Prevalence and Correlates of Genital Infections Among Newly Diagnosed Human Immunodeficiency Virus-Infected Adults Entering Human Immunodeficiency Virus Care in Windhoek, Namibia.

BACKGROUND: Identifying and treating genital infections, including sexually transmitted infections (STI), among newly diagnosed human immunodeficiency virus (HIV)-infected individuals may benefit both public and individual health. We assessed prevalence of genital infections and their correlates among newly diagnosed HIV-infected individuals enrolling in HIV care services in Namibia. METHODS: Newly diagnosed HIV-infected adults entering HIV care at 2 health facilities in Windhoek, Namibia, were recruited from December 2012 to March 2014. Participants provided behavioral and clinical data including CD4+ T lymphocyte counts. Genital and blood specimens were tested for gonorrhea, Chlamydia, trichomoniasis, Mycoplasma genitalium, syphilis, bacterial vaginosis, and vulvovaginal candidiasis. RESULTS: Among 599 adults, 56% were women and 15% reported consistent use of condoms in the past 6 months. The most common infections were bacterial vaginosis (37.2%), trichomoniasis (34.6%) and Chlamydia (14.6%) in women and M. genitalium (11.4%) in men. Correlates for trichomoniasis included being female (adjusted relative risk, [aRR], 7.18; 95% confidence interval [CI], 4.07-12.65), higher education (aRR, 0.58; 95% CI, 0.38-0.89), and lower CD4 cell count (aRR, 1.61; 95% CI, 1.08-2.40). Being female (aRR, 2.39; 95% CI, 1.27-4.50), nonmarried (aRR, 2.30; (95% CI, 1.28-4.14), and having condomless sex (aRR, 2.72; 95% CI, 1.06-7.00) were independently associated with chlamydial infection. Across all infections, female (aRR, 2.31; 95% CI, 1.79-2.98), nonmarried participants (aRR, 1.29; 95% CI, 1.06-1.59), had higher risk to present with any STI, whereas pregnant women (aRR, 1.16, 95% CI 1.03-1.31) were at increased risk of any STI or reproductive tract infection.

Health Care User Perspectives on Constructing, Contextualizing, and Co-Producing "Quality of Care".

Most of the research on health care user "quality of care" perspectives seeks discrete and measurable indicators to advance quality improvement (QI) goals. This lacks sufficiently grounded query about the meaning of "quality of care" for health users, and how context influences their ideas and experiences. We studied this between 2010 and 2011, repeatedly interviewing and shadowing 45 individuals in three of New York's hospital-based outpatient HIV care settings during routine visits. We found participants using common terminology, but across the cohort meaning varied and employed personal narratives. Participants conveyed the impact of historic and current experiences of stigma and discrimination on limiting access to care, and showed its destabilizing effects on quality constructs. Participants also felt they contributed to their health care settings' delivery of quality care. From our findings, we discuss the applicability and implications of "co-production" to conceptualize health care as jointly delivered by typical "givers" and "receivers" of care.

A simplified nutrition screen for hospitalized patients using readily available laboratory and patient information.

OBJECTIVE: We assessed admission screening information that best identifies patients who are at risk for malnutrition-related complications (MRCs). METHODS: We evaluated 13 patient characteristics associated with MRC for adults screened over a 3-mo period (n = 448) to determine which factors correlated best with the risk level assigned. The existing screen stratified patients into four levels defined as no risk, mild risk, moderate, and high risk for MRC. The analyzed variables were weight for height, wound, surgery/cancer therapy, fever, vomiting/diarrhea, poor oral intake, no oral intake, unplanned weight loss, malnutrition-related admission diagnosis, serum albumin, white blood cell count, hemoglobin, and total lymphocyte count. We modeled the relation between assigned MRC and the predictors by using state-of-the-art methods. RESULTS: The characteristics that correlated best with MRC risk level assignment were occurrence of a wound, poor oral intake, malnutrition-related admission diagnosis, serum albumin value, hemoglobin value, and total lymphocyte count. A model using four variables (malnutrition-related admission diagnosis, serum albumin value, hemoglobin value, and total lymphocyte count) was almost as good as that using six predictors. CONCLUSIONS: The ability of admission information to accurately reflect MRC risk is crucial to early initiation of restorative medical nutritional therapy. There is currently no uniform or proved standard for identifying MRC risk within 24 h of acute care admission. The ideal nutritional screen correlates well with the occurrence of MRC and also uses data routinely obtained at admission. The models described can be uniformly used by hospitals to screen patients for MRC risk.