The objective of this study was to estimate the prevalence of and risk factors for clinical lipodystrophy (LD) and metabolic disorders in human immunodeficiency virus (HIV) type 1-infected patients. A cross-sectional survey of the Aquitaine Cohort was performed in January 1999. The clinical diagnosis of LD was categorized as fat wasting (FW), peripheral fat accumulation (FA), and mixed syndromes (MS). Of the 581 patients studied, 61% were treated with protease inhibitors. The overall prevalence of LD was 38% (95% confidence interval [CI], 32-42): prevalence of FW was 16% (95% CI, 13-18); of FA, 12% (95% CI, 10-15); and of MS, 10% (95% CI, 8-13). The prevalences of metabolic abnormalities were 49% (95% CI, 44-53) for lipid disorders and 20% (95% CI, 17-23), for glucose disorders. Factors associated with LD were age (for FW and MS), male sex (for FW), AIDS stage (for MS), body mass index (for FW and FA), waist-to-hip ratio (for FA and MS), and duration of antiretroviral treatment (for FW).

Hepatic cytolysis is more frequent among patients treated with HAART than with two NRTIs. Hepatitis B and C are the major risk factors after initiation of HAART or treatment with NRTIs. Co-infections with hepatitis B virus or hepatitis C virus may modify the management of HIV-infected patients treated by HAART.

BackgroundOur objective was to limit the burden of data collection for Quality Indicators (QIs) based on medical records.MethodsThe study was supervised by the COMPAQH project. Four QIs based on medical records were tested: medical record conformity; traceability of pain assessment; screening for nutritional disorders; time elapsed before sending copy of discharge letter to the general practitioner. Data were collected by 6 Clinical Research Assistants (CRAs) in a panel of 36 volunteer hospitals and analyzed by COMPAQH. To limit the burden of data collection, we used the same sample of medical records for all 4 QIs, limited sample size to 80 medical records, and built a composite score of only 10 items to assess medical record completeness. We assessed QI feasibility by completing a grid of 19 potential problems and evaluating time spent. We assessed reliability (κ coefficient) as well as internal consistency (Cronbach α coefficient) in an inter-observer study, and discriminatory power by analysing QI variability among hospitals.ResultsOverall, 23 115 data items were collected for the 4 QIs and analyzed. The average time spent on data collection was 8.5 days per hospital. The most common feasibility problem was misunderstanding of the item by hospital staff. QI reliability was good (κ: 0.59–0.97 according to QI). The hospitals differed widely in their ability to meet the quality criteria (mean value: 19–85%).ConclusionThese 4 QIs based on medical records can be used to compare the quality of record keeping among hospitals while limiting the burden of data collection, and can therefore be used for benchmarking purposes. The French National Health Directorate has included them in the new 2009 version of the accreditation procedure for healthcare organizations.

Despite wide heterogeneity in the summaries on accreditation and in FAC decision-making, this study provides an initial insight into common quality defects and ANAES priorities for hospitals in France.