measures, connected to evidence-based interventions, could be pivotal in directing resources toward vulnerable populations to mitigate the onset of frailty.

The association between anticholinergic/sedative burden and physical frailty in people aging with HIV

OBJECTIVE

This study aimed to estimate the strength of the association between anticholinergic/sedative burden and concurrent physical frailty in people aging with HIV.

DESIGN

This cross-sectional analysis examined baseline data from 824 adults with a mean age of 53 enrolled in the Positive Brain Health Now study.

METHODS

Anticholinergic medications were identified using four methods: Anticholinergic Cognitive Burden (ACB) Scale, Anticholinergic Risk Scale (ARS), Anticholinergic Drug Scale (ADS), and the anticholinergic list of the Anticholinergic and Sedative Burden Catalog (ACSBC). Sedatives were identified using the Sedative Load Model (SLM) and the sedative list of the ACSBC. Physical frailty was assessed using a modified Fried Frailty Phenotype (FFP) based on self-report items. Multivariable logistic regression models, adjusted for sociodemographic factors, lifestyle considerations, HIV-related variables, comorbidities, and co-medication use, were used to estimate odds ratios (ORs).

RESULTS

Anticholinergic burden demonstrated associations with frailty across various methods: total anticholinergic burden (OR range: 1.22-1.32; 95% confidence interval (CI) range: 1.03-1.66), sedative burden (OR range: 1.18-1.24; 95% CI range: 1.02-1.45), high anticholinergic burden (OR range: 2.12-2.74; 95% CI range: 1.03-6.19), and high sedative burden (OR range: 1.94-2.18; 95% CI: 1.01-4.34).

CONCLUSION

The anticholinergic and sedative burdens may represent modifiable risk factors for frailty in people aging with HIV. Future studies should evaluate the effects of reducing anticholinergic and sedative burdens on frailty outcomes and explore the prognostic value of diverse scoring methods.

Frailty in people 50 years or older living with HIV: A sex perspective

OBJECTIVE

To estimate prefrailty and frailty prevalence and associated factors in people living with HIV (PLHIV) from a sex perspective.

METHODS

Cross-sectional study on PLHIV at specialized public health centres in Brazil. Data were obtained from individuals aged ≥50 years using antiretroviral therapy (ART) and with an undetectable viral load through personal interviews, clinical evaluations and medical records. Frailty and prefrailty were characterized using the Fried Frailty Phenotype tool. Multinomial regression models were performed, and the associated factors were selected through the backward stepwise method.

RESULTS

Among 670 patients, 373 men and 297 women were included. The prevalence of frailty and prefrailty was significantly higher for women (16.2% and 56.2%, respectively) than for men (11.5% and 46.4%, respectively). Low socioeconomic and educational level, multimorbidity, depression, subjective cognitive complaints, and low scores on the Mini-Mental State Exam (MMSE) were associated (P < 0.05) with frailty for both sexes. However, in the sex-specific analysis, while smoking (OR = 3.66, 95% CI: 1.58-8.48) and a history of low adherence to ART (OR = 3.10, 95% CI: 1.33-7.23) were associated with frailty in men, depression (OR = 3.39, 95% CI: 1.36- 8.44) and the absence of functional dentition (OR = 3.77, 95% CI: 1.36- 10.43) were associated with frailty in women.

CONCLUSIONS

This study adds self-reported cognitive complaints as a potential predictor of frailty in both sexes and supports the known deleterious effect of multimorbidity on frailty in adults living with HIV. Furthermore, it suggests that other possible predictors, such as depression, oral health status and adherence to ART, may be sex-specific.

The Patient Generated Index (PGI) as an early-warning system for predicting brain health challenges: a prospective cohort study for people living with Human Immunodeficiency Virus (HIV)

PURPOSE

In research people are often asked to fill out questionnaires about their health and functioning and some of the questions refer to serious health concerns. Typically, these concerns are not identified until the statistician analyses the data. An alternative is to use an individualized measure, the Patient Generated Index (PGI) where people are asked to self-nominate areas of concern which can then be dealt with in real-time. This study estimates the extent to which self-nominated areas of concern related to mood, anxiety and cognition predict the presence or occurrence of brain health outcomes such as depression, anxiety, psychological distress, or cognitive impairment among people aging with HIV at study entry and for successive assessments over 27 months.

METHODS

The data comes from participants enrolled in the Positive Brain Health Now (+ BHN) cohort (n = 856). We analyzed the self-nominated areas that participants wrote on the PGI and classified them into seven sentiment groups according to the type of sentiment expressed: emotional, interpersonal, anxiety, depressogenic, somatic, cognitive and positive sentiments. Tokenization was used to convert qualitative data into quantifiable tokens. A longitudinal design was used to link these sentiment groups to the presence or emergence of brain health outcomes as assessed using standardized measures of these constructs: the Hospital Anxiety and Depression Scale (HADS), the Mental Health Index (MHI) of the RAND-36, the Communicating Cognitive Concerns Questionnaire (C3Q) and the Brief Cognitive Ability Measure (B-CAM). Logistic regressions were used to estimate the goodness of fit of each model using the c-statistic.

RESULTS

Emotional sentiments predicted all of the brain health outcomes at all visits with adjusted odds ratios (OR) ranging from 1.61 to 2.00 and c-statistics > 0.73 (good to excellent prediction). Nominating an anxiety sentiment was specific to predicting anxiety and psychological distress (OR 1.65 & 1.52); nominating a cognitive concern was specific to predicting self-reported cognitive ability (OR 4.78). Positive sentiments were predictive of good cognitive function (OR 0.36) and protective of depressive symptoms (OR 0.55).

CONCLUSIONS

This study indicates the value of using this semi-qualitative approach as an early-warning system in predicting brain health outcomes.

Using a Decision Tree Algorithm Predictive Model for Sperm Count Assessment and Risk Factors in Health Screening Population

Purpose

Approximately 20% of couples face infertility challenges and struggle to conceive naturally. Despite advances in artificial reproduction, its success hinges on sperm quality. Our previous study used five machine learning (ML) algorithms, random forest, stochastic gradient boosting, least absolute shrinkage and selection operator regression, ridge regression, and extreme gradient boosting, to model health data from 1375 Taiwanese males and identified ten risk factors affecting sperm count.

Methods

We employed the CART algorithm to generate decision trees using identified risk factors to predict healthy sperm counts. Four error metrics, SMAPE, RAE, RRSE, and RMSE, were used to evaluate the decision trees. We identified the top five decision trees based on their low errors and discussed in detail the tree with the least error.

Results

The decision tree featuring the least error, comprising BMI, UA, ST, T-Cho/HDL-C ratio, and BUN, corroborated the negative impacts of metabolic syndrome, particularly high BMI, on sperm count, while emphasizing the link between good sleep and male fertility. Our study also sheds light on the potentially significant influence of high BUN on spermatogenesis. Two novel risk factors, T-Cho/HDL-C and UA, warrant further investigation.

Conclusion

The ML algorithm established a predictive model for healthcare personnel to assess low sperm counts. Refinement of the model using additional data is crucial for improved precision. The risk factors identified offer avenues for future investigations.

Development of Frail RISC-HIV: a Risk Score for Predicting Frailty Risk in the Short-term for Care of People with HIV

OBJECTIVE

Frailty is common among people with HIV (PWH), so we developed frail risk in the short-term for care (RISC)-HIV, a frailty prediction risk score for HIV clinical decision-making.

DESIGN

We followed PWH for up to 2 years to identify short-term predictors of becoming frail.

METHODS

We predicted frailty risk among PWH at seven HIV clinics across the United States. A modified self-reported Fried Phenotype captured frailty, including fatigue, weight loss, inactivity, and poor mobility. PWH without frailty were separated into training and validation sets and followed until becoming frail or 2 years. Bayesian Model Averaging (BMA) and five-fold-cross-validation Lasso regression selected predictors of frailty. Predictors were selected by BMA if they had a greater than 45% probability of being in the best model and by Lasso if they minimized mean squared error. We included age, sex, and variables selected by both BMA and Lasso in Frail RISC-HIV by associating incident frailty with each selected variable in Cox models. Frail RISC-HIV performance was assessed in the validation set by Harrell's C and lift plots.

RESULTS

Among 3170 PWH (training set), 7% developed frailty, whereas among 1510 PWH (validation set), 12% developed frailty. BMA and Lasso selected baseline frailty score, prescribed antidepressants, prescribed antiretroviral therapy, depressive symptomology, and current marijuana and illicit opioid use. Discrimination was acceptable in the validation set, with Harrell's C of 0.76 (95% confidence interval: 0.73-0.79) and sensitivity of 80% and specificity of 61% at a 5% frailty risk cutoff.

CONCLUSIONS

Frail RISC-HIV is a simple, easily implemented tool to assist in classifying PWH at risk for frailty in clinics.

The Impact of Frailty on All-Cause Mortality in Patients with HIV Infection: A Systematic Review and Meta-Analysis

The aim of this study was to conduct a systematic review and meta-analysis of cohort studies that have examined the association between frailty and all-cause mortality in patients with HIV infection. We searched Embase, Medline through the Ovid interface, PubMed, Cochrane Library, and Web of Science to identify potential studies. Cohort studies of death outcomes in HIV patients under debilitating conditions were included and other ineligible or inadequate data were excluded. Data related to all-cause mortality in patients with HIV were extracted. The quality of the included studies was assessed using the Newcastle-Ottawa Scale for cohort studies. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were pooled to estimate the association between frailty and all-cause mortality using Stata, version 12.0. We identified 845 unduplicated citations. Of these, six cohort studies were eligible for inclusion in the review after applying our inclusion and exclusion criteria. Pooled results demonstrated that patients with HIV experiencing frailty were at an increased risk of all-cause mortality (pooled HR = 2.69, 95% CI = 1.83-3.97, p < .001) compared with those without frailty. Frailty was significantly associated with an increased risk of all-cause mortality among patients with HIV, indicating that frailty is an important predictor of adverse clinical outcomes. Therefore, more attention should be paid to screen patients with HIV for frailty and adopt appropriate interventions and personalized treatment plans to prevent the occurrence of adverse events. However, these results need to be validated in further prospective cohort studies in ethnically or geographically diverse populations.