Evidence mapPaperPMID 41736099Full record

ArticleCritical care (London, England)2026

Detecting the metabolic transition to personalize nutritional timing: model development and preliminary validation in a large ICU cohort.

Yonatan Gargi, Neriya Levran, Jacob Vine, Amir Cohen, Dana Weiner, Dorit Stein, Ori Levi, Dor Cohen, Julia Klein, Hamutal S Taube and 7 more

Abstract read
In one paragraph

Article in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Reply to: Timing-specific neutrality in a Rigorous ICU anabolic trial.JPEN. Journal of parenteral and enteral nutrition · 2026
    Article
  2. Review
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

17 authors.

Yonatan GargiDepartments of Anesthesiology and Intensive Care, Sheba Medical Center, Ramat Gan, Israel. Yonatan.gargi@sheba.health.gov.il.ORCID http://orcid.org/0009-0009-5498-8513
Neriya LevranDepartment of Nutrition, Sheba Medical Center, Ramat Gan, Israel.ORCID http://orcid.org/0000-0001-7043-3176
Jacob VineDepartment of Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Amir CohenDepartment of Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Dana WeinerDepartment of Nutrition, Sheba Medical Center, Ramat Gan, Israel.
Dorit SteinDepartments of Nutrition and Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Ori LeviDepartments of Anesthesiology and Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Dor CohenDepartment of Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Julia KleinIntensive Care Unit, Sheba Medical Center, Ramat Gan, Israel.
Hamutal S TaubeDepartment of Intensive Care, Sheba Medical Center, Ramat Gan, Israel.
Maxim GlebovDepartment of Anesthesiology, Sheba Medical Center, Ramat Gan, Israel.
Teddy LazebnikDepartment of Information Systems, University of Haifa, Haifa, Israel. lazebnik.teddy@is.haifa.ac.il.
Mor SabanGertner Institute for Epidemiology and Healthcare Research, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel.
Shaked EfratDepartment of Clinical Pharmacology, Sheba Medical Center, Ramat Gan, Israel.
Elad DroriDepartment of Anesthesiology, Sheba Medical Center, Ramat Gan, Israel.
Yael HavivDepartment of Intensive Care, Maaynei Hayeshua, Bnei Brak, Israel.
Eran SegalDepartment of Intensive Care, Sheba Medical Center, Ramat Gan, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe metabolic transition from catabolism to anabolism is a key determinant of recovery in critical illness and should guide nutritional therapy. However, no validated clinical marker currently exists to identify this transition, and current clinical practice relies on calendar-based recommendations. We aim to develop and preliminarily validate a physiology-based, trajectory-driven model to detect the metabolic transition window in critically ill patients.

methodsWe conducted a retrospective cohort study in a tertiary-care general ICU. A daily insulin resistance index (IRI) was computed from glucose and insulin data and corrected for steroid exposure. Transition was defined as a ≥ 30% sustained drop in IRI after its peak, together with ≥ 2 of 8 physiologic recovery criteria (lactate, noradrenaline, vasopressin, adrenaline, inflammatory markers-WBC, %neutrophils, CRP, and albumin). Associations with 90-day mortality and caloric exposure were evaluated using Kaplan–Meier analysis and multivariable landmark Cox models.

resultsThe cohort included 2,350 patients (age 59.8 ± 16.5 years; SOFA 11.7 ± 3.9; 82% mechanically ventilated). A metabolic transition was identified in 94% of patients, with ~ 60% transitioning by ICU day 3. Transition by day 3 was associated with lower 90-day mortality (HR 0.72, 95% CI 0.65–0.81). Patients who never transitioned had substantially higher mortality. High caloric delivery (≥ 1.0 kcal/kg/h for ≥ 24 h) before transition was independently associated with increased 90-day mortality (OR 1.25, 95% CI 1.01–1.55), with a dose–response pattern. In contrast, high caloric delivery based on calendar timing failed to demonstrate a similar pattern.

conclusionsWe developed and validated a physiological model for detecting metabolic transition in critical illness and showed that transition occurs early and strongly predicts survival. Higher caloric delivery before transition is associated with increased mortality, supporting nutrition strategies aligned with physiological recovery rather than fixed calendar days.

Indexed as

Critical IllnessNutritional SupportAdultAgedCohort StudiesFemaleHumansInsulin ResistanceIntensive Care UnitsMaleMiddle AgedRetrospective StudiesTime FactorsCatabolismCritical illnessInsulin resistanceIntensive careMetabolismNutrition

Identifiers

PMID41736099
PMCPMC13037178

What Socratic holds

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Registered trials

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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 Socratic graph.