PURPOSE:To summarize 12-month results from the randomized controlled arm of the Wrapsody Arteriovenous Access Efficacy (WAVE) trial. MATERIALS AND METHODS:The WAVE trial was a prospective, multicenter study conducted across 43 international centers. In the randomized arm of the trial, patients with an arteriovenous fistula on hemodialysis with evidence of stenosis within the peripheral venous outflow circuit were randomized 1:1 to treatment with the Wrapsody Cell-Impermeable Endoprosthesis (CIE) or percutaneous transluminal angioplasty (PTA). Safety outcomes of interest at 12 months included device-related events and serious adverse events. Effectiveness outcomes of interest at 12 months included target lesion primary patency (TLPP), access circuit primary patency (ACPP), and the number of reinterventions. RESULTS:Two hundred forty-five patients were analyzed (CIE, n = 122; PTA, n = 123). At 12 months, TLPP and ACPP were significantly higher for patients treated with the CIE than for those treated with PTA (TLPP: 70.4% vs 38.5%, P < .0001; ACPP: 56.4% vs 31.1%, P = .0002). The mean number of reinterventions to maintain target lesion patency was significantly lower for patients treated with the CIE than for those treated with PTA at 12 months (0.49 [SD ± 0.92] vs 1.08 [SD ± 1.16], P < .0001), as was the mean number of reinterventions required to maintain access circuit patency (1.08 [SD ± 1.63] vs 1.70 [SD ± 1.93], P = .001). Device-related events were lower for the CIE versus PTA (2.9% vs 9.5%, P = .049). No significant differences were observed for the proportion of patients experiencing serious adverse events. CONCLUSIONS:The superior performance of the CIE versus PTA provides useful information to help physicians prolong vascular access patency for hemodialysis patients who experience stenosis in their venous outflow circuit.
PURPOSE:To describe the safety and effectiveness of the Wrapsody Cell-Impermeable Endoprosthesis (CIE) for restoring functionality of the arteriovenous graft (AVG) in hemodialysis patients who experienced venous outflow stenosis. MATERIALS AND METHODS:The nonrandomized arm of the Wrapsody Arteriovenous Access Efficacy (WAVE) trial comprised a single cohort of 112 patients with stenosis in the AVG of their venous outflow circuit who were treated with the CIE. The primary effectiveness endpoint was the 6-month target lesion primary patency (TLPP). The primary safety endpoint was the proportion of patients without any localized or systemic safety events through 30 days, affecting the access of the venous outflow circuit and resulting in a reintervention, hospitalization, or death. Six-month safety and effectiveness outcomes were compared with performance goals (PGs) based on historical data on stent grafts (TLPP PG, 60%; safety PG, 89%). Key secondary measures were the 12-month TLPP and the 6- and 12-month access circuit primary patency (ACPP). RESULTS:A significantly higher proportion of patients treated with the CIE were free from a localized or systemic safety event through 30 days than the safety PG (95.4% vs 89%; P = .016). The observed 6-month TLPP was significantly higher than the PG (81.4% vs 60%; P < .0001). At 12 months, the Kaplan-Meier estimate of TLPP was 60.3%; the ACPP at 6 and 12 months was 69.2% and 36.3%, respectively. CONCLUSIONS:The superior patency and confirmed safety profile of the CIE suggest that it is a safe and effective treatment for AVG outflow stenosis, offering a significant patency improvement relative to historical stent graft performance.
Artificial intelligence (AI) has grown widely into diverse areas of research over the last decade. Publications distributed over the years disclose that biochemistry and analytical chemistry are incorporating AI to the utmost level. Enormous complex data sets are produced by analytical instruments comprising a treasure of information which is very helpful to analytical chemists in characterization. Despite this, we lack capabilities in data analysis and algorithms, which restricts our aptitude to discover and employ this data entirely. Machine learning and AI are being instigated to deal with this current challenge by accelerating several other applications in analytical chemistry. A critical valuation of illustrative reports amalgamating AI with analytical chemistry, spectroscopies, and several sensors has been discussed widely. This comprehensive review evaluates the AI advancement in data interpretation, the assistance of AI in analyte identification and quantification in proteomics and metabolomics, AI databases for primary and secondary metabolites information, regulatory and ethical guidelines in analytical chemistry incorporating AI, machine learning applications in drug discovery, agriculture, cosmetic, and food and separation techniques. In summary, this current review puts forward a thorough examination concerning the advancements of AI in different domains of chemistry and strives to facilitate comprehension of its forthcoming trajectories.
Premise:Pteridophytes-vascular land plants that disperse by spores-are a powerful system for studying plant evolution, particularly with respect to the impact of abiotic factors on evolutionary trajectories through deep time. However, our ability to use pteridophytes to investigate such questions-or to capitalize on the ecological and conservation-related applications of the group-has been impaired by the relative isolation of the neo- and paleobotanical research communities and by the absence of large-scale biodiversity data sources. Methods:Here we present the Pteridophyte Collections Consortium (PCC), an interdisciplinary community uniting neo- and paleobotanists, and the associated PteridoPortal, a publicly accessible online portal that serves over three million pteridophyte records, including herbarium specimens, paleontological museum specimens, and iNaturalist observations. We demonstrate the utility of the PteridoPortal through discussion of three example PteridoPortal-enabled research projects. Results:The data within the PteridoPortal are global in scope and are queryable in a flexible manner. The PteridoPortal contains a taxonomic thesaurus (a digital version of a Linnaean classification) that includes both extant and extinct pteridophytes in a common phylogenetic framework. The PteridoPortal allows applications such as greatly accelerated classic floristics, entirely new "next-generation" floristic approaches, and the study of environmentally mediated evolution of functional morphology across deep time. Discussion:The PCC and PteridoPortal provide a comprehensive resource enabling novel research into plant evolution, ecology, and conservation across deep time, facilitating rapid floristic analyses and other biodiversity-related investigations, and providing new opportunities for education and community engagement.
