Nevin Manimala Statistics

Estimates of Resting Energy Expenditure and Total Energy Expenditure Using Predictive Equations for Individuals After Bariatric Surgery: a Systematic Review with Meta-analysis

Obes Surg. 2023 Oct 27. doi: 10.1007/s11695-023-06908-5. Online ahead of print.


PURPOSE: Patients after metabolic bariatric surgery (MBS) require attention to maintain energy balance and avoid weight regain. Predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) are needed since gold standard methods like calorimetry and doubly labeled water are rarely available in routine clinical practice. This study aimed to determine which predictive equation for REE and TEE has the lowest bias in subjects after MBS.

METHODS: MEDLINE, Embase, Web of Science, and CENTRAL searches were performed. Meta-analyses were performed with the data calculated by the predictive equations and measured by the gold standard methods for those equations that had at least two studies with these data. The DerSimonian and Laird random-effects model and the I2 statistic were used to quantify heterogeneity in the quantitative analyses. The risk of bias was assessed using the Joanna Briggs Institute critical appraisal checklist.

RESULTS: Seven studies were included. The present study found that the Mifflin St. Jeor (1990) equation had the lowest bias (mean difference = – 39.71 kcal [95%CI = – 128.97; 49.55]) for calculating REE in post-BS individuals. The Harris-Benedict (1919) equation also yielded satisfactory results (mean difference = – 54.60 kcal [95%CI = – 87.92; – 21.28]).

CONCLUSION: The predictive equation of Mifflin St. Jeor (1990) was the one that showed the lowest bias for calculating the REE of patients following MBS.

PMID:37889369 | DOI:10.1007/s11695-023-06908-5

By Nevin Manimala

Portfolio Website for Nevin Manimala