Deepak Nag Ayyala

Introduction: Fecal incontinence (FI) is characterized by both irregular and unpredictable bowel symptoms. An accurate history of symptoms is important for diagnosis and guiding management. Whether a patient's history of bowel symptoms is reliable or if there is recall bias is unknown.Aim: To evaluate the accuracy of FI symptoms based on patient's recall compared with a prospective stool diary.Methods: FI (Rome IV) patients completed a bowel questionnaire that included leakage episodes and stool consistency. Subsequently they completed a one‐week FI stool diary. Agreement and correlation between historical recall and stool diary were compared.Results: One hundred patients participated. On average they reported 12 bowel movements (BMs) and five FI episodes per week. Fifty‐two percent had completed under‐graduation, 33% high school and 15% postgraduation. Using recall, 23% of patients accurately reported the number of FI episodes, whereas 41% underestimated and 36% overestimated its prevalence compared to the FI diary. Similarly, the concordance for the number of BMs was 30%, urgency was 54%, amount of stool leakage was 16%, and stool consistency was 12.5%. The concordance for nocturnal FI events, use of pads and lack of stool awareness were 63%, 75%, and 66.6% respectively.Conclusion: There is poor concordance for key bowel symptoms including the number of FI episodes as reported by FI patients, suggesting significant recall bias. Thus, historical recall of chronic FI symptoms may be less accurate. A prospective stool diary could provide more accurate information for the evaluation of FI patients.

Background: There is a lack of data surrounding the impact of coronavirus disease 2019 (COVID-19) among rural and urban communities. This study aims to determine whether there are differences in epidemiologic characteristics and clinical outcomes among individuals with COVID-19 among these communities. Methods: This was a retrospective analysis of 155 patients admitted to a single-center tertiary academic hospital located in Augusta, Georgia, with a large proportion of hospitalized patients transferred from or residing in rural and urban counties. Hospitalized adult patients were included in the study if they were admitted to AUMC between March 13, 2020, and June 25, 2020, and had a positive polymerase chain reaction test for severe acute respiratory syndrome coronavirus 2 regardless of the presence or absence of symptomatology. Demographics, admission data, and 30-day outcomes were examined overall and by geographical variation. Results: Urban patients were more likely to be admitted to the general medical floor (P = .01), while rural patients were more likely to require an escalation in the level of care within 24 hours of admission (P = .02). In contrast, of the patients who were discharged or expired at day 30, there were no statistically significant differences in either total hospital length of stay or intensive care unit length of stay between the populations. Conclusions: There may be many social determinants of health that limit a rural patient’s ability to seek prompt medical care and contribute to decompensation within the first 24 hours of admission. This study provides insight into the differences in clinical course among patients admitted from different community settings and when accounting for comorbid conditions.

M6A methylation is a highly prevalent post-transcriptional modification in eukaryotes. MeRIP-seq or m6A-seq, which comprises immunoprecipitation of methylation fragments , is the most common method for measuring methylation signals. Existing computational tools for analyzing MeRIP-seq data sets and identifying differentially methylated genes/regions are not most optimal. They either ignore the sparsity or dependence structure of the methylation signals within a gene/region. Modeling the methylation signals using univariate distributions could also lead to high type I error rates and low sensitivity. In this paper, we propose using mean vector testing (MVT) procedures for testing differential methylation of RNA at the gene level. MVTs use a distribution-free test statistic with proven ability to control type I error even for extremely small sample sizes. We performed a comprehensive simulation study comparing the MVTs to existing MeRIP-seq data analysis tools. Comparative analysis of existing MeRIP-seq data sets is presented to illustrate the advantage of using MVTs. Mean vector testing procedures are observed to control type I error rate and achieve high power for detecting differential RNA methylation using m6A-seq data. Results from two data sets indicate that the genes detected identified as having different m6A methylation patterns have high functional relevance to the study conditions. The dimer software package for differential RNA methylation analysis is freely available at https://github.com/ouyang-lab/DIMER. Supplementary data are available at Briefings in Bioinformatics online.

INTRODUCTION: Rectal hypersensitivity is an important pathophysiological dysfunction in irritable bowel syndrome with predominant constipation (IBS-C), whose treatment remains challenging. In a randomized controlled trial, we compared the efficacy and safety of a novel sensori-behavioral treatment, sensory adaptation training (SAT) with escitalopram. METHODS: Patients with IBS-C (Rome III) with rectal hypersensitivity received 6 biweekly sessions of SAT or escitalopram 10 mg daily for 3 months. SAT was performed by repetitive gradual distension of 10-cm long highly compliant rectal balloon above tolerability thresholds using barostat. Treatment effects on sensory thresholds and symptoms were compared. Coprimary outcome measures were those achieving improvements in rectal hypersensitivity (≥20% increase in ≥2/3 sensory thresholds) and pain (≥30% decrease). RESULTS: We randomized 49 patients; 26 received SAT and 23 escitalopram. SAT significantly improved desire to defecate (Δ 13.5 ± 2.3 vs 2.2 ± 1.1 mm Hg, P = 0.0006) and maximum tolerability (Δ 14.8 ± 1.9 vs 1.6 ± 0.9 mm Hg, P < 0.0001) thresholds compared with escitalopram. There were significantly greater percentage of hypersensitivity responders with SAT than escitalopram (69% vs 17%, P < 0.001), but not pain responders (58% vs 44%, P = 0.4). Daily pain scores did not differ between groups (P = 0.8) or escitalopram (P = 0.06) but decreased with SAT (P = 0.0046) compared with baseline. SAT significantly increased rectal compliance (P < 0.019) and complete spontaneous bowel movements per week than escitalopram (P = 0.04). Five withdrew from adverse events with escitalopram and none with SAT. DISCUSSION: SAT was significantly more efficacious in improving hypersensitivity and bowel symptoms in IBS-C than escitalopram. SAT is a promising novel treatment for IBS with rectal hypersensitivity.

Estimation and hypothesis tests for the covariance matrix in high dimensions is a challenging problem as the traditional multivariate asymptotic theory is no longer valid. When the dimension is larger than or increasing with the sample size, standard likelihood based tests for the covariance matrix have poor performance. Existing high dimensional tests are either computationally expensive or have very weak control of type I error. In this paper, we propose a test procedure, CRAMP, for testing hypotheses involving one or more covariance matrices using random projections. Projecting the high dimensional data randomly into lower dimensional subspaces alleviates of the curse of dimensionality, allowing for the use of traditional multivariate tests. An extensive simulation study is performed to compare CRAMP against asymptotics-based high dimensional test procedures. An application of the proposed method to two gene expression data sets is presented.

Testing equality of mean vectors is a very commonly used criterion when comparing two multivariate random variables. Traditional tests such as Hotelling's T-squared become either unusable or output small power when the number of variables is greater than the combined sample size. In this paper, w}e propose a test using both prepivoting and Edgeworth expansion for testing the equality of two population mean vectors in the "large p, small n" setting. The asymptotic null distribution of the test statistic is derived and it is shown that the power of suggested test converges to one under certain alternatives when both n and p increase to infinity against sparse alternatives. Finite sample performance of the proposed test statistic is compared with other recently developed tests designed to also handle the "large p, small n" situation through simulations. The proposed test achieves competitive rates for both type I error rate and power. The usefulness of our test is illustrated by applications to two microarray gene expression data sets