Adherence to Anticholinergic Therapy and Clean Intermittent Self-Catheterization in Patients With Multiple Sclerosis

International audiencePurposeTo evaluate adherence to anticholinergic therapy (AT) and clean intermittent self-catheterization (CISC) in patients with multiple sclerosis (MS) and to identify factors associated with poor adherence.MethodsThis single-center study prospectively included 49 patients suffering from MS who had been prescribed AT and/or CISC. Adherence was evaluated using a self-report questionnaire. The Expanded Disability Status Scale (EDSS), Patient Global Impression of Improvement, Mini-Mental State Examination, Urinary Symptom Profile, and Hospital Anxiety and Depression (HAD) instruments were administered, and the number of daily anticholinergic pills and/or catheterizations was noted. Whether patients were receiving concomitant intradetrusor botulinum toxin injections was assessed, as were barriers to treatment, side effects, number of spontaneous micturitions, reasons for the prescription, satisfaction, and difficulties.ResultsOnly 38% of patients were adherent to AT. Experiencing side effects was related to nonadherence (P=0.02). Only 29% of patients were adherent to CISC. More intense voiding dysfunction (P<0.001), a higher frequency of CISC (P=0.03), and a higher EDSS score (P=0.02) were associated with better adherence. Conversely, the HAD score (P<0.001), depression (P<0.001), the persistence of spontaneous micturition (P<0.001), a blocking sensation during catheterization (P=0.04), and the need to adapt one’s posture or gesture to perform catheterization (P=0.04) were associated with poorer adherence.ConclusionsAdherence to AT and CISC was poor in patients with MS suffering from bladder dysfunction. Several factors related to nonadherence were identified in this study, and addressing these factors might help to improve treatment adherence

Comparison of Various Smoothness Metrics for Upper Limb Movements in Middle-Aged Healthy Subjects

Backgound: Metrics for movement smoothness include the number of zero-crossings on the acceleration profile (N0C), the log dimensionless jerk (LDLJ), the normalized averaged rectified jerk (NARJ) and the spectral arc length (SPARC). Sensitivity to the handedness and movement type of these four metrics was compared and correlations with other kinematic parameters were explored in healthy subjects. Methods: Thirty-two healthy participants underwent 3D upper limb motion analysis during two sets of pointing movements on each side. They performed forward- and backward-pointing movements at a self-selected speed to a target located ahead at shoulder height and at 90% arm length, with and without a three-second pause between forward and backward movements. Kinematics were collected, and smoothness metrics were computed. Results: LDLJ, NARJ and N0C found backward movements to be smoother, while SPARC found the opposite. Inter- and intra-subject coefficients of variation were lowest for SPARC. LDLJ, NARJ and N0C were correlated with each other and with movement time, unlike SPARC. Conclusion: There are major differences between smoothness metrics measured in the temporal domain (N0C, LDLJ, NARJ), which depend on movement time, and those measured in the frequency domain, the SPARC, which gave results opposite to the other metrics when comparing backward and forward movements

Comparison of Various Smoothness Metrics for Upper Limb Movements in Middle-Aged Healthy Subjects

Backgound: Metrics for movement smoothness include the number of zero-crossings on the acceleration profile (N0C), the log dimensionless jerk (LDLJ), the normalized averaged rectified jerk (NARJ) and the spectral arc length (SPARC). Sensitivity to the handedness and movement type of these four metrics was compared and correlations with other kinematic parameters were explored in healthy subjects. Methods: Thirty-two healthy participants underwent 3D upper limb motion analysis during two sets of pointing movements on each side. They performed forward- and backward-pointing movements at a self-selected speed to a target located ahead at shoulder height and at 90% arm length, with and without a three-second pause between forward and backward movements. Kinematics were collected, and smoothness metrics were computed. Results: LDLJ, NARJ and N0C found backward movements to be smoother, while SPARC found the opposite. Inter- and intra-subject coefficients of variation were lowest for SPARC. LDLJ, NARJ and N0C were correlated with each other and with movement time, unlike SPARC. Conclusion: There are major differences between smoothness metrics measured in the temporal domain (N0C, LDLJ, NARJ), which depend on movement time, and those measured in the frequency domain, the SPARC, which gave results opposite to the other metrics when comparing backward and forward movements