Method For Assessment Of Severity Research Articles

Non invasive techniques for direct muscle quality assessment after exercise intervention in older adults: a systematic review

BackgroundThe aging process induces neural and morphological changes in the human musculoskeletal system, leading to a decline in muscle mass, strength and quality. These alterations, coupled with shifts in muscle metabolism, underscore the essential role of physical exercise in maintaining and improving muscle quality in older adults. Muscle quality's morphological domain encompasses direct assessments of muscle microscopic and macroscopic aspects of muscle architecture and composition. Various tools exist to estimate muscle quality, each with specific technical requirements. However, due to the heterogeneity in both the studied population and study methodologies, there is a gap in the establishment of reference standards to determine which are the non-invasive and direct tools to assess muscle quality after exercise interventions. Therefore, the purpose of this review is to obtain an overview of the non-invasive tools used to measure muscle quality directly after exercise interventions in healthy older adults, as well as to assess the effects of exercise on muscle quality.Main textTo address the imperative of understanding and optimizing muscle quality in aging individuals, this review provides an overview of non-invasive tools employed to measure muscle quality directly after exercise interventions in healthy older adults, along with an assessment of the effects of exercise on muscle quality.ResultsThirty four studies were included. Several methods of direct muscle quality assessment were identified. Notably, 2 studies harnessed CT, 20 utilized US, 9 employed MRI, 2 opted for TMG, 2 adopted myotonometry, and 1 incorporated BIA, with several studies employing multiple tests. Exploring interventions, 26 studies focus on resistance exercise, 4 on aerobic training, and 5 on concurrent training.ConclusionsThere is significant diversity in the methods of direct assessment of muscle quality, mainly using ultrasound and magnetic resonance imaging; and a consistent positive trend in exercise interventions, indicating their efficacy in improving or preserving muscle quality. However, the lack of standardized assessment criteria poses a challenge given the diversity within the studied population and variations in methodologies.. These data emphasize the need to standardize assessment criteria and underscore the potential benefits of exercise interventions aimed at optimizing muscle quality.

The efficacy and safety of modified transbronchial cryobiopsy in the diagnosis of interstitial lung disease.

The objective of this study is to investigate the efficacy and safety of flexible transbronchial cryobiopsy (TBCB) in the diagnosis of diffuse parenchymal lung disease (DPLD) in a routine bronchoscopy examination room under analgesia and sedation, using neither endotracheal intubation or rigid bronchoscope nor fluoroscopy or general anesthesia. The data from 50 DPLD patients with unknown etiology who were treated in the Affiliated Hospital of Guilin Medical College from May 2018 to September 2020 were collected, and 43 were eventually included. The specimens obtained from these 43 patients were subjected to pathological examination, pathogenic microorganism culture, etc, and were analyzed in the clinical-radiological-pathological diagnosis mode to confirm the efficacy of TBCB in diagnosing the cause of DPLD. Subsequently, the intraoperative and postoperative complications of TBCB and their severity were closely observed and recorded to comprehensively evaluate the safety of TBCB. For the 43 patients included, a total of 85 TBCB biopsies were performed (1.98 [1, 4] times/case), and 82 valid tissue specimens were obtained (1.91 [1, 4] pieces/case), accounting for 96.5% (82/85) of the total sample. The average specimen size was 12.41 (1, 30) mm2. Eventually, 38 cases were diagnosed, including 11 cases of idiopathic pulmonary fibrosis, 5 cases of connective tissue-related interstitial lung disease, 5 cases of nonspecific interstitial pneumonia, 4 cases of tuberculosis, 4 cases of occupational lung injury, 3 cases of interstitial pneumonia with autoimmune characteristics, 1 case of lung cancer, 2 cases of interstitial lung disease (unclassified interstitial lung disease), 1 case of hypersensitivity pneumonitis, 1 case of pulmonary alveolar proteinosis, and 1 case of fungal infection. The remaining 5 cases were unclarified. For infectious diseases, the overall etiological diagnosis rate was 88.4% (38/43). With respect to complications, pneumothorax occurred in 4 cases (9.3%, 4/43, including 1 mild case and 3 moderate cases), of which 3 cases (75%) were closed by thoracic drainage and 1 case (25%) was absorbed without treatment. In addition, 22 cases experienced no bleeding (51.2%) and 21 cases suffered bleeding to varying degrees based on different severity assessment methods. TBCB is a minimally invasive, rapid, economical, effective, and safe diagnostic technique.

Comparative study of different cavitation erosion assessment methods in cavitating flow around a Delft Twist hydrofoil

Cavitation erosion is a common phenomenon in hydraulic machines, which severely threatens their stable operation. Although several methods for erosion risk assessment have been proposed, few researchers work on the comparative study of different cavitation erosion assessment methods. Therefore, this study utilized Large Eddy Simulation (LES) combined with Zwart-Gerber-Belamri (ZGB) cavitation model to conduct the numerical simulation for the cavitating flow around a Delft Twist hydrofoil. The Erosive Power Method (EPM), Improved Gray Level Method (IGLM) and Energy Conservative Method (ECM) are employed separately to evaluate the cavitation erosion. Among the three results, the EPM results cannot accurately predict erosion in the middle region and trailing edge region, where the U-shaped vortex collapse. The results of IGLM and ECM can predict the erosion in the middle region and erosion caused by the U-shaped vortex at the trailing edge. IGLM still needs artificial thresholds, while ECM emphasizes areas with higher cavitation risk by amplifying parameter n. The ECM method is more objective from the simulation results.

Progress in Anode Stability Improvement for Seawater Electrolysis to Produce Hydrogen.

Seawater electrolysis for hydrogen production is a sustainable and economical approach that can mitigate the energy crisis and global warming issues. Although various catalysts/electrodes with excellent activities have been developed for high-efficiency seawater electrolysis, their unsatisfactory durability, especially for anodes, severely impedes their industrial applications. In this review, attention is paid to the factors that affect the stability of anodes and the corresponding strategies for designing catalytic materials to prolong the anode's lifetime. In addition, two important aspects-electrolyte optimization and electrolyzer design-with respect to anode stability improvement are summarized. Furthermore, several methods for rapid stability assessment are proposed for the fast screening of both highly active and stable catalysts/electrodes. Finally, perspectives on future investigations aimed at improving the stability of seawater electrolysis systems are outlined.

Selecting and justifying prognostic criteria to assessing the severity of condition during traumatic illness in combined chest and abdominal trauma after acute traffic accidents

Relevance. Improving prognostic criteria to assess the severity of combined chest and abdominal trauma is urgently needed to justify the scope of intensive care in victims of road accidents during acute traumatic illness.Objective. The objective of the study is to improve the results of treatment during acute traumatic illness in combined chest and abdominal trauma after road accidents, as well as to enhance efficiency of prognostic criteria for severity assessment.Methods. A single-center retrospective and prospective controlled clinical study was conducted in 1400 victims who were treated at the N.S. Karpovich Krasnoyarsk Interdistrict Clinical Hospital of Emergency Care Medicine from 2012 to 2022 and were diagnosed with isolated or combined chest and abdominal trauma. To assess the severity of injury and perform triage, the specific method of severity assessment in combined trauma after road traffic accidents was used, which was developed by the research team of the Prof. V.F. Voino-Yasenetsky Krasnoyarsk State Medical University.Results and discussion. A detailed analysis of the indicators applied to patients of different severity showed that mild and moderate chest and abdomen injuries led to changes in hemodynamic parameters within the physiological norm. The injury in question did not cause consciousness or respiratory disorders in victims of road traffic accidents. Severe injuries led to the development of shock and respiratory failure, in combination with depression of consciousness. In order to compare across different condition severity degrees evaluated by physiological indicators, respective medians and dispersion measures were analyzed for each group. The analysis allowed to assess exacerbated severity of condition in our patients. This procedure requires further adjustment to pre-hospital emergency medical care.Conclusion. The performed statistical analysis allowed to assess the efficiency of severity assessment in victims of road accidents in prehospital setting.

Assessment of the value of 6-min walk test to predict the severity of interstitial lung disease among Indian patients

Introduction: The prevalence of interstitial lung disease (ILD) is increasing. High-resolution computerized tomography (HRCT), despite having limitations, remains the choice of method for diagnosis and assessment of severity of ILD. Objective: To determine the efficacy of 6-min walk test to assess the severity of the ILD compared to HRCT. Methodology: A cross-sectional study was done among 40 patients with ILD in a tertiary hospital in Hyderabad. The data included age, gender, smoking, HRCT, 6-min walk test, spirometry, diffusion lung capacity and medical history. Mann–Whitney U test, Kruskal–Wallis test, and ROC curve were used to determine the outcomes. Results: The mean age of participants was 57.18 + 13.01 years. 62.5% never smoked. Overall, 50% had severe ILD, and the rest had mild to moderate. The distance walked per 6-min, SpO2 before and SpO2 after, was significantly lower (p = 0.001; 0.002; <0.001, respectively) among patients with severe ILD than mild or moderate. The sensitivity and 1-specificity of the distance walked in 6-min to detect the severity of ILD was 0.90 and 0.31, respectively; sensitivity and 1-specificity of SpO2 before the test was 0.81 and 0.34, while that of SpO2 after the test was 0.90 and 0.17, respectively. Conclusion: This study found that the 6-min walk test is highly sensitive and specific for predicting the severity of ILD among patients. All three components of the 6-min walk test: distance, oxygen saturation before, and oxygen saturation after the test significantly lowered and were independent predictors of severe ILD.

Simplified Diagnosis of Urosepsis by Emergency Ultrasound Combined with Clinical Scores and Biomarkers.

Urosepsis is a life-threatening medical condition due to a systemic infection that originates in the urinary tract. Early diagnosis and treatment of urosepsis are critical to reducing mortality rates and preventing complications. Our study was aimed at identifying a fast and reliable method for early urosepsis diagnosis and severity assessment by combining prognostic scores such as SOFA and NEWS with ultrasound examination and serum markers PCT and NLR. We performed a single-center prospective observational study in the Craiova Clinical Emergency Hospital. It initially analysed 204 patients admitted for sepsis of various origins in our hospital between June and October 2023. Those with urological conditions that were suspected to have urosepsis have been selected for the study so that finally 76 patients were included as follows: the severe cases with persistent hypotension requiring vasopressor were enrolled in the septic shock group (15 patients - 19.7%), while the rest were included in the sepsis group (61 patients - 80.3%). Mortality rate in our study was 10.5% (8/76 deaths due to sepsis). Both prognostic scores SOFA and NEWS were significantly elevated in the septic shock group, as were the sepsis markers PCT and NLR. We identified a strong significant positive correlation between the NEWS and SOFA scores (r = 0.793) as well as PCT and NLR (r=0.417). Ultrasound emergency evaluation proved to be similar to CT scan in the diagnosis of urosepsis (RR = 0.944, p=0.264). ROC analysis showed similar diagnostic performance for both scores (AUC = 0.874 for SOFA and 0.791 for NEWS), PCT and NLR (AUC = 0.743 and 0.717). Our results indicate that an accurate and fast diagnosis of urosepsis and its severity may be accomplished by combining the use of simpler tools like emergency ultrasound, the NEWS score and NLR which provide a similar diagnosis performance as other more complex evaluations.

Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features

Objective. This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system. Approach. We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations. Main results. For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model. Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.

Predicting acute pancreatitis severity with enhanced computed tomography scans using convolutional neural networks

This study aimed to evaluate acute pancreatitis (AP) severity using convolutional neural network (CNN) models with enhanced computed tomography (CT) scans. Three-dimensional DenseNet CNN models were developed and trained using the enhanced CT scans labeled with two severity assessment methods: the computed tomography severity index (CTSI) and Atlanta classification. Each labeling method was used independently for model training and validation. Model performance was evaluated using confusion matrices, areas under the receiver operating characteristic curve (AUC-ROC), accuracy, precision, recall, F1 score, and respective macro-average metrics. A total of 1,798 enhanced CT scans met the inclusion criteria were included in this study. The dataset was randomly divided into a training dataset (n = 1618) and a test dataset (n = 180) with a ratio of 9:1. The DenseNet model demonstrated promising predictions for both CTSI and Atlanta classification-labeled CT scans, with accuracy greater than 0.7 and AUC-ROC greater than 0.8. Specifically, when trained with CT scans labeled using CTSI, the DenseNet model achieved good performance, with a macro-average F1 score of 0.835 and a macro-average AUC-ROC of 0.980. The findings of this study affirm the feasibility of employing CNN models to predict the severity of AP using enhanced CT scans.

Teaching Clinical Reasoning inthe Preclinical Period.

Developing the clinical reasoning skills necessary to becoming an astute diagnostician is essential for medical students. While some medical schools offer longitudinal opportunities for students to practice clinical reasoning during the preclinical curriculum, there remains a paucity of literature fully describing what that curriculum looks like. As a result, medical educators struggle to know what an effective clinical reasoning curriculum should look like, how it should be delivered, how it should be assessed, or what faculty development is necessary to be successful. We present our Introduction to Clinical Reasoning course that is offered throughout the preclinical curriculum of the Uniformed Services University of the Health Sciences. The course introduces clinical reasoning through interactive lectures and 28 case-based small group activities over 15 months.The curriculum is grounded in script theory with a focus on diagnostic reasoning. Specific emphasis is placed on building the student's semantic competence, constructing problem lists, comparing and contrasting similar diagnoses, constructing a summary statement, and formulating a prioritized differential diagnosis the student can defend. Several complementary methods of assessment are utilized across the curriculum. These include assessments of participation, knowledge, and application. The course leverages clinical faculty, graduate medical education trainees, and senior medical students as small group facilitators. Feedback from students and faculty consistently identifies the course as a highly effective and engaging way to teach clinical reasoning. Our Introduction to Clinical Reasoning course offers students repeated exposure to well-selected cases to promote their development of clinical reasoning. The course is an example of how clinical reasoning can be taught across the preclinical curriculum without extensive faculty training in medical education or clinical reasoning theory. The course can be adapted into different instructional formats to cover a variety of topics to provide the early learner with sequential exposure and practice in diagnostic reasoning.

A novel vulnerability severity assessment method for source code based on a graph neural network

A novel vulnerability severity assessment method for source code based on a graph neural network

Quantitative Assessment of Upper-Limb Volume: Implications for Lymphedema Rehabilitation?

Upper-limb lymphedema is a chronic condition characterized by the accumulation of lymphatic fluid in the arm or hand, resulting in swelling and functional impairment. The accurate and reliable volumetric assessment of limb volume is crucial for the correct management of lymphedema. This narrative review provides an overview of the different methods proposed in the literature for the volumetric assessment of upper-limb lymphedema. In more detail, several methods of volumetric assessment have been proposed in recent years, including water displacement, the centimetric method, perometry, bioimpedance spectroscopy, dual-energy X-ray absorptiometry, magnetic resonance imaging, computed tomography, and three-dimensional laser scanning techniques. On the other hand, each method is characterized by specific strengths and limitations in terms of accuracy, reliability, practicality, and cost-effectiveness. Moreover, factors including operator experience, equipment availability, and patient population characteristics might have several implications in the optimal assessment of upper-limb volume. In this context, a precise volumetric assessment is crucial to improving the rehabilitation framework, patient education, and research outcomes. As a result, the integration of emerging technologies is needed to improve the tailored management of patients with upper-limb lymphedema. In conclusion, volumetric assessment methods provide valuable insights in the management of upper-limb lymphedema, improving patient care, treatment outcomes, and research advancements. Future research should focus on testing these innovative solutions on larger samples of patients to enhance the reproducibility, accuracy, accessibility, and clinical utility of volumetric assessment methods in the complex treatment framework of upper-limb lymphedema.

Demagnetization Detection and Severity Assessment in PMSMs Using Search Coils Exploiting Machine's Symmetry

Magnet demagnetization in permanent magnet synchronous machines (PMSMs) can produce inadmissible performance degradation. Search coils (SCs) have been proven to be a viable option for its detection. Existing methods allow detection of demagnetization of one permanent magnet with three or less SCs. However, detection and severity assessment of the fault has been reported only for the particular case of using one SC per stator slot. This paper proposes two alternative methods for demagnetization detection and severity assessment of PMSMs using a reduced number of SCs. The first method relies on the zero-sequence voltage of three SCs electrically shifted 120 electrical degrees. The second method relies on the differential induced voltage between two SCs electrically shifted 360º. It will be shown that the proposed methods improve the performance of existing methods. Experimental results validating the proposed approach will be provided.

Diagnostic Accuracy of Admission C Reactive Proteins in Predicting Severity of Acute Pancreatitis Keeping CT Scan as Gold Standard

Introduction: Acute pancreatitis is common, with an alarming rise in the global incidence. The clinical course of AP is highly variable, ranging from mild, self-limiting symptoms to multiple organ dysfunction and/or death. Objective: To evaluate the diagnostic accuracy of admission C reactive proteins in predicting the severe acute pancreatitis keeping computed tomography as gold standard. Material and methods: This Cross-sectional study was conducted at Department of Gastroenterology, Aga khan hospital, Karachi from 19-06-2019 till 19-06-2020. Data was prospectively collected from patients after taking a verbal consent. 181 patients who met the diagnostic criteria were included. Quantitative data was presented as simple descriptive statistics giving mean and standard deviation and qualitative variables was presented as frequency and percentages. Sensitivity, specificity, positive and negative predictive values and diagnostic accuracy was calculated. Results: A total of 181 patients who met the inclusion and exclusion criteria were included in this study. Mean age, duration of symptoms, BMI, height, weight and CRP in our study was 49.48±10.36 years, 14.88±4.87 hours, 29.8±4.74 kg/m2, 146.5±10.41 cm, 78.9±8.58 kg and 110.9±28.54 mg/L. Sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of CRP for diagnosis of severe acute pancreatitis by taking CT scan as gold standard was found to be 88.8%, 81.5%, 94.7%, 65.9% and 87.2%. Conclusion: CRP it is an inexpensive alternative to the conventional severity assessment methods for the prediction of severity and outcome of patients with acute pancreatitis and can serve as an early indicator of the progression of acute pancreatitis into a serious state. Keywords: Severe acute pancreatitis, C reactive protein and CT scan.

Can student English competence be measured by using standardized test?: A reflection of previous English examination on assessment policy

Assessment is one the important aspect in education process. However, the assessment that relies on the examination, especially written test cannot describe the student real competence in English especially for speaking skill. This paper presents the reflection of previous policy in the assessment in English subject. This paper argues that there are discrepancy of the assessment practice and assessment theory which is implemented by the ministry of education. In addition, this paper also suggests several methods of assessment in English and provide the principles of language assessment and its implementation in the examination, finally this paper also recommended to accommodate school-based and external assessments.

Critical review of methods and models for biodiversity impact assessment and their applicability in the LCA context

Global biodiversity is in rapid decline and halting biodiversity loss is one of the most important challenges humanity must tackle now and in the immediate future. The five main direct drivers of biodiversity loss are climate change, pollution, land use, overexploitation of resources and the spread of invasive species, which result from indirect drivers such as unsustainable production and consumption. It is therefore of paramount importance that scientifically robust methods are developed to capture impacts on biodiversity from a value-chain perspective. Life Cycle Assessment (LCA) methodology allows to quantify the impact of products and organisations throughout their whole life cycle. In the LCA framework, several methods for biodiversity impact assessment have been developed. Building on previous reviews, this article aims to critically analyse methods and models for biodiversity impact assessment in LCA and beyond as comprehensively as possible, and to select those that may be most suitable for application in an LCA context. 64 methods were reviewed and 23 were selected for a detailed analysis based on availability of documentation, domain of application, geographical scope, potential to be used in LCA, and added value. The analysis addressed their goal and scope, data use and needs, and impact assessment characteristics, revealing strengths and weaknesses of the methods. There is currently no method that takes well into account at the same time the variety of pressures on biodiversity, ecosystems, taxonomic groups, essential biodiversity variables classes, and the fundamental aspects to consider in biodiversity impact assessments – but for each of these five criteria, we show which methods perform best. For the future development of biodiversity impact assessment, it is required to improve the coverage of drivers of biodiversity loss, increase ecosystem and taxonomic coverage, include the assessment of ecosystem services, and develop robust indicators that allow for complementary analysis of more essential biodiversity aspects.

VulDistilBERT: A CPS Vulnerability Severity Prediction Method Based on Distillation Model

With the vigorous development of the Internet, the ecosystem of cyber-physical systems is also developing at a high speed, but cyber-physical systems may be accompanied by unknown vulnerabilities in the process of concrete implementation. Thus, the number of vulnerabilities in cyber-physical systems has been increasing year by year. The vulnerability evaluation speed cannot keep up with the vulnerability exposure speed. The traditional manual evaluation method can no longer effectively deal with such large-scale vulnerabilities, resulting in a backlog of vulnerabilities. Therefore, the vulnerability evaluation results have a certain lag. To address this problem, the paper proposes a vulnerability severity assessment method based on the distillation model. The method first uses data augmentation and integration of optimal subsets to improve the amount of information in the vulnerability description text, then uses the DistilBERT model to characterize the text of the vulnerability description text, and then the characterized feature vectors are classified based on the linear layer to achieve the purpose of assessing vulnerability severity. Compared with the current method of manual assessment based on the CVSS metric system, this method can automate the assessment of vulnerabilities based on vulnerability description text, which improves the speed of vulnerability assessment, and the assessment accuracy and other metrics achieved by this method are improved compared with similar studies. This approach provides an automated solution for cyber-physical systems vulnerability assessment and can better address the current situation where cyber-physical systems vulnerabilities are being exposed at an accelerated rate.

Severity assessment of wheat stripe rust based on machine learning.

The accurate severity assessment of wheat stripe rust is the basis for the pathogen-host interaction phenotyping, disease prediction, and disease control measure making. To realize the rapid and accurate severity assessment of the disease, the severity assessment methods of the disease were investigated based on machine learning in this study. Based on the actual percentages of the lesion areas in the areas of the corresponding whole single diseased wheat leaves of each severity class of the disease, obtained after the image segmentation operations on the acquired single diseased wheat leaf images and the pixel statistics operations on the segmented images by using image processing software, under two conditions of considering healthy single wheat leaves or not, the training and testing sets were constructed by using two modeling ratios of 4:1 and 3:2, respectively. Then, based on the training sets, two unsupervised learning methods including K-means clustering algorithm and spectral clustering and three supervised learning methods including support vector machine, random forest, and K-nearest neighbor were used to build severity assessment models of the disease, respectively. Regardless of whether the healthy wheat leaves were considered or not, when the modeling ratios were 4:1 and 3:2, satisfactory assessment performances on the training and testing sets can be achieved by using the optimal models based on unsupervised learning and those based on supervised learning. In particular, the assessment performances obtained by using the optimal random forest models were the best, with the accuracies, precisions, recalls, and F1 scores for all the severity classes of the training and testing sets equal to 100.00% and the overall accuracies of the training and testing sets equal to 100.00%. The simple, rapid, and easy-to-operate severity assessment methods based on machine learning were provided for wheat stripe rust in this study. This study provides a basis for the automatic severity assessment of wheat stripe rust based on image processing technology, and provides a reference for the severity assessments of other plant diseases.

Global Prevalence of Diabetic Retinopathy in Pediatric Type 2 Diabetes

Type 2 diabetes (T2D) is increasing globally. Diabetic retinopathy (DR) is a leading cause of blindness in adults with T2D; however, the global burden of DR in pediatric T2D is unknown. This knowledge can inform retinopathy screening and treatments to preserve vision in this population. To estimate the global prevalence of DR in pediatric T2D. MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Library, the Web of Science, and the gray literature (ie, literature containing information that is not available through traditional publishing and distribution channels) were searched for relevant records from the date of database inception to April 4, 2021, with updated searches conducted on May 17, 2022. Searches were limited to human studies. No language restrictions were applied. Search terms included diabetic retinopathy; diabetes mellitus, type 2; prevalence studies; and child, adolescent, teenage, youth, and pediatric. Three teams, each with 2 reviewers, independently screened for observational studies with 10 or more participants that reported the prevalence of DR. Among 1989 screened articles, 27 studies met the inclusion criteria for the pooled analysis. This systematic review and meta-analysis followed the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines for systematic reviews and meta-analyses. Two independent reviewers performed the risk of bias and level of evidence analyses. The results were pooled using a random-effects model, and heterogeneity was reported using χ2 and I2 statistics. The main outcome was the estimated pooled global prevalence of DR in pediatric T2D. Other outcomes included DR severity and current DR assessment methods. The association of diabetes duration, sex, race, age, and obesity with DR prevalence was also assessed. Among the 27 studies included in the pooled analysis (5924 unique patients; age range at T2D diagnosis, 6.5-21.0 years), the global prevalence of DR in pediatric T2D was 6.99% (95% CI, 3.75%-11.00%; I2 = 95%; 615 patients). Fundoscopy was less sensitive than 7-field stereoscopic fundus photography in detecting retinopathy (0.47% [95% CI, 0%-3.30%; I2 = 0%] vs 13.55% [95% CI, 5.43%-24.29%; I2 = 92%]). The prevalence of DR increased over time and was 1.11% (95% CI, 0.04%-3.06%; I2 = 5%) at less than 2.5 years after T2D diagnosis, 9.04% (95% CI, 2.24%-19.55%; I2 = 88%) at 2.5 to 5.0 years after T2D diagnosis, and 28.14% (95% CI, 12.84%-46.45%; I2 = 96%) at more than 5 years after T2D diagnosis. The prevalence of DR increased with age, and no differences were noted based on sex, race, or obesity. Heterogeneity was high among studies. In this study, DR prevalence in pediatric T2D increased significantly at more than 5 years after diagnosis. These findings suggest that retinal microvasculature is an early target of T2D in children and adolescents, and annual screening with fundus photography beginning at diagnosis offers the best assessment method for early detection of DR in pediatric patients.

SARAspeech—Feasibility of automated assessment of ataxic speech disturbance

Ataxias are a group of movement disorders that are characterized by progressive loss of balance, impaired coordination and speech disturbance, which together lead to markedly reduced quality of life. Speech disturbance is clinically diagnosed, but methods for objective assessment of severity are lacking. Using 71 sets of speech recordings from ataxia patients, we developed an automated classification system. With a tolerance of ±1 point, this classification system correctly predicted experts’ ratings of speech disturbance according to item 4 of the Scale for Assessment and rating of ataxia (SARA) in 80% of cases. We thereby demonstrate feasibility of computer-assisted voice analysis for automated assessment of severity of speech disturbance.