Introduction: Blood glucose (BG) control performed by intensive care unit (ICU) nurses is becoming standard practice for critically ill patients. New (semi-automated) 'BG control' algorithms (or 'insulin titration' algorithms) are under development, but these require stringent validation before they can replace the currently used algorithms. Existing methods for objectively comparing different insulin titration algorithms show weaknesses. In the current study, a new approach for appropriately assessing the adequacy of different algorithms is proposed.
Methods: Two ICU patient populations (with different baseline characteristics) were studied, both treated with a similar 'nurse-driven' insulin titration algorithm targeting BG levels of 80 to 110 mg/dl. A new method for objectively evaluating BG deviations from normoglycemia was founded on a smooth penalty function. Next, the performance of this new evaluation tool was compared with the current standard assessment methods, on an individual as well as a population basis. Finally, the impact of four selected parameters (the average BG sampling frequency, the duration of algorithm application, the severity of disease, and the type of illness) on the performance of an insulin titration algorithm was determined by multiple regression analysis.
Results: The glycemic penalty index (GPI) was proposed as a tool for assessing the overall glycemic control behavior in ICU patients. The GPI of a patient is the average of all penalties that are individually assigned to each measured BG value based on the optimized smooth penalty function. The computation of this index returns a number between 0 (no penalty) and 100 (the highest penalty). For some patients, the assessment of the BG control behavior using the traditional standard evaluation methods was different from the evaluation with GPI. Two parameters were found to have a significant impact on GPI: the BG sampling frequency and the duration of algorithm application. A higher BG sampling frequency and a longer algorithm application duration resulted in an apparently better performance, as indicated by a lower GPI.
Conclusion: The GPI is an alternative method for evaluating the performance of BG control algorithms. The blood glucose sampling frequency and the duration of algorithm application should be similar when comparing algorithms.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374580 | PMC |
http://dx.doi.org/10.1186/cc6800 | DOI Listing |
JAMA Neurol
January 2025
Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore.
Importance: Biomarkers would greatly assist decision-making in the diagnosis, prevention, and treatment of chronic pain.
Objective: To undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of 2 measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).
Design, Setting, And Participants: This cohort study at a single center (Neuroscience Research Australia) recruited participants from November 2020 to October 2022 through notices placed online and at universities across Australia.
ACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFVet Res Commun
January 2025
ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Post Box No. 6450, Yelahanka, Bengaluru, Karnataka, 560119, India.
Sheeppox and Goatpox are highly contagious transboundary viral diseases of sheep and goats caused by Capripoxvirus, respectively. This study describes the development of indirect ELISA and its serodiagnostic potential as an alternative to the gold standard serum neutralization test (SNT). The homologue of vaccinia virus, ORF 117 (A27L) gene of the Romanian Fenner (RF) strain of Sheeppox virus (SPPV) was used for producing the full-length recombinant A27L (rA27L) protein (∼22 kDa) in a prokaryotic expression system.
View Article and Find Full Text PDFJ Epidemiol Glob Health
January 2025
Neurology Department, King Abdulaziz University, Jeddah, Saudi Arabia.
Sleep is influenced by various factors, including social, economic, genetic, and medical factors, and work and study schedules. Medical students are highly susceptible to sleep-related problems. In this study, we aimed to evaluate the sleep patterns and quality of medical students and determine their correlation with academic achievement.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!