Sleep apnea syndrome (SAS) is a kind of harmful systemic sleep disorder with high incidence, and the pathological mechanism of it is complicated and the diagnosis and treatment are difficult. Mining the characteristic information of SAS from the single or small physiological signal is a hot topic in the research of sleep disorders in recent years. In our study shown in this paper, the detrended fluctuation analysis (DFA) was used to analyze sleep electroencephalogram (EEG) of SAS patients and normal healthy persons based on the non-stationary and nonlinear characteristics. It was found that in both groups, the scaling exponents increased gradually with the deepening of sleep, and in the rapid eye movement (REM) stage, the scaling exponents decreased. The scaling exponents of SAS group were significantly higher than those of the healthy group. The performance of SAS diagnosis based on scaling exponents was evaluated with receiver operator characteristic (ROC) curve. The optimal threshold value 0.81 for the SAS and normal control were obtained, corresponding to the sensitivity 94.4%, specificity 99.2%, and area under curve (AUC) was 0.994. The results show that DFA scaling exponents have a good discrimination power and accuracy for the SAS, which provide a new theoretical basis for SAS diagnosis.
The research of sleep staging is not only the basis of diagnosing sleep related diseases, but also the precondition of evaluating sleep quality, and has important clinical significance. In recent years, the research of automatic sleep staging based on computer has become a hotspot and made some achievements. Feature extraction and feature classification are two key technologies in automatic sleep staging system. In order to achieve effective automatic sleep staging, we proposed a new automatic sleep staging method which combines the energy features and least squares support vector machines (LS-SVM). Firstly, we used FIR band-pass filter to extract the energy features of Pz-Oz channel sleep electroencephalogram (EEG) signals, and compared them with those from wavelet packet transform method. Then we designed an LS-SVM classifier to realize the automatic sleep stage classification. The research showed that FIR band-pass filter (with the Kaiser window) performed better than wavelet packet transform (WPT) for energy feature extraction just in terms of the data from the Sleep-EDF Database and the LS-SVM classifier (with the RBF Kernel function) designed was good, and the automatic sleep staging method proposed in this paper was better than many similar methods from other studies with an average accuracy of 88.89% and had a very prosperous application future.
The research of sleep staging is not only a basis of diagnosing sleep related diseases but also the precondition of evaluating sleep quality, and has important clinical significance. In recent years, the research of automatic sleep staging based on computer has become a hot spot and got some achievements. The basic knowledge of sleep staging and electroencephalogram (EEG) is introduced in this paper. Then, feature extraction and pattern recognition, two key technologies for automatic sleep staging, are discussed in detail. Wavelet transform and Hilbert-Huang transform, two methods for feature extraction, are compared. Artificial neural network and support vector machine (SVM), two methods for pattern recognition are discussed. In the end, the research status of this field is summarized, and development trends of next phase are pointed out.
ObjectiveTo investigate the situation of off-label drug use in dose (OLDUD) of ambroxol hydrochloride injection (AHI) in perioperative period among patients for stanford type A aortic dissection in Guangdong General Hospital, so as to provide references for the rational application of AHI in clinical practice. MethodsAll medical orders of AHI for patients had aortic arch replacement for Stanford type A aortic dissection in Guangdong General Hospital between January 2005 and December 2014 were included. The patients were divided into a mild OLDUD ( < 450 mg) group, a moderate OLDUD (450 mg≤OLDUD < 900 mg) group, and a high OLDUD (≥900 mg)group. The preoperative and postoperative features, incidence of PPCs, mortality, incidence of reintubation, time of mechanical ventilation, time stay in ICU, time stay in hospital and the overall costs among three groups were compared by SPSS 22.0 software. Resultsa) A total of 549 patients were included. The incidence of OLDUD was 99.82%. The most common PMDDs were 450 mg (n=358) and 900 mg (n=88). b) The three groups were well matched for perioperative and operative variables. c) The incidence of preoperative drug use was 8.6%. The incidences (5.5% vs. 7.7% vs. 15.7%, P=0.022) and maximum doses (180 mg vs. 300 mg vs. 450 mg, P=0.014) of preoperative drug use were statistically different in mild OLDUD, moderate OLDUD and high OLDUD groups. The days of preoperative drug use were not different (3 d vs. 2.5 d vs. 2 d, P=0.307). The days of postoperative drug use (9.5 d vs. 13 d vs. 19 d, P < 0.001) and postoperative drug use in maximum doses (7 d vs. 8 d vs. 7 d, P=0.005) were different. d) The incidence of PPCs was 100%, and the mortality (8.2% vs. 6.6% vs. 9.0%, P=0.696) was not statistically different among mild OLDUD, moderate OLDUD and high OLDUD groups. However the incidence of reintubation (14.3% vs. 13.8% vs. 27%, P=0.009), time of mechanical ventilation (37 h vs. 50 h vs. 114 h, P < 0.001), time stay in ICU (138 h vs. 178.5 h vs. 316 h, P < 0.001), time stay in hospital (25 d vs. 27 d vs. 34 d, P=0.001) and the overall costs (¥ 0.17 million vs. ¥ 0.19 million vs. ¥ 0.25 million, P < 0.001) were different among three groups. Moreover, they were all increasing along with the dose of AHI. ConclusionAHI cannot improve the prognosis of patients having aortic arch replacement for Stanford Type A Aortic Dissection in a dose-dependent manner. Further well-designed prospective studies should be conducted to verification or falsification.
ObjectiveTo retrospectively analyze off-label drug use (OLDU) situation of ambroxol hydrochloride injection (AHI) among inpatients in the Guangdong General Hospital in 2012, so as to provide references for AHI OLDU. MethodsAll medical orders of AHI for inpatients in the Guangdong General Hospital in 2012 were included, and OLDU was judged according to drug labels. We summarized situation of drug use in all departments, analyzed OLDU incidence in administration path and in dose, calculated prescribed daily dose (PDD) and utilization index (DUI) in each department to evaluate the degree of OLDU in dose. Resultsa) A total of inpatients 138 227 patient-days who used AHI were included. OLDU occurred in all departments in this hospital and the total OLDU incidence was 67.06%. b) OLDU in dose occurred in 71.43% of the departments (25/35) with an incidence of 29.53%; the top 4 departments were cardiac surgery intensive care unit department (CICU) (97.74%), cardiac surgery department (97.51%), pediatric cardiac surgery department (72.30%) and pediatric intensive care unit department (PICU) (70.28%) in order. c) The PDDs in CICU department, cardiac surgery department, PICU departments, pediatric cardiac surgery department, oncological surgery ward, neurosurgery ward and intensive care unit (ICU) were higher than the defined daily dose (DDD), of which, the DUI/cDUI in CICU, cardiac surgery department, PICU and pediatric cardiac surgery department were 1 to 3 times higher than normal level. d) No relevant adverse drug reaction/adverse event (ADR/AE) reports were received in this hospital in 2012. ConclusionAHI is widely used in the Guangdong General Hospital, and AHI OLDU is commonly-seen. Further studies should be conducted to analyze the influence factors of AHI OLDU in dose and to evaluate the rationality of its application.