Determinants of Smoking and Quitting in HIV-Infected Individuals

Background: Cigarette smoking is widespread among HIV-infected patients, who confront increased risk of smoking-related co-morbidities. The effects of HIV infection and HIV-related variables on smoking and smoking cessation are incompletely understood. We investigated the correlates of smoking and quitting in an HIV-infected cohort using a validated natural language processor to determine smoking status. Method We developed and validated an algorithm using natural language processing (NLP) to ascertain smoking status from electronic health record data. The algorithm was applied to records for a cohort of 3487 HIV-infected from a large health care system in Boston, USA, and 9446 uninfected control patients matched 3:1 on age, gender, race and clinical encounters. NLP was used to identify and classify smoking-related portions of free-text notes. These classifications were combined into patient-year smoking status and used to classify patients as ever versus never smokers and current smokers versus non-smokers. Generalized linear models were used to assess associations of HIV with 3 outcomes, ever smoking, current smoking, and current smoking in analyses limited to ever smokers (persistent smoking), while adjusting for demographics, cardiovascular risk factors, and psychiatric illness. Analyses were repeated within the HIV cohort, with the addition of CD4 cell count and HIV viral load to assess associations of these HIV-related factors with the smoking outcomes. Results: Using the natural language processing algorithm to assign annual smoking status yielded sensitivity of 92.4, specificity of 86.2, and AUC of 0.89 (95% confidence interval [CI] 0.88–0.91). Ever and current smoking were more common in HIV-infected patients than controls (54% vs. 44% and 42% vs. 30%, respectively, both P<0.001). In multivariate models HIV was independently associated with ever smoking (adjusted rate ratio [ARR] 1.18, 95% CI 1.13–1.24, P <0.001), current smoking (ARR 1.33, 95% CI 1.25–1.40, P<0.001), and persistent smoking (ARR 1.11, 95% CI 1.07–1.15, P<0.001). Within the HIV cohort, having a detectable HIV RNA was significantly associated with all three smoking outcomes. Conclusions: HIV was independently associated with both smoking and not quitting smoking, using a novel algorithm to ascertain smoking status from electronic health record data and accounting for multiple confounding clinical factors. Further research is needed to identify HIV-related barriers to smoking cessation and develop aggressive interventions specific to HIV-infected patients

Stroke in HIV

Stroke is a heterogeneous disease in persons living with human immunodeficiency virus (HIV). HIV is thought to increase the risk of stroke through both HIV-related and traditional stroke risk factors, which vary with respect to the patient's age and clinical characteristics. Numerous studies show that detectable viremia and immunosuppression increase the risk of stroke across all ages, whereas traditional risk factors are more common in the aging population with HIV. As persons living with HIV age and acquire traditional stroke risk factors, the prevalence of stroke will likely continue to increase. Large- and small-vessel disease are the most common causes of stroke, although it is important to evaluate for infectious etiology as well. Research regarding the management of stroke in patients with HIV is scant, and recommendations often parallel those for the general population. Treatment of HIV and effective reduction of traditional stroke risk factors is important to reduce the risk of stroke in persons living with HIV. Future research will help elucidate the pathophysiology of HIV and stroke risk, investigate sex differences in stroke risk, and evaluate the safety and benefits of standard stroke preventative measures and HIV-specific interventions in this population

Human Immunodeficiency Virus (HIV) Quality Indicators Are Similar Across HIV Care Delivery Models

Abstract Background. There are limited data on human immunodeficiency virus (HIV) quality indicators according to model of HIV care delivery. Comparing HIV quality indicators by HIV care model could help inform best practices because patients achieving higher levels of quality indicators may have a mortality benefit. Methods. Using the Partners HIV Cohort, we categorized 1565 patients into 3 HIV care models: infectious disease provider only (ID), generalist only (generalist), or infectious disease provider and generalist (ID plus generalist). We examined 12 HIV quality indicators used by 5 major medical and quality associations and grouped them into 4 domains: process, screening, immunization, and HIV management. We used generalized estimating equations to account for most common provider and multivariable analyses adjusted for prespecified covariates to compare composite rates of HIV quality indicator completion. Results. We found significant differences between HIV care models, with the ID plus generalists group achieving significantly higher quality measures than the ID group in HIV management (94.4% vs 91.7%, P = .03) and higher quality measures than generalists in immunization (87.8% vs 80.6%, P = .03) in multivariable adjusted analyses. All models achieved rates that equaled or surpassed previously reported quality indicator rates. The absolute differences between groups were small and ranged from 2% to 7%. Conclusions. Our results suggest that multiple HIV care models are effective with respect to HIV quality metrics. Factors to consider when determining HIV care model include healthcare setting, feasibility, and physician and patient preference

Non-Communicable Disease Preventive Screening by HIV Care Model

<div><p>Importance</p><p>The Human Immunodeficiency Virus (HIV) epidemic has evolved, with an increasing non-communicable disease (NCD) burden emerging and need for long-term management, yet there are limited data to help delineate the optimal care model to screen for NCDs for this patient population.</p><p>Objective</p><p>The primary aim was to compare rates of NCD preventive screening in persons living with HIV/AIDS (PLWHA) by type of HIV care model, focusing on metabolic/cardiovascular disease (CVD) and cancer screening. We hypothesized that primary care models that included generalists would have higher preventive screening rates.</p><p>Design</p><p>Prospective observational cohort study.</p><p>Setting</p><p>Partners HealthCare System (PHS) encompassing Brigham & Women’s Hospital, Massachusetts General Hospital, and affiliated community health centers.</p><p>Participants</p><p>PLWHA age >18 engaged in active primary care at PHS.</p><p>Exposure</p><p>HIV care model categorized as infectious disease (ID) providers only, generalist providers only, or ID plus generalist providers.</p><p>Main Outcome(s) and Measures(s)</p><p>Odds of screening for metabolic/CVD outcomes including hypertension (HTN), obesity, hyperlipidemia (HL), and diabetes (DM) and cancer including colorectal cancer (CRC), cervical cancer, and breast cancer.</p><p>Results</p><p>In a cohort of 1565 PLWHA, distribution by HIV care model was 875 ID (56%), 90 generalists (6%), and 600 ID plus generalists (38%). Patients in the generalist group had lower odds of viral suppression but similar CD4 counts and ART exposure as compared with ID and ID plus generalist groups. In analyses adjusting for sociodemographic and clinical covariates and clustering within provider, there were no significant differences in metabolic/CVD or cancer screening rates among the three HIV care models.</p><p>Conclusions</p><p>There were no notable differences in metabolic/CVD or cancer screening rates by HIV care model after adjusting for sociodemographic and clinical factors. These findings suggest that HIV patients receive similar preventive health care for NCDs independent of HIV care model.</p></div

Odds of comparative diabetes screening events by specific screening types (A1C vs. fasting glucose).

<p>Odds ratios and 95% confidence intervals are shown for for unadjusted and adjusted analyses.</p

Cohort Development.

<p>The flowchart indicates specific exclusion criteria applied in a stepwise manner to develop the final cohort for the study.</p

Comparison of Ischemic Stroke Incidence in HIV-Infected and Non–HIV-Infected Patients in a US Health Care System

BackgroundCardiovascular disease is increased among HIV-infected patients, but little is known regarding ischemic stroke rates. We sought to compare stroke rates and determine stroke risk factors in HIV-infected versus non-HIV-infected patients.MethodsAn HIV cohort and matched non-HIV comparator cohort seen between 1996 and 2009 were identified from a Boston health care system. The primary endpoint was ischemic stroke, defined using International Classification of Diseases (ICD) codes. Unadjusted stroke incidence rates were calculated. Cox proportional hazards modeling was used to determine adjusted hazard ratios (HRs).ResultsThe incidence rate of ischemic stroke was 5.27 per 1000 person-years in HIV-infected compared with 3.75 in non-HIV-infected patients, with an unadjusted HR of 1.40 [95% confidence interval (CI): 1.17 to 1.69, P &lt; 0.001]. HIV remained an independent predictor of stroke after controlling for demographics and stroke risk factors (HR: 1.21, 95% CI: 1.01 to 1.46, P = 0.043). The relative increase in stroke rates (HIV vs. non-HIV) was significantly higher in younger HIV patients (incidence rate ratio: 4.42, 95% CI: 1.56 to 11.09, age 18-29; 2.96, 1.69-4.96, age: 30-39; 1.53, 1.06-2.17, age: 40-49), and in women [HR: 2.16 (95% CI: 1.53 to 3.04) for women vs. HR: 1.18 (95% CI: 0.95 to 1.47) for men]. Among HIV patients, increased HIV RNA (HR: 1.10, 95% CI: 1.04 to 1.17, P = 0.001) was associated with an increased risk of stroke.ConclusionsStroke rates were increased among HIV-infected patients, independent of common stroke risk factors, particularly among young patients and women

Cohort Demographic and Clinical Characteristics.

<p>Cohort Demographic and Clinical Characteristics.</p