Brake response time before and after total knee arthroplasty: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Although the numbers of total knee arthroplasty (TKA) are increasing, there is only a small number of studies investigating driving safety after TKA. The parameter 'Brake Response Time (BRT)' is one of the most important criteria for driving safety and was therefore chosen for investigation.</p> <p>The present study was conducted to test the hypotheses that patients with right- or left-sided TKA show a significant increase in BRT from pre-operative (pre-op, 1 day before surgery) to post-operative (post-op, 2 weeks post surgery), and a significant decrease in BRT from post-op to the follow-up investigation (FU, 8 weeks post surgery). Additionally, it was hypothesized that the BRT of patients after TKA is significantly higher than that of healthy controls.</p> <p>Methods</p> <p>31 of 70 consecutive patients (mean age 65.7 +/- 10.2 years) receiving TKA were tested for their BRT pre-op, post-op and at FU. BRT was assessed using a custom-made driving simulator. We used normative BRT data from 31 healthy controls for comparison.</p> <p>Results</p> <p>There were no significant increases between pre-op and post-op BRT values for patients who had undergone left- or right-sided TKA. Even the proportion of patients above a BRT threshold of 700 ms was not significantly increased postop. Controls had a BRT which was significantly better than the BRT of patients with right- or left-sided TKA at all three time points.</p> <p>Conclusion</p> <p>The present study showed a small and insignificant postoperative increase in the BRT of patients who had undergone right- or left-sided TKA. Therefore, we believe it is not justified to impair the patient's quality of social and occupational life post-surgery by imposing restrictions on driving motor vehicles beyond an interval of two weeks after surgery.</p

Measuring housing and transportation affordability: A case study of Melbourne, Australia

Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies