Objective: To revalidate a local model for prediction of in-hospital mortality after coronary surgery several years after its introduction and the EuroSCORE in a specific area within its original scope. To assess the specific advantages of one type of instrument over the other in a definite context.
Study Design And Setting: Data from consecutive patients undergoing a first isolated coronary artery bypass between November 2001 and November 2003 in five hospitals in Catalonia were prospectively collected.
Results: The study included 1,605 patients. Areas under the receiver-operating characteristics curves were around 0.75 for both models. Calibration was low for both models and the local model significantly overestimated risk. The ordering of operating centers by performance was identical with each strategy but the centers labeled as outliers differed.
Conclusion: (1) Evaluation of performance of individual hospitals was consistent using both systems and almost identical when they were internally recalibrated, (2) The impact of the benchmark population characteristics on model performance may be greater than that of risk factors considered for score calculation, (3) Promoting the use of a widely used instrument as the EuroSCORE might be sufficient for most evaluations. Local scales can be useful to highlight locally relevant features and temporal trends.
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http://dx.doi.org/10.1016/j.jclinepi.2006.10.025 | DOI Listing |
Malar J
January 2025
PATH, 2201 Westlake Ave Ste 200, Seattle, WA, 98121, USA.
Background: The World Health Organization conditionally recommends reactive drug administration to reduce malaria transmission in settings approaching elimination. However, few studies have evaluated the impact of reactive focal drug administration (rFDA) in sub-Saharan Africa, and none have evaluated it under programmatic conditions. In 2016, Senegal's national malaria control programme introduced rFDA, the presumptive treatment of compound members of a person with confirmed malaria, and reactive mass focal drug administration (rMFDA), an expanded effort including neighbouring compounds during an outbreak, in 10 low transmission districts in the north of the country.
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January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
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January 2025
Universidade Federal do Pará, Belém, 66075-110, Brazil.
In Brazil, health policies implemented over the last three decades have enabled rapid testing for HIV to be made available in primary health care services. However, although these policies are national, the implementation of actions is not uniform, as they depend on the local management of local health systems. In this context, the study identified the proportion of women from sexual minorities who had never tested for HIV and the factors associated with access, in a Metropolitan Region of the Brazilian Amazon.
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January 2025
Department of Biomedical Engineering, School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China.
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical cancer patients. Addressing the issue of low accuracy in cervical cell classification, a deep convolutional neural network A2SDNet121 is proposed. A2SDNet121 takes DenseNet121 as the backbone network.
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January 2025
School of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, People's Republic of China.
Accurate and rapid segmentation of key parts of frozen tuna, along with precise pose estimation, is crucial for automated processing. However, challenges such as size differences and indistinct features of tuna parts, as well as the complexity of determining fish poses in multi-fish scenarios, hinder this process. To address these issues, this paper introduces TunaVision, a vision model based on YOLOv8 designed for automated tuna processing.
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