ArticleNutrients2026
Recalibrating Resting Energy Expenditure Prediction Equations in Asian Older Adults with Multimorbidity.
Article in Nutrients, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
BACKGROUND/
objectiveAccurate resting energy expenditure (REE) estimation is paramount for the nutritional management of older Asian adults with multimorbidity. However, standard predictive equations (PEs) lack precision for this cohort. This study aimed to recalibrate PEs using BMI-stratified, slope-only regression to enhance bedside accuracy.
methodsREE was measured via indirect calorimetry in 400 hospitalized patients (age ≥ 65). Sensitivity analyses identified significant proportional bias in existing models. Models were recalibrated and validated using 1000-iteration bootstrap resampling.
resultsStandard PEs exhibited significant bias, particularly overpredicting requirements for 68% of underweight patients. The new Singapore Older Adults Resting energy expenditure (SOAR) PE 1 (963.67 + 8.56 × weight - 5.6 × age) eliminated weight-dependent systematic errors. The recalibrated models utilizing actual body weight achieved accuracy rates of up to 64% in obese cohorts, comparable to complex adjusted-weight protocols.
conclusionsPopulation-specific recalibration is essential to mitigate the bidirectional risks of malnutrition and overfeeding in geriatric rehabilitation. The BMI-stratified multipliers provided offer a robust, clinically efficient framework for individualized nutritional care.
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