在“调查结果摘要”表格中呈现连续结果对解释提出了特别的挑战。当每个研究使用相同的结果测量时，并且该度量的单位是直观可解释的(例如，住院时间，症状持续时间)，呈现手段上的差异通常是可取的。当结果度量的自然单位不容易解释时，选择阈值来创建二元结果，并呈现相对和绝对效果成为更具吸引力的选择。当研究使用相同结构的不同度量时，计算汇总度量需要转换为每个研究的相同度量单位。最长期和最广泛使用的方法是将每个研究中的均值差异除以其标准偏差，并以标准偏差单位（标准化平均差）显示汇总结果。这种方法的缺点包括在基础人群中容易受到不同程度的异质性以及难以解释。替代方案包括以最流行或可解释的度量单位呈现结果，转换为二分法度量，并呈现相对和绝对效果，呈现干预组和对照组的手段比例，并以最小重要的差异单位呈现结果。我们概述了每种替代方案的优点和局限性，并为元分析师和指南开发人员提供指导。
结论：研究结果摘要表提供了证据质量和影响程度的简洁表述。总结连续结果的发现对解释提出了特殊的挑战，当个别试验对同一结构使用不同的措施时，这些挑战将变得令人生畏。为不同的衡量标准提供汇总估计的最常用方法，以标准偏差单位表示结果，具有与统计特性和可解释性相关的局限性。可能更可取的替代方案包括以最受欢迎的措施的自然单位呈现结果，转化为二元结果，呈现相对和绝对效果，呈现干预组和对照组的手段比例，并以预先建立的最小重要差异单位呈现结果。
Presenting continuous outcomes in Summary of Findings tables presents particular challenges to interpretation. When each study uses the same outcome measure, and the units of that measure are intuitively interpretable (e.g., duration of hospitalisation, duration of symptoms), presenting differences in means is usually desirable. When the natural units of the outcome measure are not easily interpretable, choosing a threshold to create a binary outcome and presenting relative and absolute effects become a more attractive alternative. When studies use different measures of the same construct, calculating summary measures requires converting to the same units of measurement for each study. The longest standing and most widely used approach is to divide the difference in means in each study by its standard deviation and present pooled results in standard deviation units (standardised mean difference). Disadvantages of this approach include vulnerability to varying degrees of heterogeneity in the underlying populations and difficulties in interpretation. Alternatives include presenting results in the units of the most popular or interpretable measure, converting to dichotomous measures and presenting relative and absolute effects, presenting the ratio of the means of intervention and control groups, and presenting the results in minimally important difference units. We outline the merits and limitations of each alternative and provide guidance for meta-analysts and
guideline developers.
CONCLUSIONS: Summary of Findings tables provide succinct presentations of evidence quality and magnitude of effects. Summarising the findings of continuous outcomes presents special challenges to interpretation that become daunting when individual trials use different measures for the same construct. The most commonly used approach to providing pooled estimates for different measures, presenting results in standard deviation units, has limitations related to both statistical properties and interpretability. Potentially preferable alternatives include presenting results in the natural units of the most popular measure, transforming into a binary outcome and presenting relative and absolute effects, presenting the ratio of the means of intervention and control groups, and presenting results in preestablished minimally important difference units.
