Background & Aims: Unsedated colonoscopy can be painful, poorly tolerated by patients, and associated with unsatisfactory technical performance. Previous studies report an advantage of water exchange over conventional air insufflation in reducing pain during unsedated colonoscopy. Our goal was to analyze the impact of water exchange colonoscopy on the level of maximum pain reported by patients submitted to unsedated colonoscopy, compared to conventional air insufflation. Methods: We performed a single-center, patient-blinded, prospective randomized comparative study, where patients were either allocated to the water group, in which the method of colonoscopy used was water exchange, or the standard air group, in which the examination was accomplished with air insufflation. Results: A total of 141 patients were randomized, 70 to the water and 71 to the air group. The maximum level of pain reported by patients during unsedated colonoscopy, measured by a numeric scale of pain (0-10), was significantly lower in the water group (3.39 ± 2.32), compared to the air group (4.94 ± 2.10), p < 0.001. The rate of painless colonoscopy was significantly higher in the water group (12.9 vs. 1.4%, p = 0.009). There were no significant differences between the two groups regarding indications for the procedure, quality of bowel preparation, cecal intubation time, withdrawal time, number of position changes, adenoma detection rate, and postprocedural complications. Only the number of abdominal compressions was significantly different, showing that water exchange decreases the number of compressions needed during colonoscopy. Conclusions: Water exchange was a safe and equally effective alternative to conventional unsedated colonoscopy, associated with less intraprocedural pain without impairing key performance measures.
We derive fast recursions to compute the probability that k or more consecutive customer losses take place during a busy period of a queue, the so called k-CCL probability, for regular and oscillating M X /G/1/n systems.
Background and study aims Paris Classification is used to classify gastrointestinal superficial neoplastic lesions and to predict presence of submucosal invasion. We aimed to evaluate interobserver reliability and agreement for this classification among Western endoscopists.
Methods A total of 54 superficial gastric lesions were independently classified according to Paris classification by eight endoscopists (4 experts and 4 non-experts). Observers were asked to classify two sets of images – first, obtained with high-resolution white light (HR-WL) endoscopy and secondly, with the same HR-WL images paired with images obtained with high-resolution Narrow Band Imaging (HR-NBI) – HR-WL + NBI image group.
Results Overall interobserver reliability when asked to classify in I, II or III was good both using HR-WL images and HR-WL + NBI images (wK of 0.65 and 0.70, respectively). The proportion of agreement for type III lesions was 0.48 for HR-WL images increasing to 0.74 in the HR-WL + NBI group. Interobserver reliability for identification of a IIc component was only moderate (wK 0,47). NBI improves both sensitivity and interobserver reliability among trainees (from wK 0.19 to 0.47). Specificity was higher than sensitivity in predicting submucosal invasion.
Conclusion Overall, the reliability of Paris classification is moderate to good. Training on this classification or its revision and use of technology such as NBI may improve not only reliability and agreement but also accuracy.
We address the probability that k or more Consecutive Customer Losses take place during a busy period of a queue, the so-called k-CCL probability, for oscillating GI X /M//n systems with state dependent services rates, also denoted as GI X /M(m) − M(m)//n systems, in which the service rates oscillate between two forms according to the evolution of the number of customers in the system. We derive an efficient algorithm to compute k-CCL probabilities in these systems starting with an arbitrary number of customers in the system that involves solving a linear system of equations. The results derived are illustrated for specific sets of parameters.
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