Misclassification of seat belt use In a recent article, Robertson commented on our study of seat belts and death in a crash. Robertson wrote: “What is not explained adequately by the theory [about misclassification of seat belt use] is the sudden gap in police reported use by the dead and survivors that appeared in the mid-1980s”. Robertson’s criticism seems misplaced, as we offered no theory to explain changes in the prevalence of belt use. We reported that among front seat occupant pairs in which one or both died, the prevalence of belt use decreased from 12% in 1975 to 4% in 1980, and then rose to 40% in 1998. Explaining these changes, however, was not the focus of our paper. Using matched cohort methods, we noted that the risk ratio for death, comparing belted with unbelted occupants, was 0.59 using data from 1975–83, and 0.39 using data from 1986–98. We examined theories that might explain why these risk ratio estimates changed over time. We presented evidence against the theory that seat belts have become truly more effective and against the theory that estimates changed because of changes in crash characteristics. The observed change in risk ratio estimates could be explained by either, or both, of two theories: (1) Differential misclassification. Seat belt misclassification is differential when the proportion misclassified is related to the outcome (death). Risk ratio estimates could move away from their true value and toward 0 if, over time, an increasing proportion of crash survivors were classified as belted, when they were not, or an increasing proportion of those who died were classified as unbelted, when they were: this possible mechanism is illustrated with hypothetical data in the top half of table 1. (For simplicity, the table ignores the matching used in our published analysis.) (2) Non-differential misclassification. Without regard to death or survival, some belt users could be classified as not belted, or some nonusers as belted, or both. Non-differential misclassification of a binary variable tends to bias risk ratio estimates toward 1. If nondifferential error decreased over time, more recent risk ratio estimates could be less subject to this bias; they could move away from 1 toward their true value. However, even if non-differential error was constant over time, more recent risk ratios might also tend to be less biased, because of the influence of changing seat belt prevalence: bottom half of table 1. For both differential and non-differential misclassification, the size and direction of any change over time in risk ratio estimates will be related to the size and direction of the errors and changes in the prevalence of seat belt use. The observed changes in risk ratio estimates alone cannot tell us which estimates are least subject to bias. One of us has reported that there is some degree of both differential and nondifferential misclassification of belt use; but the amount of error in recent data suitable for a matched-cohort analysis was so trivial, and biases toward 1 and toward 0 so balanced, that the misclassification did not appreciably influence the risk ratio estimate. Robertson interpreted these results as showing only that trained crash investigators were as prone to differential misclassification as police investigators. Whatever the correct interpretation, we and Robertson agree that additional measures of seat belt use would be useful. We hope that information from electronic crash recorders will be added to publicly available data, such as the Crashworthiness Data System (CDS). It might be feasible for the CDS to assess some crashes with a second investigator assigned to determine belt use only by vehicle inspection, without knowledge of occupant outcomes or the police report. To minimize costs, this additional investigation could be reserved for those crashes with front seat occupant pairs among whom at least one died. This would allow a matched cohort analysis to compare risk ratio estimates using three sources of belt information: (1) police reports; (2) the usual CDS investigation; and (3) an investigator who could not be biased by knowledge of the outcome.

Falls in older people: risk factors and strategies for prevention.

http://pic1.cmt.com.cn/newspic/files/dm-guidelines-ccp.pdf

American association of clinical endocrinologists and american college of endocrinology - clinical practice guidelines for developing a diabetes mellitus comprehensive care plan - 2015.

Characterizing locomotor dynamics is essential for understanding the neuromuscular control of locomotion. In particular, quantifying dynamic stability during walking is important for assessing people who have a greater risk of falling. However, traditional biomechanical methods of defining stability have not quantified the resistance of the neuromuscular system to perturbations, suggesting that more precise definitions are required. For the present study, average maximum finite-time Lyapunov exponents were estimated to quantify the local dynamic stability of human walking kinematics. Local scaling exponents, defined as the local slopes of the correlation sum curves, were also calculated to quantify the local scaling structure of each embedded time series. Comparisons were made between overground and motorized treadmill walking in young healthy subjects and between diabetic neuropathic (NP) patients and healthy controls (CO) during overground walking. A modification of the method of surrogate data was developed to examine the stochastic nature of the fluctuations overlying the nominally periodic patterns in these data sets. Results demonstrated that having subjects walk on a motorized treadmill artificially stabilized their natural locomotor kinematics by small but statistically significant amounts. Furthermore, a paradox previously present in the biomechanical literature that resulted from mistakenly equating variability with dynamic stability was resolved. By slowing their self-selected walking speeds, NP patients adopted more locally stable gait patterns, even though they simultaneously exhibited greater kinematic variability than CO subjects. Additionally, the loss of peripheral sensation in NP patients was associated with statistically significant differences in the local scaling structure of their walking kinematics at those length scales where it was anticipated that sensory feedback would play the greatest role. Lastly, stride-to-stride fluctuations in the walking patterns of all three subject groups were clearly distinguishable from linearly autocorrelated Gaussian noise. As a collateral benefit of the methodological approach taken in this study, some of the first steps at characterizing the underlying structure of human locomotor dynamics have been taken. Implications for understanding the neuromuscular control of locomotion are discussed.

Nonlinear time series analysis of normal and pathological human walking.

American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for Developing a Diabetes Mellitus Comprehensive Care Plan

A number of effective, low-cost strategies are available to identify and treat the person at risk for diabetic foot ulcers and lower-extremity amputation. These strategies must be more widely adopted by all diabetic care providers to maintain the integrity and function of the lower limb, and thus improve the quality of life for people with diabetes.

https://www.algeos.com/filemanager/research/Preventative%20foot%20care%20in%20people%20with%20diabetes.pdf

Preventive Foot Care in People With Diabetes

Peripheral neuropathy secondary to diabetes mellitus is believed to cause postural instability and uncoordinated gait, although this is not well documented. Two groups of patients from the Pittsburgh Epidemiology of Diabetes Complications Study, matched for age and duration of Type 1 diabetes, but with significantly different vibratory sensation thresholds as determined by Vibratron II testing, were therefore surveyed. The mean ages were 32.9 and 31.9 years and durations of diabetes were 22.0 and 18.8 years for the neuropathic and control groups, respectively. Patients provided details of fall injuries, and perception of safety during standing and walking. Multiple linear and logistic regression models were used to account for potentially associated variables such as gender, retinopathy, and duration of diabetes. The neuropathic group had adjusted odds ratios for reported injuries during gait of 15.0 relative to the control group (95% confidence intervals 1.04-216.59). The neuropathic group also reported significantly lower scores (less safe, p = 0.004) than the control group on perceived safety in unusual conditions. It is concluded that peripheral neuropathy has an effect on gait and posture which is clinically significant and that this effect merits further biomechanical study in neuropathic patients.

Problems with gait and posture in neuropathic patients with insulin-dependent diabetes mellitus.

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Problems with gait and posture in neuropathic patients with insulin-dependent diabetes mellitus.