Influencia de la concentración de calcio en el líquido de hemodiálisis sobre el control de la tensión arterial

Background

Hypertension is a highly prevalent disorder among patients undergoing haemodialysis. It contributes to greater cardiovascular risk and must be controlled. However, despite dietary measures, haemodialysis regimen optimisation and pharmacological treatment, some patients in our units continue to maintain high blood pressure levels. The objective of the study is to demonstrate that reducing calcium in dialysis fluid can help treat hypertension patients undergoing haemodialysis.

全身型幼年特发性关节炎合并肺间质病变概述

全身型幼年特发性关节炎是儿童常见的风湿性疾病之一， 肺间质病变是指以肺间质和远端气隙重构为特征， 进而导致异常气体交换的疾病。近年来， 国内外对全身型幼年特发性关节炎合并肺间质病变的报道有增多趋势。该文总结了近年来报道中全身型幼年特发性关节炎儿童合并肺间质病变的情况， 并对儿童肺间质病变的临床表现， 影像学表现， 诊断和治疗进行综述，旨在对该类疾病有更深刻的认识， 有助于肺间质病变的早期诊治。     

接受机械取栓治疗的急性脑梗死患者血栓特征研究进展

急性脑梗死是威胁我国人民健康的重大疾病,其致死率及致残率均较高,造成了沉重的社会负担。及时开通导致梗死的责任血管以恢复脑灌注是治疗该病的关键。机械取栓技术的应用使得患者的血栓组织能够被获取并得到研究。本文介绍了近年来通过机械取栓术获取的血栓的相关研究发现,以纤维蛋白为主的血栓是造成取栓困难的重要组织学原因,影像学方法可以在术前评估血栓特征。这些发现提示临床工作者可以积极开发新型血栓取出装置用于处理难治性血栓,并有必要探索精确便捷的血栓特征影像学评价方法,从而提高机械取栓疗效。     

Prediction of the response to photodynamic therapy in patients with chronic central serous chorioretinopathy based on optical coherence tomography using deep learning

PurposeTo assess the prediction of the response to photodynamic therapy (PDT) in chronic central serous chorioretinopathy (CSCR) based on spectral-domain optical coherence tomography (SD-OCT) images using deep learning (DL).MethodsRetrospective study including 216 eyes of 175 patients with CSCR and persistent subretinal fluid (SRF) who underwent half-fluence PDT. SD-OCT macular examination was performed before (baseline) and 3 months after treatment. Patients were classified into groups by experts based on the response to PDT: Group 1, complete SRF resorption (n = 100); Group 2, partial SRF resorption (n = 66); and Group 3, absence of any SRF resorption (n = 50). This work proposes different computational approaches: 1st approach compares all groups; 2nd compares groups 1 vs. 2 and 3 together; 3rd compares groups 2 vs. 3.ResultsThe mean age was 55.6 ± 10.9 years and 70.3% were males. In the first approach, the algorithm showed a precision of up to 57% to detect the response to treatment in group 1 based on the initial scan, with a mean average accuracy of 0.529 ± 0.035. In the second model, the mean accuracy was higher (0.670 ± 0.046). In the third approach, the algorithm showed a precision of 0.74 ± 0.12 to detect the response to treatment in group 2 (partial SRF resolution) and 0.69 ± 0.15 in group 3 (absence of SRF resolution).ConclusionDespite the high clinical variability in the response of chronic CSCR to PDT, this DL algorithm offers an objective and promising tool to predict the response to PDT treatment in clinical practice.     

COVID-19 vaccine induced interstitial lung disease

A 60-year-old man presented with dyspnea four days after the second dose of the coronavirus disease (COVID-19) vaccine. Imaging revealed extensive ground-glass opacification. Blood tests were notable for elevated KL-6 levels. Bronchoalveolar lavage fluid analysis showed increased lymphocyte-dominant inflammatory cells and decreased CD4/CD8 ratio. These findings were consistent with the diagnosis of drug-induced interstitial lung disease (DIILD). To the best of our knowledge, this has never been reported in previous literature. Treatment with glucocorticoids relieved his symptoms. This paper highlights that although extremely rare, COVID-19 vaccine could cause DIILD, and early diagnosis and treatment are crucial to improve patient outcomes.     

Exclusion of Patients With Brain Metastases in Published Phase III Clinical Trials for Advanced Breast Cancer

Metastatic HER2-positive (HER2+) and triple-negative breast cancer (TNBC) confer a 30% or higher risk of developing brain metastases (BrM), but BrM is typically an exclusion criteria for clinical trials, which limits the generalizability of trial results to these patients. We therefore analysed trends in the enrollment of patients with BrM, as well as the use of outcomes specific to the central nervous system (CNS), in phase III clinical trials evaluating systemic therapy for patients with advanced HER2+ and/or TNBC. Notably, 10 of the 34 trials (29%, 95% confidence interval = 15.1%-47.5%) evaluated CNS-specific outcomes and trials that completely excluded patients with BrM were significantly less likely to meet their primary endpoint (n = 6/17, 35%) than those that permitted conditional enrollment (n = 13/15, 87%) (P = .005), suggesting that enrollment of patients with BrM is not detrimental to trial success.     

Artificial Intelligence–Enabled Electrocardiogram for Atrial Fibrillation Identifies Cognitive Decline Risk and Cerebral Infarcts

ObjectiveTo investigate whether artificial intelligence–enabled electrocardiogram (AI-ECG) assessment of atrial fibrillation (AF) risk predicts cognitive decline and cerebral infarcts.Patients and MethodsThis population-based study included sinus-rhythm ECG participants seen from November 29, 2004 through July 13, 2020, and a subset with brain magnetic resonance imaging (MRI) (October 10, 2011, through November 2, 2017). The AI-ECG score of AF risk calculated for participants was 0-1. To determine the AI-ECG-AF relationship with baseline cognitive dysfunction, we compared linear mixed-effects models with global and domain-specific cognitive z-scores from longitudinal neuropsychological assessments. The AI-ECG-AF score was logit transformed and modeled with cubic splines. For the brain-MRI subset, logistic regression evaluated correlation of the AI-ECG-AF score and the high-threshold, dichotomized AI-ECG-AF score with infarcts.ResultsParticipants (N=3729; median age, 74.1 years) underwent cognitive analysis. Adjusting for age, sex, education, and APOE ?4-carrier status, the AI-ECG-AF score correlated with lower baseline and faster decline in global-cognitive z-scores (P=.009 and P=.01, respectively, non–linear-based spline-models tests) and attention z-scores (P<.001 and P=.01, respectively). Sinus-rhythm-ECG participants (n=1373) underwent MRI. As a continuous measure, the AI-ECG-AF score correlated with infarcts but not after age and sex adjustment (P=.52). For dichotomized analysis, an AI-ECG-AF score greater than 0.5 correlated with infarcts (OR, 4.61; 95% CI, 2.45-8.55; P<.001); even after age and sex adjustment (OR, 2.09; 95% CI, 1.06-4.07; P=.03).ConclusionThe AI-ECG-AF score correlated with worse baseline cognition and gradual global cognition and attention decline. High AF probability by AI-ECG-AF score correlated with MRI cerebral infarcts. However, most infarcts observed in our cohort were subcortical, suggesting that AI-ECG not only predicts AF but also detects other non-AF cardiac disease markers and correlates with small vessel cerebrovascular disease and cognitive decline.