ICU Management of Trauma Patients

What trauma patients need: the European dilemma

There is a need for implementation and maturation of an inclusive trauma system in every country in Europe, with patient centered care by dedicated surgeons. This process should be initiated by physicians and medical societies, based on the best available evidence, and supported and subsequently funded by the government and healthcare authorities. A systematic approach to organizing all aspects of trauma will result in health gain in terms of quality of care provided, higher survival rates, better functional outcomes and quality of life. In addition, it will provide reliable data for both research, quality improvement and prevention programs. Severely injured patients need surgeons with broad technical and non-technical competencies to provide holistic, inclusive and compassionate care. Here we describe the philosophy of the surgical approach and define the necessary skills for trauma, both surgical and other, to improve outcome of severely injured patients. As surgery is an essential part of trauma care, surgeons play an important role for the optimal treatment of trauma patients throughout and after their hospital stay, including the intensive care unit (ICU). However, in most European countries, it might not be obvious to either the general public, patients or even the physicians that the surgeon must assume this responsibility in the ICU to optimize outcomes. The aim of this paper is to define key elements in terms of trauma systems, trauma-specific surgical skills and active critical care involvement, to organize and optimize trauma care in Europe.

Development and validation of an artificial intelligence mobile application for predicting 30-day mortality in critically ill patients with orthopaedic trauma

BACKGROUND

Given the intricate and grave nature of trauma-related injuries in ICU settings, it is imperative to develop and deploy reliable predictive tools that can aid in the early identification of high-risk patients who are at risk of early death. The objective of this study is to create and validate an artificial intelligence (AI) model that can accurately predict early mortality among critical fracture patients.

METHODS

A total of 2662 critically ill patients with orthopaedic trauma were included from the MIMIC III database. Early mortality was defined as death within 30 days in this study. The patients were randomly divided into a model training cohort and a model validation cohort. Various algorithms, including logistic regression (LR), extreme gradient boosting machine (eXGBM), decision tree (DT), support vector machine (SVM), random forest (RF), and neural network (NN), were employed. Evaluation metrics, including discrimination and calibration, were used to develop a comprehensive scoring system ranging from 0 to 60, with higher scores indicating better prediction performance. Furthermore, external validation was carried out using 131 patients. The optimal model was deployed as an internet-based AI tool.

RESULTS

Among all models, the eXGBM demonstrated the highest area under the curve (AUC) value (0.974, 95%CI: 0.959-0.983), followed by the RF model (0.951, 95%CI: 0.935-0.967) and the NN model (0.922, 95%CI: 0.905-0.941). Additionally, the eXGBM model outperformed other models in terms of accuracy (0.915), precision (0.906), recall (0.926), F1 score (0.916), Brier score (0.062), log loss (0.210), and discrimination slope (0.767). Based on the scoring system, the eXGBM model achieved the highest score (53), followed by RF (42) and NN (39). The LR, DT, and SVM models obtained scores of 28, 18, and 32, respectively. Decision curve analysis further confirmed the superior clinical net benefits of the eXGBM model. External validation of the model achieved an AUC value of 0.913 (95%CI: 0.878-0.948). Consequently, the model was deployed on the Internet at https://30-daymortalityincriticallyillpatients-fnfsynbpbp6rgineaspuim.streamlit.app/, allowing users to input patient features and obtain predicted risks of early mortality among critical fracture patients. Furthermore, the AI model successfully stratified patients into low or high risk of early mortality based on a predefined threshold and provided recommendations for appropriate therapeutic interventions.

CONCLUSION

This study successfully develops and validates an AI model, with the eXGBM algorithm demonstrating the highest predictive performance for early mortality in critical fracture patients. By deploying the model as a web-based AI application, healthcare professionals can easily access the tool, enabling them to predict 30-day mortality and aiding in the identification and management of high-risk patients among those critically ill with orthopedic trauma.

Plasma interleukin responses as predictors of outcome stratification in patients after major trauma: a prospective observational two centre study

Background and objectives

There is a need to develop objective risk stratification tools to define efficient care pathways for trauma patients. Biomarker-based point of care testing may strengthen existing clinical tools currently available for this purpose. The dysregulation of pro- and anti-inflammatory cytokines in the pathogenesis of organ failure is well recognised. This study was carried out to evaluate whether blood concentrations of IL-6, IL-10, and IL-6:IL-10 ratios in the early stages of the illness are significantly different in patients with worsening organ function.

Materials and methods

In this prospective observational cohort study, plasma concentrations of IL-6 and IL-10 on days 1, 3 and 5 were measured in 91 major trauma patients using a multiplexed cytometric bead array approach. A composite measure of adverse outcome - defined as SOFA ≥ 2 or mortality at 7 days, was the primary outcome. IL-6 and IL-10 concentrations in early samples (days 1, 3 & 5) in patients who developed SOFA ≥ 2 on day 7 were compared against those who did not. Similar composite outcome groups at day 5 and in groups with worsening or improving SOFA scores (ΔSOFA) at days 7 and 5 were undertaken as secondary analyses.

Results

Stratification on day 7, 44 (48%) patients showed adverse outcomes. These adverse outcomes associated with significantly greater IL-6 concentrations on days 1 and 5 (Day 1: 47.65 [23.24-78.68] Vs 73.69 [39.93 - 118.07] pg/mL, P = 0.040 and Day 5: 12.85 [5.80-19.51] Vs 28.90 [8.78-74.08] pg/mL; P = 0.0019). Similarly, IL-10 levels were significantly greater in the adverse outcome group on days 3 and 5 (Day 3: 2.54 [1.76-3.19] Vs 3.16 [2.68-4.21] pg/mL; P = 0.044 and Day 5: 2.03 [1.65-2.55] Vs 2.90 [2.00-5.06] pg/mL; P <0.001). IL-6 and IL-10 concentrations were also significantly elevated in the adverse outcome groups at day 3 and day 5 when stratified on day 5 outcomes. Both IL-6 and IL-6:IL-10 were found to be significantly elevated on days 1 and 3 when stratified based on ΔSOFA at day 5. This significance was lost when stratified on day 7 scores.

Conclusions

Early IL-6 and IL-10 concentrations are significantly greater in patients who develop worsening organ functions downstream. These differences may provide an alternate biomarker-based approach to strengthen risk stratification in trauma patients.

Exploring the competencies of Chinese critical care nurses in mobile medical teams based on the onion model: A qualitative study

BACKGROUND

With frequent conflicts, natural disasters, and public health emergencies globally, mobile medical teams (MMTs) are becoming increasingly critical. Importantly, the competency of critical care nurses in MMTs can substantially affect the effectiveness and quality of its rescue efforts. Yet, these nurses' competencies are not well understood.

AIM

This study examined the competencies of critical care nurses in MMTs using the Onion Model.

DESIGN

A qualitative descriptive method was used to describe the competencies of Chinese MMT critical care nurses.

METHODS

From April to May 2022, a convenience sample of 18 participants (14 critical care nurses and 4 surgeons) from 10 MMTs was recruited for semi-structured interviews. Deductive and inductive coding methods were combined for content analysis.

RESULTS

In total, 29 competencies were identified, which were grouped into four major domains using the Onion Model. From the outer to inner layers, these domains were knowledge and skills, professional abilities, professional quality, and personal traits. Several novel competencies emerged, including field medical equipment operation skills, on-site hazard identification and safety prevention skills, triage knowledge, and field survival skills.

CONCLUSIONS

Using the Onion Model, this study furthers the understanding of the competency of critical care nurses in MMTs, especially by revealing the novel competencies. Further, the results can be used to recruit, evaluate, and train critical care nurses for MMTs.

RELEVANCE TO CLINICAL PRACTICE

Understanding MMT critical care nurses' competencies can help managers plan and provide relevant training and education before deployment, which can improve nurses' performance, and especially reduce the mortalities and disabilities from trauma.

"Stabilize the Unstable": Treatment Pathophysiology in Bleeding Trauma Patients, from the Field to the ICU. State of the Art

The results of the Global Burden of Disease (GBD) study showed that, in 2019, 8% of deaths worldwide were trauma related [...].

Surgical Science and the Evolution of Critical Care Medicine

Surgical science has driven innovation and inquiry across adult and pediatric disciplines that provide critical care regardless of location. Surgically originated but broadly applicable knowledge has been globally shared within the pages Critical Care Medicine over the last 50 years.

Dynamic structures and emerging trends in the management of major trauma: A bibliometric analysis of publications between 2012 and 2021

Objective

Major trauma is currently a global public health issue with a massive impact on health at both the individual and population levels. However, there are limited bibliometric analyses on the management of major trauma. Thus, in this study we aimed to identify global research trends, dynamic structures, and scientific frontiers in the management of major trauma between 2012 and 2021.

Methods

We searched the Web of Science Core Collection to access articles and reviews concerning the management of major traumas and conducted a bibliometric analysis using CiteSpace.

Results

Overall, 2,585 studies were screened and published by 403 institutions from 110 countries/regions. The most productive country and institution in this field of research were the USA and Monash University, respectively. Rolf Lefering was the most prolific researcher and Holcomb JB had the most co-citations. Injury published the highest number of articles, and the Journal of Trauma was the most co-cited journal. A dual-map overlay of the literature showed that the articles of most publications were confined to the areas of medicine/medical/clinical and neurology/sports/ophthalmology. Document clustering indicated severe traumatic brain injury, traumatic coagulopathy, and resuscitative endovascular balloon occlusion as the recent hot topics. The most recent burst keywords were "trauma management," "neurocritical care," "injury severity," and "emergency medical services."

Conclusion

The dynamic structures and emerging trends in the management of major trauma were extensively analyzed using CiteSpace, a visualization software. Based on the analysis, the following research hotspots emerged: management of severe traumatic brain injury and massive hemorrhage, neurocritical care, injury severity, and emergency medical service. Our findings provide pertinent information for future research and contribute toward policy making in this field.

Functional mobility effects of progressive early mobilization protocol on people with moderate-to-severe traumatic brain injury: A pre-post intervention study

BACKGROUND: Brain plasticity evoked by environmental enrichment through early mobilization may improve sensorimotor functions of patients with moderate-to-severe traumatic brain injury (TBI). Increasing evidence also suggests that early mobilization increases verticalization, which is beneficial to TBI patients in critical care. However, there are limited data on early mobilization interventions provided to patients with moderate-to-severe TBI. OBJECTIVE: We investigated the possible enhancing effects of revised progressive early mobilization on functional mobility and the rate of out-of-bed mobility attained by patients with moderate-to-severe TBI. METHODS: This is a quantitative study with a retrospective and prospective pre–post intervention design. We implemented a revised progressive early mobilization protocol for patients with moderate-to-severe TBI admitted to the trauma intensive care unit (ICU) within the previous seven days. The outcome parameters were the rate of patients attaining early mobilization (sitting on the edge of the bed) and the Perme ICU Mobility Score at discharge from the ICU. The outcome parameters in the intervention cohort were compared with those from a historical control cohort who received standard medical care a year previously. Differences in the Perme ICU Mobility Score between the two cohorts were assessed using univariate analysis of covariance. RESULTS: Forty-two patients were included in the progressive early mobilization program and were compared with 44 patients who underwent standard medical care. In the intervention cohort, 100% and 57.2% of the patients completed early rehabilitation and early mobilization, respectively, compared to 0% in the control cohort. The intervention cohort at ICU discharge showed significantly improved the Perme ICU Mobility Scores. CONCLUSIONS: The implementation of the revised progressive early mobilization program for patients with moderate-to-severe TBI resulted in significantly improved mobility at ICU discharge; however, the length of overall stay in the ICU may be not affected.

A Case Series of Trauma Resuscitation in the Intensive Care Unit Bypassing the Emergency Room During the Conversion to a COVID-19 Only Hospital

When a patient with severe trauma is admitted to the emergency room (ER), they are evaluated before transfer to either the intensive care unit (ICU) or operating room. To minimize the time until a definitive treatment can be provided, direct operating room resuscitation can be performed. In this hospital the ER was closed during the hospital’s transition to a coronavirus disease 2019-dedicated hospital, and direct ICU resuscitation for patients with trauma was performed for a short period. To perform effective trauma resuscitation, all ICU beds were reorganized to achieve a modified, experienced nurse: patient ratio (1:2-3) and 2 beds were assigned for trauma ICU resuscitation alone. The equipment for initial resuscitation was installed and ICU nurses received training. Consultations with the hospital administration, nursing, and pharmaceutical departments were completed in advance to avoid formal problems. Conversion of the ICU for direct resuscitation procedures was performed in 4 patients.

Effects of job embeddedness and nursing working environment on turnover intention among trauma center nurses: A cross-sectional study

AIM

To investigate the effects of job embeddedness and nursing working environment on trauma center nurses' turnover intention.

BACKGROUND

Trauma center nurses have higher average turnover intention than hospital nurses. However, factors that increase the turnover intention of trauma center nurses remain unexplored.

METHODS

This cross-sectional study was conducted from August to October 2019, with 120 trauma center nurses working at three trauma centers in B, D, and U cities using measures of demographic characteristics, job embeddedness, nursing working environment, and turnover intention.

RESULTS

The mean turnover intention score was 3.60/5 points. There were significant correlations among turnover intention and fit, sacrifice, foundation for quality nursing, ability and leadership of nursing managers, cooperation of nurses and doctors, nurse participation in hospital management, and sufficient manpower and material support. Turnover intention was predicted by nurse participation in hospital management, gender, clinical experience, and fit, which explained 54%.

CONCLUSIONS

Factors that influence nurses' turnover intention at trauma centers were gender, clinical experience, job fit, and especially, nurses' participation in hospital management, which had the most effect on the nursing working environment.

IMPLICATIONS FOR NURSING MANAGEMENT

To expand participation of trauma center nurses, hospital management systems and organizational culture need improvement.

Automated Assessment of Cardiovascular Sufficiency Using Non-Invasive Physiological Data

For fluid resuscitation of critically ill individuals to be effective, it must be well calibrated in terms of timing and dosages of treatments. In current practice, the cardiovascular sufficiency of patients during fluid resuscitation is determined using primarily invasively measured vital signs, including Arterial Pressure and Mixed Venous Oxygen Saturation (SvO2), which may not be available in outside-of-hospital settings, particularly in the field when treating subjects injured in traffic accidents or wounded in combat where only non-invasive monitoring is available to drive care. In this paper, we propose (1) a Machine Learning (ML) approach to estimate the sufficiency utilizing features extracted from non-invasive vital signs and (2) a novel framework to address the detrimental impact of inter-patient diversity on the ability of ML models to generalize well to unseen subjects. Through comprehensive evaluation on the physiological data collected in laboratory animal experiments, we demonstrate that the proposed approaches can achieve competitive performance on new patients using only non-invasive measurements. These characteristics enable effective monitoring of fluid resuscitation in real-world acute settings with limited monitoring resources and can help facilitate broader adoption of ML in this important subfield of healthcare.

Phosphoinositide-3-Kinase/Akt-Endothelial Nitric Oxide Synthase Signaling Pathway Mediates the Neuroprotective Effect of Sevoflurane Postconditioning in a Rat Model of Hemorrhagic Shock and Resuscitation

BACKGROUND

Although extensive reports have demonstrated the neuroprotection of sevoflurane postconditioning in cases of focal and global cerebral ischemia/reperfusion, the underlying mechanisms are not completely elucidated. This study investigated whether this effect is related to endothelial nitric oxide synthase (eNOS) and mediated by the phosphoinositide-3-kinase pathway in a rat model of hemorrhagic shock and resuscitation.

METHODS

Adult male Sprague Dawley rats were subjected to hemorrhagic shock for 60 minutes and then resuscitation for 30 minutes in experimental groups. Sevoflurane postconditioning was performed at the beginning of resuscitation to completion. At 24 hours after resuscitation, the brain infarct volume was evaluated by 2,3,5-triphenyltetrazolium chloride staining. The neuronal morphological changes and apoptosis were determined by hematoxylin and eosin staining and immunohistochemistry analysis, respectively. The activity of phosphorylated Akt and eNOS was evaluated by Western blot analysis.

RESULTS

Brain injuries such as the cerebral infarct volume and pathological neuronal changes as well as cell apoptosis were observed in the hippocampus after hemorrhagic shock and resuscitation. Postconditioning with 2.4% sevoflurane significantly attenuated brain injuries. Wortmannin prevented the improvements of neuronal characteristics elicited by sevoflurane postconditioning as well as the hyperactivity of eNOS and phosphorylated Akt.

CONCLUSIONS

Sevoflurane postconditioning could attenuate brain injury induced by hemorrhagic shock and resuscitation, and this neuroprotective effect may be partly by upregulation of eNOS through the phosphoinositide-3-kinase/Akt signaling pathway.

The relationship between serum lactate dehydrogenase level and mortality in critically ill patients

Background: To assess the association between serum lactate dehydrogenase (LDH) levels and mortality in intensive care unit patients. Materials & methods: A total of 1981 patients in the eICU Collaborative Research Database were divided into four groups according to quartiles of LDH levels. Logistic regressions were performed. Results: Elevated LDH levels were significantly associated with higher mortality (intensive care unit mortality: Q2 vs Q1: 1.046 [0.622-1.758]; Q3 vs Q1: 1.667 [1.029-2.699]; and Q4 vs Q1: 1.760 [1.092-2.839]). Similar results persisted in patients with different acute physiology and chronic health evaluation IV scores, and with or without sepsis. Conclusion: The serum LDH level may aid in the early identification of mortality risk in critically ill patients.

Therapeutic Applications of Stem Cells and Extracellular Vesicles in Emergency Care: Futuristic Perspectives

Regenerative medicine (RM) is an interdisciplinary field that aims to repair, replace or regenerate damaged or missing tissue or organs to function as close as possible to its physiological architecture and functions. Stem cells, which are undifferentiated cells retaining self-renewal potential, excessive proliferation and differentiation capacity into offspring or daughter cells that form different lineage cells of an organism, are considered as an important part of the RM approaches. They have been widely investigated in preclinical and clinical studies for therapeutic purposes. Extracellular vesicles (EVs) are the vital mediators that regulate the therapeutic effects of stem cells. Besides, they carry various types of cargo between cells which make them a significant contributor of intercellular communication. Given their role in physiological and pathological conditions in living cells, EVs are considered as a new therapeutic alternative solution for a variety of diseases in which there is a high unmet clinical need. This review aims to summarize and identify therapeutic potential of stem cells and EVs in diseases requiring acute emergency care such as trauma, heart diseases, stroke, acute respiratory distress syndrome and burn injury. Diseases that affect militaries or societies including acute radiation syndrome, sepsis and viral pandemics such as novel coronavirus disease 2019 are also discussed. Additionally, featuring and problematic issues that hamper clinical translation of stem cells and EVs are debated in a comparative manner with a futuristic perspective. Graphical Abstract.

Low skeletal muscle mass predicts poor clinical outcomes in patients with abdominal trauma

OBJECTIVE

The aim of this study was to investigate whether low skeletal muscle mass is associated with clinical outcomes in patients with abdominal trauma.

METHODS

Patients presenting to our institution with abdominal trauma from January 2010 to April 2020 were retrospectively included. Low skeletal muscle mass was defined, using computed tomography, as skeletal muscle index (SMI) at the third lumbar vertebra below the lowest sex-specific quartile within 1 wk of admission. Clinical outcomes such as complications, hospital stay, and hospital cost were recorded, and univariate and multivariate analyses were performed.

RESULTS

Among 684 patients, 451 were eligible. Of these, 112 (24.8%) were classified as having low skeletal muscle mass, based on SMI diagnostic cutoff values (42.08 cm²/m² for men and 37.35 cm²/m² for women). Low skeletal muscle mass was significantly associated with longer hospital length of stay, longer intensive care length of stay, higher cost, higher frequency of mechanical ventilation, longer duration of vasopressor use, and higher incidence of massive transfusion and overall complications (P < 0.05). Subgroup analysis showed that pneumonia, acute gastrointestinal dysfunction, cholecystitis, digestive tract fistula, gastric fistula, and intestinal fistula were significantly associated with low skeletal muscle mass (P < 0.05). Multivariate analysis showed that low skeletal muscle mass was an independent risk factor for overall complications (odds ratio [OR], 2.44; 95% confidence interval [CI], 1.33-4.49; P = 0.004), hospital length of stay (OR, 3.49; 95% CI, 1.96-6.20; P < 0.001), and hospital cost (OR, 2.67; 95% CI, 1.48-4.80; P = 0.001).

CONCLUSIONS

Low skeletal muscle mass could be an independent predictor of poor clinical outcomes in patients with abdominal trauma.

Estimating Surgical Blood Loss Volume Using Continuously Monitored Vital Signs

Background: There are currently no effective and accurate blood loss volume (BLV) estimation methods that can be implemented in operating rooms. To improve the accuracy and reliability of BLV estimation and facilitate clinical implementation, we propose a novel estimation method using continuously monitored photoplethysmography (PPG) and invasive arterial blood pressure (ABP). Methods: Forty anesthetized York Pigs (31.82 ± 3.52 kg) underwent a controlled hemorrhage at 20 mL/min until shock development was included. Machine-learning-based BLV estimation models were proposed and tested on normalized features derived by vital signs. Results: The results showed that the mean ± standard deviation (SD) for estimating BLV against the reference BLV of our proposed random-forest-derived BLV estimation models using PPG and ABP features, as well as the combination of ABP and PPG features, were 11.9 ± 156.2, 6.5 ± 161.5, and 7.0 ± 139.4 mL, respectively. Compared with traditional hematocrit computation formulas (estimation error: 102.1 ± 313.5 mL), our proposed models outperformed by nearly 200 mL in SD. Conclusion: This is the first attempt at predicting quantitative BLV from noninvasive measurements. Normalized PPG features are superior to ABP in accurately estimating early-stage BLV, and normalized invasive ABP features could enhance model performance in the event of a massive BLV.

The effectiveness of educational interventions on trauma intensive care unit nurses' competence: A systematic review and meta-analysis

OBJECTIVES

To examine the current evidence on the effect of education on intensive care unit nurses' knowledge and skills competence in caring for adult major trauma patients.

METHODOLOGY

A systematic review and meta-analysis was conducted to identify relevant studies through a comprehensive search, following strict eligibility criteria. Five databases were searched: MEDLINE, PubMed, CINAHL, Cochrane and Web of Science. A subsequent hand search was performed. The Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument tool was used to assess methodological quality.

RESULTS

Five eligible quantitative studies were identified and appraised. The overall results demonstrated that educational interventions have positive effects in improving intensive care nurses' knowledge and practice in managing major trauma patients. Meta-analysis was applied to three homogenous studies relating to knowledge outcome. Results demonstrated significant improvements immediately post-intervention and at one-to three-month follow-up [MD (mean difference) = 29.12, 95%CI (confidence interval) 10.29-47.95; P < 0.00001], and [MD = 23.70, 95%CI 8.84-38.56; P < 0.00001], respectively. A slight decrease in the knowledge and practice scores was noted from one- to three-month follow-up.

CONCLUSION

This review demonstrated the significant effects of trauma education on improving intensive care nurses' knowledge and practices. Further research should develop valid competencies and policies to drive nurses' practice and potentially improve the safety and quality of care.

Development of hemorrhage identification model using non-invasive vital signs

OBJECTIVE

Early detection and timely management of bleeding is critical as failure to recognize physiologically significant bleeding is associated with significant morbidity and mortality. Many such instances are detected late, even in highly monitored environments, contributing to delay in recognition and intervention. We propose a non-invasive early identification model to detect bleeding events using continuously collected photoplethysmography (PPG) and electrocardiography (ECG) waveforms.

APPROACH

Fifty-nine York pigs undergoing fixed-rate, controlled hemorrhage were involved in this study and a least absolute shrinkage and selection operator regression-based early detection model was developed and tested using PPG and ECG derived features. The output of the early detection model was a risk trajectory indicating the future probability of bleeding.

MAIN RESULTS

Our proposed models were generally accurate in predicting bleeding with an area under the curve of 0.89 (95% CI 0.87-0.92) and achieved an average time of 16.1 mins to detect 16.8% blood loss when a false alert rate of 1% was tolerated. Models developed on non-invasive data performed with similar discrimination and lead time to hemorrhage compared to models using invasive arterial blood pressure as monitoring data.

SIGNIFICANCE

A bleed detection model using only non-invasive monitoring performs as well as those using invasive arterial pressure monitoring.