Characterisation and evaluation of early mobilisation interventions after emergency laparotomy surgery: a scoping...

Emergency laparotomy is a high-risk surgery, and postoperative functional decline contributes to the 1-yr mortality of 25%. However, there is no established guidance around postoperative interventions to restore functional capacity, including early mobilisation. This scoping review synthesised current evidence on the definition of early mobilisation, delivery of interventions, barriers, and outcomes reported for postoperative mobilisation interventions.The review followed a structured methodological framework and was registered with Open Science Framework. Studies were identified through MEDLINE, Embase, and CINAHL. Eligible studies described an early mobilisation protocol (in isolation or as a bundled intervention) after emergency laparotomy. Data were extracted and analysed descriptively.Fourteen studies (2783 participants) were included, with all but one published since 2018. Mobilisation out of bed within 24 h of surgery was the most frequently used definition of early mobilisation. Adherence rates ranged from 31% to 96%. Interventions were heterogeneous, ranging from encouragement to achieve mobilisation targets through to comprehensive multidisciplinary programmes. Intervention groups tended to achieve earlier and greater mobilisation. Key modifiable barriers were pain, fatigue, and limited physiotherapy staffing. All studies reported physical performance outcomes; only one reported quality of life outcomes.This scoping review found heterogeneity in the delivery, dose, timing, and adherence to mobility interventions. Barriers to mobilisation after emergency laparotomy mirror those described after elective surgery. We suggest alignment in reporting the impact of individual factors (such as frailty and socioeconomic context) and core outcomes (including patient-centred measures) to standardise early postoperative mobilisation interventions and allow for synthesis of the evidence base.

Open Science Framework (https://doi.org/10.17605/OSF.IO/R63CP).