Evidence map›Paper›PMID 39178568›Full record

Trial reportThe Journal of surgical research2024

Predictive Energy Equations Inaccurately Estimate Metabolic Demands of Older Adult Trauma Patients.

Krista L Haines, Julie Walsh, Trevor Sytsma, Chidinma Tiko-Okoye, Jeroen Molinger, Shauna Howell, Suresh Agarwal, Cory Vatsaas, Christopher E Cox, Ken Schmader and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in The Journal of surgical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Krista L HainesDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina; Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina; Department of Anesthesiology, Division of Critical Care, Human Pharmacology and Physiology Laboratory (HPPL), Duke University School of Medicine, Durham, North Carolina. Electronic address: krista.haines@duke.edu.
Julie WalshDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Trevor SytsmaDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Chidinma Tiko-OkoyeDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Jeroen MolingerDepartment of Anesthesiology, Division of Critical Care, Human Pharmacology and Physiology Laboratory (HPPL), Duke University School of Medicine, Durham, North Carolina.
Shauna HowellDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Suresh AgarwalDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Cory VatsaasDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina.
Christopher E CoxDepartment of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Duke University School of Medicine, Durham, North Carolina.
Ken SchmaderDepartment of Medicine, Division of Geriatrics, Duke University School of Medicine, and GRECC, Durham VA Health Care System, Durham, North Carolina.
Paul E WischmeyerDepartment of Surgery, Division of Trauma, Acute, and Critical Care Surgery, Duke University School of Medicine, Durham, North Carolina; Department of Anesthesiology, Division of Critical Care Medicine, Duke University School of Medicine, Durham, North Carolina.

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI CATHLEEN S COLON-EMERIC, Susan Nicole Hastings · 2006 to 2026
$24.6M
NIA NIH HHS P30 AG028716
6 · The paper itself

Abstract

introductionSuboptimal nutrition promotes unfavorable outcomes in trauma patients, particularly among those aged 60 and over. While many institutions employ predictive energy equations to determine patients' energy requirements, mounting evidence shows these equations inaccurately estimate caloric needs. In this pilot randomized controlled trial, we sought to quantify the discrepancy between predictive equations and indirect calorimetry (IC)-the gold standard for determining energy requirements-in the older adult trauma population.

methodsThis is a nested cohort study within a pilot randomized control trial in which 32 older adult trauma patients were randomized 3:1 to receive IC-guided nutrition delivery versus standard of care. IC requirements of patients in the intervention arm were compared to Mifflin St. Jeor (MSJ), Harris-Benedict (HB), and the American Society for Parenteral and Enteral Nutrition-Society of Critical Care Medicine (ASPEN-SCCM) predictive energy equations.

resultsTwenty patients underwent IC to assess measured resting energy expenditure (mREE), yielding a mean (standard deviation) mREE of 23.1 ± 4.8 kcal/kg/d. MSJ and HB gave mean predictive resting energy expenditures of 17.5 ± 2.0 and 18.5 ± 2.0 kcal/kg/d in these patients, demonstrating that IC-derived values were 32.1% and 25.0% higher, respectively. When patients were stratified by body mass index (BMI), MSJ, and HB more severely underestimated caloric requirements in individuals with BMI <30 versus BMI 30-50. While the mean mREE fell within the mean predictive resting energy expenditure range prescribed by ASPEN-SCCM equations (21.4 ± 4.1 to 26.2 ± 4.3 kcal/kg/d), individuals' IC-derived values fell within their personal range in 8 of 20 cases.

conclusionsThe MSJ and HB predictive energy equations consistently and significantly underpredict metabolic demands of older adult trauma patients compared to IC and perform worse in lower BMI individuals. ASPEN-SCCM equations frequently overpredict or underpredict resting energy expenditure. While these findings should be confirmed in a larger randomized control trial, this study suggests that institutions should prioritize IC to accurately identify the metabolic demands of older trauma patients.

Indexed as

Calorimetry, IndirectEnergy MetabolismNutritional RequirementsWounds and InjuriesAgedAged, 80 and overEnergy IntakeFemaleHumansMaleMiddle AgedPilot ProjectsGeriatric trauma careIndirect calorimetryMetabolic requirementsPredictive energy equationsResting energy expenditure

Identifiers

PMID39178568
PMCPMC12928209

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.