Commonly Drawn Immunologic and Inflammatory Markers as Risk Predictors for Anal Cancer in Veterans Living With HIV.

OBJECTIVES: This study aimed to determine if immune inflammatory markers (neutrophil lymphocyte ratio [NLR], platelet lymphocyte ratio [PLR], and prognostic nutritional index [PNI]) correlate with anal cancer risk in people living with HIV and to compare these markers with the CD4/CD8 ratio. MATERIALS AND METHODS: This is a regional retrospective cohort study of veterans living with HIV who were screened for or diagnosed with anal neoplasia or cancer from 2001 to 2019. The NLR, PLR, PNI, and CD4/CD8 ratio within 1 year of anal pathology results were computed. Patients with anal cancer were compared to patients without anal cancer. Regression modeling was used to estimate the odds of developing anal cancer. RESULTS: Three hundred thirty-four patients were included (37 with anal cancer, 297 without anal cancer). In patients with anal cancer, NLR and PLR were higher (2.17 vs 1.69, p = .04; 140 vs 110, p = .02, respectively), while PNI and CD4/CD8 ratio were lower (44.65 vs 50.01, p < .001; 0.35 vs 0.80, p < .001, respectively). On multivariate logistic regression modeling, only PNI (odds ratio, 0.90; p = .001) and CD4/CD8 ratio (odds ratio, 0.05; p < .001) were associated with increased anal cancer risk. CONCLUSIONS: Although NLR and PLR independently correlate with anal cancer risk, when controlling for other risk predictors, only PNI and CD4/CD8 ratio were statistically significant biomarkers for anal cancer. The CD4/CD8 ratio is the strongest immune inflammatory marker that predicts risk of anal cancer among veterans living with HIV.

Antibiotic Prescribing Practices for Upper Respiratory Tract Infections Among Primary Care Providers: A Descriptive Study.

Background: Most antibiotics are prescribed in the ambulatory setting with estimates that up to 50% of use is inappropriate. Understanding factors associated with antibiotic misuse is essential to advancing better stewardship in this setting. We sought to assess the frequency of unnecessary antibiotic use for upper respiratory infections (URIs) among primary care providers and identify patient and provider characteristics associated with misuse. Methods: Unnecessary antibiotic prescribing was assessed in a descriptive study by using adults ≥18 years seen for common URIs in a large, Upper Midwest, integrated health system, electronic medical records from June 2017 through May 2018. Individual provider rates of unnecessary prescribing were compared for primary care providers practicing in the departments of internal medicine, family medicine, or urgent care. Patient and provider characteristics associated with unnecessary prescribing were identified with a logistic regression model. Results: A total of 49 463 patient encounters were included. Overall, antibiotics were prescribed unnecessarily for 42.2% (95% confidence interval [CI], 41.7-42.6) of the encounters. Patients with acute bronchitis received unnecessary antibiotics most frequently (74.2%; 95% CI, 73.4-75.0). Males and older patients were more likely to have an unnecessary antibiotic prescription. Provider characteristics associated with higher rates of unnecessary prescribing included being in a rural practice, having more years in practice, and being in higher volume practices such as an urgent care setting. Fifteen percent of providers accounted for half of all unnecessary antibiotic prescriptions. Conclusions: Although higher-volume practices, a rural setting, or longer time in practice were predictors, unnecessary prescribing was common among all providers.

Landscape-Scale Factors Affecting the Prevalence of Escherichia coli in Surface Soil Include Land Cover Type, Edge Interactions, and Soil pH.

Escherichia coli is deposited into soil with feces and exhibits subsequent population decline with concomitant environmental selection. Environmentally persistent strains exhibit longer survival times during this selection process, and some strains have adapted to soil and sediments. A georeferenced collection of E. coli isolates was developed comprising 3,329 isolates from 1,428 soil samples that were collected from a landscape spanning the transition from the grasslands to the eastern deciduous forest biomes. The isolate collection and sample database were analyzed together to discover how land cover, site characteristics, and soil chemistry influence the prevalence of cultivable E. coli in surface soil. Soils from forests and pasture lands had equally high prevalences of E. coli Edge interactions were also observed among land cover types, with proximity to forests and pastures affecting the likelihood of E. coli isolation from surrounding soils. E. coli is thought to be more prevalent in sediments with high moisture, but this was observed only in grass- or crop-dominated lands in this study. Because differing E. coli phylogroups are thought to have differing ecology profiles, isolates were also typed using a novel single-nucleotide polymorphism (SNP) genotyping assay. Phylogroup B1 was the dominant group isolated from soil, as has been reported in all other surveys of environmental E. coli Although differences were small, isolates belonging to phylogroups B2 and D were associated with wooded areas, slightly more acidic soils, and soil sampling after rainfall events. In contrast, isolates from phylogroups B1 and E were associated with pasture lands.IMPORTANCE The consensus is that complex niches or life cycles should select for complex genomes in organisms. There is much unexplained biodiversity in E. coli, and its cycling through complex extrahost environments may be a cause. In order to understand the evolutionary processes that lead to adaptation for survival and growth in soil, an isolate collection that associates soil conditions and isolate genome sequences is required. An equally important question is whether traits selected in soil or other extrahost habitats can be transmitted to E. coli residing in hosts via gene flow. The new findings about the distribution of E. coli in soil at the landscape scale (i) enhance our capability to study how extrahost environments influence the evolution of E. coli and other bacteria, (ii) advance our knowledge of the environmental biology of this microbe, and (iii) further affirm the emerging scientific consensus that E. coli in waterways originates from nonpoint sources not associated with human activity or livestock farming.