Relamorelin in Gastroparesis and Diabetic Gastroparesis: A Meta-Analysis on Its Efficacy and Safety

This meta-analysis aimed to evaluate the efficacy and safety of relamorelin, a synthetic ghrelin receptor agonist, for the treatment of gastroparesis and diabetic gastroparesis. A total of 1,033 participants from five randomized controlled trials were included. The primary outcome was the mean change in gastric emptying time from baseline. Relamorelin demonstrated a statistically significant improvement in gastric emptying time with a mean difference of -11.40 minutes compared to the placebo group. Furthermore, a significant improvement was observed specifically in diabetic gastroparesis patients, with a mean difference of -8.43 minutes. However, adverse effects, such as headaches, dizziness, and gastrointestinal symptoms, were more prevalent in the relamorelin group. Despite these adverse effects, the study concludes that relamorelin offers a promising avenue for gastroparesis treatment, especially given the limited existing therapeutic options. This comprehensive meta-analysis synthesizes existing evidence to inform clinical practice and guides future research in this domain.

Artificial Intelligence in the Detection of Barrett's Esophagus: A Systematic Review

Barrett's esophagus (BE) remains a significant precursor to esophageal adenocarcinoma, requiring accurate and efficient diagnosis and management. The increasing application of machine learning (ML) technologies presents a transformative opportunity for diagnosing and treating BE. This systematic review evaluates the effectiveness and accuracy of machine learning technologies in BE diagnosis and management by conducting a comprehensive search across PubMed, Scopus, and Web of Science databases up to the year 2023. The studies were organized into five categories: computer-aided systems, natural language processing and text-based systems, deep learning on histology and biopsy images, real-time and video analysis, and miscellaneous studies. Results indicate high sensitivity and specificity across machine learning applications. Specifically, computer-aided systems showed sensitivities ranging from 84% to 100% and specificities from 64% to 90.7%. Natural language processing and text-based systems achieved an accuracy as high as 98.7%. Deep learning techniques applied to histology and biopsy images displayed sensitivities up to greater than 90% and a specificity of 100%. Furthermore, real-time and video analysis technologies demonstrated high performance with assessment speeds of up to 48 frames per second (fps) and a mean average precision of 75.3%. Overall, the reviewed literature underscores the growing capability and efficiency of machine learning technologies in diagnosing and managing Barrett's esophagus, often outperforming traditional diagnostic methods. These findings highlight the promising future role of machine learning in enhancing clinical practice and improving patient care for Barrett's esophagus.

Clinical features and severity of psoriasis: a comparison of facial and nonfacial involvement in Iran

BACKGROUND

Facial involvement in psoriasis is accomplished with poor prognosis. In this study, clinical features and severity of psoriasis were compared between facial and nonfacial psoriasis involvement groups in Iran. It also evaluated these characteristics in different subtypes of facial psoriasis.

METHODS

One hundred and thirty- eight psoriatic patients having referred to our clinic entered in this cross- sectional study in 2006 - 2007. Medical information, whole body and scalp Psoriasis Area and Severity Index (PASI) scores were obtained. Variables were compared between the facial and nonfacial involvement groups and also in different subtypes of the former including peripherofacial (PF), centrofacial (CF), and mixedfacial (MF). A P-value of < 0.05 was considered as significant.

RESULTS

We found 55.0% facial involvement in Iranian psoriatic patients. MF (52.6%), CF (28.9%), and PF (18.4%), respectively were the common forms of facial involvement. The median whole body and scalp PASI scores, the number of male participants, and tongue involvement were significantly higher in patients with facial involvement. Comparing different subtypes of facial psoriasis, whole body PASI and scalp PASI scores were significantly higher in MF subtype and lower in CF subtype. Despite the least severity in the latter subtype, psoriatic arthritis and geographic tongue were shown to be more common in this subtype. Moreover, relapse history was correlated with PF subtype.

CONCLUSIONS

Facial involvement in psoriasis had significantly higher whole body and scalp PASI scores in Iran which may be an indication of more severe disease. This difference was more prominent in MF subtype.