Low-impact falls: Demands on a system of trauma management, prediction of outcome, and influence of comorbidities

Background. Falls from a low height are an extremely common source of injur y, the severity of which is often underestimated. As a result, low fall pat ients are usually not transferred to Level I trauma centers. There are surp risingly few systematic data relating to the demands made on systems of tra uma care by patients with low falls. This study addresses this issue using information from a comprehensive national trauma database. The performance of TRISS methodology, and the factors associated with prolonged hospital st ay, in low fall patients is also examined. Methods. The study included 31,419 patients. Patients with low falls (< 2 m ) were compared with those suffering high falls ( greater than or equal to 2 m), motor vehicle crashes, assault, sports injuries, and a group with unc lassified injuries. Probability of survival was estimated using TRISS, and its performance in different types of injury was assessed using measures of discrimination and calibration. The influence of coexistent medical condit ions on mortality and length of stay was investigated using logistic regres sion. Results. Low falls accounted for 45.5% of all admissions, and 43.9% or the total bed days. The low fall group was older (mean age, 61.6 years), and pr edominantly female (62.5%) in contrast to the other groups (both p < 0.001) . There were fewer severely injured patients than in all of the other group s except sports injuries. The area under the receiver operating characteris tic curve for TRISS applied to low falls (0.874) was less than that for hig h falls (0.969), motor vehicle crashes (0.973), assaults (0.960), sports (1 .000), and unclassified injuries (0.965). Also, the calibration of the TRIS S model was poor for patients with low falls. A logistic regression model d erived from a training set of 5,000 patients gave slightly improved discrim ination and markedly improved calibration when compared with TRISS. Althoug h there was a strong relationship between the number of coexistent medical conditions and the risk of dying after a low fall, including data on comorb idities in a predictive model did not improve performance. Prolonged stay ( defined as greater than the 90th centile, 23 days) was more likely in women (p < 0.005), or with advanced age (p < 0.001) or low initial calculated pr obability of survival (p < 0.001). Cardiovascular and central nervous syste m diseases and diabetes were associated with longer hospital stay (all p < 0.001). A logistic regression model using TRISS variables and comorbidity d ata gave poor prediction of prolonged stay. There was considerable variatio n in the length of stay between institutions. Conclusion. Patients with low falls make considerable demands on a system o f trauma care. TRISS methodology performs less well in this group than with other types or injury. Chronic medical conditions are associated with incr eased mortality and more prolonged stay after a low fall. Between-instituti onal variation in length of stay was considerable and this, along with the poor performance of predictive models derived from routinely collected clin ical data, make it unlikely that length of stay could be used as a measure of institutional performance. More robust audit measures for patients with low falls are required.