Evidence map›Paper›PMID 38778361›Full record

ArticleEuropean journal of medical research2024

Opportunistic screening for long-term muscle wasting in critically ill patients: insights from an acute pancreatitis cohort.

Johannes Kolck, Clarissa Hosse, Alexandra Leimbach, Nick L Beetz, Timo A Auer, Federico Collettini, Uli Fehrenbach, Christian Pille, Dominik Geisel

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Article in European journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Johannes KolckDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany. Johannes.kolck@charite.de.ORCID http://orcid.org/0000-0001-9843-2247
Clarissa HosseDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Alexandra LeimbachDepartment of Anesthesiology and Intensive Care Medicine | CCM | CVK, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Nick L BeetzDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Timo A AuerDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Federico CollettiniDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Uli FehrenbachDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
Christian PilleDepartment of Anesthesiology and Intensive Care Medicine | CCM | CVK, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Dominik GeiselDepartment of Radiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the feasibility of long-term muscle monitoring, we implemented an AI-guided segmentation approach on clinically indicated Computed Tomography (CT) examinations conducted throughout the hospitalization period of patients admitted to the intensive care unit (ICU) with acute pancreatitis (AP). In addition, we aimed to investigate the potential of muscle monitoring for early detection of patients at nutritional risk and those experiencing adverse outcomes. This cohort served as a model for potential integration into clinical practice. MATERIALS: Retrospective cohort study including 100 patients suffering from AP that underwent a minimum of three CT scans during hospitalization, totaling 749 assessments. Sequential segmentation of psoas muscle area (PMA) was performed and was relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan was calculated. Subgroup and outcome analyses were performed including ANOVA. Discriminatory power of muscle decay rates was evaluated using ROC analysis.

resultsMonitoring PMA decay revealed significant long-term losses of 48.20% throughout the hospitalization period, with an average daily decline of 0.98%. Loss rates diverged significantly between survival groups, with 1.34% PMA decay per day among non-survivors vs. 0.74% in survivors. Overweight patients exhibited significantly higher total PMA losses (52.53 vs. 42.91%; p = 0.02) and average PMA loss per day (of 1.13 vs. 0.80%; p = 0.039). The first and the maximum decay rate, in average available after 6.16 and 17.03 days after ICU admission, showed convincing discriminatory power for survival in ROC analysis (AUC 0.607 and 0.718). Both thresholds for maximum loss (at 3.23% decay per day) and for the initial loss rate (at 1.98% per day) proved to be significant predictors of mortality.

conclusionsThe innovative AI-based PMA segmentation method proved robust and effortless, enabling the first comprehensive assessment of muscle wasting in a large cohort of intensive care pancreatitis patients. Findings revealed significant muscle wasting (48.20% on average), particularly notable in overweight individuals. Higher rates of initial and maximum muscle loss, detectable early, correlated strongly with survival. Integrating this tool into routine clinical practice will enable continuous muscle status tracking and early identification of those at risk for unfavorable outcomes.

Indexed as

Critical IllnessPancreatitisTomography, X-Ray ComputedAcute DiseaseAdultAgedFemaleHospitalizationHumansIntensive Care UnitsMaleMiddle AgedMuscular AtrophyPsoas MusclesRetrospective StudiesAcute pancreatitisArtificial intelligenceComputed tomographyCritical careMuscle wasting

Identifiers

PMID38778361
PMCPMC11110383

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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.