Mortality among people with human immunodeficiency virus (HIV) infection is increasingly due to non-communicable causes. This has been observed mostly in developed countries and the routine care of HIV infected individuals has now expanded to include attention to cardiovascular risk factors. Cardiovascular risk factors such as high blood pressure are often overlooked among HIV seropositive (+) individuals in sub-Saharan Africa. We aimed to determine the effect of blood pressure on mortality among HIV+ adults in Kenya.
We performed a retrospective analysis of electronic medical records of a large HIV treatment program in western Kenya between 2005 and 2010. All included individuals were HIV+. We excluded participants with AIDS, who were <16 or >80 years old, or had data out of acceptable ranges. Missing data for key covariates was addressed by inverse probability weighting. Primary outcome measures were crude mortality rate and mortality hazard ratio (HR) using Cox proportional hazards models adjusted for potential confounders including HIV stage.
There were 49,475 (74% women) HIV+ individuals who met inclusion and exclusion criteria. Mortality rates for men and women were 3.8 and 1.8/100 person-years, respectively, and highest among those with the lowest blood pressures. Low blood pressure was associated with the highest mortality incidence rate (IR) (systolic <100 mmHg IR 5.2 [4.8-5.7]; diastolic <60 mmHg IR 9.2 [8.3-10.2]). Mortality rate among men with high systolic blood pressure without advanced HIV (3.0, 95% CI: 1.6-5.5) was higher than men with normal systolic blood pressure (1.1, 95% CI: 0.7-1.7). In weighted proportional hazards regression models, men without advanced HIV disease and systolic blood pressure ≥140 mmHg carried a higher mortality risk than normotensive men (HR: 2.39, 95% CI: 0.94-6.08).
Although there has been little attention paid to high blood pressure among HIV+ Africans, we show that blood pressure level among HIV+ patients in Kenya is related to mortality. Low blood pressure carries the highest mortality risk. High systolic blood pressure is associated with mortality among patients whose disease is not advanced. Further investigation is needed into the cause of death for such patients.
Blood pressure; HIV; Mortality; Global health; sub-Saharan Africa
Hypertension is the leading global risk factor for mortality. Hypertension treatment and control rates are low worldwide, and delays in seeking care are associated with increased mortality. Thus, a critical component of hypertension management is to optimize linkage and retention to care.
This study investigates whether community health workers, equipped with a tailored behavioral communication strategy and smartphone technology, can increase linkage and retention of hypertensive individuals to a hypertension care program and significantly reduce blood pressure among them. The study will be conducted in the Kosirai and Turbo Divisions of western Kenya. An initial phase of qualitative inquiry will assess facilitators and barriers of linkage and retention to care using a modified Health Belief Model as a conceptual framework. Subsequently, we will conduct a cluster randomized controlled trial with three arms: 1) usual care (community health workers with the standard level of hypertension care training); 2) community health workers with an additional tailored behavioral communication strategy; and 3) community health workers with a tailored behavioral communication strategy who are also equipped with smartphone technology. The co-primary outcome measures are: 1) linkage to hypertension care, and 2) one-year change in systolic blood pressure among hypertensive individuals. Cost-effectiveness analysis will be conducted in terms of costs per unit decrease in blood pressure and costs per disability-adjusted life year gained.
This study will provide evidence regarding the effectiveness and cost-effectiveness of strategies to optimize linkage and retention to hypertension care that can be applicable to non-communicable disease management in low- and middle-income countries.
This trial is registered with (NCT01844596) on 30 April 2013.
Hypertension; Linkage to care; Retention in care; Community health workers; Tailored behavioral communication; Smartphone technology; Cost-effectiveness
The World Health Organization (WHO) guidelines for monitoring the effectiveness of HIV treatment in resource-limited settings (RLS) are mostly based on clinical and immunological markers (e.g., CD4 cell counts). Recent research indicates that the guidelines are inadequate and can result in high error rates. Viral load (VL) is considered the “gold standard”, yet its widespread use is limited by cost and infrastructure. In this paper, we propose a diagnostic algorithm that uses information from routinely-collected clinical and immunological markers to guide a selective use of VL testing for diagnosing HIV treatment failure, under the assumption that VL testing is available only at a certain portion of patient visits. Our algorithm identifies the patient sub-population, such that the use of limited VL testing on them minimizes a pre-defined risk (e.g., misdiagnosis error rate). Diagnostic properties of our proposal algorithm are assessed by simulations. For illustration, data from the Miriam Hospital Immunology Clinic (RI, USA) are analyzed.
Antiretroviral failure; constrained optimization; HIV/AIDS; resource limited; ROC; tripartite classification
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects through a mediator in the setting of a continuous mediator and a binary response. Several conditional independence assumptions are introduced (with corresponding sensitivity parameters) to make these effects identifiable from the observed data. We suggest strategies for eliciting sensitivity parameters and conduct simulations to assess violations to the assumptions. This approach is used to assess mediation in a recent weight management clinical trial.
Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802 PR and 44,432 RT sequences) from the published literature (http://hivdb.Stanford.edu). Nucleic acid sequences are read into SQUAT, identified, aligned, and translated. Nucleic acid sequences are flagged if with >five 1–2-base insertions; >one 3-base insertion; >one deletion; >six PR or >18 RT ambiguous bases; >three consecutive PR or >four RT nucleic acid mutations; >zero stop codons; >three PR or >six RT ambiguous amino acids; >three consecutive PR or >four RT amino acid mutations; >zero unique amino acids; or <0.5% or >15% genetic distance from another submitted sequence. Thresholds are user modifiable. SQUAT output includes a summary report with detailed comments for troubleshooting of flagged sequences, histograms of pairwise genetic distances, neighbor joining phylogenetic trees, and aligned nucleic and amino acid sequences. SQUAT is a stand-alone, free, web-independent tool to ensure use of high-quality HIV PR/RT sequences in interpretation and reporting of drug resistance, while increasing awareness and expertise and facilitating troubleshooting of potentially problematic sequences.
HIV-1 sequence diversity can affect host immune responses and phenotypic characteristics such as antiretroviral drug resistance. Current HIV-1 sequence diversity classification uses phylogeny-based methods to identify subtypes and recombinants, which may overlook distinct subpopulations within subtypes. While local epidemic studies have characterized sequence-level clustering within subtypes using phylogeny, identification of new genotype – phenotype associations are based on mutational correlations at individual sequence positions. We perform a systematic, global analysis of position-specific pol gene sequence variation across geographic regions within HIV-1 subtypes to characterize subpopulation differences that may be missed by standard subtyping methods and sequence-level phylogenetic clustering analyses.
Materials & methods
Analysis was performed on a large, globally diverse, cross-sectional pol sequence dataset. Sequences were partitioned into subtypes and geographic subpopulations within subtypes. For each subtype, we identified positions that varied according to geography using VESPA (viral epidemiology signature pattern analysis) to identify sequence signature differences and a likelihood ratio test adjusted for multiple comparisons to characterize differences in amino acid (AA) frequencies, including minority mutations. Synonymous nonsynonymous analysis program (SNAP) was used to explore the role of evolutionary selection witihin subtype C.
In 7693 protease (PR) and reverse transcriptase (RT) sequences from untreated patients in multiple geographic regions, 11 PR and 11 RT positions exhibited sequence signature differences within subtypes. Thirty six PR and 80 RT positions exhibited within-subtype geography-dependent differences in AA distributions, including minority mutations, at both conserved and variable loci. Among subtype C samples from India and South Africa, nine PR and nine RT positions had significantly different AA distributions, including one PR and five RT positions that differed in consensus AA between regions. A selection analysis of subtype C using SNAP demonstrated that estimated rates of nonsynonymous and synonymous mutations are consistent with the possibility of positive selection across geographic subpopulations within subtypes.
We characterized systematic genotypic pol differences across geographic regions within subtypes that are not captured by the subtyping nomenclature. Awareness of such differences may improve the interpretation of future studies determining the phenotypic consequences of genetic backgrounds.
geography; HIV-1; pol gene sequences; protease; reverse transcriptase; subtyping
Dual epidemics of HIV and alcohol use disorders, and a dearth of professional resources for behavioral treatment in sub-Saharan Africa, suggest the need for development of culturally relevant and feasible interventions. The purpose of this study was to test the preliminary efficacy of a culturally adapted 6-session gender-stratified group cognitive-behavioral therapy (CBT) intervention delivered by paraprofessionals to reduce alcohol use among HIV-infected outpatients in Eldoret, Kenya.
Randomized clinical trial comparing CBT against a usual care assessment only control
A large HIV outpatient clinic in Eldoret, Kenya, part of the Academic Model for Providing Access to Healthcare collaboration
75 HIV-infected outpatients who were antiretroviral (ARV)-initiated or ARV-eligible and who reported hazardous or binge drinking
Percent drinking days (PDD) and mean drinks per drinking days (DDD) measured continuously using the Timeline Followback
There were 299 ineligible and 102 eligible outpatients with 12 refusals. Effect sizes of the change in alcohol use since baseline between the two conditions at the 30-day follow-up were large (d=.95, p=.0002, mean difference=24.93 (95% CI: 12.43, 37.43) PDD; d=.76, p=.002, mean difference=2.88 (95% CI: 1.05, 4.70) DDD). Randomized participants attended 93% of the 6 CBT sessions offered. Reported alcohol abstinence at the 90-day follow-up was 69.4% (CBT) and 37.5% (usual care). Paraprofessional counselors achieved independent ratings of adherence and competence equivalent to college-educated therapists in the U.S. Treatment effect sizes were comparable to alcohol intervention studies conducted in the U.S.
Cognitive-behavioral therapy can be successfully adapted to group paraprofessional delivery in Kenya and may be effective in reducing alcohol use among HIV-infected Kenyan outpatients.
This study examined the association between recent trends in CD4 and viral loads and cognitive test performance with the expectation that recent history could predict cognitive performance. Eighty-three human immunodeficiency virus (HIV)-infected patients with a mean CD4 count of 428 copies/ml were examined in this study (62% with undetectable plasma viral load [PVL]). We investigated the relationships between nadir CD4 cell count, 1-year trends in immunologic function/PVLs, and cognitive performance across several domains using linear regression models. Nadir CD4 cell count was predictive of current executive function (p = .004). One year clinical history for CD4 cell counts and/or PVLs were predictive of executive function, attention/working memory, and learning/memory measures (p < .05). Models that combined recent clinical history trends and nadir CD4 cell counts suggested that recent clinical trends were more important in predicting current cognitive performance for all domains except executive function. This research suggests that recent CD4 and viral load history is an important predictor of current cognitive function across several cognitive domains. If validated, clinical variables and cognitive dysfunction models may improve our understanding of the dynamic relationships between disease evolution and progression and CNS involvement.
HIV; Cognition; Neuropsychology; Executive function; Recent clinical history
Some prenatal factors may program an offspring's blood pressure, but existing evidence is inconclusive and mechanisms remain unclear. We examined the mediating roles of intrauterine and childhood growth in the associations between childhood systolic blood pressure (SBP) and 5 potentially modifiable prenatal factors: maternal smoking during pregnancy; prepregnancy BMI; pregnancy weight gain; chronic hypertension; and preeclampsia-eclampsia.
The sample contained 30 461 mother-child pairs in the Collaborative Perinatal Project. Prenatal data were extracted from obstetric forms, and children's SBP was measured at 7 years of age. Potential mediation by intrauterine growth restriction (IUGR) and childhood growth was examined by the causal step method.
Heavy maternal smoking during pregnancy was significantly associated with higher offspring SBP (adjusted mean difference versus nonsmoking: 0.73 mm Hg [95% confidence interval (CI): 0.32–1.14]), which attenuated to null (0.13 [95% CI: −0.27–0.54]) after adjustment for changes in BMI from birth to 7 years of age. Prepregnancy overweight-obesity was significantly associated with higher offspring SBP (versus normal weight: 0.89 mm Hg [95% CI: 0.52–1.26]), which also attenuated to null (−0.04 mm Hg [95% CI: −0.40–0.31]) after adjustment for childhood BMI trajectory. Adjustment for BMI trajectory augmented the association between maternal pregnancy weight gain and offspring SBP. Adjustment for childhood weight trajectory similarly changed these associations. However, all these associations were independent of IUGR.
Childhood BMI and weight trajectory, but not IUGR, may largely mediate the associations of maternal smoking during pregnancy and prepregnancy BMI with an offspring's SBP.
blood pressure; pregnancy; fetal development; infant; small for gestational age; child development; obesity
We tested hypotheses that disproportionately large placental size and vascular lesions were associated with high systolic blood pressure (SBP); and these associations might be more evident with age. The sample included 13,273 out of 40,666 full-term singletons in the Collaborative Perinatal Project. Placentas were examined by pathologists blinded of pregnancy courses and outcomes. The 4-month and 7-year SBP were measured with palpation and auscultation methods, respectively. We found that placental weight (adjusted mean difference corresponding to an increase by 1 standard deviation, 0.50 [95% confidence interval, 0.33 to 0.68]) and placenta-fetus weight ratio (0.37 [95% CI, 0.19 to 0.54]) was positively associated with 7-year SBP, but not associated with 4-month SBP. Placental largest and smallest diameters, and area were negatively associated with 4-month SBP, but positively with 7-year SBP. Placental thickness was negatively associated with 4-month SBP only. Placental volume was negatively associated with 4-month SBP (−0.60 [95% CI, −0.85 to −0.35]), but positively associated with 7-year SBP (0.48 [95% CI, 0.30 to 0.67]). Thrombi in cord vessels (adjusted mean difference vs absence, 2.73 [95% CI, −0.03 to 5.50]) and decidual vessels (2.58 [95% CI, 0.24 to 4.91]), villous microinfarcts (1.63 [95% CI, 0.71 to 2.55]), necrosis at the decidual margin (1.57 [95% CI, 0.54 to 2.59]) and basalis (3.44 [95% CI, 1.55 to 5.32]) were associated with higher 4-month SBP only. We conclude that placental inefficiency, reflected by disproportionately large weight and size, predicts long-term blood pressure, while vascular resistance and lesions may only influence short-term blood pressure.
placenta; placental insufficiency; placental circulation; fetal development; blood pressure
The objective of this study was to elucidate factors that predicted the initiation of HIV postexposure prophylaxis (PEP) for blood or body fluid exposures evaluated at Rhode Island emergency departments (EDs). The study involved a retrospective review of patient visits to all civilian Rhode Island EDs for these exposures from 1995 to mid-2001. Multivariate logistic regression models were created to evaluate predictors of the offering and the acceptance and receipt of HIV PEP from 1996 to 2001. The search identified 3622 patients who sustained a blood or body fluid exposure. Of these, 43.8% were health care workers (HCWs) and 57.2% were not HCWs. Most (52.0%) of the exposures were nonsexual. HIV PEP was offered to 21.0% and accepted and received by 9.4% of all patients. HIV PEP was offered more often after significant exposures, exposures to known HIV-infected sources, when time elapsed after the exposure was shorter, if the patients were HCWs, adults, presented to a teaching hospital, presented during the latter years of the study, or sustained nonsexual exposures. Once offered HIV PEP, patients who were male, adult, sustained a significant exposure, knew the source was HIV infected, sustained a nonsexual exposure, or were HCWs had a greater odds of accepting and receiving HIV PEP. Even when controlling for exposure significance, HIV status, and time elapsed since the exposure, several factors such as gender and type of hospital that are unrelated to the exposure appeared to influence the initiation of HIV PEP. ED providers should ensure that these factors do not inappropriately restrict its initiation.
There is increased risk of cardiovascular disease among HIV seropositive individuals. The prevalence of HIV is highest in sub-Saharan Africa; however, HIV-related cardiovascular risk research is largely derived from developed country settings. Herein, we describe the prevalence of hypertension and obesity in a large HIV treatment program in Kenya.
We performed a retrospective analysis of the electronic medical records of a large HIV treatment program in Western Kenya between 2006 and 2009. We calculated the prevalence of hypertension and obesity among HIV+ adults as well as utilized multiple logistic regression analyses to examine the relationship between clinical characteristics, HIV-related characteristics, and hypertension.
Our final sample size was 12,194. The median systolic/diastolic blood pressures were similar for both sexes (male: 110/70 mmHg, female: 110/70 mmHg). The prevalence of hypertension among men and women were 11.2% and 7.4%, respectively. Eleven percent of men and 22.6% of women were overweight/obese (body mass index ≥25 kg/m2). Ordinal logistic regression analyses showed that overweight/obesity was more strongly associated with hypertension among HIV+ men (OR 2.41, 95% CI 1.88–3.09) than a higher successive age category (OR 1.62, 95% CI 1.40–1.87 comparing 16–35, 36–45 and >45 years categories). Among women, higher age category and overweight/obesity were most strongly associated with hypertension (age category: OR 2.21, 95% CI 1.95–2.50, overweight/obesity: OR 1.80, 95% CI 1.50–2.16). Length of time on protease inhibitors was not found to be related to hypertension for men (OR 1.62, 95% CI 0.42–6.20) or women (OR 1.17, 95% CI 0.37–2.65) after adjustment for CD4 count, age and BMI.
In Western Kenya, there is a high prevalence of hypertension and overweight/obesity among HIV+ patients with differences observed between men and women. The care of HIV+ patients in sub-Saharan Africa should also include both identification and management of associated cardiovascular risk factors.
Dropout is a common occurrence in longitudinal studies. Building upon the pattern-mixture modeling approach within the Bayesian paradigm, we propose a general framework of varying-coefficient models for longitudinal data with informative dropout, where measurement times can be irregular and dropout can occur at any point in continuous time (not just at observation times) together with administrative censoring. Specifically, we assume that the longitudinal outcome process depends on the dropout process through its model parameters. The unconditional distribution of the repeated measures is a mixture over the dropout (administrative censoring) time distribution, and the continuous dropout time distribution with administrative censoring is left completely unspecified. We use Markov chain Monte Carlo to sample from the posterior distribution of the repeated measures given the dropout (administrative censoring) times; Bayesian bootstrapping on the observed dropout (administrative censoring) times is carried out to obtain marginal covariate effects. We illustrate the proposed framework using data from a longitudinal study of depression in HIV-infected women; the strategy for sensitivity analysis on unverifiable assumption is also demonstrated.
HIV/AIDS; Missing data; Nonparametric regression; Penalized splines
Longitudinal studies with binary repeated measures are widespread in biomedical research. Marginal regression approaches for balanced binary data are well developed, while for binary process data, where measurement times are irregular and may differ by individuals, likelihood-based methods for marginal regression analysis are less well developed. In this article, we develop a Bayesian regression model for analyzing longitudinal binary process data, with emphasis on dealing with missingness. We focus on the settings where data are missing at random, which require a correctly specified joint distribution for the repeated measures in order to draw valid likelihood-based inference about the marginal mean. To provide maximum flexibility, the proposed model specifies both the marginal mean and serial dependence structures using nonparametric smooth functions. Serial dependence is allowed to depend on the time lag between adjacent outcomes as well as other relevant covariates. Inference is fully Bayesian. Using simulations, we show that adequate modeling of the serial dependence structure is necessary for valid inference of the marginal mean when the binary process data are missing at random. Longitudinal viral load data from the HIV Epidemiology Research Study (HERS) are analyzed for illustration.
Repeated measures; Marginal model; Nonparametric regression; Penalized splines; HIV/AIDS; Antiviral treatment
The analysis of longitudinal repeated measures data is frequently complicated by missing data due to informative dropout. We describe a mixture model for joint distribution for longitudinal repeated measures, where the dropout distribution may be continuous and the dependence between response and dropout is semiparametric. Specifically, we assume that responses follow a varying coefficient random effects model conditional on dropout time, where the regression coefficients depend on dropout time through unspecified nonparametric functions that are estimated using step functions when dropout time is discrete (e.g., for panel data) and using smoothing splines when dropout time is continuous. Inference under the proposed semiparametric model is hence more robust than the parametric conditional linear model. The unconditional distribution of the repeated measures is a mixture over the dropout distribution. We show that estimation in the semiparametric varying coefficient mixture model can proceed by fitting a parametric mixed effects model and can be carried out on standard software platforms such as SAS. The model is used to analyze data from a recent AIDS clinical trial and its performance is evaluated using simulations.
Clinical trials; Equivalence trial; Linear mixed model; Missing data; Nonignorable dropout; Pattern-mixture model; Pediatric AIDS; Selection bias; Smoothing splines