Purpose: To explore the accuracy and cost-effectiveness of three vision screening models among preschool children in rural China.
Methods: Vision screening was carried out among children aged 4-5 years in 65 preschools in two counties in Northwest China, using Crowded Single Lea Symbols to test visual acuity. Children were assigned randomly by school to one of three screening models: screening by teachers (15 schools, 1835 children), local optometrists (30 schools, 1718 children) or volunteers (20 schools, 2183 children). Children identifying ≥2 symbols incorrectly in either eye failed screening. Accuracy of screening was compared with screenings executed by experienced optometrists among 141 children selected randomly from the three screening models. Direct and indirect costs for each model were assessed. Costs to detect a true case failed screening were estimated.
Results: The sensitivity for three models ranged from 76.9% to 87.5%, specificity from 84.9% to 86.7% and standardized positive predictive value from 83.7% to 85.7%. None differed significantly between models. The costs per case detected were $37.53, $59.14 and $52.19 for the teachers, local optometrists and volunteers. In producing the cost estimates for teacher screening and local optometrist screening models, we used a salary payment that was identical for both models (with the salary being equal to that of the optometrist). The teacher screening model was the most cost-effective.
Conclusion: Accuracy of screening by teachers, local optometrists and volunteers was the same in this setting, but the use of teachers was most cost-effective, reducing the cost per case detected by almost 40%.
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http://dx.doi.org/10.1111/aos.13954 | DOI Listing |
Pharmacoeconomics
January 2025
Belgian Health Care Knowledge Centre, Brussels, Belgium.
Background: Forecasting future public pharmaceutical expenditure is a challenge for healthcare payers, particularly owing to the unpredictability of new market introductions and their economic impact. No best-practice forecasting methods have been established so far. The literature distinguishes between the top-down approach, based on historical trends, and the bottom-up approach, using a combination of historical and horizon scanning data.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan, 430030, China.
Purpose: Since fibroblast activation protein (FAP), one predominant biomarker of cancer associated fibroblasts (CAFs), is highly expressed in the tumor stroma of various epidermal-derived cancers, targeting FAP for tumor diagnosis and treatment has shown substantial potentials in both preclinical and clinical studies. However, in preclinical settings, tumor-bearing mice exhibit relatively low absolute FAP expression levels, leading to challenges in acquiring high-quality PET images using radiolabeled FAP ligands (FAPIs) with low molar activity, because of which a saturation effect in imaging is prone to happen. Moreover, how exactly the molar dose of FAPI administered to a mouse influences the targeted PET imaging and radiotherapy remains unclear now.
View Article and Find Full Text PDFForensic Sci Med Pathol
January 2025
Department of Forensic Pathology, School of Forensic Medicine, China Medical University, Shenyang, 110122, P. R. China.
Forensic diagnosis of sudden cardiac death (SCD) is an extremely important part of routine forensic practice. The present study aimed to develop and validate nomograms for predicting the probability of SCD with special regards to ischemic heart disease-induced SCD (IHD-induced SCD) based on multiple autopsy variables. A total of 3322 cases, were enrolled and randomly assigned into a training cohort (n = 2325) and a validation cohort (n = 997), respectively.
View Article and Find Full Text PDFMayo Clin Proc
January 2025
Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN; Department of Molecular Pharmacology and Experimental Therapeutics, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, MN; Division of Heart Rhythm Services, Department of Cardiovascular Medicine, Windland Smith Rice Genetic Heart Rhythm Clinic, Mayo Clinic, Rochester, MN. Electronic address:
Objective: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
Methods: The study cohort included all patients with genetically confirmed LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic's ECG data vault comprising more than 2.5 million patients.
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