Physiologic, demographic and mechanistic factors predicting New Injury Severity Score (NISS) in motor vehicle accident victims

Maritime accidents in the Yangtze River: A time series analysis for 2011-2020

The theoretical analysis of maritime accidents is a hot topic, but the time characteristics and dynamics of maritime accidents time series are still unclear. It is difficult to draw a clear conclusion from the cause analysis, so the accident is difficult to be predicted. To bridge this gap, this research analyzes the characteristics and evolution mechanism of maritime accidents time series from the perspective of complex network theory. The visual graph algorithm is used to model the complex network of maritime accidents data in 22 jurisdictions of the Yangtze River, map the time series into a complex network, and reveal the time characteristics and dynamics of maritime accidents time series based on the complex system theory. In the empirical analysis, degree distribution, clustering coefficient and network diameter are used to analyze the characteristics of time series. The results show that the degree distribution of maritime accidents time series network presents power-law characteristics in the macro and micro levels, which shows that the maritime accidents time series is scale-free. In addition, according to the clustering coefficient and network diameter, maritime accidents time series in the Yangtze River has the characteristics of small-world and hierarchical structure. The research of this manuscript shows that the occurrence of maritime accidents is not random events and does not follow specific patterns but presents the characteristics of complex systems, and this phenomenon is common. The analysis of maritime accidents time series by complex network theory can provide theoretical support for maritime traffic safety management.

How Gender Affects Motor Vehicle Crashes: A Case Study from San Antonio, Texas

Traffic crashes are among the leading causes of injuries and fatalities worldwide. The main assumption of this study is that traffic crash rates, injury severity, and driving behaviors differ by the driver’s gender. Utilizing ten years (2011–2020) of data from the Texas Crash Record and Information System database, this study investigates how some of the most prominent driving behaviors leading to crashes and severe injuries (distracted driving, speeding, lane departure, and driving under influence) vary by gender in San Antonio, Texas. The spatial distribution of crashes associated with these driving behaviors by gender is also investigated, as well as the influence of some environmental and temporal variables on crash frequency and injury severity. This study adopted bivariate analysis and logistic regression modeling to identify the effect of different variables on crash occurrence and severity by gender. Male drivers were more likely to be involved in a speeding/DUI/lane departure-related crash and subsequent severe injuries. However, female drivers were slightly more associated with distracted-driving crashes and subsequent injuries. Nighttime, interstate/highway roads, the weekend period, and divider/marked lanes as the primary traffic control significantly increased the crash and injury risk of male drivers. Driving behavior-related crashes were mostly concentrated on some interstate road segments, major intersections, and interchanges. The results from this study can be used by authorities and policy-makers to prioritize the use of limited resources, and to run more effective education campaigns to a targeted audience.

The Value of Physiological Scoring Criteria in Predicting the In-Hospital Mortality of Acute Patients; a Systematic Review and Meta-Analysis

Introduction:

There is no comprehensive meta-analysis on the value of physiological scoring systems in predicting the mortality of critically ill patients. Therefore, the present study intended to conduct a systematic review and meta-analysis to collect the available clinical evidence on the value of physiological scoring systems in predicting the in-hospital mortality of acute patients.

Method:

An extensive search was performed on Medline, Embase, Scopus, and Web of Science databases until the end of year 2020. Physiological models included Rapid Acute Physiology Score (RAPS), Rapid Emergency Medicine Score (REMS), modified REMS (mREMS), and Worthing Physiological Score (WPS). Finally, the data were summarized and the findings were presented as summary receiver operating characteristics (SROC), sensitivity, specificity and diagnostic odds ratio (DOR).

Results:

Data from 25 articles were included. The overall analysis showed that the area under the SROC curve of REMS, RAPS, mREMS, and WPS criteria were 0.83 (95% CI: 0.79-0.86), 0.89 (95% CI: 0.86-0.92), 0.64 (95% CI: 0.60-0.68) and 0.86 (95% CI: 0.83-0.89), respectively. DOR for REMS, RAPS, mREMS and WPS models were 11 (95% CI: 8-16), 13 (95% CI: 4-41), 2 (95% CI: 2-4) and 17 (95% CI: 5-59) respectively. When analyses were limited to trauma patients, the DOR of the REMS and RAPS models were 112 and 431, respectively. Due to the lack of sufficient studies, it was not possible to limit the analyses for mREMS and WPS.

Conclusion:

The findings of the present study showed that three models of RAPS, REMS and WPS have a high predictive value for in-hospital mortality. In addition, the value of these models in trauma patients is much higher than other patient settings.

The role of gender and temporal instability in driver-injury severities in crashes caused by speeds too fast for conditions

The effect of inappropriate speed adjustment to adverse conditions on crash-injury severities, and how this effect might vary across male and female drivers, and over time, is not well understood. To study this, single-vehicle crashes occurring in rainy weather, where speed too fast for conditions is a driver action identified as a contributing factor to the crash, were considered. The differences between the resulting crash-injury severities of male and female drivers (and how these differences change over time) is then studied utilizing three years of Florida crash data and estimating random parameters multinomial logit models of driver injury severity while considering potential heterogeneity in the means and variances of parameter estimates. Model estimation results show that there were significant differences in the driver-injury severities of male and female drivers, and that the effect of factors that determine injury severities varied significantly over time (statistically significant temporal instability). This suggests that male and female drivers generally perceive and react to rainy weather conditions in fundamentally different ways, and that their responses, as reflected by the effect that explanatory variables have on injury severity probabilities, change over time. However, there were two explanatory variables that had relatively stable effects on injury-severity probabilities over time and across genders: an indicator variable for crashes involving non-collision factors (including overturn/rollover crashes) and an indicator variable for restraint usage. Policies that target these two variables could produce long-term reductions in crash-injury severities under adverse conditions.

Predictors of Acute Mortality After Open Pelvic Fracture: Experience From 37 Patients From A Level I Trauma Center

BACKGROUND

Open pelvic fractures are caused by high-energy traumas and are accompanied by organ injuries. Despite improvements in pre-hospital care, the acute mortality rate following open pelvic fractures remains high. This study aimed to report experiences in managing open pelvic fractures, identify potential independent predictors that contribute to acute mortality in such patients, and generate a scoring formula to predict mortality rate.

METHODS

Open pelvic fracture patients managed during a 42-month period were retrospectively studied. Logistic regression analysis was used to determine predictors of acute mortality. Using the Youden index, threshold values of predictors were selected. Significant predictors were weighted to create a scoring formula. The area under the curve (AUC) was tested in this specific group.

RESULTS

The incidence of open pelvic fractures in all pelvic fractures was 4.9% (37/772), and the overall mortality rate was 21.6% (8/37). All the successfully resuscitated patients entered the reconstruction stage survived and underwent the complete treatment course. Univariate and multivariate logistic regression analyses revealed that the revised trauma score (RTS) was the single independent predictor of acute mortality. A scoring formula was generated following the statistical analysis. The probability of mortality was 0% and 100% when the score was above and below -2, respectively. This model predicted mortality with an AUC of 0.948 (95% confidence interval 0.881-1.000, P < 0.01).

CONCLUSION

The RTS may be a potential predictor of acute mortality in open pelvic fracture patients. Further work would be required to validate the clinical efficacy of the generated scoring formula.

Patient and injury characteristics associated with road traffic mortality in general hospitals in southern Thailand

Background

Road traffic injuries are a major public health burden in developing countries. Thailand has the highest fatality rate from road traffic injuries in southeast Asia so that prevention of unintentional injuries is important.

Objective

To identify patient and injury characteristics associated with road traffic mortality in the southern provinces of Thailand.

Methods

Data on a total of 78,862 road traffic injuries recorded by the general hospitals in 5 southern provinces of Thailand, during 2008–2013, were obtained from the Office of Disease Prevention and Control. Chi-squared test was used to determine the association between patient/injury characteristics and road traffic mortality, and logistic regression was used to identify the strength of associations.

Results

In this study, road traffic mortality was found to be 1.8% of all injuries. Most of the deaths occurred in males (61.7%), who were aged 25–44 years (35.8%), being drivers (68.6%), using motorcycle (78.4%), and not wearing a helmet (61.0%). Road traffic mortality was higher among males, older age people, those who were not wearing a helmet or not fastening a seat belt, pedestrians and when people crashed with or by motor car, with wound being penetrating or blunt with penetrating, and when they were having head or neck, chest, or abdominal or pelvic cavity injuries.

Conclusion

Policies and measures for reducing road traffic mortality should focus on males and older aged persons, use of safety devices, and occurrence of multiple injuries.

Racial differences in presentations and predictors of acute pain after motor vehicle collision

African Americans experience a greater burden of acute pain than non-Hispanic white individuals across of variety of acute medical conditions, but it is unknown whether this is the case after trauma. We evaluated pain, pain-related characteristics (eg, peritraumatic distress), and analgesic treatment in 2 cohorts of individuals (African American [n = 931] and non-Hispanic white [n = 948]) presenting to the emergency department (ED) after a motor vehicle collision. We performed a propensity-matched analysis (n = 796 in each group) to assess racial differences in acute pain in the ED. In multivariable models conducted within the matched sample, race was associated with moderate to severe axial pain (odds ratio [OR] 3.2; 95% confidence interval [CI]: 2.1-5.0, P < 0.001) and higher average numerical rating scale scores (1.3; 95% CI: 1.1-1.6; P < 0.001). After adjustment for pain and other covariates, non-Hispanic white patients were more likely to receive an opioid analgesic in the ED (OR 2.0; 95% CI: 1.4-3.0, P < 0.001) or at discharge (OR 4.9; 95% CI: 3.4-7.1, P < 0.001) and also less likely to receive an NSAID in the ED (OR 0.54; 95% CI: 0.38-0.78; P = 0.001) or at discharge (0.31; 95% CI: 0.43-0.84). Racial differences in the severity of acute posttraumatic pain after a motor vehicle collision are not explained by factors such as socioeconomic status or crash characteristics. Despite a higher burden of acute pain, African Americans were less likely to receive opioid analgesics and more likely to receive NSAIDs. Further work is needed to understand the relationship between pain severity, disparities in analgesic treatment, and longer term outcomes, such as post-motor vehicle collision chronic pain.

Investigation of driver injury severities in rural single-vehicle crashes under rain conditions using mixed logit and latent class models

Due to limited visibility and low skid resistance on road surface, single-vehicle crashes under rain conditions, especially those occurred in rural areas, are more likely to result in driver incapacitating injuries and fatalities. A three-year crash dataset including all rural single-vehicle crashes under rain conditions from 2012 to 2014 in four South Central states, i.e., Texas, Arkansas, Oklahoma, and Louisiana, are selected in this paper to analyze the impact factors on driver injury severity. The mixed logit model (MLM) and the latent class model (LCM) are developed on the same dataset. Several parsimony indices, e.g., AIC and BIC, and as well as McFadden pseudo r-squared, are calculated for all the models to evaluate their respective performance. Results show that choosing the uniform distribution as the prior for random parameters could better improve the goodness-of-fit of the MLM than using normal and lognormal distributions. In addition, the two-class LCM also shows superiority when compared to three- and four-class LCMs. Finally, a careful comparison between these two models is conducted, and the results indicate that the LCM has a slightly better performance in analyzing the aforementioned dataset in this study. Model estimation results show that curve, on grade, signal control, multiple lanes, pickup, straight, drug/alcohol impaired, and seat belt not used can significantly increase the probability of incapacitating injuries and fatalities for drivers in the two models. On the other hand, wet, male, semi-trailer, and young can significantly decrease the probability of incapacitating injuries and fatalities for drivers. This study provides an insightful understanding of the effects of these attributes on rural single-vehicle crashes under rain conditions and beneficial references for developing effective countermeasures for severe injury prevention.

Delayed endovascular aortic repair is associated with reduced in-hospital mortality in patients with blunt thoracic aortic injury

OBJECTIVE

The traditional approach to stable blunt thoracic aortic injury (BTAI) endorsed by the Society for Vascular Surgery is early (<24 hours) thoracic endovascular aortic repair (TEVAR). Recently, some studies have shown improved mortality in stable BTAI patients repaired in a delayed manner (≥24 hours). However, the indications for use of delayed TEVAR for BTAI are not well characterized, and its overall impact on the patient's survival remains poorly understood. We sought to determine whether delayed TEVAR is associated with a decrease in mortality compared with early TEVAR in this population.

METHODS

We conducted a retrospective cohort study of adult patients with BTAI (International Classification of Diseases, Ninth Revision diagnosis code 901.0) who underwent TEVAR (International Classification of Diseases, Ninth Revision procedure code 39.73) from 2009 to 2013 using the National Sample Program data set. Missing physiologic data were imputed using chained multiple imputation. Patients were parsed into groups based on the timing of TEVAR (early, <24 hours, vs delayed, ≥24 hours). The χ², Mann-Whitney, and Fisher exact tests were used to compare baseline characteristics and outcomes of interest between groups. Multivariable logistic regression for mortality was performed that included all variables significant at P ≤ .2 in univariate analyses.

RESULTS

A total of 2045 adult patients with BTAI were identified, of whom 534 (26%) underwent TEVAR. Patients with missing data on TEVAR timing were excluded (n = 27), leaving a total of 507 patients for analysis (75% male; 69% white; median age, 40 years [interquartile range, 27-56 years]; median Injury Severity Score [ISS], 34 [interquartile range, 26-41]). Of these, 378 patients underwent early TEVAR and 129 underwent delayed TEVAR. The two groups were similar with regard to age, sex, race, ISS, and presenting physiology. Mortality was 11.9% in the early TEVAR group vs 5.4% in the delayed group, with the early group displaying a higher odds of death (odds ratio, 2.36; 95% confidence interval, 1.03-5.36; P = .042). After adjustment for age, ISS, and admission physiology, the association between early TEVAR and mortality was preserved (adjusted odds ratio, 2.39; 95% confidence interval, 1.01-5.67; P = .047).

CONCLUSIONS

Consistent with current Society for Vascular Surgery recommendations, more BTAI patients underwent early TEVAR than delayed TEVAR during the study period. However, delayed TEVAR was associated with significantly reduced mortality in this population. Together, these findings support a need for critical appraisal and clarification of existing practice guidelines in management of BTAI. Future studies should seek to understand this survival disparity and to determine optimal selection of patients for early vs delayed TEVAR.

Traumatic and Nontraumatic Spinal Cord Injuries

OBJECTIVE

Owing to the aging of the population in the United States, it is anticipated that injury mechanisms, treatment, and outcomes of spinal cord injuries (SCI) will change. There is a scarcity of literature on nontraumatic SCI. Our goal in this study was to evaluate the causes, management, complications, and outcomes after SCI.

METHODS

In a retrospective review, patients with traumatic and nontraumatic SCI admitted to the inpatient rehabilitation unit at a level 1 trauma center from 2003 to 2013 were reviewed.

RESULTS

In all, 757 entries were identified, and 685 unique patients met our inclusion criteria; 17.4% were <35 years of age, 51.7% were 35 to 64 years of age, and 30.9% were at least 65 years old. The young adults had the highest proportion of fractures (60.5%) and subluxations (21.8%), whereas the oldest group had the highest rates of stenosis (35.4%), spondylotic myelopathy (16.5%), and cancer (15.1%). In SCI patients <35 years of age, 66.6% of injuries were caused by traumatic mechanisms of injury compared with 30.2% in the geriatric cohort. In the total of all SCI, 61.6% were nontraumatic. Surgical management was more prevalent with increasing age (58.8%, 73.7%, 82.1% from youngest to oldest group), as were overall rates of complications (58.6%, 59.4%, 66.7%). Mortality rates significantly increased with age (2.5%, 18.9%, 40.6% overall mortality rates in the 3 age groups). The overall mortality rate in nontraumatic SCI patients was 27.7% compared with 14.8% in traumatic SCI patients.

CONCLUSIONS

Falls caused significantly more SCIs than expected, but most SCIs were predominantly nontraumatic in cause. The epidemiology of SCI is shifting rapidly.

Accuracy of SOFA score in prediction of 30-day outcome of critically ill patients

Objectives

Researchers have attempted to design various scoring systems to determine the severity and predict the outcome of critically ill patients. The present study aimed to evaluate the accuracy of SOFA score in predicting 1-month outcome of these patients in emergency department.

Methods

The present study is a prospective cross-sectional study of >18 year old non-trauma critically ill patients presented to EDs of 3 hospitals, Tehran, Iran, during October 2014 to October 2015. Baseline characteristics, SOFA score variables, and 1-month outcome of patients were recorded and screening performance characteristics of the score were calculated using STATA 11 software.

Results

140 patients with the mean age of 68.36 ± 18.62 years (18–95) were included (53.5% male). The most common complaints were decrease in level of consciousness (76.43%) and sepsis (60.0%), were the most frequent final diagnoses. Mean SOFA score of the patients was 7.13 ± 2.36 (minimum 2 and maximum 16). 72 (51.43%) patients died during the following 30 days and 16 (11.43%) patients were affected with multiple organ failure. Area under the ROC curve of SOFA score in predicting mortality of studied patients was 0.73 (95%CI: 0.65–0.81) (Fig. 2). Table 2 depicts screening performance characteristics of this scale in prediction of 1-month mortality in the best cut-off point of ≥7. At this cut-off point, sensitivity and specificity of SOFA in predicting 1-month mortality were 75% and 63.23%, respectively.

Conclusion

Findings of the present study showed that SOFA scoring system has fair accuracy in predicting 1-month mortality of critically ill patients. However, until a more reliable scoring system is developed, SOFA might be useful for narrative prediction of patient outcome considering its acceptable likelihood ratios.