Aims:The aim was to synthesise and discuss predictors of complete oral feeding resumption after feeding tube placement in stroke patients with dysphagia.Design: This was a systematic review, following the PRISMA 2020 checklist. Data sources: Eight databases (PubMed, Web of Science, Embase, Cochrane, CINAHL, CNKI, WanFang and Vip) were searched for eligible studies from inception up to June 2021.
Review methods:The JBI Manual for Evidence Synthesis was used to guide this systematic review. Any cross-sectional survey, longitudinal study, cohort study or casecontrol study that explored the recovery from tube feeding to complete oral feeding in patients with dysphagia after stroke was included. Qualitative studies, review articles, case reports and conference abstracts were excluded. Two reviewers independently screened and appraised the studies. The Newcastle-Ottawa scale was used for quality assessment. Content analysis was used to categorise factors predicting feeding tube removal in stroke patients with dysphagia.Results: This review included a total of 15 studies consisting of 1746 participants, of which 2 were case-control studies and 13 were cohort studies. Four studies were rated as having low risk of bias, and the other 11 had high risk of bias. The factors examined in the studies were categorised into demographic characteristics (age and sex), swallowing function (instrumental assessments and non-instrumental assessments), stroke characteristics (stroke severity, past stroke history and location of the stroke), functional status (cognitive function and physical function) and clinical measures (body mass index, geriatric nutritional risk index, white blood cell count and Creactive protein level).
Conclusions:The major limitation of this review is the failure to identify predictors of different tube feeding types. Although the current evidence is insufficient to support or oppose the predictive effect of any single factor, these factors are still valuable data for clinical staff that provide information that researchers can use in developing prognostic models. Rigorously designed and high-quality research is needed to further explore the predictive value of these factors.