Evidence map›Paper›PMID 41000662›Full record

ArticlebioRxiv : the preprint server for biology2025

Metabolic Trajectories During Surgical Stress in Patients Undergoing Cardiac Surgery.

Dohyun Ku, Jackson Bartelt, Jenna Feeley, M Citlalli Perez-Guzman, Lizda Guerrero-Arroyo, Amalia Abraham, Saaki Kollipara, Nicolas Gonzalez, Sabeena Usman, Helaina E Huneault and 10 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Dohyun KuH. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA.
Jackson BarteltDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Jenna FeeleyDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
M Citlalli Perez-GuzmanDepartment of Medicine, Division of Endocrinology, Queen's University, Kingston, Ontario, Canada.
Lizda Guerrero-ArroyoDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Amalia AbrahamDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Saaki KolliparaDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Nicolas GonzalezDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Sabeena UsmanDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Helaina E HuneaultNutrition & Health Sciences Doctoral Program, Laney Graduate School, Emory University, Atlanta, GA.
Andrea Corujo-RodriguezDepartment of Anesthesiology, Emory University, Atlanta, GA.
Georgia M DavisDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Richard G KibbeyDepartments of Internal Medicine (Endocrinology) and Cellular & Molecular Physiology, Yale University, New Haven, CT.
Dean P JonesDepartment of Medicine, Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University, Atlanta, GA.
Thomas R ZieglerDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.
Michael HalkosDepartment of Surgery, Emory School of Medicine, Atlanta, GA.
Arshed A QuyyumiEmory Clinical Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
M Ryan SmithDepartment of Medicine, Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University, Atlanta, GA.
Jing LiH. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA.
Francisco J PasquelDepartment of Medicine, Division of Endocrinology, Emory University School of Medicine, Atlanta, GA.

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Pilot Project ProgramP30ES019776 · NIEHS · EMORY UNIVERSITY · PI Carmen Joseph Marsit · 2013 to 2026
$22.6M
J: NRSA Training CoreTL1TR002382 · NCATS · EMORY UNIVERSITY · PI HENRY M BLUMBERG, Vasiliki Michopoulos · 2017 to 2026
$8.5M
Metabolic Phenotyping During Stress Hyperglycemia in Cardiac Surgery PatientsK23GM128221 · NIGMS · EMORY UNIVERSITY · PI PASQUEL, FRANCISCO J · 2018 to 2022
$957k
BLRD VA IK2 BX005913NCATS NIH HHS TL1 TR002382NCATS NIH HHS UL1 TR002378NIEHS NIH HHS P30 ES019776NIGMS NIH HHS K23 GM128221
6 · The paper itself

Abstract

Stress hyperglycemia (SH) during acute illness is linked to adverse surgical outcomes, yet the accompanying metabolic perturbations are incompletely characterized. We profiled longitudinal metabolic changes in adults without diabetes undergoing cardiac surgery to identify pathways associated with perioperative SH (defined as point of care glucose ≥140 mg/dL on ≥3 readings or ≥180 mg/dL once). Blood was collected at baseline before surgery (T0) and at 2 h (T1), 24-48 h (T2), and 72-96 h (T3) after surgical initiation. High resolution metabolomics (LC-MS) was integrated with continuous glucose monitoring and inflammatory/cardiac biomarkers. At T0, several pathways were associated with subsequent SH, including bile acid metabolism, the carnitine shuttle, and fatty acid oxidation, suggesting preoperative metabolic susceptibility. In longitudinal analyses, participants who developed SH showed coordinated postoperative changes with significant enrichment of pathways not evident at baseline, C21 steroid hormone biosynthesis, glycerophospholipid metabolism, and glycosphingolipid (ceramide) metabolism, consistent with lipid remodeling and inflammatory signaling during surgical stress. Individuals with SH also exhibited higher inflammatory biomarker levels (high sensitivity C reactive protein and soluble urokinase plasminogen activator receptor). A machine learning model using early metabolomic features predicted SH with an area under the receiver operating characteristic curve of 0.86. These findings highlight distinct preoperative and perioperative metabolic trajectories associated with SH and implicate established dysglycemia-related pathways, as well as stress-induced pathways in perioperative metabolic dysregulation. Pathway enrichment analyses were exploratory and hypothesis-generating; validation in larger cohorts and assessment of implications for clinical outcomes are warranted.

Indexed as

CABGcardiac outcomesCGMmetabolomicsPerioperative stress hyperglycemia

Identifiers

PMID41000662
PMCPMC12458452

What OpenQuestion holds

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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.