Objective: We aimed to examine biomarkers for screening unhealthy alcohol use in the trauma setting.
Summary And Background Data: Self-report tools are the practice standard for screening unhealthy alcohol use; however, their collection suffers from recall bias and incomplete collection by staff.
Methods: We performed a multi-center prospective clinical study of 251 adult patients who arrived within 24 hours of injury with external validation in another 60 patients. The Alcohol Use Disorders Identification Test served as the reference standard. The following biomarkers were measured: (1) PEth; (2) ethyl glucuronide; (3) ethyl sulfate; (4) gamma-glutamyl-transpeptidase; (5) carbohydrate deficient transferrin; and (6) blood alcohol concentration (BAC). Candidate single biomarkers and multivariable models were compared by considering discrimination (AUROC). The optimal cutpoint for the final model was identified using a criterion for setting the minimum value for specificity at 80% and maximizing sensitivity. Decision curve analysis was applied to compare to existing screening with BAC.
Results: PEth alone had an AUROC of 0.93 [95% confidence interval (CI): 0.92-0.93] in internal validation with an optimal cutpoint of 25 ng/mL. A 4- variable biomarker model and the addition of any single biomarker to PEth did not improve AUROC over PEth alone ( P > 0.05). Decision curve analysis showed better performance of PEth over BAC across most predicted probability thresholds. In external validation, sensitivity and specificity were 76.0% (95% CI: 53.0%-92.0%) and 73.0% (95% CI: 56.0%-86.0%), respectively.Conclusion and Relevance: PEth alone proved to be the single best biomarker for screening of unhealthy alcohol use and performed better than existing screening systems with BAC. PEth may overcome existing screening barriers.
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http://dx.doi.org/10.1097/SLA.0000000000004770 | DOI Listing |
J Med Internet Res
December 2024
Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
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Objective: This systematic review and meta-analysis aimed to pool the results and evaluate the heterogeneity of the current studies in using TML or DL models to diagnose LSS, thereby providing more comprehensive information for further clinical application.
JMIR Biomed Eng
December 2024
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States.
Background: Cell concentration in body fluid is an important factor for clinical diagnosis. The traditional method involves clinicians manually counting cells under microscopes, which is labor-intensive. Automated cell concentration estimation can be achieved using flow cytometers; however, their high cost limits accessibility.
View Article and Find Full Text PDFJMIR Form Res
December 2024
School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, United States.
Background: Human digital twins have the potential to change the practice of personalizing cognitive health diagnosis because these systems can integrate multiple sources of health information and influence into a unified model. Cognitive health is multifaceted, yet researchers and clinical professionals struggle to align diverse sources of information into a single model.
Objective: This study aims to introduce a method called HDTwin, for unifying heterogeneous data using large language models.
Am Psychol
December 2024
The Early Career Awards, given for the first time in 1974, recognize the large number of excellent early career psychologists. Recipients of this award may not have held a doctoral degree for more than nine years. For his pioneering and programmatic research on attentional difficulties in youth, documenting the structure, external validity, and clinical importance of cognitive disengagement syndrome (CDS), Stephen P.
View Article and Find Full Text PDFBackground: Cervical canal stenosis is one of the important pathogenic factors of cervical spondylosis. The accuracy of the Pavlov ratio measurement is crucial for the diagnosis and treatment of cervical spinal stenosis. Manual measurement is influenced by observer variability, accompanied by its inefficiency, which affects clinical evaluation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!