Initiation of treatment with rifaximin-α was associated with a marked reduction in the number of hospital admissions and hospital length of stay. These data suggest that treatment of patients with rifaximin-α for hepatic encephalopathy was generally cost saving.
A wide variation in practice is seen across the country. A robust national guideline to streamline the endoscopy practice in anticoagulated patients is needed.
Methods High definition video recordings were collected from patients with non-dysplastic (ND-BE) and dysplastic (D-BE) BE undergoing endoscopy at UCLH. A protocol was used to record areas of interest after which a matched biopsy was taken to confirm the histological diagnosis. In a blinded manner, videos were shown to 3 expert endoscopists who interpreted them based on their M and V patterns, presence of nodularity, ulceration and suspected diagnosis. Acetic acid (ACA) was used in some cases. Data was inputted into the WEKA package to construct a decision tree for dysplasia prediction. Results Videos from 47 patients (13 before and after ACA) were collected (24 ND-BE, 23 D-BE). Cases in which ACA was used, 7 had ND-BE and 6 D-BE. Experts' average accuracy for dysplasia prediction was 72.2% (66.7-76.7%). ACA did not improve dysplasia detection. In 5 cases all 3 experts failed to detect D-BE.Using ML, the most important attribute was the lesions' V pattern. If this was reported abnormal (irregular, dilated vessels) by more than one doctor, the lesion was D-BE (accuracy 79%). If D-BE was predicted despite the V pattern being reported abnormal by one or fewer experts, the lesion was still D-BE and vice versa. Conclusion Experts can diagnose D-BE in up to three-quarters of cases using i-Scan. ML can define rules learnt from expert opinion that predict dysplasia with a similar level of accuracy and are easier to learn than conventional classification systems. They could be used to train non-expert endoscopists in dysplasia detection and then used for blinded assessment of accuracy.
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