Advanced searches left 3/3

Blood Test - Springer Nature

Summarized by Plex Scholar
Last Updated: 10 August 2022

* If you want to update the article please login/register

Cost-Effectiveness Analysis of Stockholm 3 Testing Compared to PSA as the Primary Blood Test in the Prostate Cancer Diagnostic Pathway: A Decision Tree Approach

The aim of this article was to determine the cost effectiveness of using Stockholm 3 testing in comparison to the prostate-specific antigen test in the diagnostic pathway for prostate cancer. Methods We created a decision tree model for PSA and STHLM3. Starting with the initial PSA/STHLM3 test and ending with biopsy and histopathological diagnosis, the study looked at a Danish hospital perspective with a timeframe restricted to the prostate cancer diagnostic pathway. Variations in the cost of STHLM3 had the greatest effect on the incremental cost-effectiveness ratio, according to the determinate sensitivity report. Conclusions STHLM3 testing showed higher incremental efficiency when compared to the PSA method as the initial testing mode in the prostate cancer diagnostic process, but at higher price. The results were specific to the cost of the STHLM3 procedure; therefore, a lower cost of the STHLM3 test would increase the STHLM3 test's cost effectiveness in comparison to PSA tests.

Source link: https://doi.org/10.1007/s40258-022-00741-0


Application of machine learning methods for the prediction of true fasting status in patients performing blood tests

In new studies, fasting blood glucose values extracted from electronic medical records are considered reliable, which may lead to diagnostic bias due to inaccurate interpretation of fasting status. Using the results of ontological FBG with average glucose levels derived from concomitant tested HbA1c based on multi-criteria results, the theoretical true fasting status is determined. The median glucose and HbA1c levels of ontological and theoretical fasting samples in patients without diabetes mellitus were 94. 0 mg/dL and 5. 6 percent, respectively, with 92. 0 mg/dL and 5. 6 percent. In multiple logistic regression studies, the XGBoost demonstrated similar calibration and AUROC of 0. 887 to that of 0. 868, as well as concomitantly serum creatinine and lipid testing, as well as general and lipid testing. The proposed ML algorithm or multiple logistic regression models aids in the verification of the fasting status.

Source link: https://doi.org/10.1038/s41598-022-15161-2

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions