This study aimed to obtain data describing the epidemiology and antifungal susceptibility of yeasts isolated from bloodstream infections (BSI) in the Czech Republic (CR). This study presents data from the first year of a national, long-term surveillance program. All microbiologically confirmed candidemia cases in patients hospitalized at 30 Czech centers in 2023 were evaluated. This study assessed BSI incidence per 100,000 inhabitants, species distribution, and antifungal susceptibilities (EUCAST E.Def 7.4 protocol) of strains.aff Whole-genome sequencing was performed on selected isolates with acquired resistance or non-wild-type phenotypes to determine the molecular mechanisms of resistance. In total, 433 isolates from 408 unique BSI episodes in 398 patients were recorded in 2023. Candida albicans was the most frequent species (40.6%), followed by Candida glabrata (24.5%), Candida parapsilosis (14.5%), and Candida tropicalis (5.5%). In pediatric patients, C. albicans (58.8%) was the most common, followed by C. parapsilosis (17.6%). Candida auris BSI was not detected in 2023. The highest rates of acquired fluconazole resistance were detected in C. parapsilosis (16.9%) and C. glabrata (15.4%). Most fluconazole-resistant (FLC-R) C. parapsilosis isolates carried Y132F mutation in ERG11 gene (14/15; 93.3%). One isolate of C. glabrata was resistant to echinocandins (1.3%), but remained susceptible to azoles, mutations in FKS1 (G14S) and FKS2 (S663P, T926P) were identified. This nationwide survey provides the first comprehensive yeast BSI surveillance data from the Czech Republic, which spans the entire country. CR follows trends observed in developed countries, with a decline in C. albicans and a rise in C. glabrata infections. To our knowledge, this is the first report describing FLC-R C. parapsilosis isolates carrying the Y132F ERG11 mutation in CR. These findings highlight several emerging challenges that reflect global trends: a shifting spectrum of Candida species from C. albicans to non-albicans species, and rising levels of acquired azole resistance. Therefore, continuous national monitoring is essential.
Effective inhalation therapy in infants presents significant challenges owing to their distinctive airway anatomy, respiratory patterns, and behavioural factors. This study examined aerosol deposition in a realistic infant airway model under various respiratory conditions, including normal breathing and crying. The airway geometry of a 10-month-old infant was reconstructed from computed tomography scans, and both computational (in silico) and experimental (in vitro) methodologies were employed to analyse aerosol deposition patterns. The findings demonstrated that while a substantial proportion of nebulised aerosol particles (70
Immersive virtual reality (IVR) is an emerging therapeutic modality that engages older adults in psychological therapeutically oriented activities developed to improve their psychological well-being. This systematic review aims to investigate the effects of IVR psychological intervention on psychological symptoms and well-being. A systematic review and meta-analysis was conducted following the Cochrane Handbook for Systematic Reviews of Interventions. Six databases were searched, including Embase, PubMed, Web of Science, Scopus, CINAHL, and PsycINFO, covering the period from 2010 to December 2024. RevMan 5.3 was utilized for meta-analysis, and the Cochrane Risk of Bias tool was employed for quality assessment. Ten randomized controlled trials of 746 older adults were included. The IVR interventions employed reminiscence (40%), garden/forest therapy (40%), cognitive stimulation (10%), and multi-sensory stimulation to reduce psychological symptoms and improve self-perception (10%). Data pooling suggested that IVR interventions have significantly reduced depressive symptoms [n = 5; SMD = -0.83, 95%CI (-1.05, -0.60), I2 = 21%, p < .001]; anxiety [n = 5, SMD = -0.77, 95% CI (-1.32, -0.22), I2 = 70%, p = .006]. Synthesis without meta-analysis (SWiM) was conducted for stress and affect outcomes following SWiM guidance. In all three studies (100%), IVR produced statistically significant reductions in stress versus usual/standard care, and in both studies (100%), it yielded statistically significant improvements in affect-higher positive and lower negative affect-compared with the respective control conditions. IVR-based interventions could be an alternative method for alleviating the psychological symptoms of older adults. Registration: PROSPERO CRD42024575387.
Many patients receiving frontline tyrosine kinase inhibitors (TKIs) for chronic phase chronic myeloid leukemia (CML-CP) experience inadequate disease control and/or adverse events (AEs) that impair quality of life. Treatments offering optimal efficacy, safety, and tolerability will support long-term therapy. In the primary analysis from ASC4FIRST, a phase 3 randomized trial comparing asciminib with investigator-selected TKIs (IS-TKIs) in newly diagnosed CML-CP, asciminib demonstrated superior efficacy vs all IS-TKIs and vs imatinib in the imatinib stratum, meeting both primary objectives. In the secondary analysis (2.2 years median follow-up), major molecular response (MMR) rate at week 96 was 74.1% with asciminib vs 52.0% with IS-TKIs (treatment difference, 22.4%; 95% CI, 13.6%-31.3%; 1-sided P<.001), and 76.2% with asciminib vs 47.1% with imatinib in the imatinib stratum (treatment difference, 29.7%; 95% CI, 17.6%-41.8%; 1-sided P<.001), meeting both key secondary objectives. MMR rate was 72.0% with asciminib vs 56.9% with second-generation (2G) TKIs (treatment difference, 15.1%; 95% CI, 2.3%-28.0%; 1-sided P<.05), suggesting possible clinical benefit although the study was not designed to formally confirm statistical significance for this secondary endpoint. Safety/tolerability remained favorable with asciminib vs IS-TKIs. Dose reductions and interruptions, respectively, occurred with asciminib (18.5% and 46.5%), imatinib (23.2% and 47.5%), and 2G TKIs (54.9% and 63.7%). The hazard ratio for time to discontinuation of treatment due to AEs for asciminib vs 2G TKIs was 0.46 (95% CI, 0.215%-0.997%). With longer follow-up, asciminib continued to demonstrate a favorable benefit-risk profile over IS-TKIs and imatinib, supporting its potential as a treatment option for newly diagnosed CML-CP.
Morphometric measures derived from spinal cord segmentations can serve as diagnostic and prognostic biomarkers in neurological diseases and injuries affecting the spinal cord. For instance, the spinal cord cross-sectional area can be used to monitor cord atrophy in multiple sclerosis and to characterize compression in degenerative cervical myelopathy. While robust, automatic segmentation methods to a wide variety of contrasts and pathologies have been developed over the past few years, whether their predictions are stable as the model is updated using new datasets has not been assessed. This is particularly important for deriving normative values from healthy participants. In this study, we present a spinal cord segmentation model trained on a multisite (n = 75 sites, 1,631 participants) dataset, including 9 different MRI contrasts and several spinal cord pathologies. We also introduce a lifelong learning framework to automatically monitor the morphometric drift as the model is updated using additional datasets. The framework is triggered by an automatic GitHub Actions workflow every time a new model is created, recording the morphometric values derived from the model’s predictions over time. As a real-world application of the proposed framework, we employed the spinal cord segmentation model to update a recently introduced normative database of healthy participants containing commonly used measures of spinal cord morphometry. Results showed that (i) our model performs well compared with its previous versions and existing pathology-specific models on the lumbar spinal cord, images with severe compression, and in the presence of intramedullary lesions and/or atrophy achieving an average Dice score of 0.95 ± 0.03; (ii) the automatic workflow for monitoring morphometric drift provides a quick feedback loop for developing future segmentation models; and (iii) the scaling factor required to update the database of morphometric measures is nearly constant among slices across the given vertebral levels, showing minimum drift between the current and previous versions of the model monitored by the framework. The code and model are open source and accessible via Spinal Cord Toolbox v7.0.
