Single-use versus reusable flexible ureteroscopes: a comprehensive cost-analysis decision model

Purpose: The significant improvements in flexible ureterorenoscopes have made flexible ureteroscopy the main treatment modality to target upper urinary pathologies. The purpose of this study was to critically evaluate all literature concerning the cost-effectiveness of flexible ureteroscopy comparing single-use with reusable scopes. Methods: A systematic online literature review was performed in PubMed, Embase and Google Scholar databases. Two separate urologists (GSM and FCT) performed the online search and reviewed all papers considered suitable and relevant for this analysis. Because of the paucity of high quality publications, not only prospective assessments but also case control and case series studies were included in the final analysis. All factors potentially affecting surgical costs or clinical outcomes were considered in the analysis. Results: 741 studies with the previously elected terms were found. Of those, 18 were duplicated and 77 were not related to urology procedures and were excluded. Of the remaining 646 studies, 59 published between 2000 and 2018 were considered of relevance to the pre-defined queries and were selected for further analysis. Stone free and complication rates were similar between single-use and reusable scopes. In special, urinary tract infection rate following flexible ureteroscopy is not inferior if a single-use device is used instead of a reusable scope. Operative time was in average 20% shorter if a digital scope was used, single-use or not. There is a suggestion that the learning curve is shorter with single-use devices but this is not consistent in the literature. Surgeon expertise impacts the longevity of the flexible scope. Reusable digital scopes seem to last longer than optic ones, though scope longevity is very variable worldwide. New scopes usually last three to four times more than refurbished ones and single-use ureterorenoscopes have good resilience throughout long cases. Both sterilization method and cleaning process impact scope longevity, the best results being achieved with Cidex and a dedicated nurse to take care of the sterilization process. The main factors that negatively impact device longevity regarding patient and disease are lower pole pathologies, large stone burden and non-use of a ureteral access sheath. Conclusions: The cost-effectiveness of a flexible ureteroscopy program is dependent of several aspects that must be considered when deciding whether to choose between a single-use and a reusable ureterorenoscope. Disposable devices are already a reality and will progressively become the standard as manufacturing price falls significantly.Objetivo: As melhorias significativas nos ureterorrenoscópios flexíveis tornaram a ureteroscopia flexível a principal modalidade de tratamento para as patologias de trato urinário superior. O objetivo deste estudo foi avaliar criticamente toda a literatura sobre a custo-efetividade da ureteroscopia flexível comparando aparelhos de uso único com reutilizáveis. Métodos: Uma revisão sistemática da literatura online foi realizada nas bases de dados PubMed, Embase e Google Scholar. Dois urologistas distintos (GSM e FCT) realizaram a pesquisa online e revisaram todos os trabalhos considerados adequados e relevantes para esta análise. Devido à escassez de publicações de alta qualidade, não apenas as avaliações prospectivas, mas também os estudos de casos e séries de casos foram incluídos na análise final. Todos os fatores que potencialmente afetam os custos cirúrgicos ou os desfechos clínicos foram considerados na análise. Resultados: foram encontrados 741 estudos com os termos previamente eleitos. Destes, 18 eram duplicados e 77 não tinham relação com procedimentos de urologia e foram excluídos. Dos restantes 646 estudos, 59 publicados entre 2000 e 2018 foram considerados relevantes para as consultas pré-definidas e foram selecionados para análise posterior. As taxas de complicações e livres de cálculo foram semelhantes entre os escopos de uso único e reutilizáveis. Em especial, a taxa de infecção do trato urinário após ureteroscopia flexível não é inferior se um dispositivo de uso único for usado em vez de um reutilizável. O tempo cirúrgico foi em média 20% menor se um ureteroscópio digital foi usado, seja de uso único ou não. Há uma sugestão de que a curva de aprendizado é mais curta com dispositivos de uso único, mas isso não é consistente na literatura. A experiência do cirurgião afeta a longevidade do aparelho flexível. Os aparelhos digitais reutilizáveis parecem durar mais que os ópticos, embora a longevidade seja muito variável em todo o mundo. Os novos ureteroscópios costumam durar de três a quatro vezes mais do que os recondicionados e os ureterorrenoscópios de uso único apresentam boa resiliência em casos longos. Tanto o método de esterilização como o processo de limpeza impactam a longevidade do aparelho, sendo os melhores resultados alcançados com o Cidex e uma enfermeira dedicada para cuidar do processo de esterilização. Os principais fatores que impactam negativamente a longevidade do dispositivo em relação ao paciente e à doença são patologias do polo inferior, grande volume de cálculo e não uso de uma bainha de acesso ureteral. Conclusões: A relação custo-efetividade de um programa de ureteroscopia flexível é dependente de vários aspectos que devem ser considerados ao se decidir se deve escolher entre ureterorrenoscópio de uso único e reutilizável. Os dispositivos descartáveis já são uma realidade e se tornarão progressivamente o padrão a partir do momento que o preço de fabricação cair significativamente

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost