Most of the decisions taken to improve road safety are based on accident data, which makes it the back bone of any country's road safety system. Errors in this data will lead to misidentification of black spots and hazardous road segments, projection of false estimates pertinent to accidents and fatality rates, and detection of wrong parameters responsible for accident occurrence, thereby making the entire road safety exercise ineffective. Its extent varies from country to country depending upon various factors. Knowing the type of error in the accident data and the factors causing it enables the application of the correct method for its rectification. Therefore there is a need for a systematic literature review that addresses the topic at a global level. This paper fulfils the above research gap by providing a synthesis of literature for the different types of errors found in the accident data of 46 countries across the six regions of the world. The errors are classified and discussed with respect to each type and analysed with respect to income level; assessment with regard to the magnitude for each type is provided; followed by the different causes that result in their occurrence, and the various methods used to address each type of error. Among high-income countries the extent of error in reporting slight, severe, non-fatal and fatal injury accidents varied between 39-82%, 16-52%, 12-84%, and 0-31% respectively. For middle-income countries the error for the same categories varied between 93-98%, 32.5-96%, 34-99% and 0.5-89.5% respectively. The only four studies available for low-income countries showed that the error in reporting non-fatal and fatal accidents varied between 69-80% and 0-61% respectively. The logistic relation of error in accident data reporting, dichotomised at 50%, indicated that as the income level of a country increases the probability of having less error in accident data also increases. Average error in recording information related to the variables in the categories of location, victim's information, vehicle's information, and environment was 27%, 37%, 16% and 19% respectively. Among the causes identified for errors in accident data reporting, Policing System was found to be the most important. Overall 26 causes of errors in accident data were discussed out of which 12 were related to reporting and 14 were related to recording. "Capture-Recapture" was the most widely used method among the 11 different methods: that can be used for the rectification of under-reporting. There were 12 studies pertinent to the rectification of accident location and almost all of them utilised a Geographical Information System (GIS) platform coupled with a matching algorithm to estimate the correct location. It is recommended that the policing system should be reformed and public awareness should be created to help reduce errors in accident data.
Ectopic pregnancy is an extra-uterine pregnancy and is a potentially life-threatening condition that can lead to death from intra-peritoneal hemorrhage. This case reports a rare occurrence of ruptured tubal pregnancy in which the patient presented early with abdominal pain and a negative urine pregnancy test but subsequently presented again with evidence of intra-peritoneal hemorrhage. A negative urine pregnancy test is often used to rule out pregnancy, but it is not 100% sensitive. Complete assessment is critical in this important diagnosis in order to plan for the appropriate emergency management.
There is a lack of evidence that either conventional observational rating scale or biomechanical system is a better tremor assessment tool. This work focuses on comparing a biomechanical system and the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale in terms of test-retest reliability. The Parkinson's disease tremors were quantified by biomechanical system in joint angular displacement and predicted rating, as well as assessed by three raters using observational ratings. Qualitative comparisons of the validity and function are made also. The observational rating captures the overall severity of body parts, whereas the biomechanical system provides motion- and joint-specific tremor severity. The tremor readings of the biomechanical system were previously validated against encoders' readings and doctors' ratings; the observational ratings were validated with previous ratings on assessing the disease and combined motor symptoms rather than on tremor specifically. Analyses show that the predicted rating is significantly more reliable than the average clinical ratings by three raters. The comparison work removes some of the inconsistent impressions of the tools and serves as guideline for selecting a tool that can improve tremor assessment. Nevertheless, further work is required to consider more variabilities that influence the overall judgement.