This study explored the potential utility of gait analysis using a single sensor unit (inertial measurement unit [IMU]) as a simple tool to detect peripheral neuropathy in people with diabetes. Seventeen people (14 men) aged 63±9 years (mean±SD) with diabetic peripheral neuropathy performed a 10-m walk test instrumented with an IMU on the lower back. Compared to a reference healthy control data set (matched by gender, age, and body mass index) both spatiotemporal and gait control variables were different between groups, with walking speed, step time, and SDa (gait control parameter) demonstrating good discriminatory power (receiver operating characteristic area under the curve >0.8). These results provide a proof of principle of this relatively simple approach which, when applied in clinical practice, can detect a signal from those with known diabetes peripheral neuropathy. The technology has the potential to be used both routinely in the clinic and for tele-health applications. Further research should focus on investigating its efficacy as an early indicator of or effectiveness of the management of peripheral neuropathy. This could support the development of interventions to prevent complications such as foot ulceration or Charcot's foot.
Accelerometry ; Dataset ; Diabetes Complications ; Diabetic Neuropathies ; Foot ; Foot Ulcer ; Gait ; Peripheral Nervous System Diseases ; Walking

Objective: Familial hypercholesterolaemia (FH) variant positive subjects have over double the cardiovascular risk of low-density-lipoprotein-cholesterol (LDL-C) matched controls. It is desirable to optimise FH variant detection. Methods: We identified 213 subjects with FH gene panel reports (LDLR, APOB, PCSK9, and APOE) based on total cholesterol >310 mg/dL; excluding triglycerides >400 mg/dL, cascade screening, and patients without pre-treatment LDL-C recorded. Demographic, clinical and lipid parameters were recorded. Results: A 31/213 (14.6%) patients had pathogenic or likely pathogenic FH variants. 10/213 (4.7%) had variants of uncertain significance. Compared with patients without FH variants, patients with FH variants were younger (median age, 39 years vs. 48 years), had more tendon xanthomata (25.0% vs. 11.4%), greater proportion of first degree relatives with total cholesterol >95th percentile (40.6% vs. 16.5%), higher LDL-C (median, 271 mg/dL vs. 236 mg/dL), and lower triglycerides (median, 115 mg/dL vs. 159 mg/dL). The Besseling et al. model (c-statistic 0.798) improved FH variant discrimination over Friedewald LDL-C (c-statistic 0.724), however, Dutch Lipid Clinic Network Score (DLCNS) did not (c-statistic 0.665). Sampson LDL-C (c-statistic 0.734) had similar discrimination to Friedewald. Conclusion Although tendon xanthomata and first degree relatives with high total cholesterol >95th percentile were associated with FH variants, DLCNS or Simon Broome criteria did not improve FH detection over LDL-C. Sampson LDL-C did not significantly improve discrimination over Friedewald. Although lower triglycerides and younger age of presentation are positively associated with presence of FH variants, this information is not commonly used in FH detection algorithms apart from Besseling et al.