Enhanced pro-inflammatory response and higher mortality rates in geriatric trauma patients

Development and validation of a machine learning-based model to assess probability of systemic inflammatory response syndrome in patients with severe multiple traumas

BACKGROUND

Systemic inflammatory response syndrome (SIRS) is a predictor of serious infectious complications, organ failure, and death in patients with severe polytrauma and is one of the reasons for delaying early total surgical treatment. To determine the risk of SIRS within 24 h after hospitalization, we developed six machine learning models.

MATERIALS AND METHODS

Using retrospective data about the patient, the nature of the injury, the results of general and standard biochemical blood tests, and coagulation tests, six models were developed: decision tree, random forest, logistic regression, support vector and gradient boosting classifiers, logistic regressor, and neural network. The effectiveness of the models was assessed through internal and external validation.

RESULTS

Among the 439 selected patients with severe polytrauma in 230 (52.4%), SIRS was diagnosed within the first 24 h of hospitalization. The SIRS group was more strongly associated with class II bleeding (39.5% vs. 60.5%; OR 1.81 [95% CI: 1.23-2.65]; P = 0.0023), long-term vasopressor use (68.4% vs. 31.6%; OR 5.51 [95% CI: 2.37-5.23]; P < 0.0001), risk of acute coagulopathy (67.8% vs. 32.2%; OR 2.4 [95% CI: 1.55-3.77]; P < 0.0001), and greater risk of pneumonia (59.5% vs. 40.5%; OR 1.74 [95% CI: 1.19-2.54]; P = 0.0042), longer ICU length of stay (5 ± 6.3 vs. 2.7 ± 4.3 days; P < 0.0001) and mortality rate (64.5% vs. 35.5%; OR 10.87 [95% CI: 6.3-19.89]; P = 0.0391). Of all the models, the random forest classifier showed the best predictive ability in the internal (AUROC 0.89; 95% CI: 0.83-0.96) and external validation (AUROC 0.83; 95% CI: 0.75-0.91) datasets.

CONCLUSIONS

The developed model made it possible to accurately predict the risk of developing SIRS in the early period after injury, allowing clinical specialists to predict patient management tactics and calculate medication and staffing needs for the patient.

LEVEL OF EVIDENCE

Level 3.

TRIAL REGISTRATION

The study was retrospectively registered in the ClinicalTrials.gov database of the National Library of Medicine (NCT06323096).

Extremity fractures, attempted suicide, blood transfusion and thromboembolic events are independent risk factors for a prolonged hospital stay in severely injured elderly

METHODS

Due to demographic change, the number of polytraumatized geriatric patients (> 64 years) is expected to further increase in the coming years. In addition to the particularities of the accident and the associated injury patterns, prolonged inpatient stays are regularly observed in this group. The aim of the evaluation is to identify further factors that cause prolonged inpatient stays. A study of the data from the TraumaRegister DGU® from 2016-2020 was performed. Inclusion criteria were an age of over 64 years, intensive care treatment in the GAS-region, and an Injury Severity Score (ISS) of at least 16 points. All patients who were above the 80th percentile for the average length of stay or average intensive care stay of the study population were defined as so-called long-stay patients. This resulted in a prolonged inpatient stay of > 25 days and an intensive care stay of > 13 days. Among other, the influence of the cause of the accident, injury patterns according to body regions, the occurrence of complications, and the influence of numerous clinical parameters were examined.

RESULTS

A total of 23,026 patients with a mean age of 76.6 years and a mean ISS of 24 points were included. Mean ICU length of stay was 11 ± 12.9 days (regular length of stay: 3.9 ± 3.1d vs. prolonged length of stay: 12.8 ± 5.7d) and mean inpatient stay was 22.5 ± 18.9 days (regular length of stay: 20.7 ± 15d vs. 35.7 ± 22.3d). A total of n = 6,447 patients met the criteria for a prolonged length of stay. Among these, patients had one more diagnosis on average (4.6 vs. 5.8 diagnoses) and had a higher ISS (21.8 ± 6 pts. vs. 26.9 ± 9.5 pts.) Independent risk factors for prolonged length of stay were intubation duration greater than 6 days (30-fold increased risk), occurrence of sepsis (4x), attempted suicide (3x), presence of extremity injury (2.3x), occurrence of a thromboembolic event (2.7x), and administration of red blood cell concentrates in the resuscitation room (1.9x).

CONCLUSIONS

The present analysis identified numerous independent risk factors for significantly prolonged hospitalization of the geriatric polytraumatized patient, which should be given increased attention during treatment. In particular, the need for a smooth transition to psychiatric follow-up treatment or patient-adapted rehabilitative care for geriatric patients with prolonged immobility after extremity injuries is emphasized by these results.

Whole blood for old blood: Use of whole blood for resuscitation in older trauma patients

INTRODUCTION

Older patients are expected to comprise 40 % of trauma admissions in the next 30 years. The use of whole blood (WB) has shown promise in improving mortality while lowering the utilization of blood products. However, the use of WB in older trauma patients has not been examined. The objective of our study is to determine the safety and efficacy of a WB first transfusion strategy in injured older patients.

METHODS

Older trauma patients, defined as age ≥55 years old, were reviewed from March 2016-November 2021. Patients that received a WB first resuscitation strategy were compared to those that received a ratio based component strategy. Demographics as well as complications rates, blood product transfusion volumes, and mortality were evaluated. Univariate and multivariable analysis was used to determine independent predictors of mortality.

RESULTS

There were 388 older trauma patients that received any blood products during the study period. A majority of patients received a WB first resuscitation strategy (83 %). Compared to patients that received component therapy, patients that received WB first were more likely female, less likely to have a penetrating mechanism, and had a slightly lower injury severity score. The-30 day mortality rate was comparable (WB 36% vs component 37 %, p = 0.914). While rates of AKI were slightly higher in those that received WB, this did not result in increased rates of renal replacement therapy (3 % vs 2 %, p = 1). Further, compared to patients that received components, patients that were resuscitated with a WB first strategy significantly utilized lower median volumes of platelets (0 mL vs 197 mL, p < 0.001), median volumes of plasma (0 mL vs 1253 mL, p < 0.001, and median total volume of blood products (1000 mL vs 2859 mL, p < 0.001).

CONCLUSION

The use of WB in the older trauma patient appears safe, with mortality and complication rates comparable to component therapy. Blood product utilization is significantly less in those that are resuscitated with WB first.

Reality of treatment for severely injured patients: are there age-specific differences?

BACKGROUND

Major trauma and its consequences are one of the leading causes of death worldwide across all age groups. Few studies have conducted comparative age-specific investigations. It is well known that children respond differently to major trauma than elderly patients due to physiological differences. The aim of this study was to analyze the actual reality of treatment and outcomes by using a matched triplet analysis of severely injured patients of different age groups.

METHODS

Data from the TraumaRegister DGU® were analyzed. A total of 56,115 patients met the following inclusion criteria: individuals with Maximum Abbreviated Injury Scale > 2 and < 6, primary admission, from German-speaking countries, and treated from 2011-2020. Furthermore, three age groups were defined (child: 3-15 years; adult: 20-50 years; and elderly: 70-90 years). The matched triplets were defined based on the following criteria: 1. exact injury severity of the body regions according to the Abbreviated Injury Scale (head, thorax, abdomen, extremities [including pelvis], and spine) and 2. level of the receiving hospital.

RESULTS

A total of 2,590 matched triplets could be defined. Traffic accidents were the main cause of severe injury in younger patients (child: 59.2%; adult: 57.9%). In contrast, low falls (from < 3 m) were the most frequent cause of accidents in the elderly group (47.2%). Elderly patients were least likely to be resuscitated at the scene. Both children and elderly patients received fewer therapeutic interventions on average than adults. More elderly patients died during the clinical course, and their outcome was worse overall, whereas the children had the lowest mortality rate.

CONCLUSIONS

For the first time, a large patient population was used to demonstrate that both elderly patients and children may have received less invasive treatment compared with adults who were injured with exactly the same severity (with the outcomes of these two groups being opposite to each other). Future studies and recommendations should urgently consider the different age groups.

Utilizing predictive machine-learning modelling unveils feature-based risk assessment system for hyperinflammatory patterns and infectious outcomes in polytrauma

Purpose

Earlier research has identified several potentially predictive features including biomarkers associated with trauma, which can be used to assess the risk for harmful outcomes of polytraumatized patients. These features encompass various aspects such as the nature and severity of the injury, accompanying health conditions, immune and inflammatory markers, and blood parameters linked to organ functioning, however their applicability is limited. Numerous indicators relevant to the patients` outcome are routinely gathered in the intensive care unit (ICU) and recorded in electronic medical records, rendering them suitable predictors for risk assessment of polytraumatized patients.

Methods

317 polytraumatized patients were included, and the influence of 29 clinical and biological features on the complication patterns for systemic inflammatory response syndrome (SIRS), pneumonia and sepsis were analyzed with a machine learning workflow including clustering, classification and explainability using SHapley Additive exPlanations (SHAP) values. The predictive ability of the analyzed features within three days after admission to the hospital were compared based on patient-specific outcomes using receiver-operating characteristics.

Results

A correlation and clustering analysis revealed that distinct patterns of injury and biomarker patterns were observed for the major complication classes. A k-means clustering suggested four different clusters based on the major complications SIRS, pneumonia and sepsis as well as a patient subgroup that developed no complications. For classification of the outcome groups with no complications, pneumonia and sepsis based on boosting ensemble classification, 90% were correctly classified as low-risk group (no complications). For the high-risk groups associated with development of pneumonia and sepsis, 80% of the patients were correctly identified. The explainability analysis with SHAP values identified the top-ranking features that had the largest impact on the development of adverse outcome patterns. For both investigated risk scenarios (infectious complications and long ICU stay) the most important features are SOFA score, Glasgow Coma Scale, lactate, GGT and hemoglobin blood concentration.

Conclusion

The machine learning-based identification of prognostic feature patterns in patients with traumatic injuries may improve tailoring personalized treatment modalities to mitigate the adverse outcomes in high-risk patient clusters.

EVALUATION OF CYFRA 21-1, ANGIOPOETIN-2, PENTRAXIN-3, SRAGE, IL-6, AND IL-10 IN POLYTRAUMATIZED PATIENTS WITH CONCOMITANT THORACIC TRAUMA-HELPFUL MARKERS TO PREDICT PNEUMONIA?

ABSTRACT

Background: Pneumonia is a frequent complication after polytrauma. This study aims to evaluate the ability of different serum markers to identify patients at risk of developing pneumonia after polytrauma. Methods: A retrospective analysis of prospectively collected data in polytraumatized patients with concomitant thoracic trauma (Injury Severity Score ≥16, Abbreviated Injury Scale Thorax ≥ 3) was performed. The study cohort was divided into patients with and without pneumonia during the clinical course. Serum levels of lung epithelial (CYFRA 21-1), endothelial (Ang-2), and inflammatory (PTX-3, sRAGE, IL-6, IL-10) markers were measured upon arrival in the trauma room and on days 2 and 5. Results: A total of 73 patients and 16 healthy controls were included in this study. Of these, 20 patients (27.4%) developed pneumonia. Polytraumatized patients showed significantly increased CYFRA 21-1 levels with a distinct peak after admission compared with healthy controls. Serum PTX-3 significantly increased on day 2 in polytraumatized patients compared with healthy controls. Injury Severity Score and demographic parameters were comparable between both groups (pneumonia vs. no pneumonia). No statistically significant difference could be observed for serum levels of CYFRA 21-1, Ang-2, PTX-3, sRAGE, IL-6, and IL-10 between the groups (pneumonia vs. no pneumonia) on all days. Logistic regression revealed a combination of IL-6, IL-10, sRAGE, and PTX-3 to be eventually helpful to identify patients at risk of developing pneumonia and our newly developed score was significantly higher on day 0 in patients developing pneumonia ( P < 0.05). Conclusion: The investigated serum markers alone are not helpful to identify polytraumatized patients at risk of developing pneumonia, while a combination of IL-6, IL-10, PTX-3, and sRAGE might be.

Diagnostic and Prognostic Potential of Exosomal Cytokines IL-6 and IL-10 in Polytrauma Patients

Trauma remains a leading cause of morbidity and mortality. Polytraumatized patients need a precise, early diagnosis to avoid complications such as multiorgan failure or sepsis. Inflammatory cytokines, commonly used for diagnosis, have a short half-life, which limits their efficacy as a diagnostic or prognostic marker. In this study, we hypothesized that cytokines in exosomes could have a longer half-life, and therefore could be used as diagnostic and prognostic markers in polytrauma patients. Plasma samples from polytraumatized patients (ISS ≥ 16, n = 18) were collected in the emergency room (ER) 1, 2, 3 and 5 days after trauma. Plasma-exosomes were isolated via size exclusion chromatography from polytraumatized patients and healthy volunteers (n = 10). The systemic and exosomal concentrations of interleukin (IL)-6, IL-10, IL-1β and TNF were measured using high-sensitive ELISAs. To investigate the diagnostic and prognostic potential of exosomal cytokines, data were correlated with clinical outcome parameters (injury severity, ventilation time, time in ICU and survival) documented in the patients' electronic records. Despite the use of high-sensitive ELISAs, IL-1β and TNF alpha were not detected in exosomes. IL-6 and IL-10 were detectable in polytraumatized patient exosomes at all time points. A decrease over time of both systemic and exosomal IL-6 concentrations was observed. Furthermore, exosomal and systemic IL-6 concentrations moderately correlated (r = 0.63). Exosomal IL-6 in the ER moderately correlated with the Injury Severity Score (ISS) (mean 35.5 ± 11.5) (r = 0.45) and was associated with non-survival in polytrauma patients (p < 0.05). In contrast to IL-6, no correlation between systemic and exosomal IL-10 concentrations was found. Exosomal IL-10 concentrations remained unchanged throughout the observation time, whereas systemic IL-10 concentrations peaked in the ER and were significantly reduced after 24 h. Data from this study support our hypothesis that some cytokines (IL-10), but not all (IL-6), are detectable in exosomes significantly longer than they are in plasma. This might indicate that they are protected from degradation. Although we did not find a correlation between IL-10 exosomal concentration and patient outcome, our data confirm that exosomal cytokines are of interest as potential diagnostic and prognostic markers in polytrauma patients, and require further detailed research.

[Relationship Between Frailty and Poor Prognosis in Older Trauma Patients in the Emergency Department: A Prospective Cohort Study]

Objective

To explore the relationship between frailty and adverse outcomes in older trauma patients in the emergency department.

Methods

A prospective cohort study was conducted. Older trauma patients admitted to the emergency department of three tertiary-care hospitals in Chengdu between January 2021 and August 2021 were enrolled. The patients were divided into a frailty group and a non-frailty group according to their assessment results for Trauma-Specific Frailty Index (TSFI). The end points, including falls, readmission, and deaths, were documented during the 6-month follow-up. Cox risk regression model was used to analyze the relationship between frailty and adverse outcomes in older trauma patients in the emergency department.

Results

A total of 375 older trauma patients in the emergency department were enrolled, including 131 in the frailty group and 244 in the non-frailty group. After 6 months of follow-up, the incidences of falls, readmission and deaths in older trauma patients in the emergency department were 18.93%, 14.40%, and 7.73%, respectively. The incidences of falls (28.24% vs. 13.93%, P=0.001), readmission (25.95% vs. 8.20%, P=0.000), and deaths (12.98% vs. 4.92%, P=0.005) in older trauma patients in the emergency department in the frailty group were higher than those in the non-frailty group. After adjusting for multiple confounding factors using the Cox regression model, the risks of falls (hazard ratio [ HR]=1.859, 95% confidence interval [ CI]: 1.070-3.230, P=0.028] and readmission ( HR=2.920, 95% CI: 1.537-5.547, P=0.001) were higher in the frailty group than those in the non-frailty group, but there was no significant difference in the risk of deaths between the frailty group and the non-frailty group.

Conclusion

Frailty is a risk factor for falls and readmissions in older trauma patients in the emergency department and the association between frailty and the risk of deaths in older trauma patients in the emergency department needs to be validated by further studies.

Lung failure after polytrauma with concomitant thoracic trauma in the elderly: an analysis from the TraumaRegister DGU®

Background

In developed countries worldwide, the number of older patients is increasing. Pulmonary complications are common in multiple injured patients with chest injuries. We assessed whether geriatric patients develop lung failure following multiple trauma with concomitant thoracic trauma more often than younger patients.

Methods

A retrospective analysis of severely injured patients with concomitant blunt thoracic trauma registered in the TraumaRegister DGU® (TR-DGU) between 2009 and 2018 was performed. Patients were categorized into four age groups: 55–64 y, 65–74 y, 75–84 y, and ≥ 85 y. Adult patients aged 18–54 years served as a reference group. Lung failure was defined as PaO2/FIO2 ≤ 200 mm Hg, if mechanical ventilation was performed.

Results

A total of 43,289 patients were included, of whom 9238 (21.3%) developed lung failure during their clinical stay. The rate of posttraumatic lung failure was seen to increase with age. While lung failure markedly increased the length of hospital stay, duration of mechanical ventilation, and length of ICU stay independent of the patient’s age, differences between younger and older patients with lung failure in regard to these parameters were clinically comparable. In addition, the development of respiratory failure showed a distinct increase in mortality with higher age, from 16.9% (18–54 y) to 67.2% (≥ 85 y).

Conclusion

Development of lung failure in severely injured patients with thoracic trauma markedly increases hospital length of stay, length of ICU stay, and duration of mechanical ventilation in patients, regardless of age. The development of respiratory failure appears to be related to the severity of the chest trauma rather than to increasing patient age. However, the greatest effects of lung failure, particularly in terms of mortality, were observed in the oldest patients.

An increasing trend in geriatric trauma patients undergoing surgical stabilization of rib fractures

Purpose

The proportion of geriatric trauma patients (GTPs) (age ≥ 65 years old) with chest wall injury undergoing surgical stabilization of rib fractures (SSRF) nationally is unknown. We hypothesize a growing trend of GTPs undergoing SSRF, and sought to evaluate risk of respiratory complications and mortality for GTPs compared to younger adults (18–64 years old) undergoing SSRF.

Methods

The Trauma Quality Improvement Program (2010–2016) was queried for patients with rib fracture(s) who underwent SSRF. GTPs were compared to younger adults. A multivariable logistic regression analysis was performed.

Results

From 21,517 patients undergoing SSRF, 3,001 (16.2%) were GTPs. Of all patients undergoing SSRF in 2010, 10.6% occurred on GTPs increasing to 17.9% in 2016 (p < 0.001) with a geometric-mean-annual increase of 11.5%. GTPs had a lower median injury severity score (18 vs. 22, p < 0.001), but had a higher rate of mortality (4.7% vs. 1.2%, p < 0.001). After controlling for covariates, GTPs had an increased associated risk of mortality (OR 4.80, CI 3.62–6.36, p < 0.001). On a separate multivariate analysis for all trauma patients with isolated chest Abbreviated Injury Scale 3, GTPs were associated with a similar four-fold risk of mortality (OR 4.21, CI 1.98–6.32, p < 0.001).

Conclusion

Spanning 7 years of data, the proportion of GTPs undergoing SSRF increased by over 7%. Although GTPs undergoing SSRF had lesser injuries, their risk of mortality was four times higher than other adult trauma patients undergoing SSRF, which was similar to their increased background risk of mortality. Ultimately, SSRF in GTPs should be considered on an individualized basis with careful attention to risk–benefit ratio.

Electronic supplementary material

The online version of this article (10.1007/s00068-020-01526-7) contains supplementary material, which is available to authorized users.