Objectives: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the available evidence on these innovative techniques to improve CKD diagnosis and patient management. Methods: We included English language studies retrieved from PubMed. The review is therefore to be classified as a “rapid review”, since it includes one database only, and has language restrictions; the novelty and importance of the issue make missing relevant papers unlikely. We extracted 16 variables, including: main aim, studied population, data source, sample size, problem type (regression, classification), predictors used, and performance metrics. We followed the Preferred Reporting Items for Systematic Reviews (PRISMA) approach; all main steps were done in duplicate. Results: From a total of 648 studies initially retrieved, 68 articles met the inclusion criteria. Models, as reported by authors, performed well, but the reported metrics were not homogeneous across articles and therefore direct comparison was not feasible. The most common aim was prediction of prognosis, followed by diagnosis of CKD. Algorithm generalizability, and testing on diverse populations was rarely taken into account. Furthermore, the clinical evaluation and validation of the models/algorithms was perused; only a fraction of the included studies, 6 out of 68, were performed in a clinical context. Conclusions: Machine learning is a promising tool for the prediction of risk, diagnosis, and therapy management for CKD patients. Nonetheless, future work is needed to address the interpretability, generalizability, and fairness of the models to ensure the safe application of such technologies in routine clinical practice. Graphical

Undetected infection and delayed isolation of infected individuals are key factors driving the monkeypox virus (now termed mpox virus or MPXV) outbreak. To enable earlier detection of MPXV infection, we developed an image-based deep convolutional neural network (named MPXV-CNN) for the identification of the characteristic skin lesions caused by MPXV. We assembled a dataset of 139,198 skin lesion images, split into training/validation and testing cohorts, comprising non-MPXV images (n = 138,522) from eight dermatological repositories and MPXV images (n = 676) from the scientific literature, news articles, social media and a prospective cohort of the Stanford University Medical Center (n = 63 images from 12 patients, all male). In the validation and testing cohorts, the sensitivity of the MPXV-CNN was 0.83 and 0.91, the specificity was 0.965 and 0.898 and the area under the curve was 0.967 and 0.966, respectively. In the prospective cohort, the sensitivity was 0.89. The classification performance of the MPXV-CNN was robust across various skin tones and body regions. To facilitate the usage of the algorithm, we developed a web-based app by which the MPXV-CNN can be accessed for patient guidance. The capability of the MPXV-CNN for identifying MPXV lesions has the potential to aid in MPXV outbreak mitigation.

A supply chain (SC) is a network of interests, information, and materials involved in processes that produce value for customers. The implementation of blockchain technology in SC management in healthcare has had results. This review aims to summarize how blockchain technology has been used to address SC challenges in healthcare, specifically for drugs, medical devices (DMDs), and blood, organs, and tissues (BOTs). A systematic review was conducted by following the PRISMA guidelines and searching the PubMed and Proquest databases. English-language studies were included, while non-primary studies, as well as surveys, were excluded. After full-text assessment, 28 articles met the criteria for inclusion. Of these, 15 (54%) were classified as simulation studies, 12 (43%) were classified as theoretical, and only one was classified as a real case study. Most of the articles (n = 23, 82%) included the adoption of smart contracts. The findings of this systematic review indicated a significant but immature interest in the topic, with diverse ideas and methodologies, but without effective real-life applications.

Context: Cardiovascular diseases (CVDs) and cancer are the two main leading causes of death and disability worldwide. Suboptimal diet, poor in vegetables, fruits, legumes and whole grain, and rich in processed and red meat, refined grains, and added sugars, is a primary modifiable risk factor. Based on health, economic and ethical concerns, plant-based diets have progressively widespread worldwide. Objective: This umbrella review aims at assessing the impact of animal-free and animal-products-free diets (A/APFDs) on the risk factors associated with the development of cardiometabolic diseases, cancer and their related mortalities. Data sources: PubMed and Scopus were searched for reviews, systematic reviews, and meta-analyses published from 1st January 2000 to 31st June 2023, written in English and involving human subjects of all ages. Primary studies and reviews/meta-analyses based on interventional trials which used A/APFDs as a therapy for people with metabolic diseases were excluded. Data extraction: The umbrella review approach was applied for data extraction and analysis. The revised AMSTAR-R 11-item tool was applied to assess the quality of reviews/meta-analyses. Results: Overall, vegetarian and vegan diets are significantly associated with better lipid profile, glycemic control, body weight/BMI, inflammation, and lower risk of ischemic heart disease and cancer. Vegetarian diet is also associated with lower mortality from CVDs. On the other hand, no difference in the risk of developing gestational diabetes and hypertension were reported in pregnant women following vegetarian diets. Study quality was average. A key limitation is represented by the high heterogeneity of the study population in terms of sample size, demography, geographical origin, dietary patterns, and other lifestyle confounders. Conclusions: Plant-based diets appear beneficial in reducing cardiometabolic risk factors, as well as CVDs, cancer risk and mortality. However, caution should be paid before broadly suggesting the adoption of A/AFPDs since the strength-of-evidence of study results is significantly limited by the large study heterogeneity alongside the potential risks associated with potentially restrictive regimens.

Objectives: Population ageing and the rise in chronic diseases place continual stress on healthcare systems. Scarce resources often impede equitable access to healthcare, particularly in rural areas, resulting in prolonged waiting times and heightened risks of morbidity and mortality. Telemedicine has emerged as a promising solution, offering remote and equitable care that could potentially bridge access gaps and enhance health outcomes. This systematic review aims to quantitatively examine the impact of telemedicine implementation on waiting times, defined as the time passed from the booking of a visit for an outpatient to the administration of the service. Design: A systematic review was conducted using studies on telemedicine interventions that specifically addressed waiting times. Bias assessment was performed with three tools: ROBINS-I (“Risk of Bias In Non-Randomized Studies of Interventions”), AXIS ("Appraisal tool for Cross-Sectional Studies") and RoB-2 ("Risk of Bias-2"). A weighted mean approach was used to synthesise results, with medians synthesised using a median approach. Data sources: Articles in English were retrieved from the PubMed and Scopus databases. Eligibility criteria: Studies were excluded if they did not specifically address waiting times related to telemedicine interventions. Only studies that considered waiting times defined as the time passed from the booking of a visit for an outpatient to the administration of the service and any telemedicine intervention were included. Data extraction and synthesis: A total of 53 records were included, encompassing 270 388 patients in both the experimental and control groups. The weighted mean reduction in waiting times was calculated, and bias was assessed. No record was evaluated to be at high risk of bias, with 69.8% of studies evaluated at low risk and 26.4% at moderate risk (3.8% were surveys). Results were synthesised using a weighted mean approach for studies reporting means, and a median approach for studies reporting medians. Results: Overall, a weighted mean reduction of 25.4 days in waiting times was observed. Focusing on clinical specialties (n=114 042), the weighted mean reduction amounted to 34.7 days, while in surgical patients (n=156 346), telemedicine was associated with a weighted mean of 17.3 days saved. Conclusions: The implementation of telemedicine solutions may significantly improve waiting times, potentially leading to more efficient and equitable healthcare systems. PROSPERO registration number: CRD42023490822.

Purpose: Compression of the peroneal nerve is recognized as a common cause of falls. The superficial course of the peroneal nerve exposes it to trauma and pressure from common activities such as crossing of legs. The nerve can be exposed also to distress due to metabolic problems such as diabetes. The purpose of our manuscript is to review common peroneal nerve dysfunction symptoms and treatment as well as provide a systematic assessment of its relation to falls. Methods: We pooled the existing literature from PubMed and included studies (n = 342) assessing peroneal nerve damage that is related in any way to falls. We excluded any studies reporting non-original data, case reports and non-English studies. Results: The final systematic assessment included 4 articles. Each population studied had a non-negligible incidence of peroneal neuropathy. Peroneal pathology was found to be consistently associated with falls. Conclusion: The peroneal nerve is an important nerve whose dysfunction can result in falls. This article reviews the anatomy and care of the peroneal nerve. The literature review highlights the strong association of this nerve’s pathology with falls.