Cohort profile: the ESC EURObservational Research Programme Non-ST-segment elevation myocardial infraction (NSTEMI) Registry

AIMS

The European Society of Cardiology (ESC) EURObservational Research Programme (EORP) Non-ST-segment elevation myocardial infarction (NSTEMI) Registry aims to identify international patterns in NSTEMI management in clinical practice and outcomes against the 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without ST-segment-elevation.

METHODS AND RESULTS

Consecutively hospitalised adult NSTEMI patients (n = 3620) were enrolled between 11 March 2019 and 6 March 2021, and individual patient data prospectively collected at 287 centres in 59 participating countries during a two-week enrolment period per centre. The registry collected data relating to baseline characteristics, major outcomes (in-hospital death, acute heart failure, cardiogenic shock, bleeding, stroke/transient ischaemic attack, and 30-day mortality) and guideline-recommended NSTEMI care interventions: electrocardiogram pre- or in-hospital, pre-hospitalization receipt of aspirin, echocardiography, coronary angiography, referral to cardiac rehabilitation, smoking cessation advice, dietary advice, and prescription on discharge of aspirin, P2Y12 inhibition, angiotensin converting enzyme inhibitor (ACEi)/angiotensin receptor blocker (ARB), beta-blocker, and statin.

CONCLUSION

The EORP NSTEMI Registry is an international, prospective registry of care and outcomes of patients treated for NSTEMI, which will provide unique insights into the contemporary management of hospitalised NSTEMI patients, compliance with ESC 2015 NSTEMI Guidelines, and identify potential barriers to optimal management of this common clinical presentation associated with significant morbidity and mortality.

Age-based variability in the association between restraint use and injury type and severity in multi-occupant crashes

PURPOSE

Previous studies have shown older adults receive relatively less protection from seat belts against fatal injuries, however it is unknown how seat belt protection against severe and torso injury changes with age. We estimated age-based variability in seat belt protection against fatal injuries, injuries with maximum abbreviated injury scale greater than two (MAIS 3+), and torso injuries.

METHODS

We leveraged the Crash Outcome Data Evaluation System to analyze binary indicators of fatal, MAIS 3+, and torso injuries. Using a matched cohort design and conditional Poisson regression, we estimated age-based relative risks (RR) of the outcomes associated with seat belt use.

RESULTS

Our results suggested that seat belts were highly protective against fatal injuries for all ages. For ages 16-30, seat belt use was associated with 66% lower risk of MAIS3+ injury (RR 0.34, 95% CI 0.30, 0.38) for occupants of the same vehicle, whereas for ages 75 and older, seat belt use was associated with 38% lower risk of MAIS3+ injury (RR 0.62; 95% CI 0.45, 0.86) for occupants in the same vehicle. The association between restraint use and torso injury also attenuated with age.

CONCLUSIONS

In multi-occupant crashes, seat belts were highly protective against fatal and MAIS3+ injury, however seat belt protection against MAIS3+ and torso injury attenuated with age.

Socioeconomic and Demographic Factors Effect in Association with Driver's Medical Services after Crashes

Motor vehicle crashes are the third leading cause of preventable-injury deaths in the United States. Previous research has found links between the socioeconomic characteristics of driver residence zip codes and crash frequencies. The objective of the study is to extend earlier work by investigating whether the socioeconomic characteristics of a driver’s residence zip code influence their likelihood of resulting in post-crash medical services. Data were drawn from General Use Model (GUM) data for police crash reports linked to hospital records in Kentucky, Utah, and Ohio. Zip-code-level socioeconomic data from the American Community Survey were also incorporated into analyses. Logistic regression models were developed for each state and showed that the socioeconomic variables such as educational attainment, median housing value, gender, and age have p-values < 0.001 when tested against the odds of seeking post-crash medical services. Models for Kentucky and Utah also include the employment-to-population ratio. The results show that in addition to age and gender, educational attainment, median housing value and rurality percentage at the zip code level are associated with the likelihood of a driver seeking follow-up medical services after a crash. It is concluded that drivers from areas with lower household income and lower educational attainment are more likely to seek post-crash medical services, primarily in emergency departments. Female drivers are also more likely to seek post-crash medical services.

Exploring mobility pattern changes between before, during and after COVID-19 lockdown periods for young adults

The paper aims to investigate changes in travel behavior due to COVID-19 focusing in one of the most active social groups in Greece. A questionnaire survey was conducted and 306 young adults (age 18-34 years) living in various Greek cities responded. The survey collected information about travel-related preferences before, during and after the 1st lockdown and during the 2nd lockdown of the COVID-19 pandemic in Greece. City attributes of the respondent's residency location before and after the 1st lockdown were collected. The data are analyzed descriptively and through statistical modelling techniques. During the 1st lockdown an important increase in physical exercise frequency was observed, but this increase was not permanent. The COVID-19 pandemic resulted in essential reductions in the frequency of public transport use and in an increase of walking frequency. The public transport use reduction was mainly attributed to people that had access to a private car and after the 1st lockdown moved to a smaller city. On the other hand, the changes in walking frequency are closely linked to the city's attributes. Useful policy implications are being derived about how the pandemic can assist in promoting sustainable urban mobility goals.

Association between excessive supraventricular ectopic activity and future diagnosis of atrial fibrillation in patients with cryptogenic stroke

Funding Acknowledgements

Type of funding sources: None.

Background

The relationship between the excessive supraventricular ectopic activity (ESVEA) and the subclinical atrial fibrillation (AF) in patients with cryptogenic stroke is yet not fully understood.

Purpose

The aim of this study is to examine the prognostic significance of ESVEA for the development of AF in those patients.

Methods

The study retrospectively included 124patients, hospitalized for a cryptogenic stroke between 2014 and 2015. Twenty-four hour inpatient Holter monitoring, was used to define ESVEA as the presence of ≥20 premature atrial complexes per hour (PACs/h), along with a duration of the longest run of supraventricular tachycardia (LSVR) ≥5 seconds. After approximately 5 years of follow-up, the patients were examined for AF.

Results

The remaining 111 patients(12 died and 1 was lost during follow-up) had a median age of 56 and 13 (11.71%) of them were diagnosed with AF (AF patients). The median value of CHA2DS2-VASc score was 3 and was similar for the two groups (p=0.252). Patients with AF had a significantly higher number of PACs/h and a longer duration of LSVR compared to nonAF patients (16.67 vs. 0.21, p&lt;0.001 and 3 vs. 0 seconds, p&lt;0.001, respectively). The existence of ESVEA was also significantly more prevalent among the AF patients (46.15%, 95% CI: 17.78% - 74.22%) compared to non-AF ones (6.1%, 95% CI: 1.3% - 10.7%, p&lt;0.001). ROC analysis revealed the high diagnostic test accuracy of both PACs/h and LSVR for AF. The area under the curve was 97.2% (p&lt;0.001) for PACs/h and 81.1% (p&lt;0.001) for LSVR.

Conclusions

Excessive atrial ectopy, detected with 24h inpatient Holter monitoring, is a significant indicator of future development of AF, in patients presenting originally with a cryptogenic stroke.

Use of codes data to improve estimates of at-fault risk for elderly drivers

The fastest-growing demographic in the United States is people aged 65 and over. Because elderly drivers may experience decline in the physical and mental faculties required for driving (which could lead to unsafe driving behaviors), it is critical to determine whether elderly drivers are more likely than younger drivers to be at fault in a crash. This study uses Kentucky crash data and linked hospital and emergency department records to evaluate whether linked data can more accurately estimate the crash propensity of elderly drivers to be at-fault in injury crashes. The Kentucky crash data is edited to conform to the General Use Model (GUM), with crash propensities for linked data compared to propensities developed using the GUM dataset alone. The quasi-induced exposure method is used to determine crash exposure. Factors such as age, gender, and crash location are explored to assess their influence on the risk of a driver being at fault in an injury crash. The overall findings are consistent with previous research - elderly drivers are more likely than younger drivers to be at fault in a crash. Linking crash with hospital and emergency department records could also establish a clearer understanding of the injury crash propensity of all age groups. Equipped with this knowledge, transportation practitioners can design more targeted and effective countermeasures and safety programs to improve the safety of all motorists.

Identifying high-risk commercial vehicle drivers using sociodemographic characteristics

Crash data, from the state of Kentucky, for the 2015-2016 period, show that per capita crash rates and increases in crash-related fatalities were higher than the national average. In an effort to explain why the U.S. Southeast experiences higher crash rates than other regions of the country, previous research has argued the regions unique socioeconomic conditions provide a compelling explanation. Taking this observation as a starting point, this study examines the relationship between highway safety and socioeconomic and demographic characteristics, using an extensive crash dataset from Kentucky. Its focus is single- and two-unit crashes that involve commercial motor vehicles (CMVs) and automobiles. Using binary logistic regression and the quasi-induced exposure technique to analyze data on the socioeconomic and demographic attributes of the zip codes in which drivers reside, factors are identified which can serve as indicators of crash occurrence. Variables such as income, education level, poverty level, employment, age, gender, and rurality of the driver's zip code influence the likelihood of a driver being at fault in a crash. Socioeconomic factors exert a similar influence on CMV and automobile crashes, irrespective of the number of vehicles involved. Research findings can be used to identify groups of drivers most likely to be involved in crashes and develop targeted and efficient safety programs.

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

INTRODUCTION

The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population.

METHOD

Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS.

RESULTS

The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations.

CONCLUSIONS

Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.

Driver License Renewal for the Elderly: A Case Study

Periodic renewal of driver licenses is an integral part of the driver licensing procedures for most states. Renewal of driver licenses is usually required every 4 years, and many states conduct vision tests before granting renewal. A few states require additional testing, whereas several states have no vision testing or any other examinations at renewal. Still fewer have additional requirements for older drivers. The increasing percentage of older drivers and the visual changes due to aging or disease are also additional concerns. Thus, it was considered important to systematically review current practices regarding license renewal and retesting and identify potential changes in these procedures. For older drivers, a more frequent renewal period is proposed, accompanied by a vision screening and a medical questionnaire to determine physical and mental status of older drivers.

Gender Effect on the Accident Patterns of Elderly Drivers

Increased suburbanization, a greater dependency on the automobile, the continuous growth of the elderly population, and a significant increase in the number of elderly female drivers have created the need for research to investigate gender distinctions in the accident patterns of elderly drivers. Differences in accident patterns between younger and older drivers in this investigation are attributed partially to aging-related diminished abilities and partially to differences in drivership and licensure levels between the past and the present. This study analyzes and compares the accident patterns of elderly males and females. It shows that females aged 65 and over have higher accident involvement rates than elderly males. Accident exposure data indicate a similar exposure for elderly males and females making the higher rates for females more significant. In contrast, the accident patterns of males and females under 65 are similar, suggesting that gender-related differences may disappear in the future.

Evaluation of a simulation-based surrogate safety metric

The development of surrogate safety measures is essential due to the problems of availability and quality of historical crash data. The Aggregate Conflict Propensity Metric (ACPM) is a surrogate metric recently proposed and it is based on conflict studies and traffic simulations. ACPM is expected to be capable of assessing the relative safety levels of traffic facilities and/or treatments in order to help traffic engineers to select appropriate treatments based on traffic safety estimates. This paper presents three experimental tests conducted to evaluate the reliability of ACPM. In each test, ACPM is compared to a traditional conflict indicator in terms of identifying and ranking safety of traffic conditions under various traffic volumes based on traffic simulations. ACPM shows its strength and reliability in all three tests, as it provides results highly consistent with the Highway Safety Manual. The experimental tests indicate that ACPM is a promising surrogate safety measure that can appropriately identify relative safety among traffic treatments and/or facilities and provide traffic engineers with useful information on potential safety impact.

Quasi-induced exposure method: evaluation of not-at-fault assumption

Crash rates are used to establish the relative safety of various variables of concern such as driver classes, vehicle types and roadway components. Appropriate exposure data for estimating crash rates is critical but crash databases do not contain information on driver or vehicle exposure. The quasi-induced exposure method, which uses not-at-fault driver/vehicle data as an exposure metric, is a technique used in order to overcome this problem. The basic assumption made here is that not-at-fault drivers represent the total population in question. This paper examines the validity of this assumption using the Kentucky crash database to define two samples of not-at-fault drivers. One sample included only not-at-fault drivers selected from the first two vehicles in a multi-vehicle crash (two or more vehicles involved) while the other included the not-at-fault drivers from multi-vehicle crashes with more than two vehicles involved and excluding the first two drivers. The assumption is that the randomness of the involvement of drivers in the second sample is more reasonable than the drivers in the first two vehicles involved in crashes. The results indicate that these two samples are similar; there is no statistical evidence demonstrating that both samples represent two different populations in the maneuvers and other variables/factors examined here; and they are representative simple random samples of the driver population with respect to the distribution of the driver age when there is no reasonable doubt about investigating officers' judgments. Thus, estimating relative crash propensities for any given driver type by using the quasi-induced exposure approach will yield reasonable estimates of exposure.

Crash involvement of drivers with multiple crashes

A goal for any licensing agency is the ability to identify high-risk drivers. Kentucky data show that a significant number of drivers are repeatedly involved in crashes. The objective of this study is the development of a crash prediction model that can be used to estimate the likelihood of a driver being at fault for a near future crash occurrence. Multiple logistic regression techniques were employed using the available data for the Kentucky licensed drivers. This study considers as crash predictors the driver's total number of previous crashes, citations accumulated, the time gap between the latest two crashes, crash type, and demographic factors. The driver's total number of previous crashes was further disaggregated into the drivers' total number of previous at-fault and not-at-fault crashes. The model can be used to correctly classify at-fault drivers up to 74.56% with an overall efficiency of 63.34%. The total number of previous at-fault crash involvements, and having previous driver license suspensions and traffic school referrals are strongly associated with a driver being responsible for a subsequent crash. In addition, a driver's likelihood to be at fault in a crash is higher for very young or very old, males, drivers with both speeding and non-speeding citations, and drivers that had a recent crash involvement. Thus, the model presented here enables agencies to more actively monitor the likelihood of a driver to be at fault in a crash.

Evaluating the impact of passengers on the safety of older drivers

PROBLEM

This study involved a quasi-induced exposure analysis of 4 years of crashes involving older drivers in the state of Kentucky.

METHOD

Single- and multivehicle crashes were disaggregated according to the number of passengers: (a) no passenger, (b) one passenger, and (c) two or more passengers.

RESULTS

Overall, the presence of two or more passengers was found to negatively impact the probability that drivers 75 years of age or older were at fault in crashes. Several potential factors were studied for interactive effects with passengers: vehicle occupant gender mix, time of the day, road curvature, grade, and number of lanes. The negative impact of passengers increased for some geometric road conditions. However, older drivers were found to be safer at night when carrying two or more passengers. The presence or absence of passengers was not found to affect the 65- to 74-year-old driver group. Groups of male vehicle occupants with a 75+ male driver were found to have high single-vehicle crash rates.

IMPACT

These results are among the first to directly consider the effect of passengers on the crash-causing propensity of older drivers and the findings suggest more work is warranted to consider causes for the crash rate differences.

Quasi-induced exposure: methodology and insight

Even though the numerator in accident rates can be accurately determined nowadays, the denominator of these rates is an item of discussion and debate within the highway safety community. A critical examination of an induced exposure technique, based on the non-responsible driver/vehicle of a two-vehicle accident (quasi-induced exposure), is presented here. Differences in exposure for a series of accident location and time combinations are investigated, the assumption of similarities between drivers of single-vehicle accidents and the responsible driver of multiple-vehicle accidents is refuted, and the use of the non-responsible driver as a measure of exposure is tested using vehicle classification data. The results of the analyses reveal the following: (1) accident exposure is different for different location and time combinations: (2) induced exposure estimates provide an accurate reflection of exposure to multiple-vehicle accidents; (3) induced exposure estimates are acceptable surrogates for vehicle miles of travel when estimates are made for conditions during which the mix of road users is fairly constant; and (4) the propensity for involvement in single-vehicle accidents is generally different than that in multiple-vehicle accidents for a given class of road users. We concluded that the quasi-induced exposure is a powerful technique for measuring relative exposure of drivers or vehicles when real exposure data are missing.

Trends in highway safety: effects of an aging population on accident propensity

Aging of the United States population has a potentially adverse effect on highway safety. A key question is whether the known deterioration of driving skills with aging will be compensated by other factors, especially improved learning and attitudinal experiences of more recent cohorts. We investigate effects of driver age, cohort, and gender on accident propensity and evaluate confounding effects of year, location, and lighting. The accident propensity of different groups of drivers is measured, using a database of two-vehicle accidents, by the ratio of the number of at-fault drivers of a specific group to the corresponding number of not-at-fault drivers. Logistic regression modelling determines the statistical significance of the findings. The analysis reveals the following statistically significant effects: (a) middle-aged drivers are safer than younger drivers who, in turn, are safer than older drivers; (b) female drivers are safer on average than male drivers; (c) younger female drivers are safer than younger male drivers; (d) older male drivers are safer than older female drivers; (e) more recent cohorts of older drivers are safer than more distant cohorts; and (f) more distant cohorts of younger drivers are safer than more recent cohorts. We conclude that driver cohort provides a plausible explanation for many of the measurable, time-related accident trends that are observed. Accordingly, older drivers will be safer in the future because they will have acquired basic driving skills and attitudes in increasingly more automobile-dominated times. At the same time, the cohort effect appears small relative to other time related effects, notably aging, and older drivers will continue to be a high-risk component of the driving population and to require special consideration in driver education and licensing and in highway design and operations.