Marta Alves, Sofia Serra, Teresa Costa, Carlos Brás-Geraldes, Ana Luisa Papoila, Bruno Heleno
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引用次数: 0
摘要
目的:本综述旨在对统计模型的文献进行系统概述,以估计婴儿体重增长曲线,检查研究设计、样本量和统计方法等关键特征。生长模型最初是通过对每个个体分别建模来估计个体的生长曲线。随后,为了估计平均轨迹,提出了使用混合效应回归模型的方法。在这种情况下,更灵活的模型也被应用,能够估计更多的参数(例如,位置、规模和形状的广义加性模型;通过平移和旋转模型叠加)。纳入标准:基于前瞻性/回顾性队列或横断面研究的估计24个月以下婴儿体重增长曲线的统计/数学方法的研究将被纳入。只考虑用英语、葡萄牙语或西班牙语发表的研究。病例系列报告、评论、短信出版物、书籍和只有摘要的论文,如会议记录,将被排除在外。方法:本综述将按照JBI范围综述方法学进行。PubMed, Scopus, Web of Science Core Collection, SciELO和LILACS将搜索已发表的研究,而ProQuest和RCAAP将搜索未发表的研究。搜索结果将被导入Rayyan以删除重复项。两名审稿人将独立筛选标题、摘要和全文文章。任何分歧将通过讨论或与第三方审稿人解决。所得数据,即数学/统计方法和模型,将以表格形式摘要,并附有叙述摘要。评审注册:Open Science Framework https://osf.io/95udq。
Growth curve models for weight among infants: a scoping review protocol.
Objective: This scoping review aims to provide a systematic overview of the literature on statistical models to estimate weight growth curves among infants, examining key features such as study design, sample size, and statistical approaches.
Introduction: Growth models were first developed to estimate individuals' growth curves by modeling each individual separately. Later, with the aim of estimating mean trajectories, approaches using mixed effects regression models were proposed. More flexible models were also applied in this context, enabling the estimation of more parameters (eg, Generalized Additive Models for Location, Scale, and Shape; SuperImposition by Translation and Rotation models).
Inclusion criteria: Studies of statistical/mathematical methodologies for estimating weight growth curves of infants under 24 months of age, based on prospective/retrospective cohorts, or cross-sectional studies will be included. Only studies published in English, Portuguese, or Spanish will be considered. Case series reports, reviews, short letter publications, books, and abstract-only papers, such as conference proceedings, will be excluded.
Methods: This review will be conducted in accordance with the JBI methodology for scoping reviews. PubMed, Scopus, Web of Science Core Collection, SciELO, and LILACS will be searched for published studies, while ProQuest and RCAAP will be searched for unpublished studies. Search results will be imported into Rayyan to remove duplicates. Two reviewers will independently screen titles, abstracts, and full-text articles. Any disagreements will be resolved through discussion or with a third reviewer. The resulting data, namely mathematical/statistical approaches and models, will be summarized in tabular format, accompanied by a narrative summary.
Review registration: Open Science Framework https://osf.io/95udq.