BACKGROUND: The diagnosis and management of biliary dyskinesia in children and adolescents remains variable and controversial. The American Pediatric Surgical Association Outcomes and Evidence-Based Practice Committee (APSA OEBP) performed a systematic review of the literature to develop evidence-based recommendations.
METHODS: Through an iterative process, the membership of the APSA OEBP developed five a priori questions focused on diagnostic criteria, indications for cholecystectomy, short and long-term outcomes, predictors of success/benefit, and outcomes of medical management. A systematic review was conducted, and articles were selected for review following Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. Risk of bias was assessed using Methodologic Index for Non-Randomized Studies (MINORS) criteria. The Oxford Levels of Evidence and Grades of Recommendation were utilized.
RESULTS: The diagnostic criteria for biliary dyskinesia in children and adolescents are not clearly defined. Cholecystectomy may provide long-term partial or complete relief in some patients; however, there are no reliable predictors of symptom relief. Some patients may experience resolution of symptoms with non-operative management.
CONCLUSIONS: Pediatric biliary dyskinesia remains an ill-defined clinical entity. Pediatric-specific guidelines are necessary to better characterize the condition, guide work-up, and provide management recommendations. Prospective studies are necessary to more reliably identify patients who may benefit from cholecystectomy.
METHODS: Level 3-4.
METHODS: Systematic Review of Level 3-4 Studies.

Hypertrophic cardiomyopathy (HCM) of the newborn is a rare condition, characterized by great clinical variability, with a relative paucity of data on the pediatric population, especially newborns. Early diagnosis can have an impact on the patient\'s life course and prevent progression to sudden death. In this article, we report the case of a newborn admitted with late-onset neonatal respiratory distress, complicated by heart failure. The newborn was matured by two antenatal injections of betamethasone, which were received as part of a threat of premature delivery. Echocardiography revealed hypokinetic HCM. The rapidity of the establishment of the diagnosis contributed to the patient\'s survival and improvement within a few weeks under well-managed medical treatment. A complete workup was conducted, with negative results. The most suggested explanation for this condition was the use of antenatal corticosteroids.

We performed a comprehensive study of protein (total protein, medium-molecular-weight peptides, creatinine, and urea), purine (uric acid), and lipid (cholesterol, triglycerides) metabolism, activity of AST, ALT, and acid phosphatase in blood plasma of white male rats under conditions of restriction of motor activity up to 28 days. Patterns of changes in metabolic profile during hypokinesia were established: prevalence of catabolic processes and atherogenic shifts in the lipid spectrum with maximum manifestation on 14-21 days of the experiment.

BACKGROUND: The current approach to assessing bradykinesia in Parkinson\'s Disease relies on the Unified Parkinson\'s Disease Rating Scale (UPDRS), which is a numeric scale. Inertial sensors offer the ability to probe subcomponents of bradykinesia: motor speed, amplitude, and rhythm. Thus, we sought to investigate the differential effects of high-frequency compared to low-frequency subthalamic nucleus (STN) deep brain stimulation (DBS) on these quantified facets of bradykinesia.
METHODS: We recruited advanced Parkinson\'s Disease subjects with a chronic bilateral subthalamic nucleus (STN) DBS implantation to a single-blind stimulation trial where each combination of medication state (OFF/ON), electrode contacts, and stimulation frequency (60 Hz/180 Hz) was assessed. The Kinesia One sensor system was used to measure upper limb bradykinesia. For each stimulation trial, subjects performed extremity motor tasks. Sensor data were recorded continuously. We identified STN DBS parameters that were associated with improved upper extremity bradykinesia symptoms using a mixed linear regression model.
RESULTS: We recruited 22 subjects (6 females) for this study. The 180 Hz STN DBS (compared to the 60 Hz STN DBS) and dopaminergic medications improved all subcomponents of upper extremity bradykinesia (motor speed, amplitude, and rhythm). For the motor rhythm subcomponent of bradykinesia, ventral contacts yielded improved symptom improvement compared to dorsal contacts.
CONCLUSIONS: The differential impact of high- and low-frequency STN DBS on the symptoms of bradykinesia may advise programming for these patients but warrants further investigation. Wearable sensors represent a valuable addition to the armamentarium that furthers our ability to conduct objective, quantitative clinical assessments.

BACKGROUND: The core clinical sign of Parkinson\'s disease (PD) is bradykinesia, for which a standard test is finger tapping: the clinician observes a person repetitively tap finger and thumb together. That requires an expert eye, a scarce resource, and even experts show variability and inaccuracy. Existing applications of technology to finger tapping reduce the tapping signal to one-dimensional measures, with researcher-defined features derived from those measures.
OBJECTIVE: (1) To apply a deep learning neural network directly to video of finger tapping, without human-defined measures/features, and determine classification accuracy for idiopathic PD versus controls. (2) To visualise the features learned by the model.
METHODS: 152 smartphone videos of 10s finger tapping were collected from 40 people with PD and 37 controls. We down-sampled pixel dimensions and videos were split into 1 s clips. A 3D convolutional neural network was trained on these clips.
RESULTS: For discriminating PD from controls, our model showed training accuracy 0.91, and test accuracy 0.69, with test precision 0.73, test recall 0.76 and test AUROC 0.76. We also report class activation maps for the five most predictive features. These show the spatial and temporal sections of video upon which the network focuses attention to make a prediction, including an apparent dropping thumb movement distinct for the PD group.
CONCLUSIONS: A deep learning neural network can be applied directly to standard video of finger tapping, to distinguish PD from controls, without a requirement to extract a one-dimensional signal from the video, or pre-define tapping features.

Bradykinesia is a term describing several manifestations of movement disruption caused by Parkinson\'s disease (PD), including movement slowing, amplitude reduction, and gradual decrease of speed and amplitude over multiple repetitions of the same movement. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves bradykinesia in patients with PD. We examined the effect of DBS on specific components of bradykinesia when applied at two locations within the STN, using signal processing techniques to identify the time course of amplitude and frequency of repeated hand pronation-supination movements performed by participants with and without PD. Stimulation at either location increased movement amplitude, increased frequency, and decreased variability, though not to the range observed in the control group. Amplitude and frequency showed decrement within trials, which was similar in PD and control groups and did not change with DBS. Decrement across trials, by contrast, differed between PD and control groups, and was reduced by stimulation. We conclude that DBS improves specific aspects of movement that are disrupted by PD, whereas it does not affect short-term decrement that could reflect muscular fatigue.NEW & NOTEWORTHY In this study, we examined different components of bradykinesia in patients with Parkinson\'s disease (PD). We identified different components through signal processing techniques and their response to deep brain stimulation (DBS). We found that some components of bradykinesia respond to stimulation, whereas others do not. This knowledge advances our understanding of brain mechanisms that control movement speed and amplitude.

Reduced spontaneous blinking is a recognized Parkinson\'s disease (PD) feature. In contrast, voluntary blinking has been less studied and might serve as a measurable marker of facial bradykinesia. We tested 31 PD patients and 31 controls. Participants were filmed during conversation and a rapid blinking task. Both tasks were videorecorded to count the number of blinks per second. PD patients had lower blink rates. Rapid blinking accurately discriminated between groups with 77% sensitivity and 71% specificity. To conclude, rapid blinking may be a simple and quantifiable task of facial bradykinesia.
Decreased blinking without conscious effort is a well-known characteristic of Parkinson’s disease (PD). However, voluntary blinking, which is blinking on purpose, has not been studied as much and could be a sign of slower facial movements. We studied a group of people with PD and another one without the disease. We recorded videos of them talking and doing a task where they blinked quickly. Then, we counted how many times they blinked per second in each video. We found that people with PD blinked less often. The rapid blinking task accurately distinguished between those with PD and those without it, being correct about 77% of the time for spotting PD and 71% for spotting non-PD. In conclusion, the rapid blinking task could be a simple and measurable way to identify slower facial movements in PD.

Bradykinesia, or slowness of movement, is a defining feature of Parkinson disease (PD) and a major contributor to the negative effects on quality of life associated with this disorder and related conditions. A dominant pathophysiological model of bradykinesia in PD has existed for approximately 30 years and has been the basis for the development of several therapeutic interventions, but accumulating evidence has made this model increasingly untenable. Although more recent models have been proposed, they also appear to be flawed. In this Perspective, I consider the leading prior models of bradykinesia in PD and argue that a more functionally related model is required, one that considers changes that disrupt the fundamental process of accurate information transmission. In doing so, I review emerging evidence of network level functional connectivity changes, information transfer dysfunction and potential motor code transmission error and present a novel model of bradykinesia in PD that incorporates this evidence. I hope that this model may reconcile inconsistencies in its predecessors and encourage further development of therapeutic interventions.

BACKGROUND: Parkinson\'s disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson\'s Disease Rating Scale (MDS-UPDRS). Despite its reliability, the scale is bounded by a 5-point scale that limits its ability to track subtle changes in disease progression and is prone to subjective interpretations. We aimed to develop an automated system to objectively quantify motor symptoms in PD using Machine Learning (ML) algorithms to analyze videos and capture nuanced features of disease progression.
METHODS: We analyzed videos of the Finger Tapping test, a component of the MDS-UPDRS, from 24 healthy controls and 66 PD patients using ML algorithms for hand pose estimation. We computed multiple movement features related to bradykinesia from videos and employed a novel tiered classification approach to predict disease severity that employed different features according to severity. We compared our video-based disease severity prediction approach against other approaches recently introduced in the literature.
RESULTS: Traditional kinematics features such as amplitude and velocity changed linearly with disease severity, while other non-traditional features displayed non-linear trends. The proposed disease severity prediction approach demonstrated superior accuracy in detecting PD and distinguishing between different levels of disease severity when compared to existing approaches.

BACKGROUND: People with Parkinson\'s disease (PD) have impaired upper limb motor coordination, limiting the execution of activities of daily living. This study investigated the feasibility and safety of a short-term Pilates-based exercise program in the treatment of upper limb motor coordination for people with PD.
METHODS: Fifteen patients - n (%) 4 women/11 men (27/73), median [interquartile range] age 66 [9] years - participated in this quasi-experimental (before-and-after) clinical trial. Patients underwent a 6-week (30 min/day, 3 days/week) Pilates exercise program using Reformer, Cadillac, Chair, and Barrel equipment. Feasibility was evaluated by adherence to the program and the ability to perform the exercises including progressions on difficulty. Safety was evaluated based on self-reported adverse events. Clinical and functional trends before and after the intervention were also computed regarding handgrip strength (HGS), fine motor coordination (9 Hole Peg Test; 9HPT), bradykinesia (Movement Disorder Society - Unified Parkinson\'s disease Rating Scale; MDS-UPDRS), and upper limb functionality (Test D\'évaluation des Membres Supérieurs des Personnes Âgées, TEMPA).
RESULTS: Of the 18 Pilates sessions, exercise adherence was 100%. The only adverse event observed was mild muscle pain. Pre-post differences were observed only for body bradykinesia and hypokinesia (1.0 [0.0] vs. 0.0 [1.0] s, adjusted p = 0.048).
CONCLUSIONS: A short-term Pilates-based exercise program in the treatment of upper limb muscle strength, manual dexterity, bradykinesia, and functionality is feasible and safe for people with PD. Changes in upper limb bradykinesia encourage randomized clinical trials.