Background The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions. Objective The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence. Methods We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials. Results Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I2=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I2=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I2=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I2=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I2=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I2=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss. Conclusions Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.
Objective To determine the prevalence and to characterize the different types of strokes in children with cancer at the Children’s Cancer Center of Lebanon (CCCL), in addition to assess the factors and clinical findings leading to stroke in children. Methods We retrospectively reviewed the medical records and brain images (MRIs and CTs) of children admitted to the CCCL and diagnosed with cancer between years 2008 and 2017. Brain images were reviewed for the strokes’ onset, size, location, possible origin, its recurrence and type: intracranial hemorrhage (ICH), acute arterial ischemic stroke, and cerebral sinus venous thrombosis (CSVT) with and without venous infarct. Medical charts of the patients were reviewed for age, sex, their type of cancer, the treatment protocol they followed, and abnormal findings on their laboratory studies and neurological exams. Results Out of the 905 charts reviewed, twenty-seven children with variable types of cancer had strokes, with a prevalence of 2.9%. Their median age at cancer diagnosis was 9.4 (4.8-13.7) years and the median age at stroke onset was 10.6 (6.7-15.5) years. The median time between the cancer diagnosis and the stroke episode was 6 months. CSVT cases were the most common (60%) followed by acute arterial ischemic (22%) and hemorrhagic strokes (18%), with CSVT being the latest to occur. We observed that the different types of strokes were related to some types of cancer. Of the children that had acute arterial ischemic stroke in this cohort, 83% had brain tumors, of the children who had CSVT, 87.5% had leukemia, and of the children who had hemorrhagic stroke, 40% had leukemia. Neurological abnormalities were more prevalent in acute arterial ischemic stroke (80%). Patients with CSVT recovered better than those with other types of strokes. Strokes recurred in 60% of ischemic strokes. L-Asparaginase was significantly associated with CSVT. Conclusions The prevalence of strokes was 2.9% in children with cancer. We were able to identify factors related to the types of the stroke that occurred in children including the type and location of the cancer the type of treatment received, and stroke recurrence.
ObjectiveTo determine the incidence of pituitary incidentalomas in the paediatric population and among its different age subgroups as well as to identify the characteristics of these lesions. Additionally, we aim to give a perspective on the management and follow‐up of these patients.Design and PatientsWe retrospectively studied MRI of children aged 18 years or below who underwent MRI with sellar region within their field of view between January 2010 and December 2018.MeasurementsPituitary lesions were considered incidental according to the definition by the Endocrine Society. We reported the size, location and signal characteristics of each lesion. Medical charts of the subjects were reviewed for age, sex, the MRI indication and the hormonal assays levels.ResultsWe identified 40 pituitary lesions of which 31 were incidental lesions. The incidence of pituitary incidentaloma in our cohort was 22 per 1000 patients with female predisposition ( 64.5%) and a mean age of 11 ± 6 years. Rathke's cleft cyst was the most prevalent lesion, accounting for 67.7% followed by cystic pituitary lesions and microadenomas. The most common indications for imaging were growth disturbance (12.9%) followed by headache (9.7%). Abnormal laboratory workup was present in 13% of the subjects. Incidental lesions were more common in the older age groups compared to young children.ConclusionIncidental pituitary lesions in the paediatric population are relatively infrequent and increases with age. Rathke's cleft cyst is the most common incidentally encountered pituitary lesion followed by cystic pituitary lesions and microadenomas.
Objective: This pilot study aims to identify white matter (WM) tract abnormalities in Autism Spectrum Disorders (ASD) toddlers and pre-schoolers by Diffusion Tensor Imaging (DTI), and to correlate imaging findings with clinical improvement after early interventional and Applied Behavior Analysis (ABA) therapies by Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP). Methods: DTI scans were performed on 17 ASD toddlers/pre-schoolers and seven age-matched controls. Nine ASD patients had follow-up MRI 12 months following early intervention and ABA therapy. VB-MAPP was assessed and compared at diagnosis, 6 and 12 months after therapies. Tract-Based Spatial Statistics (TBSS) was used to measure fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial (RD) diffusivity. Results: VB-MAPP scores improved at 6 and 12 months after early intervention and ABA therapy compared to scores at baseline. TBSS analysis showed significant FA decrease and/or RD increase in ASD patients before therapy vs. controls in inferior fronto-occipital fasciculi, uncinate fasciculi, left superior fronto-occipital fasciculus, forceps minor, left superior fronto-occipital fasciculus, right superior longitudinal fasciculus, corona radiate bilaterally, and left external capsule. A significantly FA increase in 21 tracts and ROIs is reported in post- vs. pre-therapy DTI analysis. Conclusion: DTI findings highlighted ASD patient WM abnormalities at diagnosis and confirmed the benefits of 12 months of early intervention and ABA therapy on clinical and neuro imaging outcomes.
BACKGROUND AND PURPOSE:There is a paucity of data regarding the incidence of structural brain lesions in children with new-onset unprovoked seizures. Our aim was to determine the frequencies and types of epileptogenic lesions detected on a dedicated epilepsy protocol MR imaging according to age group, the presence of developmental delay, and the number and types of seizures. MATERIALS AND METHODS:Consecutive children between 6 months and 18 years of age with new-onset unprovoked seizures were included. The frequencies and types of epileptogenic lesions were determined and then stratified according to sex, age groups, the presence of developmental delay, and the number and types of seizures at presentation. Multivariate analysis was used to identify variables significantly associated with the presence of epileptogenic lesions.RESULTS: One thousand children were included. An epileptogenic lesion was identified in 26%, with malformations of cortical development being the most common lesion (32%), followed by hypoxic-ischemic injury (20%) and vascular etiologies (16%). Univariate analysis showed a significant increase in the frequency of epileptogenic lesions with decreasing age, the presence of developmental delay, and the number and types of seizures at presentation. The presence of developmental delay and seizure type at presentation remained significant in a multivariate analysis. CONCLUSIONS:We documented a relatively high rate of epileptogenic lesions in children with new-onset seizures, with the presence of developmental delay and specific seizure types being associated with a higher likelihood of detecting an epileptogenic lesion on neuroimaging. This study fulfills the requirements of the study design recommended by the Practice Committee of the American Academy of Neurology, and we hope that our results will assist the relevant societies and committees in formulating neuroimaging guidelines for children with new-onset seizures.ABBREVIATIONS: DD ¼ developmental delay; MCD ¼ malformations of cortical development; MTS ¼ mesial temporal sclerosis; NCS ¼ neurocutaneous syndromes; PVL ¼ periventricular leukomalacia A brain MR imaging is useful in the work-up of patients with new-onset seizures because it can help define the electroclinical syndrome, identify surgically remediable lesions, and assist in predicting medical refractoriness. 1,2 In addition, according to the new proposed definition of epilepsy, a brain MR imaging may
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