Min-Max, Min-Max-Median, and Min-Max-IQR in Deciding Optimal Diagnostic Thresholds: Performances of a Logistic Regression Approach on Simulated and Real Data

Combining biomarkers and their statistics is used to increase the prediction performance of a diagnosis, but no gold standard method exists. We introduced and evaluated an approach using linear combinations of summary-based statistics tested in logistic regression models with 10-fold repeated cross-validation. We used AUC (area under the ROC- receiver operating characteristic curve), the value of the Youden index, sensitivity (Se), specificity (Sp), diagnostic odds ratio (DOR), Efficiency Index (EI) and Inefficiency Index (InI) as performance metrics on the real-data set. We tested the approaches in multivariate normal distribution simulations with 4, 10, and 100 biomarkers and on real data. The results show that the summary-based models, especially minimum-maximum-median regression model (LR(MMM)) and minimum-maximum-interquartile range model (LR(MMIQR)), have similar performances or slightly better performances than the classical LR model regardless of the imposed mean of biomarkers or covariance matrixes on both simulated and real-data. The differences in AUCs were higher as the number of combined biomarkers increased (LR(MMIQR) model vs. LR model: 0.09 equal or unequal means of four biomarkers, 0.26 equal means, and 0.11 unequal means of 10 biomarkers). In real data, the linear combination of four biomarkers on LR(MMM) and LR(MMIQR) slightly increases the AUCs compared to the LR model. The model's performances were marginally low and without clinical relevance. The linear combination of summary-based statistics, specifically LR(MMM) and LR(MMIQR), exhibits similar performances as the classical LR model when biomarkers are linearly combined to increase diagnostic accuracy. Although the models perform on simulation data-sets, no clinical relevance of the combination is observed in the applied real-data

Preparation and Characterization of Tin Oxide Thin Films

Tin oxide (SnO) thin films were prepared onto glass substrates by thermal evaporation under vacuum. The substrate temperature was kept constant at 300 K during the film growth. The structural studies using transmission electron microscopy (TEM) analysis showed that the SnO thin films have a polycrystalline and tetragonal crystal structure with preferential orientation of (110) planes parallel to the substrate. Optical transmission and reflection spectra, at normal incidence, in the spectral range 300-1100 nm, are investigated. The optical properties of SnO thin films were determined. The optical energy band gap, Eg, has been estimated from the absorption coefficient values using Tauc’s procedure. It is found that the SnO thin films exhibit direct band gap

The Physics of the B Factories

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council