Developing a taxonomy to describe offspring outcomes in studies involving pregnant mammals' exposure to non-tobacco nicotine: A systematic scoping review

构建分类体系以描述妊娠哺乳动物暴露于非烟草尼古丁的研究中后代结局:一项系统性范围综述

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Abstract

INTRODUCTION: Many countries recommend Nicotine Replacement Therapy (NRT) for smoking cessation in pregnancy. Preclinical studies of nicotine exposure to pregnant mammals could indicate how nicotine may adversely affect the developing fetus. As a first step towards summarising this literature, we undertook a systematic scoping review to determine the number and nature of offspring outcomes studied. METHODS: We searched MEDLINE and EMBASE databases for papers reporting empirical data on offspring outcomes following nicotine exposure to pregnant non-human mammals. We excluded studies that investigated exposure to only smoking, e-cigarettes, nicotine vaccines, or studies with no 'nicotine only' group. We developed a draft taxonomy and using this, described and quantified outcomes reported. RESULTS: We identified 476 studies, which reported 729 offspring outcomes. The draft taxonomy classified outcomes as being measured in i) whole animals, ii) body systems and iii) 'other'. Body system outcomes were further categorised as being functional changes, or changes at macroscopic or cellular levels. The most frequently used outcomes were those detecting changes in the brain (n = 265), physical parameters measured in whole animals (n = 122) and any respiratory system changes (n = 97). CONCLUSIONS: This scoping review quantifies the nature and frequency of outcomes used in preclinical studies investigating the potential impacts of nicotine administration in pregnancy on offspring. Systematic reviews of studies investigating outcomes involving animal brains, respiratory system, or 'whole animal' outcomes may have greatest potential for further advancing knowledge regarding impacts of gestational nicotine exposure on offspring. PROTOCOL AND REGISTRATION: Protocol for this review can be found on Open Science Framework (https://osf.io/ptmzc/).

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