Objective To explore the difference of intervention effect between high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on patients with metabolic syndrome (MetS). Methods China National Knowledge Infrastructure, WanFang Data, PubMed, Web of Science and EBSCO were searched for randomized controlled trials (RCTs) till May 2022. Two reviewers independently reviewed the literature, extracted data, and assessed the risk of bias of included RCTs. Comprehensive Meta-Analysis software was used for meta-analysis. Result A total of 5 RCTs were included, including 216 patients. The results of meta-analysis showed that: except fasting blood glucose, high-density lipoprotein cholesterol, systolic blood pressure, waist circumference, body mass index and body fat percentage (P>0.005), low-density lipoprotein cholesterol [mean difference (MD)=−7.487 mg/dL, 95% confidence interval (CI) (−12.543, −2.431) mg/dL, P=0.004], total cholesterol [MD=−11.487 mg/dL, 95%CI (−16.523, −6.452) mg/dL, P<0.001], triglycerides [MD=−26.296 mg/dL, 95%CI (−50.557, −2.035) mg/dL, P=0.034] and diastolic blood pressure [MD=−2.770 mm Hg (1 mm Hg=0.133 kPa), 95%CI (−5.131, −0.409) mm Hg, P=0.021] of HIIT were better than MICT. Conclusion In terms of blood glucose indicators and morphological indicators, the effect of HIIT group and MICT group was similar, but the effect of HIIT on blood lipid indicators and blood pressure indicators of patients with MetS was better than MICT.
ObjectiveTo set reference intervals of the levels of thyroid hormones among normal pregnant women without presence of thyroid antibodies during three trimesters of pregnancy in Quanzhou city, Fujian province. MethodsA total of 490 pregnant women during 4-39 week pregnancy without presence of thyroid antibodies were enrolled in Quanzhou city, Fujian province. Levels of thyroid stimulating hormone (TSH), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid peroxidase antibodies (TPO-Ab) were detected through the electrochemistry immunoassay (ECL) method. In addition, a total of 51 healthy women without pregnancy were enrolled to set the reference intervals of levels of thyroid hormones among normal pregnant women without presence of thyroid antibodies. ResultsThe median levels of TPO-Ab were in the reference intervals provided by the pharmaceutical factory. Levels of FT3 and FT4 gradually decreased from the first to the third trimester (P < 0.01), levels of serum TSH gradually increasd from the first to the third trimester (P < 0.01). Compared with those of pregnant women, levels of thyroid hormone in normal non-pregnant women were higher in the first trimester, lower in the second and the third trimesters (P < 0.01). During three trimesters, the reference intervals of FT3 in the three trimesters were (first: 3.75 to 7.23; second 3.31 to 4.9; and third: 3.16 to 4.48 pmol/L); the reference intervals of FT4 were (first: 12.85 to 25.3; second: 12.03 to 20.14; and third: 11.02 to 19.43 pmol/L); and the reference intervals of TSH were (first: 0.01 to 3.79; second: 1.09 to 4.19; and third: 1.08 to 5.95 mIU/L), respectively. ConclusionThrough this detection, we set the levels of thyroid hormones among normal pregnant women without presence of thyroid antibodies during three trimesters of pregnancy in Quanzhou city.
Objectives To detect expressions of heat shock protein 70 (HSP70) and glial fibrillary acidic protein (GFAP) , and to estimate the post-injury interval after concussion of brain via the ratios of percentage of HSP70/GFAP-positive cells. Methods We established a brain concussion model of rat. Tissue levels of HSP70 and GFAP were determined by immunohistochemical staining at different time points after injury. Finally, the relationship between the ratio of percentage of HSP70/GFAP-positive cells and the post-injury interval was measured. Results The ratio of percentage of positive cells (increased from 7.15 to 11.73) and the percentage of HSP70-positive cells (P<0.05, compared with control group) increased, and the percentage of GFAP-positive cells did not change remarkably (P<0.05, compared with control group); the post-injury interval was between 0.5 hour and 3 hours. High ratio (>6.66) and high percentage of HSP70 and GFAP-positive cells (P<0.05, compared with control group) indicated the post-injury interval was between 3 and 12 hours. A low ratio (<6.66) and high percentage of HSP70 and GFAP-positive cells (P<0.05, compared with control group) suggested that the post-injury interval was later than 12 hours. Conclusion By analyzing the variation rule of the ratio of percentage positive cells after brain concussion, the post-injury interval after concussion of brain could be estimated.
In order to quantitatively analyze the morphology and period of pulse signals, a time-space analytical modeling and quantitative analysis method for pulse signals were proposed. Firstly, according to the production mechanism of the pulse signal, the pulse space-time analytical model was built after integrating the period and baseline of pulse signal into the analytical model, and the model mathematical expression and its 12 parameters were obtained for pulse wave quantification. Then, the model parameters estimation process based on the actual pulse signal was presented, and the optimization method, constraints and boundary conditions in parameter estimation were given. The spatial-temporal analytical modeling method was applied to the pulse waves of healthy subjects from the international standard physiological signal sub-database Fantasia of the PhysioNet in open-source, and we derived some changes in heartbeat rhythm and hemodynamic generated by aging and gender difference from the analytical models. The model parameters were employed as the input of some machine learning methods, e.g. random forest and probabilistic neural network, to classify the pulse waves by age and gender, and the results showed that random forest has the best classification performance with Kappa coefficients over 98%. Therefore, the space-time analytical modeling method proposed in this study can effectively quantify and analyze the pulse signal, which provides a theoretical basis and technical framework for some related applications based on pulse signals.
Objective To investigate the effectiveness and long-term stability of small fenestration vertebral bone grafting and transpedicular bone grafting in the treatment of Denis types A and B thoracolumbar burst fractures. Methods Between January 2012 and February 2014, 50 patients with Denis type A or B thoracolumbar burst fractures were treated with vertebroplasty and pedicle screw rod fixation system, and the clinical data were retrospectively analyzed. Small fenestration vertebral bone grafting by trans-interlaminar approach was used in 30 cases (group A), and bone grafting by unilateral transpedicular approach was used in 20 cases (group B). X-ray and CT examinations of the thoracolumbar vertebrae were performed routinely before and after operation. There was no significant difference in sex, age, cause of injury, time from injury to operation, fracture type, injury segment, and preoperative Frankel classification, the percentage of the anterior body height of the injured vertebra, and visual analogue scale (VAS) score between two groups (P>0.05). There was significant difference in preoperative Cobb angle of kyphosis between two groups (P<0.05). The Cobb angle of kyphosis, the percentage of the anterior body height of the injured vertebra, and the recovery of neurological function were recorded and compared between two groups. Results The patients were followed up for 16-31 months (mean, 19.1 months) in group A and for 17-25 months (mean, 20.2 months) in group B. Primary healing of incisions was obtained in the two groups; no nerve injury and other operative complications occurred. The neurological function was improved in varying degrees in the other patients with neurological impairment before operation except patients at grade A of Frankel classification. The lumbar back pain was relieved in two groups. There was significant difference in VAS score between before operation and at 3 months after operation or last follow-up in two groups (P<0.05), but no significant difference was found between at 3 months and last follow-up in two groups and between two groups at each time point after operation (P>0.05). X-ray examination showed that there was no breakage of nail and bar, or dislocation and loosening of internal fixation during follow-up period. The bone grafts filled well and fused in the fractured vertebra. The vertebral height recovered well after operation. The percentage of the anterior body height of the in-jured vertebra and Cobb angle of kyphosis at 1 week, 3 months, and last follow-up were significantly better than preope-rative ones in two groups (P<0.05), but there was no significant difference between different time points after operation (P>0.05), and between two groups at each time point after operation (P>0.05). Conclusion For Denis types A and B thoracolumbar burst fractures, vertebral bone grafting and pedicle screw internal fixation through interlaminal small fene-stration or transpedicular approach can restore the vertebral height, correct kyphosis, and maintain the vertebral stability, which reduce the risk of complications of loosening and breakage of internal fixators. The appropriate bone grafting approach can be chosen based on the degree of spinal canal space occupying, collapse of vertebral and spinal cord injury.
Seizure clusters, a severe form of epilepsy requiring urgent intervention, are challenging to manage in out-of-hospital settings due to limitations of traditional benzodiazepine administration routes. Diazepam nasal spray (DZP-NS), a novel intranasal formulation, achieves rapid absorption through the nasal mucosa, bypassing first-pass metabolism, with bioavailability comparable to rectal gel and faster onset. Clinical studies demonstrate its high efficacy in treating seizure clusters and prolonged seizures (≥5 minutes), with an initial control rate of 87.4% and low second-dose utilization (12.6%). No severe adverse reactions, such as cardiorespiratory depression, were observed. Long-term use (12 months) showed no tolerance development, significantly extending seizure intervals (SEIVAL) (from 12.2 to 25.7 days) and improving quality of life scores, particularly in "epilepsy-related concerns" and "social functioning" domains. The non-invasive delivery method was favored by over 80% of patients and healthcare providers for its convenience compared to rectal administration. Subgroup analyses confirmed consistent safety and efficacy across genders, ages, concomitant medications (including cannabidiol), and patients with allergy histories. In conclusion, DZP-NS provides an efficient, safe, and socially accepted out-of-hospital rescue therapy for seizure clusters, positioning it as a potential cornerstone in standardized epilepsy emergency care.
ObjectiveTo investigate the effect of the interval between neoadjuvant chemoradiotherapy (nCRT) and surgery on the clinical outcome of esophageal cancer.MethodsPubMed and EMbase databases from inception to March 2018 were retrieved by computer. A random-effect model was used for all meta-analyses irrespective of heterogeneity. The meta-analysis was performed by RevMan5.3 software. The primary outcomes were operative mortality, incidence of anastomotic leakage, and overall survival; secondary outcomes were pathologic complete remission rate, R0 resection rate, and positive resection margin rate.ResultsA total of 17 studies with 18 173 patients were included. Among them, 13 were original studies with 2 950 patients, and 4 were database-based studies with a total of 15 223 patients. The results showed a significant positive correlation between the interval and operative mortality (Spearman coefficient=0.360, P=0.027). Dose-response meta-analysis revealed that there was a relatively better time window for surgery after nCRT. Further analysis for primary outcomes at different time cut-offs found the following results: (1) when the time cut-off point within 30-70 days, the shorter interval was associated with a reduced operative mortality (7-8 weeks: RR=0.67, 95% CI 0.55-0.81, P<0.05; 30-46 days: RR=0.63, 95%CI 0.47-0.85, P<0.05; 60-70 days: RR=0.64, 95%CI 0.48-0.85, P<0.05); (2) when the time cut-off point within 30-46 days, the shorter interval correlated with a reduced incidence of anastomotic leakage (RR=0.39, 95%CI 0.21-0.72, P<0.05); when the time cut-off point within 7-8 weeks, the shorter interval could achieve a critical-level effect of reducing the incidence of anastomotic leakage (RR=0.73, 95%CI 0.52-1.03, P>0.05); (3) when the time cut-off point within 7-8 weeks, increased interval significantly was associated with the poor overall survival (HR=1.17, 95% CI 1.00-1.36, P<0.05). Secondary outcomes found that the shorter interval could significantly reduce the positive resection margin rate (RR=0.53, 95% CI 0.38-0.75, P<0.05) when time cut-off point within 56-60 days.ConclusionShortening the interval between nCRT and surgery can reduce the operative mortality, the incidence of anastomotic leakage, long-term mortality risk, and positive resection margin rate. It is recommended that surgery should be performed as soon as possible after the patient's physical recovery, preferably no more than 7-8 weeks, which supports the current study recommendation (within 3-8 weeks after nCRT).
Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution layers, four pooling layers, two full connection layers and one classification layer. The automatic feature extraction and classification were realized by the structure of the proposed CNN model. The model was verified by the whole night single-channel sleep electrocardiogram (ECG) signals of 70 subjects from the Apnea-ECG dataset. Our results showed that the accuracy of per-segment SA detection was ranged from 80.1% to 88.0%, using the input signals of single-channel ECG signal, RR interval (RRI) sequence, R peak sequence and RRI sequence + R peak sequence respectively. These results indicated that the proposed CNN model was effective and can automatically extract and classify features from the original single-channel ECG signal or its derived signal RRI and R peak sequence. When the input signals were RRI sequence + R peak sequence, the CNN model achieved the best performance. The accuracy, sensitivity and specificity of per-segment SA detection were 88.0%, 85.1% and 89.9%, respectively. And the accuracy of per-recording SA diagnosis was 100%. These findings indicated that the proposed method can effectively improve the accuracy and robustness of SA detection and outperform the methods reported in recent years. The proposed CNN model can be applied to portable screening diagnosis equipment for SA with remote server.
Missing data represent a general problem in many scientific fields, especially in medical survival analysis. Dealing with censored data, interpolation method is one of important methods. However, most of the interpolation methods replace the censored data with the exact data, which will distort the real distribution of the censored data and reduce the probability of the real data falling into the interpolation data. In order to solve this problem, we in this paper propose a nonparametric method of estimating the survival function of right-censored and interval-censored data and compare its performance to SC (self-consistent) algorithm. Comparing to the average interpolation and the nearest neighbor interpolation method, the proposed method in this paper replaces the right-censored data with the interval-censored data, and greatly improves the probability of the real data falling into imputation interval. Then it bases on the empirical distribution theory to estimate the survival function of right-censored and interval-censored data. The results of numerical examples and a real breast cancer data set demonstrated that the proposed method had higher accuracy and better robustness for the different proportion of the censored data. This paper provides a good method to compare the clinical treatments performance with estimation of the survival data of the patients. This provides some help to the medical survival data analysis.
Predicting the termination of paroxysmal atrial fibrillation (AF) may provide a signal to decide whether there is a need to intervene the AF timely. We proposed a novel RdR RR intervals scatter plot in our study. The abscissa of the RdR scatter plot was set to RR intervals and the ordinate was set as the difference between successive RR intervals. The RdR scatter plot includes information of RR intervals and difference between successive RR intervals, which captures more heart rate variability (HRV) information. By RdR scatter plot analysis of one minute RR intervals for 50 segments with non-terminating AF and immediately terminating AF, it was found that the points in RdR scatter plot of non-terminating AF were more decentralized than the ones of immediately terminating AF. By dividing the RdR scatter plot into uniform grids and counting the number of non-empty grids, non-terminating AF and immediately terminating AF segments were differentiated. By utilizing 49 RR intervals, for 20 segments of learning set, 17 segments were correctly detected, and for 30 segments of test set, 20 segments were detected. While utilizing 66 RR intervals, for 18 segments of learning set, 16 segments were correctly detected, and for 28 segments of test set, 20 segments were detected. The results demonstrated that during the last one minute before the termination of paroxysmal AF, the variance of the RR intervals and the difference of the neighboring two RR intervals became smaller. The termination of paroxysmal AF could be successfully predicted by utilizing the RdR scatter plot, while the predicting accuracy should be further improved.