Clinical and radiological risk factors for poor outcomes in patients with spontaneous muscle hematomas.

PURPOSE: Spontaneous muscle hematomas (SMH) are frequently seen in the Emergency Department (ED), particularly as a complication of anticoagulation treatments. To date, there are no standard guidelines for the management of this condition in the ED. This work aims to identify clinical-radiological parameters of SMH at risk of poor outcomes. METHOD: This is a retrospective, observational cohort study conducted in an urban teaching hospital from 2016 to 2019. A multivariate logistic regression analysis was performed to identify parameters independently associated with an adverse outcome defined as the need for treatment (blood products, TAE, surgery) or hospitalization. The parameters analyzed were hematoma size, anticoagulation therapy, age, and the Charlson Comorbidity Index (CCI). ROC analysis was performed to identify the best cut-off hematoma size value to predict poor outcomes. RESULTS: Our study enrolled 231 patients aged between 18 and 96 years, with a mean age of 67 years. In our population, 125 patients (54.1 % %) were on anticoagulant therapy. Multivariate analysis showed that an SMH diameter > 5.5 cm was independently associated with poor outcome ((odds Ratio [95 % CI] 4,009 [1,786-9,001], p 0.001). Among clinical parameters, only advanced age was proved to be an independent predictor of adverse outcomes (odds Ratio [95 % CI] 1,035 [1,003-1,069], p = 0.033) CONCLUSIONS: Our data suggest that an SMH diameter greater than 5.5 cm on a CT scan and advanced age are predictors of poor outcomes. Surprisingly, anticoagulant therapy seems to play a minor role in the outcome of SMHs.

Telework and MaaS adoption in a post-pandemic scenario. Evidence from municipal employees of Padua, Italy.

In recent years, the adoption of teleworking has witnessed a significant surge, partly driven by the COVID-19 pandemic. The existing literature suggests that its implementation has elicited mixed reactions from workers; while some workers have expressed satisfaction with its introduction, others prefer to work in a traditional, on-site setting. Concurrently, there has been a growing interest in Mobility-as-a-Service (MaaS) and an increase in the number of companies offering such services. However, there is limited research exploring the relationship between teleworking and the utilization of MaaS. This paper aims to fill this gap, by analyzing (1) which factors influence users to adopt teleworking in a post-pandemic scenario and (2) the relationship between willingness to telework and the propensity to join a MaaS system. An ordered logit model and a mixed logit model were developed to achieve the two goals, respectively. These models were calibrated and validated using data collected from questionnaires administered to Padua Municipality employees between October 2020 and January 2021. As expected, the employees most inclined toward teleworking are those who seek more flexibility and are unable to commute by private means. In addition, results show that employees who expressed the preference to telework more in the future are less likely to adopt MaaS, suggesting that the increased popularity of teleworking due to the pandemic may have a negative effect on the uptake of MaaS. These findings were utilized to formulate several policy recommendations.

Image-Guided Localization Techniques for Metastatic Axillary Lymph Nodes in Breast Cancer; What Radiologists Should Know.

Targeted axillary dissection (TAD) is an axillary staging technique after NACT that involves the removal of biopsy-proven metastatic lymph nodes in addition to sentinel lymph node biopsy (SLNB). This technique avoids the morbidity of traditional axillary lymph node dissection and has shown a lower false-negative rate than SLNB alone. Therefore, marking positive axillary lymph nodes before NACT is critical in order to locate and remove them in the subsequent surgery. Current localization methods include clip placement with intraoperative ultrasound, carbon-suspension liquids, localization wires, radioactive tracer-based localizers, magnetic seeds, radar reflectors, and radiofrequency identification devices. The aim of this paper is to illustrate the management of axillary lymph nodes based on current guidelines and explain the features of axillary lymph node markers, with relative advantages and disadvantages.

The Effect of Partial Sleep Deprivation and Time-on-Task on Young Drivers' Subjective and Objective Sleepiness.

Despite sleepiness being considered one of the main factors contributing to road crashes, and even though extensive efforts have been made in the identification of techniques able to detect it, the assessment of fitness-to-drive regarding driving fatigue and sleepiness is still an open issue. In the literature on driver sleepiness, both vehicle-based measures and behavioral measures are used. Concerning the former, the one considered more reliable is the Standard Deviation of Lateral Position (SDLP) while the PERcent of eye CLOSure over a defined period of time (PERCLOS) seems to be the most informative behavioral measure. In the present study, using a within-subject design, we assessed the effect of a single night of partial sleep deprivation (PSD, less than 5 h sleeping time) compared to a control condition (full night of sleep, 8 h sleeping time) on SDLP and PERCLOS, in young adults driving in a dynamic car simulator. Results show that time-on-task and PSD affect both subjective and objective sleepiness measures. Moreover, our data confirm that both objective and subjective sleepiness increase through a monotonous driving scenario. Considering that SDLP and PERCLOS were often used separately in studies on driver sleepiness and fatigue detection, the present results have potential implications for fitness-to-drive assessment in that they provide useful information allowing to combine the advantages of the two measures for drowsiness detection while driving.

Driving fatigue increases after the Spring transition to Daylight Saving Time in young male drivers: A pilot study.

The Spring transition to Daylight Saving Time (DST) has been associated with several health and road safety issues. Previous literature has focused primarily on the analysis of historical crash and hospitalization data, without investigating specific crash contributing factors, such as driving fatigue. The present study aims to uncover the effects of DST-related circadian desynchrony and sleep deprivation on driving fatigue, by means of a driving simulator experiment. Eighteen participants (all males, age range 21-30 years, mean = 24.2, SD = 2.9) completed two 50-minute trials (at one week distance, same time and same day of the week) on a monotonous highway environment, the second one taking place in the week after the Spring transition to DST. Driving fatigue was evaluated by analysing several different variables (including driving-based, physiological and subjective indices) and by comparison with a historical cohort of pertinent, matched controls who had also undergone two trials, but in the absence of any time change in between. Results showed a considerable rise in fatigue levels throughout the driving task in both trials, but with significantly poorer performance in the post-DST trial, documented by a worsening in vehicle lateral control and an increase in eyelid closure. However, participants seemed unable to perceive this decrease in their alertness, which most likely prevented them from implementing fatigue-coping strategies. These findings indicate that DST has a detrimental effect on driving fatigue in young male drivers in the week after the Spring transition, and provide valuable insights into the complex relationship between DST and road safety.

Driving simulator performance worsens after the Spring transition to Daylight Saving Time.

Circadian desynchrony and sleep deprivation related to the Spring transition to Daylight Saving Time (DST) have been associated with several unfavorable outcomes, including an increase in road traffic accidents. As previous work has mainly focused on analyzing historical crash/hospitalization data, there is virtually no literature investigating the effects of DST on specific driving performance indicators. Here, the effect of the Spring transition to DST on driving performance was investigated by means of a driving simulator experiment, in which participants completed two trials (one week distance, same time and day of the week) on exactly the same simulated route, the second trial taking place in the week after the transition to DST. Results were compared to those of a control group (who also underwent two trials, both before the DST transition), and documented significant worsening of driving performance after DST, as measured by a comprehensive set of simulator-derived indices.

A conflict-based approach for real-time road safety analysis: Comparative evaluation with crash-based models.

An innovative approach for real-time road safety analysis is presented in this work. Unlike traditional real-time crash prediction models (RTCPMs), in which crash data are used in the training phase, a real-time conflict prediction model (RTConfPM) is proposed. This model can be trained using surrogate measures of safety, and can therefore be applied even in situations in which highly spatial/temporal-accurate crash data are unavailable or unreliable. The application of an RTConfPM consists of using a set of input variables recorded during a given time interval, to predict whether there will be an increased risk of unsafe situations in the following interval. This paper presents an RTConfPM to predict rear-end crashes, using time-to-collision values recorded with radar sensors on multiple motorway cross-sections to define unsafe situations, and traffic conditions recorded on the same sections as input to the model. The RTConfPM is compared to a traditional RTCPM, trained with a dataset of crashes located on the same motorway, and using the same traffic data as input. In both approaches, variable selection is performed with Pearson's correlation test and random forest; synthetic minority oversampling technique (SMOTE) is used to balance the classes in the training dataset, support vector machine (SVM) is used as classifier, and Monte Carlo cross-validation is adopted for robustness. The two approaches are evaluated considering accuracy, recall, specificity/false alarm rate, and area under the curve (AUC). As shown by the results of this paper, the conflict-based approach appears promising, and is able to predict the occurrence of unsafe situations within 5 min with more than 93% accuracy, recall and specificity, significantly outperforming the RTCPM.

Smart Materials: Cementitious Mortars and PCM Mechanical and Thermal Characterization.

Climate change (CC) is predominantly connected to greenhouse gas (GHG) emissions from the construction sector. It is clear how it is necessary to rethink construction materials in order to reduce GHG emissions. Among the various strategies proposed, recent research has investigated the potential of smart materials. This study in particular aims to develop an innovative building component that combines high energy performance with reduced thickness and weight. For this reason, the potential of Phase Change Materials (PCM) in cement-based mixes is investigated, comparing the performance of a traditional mix with two innovative mixes made with the addition of 3% and 7% PCM. This work characterizes the new material, analyzing its mechanical and thermal performance, highlighting how the mix strength decreases as the PCM ratio increases; however, both mixes may be considered suitable for masonry structures and may be classified as M5 and M15. Furthermore, from the analysis of the thermal performance, it emerges that the mix presents good behavior in terms of insulating properties.

Visual Feedback Effectiveness in Reducing Over Speeding of Moped-Riders.

The use of assistance systems aimed at reducing road fatalities is spreading, especially for car drivers, but less effort has been devoted to developing and testing similar systems for powered two-wheelers (PTWs). Considering that over speeding represents one of the main causal factors in road crashes and that riders are more vulnerable than drivers, in the present study we investigated the effectiveness of an assistance system which signaled speed limit violations during a simulated moped-driving task, in optimal and poor visibility conditions. Participants performed four conditions of simulated riding: one baseline condition without Feedback, one Fog condition in which visual feedback was provided so as to indicate to the participants when a speed limit (lower than that indicated by the traffic signals) was exceeded, and two post-Feedback conditions with and without Fog, respectively, in which no feedback was delivered. Results showed that participants make fewer speeding violations when the feedback is not provided, after 1 month, and regardless of the visibility condition. Finally, the feedback has been proven effective in reducing speed violations in participants with an aggressive riding style, as measured in the baseline session.

Precision teaching to improve drivers' lane maintenance.

INTRODUCTION: This study investigates the effect of precision teaching signals on lane maintenance. METHODS: In experiment 1, the control group drove a simulator with no signals. In experiment 2, drivers were presented with auditory signals depending on their position within or outside the lane. In experiment 3, visual signals were presented in addition to auditory signals to examine the effect of redundancy on drivers' lane maintenance. RESULTS: Results showed an improvement in lane maintenance in experiment 2. Cross-experiment analysis indicated this effect not to be the result of learning. Data from experiment 3 also showed that presenting redundant signals did not further reduce lane variability or help drivers maintain a more central position within the lane. CONCLUSIONS: Taken together, data suggest precision teaching be effective as an educational tool to improve lane maintenance. Practical Applications: Our study shows the potential for precision teaching to serve as a valuable tool in driver training.