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The scoring of crescents (Cs) was recently added to the Oxford classification for IgA nephropathy (IgAN). Because of the short-term use of the C score in clinical practice, its validity and applicability need to be verified. We, retrospectively, analyzed the clinicopathological data of 144 primary IgAN patients diagnosed at our hospital from March 2017 to March 2019 and with complete ≥6-month follow-up data. We found that the C score was positively correlated with the Lee’s classification in the assessment of renal pathological changes and significantly correlated with increased proteinuria and decreased estimated glomerular filtration rate. Univariate Cox regression analysis showed an association of C formation with IgAN prognosis, and multivariate Cox regression indicated Cs as an independent prognosis factor. The optimal proportion of Cs for prognosis prediction by the receiver operating characteristic curve was 11%. Kaplan–Meier survival curve revealed a significantly decreased renal survival rate in patients with C proportions ≥11%. Further multivariate Cox regression analysis confirmed that the C proportion ≥11% is an independent risk factor for poor prognosis of IgAN patients. Our findings demonstrate that Cs are independently related to the prognosis of patients with IgAN, and the proportion of Cs ≥11% is an independent risk factor for poor outcomes.

Introduction: Arteriovenous fistula (AVF) dysfunction is a prevalent complication among maintenance hemodialysis patients. However, the factors influencing AVF patency remain unclear. To address this, we conducted a study aimed at identifying factors contributing to AVF dysfunction in this patient population. Methods: The study compared clinical data, vascular calcification score, and laboratory data focusing on blood cell composition and coagulation in 100 maintenance hemodialysis patients in whom an AVF had been inserted from January through September of 2022. The patients were divided into a group in which the AVF functioned without issues and a group in which the AVF was dysfunctional, defined as not able to provide a blood flow of greater than 200 mL/min. Findings: Patients in the 2 groups (56 in the dysfunctional AVF group and 44 in the group with satisfactory AVF function) were similar demographically. Compared with the normally functioning AVF group, the AVF dysfunction group exhibited significantly higher Agatston calcium scores (20.5 [1.28, 298] median [Q1, Q3] vs. 1.14 [0.00, 11.6]; p = 0.01), elevated triglyceride levels (1.1 [0.6, 1.2] mmol/L vs. 0.5 [0.3, 0.8]; p < 0.01), increased prothrombin activity (113 ± 22.1% vs. 99.4 ± 23.1; p < 0.01), lower prothrombin time (10.4 [9.8, 10.8] s vs. 11.0 [10.3, 11.5]; p < 0.01), higher red blood cell (RBC) counts (3.5 ± 0.7 · 1012/L vs. 3.0 ± 0.7; p < 0.01), and elevated hemoglobin levels (98.0 ± 21.8 g/L vs. 84.9 ± 24.2; p < 0.01). Higher C‐reactive protein (20.2 [3.3, 20.2] mg/L vs. 17.8 [6.2, 17.8]; p = 0.01) and procalcitonin levels (0.9 [0.4, 0.9] ng/mL vs. 0.5 [0.2, 0.7]; p < 0.01) were also noted. Logistic regression analysis indicated that platelet/lymphocyte ratio, monocyte/lymphocyte ratio, and RBC count were factors associated with AVF dysfunction. Increased monocyte/lymphocyte ratio and RBC count correlated with higher risk, while a higher platelet/lymphocyte ratio was associated with lower risk. Discussion: Arteriovenous fistula dysfunction in maintenance hemodialysis patients is associated with higher proportions of specific hematological parameters, particularly elevated RBC count, and altered platelet/lymphocyte and monocyte/lymphocyte ratios. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to evaluate the characteristics and prognostic factors for coronavirus disease 2019 (COVID-19) patients on maintenance hemodialysis (HD). Methods: All admitted HD patients who were infected with SARS-CoV-2 from December 1, 2022, to January 31, 2023, were included. Patients with pneumonia were further classified into the mild, moderate, severe, and critical illness. Clinical symptoms, laboratory results, radiologic findings, treatment, and clinical outcomes were collected. Independent risk factors for progression to critical disease and in-hospital mortality were determined by the multivariate regression analysis. The receiver operating characteristic analysis with the area under the curve was used to evaluate the predictive performance of developing critical status and in-hospital mortality. Results: A total of 182 COVID-19 patients with HD were included, with an average age of the 61.55 years. Out of the total, 84 (46.1%) patients did not have pneumonia and 98 (53.8%) patients had pneumonia. Among patients with pneumonia, 48 (49.0%) had moderate illness, 26 (26.5%) severe illness, and 24 (24.5%) critical illness, respectively. Elder age [HR (95% CI): 1.07 (1.01–1.13), p <0.01], increased levels of lactate dehydrogenase (LDH) [1.01 (1.003–1.01), p <0.01], and C-reactive protein (CRP) [1.01 (1.00–1.01), p = 0.04] were risk factors for developing critical illness. Elder age [1.11 (1.03–1.19), p = 0.01], increased procalcitonin (PCT) [1.07 (1.02–1.12), p = 0.01], and LDH level [1.004 (1–1.01), p = 0.03] were factors associated with increased risk of in-hospital mortality. Conclusion: Age, CRP, PCT, and LDH can be used to predict negative clinical outcomes for HD patients with COVID-19 pneumonia. [ABSTRACT FROM AUTHOR]

To date, the coronavirus disease 2019 (COVID‐19) has a worldwide distribution. Risk factors for mortality in critically ill patients, especially detailed self‐evaluation indicators and laboratory‐examination indicators, have not been well described. In this paper, a total of 192 critically ill patients (142 were discharged and 50 died in the hospital) with COVID‐19 were included. Self‐evaluation indicators including demographics, baseline characteristics, and symptoms and detailed lab‐examination indicators were extracted. Data were first compared between survivors and nonsurvivors. Multivariate pattern analysis (MVPA) was performed to identify possible risk factors for mortality of COVID‐19 patients. MVPA achieved a relatively high classification accuracy of 93% when using both self‐evaluation indicators and laboratory‐examination indicators. Several self‐evaluation factors related to COVID‐19 were highly associated with mortality, including age, duration (time from illness onset to admission), and the Barthel index (BI) score. When the duration, age increased by 1 day, 1 year, BI decreased by 1 point, the mortality increased by 3.6%, 2.4%, and 0.9% respectively. Laboratory‐examination indicators including C‐reactive protein, white blood cell count, platelet count, fibrin degradation products, oxygenation index, lymphocyte count, and d‐dimer were also risk factors. Among them, duration was the strongest predictor of all‐cause mortality. Several self‐evaluation indicators that can simply be obtained by questionnaires and without clinical examination were the risk factors of all‐cause mortality in critically ill COVID‐19 patients. The prediction model can be used by individuals to improve health awareness, and by clinicians to identify high‐risk individuals. [ABSTRACT FROM AUTHOR]

Abstract Background Anatomy ontologies play an increasingly important role in developing integrated bioinformatics applications. One of the primary relationships between anatomical tissues represented in such ontologies is part-of. As there are a number of ways to divide up the anatomical structure of an organism, each may be represented by more than one valid partonomic (part-of) hierarchy. This raises the issue of how to represent and integrate multiple such hierarchies. Results In this paper we describe a solution that is based on our work on an anatomy ontology for mouse embryo development, which is part of the Edinburgh Mouse Atlas Project (EMAP). The paper describes the basic conceptual aspects of our approach and discusses strengths and limitations of the proposed solution. A prototype was implemented in Prolog for evaluation purposes. Conclusion With the proposed name set approach, rather than having to standardise hierarchies, it is sufficient to agree on a suitable set of basic tissue terms and their meaning in order to facilitate the integration of multiple partonomic hierarchies.

This study documents the seasonal variation of precipitation over the whole Indochina Peninsula (ICP) and associated changes in atmospheric winds and surface heat fluxes and investigates the impact of the ICP precipitation‐related heating and circulation on spring sea surface warming in the South China Sea (SCS). Climatologically, most of the ICP experiences the rainy season from May to October and the period from November to April is the dry season. The summer wet‐winter dry pattern dominates the seasonal rainfall variation in most regions and the maximum rainfall along the west coast occurs during June through August in association with monsoon westerly winds. A pronounced semi‐annual rainfall variation is observed along central Vietnam with a primary peak in October and a secondary peak in May, which is related to northeasterly and southwesterly winds, respectively. Surface heat fluxes change drastically over the ICP in March–April and play an important role in increasing the thermal contrast with the neighbouring waters and heating the atmospheric column, which causes upward motion and precipitation over the ICP. The induced compensatory downward motion over the northern SCS leads to an increase in downward shortwave radiation and a decrease in surface wind speed and turbulent heat fluxes, which contributes to the SCS warming before the summer monsoon onset. Downward shortwave radiation heats the atmospheric column through sensible heat flux, increasing the thermal contrast with the neighbouring waters, causing upward motion and precipitation over the ICP. The upward motion over the ICP in March–April triggers a regional zonal vertical circulation, inducing compensatory downward motion over the SCS. In turn, the downward motion over the SCS leads to an increase in downward shortwave radiation and a decrease in surface wind speed and turbulent heat fluxes, contributing to the SCS warming. [ABSTRACT FROM AUTHOR]