Zhang Yufang, Ma Peifen, Zhang Xiu, Pei Zhuoxi, Wang Haixia, Dou Xinman
Department of Nursing.
The Second Ward of Orthopedics Department.
Medicine (Baltimore). 2020 Oct 23;99(43):e22736. doi: 10.1097/MD.0000000000022736.
Gastrointestinal manifestations are common in patients with COVID-19, but the association between specific digestive symptoms and COVID-19 prognosis remains unclear. This study aims to assess whether digestive symptoms are associated with COVID-19 severity and mortality.
We will search PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials up to September, 2020, to identify studies that compared the prevalence of at least one specific digestive symptom between severe and non-severe COVID-19 patients or between non-survivors and survivors. Two independent reviewers will assess the risk of bias of the included cohort studies using the modified Newcastle-Ottawa Scale. Meta-analyses will be conducted to estimate the pooled prevalence of individual symptoms using the inverse variance method with the random-effects model. We will conduct subgroup analyses, sensitivity analyses, and meta-regression analyses to explore the sources of heterogeneity. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach will be used to assess the quality of the evidence.
The results of this study will be published in a peer-reviewed journal.
Our meta-analysis will comprehensively evaluate the association between different digestive symptoms and the severity and mortality of patients infected with COVID-19. This study will provide evidence to help determine whether special protective measures and treatment options are needed for patients with digestive system comorbidities during the COVID-19 pandemic.
INPLASY202090055.
胃肠道表现在新型冠状病毒肺炎(COVID-19)患者中很常见,但特定消化症状与COVID-19预后之间的关联仍不清楚。本研究旨在评估消化症状是否与COVID-19的严重程度和死亡率相关。
我们将检索截至2020年9月的PubMed、Embase、Web of Science和Cochrane对照试验中央注册库,以识别比较重症和非重症COVID-19患者之间或非幸存者与幸存者之间至少一种特定消化症状患病率的研究。两名独立的评审员将使用改良的纽卡斯尔-渥太华量表评估纳入队列研究的偏倚风险。将采用随机效应模型的逆方差法进行荟萃分析,以估计个体症状的合并患病率。我们将进行亚组分析、敏感性分析和荟萃回归分析,以探索异质性的来源。将使用推荐分级评估、制定和评价(GRADE)方法评估证据质量。
本研究结果将发表在同行评审期刊上。
我们的荟萃分析将全面评估不同消化症状与COVID-19感染患者的严重程度和死亡率之间的关联。本研究将提供证据,以帮助确定在COVID-19大流行期间,消化系统合并症患者是否需要特殊的保护措施和治疗方案。
INPLASY注册号:INPLASY202090055。