Risk factors for death in HIV-infected adult african patients recieving anti-retroviral therapy

Objective: To determine risk factors for death in HIV-infected African patients on anti-retroviral therapy (ART).Design: Retrospective Case-control study.Setting: The MOH-USAID-AMPATH Partnership ambulatory HIV-care clinics in western Kenya.Results: Between November 2001 and December 2005 demographic, clinical and laboratory data from 527 deceased and 1054 living patients receiving ART were compared to determine independent risk factors for death. Median age at ART initiation was 38 versus 36 years for the deceased and living patients respectively (p<0.0148). Mediantime from enrollment at AMPATH to initiation of ART was two weeks for both groups while median time on ART was eight weeks for the deceased and fourty two weeks for the living (p<0.0001). Patients with CD4 cell counts <100/mm3 were more likely to die than those with counts >100/mm3 (HR=1.553. 95% CI (1.156, 2.087), p<0.003). Patientsattending rural clinics had threefold higher risk of dying compared to patients attending clinic at a tertiary referral hospital (p<0.0001). Two years after initiating treatment fifty percent of non-adherent patients were alive compared to 75% of adherent patients. Male gender, WHO Stage and haemoglobin level <10 grams% were associated with time to death while age, marital status, educational level, employment status andweight were not.Conclusion: Profoundly immunosuppressed patients were more likely to die early in the course of treatment. Also, patients receiving care in rural clinics were at greater risk of dying than those receiving care in the tertiary referral hospital

Impact of the Kenya post-election crisis on clinic attendance and medication adherence for HIV-infected children in western Kenya

<p>Abstract</p> <p>Background</p> <p>Kenya experienced a political and humanitarian crisis following presidential elections on 27 December 2007. Over 1,200 people were killed and 300,000 displaced, with disproportionate violence in western Kenya. We sought to describe the immediate impact of this conflict on return to clinic and medication adherence for HIV-infected children cared for within the USAID-Academic Model Providing Access to Healthcare (AMPATH) in western Kenya.</p> <p>Methods</p> <p>We conducted a mixed methods analysis that included a retrospective cohort analysis, as well as key informant interviews with pediatric healthcare providers. Eligible patients were HIV-infected children, less than 14 years of age, seen in the AMPATH HIV clinic system between 26 October 2007 and 25 December 2007. We extracted demographic and clinical data, generating descriptive statistics for pre- and post-conflict antiretroviral therapy (ART) adherence and post-election return to clinic for this cohort. ART adherence was derived from caregiver-report of taking all ART doses in past 7 days. We used multivariable logistic regression to assess factors associated with not returning to clinic. Interview dialogue from was analyzed using constant comparison, progressive coding and triangulation.</p> <p>Results</p> <p>Between 26 October 2007 and 25 December 2007, 2,585 HIV-infected children (including 1,642 on ART) were seen. During 26 December 2007 to 15 April 2008, 93% (N = 2,398) returned to care. At their first visit after the election, 95% of children on ART (N = 1,408) reported perfect ART adherence, a significant drop from 98% pre-election (p < 0.001). Children on ART were significantly more likely to return to clinic than those not on ART. Members of tribes targeted by violence and members of minority tribes were less likely to return. In qualitative analysis of 9 key informant interviews, prominent barriers to return to clinic and adherence included concerns for personal safety, shortages of resources, hanging priorities, and hopelessness.</p> <p>Conclusion</p> <p>During a period of humanitarian crisis, the vulnerable, HIV-infected pediatric population had disruptions in clinical care and in medication adherence, putting children at risk for viral resistance and increased morbidity. However, unique program strengths may have minimized these disruptions.</p

Sampling-Based Approaches to Improve Estimation of Mortality among Patient Dropouts: Experience from a Large PEPFAR-Funded Program in Western Kenya

Monitoring and evaluation (M&E) of HIV care and treatment programs is impacted by losses to follow-up (LTFU) in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices.In a large antiretroviral therapy (ART) program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003), and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020), with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001) and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001). Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001). Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%), revised to 2.8% (2.3%-3.1%) when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6%) and 9.9% (8.4%-11.5%) through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%), 3.4% (2.9%-4.0%), 10.5% (8.7%-12.3%) and 10.7% (8.9%-12.6%) respectively. CONCLUSIONS/SIGNIFICANCE ABSTRACT: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large HIV care and treatment programs

Correcting Mortality for Loss to Follow-Up: A Nomogram Applied to Antiretroviral Treatment Programmes in Sub-Saharan Africa

Matthias Egger and colleagues present a nomogram and a web-based calculator to correct estimates of program-level mortality for loss to follow-up, for use in antiretroviral treatment programs