Performance of a modified fracture risk assessment tool for fragility fracture prediction among older veterans living with HIV.

OBJECTIVE: Fragility fractures (fractures) are a critical outcome for persons aging with HIV (PAH). Research suggests that the fracture risk assessment tool (FRAX) only modestly estimates fracture risk among PAH. We provide an updated evaluation of how well a 'modified FRAX' identifies PAH at risk for fractures in a contemporary HIV cohort. DESIGN: Cohort study. METHODS: We used data from the Veterans Aging Cohort Study to evaluate veterans living with HIV, aged 50+ years, for the occurrence of fractures from 1 January 2010 through 31 December 2019. Data from 2009 were used to evaluate the eight FRAX predictors available to us: age, sex, BMI, history of previous fracture, glucocorticoid use, rheumatoid arthritis, alcohol use, and smoking status. These predictor values were then used to estimate participant risk for each of two types of fractures (major osteoporotic and hip) over the subsequent 10 years in strata defined by race/ethnicity using multivariable logistic regression. RESULTS: Discrimination for major osteoporotic fracture was modest [Blacks: area under the curve (AUC) 0.62; 95% confidence interval (CI) 0.62, 0.63; Whites: AUC 0.61; 95% CI 0.60, 0.61; Hispanic: AUC 0.63; 95% CI 0.62, 0.65]. For hip fractures, discrimination was modest to good (Blacks: AUC 0.70; 95% CI 0.69, 0.71; Whites: AUC 0.68; 95% CI 0.67, 0.69]. Calibration was good in all models across all racial/ethnic groups. CONCLUSION: Our 'modified FRAX' exhibited modest discrimination for predicting major osteoporotic fracture and slightly better discrimination for hip fracture. Future studies should explore whether augmentation of this subset of FRAX predictors results in enhanced prediction of fractures among PAH.

Comparison of quantitative ultrasonography and dual X-ray absorptiometry for bone status assessment in South African children living with HIV.

Children living with HIV (CLHIV) have decreased bone mineral content (BMC) and density (BMD), increasing risk for fracture and future osteoporosis. While DXA is the gold-standard for bone assessments, it lacks availability in resource-constrained settings (RCS). Quantitative ultrasound (QUS) offers an alternative owing to its portability, low cost, ease of handling, and lack of ionizing radiation. While QUS has detected reduced bone quality in CLHIV, the relationship between QUS and DXA in this population remains unexplored. At baseline and 12 months, BMC and BMD of the whole body, lumbar spine, and radius were measured by DXA in a longitudinal cohort of CLHIV in Johannesburg, South Africa. Calcaneal speed of sound (SOS) and broadband ultrasound attenuation (BUA) and radius SOS were obtained by QUS, and calcaneal stiffness index (SI) was calculated. Spearman correlations, with and without HIV stratification, were performed between QUS and DXA measurements at each visit and for absolute difference in measurements between visits. At baseline and 12-months, calcaneal BUA and SI displayed strong positive correlations with DXA, with only modest correlations between radial QUS and DXA at baseline. Longitudinal measures of QUS did not correlate with DXA. At both baseline and 12-months, individuals with DXA whole-body BMD z-score < -1 displayed significantly lower calcaneal BUA and SI. Cross-sectionally, calcaneal QUS correlates strongly with whole body DXA and may represent a viable diagnostic alternative in RCS. Longitudinally, the two methods do not correlate well, possibly reflecting that each method assesses distinct aspects of bone architecture.

Challenges and opportunities of telehealth digital equity to manage HIV and comorbidities for older persons living with HIV in New York State.

BACKGROUND: Older persons living with HIV (PLWH) need routine healthcare to manage HIV and other comorbidities. This mixed methods study investigated digital equity, constituted as access, use and quality, of HIV and specialty telehealth services for PLWH > 50 years during the initial wave of the COVID-19 pandemic when services transitioned to remote care. METHODS: A survey of closed and open-ended questions was administered to 80 English (N = 63) and Spanish (N = 17) speaking PLWH receiving HIV care at an Academic Medical Center (N = 50) or a Federally Qualified Health Center (N = 30) in New York State. Quantitative analyses examined characteristics predicting telehealth use and visit quality. Qualitative analyses utilized thematic coding to reveal common experiences. Results were integrated to deepen the interpretation. RESULTS: Telehealth access and use were shaped by multiple related and unstable factors including devices and connectivity, technology literacy, and comfort including privacy concerns. Participants demonstrated their substantial effort to achieve the visit. The majority of patients with a telehealth visit perceived it as worse than an in-person visit by describing it as less interpersonal, and resulting in poorer outcomes, particularly participants with less formal education. Technology was not only a barrier to access, but also influenced perceptions of quality. CONCLUSIONS: In the COVID-19 pandemic initial wave, barriers to using telehealth were unequally distributed to those with more significant access and use challenges. Beyond these barriers, examining the components of equity indicate further challenges replicating in-person care using telehealth formats for older PLWH. Work remains to establish telehealth as both equitable and desirable for this population.

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients.

Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill.

Cardiovascular Risk Assessment Varies Widely by Calculator and Race/Ethnicity in a Majority Latinx Cohort Living with HIV.

Comparison of cardiovascular disease (CVD) risk calculators in Latinx majority populations living with HIV can assist clinicians in selecting a calculator and interpreting results. 10-year CVD risks were estimated for 652 patients seen ≥ 2 times over 12 months in a public clinic using three risk calculators: Atherosclerotic CVD risk Calculator (ASCVD), Framingham Risk Calculator (FRC), and Data Collection on Adverse Effects of Anti-HIV Drugs Study (D:A:D) Calculator. Median estimated 10-year CVD risk in this population was highest using FRC (11%), followed by D:A:D (10%), and lowest with ASCVD (5%; p < 0.001). However, D:A:D classified 44.3% in a high/very high risk category compared to FRC (20.7%) and ASCVD (33.4%) (all p < 0.001). ASCVD risk estimates differed significantly by race/ethnicity (p < 0.001). Risk varied widely across three risk calculators and by race/ethnicity, and providers should be aware of these differences when choosing a calculator for use in majority minority populations.

Longitudinal analysis of social and behavioral determinants of health in the EHR: exploring the impact of patient trajectories and documentation practices.

Social and behavioral determinants of health (SBDH) are environmental and behavioral factors that impede disease self-management and can exacerbate clinical conditions. While recent research in the informatics community has focused on building systems that can automatically infer SBDH from the patient record, it is unclear how such determinants change overtime. This study analyzes the longitudinal characteristics of 4 common SBDH as expressed in the patient record and compares the rates of change among distinct SBDH. In addition, manual review of patient notes was undertaken to establish whether changes in patient SBDH status reflected legitimate changes in patient status or rather potential data quality issues. Our findings suggest that a patient's SBDH status is liable to change over time and that some changes reflect poor social history taking by clinicians.

Improved fracture prediction using different fracture risk assessment tool adjustments in HIV-infected women.

OBJECTIVES: A fracture risk assessment tool (FRAX) using clinical risk factors (CRFs) alone underestimates fracture risk in HIV-infected men. Our objective was to determine whether accuracy of FRAX would be improved by considering HIV as a cause of secondary osteoporosis, and further improved with addition of dual-energy X-ray absorptiometry parameters in HIV-infected women. DESIGN: Subgroup analysis of Women's Interagency HIV Study. METHODS: We included 1148 women (900 HIV-infected and 248 uninfected) over age 40 with data to approximate FRAX CRFs and 10-year observational data for incident fragility fractures; 181 (20%) HIV-infected women had dual-energy X-ray absorptiometry data. Accuracy of FRAX was evaluated by the observed/estimated ratios of fracture in four models: CRFs alone; CRFs with HIV included as a cause of secondary osteoporosis; CRFs and femoral neck bone mineral density (FN BMD); and CRFs, FN BMD and trabecular bone score. RESULTS: FRAX using CRFs were less accurate in HIV-infected than uninfected women for major osteoporotic (observed/estimated ratio: 5.05 vs. 3.26, P < 0.001) and hip fractures (observed/estimated ratio: 19.78 vs. 7.94, P < 0.001), but improved when HIV was included as a cause of secondary osteoporosis. Among HIV-infected women, FRAX accuracy improved further with addition of FN BMD (observed/estimated ratio: 4.00) for hip fractures, but no further with trabecular bone score. CONCLUSION: FRAX using CRFs alone underestimated fracture risk more in older HIV-infected women than otherwise similar uninfected women. Accuracy is improved when including HIV as a cause of secondary osteoporosis for both major osteoporotic and hip fractures, whereas addition of FN BMD only improved accuracy for hip fracture.

Population Pharmacokinetics of Polymyxin B in Acutely Ill Adult Patients.

Polymyxin B (PB) has reemerged as a common treatment against multidrug-resistant Gram-negative pathogens. However, nephrotoxicity remains a significant dose-limiting side effect, and contemporary pharmacokinetic (PK) data are limited. This study sought to evaluate PB exposure differences in various loading and nonloading strategies according to total body weight (TBW) and adjusted body weight (ABW). Patients treated with PB had plasma samples obtained for clinical care and analyzed using liquid chromatography-tandem mass spectrometry. Compartmental PK models with linear and allometric scaling of TBW were explored. Semiparametric Monte Carlo simulation evaluated the total (i.e., protein bound plus unbound) area under the plasma concentration-time curve (AUCtotal) during the first 24 h of therapy and at 96 h posttherapy for each regimen at the 10th, 50th, and 90th percentiles of TBW and ABW in the derivation cohort. Literature-based values of the 24-h total AUC/MIC ratio (AUC/MICtotal) of ≥50 defined efficacy, and literature-based values of the 72- to 96-h AUCtotal of ≥100 µg · h/ml defined toxicity. Fifty-two patients contributed 156 PB plasma samples. A two-compartment model with allometric scaling of TBW produced a comparable fit (Akaike information criterion [AIC] = 376.7) to that achieved with linear scaling (AIC = 378). The regimen of a loading dose of 2.5 mg/kg of body weight plus a fixed dose of 100 mg every 12 h had the highest probability of achieving a 24-h AUC/MICtotal of ≥50 with the lowest probability of toxicity in all groups at 24 h, aside from those with the lowest 10th percentile of body weight. This is the first study to suggest that a weight-based loading and fixed maintenance (i.e., weight-independent) dosing strategy for polymyxin B may maximize efficacy while balancing toxicity concerns for most patients.

Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.

OBJECTIVE: Universal HIV screening programs are costly, labor intensive, and often fail to identify high-risk individuals. Automated risk assessment methods that leverage longitudinal electronic health records (EHRs) could catalyze targeted screening programs. Although social and behavioral determinants of health are typically captured in narrative documentation, previous analyses have considered only structured EHR fields. We examined whether natural language processing (NLP) would improve predictive models of HIV diagnosis. METHODS: One hundred eighty-one HIV+ individuals received care at New York Presbyterian Hospital before a confirmatory HIV diagnosis and 543 HIV negative controls were selected using propensity score matching and included in the study cohort. EHR data including demographics, laboratory tests, diagnosis codes, and unstructured notes before HIV diagnosis were extracted for modeling. Three predictive algorithms were developed using machine-learning algorithms: (1) a baseline model with only structured EHR data, (2) baseline plus NLP topics, and (3) baseline plus NLP clinical keywords. RESULTS: Predictive models demonstrated a range of performance with F measures of 0.59 for the baseline model, 0.63 for the baseline + NLP topic model, and 0.74 for the baseline + NLP keyword model. The baseline + NLP keyword model yielded the highest precision by including keywords including "msm," "unprotected," "hiv," and "methamphetamine," and structured EHR data indicative of additional HIV risk factors. CONCLUSIONS: NLP improved the predictive performance of automated HIV risk assessment by extracting terms in clinical text indicative of high-risk behavior. Future studies should explore more advanced techniques for extracting social and behavioral determinants from clinical text.

Towards the Inference of Social and Behavioral Determinants of Sexual Health: Development of a Gold-Standard Corpus with Semi-Supervised Learning.

Social and behavioral determinants of health (SBDH) are environmental and behavioral factors that are increasingly recognized for their impact on health outcomes. We describe ongoing research to extract SBDH related to sexual health from clinical documentation. Our work addresses several challenges. First, there is no standard set of SBDHs for sexual health; we describe our curation of 38 such SBDHs. Second, it is unknown how SBDH related to sexual health are expressed in clinical notes; we detail the characteristics of an annotated corpus. Third, SBDH documentations are rare; we describe the use of semi-supervised learning to accelerate the annotation process by identifying notes likely to document SBDH. Fourth, we describe preliminary results to infer an array of SBDH from clinical documentation using supervised learning.

Survey of HIV care providers on management of HIV serodiscordant couples - assessment of attitudes, knowledge, and practices.

Human immunodeficiency virus (HIV) serodiscordant couples are at risk of sexual transmission of HIV between the infected and uninfected partner. We assessed New York area care providers for people living with HIV regarding attitudes, knowledge, and practice patterns toward fertility and conception in serodiscordant couples. Data were collected via a survey distributed in October 2013. Seventeen percent of respondents reported prescribing antiretroviral preexposure prophylaxis (PrEP) for a woman in a serodiscordant couple, and 38% percent of respondents reported having counseled serodiscordant couples on timed, unprotected intercourse without PrEP. Respondents who reported being "very" familiar with the data on HIV transmission in serodiscordant couples were more likely to report counseling their patients in timed, unprotected intercourse compared with those who reported less familiarity with the data (41% vs. 8%, p = 0.001). Although only 20% reported being "very" or "somewhat" familiar with the data on the safety of sperm washing with intrauterine insemination, those who did were more likely to have reported referring a patient for assisted reproductive technology (61% vs. 32%, p = 0.006). Effective patient counseling and referral for appropriate reproductive options were associated with knowledge of the literature pertaining to these options. This emphasizes the need for further provider education on reproductive options and appropriate counseling for serodiscordant couples.