Acute kidney injury in patients with COVID-19 compared to those with influenza: a systematic review and meta-analysis

BackgroundCOVID-19 and influenza can both lead to acute kidney injury (AKI) as a common complication. However, no meta-analysis has been conducted to directly compare the incidence of AKI between hospitalized patients with COVID-19 and influenza. The objective of our study aims to investigate the incidence and outcomes of AKI among hospitalized patients between these two groups.Materials and methodsA systematic search of PubMed, Embase, and Cochrane databases was conducted from December 2019 to August 2023 to identify studies examining AKI and clinical outcomes among hospitalized patients with COVID-19 and influenza. The primary outcome of interest was the incidence of AKI, while secondary outcomes included in-hospital mortality, recovery from AKI, hospital and ICU stay duration. The quality of evidence was evaluated using Cochrane and GRADE methods.ResultsTwelve retrospective cohort studies, involving 17,618 hospitalized patients with COVID-19 and influenza, were analyzed. COVID-19 patients showed higher AKI incidence (29.37% vs. 20.98%, OR: 1.67, 95% CI 1.56–1.80, p < 0.01, I2 = 92.42%), and in-hospital mortality (30.95% vs. 5.51%, OR: 8.16, 95% CI 6.17–10.80, p < 0.01, I2 = 84.92%) compared to influenza patients with AKI. Recovery from AKI was lower in COVID-19 patients (57.02% vs., 80.23%, OR: 0.33, 95% CI 0.27–0.40, p < 0.01, I2 = 85.17%). COVID-19 patients also had a longer hospital stay (SMD: 0.69, 95% CI 0.65–0.72, p < 0.01, I2 = 98.94%) and longer ICU stay (SMD: 0.61, 95% CI 0.50–0.73, p < 0.01, I2 = 94.80%) than influenza patients. In our study, evidence quality was high (NOS score 7–9), with low certainty for AKI incidence and moderate certainty for recovery form AKI by GRADE assessment.ConclusionCOVID-19 patients had higher risk of developing AKI, experiencing in-hospital mortality, and enduring prolonged hospital/ICU stays in comparison to influenza patients. Additionally, the likelihood of AKI recovery was lower among COVID-19 patients

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Bidirectional association between infectious gastroenteritis and inflammatory bowel disease: a population-based study

Abstract Background Intertwined association between infectious gastroenteritis (IGE) and inflammatory bowel disease (IBD) has not been investigated clearly. We aimed to examine the bidirectional association between IGE and IBD. Methods A bidirectional study using the Taiwan National Health Insurance Research Database was designed. Through a case-control design, we identified 2899 new IBD cases during 2006–2017 and matched to 28,990 non-IBD controls. We used conditional logistic regression model to estimate odds ratios (OR) of IBD for previous IGE in different exposure time-windows within 5-years before IBD diagnosis and Poisson regression model to estimate incidence rate ratio (IRR) of subsequent IGE for IBD group to non-IBD group. Results The mean age at the initial IBD diagnosis was 41 years. More IBD patients (21.49%) than controls (12.60%) had been exposed to IGE during > 6 months to 5 years before IBD diagnosis, the OR of IBD for IGE was 1.89 [95% confidence interval: 1.69–2.11]. Excess OR decreased as IGE exposure time before the index date increased. More IGE episodes were associated with additional increase in IBD risk (OR: 1.64, 2.19, 2.57, 3.50, and 4.57 in patients with 1, 2, 3, 4, and ≥ 5 IGE episodes, respectively). The IRR of having IGE for IBD group to non-IBD group was 2.42 before IBD diagnosis and increased to 5.74 after IBD diagnosis. Conclusions These findings suggested an IGE-IBD bidirectional association. More attention is needed for physicians to develop preventive strategies and be aware of the higher risk of subsequent IGE in IBD patients

Impact of type of dialyzable beta-blockers on subsequent risk of mortality in patients receiving dialysis: A systematic review and meta-analysis.

BackgroundBeta-blockers has been reported to improve all-cause mortality and cardiovascular mortality in patients receiving dialysis, but type of beta-blockers (i.e., high vs. low dialyzable) on patient outcomes remains unknown. This study aimed at assessing the outcomes of patients receiving dialyzable beta-blockers (DBBs) compared to those receiving non-dialyzable beta-blockers (NDBBs).MethodsWe searched the databases including PubMed, Embase, Cochrane, and ClinicalTrials.gov until 28 February 2022 to identify articles investigating the impact of DBBs/NDBBs among patients with renal failure receiving hemodialysis/peritoneal dialysis (HD/PD). The primary outcome was risks of all-cause mortality, while the secondary outcomes included risk of overall major adverse cardiac event (MACE), acute myocardial infarction (AMI) and heart failure (HF). We rated the certainty of evidence (COE) by Cochrane methods and the GRADE approach.ResultsAnalysis of four observational studies including 75,193 individuals undergoing dialysis in hospital and community settings after a follow-up from 180 days to six years showed an overall all-cause mortality rate of 11.56% (DBBs and NDBBs: 12.32% and 10.7%, respectively) without significant differences in risks of mortality between the two groups [random effect, aHR 0.91 (95% CI, 0.81-1.02), p = 0.11], overall MACE [OR 1.03 (95% CI, 0.78-1.38), p = 0.82], and AMI [OR 1.02 (95% CI, 0.94-1.1), p = 0.66]. Nevertheless, the pooled odds ratio of HF among patients receiving DBBs was lower than those receiving NDBB [random effect, OR 0.87 (95% CI, 0.82-0.93), pConclusionsThe use of dialyzable and non-dialyzable beta-blockers had no impact on the risk of all-cause mortality, overall MACE, and AMI among dialysis patients. However, DBBs were associated with significant reduction in risk of HF compared with NDBBs. The limited number of available studies warranted further large-scale clinical investigations to support our findings

Additional file 1 of Bidirectional association between infectious gastroenteritis and inflammatory bowel disease: a population-based study

Additional file 1: Figure S1. Flow chart for study subject selection. Table S1. ICD codes of immune-related diseases

Variants in FAT1 and COL9A1 genes in male population with or without substance use to assess the risk factors for oral malignancy.

A number of genetic variants were suggested to be associated with oral malignancy, few variants can be replicated. The aim of this study was to identify significant variants that enhanced personal risk prediction for oral malignancy. A total of 360 patients diagnosed with oral squamous cell carcinoma, 486 controls and 17 newly diagnosed patients with OPMD including leukoplakia or oral submucous fibrosis were recruited. Fifteen tagSNPs which were derived from somatic mutations were genotyped and examined in associations with the occurrence of oral malignancy. Environmental variables along with the SNPs data were used to developed risk predictive models for oral malignancy occurrence. The stepwise model analysis was conducted to fit the best model in an economically efficient way. Two tagSNPs, rs28647489 in FAT1 gene and rs550675 in COL9A1 gene, were significantly associated with the risk of oral malignancy. The sensitivity and specificity were 85.7% and 85.5%, respectively (area under the receiver operating characteristic curve (AUC) was 0.91) for predicting oral squamous cell carcinoma occurrence with the combined genetic variants, betel-quid, alcohol and age. The AUC for OPMD was only 0.69. The predictive probability of squamous cell carcinoma occurrence for genetic risk score without substance use increased from 10% up to 43%; with substance use increased from 73% up to 92%. Genetic variants with or without substance use may enhance risk prediction for oral malignancy occurrence in male population. The prediction model may be useful as a clinical index for oral malignancy occurrence and its risk assessments

Novel Radiographic Measurements for Operatively Treated Haglund’s Deformity

Background: Haglund’s deformity, which is characterized by a bony prominence of the posterosuperior aspect of the calcaneus, causes posterior heel pain. To date, there is no standard radiographic parameter to diagnose symptomatic Haglund’s deformity. Herein, we proposed novel radiographic measurements to distinguish between patients with and without symptomatic Haglund’s deformity. Methods: We retrospectively evaluated ankle radiographs of 43 patients who underwent surgery for symptomatic Haglund’s deformity (Haglund group) and 41 healthy individuals (control group) free of heel complaints. Fowler–Phillip angle (FPA), Heneghan–Pavlov parallel pitch lines (PPL), Haglund’s deformity height, bump height, and bump-calcaneus ratio were measured and compared between the groups. Furthermore, the reliability and cut-off value of each parameter were validated via ICC and ROC curve analysis, respectively. Results: The bump height (p p < 0.001) showed significant differences between the control and Haglund groups, unlike FPA, PPL, and Haglund’s deformity height. ROC curve analysis revealed that the AUC of bump-calcaneus ratio was larger than that of bump height. The optimal threshold was 4 mm or higher for bump height and 7.5% or higher for bump-calcaneus ratio. The intra- and inter- observer ICCs were, respectively, 0.965 and 0.898 for bump height and 0.930 and 0.889 for bump-calcaneus ratio. Conclusions: This study proposes two novel radiographic parameters to identify operatively treated Haglund’s deformity, namely bump height and bump-calcaneus ratio. They are easy to measure and intuitive. Both of them are effective diagnostic parameters for Haglund’s deformity. Furthermore, bump-calcaneus ratio is more reliable diagnostic parameter than bump height

Machine Learning Algorithm Predicts Mortality Risk in Intensive Care Unit for Patients with Traumatic Brain Injury

Background: Numerous mortality prediction tools are currently available to assist patients with moderate to severe traumatic brain injury (TBI). However, an algorithm that utilizes various machine learning methods and employs diverse combinations of features to identify the most suitable predicting outcomes of brain injury patients in the intensive care unit (ICU) has not yet been well-established. Method: Between January 2016 and December 2021, we retrospectively collected data from the electronic medical records of Chi Mei Medical Center, comprising 2260 TBI patients admitted to the ICU. A total of 42 features were incorporated into the analysis using four different machine learning models, which were then segmented into various feature combinations. The predictive performance was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and validated using the Delong test. Result: The AUC for each model under different feature combinations ranged from 0.877 (logistic regression with 14 features) to 0.921 (random forest with 22 features). The Delong test indicated that the predictive performance of the machine learning models is better than that of traditional tools such as APACHE II and SOFA scores. Conclusion: Our machine learning training demonstrated that the predictive accuracy of the LightGBM is better than that of APACHE II and SOFA scores. These features are readily available on the first day of patient admission to the ICU. By integrating this model into the clinical platform, we can offer clinicians an immediate prognosis for the patient, thereby establishing a bridge for educating and communicating with family members

Artificial intelligence deep learning for 3D IC reliability prediction.

Three-dimensional integrated circuit (3D IC) technologies have been receiving much attention recently due to the near-ending of Moore's law of minimization in 2D IC. However, the reliability of 3D IC, which is greatly influenced by voids and failure in interconnects during the fabrication processes, typically requires slow testing and relies on human's judgement. Thus, the growing demand for 3D IC has generated considerable attention on the importance of reliability analysis and failure prediction. This research conducts 3D X-ray tomographic images combining with AI deep learning based on a convolutional neural network (CNN) for non-destructive analysis of solder interconnects. By training the AI machine using a reliable database of collected images, the AI can quickly detect and predict the interconnect operational faults of solder joints with an accuracy of up to 89.9% based on non-destructive 3D X-ray tomographic images. The important features which determine the "Good" or "Failure" condition for a reflowed microbump, such as area loss percentage at the middle cross-section, are also revealed