Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm

Background and aims Celiac disease with its endoscopic manifestation of villous atrophy is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of villous atrophy at routine esophagogastroduodenoscopy may improve diagnostic performance. Methods A dataset of 858 endoscopic images of 182 patients with villous atrophy and 846 images from 323 patients with normal duodenal mucosa was collected and used to train a ResNet 18 deep learning model to detect villous atrophy. An external data set was used to test the algorithm, in addition to six fellows and four board certified gastroenterologists. Fellows could consult the AI algorithm’s result during the test. From their consultation distribution, a stratification of test images into “easy” and “difficult” was performed and used for classified performance measurement. Results External validation of the AI algorithm yielded values of 90 %, 76 %, and 84 % for sensitivity, specificity, and accuracy, respectively. Fellows scored values of 63 %, 72 % and 67 %, while the corresponding values in experts were 72 %, 69 % and 71 %, respectively. AI consultation significantly improved all trainee performance statistics. While fellows and experts showed significantly lower performance for “difficult” images, the performance of the AI algorithm was stable. Conclusion In this study, an AI algorithm outperformed endoscopy fellows and experts in the detection of villous atrophy on endoscopic still images. AI decision support significantly improved the performance of non-expert endoscopists. The stable performance on “difficult” images suggests a further positive add-on effect in challenging cases

Real-world effectiveness of caplacizumab vs the standard of care in immune thrombotic thrombocytopenic purpura

Immune thrombotic thrombocytopenic purpura (iTTP) is a thrombotic microangiopathy caused by anti-ADAMTS13 antibodies. Caplacizumab is approved for adults with an acute episode of iTTP in conjunction with plasma exchange (PEX) and immunosuppression. The objective of this study was to analyze and compare the safety and efficacy of caplacizumab vs the standard of care and assess the effect of the concomitant use of rituximab. A retrospective study from the Spanish TTP Registry of patients treated with caplacizumab vs those who did not receive it was conducted. A total of 155 patients with iTTP (77 caplacizumab, 78 no caplacizumab) were included. Patients initially treated with caplacizumab had fewer exacerbations (4.5% vs 20.5%; P <.05) and less refractoriness (4.5% vs 14.1%; P <.05) than those who were not treated. Time to clinical response was shorter when caplacizumab was used as initial treatment vs caplacizumab used after refractoriness or exacerbation. The multivariate analysis showed that its use in the first 3 days after PEX was associated with a lower number of PEX (odds ratio, 7.5; CI, 2.3-12.7; P <.05) and days of hospitalization (odds ratio, 11.2; CI, 5.6-16.9; P <.001) compared with standard therapy. There was no difference in time to clinical remission in patients treated with caplacizumab compared with the use of rituximab. No severe adverse event was described in the caplacizumab group. In summary, caplacizumab reduced exacerbations and refractoriness compared with standard of care regimens. When administered within the first 3 days after PEX, it also provided a faster clinical response, reducing hospitalization time and the need for PEX