Ultrasound findings in painful spastic hip. Muscle thickness in children with cerebral palsy.

BACKGROUND: In cerebral palsy (CP), spasticity is the dominant symptom and hip pain is one of the most common secondary conditions. Aetiology is not clear. Musculoskeletal ultrasound (MSUS) is a low-cost, non-invasive imaging technique that allows assessment of structural status, dynamic imaging, and quick contralateral comparison. OBJECTIVE: A retrospective case-matched-control study. To investigate associated factors with painful spastic hip and to compare ultrasound findings (focusing on muscle thickness) in children with CP vs. typically developing (TD) peers. SETTING: Paediatric Rehabilitation Hospital in Mexico City, from August to November 2018. PARTICIPANTS: 21 children (13 male, 7 + 4.26 years) with CP, in Gross Motor Function Classification System (GMFCS) levels IV to V, with spastic hip diagnosis (cases) and 21 children age- and sex-matched (7 + 4.28 years) TD peers (controls). CHARACTERISTICALLY DATA: Sociodemographic data, CP topography, degree of spasticity, mobility arch, contractures, Visual Analog Scale (VAS), GMFCS, measurements of the volumes of eight major muscles of the hip joint and MSUS findings of both hips. RESULTS: All children with CP group reported chronic hip pain. Associated factors for hip pain (high VAS hip pain score) were degree of hip displacement (percentage of migration), Ashworth Level, GMFCS level V. No synovitis, bursitis or tendinopathy was found. Significant differences (p < 0.05) were found in muscle volumes in all hip muscles (right and left) except in the right and left adductor longus. CONCLUSION: Though possibly the most important issue with diminished muscle growth in CP children is the influence on their long-term function, it is likely that training routines that build muscle size may also increase muscle strength and improve function in this population. To improve the choice of treatments in this group and maintain muscle mass, longitudinal investigations of the natural history of muscular deficits in CP as well as the impact of intervention are needed.

A Novel Technique for the Evaluation and Interpretation of Elastography in Salivary Gland Involvement in Primary Sjögren Syndrome.

Ultrasound (US) of major salivary glands (MSG) evaluates echogenicity, border features and vascularization, with elastography, it can detect tissue elasticity and glandular fibrosis, related to inflammation in Primary Sjögren's syndrome (pSS). This study aimed to develop a novel technique by pixel analysis for evaluation and interpretation of elastography in MSG in pSS. A cross-sectional and observational multicenter study was conducted. The US of MSG performed in orthogonal planes in grayscale, Doppler, and shear-wave elastography. For elastography images of each gland were analyzed with the open-source program ImageJ to perform a pixel analysis. Statistical analysis was performed with the IBM-SPSS v25 program. Fifty-nine women with a mean age of 57.69 (23-83) years were recruited; pSS mean duration of 87 (5-275) months, and 12 healthy women without sicca symptoms as a control group with a mean age of 50.67 (42-60) years. Intragroup analysis showed p-values >0.05 between sicca symptoms, ocular/dryness tests, biopsy, US, and pixel analysis; correlation between Hocevar and pixel analysis was not found (rho < 0.1, p >0.5). MSG anatomical size was 41.7 ± 28.2 mm vs. 67.6 ± 8.8 mm (p ≤ 0.0001); unstimulated whole saliva flow rate was 0.80 ± 0.80 ml/5 min vs. 1.85 ± 1.27 ml/5 min (p = 0.016). The elastography values (absolute number of pixels) were 572.38 ± 99.21 vs. 539.69 ± 93.12 (p = 0.290). A cut-off point risk for pSS identified with less than 54% of red pixels in the global MSG mass [OR of 3.8 95% CI (1.01-15.00)]. Pixel analysis is a new tool that could lead to a better understanding of the MSG chronic inflammatory process in pSS.

Smart Homes as Enablers for Depression Pre-Diagnosis Using PHQ-9 on HMI through Fuzzy Logic Decision System.

Depression is a common mental illness characterized by sadness, lack of interest, or pleasure. According to the DSM-5, there are nine symptoms, from which an individual must present 4 or 5 in the last two weeks to fulfill the diagnosis criteria of depression. Nevertheless, the common methods that health care professionals use to assess and monitor depression symptoms are face-to-face questionnaires leading to time-consuming or expensive methods. On the other hand, smart homes can monitor householders' health through smart devices such as smartphones, wearables, cameras, or voice assistants connected to the home. Although the depression disorders at smart homes are commonly oriented to the senior sector, depression affects all of us. Therefore, even though an expert needs to diagnose the depression disorder, questionnaires as the PHQ-9 help spot any depressive symptomatology as a pre-diagnosis. Thus, this paper proposes a three-step framework; the first step assesses the nine questions to the end-user through ALEXA or a gamified HMI. Then, a fuzzy logic decision system considers three actions based on the nine responses. Finally, the last step considers these three actions: continue monitoring through Alexa and the HMI, suggest specialist referral, and mandatory specialist referral.