Time for clinical decision support systems tailoring individual patient therapy to improve renal and cardiovascular outcomes in diabetes and nephropathy

是时候引入临床决策支持系统,为糖尿病肾病患者量身定制治疗方案,以改善肾脏和心血管预后了。

阅读:1

Abstract

The current guideline treatment for patients with diabetes and nephropathy to lower the high risk of renal and cardiovascular (CV) morbidity and mortality is based on results of clinical studies that have tested new drugs in large groups of patients with diabetes and high renal/CV risk. Although this has delivered breakthrough therapies like angiotensin receptor blockers, the residual renal/CV risk remains extremely high. Many subsequent trials have tried to further reduce this residual renal/CV risk, without much success. Post hoc analyses have indicated that these failures are, at least partly, due to a large variability in response between and within the patients. The current 'group approach' to designing and evaluating new drugs, as well as group-oriented drug registration and guideline recommendations, does not take this individual response variation into account. Like with antibiotics and cancer treatment, a more individual approach is warranted to effectively optimize individual results. New tools to better evaluate the individual risk change have been developed for improved clinical trial design and to avoid trial failures. One of these tools, the composite multiple parameter response efficacy score , is based on monitoring changes in all available risk factors and integrating them into a prediction of ultimate renal and CV risk reduction. This score has also been modelled into a clinical decision support system for use in monitoring and changing the therapy in individual patients to protect them from renal/CV events. In conclusion, future treatment of renal/CV risk in diabetes should transition from an era of 'one size fits all' into the new era of 'a fit for each size'.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。