The Impact of Physical Activity on Adolescent Low Back Pain: A Systematic Review.

The relationship between physical activity and low back pain (LBP) in adolescents is complex, with conflicting evidence on whether activity is protective or a risk factor. The COVID-19 pandemic has introduced new challenges, increasing sedentary behaviors among adolescents. This systematic review updates the evidence on the association between physical activity and LBP in this population, focusing on the impact of the pandemic.

Patients treated by magnetic growing rods for early-onset scoliosis reach the expected average growth.

Introduction: Magnetic controlled growing rods (MCGRs) are one of the most common procedures to treat early-onset scoliosis (EOS). One of the major concerns is that patients treated with MGCR do not reach an adequate height with MGCR. The present study has one of the largest sample sizes of EOS patients treated by MGCR.

Ultrasonographic assessment of magnetic growing rods overestimates the lengthening of the thoracic spine compared to radiographs in early-onset scoliotic patients.

Purpose: Magnetic growing rods (MGRs) are one of the most common procedures to treat early-onset scoliosis (EOS). Radiographic examinations (X-ray) or ultrasonographic (US) assessments are used to evaluate the lengthening of the rods. X-ray exposes patients to radiation, while the US has not been validated and may be affected by the radiologist's ability to assess elongation.

Fuzzy Entropy-Based Spatial Hotspot Reliability.

Cluster techniques are used in hotspot spatial analysis to detect hotspots as areas on the map; an extension of the Fuzzy C-means that the clustering algorithm has been applied to locate hotspots on the map as circular areas; it represents a good trade-off between the accuracy in the detection of the hotspot shape and the computational complexity. However, this method does not measure the reliability of the detected hotspots and therefore does not allow us to evaluate how reliable the identification of a hotspot of a circular area corresponding to the detected cluster is; a measure of the reliability of hotspots is crucial for the decision maker to assess the need for action on the area circumscribed by the hotspots. We propose a method based on the use of De Luca and Termini's Fuzzy Entropy that uses this extension of the Fuzzy C-means algorithm and measures the reliability of detected hotspots.

A New Validity Index Based on Fuzzy Energy and Fuzzy Entropy Measures in Fuzzy Clustering Problems.

Two well-known drawbacks in fuzzy clustering are the requirement of assigning in advance the number of clusters and random initialization of cluster centers. The quality of the final fuzzy clusters depends heavily on the initial choice of the number of clusters and the initialization of the clusters, then, it is necessary to apply a validity index to measure the compactness and the separability of the final clusters and run the clustering algorithm several times. We propose a new fuzzy C-means algorithm in which a validity index based on the concepts of maximum fuzzy energy and minimum fuzzy entropy is applied to initialize the cluster centers and to find the optimal number of clusters and initial cluster centers in order to obtain a good clustering quality, without increasing time consumption.