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James E Winslow

Publications and source records attributed to James E Winslow.

3 recordsLinked to original sources
PubMed2006

Risk of thoracolumbar fractures doubled in victims of motor vehicle collisions with cervical spine fractures.

BACKGROUND: An association between cervical fractures and thoracolumbar fractures after blunt trauma has long been assumed, but not adequately demonstrated. We sought to determine the actual association between these injuries in a large nationwide data set. METHODS: The National Trauma Databank (NTDB) was queried for victims of blunt vehicular trauma with at least minimal injury. An odds ratio was calculated for the association between cervical spine fractures and thoracolumbar fractures. RESULTS: Overall 190,183 NTDB patient records met the criteria of a motor vehicle crash with more than minimal injury. Of these 7.51% (14,292) had cervical spine fractures, 4.73% (8,996) had thoracic spine fractures, 5.93% (11,280) had lumbar spine fractures, and 9.79% (18,623) had either thoracic or lumbar fractures. Of patients with a cervical spine fracture, 13.06% (2,433) also had a thoracic or lumbar fracture, whereas among patients without cervical spine fracture only 6.91% (11,859) had a thoracolumbar fracture. The odds ratio (OR) for a thoracolumbar fracture in the presence of a cervical spine fracture was 2.02 (p < 0.0001) (95% confidence interval 1.9318-2.1201). CONCLUSION: These data confirm a strong association between cervical spine fractures and thoracolumbar fractures after blunt vehicular trauma, and support the practice of imaging the complete spine when a cervical fracture is identified.

Accidents, Traffic↗
PubMed2005

Method for determining automatic external defibrillator need at mass gatherings.

OBJECTIVES: A method for determining the number of automatic external defibrillators (AEDs) required for a 3-min response at mass gatherings has been described previously. Our study sought to modify the method, replicate it, then validate the results. METHODS: Emergency medical technicians (EMTs) were timed walking defined courses in a football stadium. Velocities were obtained for a horizontal distance and ascending/descending upper and lower decks. This was replicated in a basketball arena. To validate, actual response times were compared to predicted times for predetermined distances in each venue. Predicted response times were calculated using the second standard deviation velocities as the most pessimistic. Numbers of AEDs needed were calculated using predicted response times for each venue's longest distance. RESULTS: Average velocities in m/s (football) were horizontal 1.7, lower deck 1.6 ascending and 1.4 descending, upper deck 1.0 ascending and 1.1 descending. Average velocities (basketball) were horizontal 1.7, lower deck 1.2 ascending and descending, upper deck 0.9 ascending and descending. In the validation phase, every EMT completed the four predetermined courses within the predicted intervals. Predicted response times were 363 s for the longest football stadium distance, and 187 s for the basketball arena. For a 3-min (180 s) response, the number of AEDs required can be calculated. CONCLUSION: This method was easily replicated and appears to be useful for determining the number of AEDs at mass gatherings. The number of AEDs needed for any desired response interval can be calculated using the predicted response time for the longest distance within an arena.

Adult↗