The aim of the present study was to validate, and if necessary update, a predictive model previously developed using a classification and regression tree (CART) algorithm for predicting successful extubation (ES) using a new cohort. This prospective cohort study enrolled adults admitted to 10 intensive care units, who had successfully passed a spontaneous breathing trial (SBT) and were considered ready for extubation. After extubation, the patients were followed up for 48 h. The primary outcome measure was ES, defined as the ability to maintain spontaneous unassisted breathing for >48 h after extubation. The 3-factor CART model was applied to patients in this cohort. The predicted probability of ES for each patient in this validation cohort was calculated based on the original CART model using the Laplace correction method. The performance was assessed by discrimination and calibration. A decision curve analysis was used assess the clinical net benefit (NB). Extubation failure (EF) occurred in 90/530 patients (17%). Among the 90 patients, 72 (13.6%) were reintubated, while 18 patients remained on rescue noninvasive ventilation within 48 h after extubation. The original CART model showed high discrimination but only moderate calibration with predicted probabilities that were systematically lower than expected. The original CART model was updated, and the updated model preserved excellent discrimination (area under the receiver operating characteristic curve, 0.91; 95% confidence interval, 0.87 to 0.93), but exhibited near-perfect calibration (calibration slope, 1; intercept, 0). Between threshold probabilities of 50 and 80%, the NB of using this updated model is significantly improved compared with the current strategy. The updated CART model may be used to estimate the predicted probability of ES after a successful SBT for individual patients. Applying this model appears to produce a substantial clinical consequence with regard to potential reduction in unexpected EFs.
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http://dx.doi.org/10.3892/etm.2015.2678 | DOI Listing |
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Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, West China Second Hospital, State Key Laboratory of Biotherapy, and Department of Neurosurgery, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China.
Genome-wide functional genetic screening has been widely used in the biomedicine field, which makes it possible to find a needle in a haystack at the genetic level. In cancer research, gene mutations are closely related to tumor development, metastasis, and recurrence, and the use of state-of-the-art powerful screening technologies, such as clustered regularly interspaced short palindromic repeat (CRISPR), to search for the most critical genes or coding products provides us with a new possibility to further refine the cancer mapping and provide new possibilities for the treatment of cancer patients. The use of CRISPR screening for the most critical genes or coding products has further refined the cancer atlas and provided new possibilities for the treatment of cancer patients.
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Université de Franche-Comté, EFS, INSERM, UMR RIGHT, F-, 25000, Besançon, France.
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View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
View Article and Find Full Text PDFInt Immunopharmacol
January 2025
Department of Rheumatology and Clinical Immunology, Department of Health Management, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, State Key Laboratory of Complex Severe and Rare Diseases, China; Department of Health Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China. Electronic address:
Int J Mol Sci
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MRL, Merck & Co., Inc., Rahway, NJ 07065, USA.
Despite the success of combination antiretroviral therapy (cART) to suppress HIV replication, HIV persists in a long-lived reservoir that can give rise to rebounding viremia upon cART cessation. The translationally active reservoir consists of HIV-infected cells that continue to produce viral proteins even in the presence of cART. These active reservoir cells are implicated in the resultant viremia upon cART cessation and likely contribute to chronic immune activation in people living with HIV (PLWH) on cART.
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