PubMed · 9465426
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1998. Instant analysis.. https://pubmed.ncbi.nlm.nih.gov/9465426/
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In the field of the documentation of forensics-relevant injuries, from the reconstructive point of view, the forensic, CAD-supported photogrammetry plays an important role; particularly so when a detailed 3-D reconstruction is vital. This is demonstrated with a soft-tissue injury to the face caused by being run over by a car tire. Since the objects (injury and surface of the tire) to be investigated will be evaluated in virtual space, they must be series photographed. These photo sequences are then evaluated with the RolleiMetric multi-image evaluation system. This system measures and calculates the spatial location of points shown in the photo sequences, and creates 3-D data models of the objects. In a 3-D CAD program, the model of the injury is then compared against the model of the possible injury-causing instrument. The validation of the forensic, CAD-supported photogrammetry, as shown by the perfect 3-D match between the tire tread and the facial injury, demonstrates how greatly this 3-D method surpasses the classic 2-D overlay method (one-to-one photography).
Older drivers have elevated crash rates and are more likely to be injured or die if they have a crash. Medical conditions and medications have been hypothesized as determinants of crash involvement. This population-based case-control study sought to identify medical conditions and medications associated with risk of at-fault crashes among older drivers. A total of 901 drivers aged 65 years and older were selected in 1996 from Alabama Department of Public Safety driving records: 244 at-fault drivers involved in crashes; 182 not at-fault drivers involved in crashes; and 475 drivers not involved in crashes were enrolled. Information on demographic factors, chronic medical conditions, medications, driving habits, visual function, and cognitive status was collected. Older drivers with heart disease (odds ratio (OR) = 1.5, 95% confidence interval (CI): 1.0, 2.2) or stroke (OR = 1.9, 95% CI: 0.9, 3.9) were more likely to be involved in at-fault automobile crashes. Arthritis was also associated with an increased risk among females (OR =1.8, 95% CI: 1.1, 2.9). Use of nonsteroidal antiinflammatory drugs (OR = 1.7, 95% CI 1.0, 2.6), angiotensin converting enzyme inhibitors (OR = 1.6, 95 CI: 1.0, 2.7), and anticoagulants (OR = 2.6, 95% CI: 1.0, 73) was associated with an increased risk of at-fault involvement in crashes. Benzodiazepine use (OR = 5.2, 95% CI: 0.9, 30.0) was also associated with an increased risk. Calcium channel blockers (OR = 0.5, 95% CI: 0.2, 0.9) and vasodilators (OR = 0.3, 95% CI: 0.1, 1.0) were associated with a reduced risk of crash involvement. The identification of medical conditions and medications associated with risk of crashes is important for enhancing the safety and mobility of older drivers.