Systematic review exploring the relationship between sexual abuse and lower urinary tract symptoms.

INTRODUCTION AND HYPOTHESIS: Patients presenting with lower urinary tract symptoms (LUTS) may report a history of sexual abuse (SA), and survivors of SA may report LUTS; however, the nature of the relationship is poorly understood. The aim of this review is to systematically evaluate studies that explore LUT dysfunction in survivors of SA. METHODS: A systematic literature search of six databases, Cochrane Database of Systematic Reviews, MEDLINE, EMBASE, CINAHL, AMED, and PsycINFO, was performed. The last search date was June 2021 (PROSPERO CRD42019122080). Studies reporting the prevalence and symptoms of LUTS in patients who have experienced SA were included. The literature was appraised according to the PRISMA statement. The quality of the studies was assessed. RESULTS: Out of 272 papers retrieved, 18 publications met the inclusion criteria: studies exploring LUTS in SA survivors (n=2), SA in patients attending clinics for their LUTs (n=8), and cross-sectional studies (n=8). SA prevalence ranged between 1.3% and 49.6%. A history of SA was associated with psychosocial stressors, depression, and anxiety. LUTS included urinary storage symptoms, voiding difficulties, voluntary holding of urine and urinary tract infections. Most studies were of moderate quality. Assessment of SA and LUTS lacked standardisation. CONCLUSIONS: The review highlights the need for a holistic assessment of patients presenting with LUTS. Although most of the studies were rated as being of 'moderate' quality, the evidence suggests the need to provide a "safe space" in clinic for patients to share sensitive information about trauma. Any such disclosure should be followed up with further assessment.

Visual tests predict dementia risk in Parkinson disease.

OBJECTIVE: To assess the role of visual measures and retinal volume to predict the risk of Parkinson disease (PD) dementia. METHODS: In this cohort study, we collected visual, cognitive, and motor data in people with PD. Participants underwent ophthalmic examination, retinal imaging using optical coherence tomography, and visual assessment including acuity and contrast sensitivity and high-level visuoperception measures of skew tolerance and biological motion. We assessed the risk of PD dementia using a recently described algorithm that combines age at onset, sex, depression, motor scores, and baseline cognition. RESULTS: One hundred forty-six people were included in the study (112 with PD and 34 age-matched controls). The mean disease duration was 4.1 (±2·5) years. None of these participants had dementia. Higher risk of dementia was associated with poorer performance in visual measures (acuity: ρ = 0.29, p = 0.0024; contrast sensitivity: ρ = -0.37, p < 0.0001; skew tolerance: ρ = -0.25, p = 0.0073; and biological motion: ρ = -0.26, p = 0.0054). In addition, higher risk of PD dementia was associated with thinner retinal structure in layers containing dopaminergic cells, measured as ganglion cell layer (GCL) and inner plexiform layer (IPL) thinning (ρ = -0.29, p = 0.0021; ρ = -0.33, p = 0.00044). These relationships were not seen for the retinal nerve fiber layer that does not contain dopaminergic cells and were not seen in unaffected controls. CONCLUSION: Visual measures and retinal structure in dopaminergic layers were related to risk of PD dementia. Our findings suggest that visual measures and retinal GCL and IPL volumes may be useful to predict the risk of dementia in PD.

Building a Digital Wind Farm.

The purpose of this paper is to provide a high level, holistic overview of the work being undertaken in the wind energy industry. It summarises the main techniques used to simulate both aerodynamic and structural issues associated with wind turbines and farms. The motivation behind this paper is to provide new researchers with an outlook of the modelling and simulation landscape, whilst highlighting the trends and direction research is taking. Each section summarises an individual area of simulation and modelling, covering the important historical research findings and a comprehensive analysis of recent work. This segregated approach emphasises the key components of wind energy. Topics range in geometric scales and detail, ranging from atmospheric boundary layer modelling, to fatigue and fracture in the turbine blades. More recent studies have begun to combine a range of scales and physics to better approximate real systems and provide higher fidelity and accurate analyses to manufacturers and companies. This paper shows a clear trend towards coupling both scales and physics into singular models utilising high performance computing system.