Aniridia is an autosomal dominant eye anomaly caused by haploinsufficiency of the PAX6 gene, of which abnormalities include base alterations, position effects and deletions. When deletion involves its adjacent genes, i.e., those in the PAX6-WT1 critical region (WTCR), patients are predisposed to Wilms tumor. We studied 18 patients with aniridia, five of whom had chromosome deletion involving 11p13, two a translocation t(10;11)(p13;p13) or a der(14;21)(q10;q10)mat, and 11 had a normal karyotype. Fluorescence in situ hybridization (FISH) using four P1-derived artificial chromosome (PAC) clones located at WTCR was carried out in the 18 patients to identify a deletion extent. Of the 18 patients, eight had a deletion of WTCR: four had microscopic deletion and four a deletion of WTCR. Deleted region in one patient with a microscopic deletion was distal to the critical region. Four of the eight patients with a deletion encompassing WTCR developed Wilms tumor, and the other four did not (two were too young to be evaluated for the tumor development). The data in the present study, together with four similar previous works, indicate that of a total of 102 aniridia patients, 29 had a deletion spanning WTCR. Wilms tumor developed in 13 (45%) of the 29 patients, whereas patients without deletion in this region did not develop the tumor. In other words, aniridia patients with WT1 deletion run a high risk of developing Wilms tumor, and those without the deletion do not.
<b><i>Introduction:</i></b> In dialysis patients, cardiovascular disease (CVD) and infectious disease contribute to poor clinical outcomes. We investigated if a higher monocyte/lymphocyte ratio (MLR) is associated with an increased risk of CVD events and infectious disease hospitalizations in incident dialysis patients. <b><i>Methods:</i></b> In an ongoing observational prospective cohort study, 132 Japanese dialysis patients (age 58.7 ± 11.7 years; 70% men) starting dialysis therapy were enrolled and followed up for a median of 48.7 months. Laboratory biomarkers, including white blood cell count and its differential count, were determined at baseline. Event-free time and relative risks (RRs) were calculated using the Kaplan-Meier curves and Cox models, respectively. <b><i>Results:</i></b> When divided into 2 groups according to median MLR (0.35 [range, 0.27–0.46]), the periods without CVD events were significantly shorter in the high MLR group than in the low MLR group (log-rank test = 5.60, <i>p</i> = 0.018). The RR of CVD events, after adjusting for age, sex, and diabetes, was 2.43 (1.22–4.84) in the high MLR group compared to the low MLR group. The periods without infections requiring hospitalization were also shorter (log-rank test = 4.16, <i>p</i> = 0.041). The RR of infections requiring hospitalization was 1.98 (1.02–3.83) after the same adjustments. The number of CVD events was higher in the high MLR group (18.6 events per 100 person-years at risk [pyr]) than the low MLR group (11.1 events per 100 pyr). The duration of infectious disease hospitalization was longer in the high MLR group (6.3 days per pyr) than in the low MLR group (2.8 days per pyr). <b><i>Conclusion:</i></b> A higher MLR is associated with increased risks of both CVD events and infectious disease hospitalization in dialysis patients.
BackgroundWhen facing unprecedented emergencies such as the coronavirus disease 2019 (COVID-19) pandemic, a predictive artificial intelligence (AI) model with real-time customized designs can be helpful for clinical decision-making support in constantly changing environments. We created models and compared the performance of AI in collaboration with a clinician and that of AI alone to predict the need for supplemental oxygen based on local, non-image data of patients with COVID-19.Materials and methodsWe enrolled 30 patients with COVID-19 who were aged >60 years on admission and not treated with oxygen therapy between December 1, 2020 and January 4, 2021 in this 50-bed, single-center retrospective cohort study. The outcome was requirement for oxygen after admission.ResultsThe model performance to predict the need for oxygen by AI in collaboration with a clinician was better than that by AI alone. Sodium chloride difference >33.5 emerged as a novel indicator to predict the need for oxygen in patients with COVID-19. To prevent severe COVID-19 in older patients, dehydration compensation may be considered in pre-hospitalization care.ConclusionIn clinical practice, our approach enables the building of a better predictive model with prompt clinician feedback even in new scenarios. These can be applied not only to current and future pandemic situations but also to other diseases within the healthcare system.
Fabry disease is a rare X-linked lysosomal storage disorder caused by mutations in the alpha-galactosidase A (GLA) gene that results in deficiency of the enzyme GLA and leads to the accumulation of globotriaosylceramide (GL-3) in cells. The accumulation of GL-3 may lead to life-threatening complications. Significant advances in genetic sequencing technology have led to a better understanding of genotype-phenotype interactions in Fabry disease. Fabry disease with an R112H mutation is known as the non-classic type. However, the long-term clinical course of the disease remains unknown. We herein report a patient with a 30-year natural history of non-classic Fabry disease with an R112H mutation.
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