Latest news with #crashrisk
Medscape
a day ago
- Automotive
- Medscape
Crash Risk After Heart Device Implant Still Hard to Predict
TOPLINE: Models using driving and health data to predict 1-year crash risk after the implantation of a cardioverter-defibrillator showed poor discrimination between individuals who crashed motor vehicles and those who did not. However, such models with good calibration may help guide discussions about crash risk between clinicians and patients. METHODOLOGY: Clinical guidelines recommend temporarily ceasing driving after the implantation of a cardioverter-defibrillator; however, these restrictions can result in social isolation or loss of income. Empirical data to inform such driving restrictions are limited. Researchers in Canada used population-based administrative data and identified licensed drivers who had a first implantation of a cardioverter-defibrillator between 1998 and 2018 to estimate the subsequent risk for a motor vehicle crash using prediction models. The recipients were stratified into two cohorts according to the indication for their implants: those receiving implants for primary prevention of sudden cardiac death (n = 3652; median age, 66 years; 18% women) and those receiving implants for secondary prevention (n = 3408; median age, 65 years; 16% women). The outcome of interest was the involvement of the implant recipient as a driver in one or more crashes within the first year after the implantation procedure; crashes considered were those attended by police and/or involving an insurance claim. TAKEAWAY: Overall, 352 drivers (9.6%) in the primary prevention cohort and 270 drivers (7.9%) in the secondary prevention cohort were involved in crashes within the first year after implantation. The crash prediction models poorly distinguished between individuals who crashed and those who did not in both the primary and secondary prevention cohorts (c-statistics, 0.60 and 0.61, respectively). However, the models showed good calibration for both cohorts (calibration slopes, 1.14 and 1.07, respectively), suggesting that the models could be helpful in guiding discussions between clinicians and patients. In the primary prevention cohort, the top predictors of crash were male sex, number of crashes in the past year, and active vehicle insurance in the past year; in the secondary prevention cohort, the predictors were male sex, no history of seizure, active opioid prescriptions, and active vehicle insurance in the past year. IN PRACTICE: "Clinicians already use clinical intuition and common sense to identify patients at higher risk of SCI [sudden cardiac incapacitation] , reserving their most strident advice to avoid driving for the individuals they consider to be at highest risk," the researchers noted. "Using baseline health and driving data to formally predict post-implantation crash risk and personalize driving restrictions is a strategy that has the potential to strengthen this clinical practice, but our findings suggest this approach is not yet ready to deploy in clinical practice," they added. SOURCE: This study was led by John A. Staples of the University of British Columbia in Vancouver, British Columbia, Canada. It was published online on June 24, 2025, in Heart. LIMITATIONS: This study lacked a direct measure of road exposure, which may have affected the model performance. Data regarding several parameters, including the indication for implantation, were missing at several occasions. The researchers were unable to identify the crashes specifically caused by sudden cardiac incapacitation. DISCLOSURES: This study received a grant from the Heart and Stroke Foundation of Canada. One author reported receiving a Mentored Clinician Scientist Award from Vancouver Coastal Health Research Institute and a Health Professional-Investigator Award from Michael Smith Health Research BC. Another author reported receiving support from Michael Smith Health Research BC and the British Columbia Emergency Medicine Network. This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
Yahoo
6 days ago
- Automotive
- Yahoo
Greater Than and Honda announce R&D partnership to quantify crash risk using AI risk intelligence
New R&D partnership utilizes Greater Than's AI risk intelligence to uncover crash risk pattern Data-driven insights will pinpoint high-risk areas and reveal the behavioral and environmental factors behind them Project outcomes are expected to fuel breakthroughs in driver safety innovation, infrastructure design, and mobility solutions STOCKHOLM, June 25, 2025 /PRNewswire/ -- Greater Than, the global provider of risk intelligence into road safety and climate impact, is proud to announce a new research and development partnership with multinational automotive manufacturer Honda, focused on quantifying crash risk through deep AI-driven data insights. The R&D initiative will analyze large-scale anonymized driving data to identify areas with high crash risk. By applying Greater Than's globally unique AI technology that measures the driver influence on risk, the project will identify reasons for elevated crash risks in specific geographical areas, providing scope for targeted and informed changes to reduce risk. "Partnering with Greater Than allows us to tap into the next generation of AI-driven risk analysis," said Yuki Ishikawa, Software-Defined Vehicle (SDV) Integrated Strategy Division at Honda. "Unlocking deep insights from real-world driving behavior and better understanding the factors behind crash risk supports our mission to achieve zero traffic collision fatalities involving Honda motorcycles and automobiles worldwide by 2050." In the first phase of the project, Greater Than will apply its AI technology, trained for over 20+ years using real-life driving data, to uncover meaningful risk insights from the anonymized driving data and draw conclusions on the factors contributing to risk level across different geographical areas in Japan. Greater Than will then overlay data such as road types, infrastructure and nearby buildings, to understand how external surroundings influence crash risk. "This is an exciting and commercially strategic project that transforms anonymized driving data into powerful, actionable insights," said Johan Forseke, Head of APAC at Greater Than. "The ability to predict crash risk with AI-driven precision offers Honda a clear competitive edge. The findings will not only unlock new opportunities for innovation in safety technology but also create tangible value for infrastructure planning and broader mobility solutions." This collaboration highlights the growing role of predictive AI in transforming the mobility landscape with a safety-first mindset. Press contact Greater ThanPR@ 855 593 This information was brought to you by Cision The following files are available for download: Honda x Greater Than press release 2025-06-25 Honda x Greater Than - Press Release View original content: Melden Sie sich an, um Ihr Portfolio aufzurufen.
CNA
18-06-2025
- Automotive
- CNA
Honda to recall over 259,000 US vehicles over brake pedal issue, NHTSA says
Honda Motor is recalling 259,033 vehicles in the U.S. due to a faulty brake pedal that can shift out of position and hinder braking, raising the risk of crashes or injury, the U.S. National Highway Traffic Safety Administration said on Wednesday. The company is recalling certain 2021-2025 Acura TLX, 2023-2025 Acura MDX, and 2023-2025 Honda Pilot vehicles, NHTSA said.
