Eyelid ptosis and muscle weakness in a child with Kawasaki disease: a case report

Background Kawasaki disease (KD) is an acute febrile vasculitis that often occurs in children under 5 years. Ptosis and muscle weakness associated with KD are rarely documented. Case presentation We present a case of KD with eyelid ptosis and muscle weakness in a 3-year-old boy. At admission, grade IV and grade III muscle strength were recorded for upper and lower limbs, respectively. Diminished patellar tendon reflex was noted. Laboratory evaluation showed hypokalemia with the serum potassium concentration of 2.62 mmol/L. Intravenous immunoglobulin (IVIG) and aspirin were initiated immediately accompanied with methylprednisolone for adjunctive therapy. Potassium supplement was administered at the same time, which resulted in the correction of hypokalemia on the 2nd day of admission but no improvement in ptosis and muscle weakness. Neostigmine testing, lumber puncture, electromyography, and cerebral and full spine MRI were performed, which, however, did not find evidence for neural and muscle diseases. On the 5th day, the fever was resolved. On the 6th day, eyelid ptosis disappeared. And on the 14th day, the muscle strength and muscle tension returned to normal, patellar tendon reflex could be drawn out normally, and the boy regained full ambulatory ability. Conclusions KD might affect the neural and muscular systems, and KD complicated with eyelid ptosis and muscle weakness is responsive to the standard anti-inflammatory treatment plus adjunctive corticosteroid therapy.

Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices

Deep tendon reflexes are one of the main components of the clinical nervous system examinations. These assessments are inexpensive and quick. However, evaluation can be subjective and qualitative. This study aimed to objectively evaluate hyperreflexia of the patellar tendon reflex using portable mechanomyography (MMG) and electromyography (EMG) devices. This study included 10 preoperative patients (20 legs) who had a pathology that could cause bilateral patellar tendon hyperreflexia and 12 healthy volunteers (24 legs) with no prior history of neurological disorders. We attached MMG/EMG sensors onto the quadriceps and tapped the patellar tendon with maximal and constant force. Our results showed a significantly high amplitude of the root mean square (RMS) and low frequency of the mean power frequency (MPF) in the rectus femoris, vastus medialis, and vastus lateralis muscles in both EMG and MMG with both maximal and constant force. Especially in the patients with cervical and thoracic myelopathy, the receiver operating characteristic (ROC) curve for diagnosing hyperreflexia of the patellar tendon showed a moderate to very high area under the curve for all EMG–RMS, EMG–MPF, MMG–RMS, and MMG–MPF values. The use of EMG and MMG for objectively quantifying the patellar tendon reflex is simple and desirable for future clinical applications and could help diagnose neurological disorders.

IMPLEMENTATION OF A SMARTPHONE WIRELESS GYROSCOPE PLATFORM WITH MACHINE LEARNING FOR CLASSIFYING DISPARITY OF A HEMIPLEGIC PATELLAR TENDON REFLEX PAIR

The patellar tendon reflex response provides fundamental means of assessing a subject’s neurological health. Dysfunction regarding the characteristics of the reflex response may warrant the escalation to more advanced diagnostic techniques. Current strategies involve the manual elicitation of the patellar tendon reflex by a highly skilled clinician with subsequent interpretation according to an ordinal scale. The reliability of the ordinal scale approach is a topic of contention. Highly skilled clinicians have been in disagreement regarding even the observation of asymmetric reflex pairs. An alternative strategy incorporated the ubiquitous smartphone with a software application to function as a wireless gyroscope platform for quantifying the reflex response. Each gyroscope signal recording of the reflex response can be conveyed wirelessly through Internet connectivity as an email attachment. The reflex response is evoked through a potential energy impact pendulum that enables prescribed targeting and potential energy level. The smartphone functioning as a wireless gyroscope platform reveals an observationally representative gyroscope signal of the reflex response. Three notably distinguishable attributes of the reflex response are incorporated into a feature set for machine learning: maximum angular rate of rotation, minimum angular rate of rotation, and time disparity between maximum and minimum angular rate of rotation. Four machine learning platforms such as the J48 decision tree, K-nearest neighbors, logistic regression, and support vector machine, were applied to the patellar tendon reflex response feature set incorporating a hemiplegic patellar tendon reflex pair. The J48 decision tree attained 98% classification accuracy, and the K-nearest neighbors, logistic regression, and support vector machine achieved perfect classification accuracy for distinguishing between a hemiplegic affected leg and unaffected leg patellar tendon reflex pair. The research findings reveal the potential of machine learning for enabling advanced diagnostic acuity respective of the gyroscope signal of the patellar tendon reflex response.