Bmc Med
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Adult-onset Still's disease (AOSD) is a systemic autoinflammatory disease characterized by innate immune system activation, with a high risk for macrophage activation syndrome (MAS). MAS development is associated with monocyte/macrophage activation and cytokine storm. Monocytes consist of three different subsets, classical monocytes (CMs, CD14brightCD16 -), intermediate monocytes (IMs, CD14brightCD16 +), and non-classical monocytes (NCMs, CD14dimCD16 +), each has distinct roles in inflammatory regulation. However, the frequencies and regulatory mechanism of monocyte subsets in AOSD patients have not been identified. ⋯ Our results demonstrated that the proportions of IMs were elevated in AOSD and associated with MAS. The DNA component in NETs from AOSD plays an important role in the formation of IMs, shedding new light for the therapeutic target.
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Meta Analysis
Self-collection of samples for group B streptococcus testing during pregnancy: a systematic review and meta-analysis.
Sample self-collection for reproductive tract infection diagnosis has been found to offer greater convenience, privacy, autonomy, and expanded access to testing in non-pregnant adults. This review aimed to determine whether sample self-collection is as accurate as provider-collection for detection of group B streptococcus colonisation in pregnancy and whether a strategy of self-collection compared to provider-collection might improve maternal and neonatal health outcomes. ⋯ Self-collected samples for group B streptococcus detection in pregnancy had high specificity compared to provider-collection, but lower sensitivity, particularly for included trials. Studies investigating the effect of self-collection on health outcomes, and further higher quality trials comparing accuracy of self-collection to provider-collection, are required.
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Each year, thousands of clinical prediction models are developed to make predictions (e.g. estimated risk) to inform individual diagnosis and prognosis in healthcare. However, most are not reliable for use in clinical practice. ⋯ Instability is concerning as an individual's predicted value is used to guide their counselling, resource prioritisation, and clinical decision making. If different samples lead to different models with very different predictions for the same individual, then this should cast doubt into using a particular model for that individual. Therefore, visualising, quantifying and reporting the instability in individual-level predictions is essential when proposing a new model.
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More than half of patients with tuberous sclerosis complex (TSC) suffer from drug-resistant epilepsy (DRE), and resection surgery is the most effective way to control intractable epilepsy. Precise preoperative localization of epileptogenic tubers among all cortical tubers determines the surgical outcomes and patient prognosis. Models for preoperatively predicting epileptogenic tubers using 18F-FDG PET images are still lacking, however. We developed noninvasive predictive models for clinicians to predict the epileptogenic tubers and the outcome (seizure freedom or no seizure freedom) of cortical tubers based on 18F-FDG PET images. ⋯ The 18F-FDG PET image-based LR model can be used to noninvasively identify epileptogenic tubers and predict the long-term outcomes of cortical tubers in TSC patients.
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Observational Study
Prediction of acute kidney injury incidence following acute type A aortic dissection surgery with novel biomarkers: a prospective observational study.
Acute kidney injury (AKI) is a prevalent complication following acute type A aortic dissection (ATAAD) surgery and is closely associated with unfavorable prognostic outcomes. Hence, the development of a robust and efficient diagnostic approach to identify high-risk patients is of paramount importance. ⋯ Our study underscored the augmentation of plasma S100A8/A9, PTX3, and CHI3L1 levels immediately post-surgery in patients developing ASA-AKI. The incorporation of these three biomarkers, in conjunction with the Cleveland Clinic score and NGAL, into a nomogram demonstrated commendable predictive efficacy. This presents a practical tool for identifying patients at an elevated risk of AKI following ATAAD surgery.