Morning only 4-L SF-PEG provided superior cleansing with less bloating as compared to 2-L PEG + Asc bowel preparation for afternoon colonoscopy. Thus, future studies evaluating efficacy of morning only preparation for afternoon colonoscopy should use 4-L SF-PEG as the standard comparator.

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Background: Heart failure (HF) is the leading cause of hospitalizations and readmissions in the United States. Approximately one-third of patients admitted for HF are readmitted within 3 months; however, there are few markers that can identify those at highest risk for readmission. The purpose of this study was to identify clinical and laboratory markers associated with hospital readmission in decompensated HF. Hypothesis: Clinical and laboratory markers are associated with readmission rates in decompensated HF. Methods: Clinical and laboratory data from 412 patients admitted with HF were analyzed using a multivariable logistic regression analysis to find predictors of HF readmission by 30 days. Results: HF readmission rates at 30 days were lowest in those with at least 2 of the following discharge criteria: net fluid reduction >1.3 L (odds ratio [OR]: 0.27, P = 0.019), serum sodium level >135 (OR: 0.46, P = 0.034), and N-terminal brain natriuretic peptide level reduction >23% (OR: 0.11, P = 0.048). In multivariate analysis, those patients meeting ≥2 criteria had a very low risk of 30-day readmission (OR: 0.10, 95% confidence interval: 0.01-0.68, P = 0.019) compared to patients who failed to meet 2 criteria. Conclusions: A negative fluid balance, normal serum sodium, and net reduction in N-terminal brain natriuretic peptide level during hospitalization may be important indices to target to help reduce the likelihood of HF readmission within 30 days. IntroductionIn the United States, the estimated prevalence of heart failure (HF) approaches 6 million individuals.1 Despite advances in the medical management of HF, it remains the leading cause of hospitalizations and readmissions. 2 Within 3 months of a HF hospitalization, there is a national 30% readmission rate and an associated 10% mortality rate.

Background. It has been observed that African American race is associated with a lower prevalence of atrial fibrillation (AF) compared to Caucasian race. To better quantify the association between African American race and AF, we performed a meta-analysis of published studies among different patient populations which reported the presence of AF by race. Methods. A literature search was conducted using electronic databases between January 1999 and January 2011. The search was limited to published studies in English conducted in the United States, which clearly defined the presence of AF in African American and Caucasian subjects. A meta-analysis was performed with prevalence of AF as the primary endpoint. Results. In total, 10 studies involving 1,031,351 subjects were included. According to a random effects analysis, African American race was associated with a protective effect with regard to AF as compared to Caucasian race (odds ratio 0.51, 95% CI 0.44 to 0.59, P < 0.001). In subgroup analyses, African American race was significantly associated with a lower prevalence of AF in the general population, those hospitalized or greater than 60 years old, postcoronary artery bypass surgery patients, and subjects with heart failure. Conclusions. In a broad sweep of subjects in the general population and hospitalized patients, the prevalence of AF in African Americans is consistently lower than in Caucasians.

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Importance: Currently, there is no unified framework linking disease progression to established viral levels, clinical tests, inflammatory markers, and investigational treatment options. Objective: It may take many weeks or months to establish a standard treatment approach. Given the growing morbidity and mortality with respect to COVID-19, we present a treatment approach based on a thorough review of scholarly articles and clinical reports. Our focus is on staged progression, clinical algorithms, and individualized treatment. Evidence Review: We followed the protocol for a quality review article proposed by Heyn et. al.1 A literature search was conducted to find all relevant studies related to COVID-19. The search was conducted between April 1, 2020 and April 13, 2020 using the following electronic databases: PubMed (1809 to present), Google Scholar (1900 to present), MEDLINE (1946 to present), CINAHL (1937 to present), and Embase (1980 to present). Keywords used included COVID-19, 2019-nCov, SARS-CoV-2, SARS-CoV, and MERS-CoV, with terms such as efficacy, seroconversion, microbiology, pathophysiology, viral levels, inflammation, survivability, and treatment and pharmacology. No language restriction was placed on the search. Reference lists were manually scanned for additional studies. Findings: Of the articles found in the literature search, 70 were selected for inclusion in this study (67 cited in the body of the manuscript and 3 additional unique references in the Figures). The articles represent work from China, Japan, Taiwan, Vietnam, Rwanda, Israel, France, the United Kingdom, the Netherlands, Canada, and the United States. Most of the articles were cohort or case studies, but we also drew upon information found in guidelines from hospitals and clinics instructing their staff on procedures to follow. In addition, we based some decisions on data collected by agencies such as the CDC, FDA, IHME, ISDA, and Worldometer. None of the case studies or cohort studies used a large number of participants. The largest group of participants numbered less than 500 and some case studies had fewer than 30 patients. However, the review of the literature revealed the need for individualized treatment protocols due to the variability of patient clinical presentation and survivability. A number of factors appear to influence mortality: the stage at which the patient first presented for care, pre-existing health conditions, age, and the viral load the patient carried. Conclusion and Relevance: COVID-19 can be divided into three distinct Stages, beginning at the time of infection (Stage I), sometimes progressing to pulmonary involvement (Stage II, with or without hypoxemia) and less frequently to systemic inflammation (Stage III). In addition to modeling the stages of disease progression, we have also created a treatment algorithm which considers age, comorbidities, clinical presentation, and disease progression to suggest drug classes or treatment modalities. This paper presents the first evidence-based recommendations for individualized treatment for COVID-19.

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