Objectives To define the incidence and risk factors for methicillin resistant Staphylococcus aureus (MRSA) bacteraemia in an HIV‐infected population. Methods From January 1, 2000 to December 31, 2004, we conducted a retrospective cohort study. We identified all cases of Staphylococcus aureus bacteraemia (SAB), including MRSA, among patients enrolled in the Johns Hopkins Hospital out‐patient HIV clinic. A conditional logistic regression model was used to identify risk factors for MRSA bacteraemia compared with methicillin‐sensitive SAB and no bacteraemia in unmatched (1:1) and matched (1:4) nested case‐control analyses, respectively. Results Of 4607 patients followed for a total of 11 020 person‐years (PY) of follow‐up, 216 episodes of SAB occurred (incidence: 19.6 cases per 1000 PY), including 94 cases (43.5%) which were methicillin‐resistant. The incidence of MRSA bacteraemia increased from 5.3 per 1000 PY in 2000–2001 to 11.9 per 1000 PY in 2003–2004 (P=0.001). Multivariate analysis demonstrated that independent predictors of MRSA bacteraemia (vs. no bacteraemia) were injection drug use (IDU), end‐stage renal disease (ESRD) and CD4 count <200 cells/μL. Conclusions MRSA bacteraemia was an increasingly common diagnosis in our HIV‐infected cohort, especially in patients with history of IDU, low CD4 cell count and ESRD.
Five factors have been shown to influence the 20-fold variation of fetal hemoglobin fHb F) levels in sickle cell anemia (SS): age, sex, the a-globin gene number, @-globin haplotypes, and an X-linked locus that regulates the production of Hb F-containing erythrocytes (F cells), ie, the F-cell production (FCP) locus. To determine the relative importance of these factors, we studied 257 Jamaican SS subjects from a Cohort group identified by newborn screening and from a Sib Pair study. Linear regression analyses showed that each variable, when analyzed alone, had a significant association with Hb F levels ( P c .05). Multiple regression analysis, including all variables, showed that the FCP locus is the
ObjectiveTo estimate the rate of combination antiretroviral treatment change and factors associated with combination antiretroviral treatment change among patients recruited in the Australian HIV Observational Database (AHOD). MethodsAnalyses were based on patients in the AHOD who had commenced combination antiretroviral treatment after 1 January 1997. Combination antiretroviral treatment change was de®ned as the addition or change of at least one antiretroviral drug. A random-effect Poisson regression model was used to assess factors associated with increased rates of combination antiretroviral treatment change. ResultsA total of 596 patients in the AHOD were included in the analysis, with a median follow-up of 2.3 years. The overall rate of antiretroviral treatment change in this group was 0.45 combinations per year. In a multivariate analysis, a low CD4 count (, 200 cells/mL) at baseline was associated with an increased rate of treatment change [rate ratio (RR) 1.43; 95% con®dence interval (CI), 1.13, 1.80; P 0.003)]. Combinations including a nonnucleoside reverse transcriptase inhibitor were also associated with slower rates of change than treatment combinations including a protease inhibitor (RR 0.64, 95% CI, 0.51, 0.80, P , 0.001). ConclusionInitiating combination antiretroviral at a CD4 cell count , 200 cells/mL may be associated with poorer patient outcomes. However, the possibility that clinician or patient concerns about low immunological status led to faster rates of treatment change in this group cannot be discounted.
Introduction Risk adjusted thirty-day hospital readmission rate is a commonly used benchmark for hospital quality of care and for Medicare reimbursement. Persons living with HIV (PLWH) may have high readmission rates. This study compared 30-day readmission rates by HIV status in a multi-state sample with planned subgroup comparisons by insurance and diagnostic categories. Methods Data for all acute care, non-military hospitalizations in 9 states in 2011 were obtained from the Healthcare Costs and Utilization Project. The primary outcome was readmission for any cause within 30 days of hospital discharge. Factors associated with readmission were evaluated using multivariate logistic regression. Results 5,484,245 persons, including 33,556 (0.6%) PLWH, had a total of 6,441,695 index hospitalizations, including 45,382 (0.7%) among PLWH. Unadjusted readmission rates for hospitalizations of HIV-uninfected persons and PLWH were 11.2% (95% CI: 11.2, 11.2) and 19.7% (19.3, 20.0), respectively. After adjustment for age, gender, race, insurance, and diagnostic category, HIV was associated with 1.50 (1.46, 1.54) times higher odds of readmission. Predicted, adjusted readmission rates were higher for PLWH within every insurance category, including Medicaid (12.9% [12.8, 13.0] and 19.1% [18.4, 19.7] for HIV-uninfected persons and PLWH, respectively) and Medicare (13.2% [13.1, 13.3] and 18.0% [17.4, 18.7], respectively) and within every diagnostic category. Discussion HIV is associated with significantly increased readmission risk independent of demographics, insurance, and diagnostic category. The 19.7% 30-day readmission rate may serve as a preliminary benchmark for assessing quality of care of PLWH. Policymakers may consider adjusting for HIV when calculating a hospital’s expected readmission rate.
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