Evidence map›Paper›PMID 40176162›Full record

ArticleEuropean journal of medical research2025

Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients?

Lea Gröbli, Yannik Kalbas, Franziska Kessler, Jakob Hax, Teuben Michel, Kai Sprengel, Roman Pfeifer, Martin Mächler, Hans-Christoph Pape, Sascha Halvachizadeh and 1 more

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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

11 authors.

Lea GröbliDepartment of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.
Yannik KalbasDepartment of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-1550-328X
Franziska KesslerHarald-Tscherne Laboratory for Orthopaedic and Trauma Research, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0009-0009-9084-3549
Jakob HaxDepartment of Knee and Hip Surgery, Schulthess Klinik, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-7641-052X
Teuben MichelDepartment of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-0310-4668
Kai SprengelFaculty of Health Sciences and Medicine, Hirslanden Clinic St. Anna, University of Lucerne, 6006, Lucerne, Switzerland.ORCID http://orcid.org/0000-0001-5921-8272
Roman PfeiferDepartment of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-1543-3995
Martin MächlerSeminar of Statistics, ETH Zurich, 8092, Zurich, Switzerland.
Hans-Christoph PapeDepartment of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-2059-4980
Sascha Halvachizadeh *Department of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-1393-3232
Felix Karl-Ludwig Klingebiel *Department of Trauma Surgery, University Hospital Zurich, University of Zurich, Raemistr. 100, 8091, Zurich, Switzerland. felixkarl-ludwig.klingebiel@usz.ch.ORCID http://orcid.org/0000-0002-6438-5208

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNumerous studies have investigated variables that predict mortality and complications following severe trauma. These studies, however, mainly focus on admission values or a single variable. The aim of this study was to investigate the predictive quality of multiple routine clinical measurements (at admission and in the ICU).

methodsRetrospective cohort study of severely injured patients treated at one Level 1 academic trauma centre. INCLUSION CRITERIA: severe injury (ISS ≥ 16 points), primary admission and complete data set. Exclusion criteria end-of-life treatment based on advanced directive, secondary transferred patients. PRIMARY OUTCOME: mortality, pneumonia, sepsis. Routine clinical parameters were stratified based on measurement timepoint into Group TB (Trauma Bay, admission) and into Group intensive care unit (ICU, 72 h after admission). Prediction of complications and mortality were calculated using two prediction methods: adaptive boosting (AdaBoost, artificial intelligence, AI) and LASSO regression analysis.

resultsInclusion of 3668 cases. Overall mean age 45.5 ± 20 years, mean ISS 28.2 ± 15.1 points, incidence pneumonia 19.0%, sepsis 14.9%, death from haemorrhagic shock 4.1%, death from multiple organ failure 1.9%, overall mortality rate 26.8%. Highest predictive value for complications for Group TB include abbreviated injury scale (AIS), new injury severity score (NISS) and systemic Inflammatory Response Syndrome (SIRS) score. Highest predictive quality for complications for Group ICU include late lactate values, haematocrit, leukocytes, and CRP. Sensitivity and specificity of late prediction models using a 25% cutoff were 73.61% and 76.24%, respectively.

conclusionsThe predictive quality of routine clinical measurements strongly depends on the timepoint of the measurement. Upon admission, the injury severity and affected anatomical regions are more predictive, while during the ICU stay, laboratory parameters are better predictor of adverse outcomes. Therefore, the dynamics of pathophysiologic responses should be taken into consideration, especially during decision making of secondary definitive surgical interventions. LEVEL OF EVIDENCE: III (retrospective cohort study).

Indexed as

Intensive Care UnitsWounds and InjuriesAdultAgedFemaleHumansMaleMiddle AgedPatient AdmissionPredictive Value of TestsRetrospective StudiesSepsisArtificial intelligenceComplicationsPolytraumaPrediction

Identifiers

PMID40176162
PMCPMC11963442

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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.