Abstract

Enteral feeding is very common following an acquired brain injury. However, no prognostic models for oral food intake have been developed for subacute rehabilitation. The aim of this study was to develop a prognostic model and online tool, coined "subacute prognosis of oral nutrition" (SPOON), for complete oral intake in tube-fed subjects with acquired brain injury. The model was developed using routinely gathered clinical data from a cohort of 1233 adult patients who were tube-fed at admission for sub-acute inpatient rehabilitation. Candidate predictors were included based on scientific evidence and their availability in the medical records within the first days following admission. The outcome was time until achieving complete oral food intake without any tube-feeding supplements. Time until complete oral intake was analyzed by discrete time-to-event analysis with logit-link and presented as daily odds ratios (OR) with 95% confidence intervals (CI). The following predictors of complete oral intake were included in the model: age, diagnosis, cuffed tracheostomy tube, days from injury to admission for rehabilitation, and the Early Functional Abilities (EFA) sum score. Multiple adjusted analyses were performed stratified by cuffed tracheostomy tube status. Some of the strongest predictors of complete oral intake were age 18-40 years, OR 1.99 (95%CI: 1.53; 2.59); 0-2 weeks since injury, OR 3.75 (95%CI: 2.72; 5.16); and EFA 61-100 (slight/no disturbance in function), OR 5.81 (95%CI: 4.47; 7.55). The online prognostic tool SPOON was evaluated in a usability study. Based on feedback from clinicians, the tool was further refined to enable extraction of data for prediction directly from medical records. The objective of SPOON is to complement the planning of rehabilitation initiatives and inform discussions to determine if a percutaneous endoscopic gastrostomy (PEG) tube should be inserted. SPOON is being implemented locally, but external validation based on appropriate data modeling is warranted before further clinical implementation.

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