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Sethi, Saurabh

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Sethi

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Saurabh

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Sethi, Saurabh
Author's Publications: search.filters.isAuthorOfPublication.66196017-b943-4b81-ae00-e73dd67ea2d5

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    A meta-analysis on efficacy and safety: single-balloon vs. double-balloon enteroscopy
    (Oxford University Press, 2015) Wadhwa, Vaibhav; Sethi, Saurabh; Tewani, Sumeet; Garg, Sushil Kumar; Pleskow, Douglas; Chuttani, Ram; Berzin, Tyler; Sethi, Nidhi; Sawhney, Mandeep
    Background and aim: Double-balloon enteroscopy (DBE) and single-balloon enteroscopy (SBE) are new techniques capable of providing deep enteroscopy. Results of individual studies comparing these techniques have not been able to identify a superior strategy. Our aim was to systematically pool all available studies to compare the efficacy and safety of DBE with SBE for evaluation of the small bowel. Methods: Databases were searched, including PubMed, Embase, and the Cochrane Central Register of Controlled Trials. The main outcome measures were complete small-bowel visualization, diagnostic yield, therapeutic yield, and complication rate. Statistical analysis was performed using Review Manager (RevMan version 5.2). Meta-analysis was performed using fixed-effect or random-effect methods, depending on the absence or presence of significant heterogeneity. We used the χ2 and I2 test to assess heterogeneity between trials. Results were expressed as risk ratios (RR) or mean differences with 95% confidence intervals (CI). Results: Four prospective, randomized, controlled trials with a total of 375 patients were identified. DBE was superior to SBE for visualization of the entire small bowel [pooled RR = 0.37 (95% CI: 0.19–0.73; P = 0.004)]. DBE and SBE were similar in ability to provide diagnosis [pooled RR = 0.95 (95% CI: 0.77–1.17; P = 0.62)]. There was no significant difference between DBE and SBE in therapeutic yield [pooled RR = 0.78 (95% CI: 0.59–1.04; P = 0.09)] and complication rate [pooled RR = 1.08 (95% CI: 0.28–4.22); P = 0.91]. Conclusions: DBE was superior to SBE with regard to complete small bowel visualization. DBE was similar to SBE with regard to diagnostic yield, ability to provide treatment and complication rate, but these results should be interpreted with caution as they is based on very few studies and the overall quality of the evidence was rated as low to moderate, due to the small sample size.
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    A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection
    (Public Library of Science, 2015) Na, Xi; Martin, Alan J.; Sethi, Saurabh; Kyne, Lorraine; Garey, Kevin W.; Flores, Sarah W.; Hu, Mary; Shah, Dhara N.; Shields, Kelsey; Leffler, Daniel; Kelly, Ciaran
    Background and Aims Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI. Methods: A cohort totaling 638 patients with CDI was prospectively studied at three tertiary care clinical sites (Boston, Dublin and Houston). The clinical prediction rule (CPR) was developed by multivariate logistic regression analysis using the Boston cohort and the performance of this model was then evaluated in the combined Houston and Dublin cohorts. Results: The CPR included the following three binary variables: age ≥ 65 years, peak serum creatinine ≥2 mg/dL and peak peripheral blood leukocyte count of ≥20,000 cells/μL. The Clostridium difficile severity score (CDSS) correctly classified 76.5% (95% CI: 70.87-81.31) and 72.5% (95% CI: 67.52-76.91) of patients in the derivation and validation cohorts, respectively. In the validation cohort, CDSS scores of 0, 1, 2 or 3 were associated with severe clinical outcomes of CDI in 4.7%, 13.8%, 33.3% and 40.0% of cases respectively. Conclusions: We prospectively derived and validated a clinical prediction rule for severe CDI that is simple, reliable and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent complications of CDI.