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Abstract
Purpose Calculation of estimated energy requirements (EER) is critical in achieving nutritional targets in pre-lung transplantation (LT) candidates. This study compared bedside prediction of EER using simple equations with a more complex technology based EER using a multisensor device (Sensewear v8.1, SW). SW estimated energy requirements was then compared to estimated energy intake (EEI) at pre-LT assessment. Methods Single institution retrospective cross-sectional observational study of adult patients assessed for LT between Oct 2016 and Apr 2019. Patients wore the SW device on their left tricep for a minimum of 3 days. Patients with poor compliance, Results 117 patients were included. 55% male, mean age 51.8 ±13.8years, BMI 25.1±4.5kg/m2. 4 patients were assessed as underweight, 53 healthy weight, 44 overweight and 17 obese. 17% of patients were assessed as malnourished (SGA-B, mild-moderately malnourished). Respiratory disease: CF (15%), COPD (41%), IPF (31%), other (13%). Food record data existed for 82% of candidates (n=96). There was strong agreement between all predictive equations and SW. Schofield had the strongest correlation (0.836, p Conclusion Whilst all EER equations correlated well with SW as the reference standard, Schofield had the strongest agreement with SW, while larger variations were observed with other equations (over/underestimation) which may be clinically relevant for some patients. EER predictive energy equations provide a simple, rapid and accurate assessment of nutritional requirements in pre-lung transplantation.
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