Pharmacologic interventions for painful diabetic neuropathy: an umbrella systematic review and comparative effectiveness network meta-analysis (Protocol)

医学 荟萃分析 随机对照试验 系统回顾 协议(科学) 糖尿病神经病变 重症监护医学 梅德林 神经病理性疼痛 周围神经病变 物理疗法 糖尿病 替代医学 外科 内科学 麻醉 病理 内分泌学 法学 政治学
作者
Marcio L. Griebeler,Απόστολος Τσάπας,Juan P. Brito,Zhen Wang,Olivia J Phung,Víctor M. Montori,Víctor M. Montori
出处
期刊:Systematic Reviews [Springer Nature]
卷期号:1 (1) 被引量:12
标识
DOI:10.1186/2046-4053-1-61
摘要

Neuropathic pain can reduce the quality of life and independence of 30% to 50% of patients with diabetes. The comparative effectiveness of analgesics for patients with diabetic neuropathy remains unclear. The aim of the current work, therefore, was to summarize the evidence about the analgesic effectiveness of the most common oral and topical agents used for the treatment of peripheral diabetic neuropathy. We will use an umbrella approach (systematic review of systematic reviews) to identify eligible randomized controlled trials (RCTs) for the most common oral or topical analgesics for painful diabetic neuropathy. Two reviewers will independently determine RCT eligibility. Disagreement will be solved by consensus and arbitrated by a third reviewer. We will extract descriptive, methodological and efficacy data in duplicate. Results will be pooled and analyzed using classic random-effects meta-analyses and network meta-analyses to compute the absolute and relative efficacy of therapeutic options. We will use the I 2 statistic and Cochran's Q test to assess heterogeneity. Risk of bias and publication bias, if appropriate, will be evaluated, as well as overall strength of the evidence. This network meta-analysis aims to synthesize available direct and indirect evidence of effectiveness of analgesics in the treatment of painful diabetic neuropathy. The network approach will offer the opportunity to generate a ranking based on efficacy and along with known side effects, costs, and administration burdens will enable patients and clinicians to make choices that best reflect their preferences for treatment of painful diabetic neuropathy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
虾仁完成签到,获得积分10
刚刚
1秒前
lilac应助啦啦啦采纳,获得10
1秒前
gy关闭了gy文献求助
1秒前
MADKAI发布了新的文献求助10
1秒前
清秀的砖头完成签到,获得积分10
1秒前
小马甲应助等待的乐儿采纳,获得10
1秒前
CodeCraft应助萌萌采纳,获得10
2秒前
2秒前
2秒前
sv发布了新的文献求助10
2秒前
LIU发布了新的文献求助10
2秒前
3秒前
3秒前
Owen应助xiuxiu_27采纳,获得10
4秒前
iW完成签到 ,获得积分10
4秒前
5秒前
woommoow完成签到,获得积分10
5秒前
6秒前
6秒前
200303am发布了新的文献求助10
6秒前
6秒前
6秒前
开天神秀完成签到,获得积分10
7秒前
566完成签到,获得积分10
7秒前
jackysuen完成签到,获得积分10
7秒前
MARS完成签到,获得积分10
8秒前
HEIKU应助鲤鱼凛采纳,获得10
9秒前
自然的依丝完成签到,获得积分20
9秒前
step_stone完成签到,获得积分10
10秒前
愉快彩虹发布了新的文献求助10
10秒前
cdu完成签到,获得积分10
11秒前
星辰轨迹完成签到,获得积分10
11秒前
MARS发布了新的文献求助10
11秒前
Jenny应助哈尼妞妞122采纳,获得10
11秒前
岁月轮回发布了新的文献求助10
12秒前
MADKAI发布了新的文献求助10
12秒前
高文强完成签到,获得积分10
12秒前
12秒前
习习应助坚定的诗双采纳,获得10
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759