Background and Objectives: The key pathogenetic mechanism of glucose metabolism disorders, insulin resistance (IR), can be assessed using the Homeostasis Model Assessment of IR (HOMA-IR). However, its application in clinical practice is limited due to the absence of cut-offs. In this study, we aimed to define the cut-offs for the Czech population. Methods: After undergoing anthropometric and biochemical studies, the sample of 3539 individuals was divided into either nondiabetics, including both subjects with normal glucose tolerance (NGT, n = 1947) and prediabetics (n = 1459), or diabetics (n = 133). The optimal HOMA-IR cut-offs between subgroups were determined to maximize the sum of the sensitivity and specificity for diagnosing type 2 diabetes mellitus (T2DM) or prediabetes. The predictive accuracy was illustrated using receiver operating characteristic (ROC) curves. Logistic regression was performed to assess the association between a target variable (presence/absence of T2DM) depending on the HOMA-IR score as well as on the age and sex. Results: The HOMA-IR cut-off between nondiabetics and diabetics for both sexes together was 3.63, with a sensitivity of 0.56 and a specificity of 0.86. The area under the ROC curve was 0.73 for T2DM diagnosing in both sexes. The HOMA-IR cut-off between the NGT subjects and prediabetics was 1.82, with a sensitivity of 0.60 and a specificity of 0.66. Logistic regression showed that increased HOMA-IR is a risk factor for the presence of T2DM (odds ratio (OR) 1.2, 95% confidence interval (CI) 1.14–1.28, p < 0.0001). The predictive ability of HOMA-IR in diagnosing T2DM is statistically significantly lower in females (OR 0.66, 95% CI 0.44–0.98). The results are valid for middle-aged European adults. Conclusions: The results suggest the existence of HOMA-IR cut-offs signaling established IR. Introduction of the instrument into common clinical practice, together with the known cut-offs, may contribute to preventing T2DM.

High vaccination coverage among healthcare workers (HCWs) is crucial for managing the COVID-19 pandemic. The aim was to determine the demand for vaccination among all employees (n = 4553) of a tertiary care hospital after several weeks of the vaccine’s availability, and to analyze motives for acceptance and reasons for hesitancy through an anonymous online questionnaire. Upon the completion of data collection, the hospital’s vaccination coverage was at 69.8%. A total of 3550 completed questionnaires were obtained (2657 from vaccinated, 893 from unvaccinated employees). Significant predictors of vaccine acceptance were: age (odds ratio (OR) 1.01, 95% confidence interval (CI) 1.01–1.02), sex (OR (females) 0.58, 95% CI 0.45–0.75), job type (OR (non-physician HCWs) 0.54, 95% CI 0.41–0.72; OR (non-HCWs) 0.51, 95% CI 0.37–0.71), fear of COVID-19 (OR 1.4, 95% CI 1.34–1.46), history of COVID-19 (OR 0.41, 95% CI 0.34–0.49) and of influenza vaccination (OR 2.74, 95% CI 2.12–3.57). The most frequent motive for acceptance was the effort to protect family members (84%), while concerns about vaccine safety and side effects (49.4%), followed by distrust in the vaccine’s efficacy (41.1%) were the top reasons for hesitancy. To increase vaccination coverage among HCWs, it is necessary to raise awareness of vaccine safety and efficacy.

BACKGROUND: Catheter ablation for atrial fibrillation (AF) is one of the most common cardiovascular procedures being performed worldwide. Despite the large body of evidence of its effectiveness, with a single exception, prior ablation studies were largely unblinded trials. Accordingly, residual concerns remained about placebo effects, both for AF recurrence and, in particular, on subjective outcomes such as quality of life or anxiety. Here, we compared pulsed field ablation (PFA) with a sham procedure to treat patients with symptomatic AF. METHODS: This prospective, sham-controlled, single-blind, randomized clinical trial with blinded end-point assessment enrolled patients with AF that was highly symptomatic (Atrial Fibrillation Effect on Quality-of-Life score 0.99). For the second co–primary end point, Atrial Fibrillation Effect on Quality-of-Life scores showed greater improvement from baseline with PFA than sham (improved by 43.9+18.1 points versus 11.3+27.9 points; posterior median difference, 32.6 [95% bayesian credible interval, 20.2–44.9]; posterior probability of superiority >0.99). AF burden at 6 months was significantly lower in the PFA than the sham group (0 [0–0] versus 0.43 [0.04–3.47]; between group median difference, −0.39 [95% credible interval, −2.5 to −0.1], posterior probability of superiority >0.99). The Hospital Anxiety and Depression Scale score changed by −4 points (−7.8 to −2.0) with PFA and by −0.5 (−4.5 to 1.0) with sham (group median difference, −3.5 [95% credible interval, −6.0 to −1.0]; posterior probability of superiority >0.99). CONCLUSIONS: In patients with AF, PFA was superior to sham in reducing arrhythmia recurrences and burden and improving quality of life and AF-associated psychological distress. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05717725.

This work presents a comparative analysis of various machine learning (ML) methods for predicting item difficulty in English reading comprehension tests using text features extracted from item wordings. A wide range of ML algorithms are employed within both the supervised regression and the classification tasks, including regularization methods, support vector machines, trees, random forests, back-propagation neural networks, and Naïve Bayes; moreover, the ML algorithms are compared to the performance of domain experts. Using f-fold cross-validation and considering the root mean square error (RMSE) as the performance metric, elastic net outperformed other approaches in a continuous item difficulty prediction. Within classifiers, random forests returned the highest extended predictive accuracy. We demonstrate that the ML algorithms implementing item text features can compete with predictions made by domain experts, and we suggest that they should be used to inform and improve these predictions, especially when item pre-testing is limited or unavailable. Future research is needed to study the performance of the ML algorithms using item text features on different item types and respondent populations.

Aqueous solutions of some polymers exhibit a lower critical solution temperature (LCST); that is, they form phase‐separated aggregates when heated above a threshold temperature. Such polymers found many promising (bio)medical applications, including in situ thermogelling with controlled drug release, polymer‐supported radiotherapy (brachytherapy), immunotherapy, and wound dressing, among others. Yet, despite the extensive research on medicinal applications of thermoresponsive polymers, their biodistribution and fate after administration remained unknown. Thus, herein, they studied the pharmacokinetics of four different thermoresponsive polyacrylamides after intramuscular administration in mice. In vivo, these thermoresponsive polymers formed depots that subsequently dissolved with a two‐phase kinetics (depot maturation, slow redissolution) with half‐lives 2 weeks to 5 months, as depot vitrification prolonged their half‐lives. Additionally, the decrease of T_CP of a polymer solution increased the density of the intramuscular depot. Moreover, they detected secondary polymer depots in the kidneys and liver; these secondary depots also followed two‐phase kinetics (depot maturation and slow dissolution), with half‐lives 8 to 38 days (kidneys) and 15 to 22 days (liver). Overall, these findings may be used to tailor the properties of thermoresponsive polymers to meet the demands of their medicinal applications. Their methods may become a benchmark for future studies of polymer biodistribution.

BackgroundCOVID-19 survivors may experience long-term health problems, including deterioration of cardiorespiratory fitness (CRF), as demonstrated by several cross-sectional studies that compared the results of cardiopulmonary exercise tests (CPET) performed only after COVID-19 with predicted values. This study aimed to analyze a change in CRF between repeated CPETs in response to suffered COVID-19.MethodsA total of 127 healthcare workers (HCWs; mean age 55.7 years) underwent two CPETs with a mean interval of 762 days. Forty HCWs suffered from COVID-19 (mild to moderate severity) in the interim (321 days before the second CPET), and 87 HCWs formed a control group. Mixed-effects regression with multiple adjustment and interaction terms was used for two response variables - maximum oxygen uptake (VO2 max) and power output.ResultsBetween both CPETs, mean VO2 max decreased statistically significantly in the COVID-19 subgroup (by 3.12 mL/kg/min, p = .034) and insignificantly in controls (by 0.56 mL/kg/min, p = .412). The proportion of HCWs achieving predicted VO2 max decreased from 75.9% to 59.5% (p = .161) in COVID-19 survivors, while it increased from 73.8% to 81% (p = .274) in controls. COVID-19 (& beta; = -0.66, p = .014) and body mass index (& beta; = -0.49, p < .001) were independent negative predictors of VO2 max change. COVID-19 was not associated with a change in power output.ConclusionsOn the basis of repeated CPETs, COVID-19 significantly, albeit rather modestly, reduces CRF almost one year after infection. The reduction persists even after the acute phase with mild or moderate severity.