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评论:在缺乏遗传数据的情况下,基于孟德尔随机化的因果推断。

Commentary: Mendelian randomization-inspired causal inference in the absence of genetic data.

机构信息

Medical Research Council Integrative Epidemiology Unit and School of Social and Community Medicine, University of Bristol, Bristol, UK.

Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU).

出版信息

Int J Epidemiol. 2017 Jun 1;46(3):962-965. doi: 10.1093/ije/dyw327.

Abstract

Studying the long-term causal effects of alcohol drinking is notoriously difficult. Epidemiological studies that use conventional analytical approaches are likely to be confounded and affected by reporting/recall bias and reverse causality, specifically in the form of the sick quitter effect (individuals quitting or never starting to consume alcohol due to underlying ill health).1 Decades of observational data showing J-shaped relationships of alcohol with risk of disease and in particular cardiovascular disease,2 fuelled by confirmation bias, have resulted in alcohol policies such that individuals are recommended to drink in moderation, due to putative cardioprotective effects. Critically, randomized controlled trials (RCTs) to investigate the long-term effects of alcohol drinking are not feasible for reasons including lack of suitable and ethical interventions and extended duration (and hence cost and likely high loss to follow-up).

摘要

研究饮酒的长期因果效应是众所周知的困难。使用传统分析方法的流行病学研究可能会受到混杂因素的影响,并受到报告/回忆偏倚和反向因果关系的影响,特别是以“患病戒酒者效应”(由于潜在的健康问题,个体戒酒或从不开始饮酒)的形式。几十年来的观察性数据显示,酒精与疾病风险,特别是心血管疾病之间存在 J 形关系,2 这种关系受到确认偏倚的推动,导致了这样的酒精政策,即建议个体适量饮酒,因为据称有心脏保护作用。至关重要的是,由于缺乏合适和符合伦理的干预措施以及较长的持续时间(因此成本高,随访率可能很高),进行饮酒长期影响的随机对照试验(RCT)是不可行的。

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