scholarly journals Comparison of road traffic accidents presenting to the emergency department of a teaching hospital before and during lockdown

2021 ◽  
Vol 8 (9) ◽  
pp. 4297
Author(s):  
Siddharth Rao P. S. ◽  
Sumayya Nazneen Sayyada ◽  
Souri Reddy Pyreddy
Keyword(s):  
Teaching Hospital ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Tertiary Care ◽  
Mass Casualties ◽  
Road Traffic Accidents ◽  
Patient Demographics ◽  
Disproportionate Number ◽  
Type Of Injury ◽  
The Impact

Background: Road traffic accidents (RTAs) are a major cause of misery, disability and death globally, with a disproportionate number occurring in developing countries. With COVID-19 reaching pandemic proportion, a nationwide lockdown was announced on 24 March 2020 which resulted in the complete closure vehicular movement. This study aimed to assess the impact of lockdown on the number of RTAs brought to our rural tertiary care teaching hospital situated on National highway number 65.Methods: Medico-legal records were reviewed retrospectively at Kamineni institute of medical sciences hospital. The cases were classified into two groups. The pre-lockdown group included cases reporting to casualty from 1 April 2019 to 31 July 2019. The lockdown group included cases reporting to casualty from 1 April 2020 to 31 July 2020. Patient demographics, type of injury, time of injury, mode of injury were collected for all cases and analysed using simple mathematical tools.Results: There was a significant decrease in the total number of RTAs during lockdown phases 1 and 2 and during unlocking phases 1 and 2 by 52.1%. Bike skid was the most common mode of injury. The highest number of RTAs was observed between 6 am to 6 pm and the most commonly affected gender was male especially in the age group of 15-45 years.Conclusions: RTA numbers can be reduced by strict implementation of traffic rules and better road infrastructure. One positive effect of the measures implemented to control the spread of COVID-19 was the reduction of traffic accidents and mass casualties.

scholarly journals A demographic study on type of accidents, injuries and associated factors, patients attending emergency trauma care at tertiary care teaching hospital

2017 ◽  
Vol 4 (7) ◽  
pp. 2457
Author(s):  
Raja Vikram Prasad ◽  
C. Y. Nandanwar ◽  
B. S. Isaac Ebenezer
Keyword(s):  
Teaching Hospital ◽  
Trauma Care ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Tertiary Care ◽  
Road Traffic Accidents ◽  
Tertiary Care Teaching Hospital ◽  
Care Teaching ◽  
Premature Deaths ◽  
Written Informed Consent

Background: Road traffic accidents (RTA) is considered to be among top five cause of concern in with morbidity and mortality with socioeconomic repercussions among developing countries. RTA’s are manmade disaster which involves human suffering and socioeconomic costs in terms of premature deaths, injuries, etc. The objective of study was to know the prevalence of various types of accidents, injuries and associated factors.Methods: This study is prospective observational study, was conducted at Tertiary Care Teaching Hospital, SRMC, A.P. Enrollment of patients were registered in emergency trauma care, included all types of accidents and injuries. Patients were interviewed with the pre-tested proforma. After written informed consent, victims were interviewed and attendants were interviewed where patients were unable to answer which is part of Inclusion criteria in the study. Injuries recorded were graded according to Trauma Index. Other required information was collected from medicolegal records from hospital medical records department.Results: Total of 153 cases recorded at emergency Trauma care unit, of which males are 135 (88.235%) and females 18 (11.764%). The highest percentage was falling between 20-29 years followed by 30-39, 40-49 years.3,4 According to trauma index injuries, Minor were 108 (70.588%) and Major were 45  (20.411%). Of all injuries RTA’s were 111 (72.549%), recorded as the major portion.2 The injuries were more due to Bikes 51 (45.945%), followed by pedestrians 30 (27.027%) as victims, which took place in the evening and late nights were 93 (60.784%), followed by early mornings were 42 (27.450%).Conclusions:Conclusions of study showed that males were involved more than females in RTA’s falling between 20-49 years. Most of the injuries recorded were minor followed by major injuries from Road Traffic Accidents, which occurred during evenings and late nights. Type of vehicles involved in RTA’s was two wheelers followed by pedestrians and people who travelled in share Autos.  

scholarly journals The Pattern of Injury from Road Traffic Accident Presenting at Emergency Department of Kathmandu Medical College

2019 ◽  
Vol 17 (2) ◽  
pp. 206-208
Author(s):  
Anu Kushwaha ◽  
Pankaj Singh
Keyword(s):  
Emergency Department ◽  
Teaching Hospital ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
College Teaching ◽  
Road Traffic Accidents ◽  
Medical College ◽  
Type Of Injury

Background: Road traffic accidents are the major public health problem. The objective of the study was to analyze road traffic accidents presenting in Kathmandu Medical College Emergency Department.Methods: The data from all consecutive road traffic accident cases brought to Emergency Department Kathmandu Medical College Teaching Hospital were collected from 2018 Jan-2018 June. Factors like age of the patients, time of the accident, influence of illicit substances and type of injury were documented.Results: Males (74) were common victims than the females (26). Eldest patient was 65 years of the age while youngest patient was 4 years. Most common type of injury was fracture in male 28 (37%)and laceration in females8 (38%). Alcohol intoxication was evident by positive alcohol smell test in 10 (13.6%) males and 6(23%) females. Conclusions: Road traffic accidents are major health concern in Kathmandu Medical College Teaching Hospital and preventive measures should be considered to reduce such health burden. Keywords: Alcohol; Injury;Pattern; RTA.

Profile of Road Traffic Accident Injuries in a Tertiary Care Teaching Hospital – An Institution Based Cross Sectional Observational Study in Velammal Medical College Hospital and Research Institute, Tamil Nadu

2021 ◽  
Vol 8 (14) ◽  
pp. 904-908
Author(s):  
Kumaran R ◽  
Yogaraj S
Keyword(s):  
Observational Study ◽  
Teaching Hospital ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Tertiary Care ◽  
Road Traffic Accidents ◽  
Abdominal Injuries ◽  
College Hospital ◽  
Cross Sectional ◽  
Medical College

BACKGROUND Road traffic accidents (RTA) account for most of the injury patients encountered in the department of emergency resulting in significant death and morbidity. The current research was conducted to analyse the demographic, clinical and radiological profile of patients presenting with RTA to a tertiary care teaching hospital (Velammal Medical College Hospital and Research Institute). METHODS This cross-sectional observational study was done among 68 subjects presenting with RTA to the department of emergency medicine. Detailed history taking, clinical & radiological investigations including plain radiographs, ultrasound and computed tomography (CT) were done. Site of injury was considered as primary outcome of the study. The data was analysed statistically by deriving mean and standard deviation. International Business Machines Statistical Package for the Social Sciences (IBM SPSS) version 22 was used for statistical analysis. RESULTS Among the study population, the mean age was 36.18 ± 13.73 years. 83.82 % were males. Individuals aged less than 40 years of age were greatly involved in RTA. Majority (77.9 %) had abdominal injuries followed by 36.7 % with craniofacial trauma, 25 % had thoracic trauma, 17.6 % had spinal trauma, and 10.2 % had extremity and pelvic bone injuries. In abdominal trauma, spleen (26.4 %) was the commonly affected organ. Liver (25 %) and renal injuries (16.17 %) were next commonly observed. A significant difference (P-value < 0.05) was found in abdominal injuries due to different types of vehicles. CONCLUSIONS RTIs are common in the younger population. The predominance of the male population was seen. The most common organ to be injured was spleen. Proper understanding of the pattern of trauma may help in improving the outcome. Early diagnosis, aggressive resuscitation and timely surgical intervention were essential in improving the outcome in trauma patients. KEYWORDS Road Traffic Accidents, Road Traffic Injuries, Head Injury, Blunt Abdominal Trauma, CT Scan

scholarly journals Comparison of Prediction Models for Mortality Related to Injuries from Road Traffic Accidents after Correcting for Undersampling

2021 ◽  
Vol 18 (11) ◽  
pp. 5604
Author(s):  
Yookyung Boo ◽  
Youngjin Choi
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
National Level ◽  
Brier Score ◽  
Support Vector ◽  
Main Diagnosis ◽  
Road Traffic Accidents ◽  
Multiple Variables ◽  
Type Of Injury ◽  
Kernel Model

In this study, four models—logistic regression (LR), random forest (RF), linear support vector machine (SVM), and radial basis function (RBF)-SVM—were compared for their accuracy in determining mortality caused by road traffic injuries. They were tested using five years of national-level data from the Korea Disease Control and Prevention Agency’s (KDCA) National Hospital Discharge In-Depth Survey (2013 through to 2017). Model performance was measured for accuracy, precision, recall, F1 score, and Brier score metrics using classification analysis that included characteristics of patients, accidents, injuries, and illnesses. Due to the number of variables and differing units, the rates of survival and mortality related to road traffic accidents were imbalanced, so the data was corrected and standardized before the classification models’ performances were compared. Using the importance analysis, the main diagnosis, the type of injury, the site of the injury, the type of injury, the operation status, the type of accident, the role at the time of the accident, and the sex were selected as the analysis factors. The biggest contributing factor was the role in the accident, which is the driver, and the major sites of the injuries were head injuries and deep injuries. Using selected factors, comparisons of the classification performance of each model indicated RBF-SVM and RF models were superior to the others. Of the SVM models, the RBF kernel model was superior to the linear kernel model; it can be inferred that the performance of the high-dimensional transformed RBF model is superior when the dimension is complex because of the use of multiple variables. The findings suggest there are limitations to analyses involving imbalanced, multidimensional original data, such as data on road traffic mortality. Thus, analyses must be performed after imbalances are corrected.

scholarly journals Using the Interval Type-2 Fuzzy Inference Systems to Compare the Impact of Speed and Space Perception on the Occurrence of Road Traffic Accidents

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1548
Author(s):  
Marjana Čubranić-Dobrodolac ◽  
Libor Švadlenka ◽  
Svetlana Čičević ◽  
Aleksandar Trifunović ◽  
Momčilo Dobrodolac
Keyword(s):  
Traffic Accidents ◽  
Driving Simulator ◽  
Fuzzy Inference ◽  
Road Traffic ◽  
Space Perception ◽  
Road Traffic Accidents ◽  
Inference System ◽  
Interval Type ◽  
The Impact

A constantly increasing number of deaths on roads forces analysts to search for models that predict the driver’s propensity for road traffic accidents (RTAs). This paper aims to examine a relationship between the speed and space assessment capabilities of drivers in terms of their association with the occurrence of RTAs. The method used for this purpose is based on the implementation of the interval Type-2 Fuzzy Inference System (T2FIS). The inputs to the first T2FIS relate to the speed assessment capabilities of drivers. These capabilities were measured in the experiment with 178 young drivers, with test speeds of 30, 50, and 70 km/h. The participants assessed the aforementioned speed values from four different observation positions in the driving simulator. On the other hand, the inputs of the second T2FIS are space assessment capabilities. The same group of drivers took two types of space assessment tests—2D and 3D. The third considered T2FIS sublimates of all previously mentioned inputs in one model. The output in all three T2FIS structures is the number of RTAs experienced by a driver. By testing three proposed T2FISs on the empirical data, the result of the research indicates that the space assessment characteristics better explain participation in RTAs compared to the speed assessment capabilities. The results obtained are further confirmed by implementing a multiple regression analysis.

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