The registry should collect the prehospital management or link with the Thai EMS database

Data on treatment, outcome and post-crash transportation were collected from medical records. If a patient was admitted to the hospital, the outcome of treatment was reassessed at day 30 after a crash to be consistent with the World Health Organization definition of road traffic death. Alcohol-use information was obtained in various ways: from patients who verbally indicated that they had consumed alcohol prior to the injury; from relatives or from those who transported patients to the hospital; or by physical examination by a health provider, or laboratory testing. These data were then entered into the NIEM electronic database. This study was reviewed and approved by the Faculty of Medicine Siriraj Hospital Institutional Review Board. We conducted a retrospective review study using data collected by the NIEM registry during the 2008–2015 New Year holiday and 2008–2014 Songkran holiday. We excluded patients who died at the scene and those who were not transported to hospitals because no transportation method for these patients had been recorded in the registry. Severe RTI patients were defined as patients who were admitted to the hospital, were referred, or had died in the emergency department.Subsequently, we categorized data into two cohorts: a control group, and an EMS utilization group, which included patients who were transported to hospitals by FR, BLS, ILS, or ALS ambulances. The registry also recorded the vehicle type. We further classified the data according to whether the victims were vulnerable road users or non-vulnerable road users.We also categorized the time of the day that patients visited hospitals,vertical outdoor farming dividing the day by 06:00–17:59 and 18:00–05:59.

Patients who used helmets and seat belts were combined. Mortality included death in EDs and during referral, death in the initial 24 hours after admission, and death 1–30 days after admission. Survival was defined as patients who either survived after 30 days of admission or were discharged from hospital.Logistic regression was used to analyze the primary outcome, which was the association between EMS utilization and mortality of RTI patients; we then adjusted the outcome for factors that affected injury severity, such as age, sex, being a vulnerable road user, road characteristics, alcohol consumption, and helmet or seat belt use.We conducted subgroup analyses to identify factors related to the mortality of patients who were transported by EMS. Univariate analysis was conducted using chi-square test and Fisher’s exact test. We included factors that have been proven to be associated with RTI severity, as mentioned above, and level of EMS in a multiple logistic regression model. P values <0.05 were considered significant. We calculated statistics using R version 3.2.1.This study describes outcomes of severe RTI patients transported by EMS compared with patients transported by private vehicles. We conducted the analysis using a nationwide registry in Thailand, which has the highest traffic accident mortality rate in the world. Moreover, the registry collected data during holidays with a high incidence of RTIs. In this cohort, severe RTI patients transported by ambulance had a higher mortality rate than patients transported to hospitals by private vehicles, and this finding is in line with those of other studies.The higher mortality rate might be attributed to the fact that patients who were transported by EMS were more severely injured than those in the control group.

Our results demonstrated that approximately 40% of severe RTI patients were transported to hospitals by ambulance, which was less than reports from other countries. Recently, Huang et al. reported that 73.4% of RTI patients in Taiwan were transported by EMS. One possible reason for not using EMS may have been that patients might not have known or might have forgotten the four-digit number for ambulance services.This contact number is different from those of other public service agencies such as the police and fire departments. A continuous advertisement of the emergency number should be done to increase EMS use in Thailand. The demographic data revealed that the patients who used EMS had more factors that increased injury severity than the control group; for example, our analysis demonstrated that severe RTI patients transported by ambulance reported current alcohol consumption more than those who were not. Recent studies have reported that alcohol intoxication is associated with greater injury severity and higher mortality rates among RTI patients.We also found that severe RTI patients transported by EMS were more often injured on highways than patients who were not. This shows that the patients in the EMS use group were more severely injured than those in the control group, since accidents on highways were more likely to have occurred at high speed, which was associated with more severe injuries.Although we analyzed multiple logistic regression to adjust for confounding factors, certain factors related to injury severity were not included in the registry, such as vehicle speed, comorbidity, prehospital care time, or injury severity scores.To find out the real effect of EMS use in clinical outcomes of RTI patients, the registry should collect information about other factors related to severity of injuries. The subgroup analysis identified factors associated with mortality among severe RTI patients transported by EMS. It demonstrated that patients who were transported by ALS teams had significantly increased mortality. This might have been due to the fact that patients transported by ALS teams were at higher risk of increased severity when compared with patients transported by other EMS levels.

Another possibility is that ALS team use might increase the on-scene time, due to prehospital interventions such as administering intravenous fluids or performing endotracheal intubation,rolling grow table as opposed to the “scoop and run” concept. This concurs with findings of previous studies that the use of ALS teams did not improve clinical outcomes.The Ontario Prehospital Advanced Life Support Major Trauma Study demonstrated that implementation of ALS teams did not improve the survival of major trauma patients when compared with patients treated by BLS teams.The study also revealed that among patients with a Glasgow Coma Score less than 9 who needed endotracheal intubation, those transported by ALS teams had a significantly lower survival rate.However, our registry did not collect prehospital care time and prehospital intervention. Further studies should be conducted to determine the real effect of ALS teams on the clinical outcomes of RTI patients by analyzing all confounding factors. Helmet or seat belt use was a factor that reduced mortality in severe RTI patients transported by ambulance. This concurred with the findings of previous studies that showed that these protective devices reduce injury severity.Abu-Zidan et al. reported that restrained RTI patients showed significantly less severe injury as well as fewer surgeries compared with unrestrained patients.Furthermore, Nash et al. reported that seat belt use was associated with a significant reduction in injury severity, mortality rate, and length of stay among RTI patients.Liu et al. reviewed 61 observational studies and found that helmet use was a significant factor in reducing mortality and head injury in motorcycle crashes.Only 13.89% of patients in this cohort wore a helmet or seat belt, although Thai law requires helmet and seat belt use. Further studies should be conducted to explore barriers to helmet and seat belt use.Although we analyzed data from the largest RTI registry in the country, revealing high mortality rates among RTI patients, our study has certain limitations. First, because it was a retrospective observational study, there were missing data regarding accident time, helmet and seat belt use, alcohol consumption status, and road characteristics. Second, the collection method in the registry had a potential for recall bias since the data collectors interviewed patients or their relatives at the hospital. Third, the registry collects data only in the long holiday periods. Given the lack of data for non-holidays the registry could not represent the effect of EMS utilization during non-holidays. We also excluded patients who died at the scene and were not transported to hospitals. This might have changed the injury severity of the whole population. Furthermore, the analysis combined patients using helmet and seat belt in one variable as a protective factor for overall RTI patients, when the injuries have different mechanisms. Further investigation should conduct subgroup analysis comparing those using motorcycles vs. four-wheel vehicles. Moreover, as mentioned earlier, the registry did not collect data on confounding variables that could affect clinical outcomes, such as ISS, prehospital care time, vehicle speed, or patient comorbidities. Lacking prehospital intervention is another limitation.

Alcohol consumption was defined using patient history data and physical examination by the physician, which is not the gold standard. Blood alcohol levels should perhaps be included in the registry. Improving the registry will help enhance our understanding of these characteristics as well as the effects of EMS utilization on clinical outcomes. Aside from our suggestions to improve the registry, there are further implications from the results of this study. Since we found that the RTI patients transported by EMS during the holidays had increased mortality rates, we recommend that this group of patients be evaluated in a trauma resuscitation room earlier, especially for patients transported by ALS teams. And to reduce time spent in the ED, prehospital notification should be given to receiving hospitals by the ambulance team before arrival.The incidence of spinal epidural abscess , a highly morbid and potentially lethal deep tissue infection of the central nervous system, has risen significantly over the past decade.1, 2 Our tertiary care institution has experienced an increase of more than 200%, from 2.5 to 8 cases per 10,000 hospital admissions since 2005.Although the reasons are not clearly defined, various factors, such as an expanded, comorbidly ill, aging population, and procedures or behaviors predisposing to bacteremia, have been posited to contribute to the increased incidence of SEA.Because SEA may rapidly and unpredictably evolve to irreversible neurologic injury and diagnostic delays remain common,our goal was to use these data to inform a discrimination model that could be employed at the time of initial clinical presentation to prioritize potential cases for expeditious, advanced imaging to optimize patient outcomes.The design and selection criteria for cases and controls have been previously described.To ensure clinical relevance, the case and control groups were drawn from patients who presented with findings that either raised concern for SEA or who underwent a “rule-out” evaluation; magnetic resonance imaging or computed tomography and micro-biologic data were used to assign patients to the appropriate group. Baystate Medical Center , a 720-bed tertiary-care, regional, academic medical center currently serving a population of approximately 850,000 people in western Massachusetts experiences more than 33,000 annual adult discharges with a corresponding case-mix index of 1.72, indicating high severity and complexity of its inpatients relative to their diagnosis related group. Encounters were coded as “confirmed” SEA if there was a radiologist-confirmed finding of an epidural lesion on advanced imaging with a positive culture from lesion or blood; “probable” if there was a radiologist confirmed epidural lesion in the absence of positive cultures from lesion or blood; and “control” if no lesion was identified by the radiologist on the imaging study. This study was approved by the institutional review board.We preliminarily evaluated baseline comparison between cases and controls using univariable analyses and direct visualization methods. Because our goal was to develop a discrimination model, we used the Integrated Discrimination Improvement Index to identify candidate discriminators.The IDI represents the degree to which a candidate variable increases the event probability in cases, while decreasing the event probability in controls, thus discriminating cases from non-cases. We selected candidate predictive factors if they were immediately discernible upon clinical presentation and if their univariable IDI was >0.02, suggesting meaningful discrimination properties. To reduce bias in the prediction model, candidate variables had to have at least 20 events to be considered.The multi-variable logistic regression model initially included all candidate variables and was then refined using a backwards selection process, with a p-value for removal of 0.05. We used Youden’s J7 to identify the cut point that maximized sensitivity and specificity. Areas under the receiver operator curve of the full- vs. restricted-models were compared using previously described methods.We assessed model fit using the Hosmer-Lemeshow goodness of fit and Stukel tests. Because measures of model validation may be overly optimistic when derived on the sample used for coefficient estimation, we generated bootstrapped validation measures.We used Stata 14.2 and R for analyses.