Long-Term Implications of Atrial Fibrillation in Patients With Degenerative Mitral Regurgitation

Background

Scientific guidelines consider atrial fibrillation (AF) complicating degenerative mitral regurgitation (DMR) a debated indication for surgery.

常规心电图与动态心电图诊断心律失常112例分析

心律失常是心血管系统疾病中经常出现的症状,心律失常由起源部位、心搏频率、心脏冲动传导等异常因素而引发,早发现、早确诊、早治疗对患者的健康具有重要意义。心律失常与高血压病、糖尿病、心血管病、电解质紊乱等密切相关。不同的人群、不同时期,心律失常表现也不一致,出现的频次也有不同的表现。现对本院作常规心电图、动态心电图(Holter)112例患者的结果比较进行分析。     

Multidimensional Ultrasound Doppler Signal Analysis for Fetal Activity Monitoring

Fetal activity parameters such as movements, heart rate and the related parameters are essential indicators of fetal wellbeing, and no device provides simultaneous access to and sufficient estimation of all of these parameters to evaluate fetal health. This work was aimed at collecting these parameters to automatically separate healthy from compromised fetuses. To achieve this goal, we first developed a multi-sensor–multi-gate Doppler system. Then we recorded multidimensional Doppler signals and estimated the fetal activity parameters via dedicated signal processing techniques. Finally, we combined these parameters into four sets of parameters (or four hyper-parameters) to determine the set of parameters that is able to separate healthy from other fetuses. To validate our system, a data set consisting of two groups of fetal signals (normal and compromised) was established and provided by physicians. From the estimated parameters, an instantaneous Manning-like score, referred to as the ultrasonic score, was calculated and was used together with movements, heart rate and the associated parameters in a classification process employing the support vector machine method. We investigated the influence of the sets of parameters and evaluated the performance of the support vector machine using the computation of sensibility, specificity, percentage of support vectors and total classification error. The sensitivity of the four sets ranged from 79% to 100%. Specificity was 100% for all sets. The total classification error ranged from 0% to 20%. The percentage of support vectors ranged from 33% to 49%. Overall, the best results were obtained with the set of parameters consisting of fetal movement, short-term variability, long-term variability, deceleration and ultrasound score. The sensitivity, specificity, percentage of support vectors and total classification error of this set were respectively 100%, 100%, 35% and 0%. This indicated our ability to separate the data into two sets (normal fetuses and pathologic fetuses), and the results highlight the excellent match with the clinical classification performed by the physicians. This work indicates the feasibility of detecting compromised fetuses and also represents an interesting method of close fetal monitoring during the entire pregnancy.     

Prevalence of shift work disorder among hospital personnel: A cross‐sectional study using objective working hour data

The prevalence of shift work disorder (SWD) has been studied using self‐reported data and the International Classification of Sleep Disorders, Second Edition (ICSD‐2) criteria. We examined the prevalence in relation to ICSD‐2 and ICSD‐3 criteria, work schedules and the number of non‐day shifts (work outside 06:00–18:00 hours) using objective working‐hours data. Secondly, we explored a minimum cut‐off for the occurrence of SWD symptoms. Hospital shift workers without (n = 1,813) and with night shifts (n = 2,917) and permanent night workers (n = 84) answered a survey (response rate 69%) on SWD and fatigue on days off. The prevalence of SWD was calculated for groups with ≥1, ≥3, ≥5 and ≥7 monthly non‐day shifts utilizing the working hours registry. ICSD‐3‐based SWD prevalence was 2.5%–3.7% (shift workers without nights), 2.6%–9.5% (shift workers with nights) and 6.0% (permanent night workers), depending on the cut‐off of non‐day shifts (≥7–1/month, respectively). The ICSD‐2‐based prevalence was higher: 7.1%–9.2%, 5.6%–33.5% and 16.7%, respectively. The prevalence was significantly higher among shift workers with than those without nights (p‐values <.001) when using the cut‐offs of ≥1–3 non‐day shifts. Shift workers with nights who had ≥3 days with ICSD‐3‐based SWD symptoms/month more commonly had fatigue on days off (49.3%) than those below the cut‐off (35.8%, p < .05). The ICSD‐3 criteria provided lower estimates for SWD prevalence than ISCD‐2 criteria, similarly to exclusion of employees with the fewest non‐day shifts. The results suggest that a plausible cut‐off for days with ICSD‐3‐based SWD symptoms is ≥3/month, resulting in 3%–6% prevalence of SWD.