Optimal Estimate for Energy Requirements in Adult Patients With the m.3243A>G Mutation in Mitochondrial DNA

Aim We aimed to identify the optimal method to estimate total energy expenditure (TEE) in mitochondrial disease (MD) patients. Methods Resting energy expenditure (REE) was measured in MD patients carrying the m3243A>G mutation using indirect calorimetry (IC) and compared with results of 21 predictive equations (PEs) for REE and with REE-IC measurements in healthy controls. Physical activity level (PAL) was measured using accelerometery (SenseWear) and compared with a fixed average PAL (1.4) as well as patients' self-estimated activity levels. TEE was calculated as REE-IC x PAL SenseWear and compared with usual care and energy recommendations for healthy adults. Results Thirty-eight MD patients (age: 48 +/- 13 years; body mass index 24 +/- 4 kg/m(2); male 20%) and 25 matched controls were included. The accuracy of most PEs was between 63% and 76%. The difference in REE-IC in healthy controls (1532 +/- 182 kcal) and MD patients (1430 +/- 221) was borderline not significant (P= .052). Patients' PAL estimations PAL were 18%-34% accurate at the individual level. The fixed activity factor was 53% accurate. Patients overestimated their PAL. Usual care predicted TEE accurately in only 32% of patients. Conclusion TEE is lower in these MD patients than the recommendations for healthy adults because of their lower physical activity. In MD patients, 6 PEs for REE provide a reliable alternative for IC, with an accuracy of 71%-76%. As PAL is highly variable and not reliably estimated by patients, measurement of PAL using accelerometery is recommended in this population.

Automated summary

The aim of this study was to identify the optimal method for estimating total energy expenditure (TEE) in patients with mitochondrial disease (MD). It was found that TEE in MD patients is lower than recommended for healthy adults due to lower physical activity. Predictive equations (PEs) for resting energy expenditure (REE) provide a reliable alternative to indirect calorimetry (IC) in MD patients, with an accuracy of 71% to 76%. Accelerometry is recommended for measuring PAL in this population as patients' estimations of PAL are highly variable and unreliable.