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Introduction: Few studies have described obstetric and critical care outcomes in pregnant women with COVID‐19 needing intensive care unit (ICU) admission. Material and methods: Obstetric and critical care outcomes of COVID‐19 women admitted to eight ICUs from April 1, 2020 to September 15, 2021, in the North West of England were retrospectively analyzed. Women admitted to ICU were assigned to three groups: antepartum women discharged from ICU prior to delivery (antepartum ICU‐discharged group), antepartum women who had expedited delivery (antepartum ICU‐delivered group) and a postpartum group. Our aims were to describe maternal characteristics and assess how delivery influenced the obstetric and critical care outcomes in these women. Results: During the study period, 615 women tested positive for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), of whom 62 (10.1%) needed ICU admission due to symptomatic COVID‐19. Pregnancy loss (3.2%) was recorded in two women. Detailed obstetric and critical outcomes from 60 women are reported. Nine antepartum women (15%) admitted to ICU were discharged and continued their pregnancy, 13 antepartum women (21.7%) had expedited delivery by cesarean birth after ICU admission and 38 (63.3%) women were admitted to ICU during the postpartum period. Antepartum ICU‐discharged women contracted the SARS‐CoV‐2 at an earlier median gestational age (23 weeks; p = 0.0003) and needed ICU admission at an earlier median gestational age (28 weeks, p = 0.03) compared with antepartum ICU‐delivered (28 and 32 weeks) and postpartum women (35.5 and 36 weeks). Antepartum ICU‐discharged women had the lowest rate of mechanical ventilation receipt (11.1%) compared with antepartum ICU‐delivered women (52.3%) and postpartum women (44.3%) but the difference was not statistically significant (p = 0.13). No significant differences were observed in the frequency and severity of critical care complications in the antepartum ICU‐discharged, antepartum‐ICU delivered and postpartum women. Conclusions: Of the women admitted to ICU antepartum, 40% were discharged while remaining pregnant and 60% had expedited delivery. Antepartum women who were discharged from ICU without giving birth may receive lower rates of mechanical ventilation than those who delivered in ICU or admitted postpartum; however, further studies are needed to confirm or refute this association. [ABSTRACT FROM AUTHOR]

Background Plasma volume (PV) calculated from hematocrit and body weight has applications in cardiovascular disease. The current study investigated the validity of the calculated PV for predicting volume overload and its prognostic utility in patients undergoing hemodialysis (HD).Patients and methods Fifty-four HD patients were prospectively enrolled, and their actual PV (aPV) and relative PV status (PVS) were calculated. Bioelectrical impedance analysis (BIA) with assessment of and total body water (TBW), intracellular water (ICW), extracellular water (ECW), and overhydration (OH) and routine blood examinations were performed before dialysis. A second cohort of 164 HD patients was retrospectively enrolled to evaluate the relationship between the calculated PVS and the outcome, with an endpoint of all-cause mortality.Results aPV was significantly associated with TBW, ICW, ECW, OH, and ECW/TBW (all p 8.72% was significantly associated with an increased incidence of all-cause mortality (HR = 2.48, p = 0.0023).Conclusions aPV was most strongly associated with ECW measured using BIA. HD patients with higher time-averaged PVS had a higher rate of all-cause mortality.

PurposeThe aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders.MethodsWe applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR

BackgroundGouty arthritis (GA) is a crystal-related joint disease caused by the deposition of monosodium urate (MSU) crystals, directly associated with hyperuricemia resulting from purine metabolism disorder and/or reduced uric acid excretion. Acute attacks of typical gouty arthritis are generally relieved through the clinical use of NSAIDs, colchicine, or glucocorticoids. However, managing patients with chronic refractory gout poses challenges due to complications such as multiple tophi, gouty nephropathy, diabetes, and gastrointestinal bleeding. While there have been numerous studies on gout in recent years, research specifically regarding chronic refractory gout remains limited. The management of such cases still faces several unresolved issues, including recurrent disease flare-ups and poor patient compliance leading to inadequate drug utilization and increased risk of side effects. In this report, we present a case of successful improvement in chronic refractory gouty arthritis using the biologic agent upadacitinib sustained-release tablets.Case presentationOur case report involves a 53 years-old Asian patient with recurrent gouty arthritis who had a history of over 20 years without regular treatment, presenting with tophi and an increasing number of painful episodes. During hospitalization, various analgesics and anti-inflammatory drugs provided inadequate relief, requiring the use of steroids to alleviate symptoms. However, tapering off steroids proved challenging. We decided to add upadacitinib sustained-release tablets to the treatment regimen, which ultimately improved the patient’s condition. After 6 months of follow-up, the patient has not experienced any further acute pain episodes.ConclusionThis case highlights the potential therapeutic effect of upadacitinib sustained-release tablets during the acute phase of chronic refractory gouty arthritis.

Abstract Background The incidence of kidney disease caused by thyroid cancer is rising worldwide. Observational studies cannot recognize whether thyroid cancer is independently associated with kidney disease. We performed the Mendelian randomization (MR) approach to genetically investigate the causality of thyroid cancer on immunoglobulin A nephropathy (IgAN). Methods and results We explored the causal effect of thyroid cancer on IgAN by MR analysis. Fifty-two genetic loci and single nucleotide polymorphisms were related to thyroid cancer. The primary approach in this MR analysis was the inverse variance weighted (IVW) method, and MR‒Egger was the secondary method. Weighted mode and penalized weighted median were used to analyze the sensitivity. In this study, the random-effect IVW models showed the causal impact of genetically predicted thyroid cancer across the IgAN risk (OR, 1.191; 95% CI, 1.131–1.253, P

Abstract Background Screening for hyperthyroidism using gold-standard diagnostic criteria in the general population is not cost-effective, leading to a relatively high rate of undiagnosed and untreated patients. This study aimed to establish a deep learning-based system to detect hyperthyroidism based on retinal photographs. Methods The multicenter, observational study included retinal photographs taken from participants in two hospitals and 24 health care centers throughout China. We first trained two models to identify hyperthyroidism: in model #1, the non-hyperthyroidism individuals were randomly selected, while in model #2, the non-hyperthyroidism group was matched for age and gender with the hyperthyroidism group. After internal validation, we selected the better model for further evaluation using external validation datasets. Results The study included 22,940 retinal photographs of 11,409 participants for the model development, and 3862 retinal photographs (1870 participants) which were obtained from two hospitals and four medical centers as the external validation datasets. Model #1 achieved a higher area under the receiver operator curve (AUC) than model #2 (0.907, 95% CI: 0.894–0.918 versus 0.850, 95% CI: 0.832–0.866) in the internal validation so that model #1 was used for further evaluation. In external datasets, model #1 reached AUCs ranging from 0.816 (95% CI 0.789–0.846) to 0.849 (95% CI 0.824–0.874) and achieved accuracies between 0.735 (95% CI 0.700–0.773) and 0.796 (95% CI 0.765–0.824). Heatmaps showed a focus of the DL-algorism on large fundus vessels and the optic nerve head. Conclusions Retinal fundus photographs may serve for DL systems for a cost-effective and non-invasive method to detect hyperthyroidism.

Background: The deposition of calcium oxalate (CaOx) and calcium phosphate (CaP) is the most common cause of kidney stone disease (KSD). Whether KSDs caused by CaOx and CaP have common genetic targets or signaling pathways remained unclear.Methods: The present study utilized public data GSE73680 to analyze differentially expressed genes between CaOx or CaP tissues and normal tissues, respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of co-DEGs were performed. The protein-protein interaction (PPI) network was constructed to identify hub genes, and the top hub gene was selected for gene set enrichment analysis (GSEA). Finally, real-time PCR of patients’ urine was performed to validate the bioinformatic results.Results: In total, 155 significantly co-upregulated DEGs and 64 co-downregulated DEGs were obtained from the datasets. The Gene Ontology analysis showed that DEGs were significantly enriched in chemical stimulus in sensory perception, detection of chemical stimulus in sensory perception of smell, and olfactory receptor activity. The KEGG analysis showed that the olfactory transduction pathway was significantly enriched. According to protein-protein interaction, 10 genes were identified as the hub genes, and CCL7 was the top hub gene. The olfactory transduction, maturity-onset diabetes of the young, linoleic acid metabolism, and fat digestion and absorption were significantly enriched in the high-CCL7 subgroup by GSEA. In total, 9 patients who had primarily CaOx mixed with some CaP stones and 9 healthy subjects were enrolled. The RT-PCR results showed that CCL7 level in the stone group was significantly higher than that in the control group (p < 0.05). For the olfactory transduction pathway, the expression of OR10A5, OR9A2, and OR1L3 was significantly upregulated in the stone group compared with the control group (p < 0.05).Conclusion: CCL7 may play a key role in the development of both CaOx and CaP, and this process may depend on olfactory transduction pathway activation.

Summary: Retinopathy of prematurity (ROP) is currently one of the leading causes of infant blindness worldwide. Recently significant progress has been made in deep learning-based computer-aided diagnostic methods. However, deep learning often requires a large amount of annotated data for model optimization, but this requires long hours of effort by experienced doctors in clinical scenarios. In contrast, a large number of unlabeled images are relatively easy to obtain. In this paper, we propose a new semi-supervised learning framework to reduce annotation costs for automatic ROP staging. We design two consistency regularization strategies, prediction consistency loss and semantic structure consistency loss, which can help the model mine useful discriminative information from unlabeled data, thus improving the generalization performance of the classification model. Extensive experiments on a real clinical dataset show that the proposed method promises to greatly reduce the labeling requirements in clinical scenarios while achieving good classification performance.