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BackgroundIncreases in multimorbidity and obesity have been noted in HIV-infected populations in the current treatment era. Patterns of multimorbid disease clustering and the impact of obesity on multimorbidity are understudied in this population.MethodsWe examined obesity and multimorbidity patterns among 1844 HIV-infected patients in the UAB 1917 Clinic. Exploratory factor analysis was used to identify the underlying factor structure responsible for clustering. Patterns among the resulting morbidity factors by body mass index (BMI) category were explored. Multivariable logistic regression models were fit to identify predictors of multimorbidity cluster patterns.ResultsThe prevalence of multimorbidity was 65% (1205/1844). Prevalence increased with progressive BMI categories from underweight (64%) to obese (79%). Three multimorbidity clusters were identified: "metabolic," including hypertension, gout, diabetes mellitus, and chronic kidney disease (range, 0.41-0.84; P < 0.001); "Behavioral," including mood disorders, dyslipidemia, chronic obstructive pulmonary disease, chronic ulcer disease, osteoarthritis, obstructive sleep apnea, and cardiac disorders (range, 0.32-0.57; P < 0.001); "Substance Use," including alcohol abuse, substance abuse, tobacco abuse, and hepatitis C (range, 0.53-0.89; P < 0.001). Obesity was associated with increased odds of multimorbidity (obese vs. normal BMI category: OR = 1.52, 95% CI: 1.15 to 2.00).ConclusionsThree patterns of disease clustering were identified. Obesity was associated with a higher likelihood of multimorbidity. The management of multimorbidity and obesity will need to be addressed in future clinical practice guidelines to enhance long-term outcomes of HIV-infected patients in the current treatment era.

BackgroundIncreases in multimorbidity and obesity have been noted in HIV-infected populations in the current treatment era. Patterns of multimorbid disease clustering and the impact of obesity on multimorbidity are understudied in this population.MethodsWe examined obesity and multimorbidity patterns among 1844 HIV-infected patients in the UAB 1917 Clinic. Exploratory factor analysis was used to identify the underlying factor structure responsible for clustering. Patterns among the resulting morbidity factors by body mass index (BMI) category were explored. Multivariable logistic regression models were fit to identify predictors of multimorbidity cluster patterns.ResultsThe prevalence of multimorbidity was 65% (1205/1844). Prevalence increased with progressive BMI categories from underweight (64%) to obese (79%). Three multimorbidity clusters were identified: "metabolic," including hypertension, gout, diabetes mellitus, and chronic kidney disease (range, 0.41-0.84; P < 0.001); "Behavioral," including mood disorders, dyslipidemia, chronic obstructive pulmonary disease, chronic ulcer disease, osteoarthritis, obstructive sleep apnea, and cardiac disorders (range, 0.32-0.57; P < 0.001); "Substance Use," including alcohol abuse, substance abuse, tobacco abuse, and hepatitis C (range, 0.53-0.89; P < 0.001). Obesity was associated with increased odds of multimorbidity (obese vs. normal BMI category: OR = 1.52, 95% CI: 1.15 to 2.00).ConclusionsThree patterns of disease clustering were identified. Obesity was associated with a higher likelihood of multimorbidity. The management of multimorbidity and obesity will need to be addressed in future clinical practice guidelines to enhance long-term outcomes of HIV-infected patients in the current treatment era.

BackgroundCooccurring pain, mood disorders, and substance abuse are common in HIV-infected patients. Our objective was to investigate the relationship between pain, alone and in the context of mood disorders and substance abuse, on clinic utilization, antiretroviral therapy adherence, and virologic suppression.MethodsPain, mood disorders, and substance abuse were assessed at the first visit. No-show and urgent visits were measured over a 1-year period. Models were adjusted for age, race, sex, insurance status, CD4(+) T-lymphocyte count, and HIV risk factor.ResultsAmong 1521 participants, 509 (34%) reported pain, 239 (16%) had pain alone, 189 (13%) had pain and a mood disorder, and 30 (2%) had pain and substance abuse. In univariate models, participants with pain, mood disorders, and substance abuse had higher odds of a no-show visit than those without these conditions [odds ratio (OR), 1.4; 95% confidence interval (CI), 1.1-1.8; OR, 1.5; 95% CI, 1.2-1.9; OR, 2.0; 95% CI, 1.4-2.8, respectively]. In the multivariable model, pain increased the odds of a no-show visit only in participants without substance abuse (OR, 1.5; 95% CI, 1.1-1.9) and pain reduced the odds of a no-show visit in participants with substance abuse (OR, 0.5; 95% CI, 0.2-0.9; P for interaction = 0.0022).ConclusionsIn this study, pain increased the odds of no-show visits but only for participants without substance abuse. Because pain, mood disorders, and substance abuse are highly prevalent in HIV-infected patients, our findings have implications for HIV treatment success. Interventions that incorporate pain management may be important for improving health outcomes in patients living with HIV infection.

BackgroundCooccurring pain, mood disorders, and substance abuse are common in HIV-infected patients. Our objective was to investigate the relationship between pain, alone and in the context of mood disorders and substance abuse, on clinic utilization, antiretroviral therapy adherence, and virologic suppression.MethodsPain, mood disorders, and substance abuse were assessed at the first visit. No-show and urgent visits were measured over a 1-year period. Models were adjusted for age, race, sex, insurance status, CD4(+) T-lymphocyte count, and HIV risk factor.ResultsAmong 1521 participants, 509 (34%) reported pain, 239 (16%) had pain alone, 189 (13%) had pain and a mood disorder, and 30 (2%) had pain and substance abuse. In univariate models, participants with pain, mood disorders, and substance abuse had higher odds of a no-show visit than those without these conditions [odds ratio (OR), 1.4; 95% confidence interval (CI), 1.1-1.8; OR, 1.5; 95% CI, 1.2-1.9; OR, 2.0; 95% CI, 1.4-2.8, respectively]. In the multivariable model, pain increased the odds of a no-show visit only in participants without substance abuse (OR, 1.5; 95% CI, 1.1-1.9) and pain reduced the odds of a no-show visit in participants with substance abuse (OR, 0.5; 95% CI, 0.2-0.9; P for interaction = 0.0022).ConclusionsIn this study, pain increased the odds of no-show visits but only for participants without substance abuse. Because pain, mood disorders, and substance abuse are highly prevalent in HIV-infected patients, our findings have implications for HIV treatment success. Interventions that incorporate pain management may be important for improving health outcomes in patients living with HIV infection.

Abstract We assessed CD4 count at initial presentation for HIV care among ≥50-year-olds from 1997-2007 in 13 US and Canadian clinical cohorts and compared to

BACKGROUND. Initiatives to improve early detection and access to human immunodeficiency virus (HIV) services have increased over time. We assessed the immune status of patients at initial presentation for HIV care from 1997 to 2007 in 13 US and Canadian clinical cohorts. METHODS. We analyzed data from 44,491 HIV-infected patients enrolled in the North American-AIDS Cohort Collaboration on Research and Design. We identified first presentation for HIV care as the time of first CD4(+) T lymphocyte (CD4) count and excluded patients who prior to this date had HIV RNA measurements, evidence of antiretroviral exposure, or a history of AIDS-defining illness. Trends in mean CD4 count (measured as cells/mm(3)) and 95% confidence intervals were determined using linear regression adjusted for age, sex, race/ethnicity, HIV transmission risk, and cohort. RESULTS. Median age at first presentation for HIV care increased over time (range, 40-43 years; P < .01), whereas the percentage of patients with injection drug use HIV transmission risk decreased (from 26% to 14%; P < .01) and heterosexual transmission risk increased (from 16% to 23%; P < .01). Median CD4 count at presentation increased from 256 cells/mm(3) (interquartile range, 96-455 cells/mm(3)) to 317 cells/mm(3) (interquartile range, 135-517 cells/mm(3)) from 1997 to 2007 (P < .01). The percentage of patients with a CD4 count > or = 350 cells/mm(3) at first presentation also increased from 1997 to 2007 (from 38% to 46%; P < .01). The estimated adjusted mean CD4 count increased at a rate of 6 cells/mm(3) per year (95% confidence interval, 5-7 cells/mm(3) per year). CONCLUSION. CD4 count at first presentation for HIV care has increased annually over the past 11 years but has remained

Introduction: HIV-1 infection leads to chronic inflammation and to an increased risk of non-AIDS mortality. Our objective was to determine whether AIDS-defining events (ADEs) were associated with increased overall and cause-specific non-AIDS related mortality after antiretroviral therapy (ART) initiation. Methods: We included HIV treatment-naive adults from the Antiretroviral Therapy Cohort Collaboration (ART-CC) who initiated ART from 1996 to 2014. Causes of death were assigned using the Coding Causes of Death in HIV (CoDe) protocol. The adjusted hazard ratio (aHR) for overall and cause-specific non-AIDS mortality among those with an ADE (all ADEs, tuberculosis (TB), Pneumocystis jiroveci pneumonia (PJP), and non-Hodgkin's lymphoma (NHL)) compared to those without an ADE was estimated using a marginal structural model. Results: The adjusted hazard of overall non-AIDS mortality was higher among those with any ADE compared to those without any ADE (aHR 2.21, 95% confidence interval (CI) 2.00 to 2.43). The adjusted hazard of each of the cause-specific non-AIDS related deaths were higher among those with any ADE compared to those without, except metabolic deaths (malignancy aHR 2.59 (95% CI 2.13 to 3.14), accident/suicide/overdose aHR 1.37 (95% CI 1.05 to 1.79), cardiovascular aHR 1.95 (95% CI 1.54 to 2.48), infection aHR (95% CI 1.68 to 2.81), hepatic aHR 2.09 (95% CI 1.61 to 2.72), respiratory aHR 4.28 (95% CI 2.67 to 6.88), renal aHR 5.81 (95% CI 2.69 to 12.56) and central nervous aHR 1.53 (95% CI 1.18 to 5.44)). The risk of overall and cause-specific non-AIDS mortality differed depending on the specific ADE of interest (TB, PJP, NHL). Conclusions: In this large multi-centre cohort collaboration with standardized assignment of causes of death, non-AIDS mortality was twice as high among patients with an ADE compared to without an ADE. However, non-AIDS related mortality after an ADE depended on the ADE of interest. Although there may be unmeasured confounders, these findings suggest that a common pathway may be independently driving both ADEs and NADE mortality. While prevention of ADEs may reduce subsequent death due to NADEs following ART initiation, modification of risk factors for NADE mortality remains important after ADE survival. Keywords: AIDS-defining events; non-AIDS mortality; tuberculosis; Pneumocystis jiroveci pneumonia; non-Hodgkin's lymphoma; marginal structural model, 1 | INTRODUCTION In the era of antiretroviral therapy (ART), there have been striking decreases in acquired immune deficiency syndrome (AIDS)-related mortality [1-3] and prolongation of life expectancy [4-7] for [...]