Multiple organ dysfunction syndrome (MODS) prediction score in multi-trauma patients

Adjunctive hemoperfusion with Resin Hemoadsorption (HA) 330 cartridges improves outcomes in patients sustaining multiple Blunt Trauma: a prospective, quasi-experimental study

BACKGROUND

Multi-organ dysfunction syndrome and multi-organ failure are the leading causes of late death in patients sustaining severe blunt trauma. So far, there is no established protocol to mitigate these sequelae. This study assessed the effect of hemoperfusion using resin-hemoadsorption 330 (HA330) cartridges on mortality and complications such as acute respiratory distress syndrome (ARDS) and systemic inflammatory response syndrome (SIRS) among such patients.

METHODS

This quasi-experimental study recruited patients ≥ 15 years of age with blunt trauma, injury severity score (ISS) ≥ 15, or initial clinical presentation consistent with SIRS. They were divided into two groups: the Control group received only conventional acute care, while the case group received adjunctive hemoperfusion. P-values less than 0.05 were statistically significant.

RESULTS

Twenty-five patients were included (Control and Case groups: 13 and 12 patients). The presenting vital signs, demographic and injury-related features (except for thoracic injury severity) were similar (p > 0.05). The Case group experienced significantly more severe thoracic injuries than the Control group (Thoracic AIS, median [IQR]: 3 [2-4] vs. 2 [0-2], p = 0.01). Eleven and twelve patients in the Case group had ARDS and SIRS before the hemoperfusion, respectively, and these complications were decreased considerably after hemoperfusion. Meanwhile, the frequency of ARDS and SIRS did not decrease in the Control group. Hemoperfusion significantly reduced the mortality rate in the Case group compared to the Control group (three vs. nine patients, p = 0.027).

CONCLUSIONS

Adjunctive Hemoperfusion using an HA330 cartridge decreases morbidity and improves outcomes in patients suffering from severe blunt trauma.

A machine learning method for predicting the probability of MODS using only non-invasive parameters

OBJECTIVES

Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essential for the rescue and treatment of trauma patients However, existing methods are invasive, easily affected by artifacts and can be difficult to perform in a pre-hospital setting. We aim to develop prediction models for patients with MODS using only non-invasive parameters.

METHOD

In this study, records from 2319 patients were extracted from the Multiparameter Intelligent Monitoring in Intensive Care Ⅲ database (MIMIC Ⅲ), based on the sequential organ failure assessment (SOFA) score. Seven commonly used machine learning (ML) methods were selected and applied to develop a real-time prediction method for MODS based on full parameters (laboratory parameter. drug and non-invasive parameters, 57 parameters in total) and non-invasive parameters only (17 parameters) and compared with four traditional scoring systems.

RESULTS

The prediction results using LightGBM (LGBM) and Adaboost based on the full parameter modeling were 0.959 for area under receiver operating characteristic curve (AUC), outperforming four traditional scoring systems. The removal of 40 parameters and retaining of 17 non-invasive parameters decreased the AUC value of LGBM by 0.015, which still outperformed all traditional scoring systems.

CONCLUSIONS

A real-time and accurate MODS prediction method was developed in this paper based on non-invasive parameters by comparing the performance of four ML methods, which proved to be superior to the traditional scoring systems. This method can help medical staff to diagnose MODS as soon as possible and can improve the survival rate of patients in a pre-hospital setting.

Moderate to severe leukocytosis with vasopressor use is associated with increased mortality in trauma patients

Background

Leukocytosis is a rise in white blood cell (WBC) count and clinical outcomes of moderate to severe leukocytosis in trauma patients have not been described. We hypothesized that trauma patients with severe leukocytosis (SL; ≥40.0 × 109 leukocytes/L) have higher rates of in-hospital complications and mortality than those with moderate leukocytosis (ML; 25.0-39 × 109 leukocytes/L).

Methods

We performed a retrospective analysis (2010-2017) on trauma patients developing ML or SL at a single Level-I trauma center. A multivariable logistic regression analysis for risk factors were performed.

Results

From 15,807 trauma admissions, 332 (2.1%) had ML or SL. Of these, 308 (92.8%) were ML and 24 (7.2%) were SL. Patients with ML and SL reached their peak WBC count in 1 and 10 days after admission respectively (p < 0.001). SL patients suffered higher rates of in-hospital complications (p < 0.05) and mortality compared to those without ML or SL (14.5% vs. 3.3%, p < 0.001). Between ML and SL, mortality rates rose with leukocytosis severity (13.3% vs. 29.2%, p = 0.03). Among all patients with ML or SL, vasopressor use was the strongest independent risk factor for mortality (OR 12.61, p < 0.001).

Conclusion

Clinicians should be weary of the increased mortality rates and in-hospital complications in SL patients. Among patients with ML or SL, vasopressor use, rather than SL, was the strongest predictor of mortality. Patients with ML had a quicker time course to peak leukocytosis compared to SL, suggesting these two entities to be distinct in etiology and outcome, warranting future research.

Anemia after Pediatric Congenital Heart Surgery

The postoperative course of infants following congenital heart surgery is associated with significant blood loss and anemia. Optimal transfusion thresholds for cardiac surgery patients while in pediatric intensive care unit (PICU) remain a subject of debate. The goal of this study is to describe the epidemiology of anemia and the transfusion practices during the PICU stay of infants undergoing congenital heart surgery. A retrospective cohort study was performed in a PICU of a tertiary university-affiliated center. Infants undergoing surgery for congenital heart disease (CDH) before 6 weeks of age between February 2013 and June 2019 and who were subsequently admitted to the PICU were included. We identified 119 eligible patients. Mean age at surgery was 11 ± 7 days. Most common cardiac diagnoses were d-Transposition of the Great Arteries (55%), coarctation of the aorta (12.6%), and tetralogy of Fallot (11.8%). Mean hemoglobin level was 14.3 g/dL prior to surgery versus 12.1 g/dL at the PICU admission. Hemoglobin prior to surgery was systematically higher than hemoglobin at the PICU entry, except in infants with Hypoplastic Left Heart Syndrome. The average hemoglobin at PICU discharge was 11.7 ± 1.9 g/dL. Thirty-three (27.7%) patients were anemic at PICU discharge. Fifty-eight percent of patients received at least one red blood cell (RBC) transfusion during PICU stay. This study is the first to describe the epidemiology of anemia at PICU discharge in infants following cardiac surgery. Blood management of this distinctive and vulnerable population requires further investigation as anemia is a known risk factor for adverse neurodevelopment delays in otherwise healthy young children.

Emerging patterns of hypercoagulability associated with critical COVID-19: A review

While the COVID-19 pandemic sweeps the world, much evidence is being gathered regarding its novel pathological mechanisms. It is the authors' clinical experience that patients in the intensive care unit suffering from COVID-19 are extremely pro-coagulable, with venous and arterial thromboembolism frequently observed, and losses of vascular access lines and filtration circuits to thrombosis now commonplace. Here, we explore the evidence for hypercoagulability in this group, presenting evidence of both a localised pulmonary hypercoagulability, and a systemic hypercoagulability resulting in thrombosis distant to the pulmonary vasculature. Furthermore, we discuss the possible risk factors exacerbated by, or selected for in COVID-19. We review the available evidence for use of plasma D-dimer as a prognostic marker, exploring the possibility that it acts as a marker of a COVID-19-associated hypercoagulability. We review the evidence for a pro-coagulant subtype of disseminated intravascular coagulation, discussing its clinical significance. Finally, we discuss the current evidence surrounding treatment of COVID-19 hypercoagulability, including prophylactic and treatment-dose heparin, thrombolytic agents, antiplatelet agents, and direct thrombin inhibitors, among others. We suggest areas in which further investigation is urgently needed to reduce the startling incidence of thrombosis in this group, a complication no doubt contributing to morbidity and mortality.

Integrating artificial neural network and scoring systems to increase the prediction accuracy of patient mortality and organ dysfunction

The aim of this study was to develop and compare techniques to increase the prediction accuracy of patient mortality and organ dysfunction in the Intensive Care Units (hereinafter ICU) of hospitals. Patient mortality was estimated with two models of artificial neural network (ANN)-backpropagation (BP) and simplified acute physiology score (SAPS). Organ dysfunction was predicted by coupled ANN self-organizing map (SOM) and logistic organ dysfunction score (LODS) method on the basis of patient conditions. Input dataset consisted of 36 features recorded for 4,000 patients in the ICU. An integrated response surface methodology (RSM) and genetic algorithm (GA) was developed to achieve the best topology of the ANN-BP model. Although mortality prediction of the best ANN-BP (MSE = 0.0036, AUC = 0.83, R2 = 0.81) was more accurate than that of the SAPS score model (MSE = 0.0056, AUC = 0.82, R2 = 0.78), the execution time of the former (=45 min) was longer than that of the latter (=20 min). Therefore, the principal component analysis (PCA) was used to reduce the input feature dimensions, which, in turn, reduced the execution time up to 50%. Data reduction also helped to increase the network accuracy up to 90%. The likelihood of organ dysfunction determined by coupled ANN and scoring method technique can be much more efficient than the LODS model alone because the SOM could successfully classify the patients in 64 classes. The primary patient classification plays a major role in increasing the efficiency of an estimator.

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction

The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underway and the early drivers of clinical outcome cannot be readily determined. Thus, there is a need to better understand the immediate immune response to injury and how this might influence important patient outcomes such as multi-organ dysfunction syndrome (MODS). In this study, we have assessed the immune response to trauma in 61 patients at three different post-injury time points (ultra-early (<=1 h), 4-12 h, 48-72 h) and analysed relationships with the development of MODS. We developed a pipeline using Absolute Shrinkage and Selection Operator and Elastic Net feature selection methods that were able to identify 3 physiological features (decrease in neutrophil CD62L and CD63 expression and monocyte CD63 expression and frequency) as possible biomarkers for MODS development. After univariate and multivariate analysis for each feature alongside a stability analysis, the addition of these 3 markers to standard clinical trauma injury severity scores yields a Generalized Liner Model (GLM) with an average Area Under the Curve value of 0.92 ± 0.06. This performance provides an 8% improvement over the Probability of Survival (PS14) outcome measure and a 13% improvement over the New Injury Severity Score (NISS) for identifying patients at risk of MODS.

Trauma-Induced Damage-Associated Molecular Patterns-Mediated Remote Organ Injury and Immunosuppression in the Acutely Ill Patient

Trauma is one of the leading causes of death and disability in the world. Multiple trauma or isolated traumatic brain injury are both indicative of human tissue damage. In the early phase after trauma, damage-associated molecular patterns (DAMPs) are released and give rise to sterile systemic inflammatory response syndrome (SIRS) and organ failure. Later, protracted inflammation following sepsis will favor hospital-acquired infection and will worsen patient’s outcome through immunosuppression. Throughout medical care or surgical procedures, severe trauma patients will be subjected to endogenous or exogenous DAMPs. In this review, we summarize the current knowledge regarding DAMP-mediated SIRS or immunosuppression and the clinical consequences in terms of organ failure and infections.