Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients?
Abstract Introduction Numerous 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 clin...
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BMC
2025-04-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02477-8 |
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| author | Lea Gröbli Yannik Kalbas Franziska Kessler Jakob Hax Teuben Michel Kai Sprengel Roman Pfeifer Martin Mächler Hans-Christoph Pape Sascha Halvachizadeh Felix Karl-Ludwig Klingebiel |
| author_facet | Lea Gröbli Yannik Kalbas Franziska Kessler Jakob Hax Teuben Michel Kai Sprengel Roman Pfeifer Martin Mächler Hans-Christoph Pape Sascha Halvachizadeh Felix Karl-Ludwig Klingebiel |
| author_sort | Lea Gröbli |
| collection | DOAJ |
| description | Abstract Introduction Numerous 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). Methods Retrospective 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. Results Inclusion 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. Conclusions The 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). |
| format | Article |
| id | doaj-art-913f3abaa38144a7b60e0416bceaecf9 |
| institution | DOAJ |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
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| series | European Journal of Medical Research |
| spelling | doaj-art-913f3abaa38144a7b60e0416bceaecf92025-08-20T03:04:59ZengBMCEuropean Journal of Medical Research2047-783X2025-04-0130111110.1186/s40001-025-02477-8Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients?Lea Gröbli0Yannik Kalbas1Franziska Kessler2Jakob Hax3Teuben Michel4Kai Sprengel5Roman Pfeifer6Martin Mächler7Hans-Christoph Pape8Sascha Halvachizadeh9Felix Karl-Ludwig Klingebiel10Department of Trauma Surgery, University Hospital Zurich, University of ZurichDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichHarald-Tscherne Laboratory for Orthopaedic and Trauma Research, University Hospital Zurich, University of ZurichDepartment of Knee and Hip Surgery, Schulthess KlinikDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichFaculty of Health Sciences and Medicine, Hirslanden Clinic St. Anna, University of LucerneDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichSeminar of Statistics, ETH ZurichDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichDepartment of Trauma Surgery, University Hospital Zurich, University of ZurichAbstract Introduction Numerous 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). Methods Retrospective 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. Results Inclusion 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. Conclusions The 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).https://doi.org/10.1186/s40001-025-02477-8PolytraumaPredictionComplicationsArtificial intelligence |
| spellingShingle | Lea Gröbli Yannik Kalbas Franziska Kessler Jakob Hax Teuben Michel Kai Sprengel Roman Pfeifer Martin Mächler Hans-Christoph Pape Sascha Halvachizadeh Felix Karl-Ludwig Klingebiel Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? European Journal of Medical Research Polytrauma Prediction Complications Artificial intelligence |
| title | Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? |
| title_full | Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? |
| title_fullStr | Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? |
| title_full_unstemmed | Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? |
| title_short | Are the same parameters measured at admission and in the ICU comparable in their predictive values for complication and mortality in severely injured patients? |
| title_sort | are the same parameters measured at admission and in the icu comparable in their predictive values for complication and mortality in severely injured patients |
| topic | Polytrauma Prediction Complications Artificial intelligence |
| url | https://doi.org/10.1186/s40001-025-02477-8 |
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