To assess the rel iabil ity of diabetic cutaneous ulcer surface area (DCUSA) measurement usingdigital planimetry method (A) and transparency tracing method (B). Methods Images of diabetic cutaneous ulcers from35 inpatients with diabetic skin ulcers from September 2005 to April 2007 were taken by a digital camera once a week or twice a week over a period of 12 weeks, resulting in 305 photographs; the ulcers were traced on a grid with acetate wound tracings, simultaneously. A total of 305 pairs of DCUSA which were calculated respectively throughout digital camera combined with Image J medical imaging software and transparency tracing with grid sheet by two independent observers sequentially were obtained. The intraclass correlation coefficients (ICCs, one-way random effect model) was used as an indicator of chancecorrected agreement to estimate the relative rel iabil ity for the interobserver data. Multiple l inear regression analysis was also used to measure the relationship of these two methods. Results DCUSA obtained from method A and obtained from method B was (4.84 ± 7.73) cm2 and (5.03 ± 7.89) cm2, respectively; no significant difference was found (P gt; 0.05). ICCs was high (ICCs=0.949 for method B and 0.965 for method A), indicating that the relative rel iabil ity for the interobserver was excellent. The method A were highly correlated with measurements obtained from method B (r = 0.957, P lt; 0.05). Conclusion The digital planimetry method described in this study represents a simple, practical, without any wound damage and contamination, and inexpensive technique to accurately evaluate the areas of diabetic cutaneous ulcers. The photographic technique combined with Image J medical imaging software should be considered for wound measurement.
Objective Secondary osteoporosis is very common in patients with primary osteoporosis. Diabetes is a known cause of secondary osteoporosis. While type I diabetes has been clearly linked with diabetic osteoporosis, the effect of type II diabetes on bone health is controversial.Methods In the present study, we investigated the associations between type II diabetes and osteoporosis as well as fractures at different skeletal sites in Women’s Health Initiative participants.Results Common risk factors such as age, race, BMI, HRT use, and the history of fractures were significantly associated with osteoporosis and fractures in this study population. Diabetic women appeared to have a decreased risk of osteoporosis although it no longer remained significant after adjusting for other risk factors (crude HR=0.78, 95%CI 0.61 to 0.99; adjusted HR=0.93, 95%CI 0.73 to 1.19). The impact of diabetes on fractures varied at different body sites. There was a significant increase of risk of hip fracture (HR=2.54, 95%CI 1.14 to 5.66), but not spine fracture (HR=1.71, 95%CI 0.81 to 3.60) and arm fracture (HR=0.92, 95%CI 0.48 to 1.76) among the women with diabetes. Although the overall risk of fractures in diabetic women did not differ significantly from non-diabetic women (HR=1.37, 95%CI 0.89 to 2.09), the difference had a two-fold increase and was statistically significant after 2,000 days (HR=2.01, 95%CI 1.21 to 3.35), indicating a different hazard at different stages of diabetes.Conclusion Our findings suggest that type II diabetes may not be clearly associated with osteoporosis, it increases a site-specific fracture risk at least in the hip. In addition, the overall fracture risk appears to increase in a time-dependent manner.
Objective To investigate the pleural effusion lymphocyte subsets in patients with pneumonia complicated with pleural effusion and its relationship with the occurrence of critical illness. MethodsPatients with pneumonia complicated with pleural effusion (246 cases) admitted to our hospital from January 2020 to June 2022 were selected as the research subjects. According to the severity of pneumonia, they were divided into a critical group (n=150) and a non-critical group (n=96). After 1:1 matching by propensity score matching method, there were 60 cases in each group. The general data of the two groups were compared. CD3+, CD4+, CD8+, CD4+/CD8+ ratio were detected by flow cytometry. Multivariate logistic regression was used to analyze the risk factors of critical pneumonia, and a nomogram prediction model was constructed and evaluated. The relationship between PSI score and lymphocyte subsets in pleural effusion was analyzed by local weighted regression scatter smoothing (LOWESS). Results After matching, the differences between the two groups of patients in the course of disease, heat peak, heat course, atelectasis, peripheral white blood cell count (WBC), C-reactive protein (CRP), D-dimer (D-D), procalcitonin (PCT) and hemoglobin were statistically significant (P<0.05). Compared with the non-critical group, the proportion of CD3+, CD4+, CD4+/CD8+ cells in critical group was lower (P<0.05), and the proportion of CD8+ cells was higher (P<0.05). Combined atelectasis, increased course of disease, fever peak and fever course, increased WBC, CRP, D-D, CD8+ and PCT levels, and decreased CD3+, CD4+, CD4+/CD8+ and Hb levels were independent risk factors for the occurrence of critical pneumonia (P<0.05). The nomogram prediction model based on independent influencing factors had high discrimination, accuracy and clinical applicability. There was a certain nonlinear relationship between pneomonia severity index and CD3+, CD4+, CD8+ and CD4+/CD8+. Conclusions Lymphocyte subsets in pleural effusion are closely related to the severity of pneumonia complicated with pleural effusion. If CD3+, CD4+, CD8+ and CD4+/CD8+ are abnormal, attention should be paid to the occurrence of severe pneumonia.
In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCI) systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset Ⅳa from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.
Impedance cardiography (ICG) is essential in evaluating cardiac function in patients with cardiovascular diseases. Aiming at the problem that the measurement of ICG signal is easily disturbed by motion artifacts, this paper introduces a de-noising method based on two-step spectral ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA). Firstly, the first spectral EEMD-CCA was performed between ICG and motion signals, and electrocardiogram (ECG) and motion signals, respectively. The component with the strongest correlation coefficient was set to zero to suppress the main motion artifacts. Secondly, the obtained ECG and ICG signals were subjected to a second spectral EEMD-CCA for further denoising. Lastly, the ICG signal is reconstructed using these share components. The experiment was tested on 30 subjects, and the results showed that the quality of the ICG signal is greatly improved after using the proposed denoising method, which could support the subsequent diagnosis and analysis of cardiovascular diseases.
Objective To analyze the causal relationship between gut microbiota and tic disorder based on Mendelian randomization (MR). Methods A total of 196 known microbiota (9 phyla, 16 classes, 20 orders, 32 families, and 119 genera) in the human intestinal microbiota dataset downloaded from the MiBioGen database were selected as the exposure factors, and the dataset of tic disorder (finn-b-KRA_PSY_TIC) containing 172 patients and 218620 controls was downloaded from the genome-wide association study database as the outcome variable. Inverse variance weighted was used as the main analysis method, and the causal relationship between gut microbiota and tic disorder was evaluated using odds ratio (OR) and its 95% confidence interval (CI). Horizontal pleiotropy was tested by MR-Egger intercept and MR-PRESSO global test, heterogeneity was assessed by Cochran’s Q test, and sensitivity analysis was performed by leave-one-out method. Results Inverse variance weighted results showed that the Family Rhodospirillaceae [OR=0.398, 95%CI (0.191, 0.831), P=0.014], Order Rhodospirillales [OR=0.349, 95%CI (0.164, 0.743), P=0.006], and Parasutterella [OR=0.392, 95%CI (0.171, 0.898), P=0.027] had negative causal relationships with tic disorder. The Genus Lachnospira [OR=8.784, 95%CI (1.160, 66.496), P=0.035] and Candidatus Soleaferrea [OR=2.572, 95%CI (1.161, 5.695), P=0.020] had positive causal relationships with tic disorder. In addition, MR-Egger intercept and MR-PRESSO global test showed no horizontal pleiotropy, Cochran’s Q test showed no heterogeneity, and leave-one-out sensitivity analysis showed the results were stable. Conclusions A causal relationship exists between gut microbiota and tic disorder. The Family Rhodospirillaceae, Order Rhodospirillales, and Parasutterella are associated with a decreased risk of tic disorder, while the Genus Lachnospira and Candidatus Soleaverea can increase the risk of tic disorder.
ObjectiveTo explore the correlation between readiness for hospital discharge and short-term quality of life among colorectal cancer (CRC) patients following enhanced recovery after surgery (ERAS) mode.MethodsSurveys of 127 CRC patients following ERAS mode were conducted in the West China Hospital of Sichuan University. The Readiness for Hospital Discharge Scale and EORTC QLQ-C30 Scale were issued at the discharge and 1 month after the operation, respectively.ResultsThe total score of RHDS was 149.43±33.25. The score of global quality of life was 66.80±18.84. Correlation analysis showed that the total score of RHDS was positively correlated with the score of global quality of life (r=0.220, P=0.013), and negatively correlated with the scores of fatigue, nausea and vomiting, pain, loss of appetite (r=–0.304, P=0.001; r=–0.189, P=0.033; r=–0.257, P=0.004; r=–0.254, P=0.004). The score of personal status dimension were positively correlated with the score of global quality of life and emotional function (r=0.213, P=0.016; r=0.197, P=0.027), and negatively correlated with scores of fatigue, pain and insomnia (r=–0.311, P=0.000; r=–0.264, P=0.003; r=–0.257, P=0.004). The score of knowledge dimension was negatively correlated with nausea and vomiting, pain and loss of appetite (r=–0.212, P=0.017; r=–0.182, P=0.040; r=–0.239, P=0.007). The score of coping ability dimension was positively correlated with the score of global quality of life and physical function (r=0.204, P=0.021; r=0.204, P=0.021), while negatively correlated with scores of fatigue, pain, insomnia and loss of appetite (r=–0.349, P=0.000; r=–0.240, P=0.007; r=–0.202, P=0.022; r=–0.201, P=0.024). The score of expected support was positively correlated with the score of global quality of life (r=0.220, P=0.013), and negatively correlated with scores of fatigue and loss of appetite (r=–0.249, P=0.005; r=–0.227, P=0.010).ConclusionsThe short term quality of life among CRC patients following ERAS keeps at upper middle level, and positively correlated with the readiness for hospital discharge. It is suggested that discharge preparation service is of great significance to improve the quality of life of patients.
This paper realized a portable brain-computer interface (BCI) system tailored for smart healthcare. Through the decoding of steady-state visual evoked potential (SSVEP), this system can rapidly and accurately identify the intentions of subjects, thereby meeting the practical demands of daily medical scenarios. Firstly, an SSVEP stimulation interface and an electroencephalogram (EEG) signal acquisition software were designed, which enable the system to execute multi-target and multi-task operations while also incorporating data visualization functionality. Secondly, the EEG signals recorded from the occipital region were decomposed into eight sub-frequency bands using filter bank canonical correlation analysis (FBCCA). Subsequently, the similarity between each sub-band signal and the reference signals was computed to achieve efficient SSVEP decoding. Finally, 15 subjects were recruited to participate in the online evaluation of the system. The experimental results indicated that in real-world scenarios, the system achieved an average accuracy of 85.19% in identifying the intentions of the subjects, and an information transfer rate (ITR) of 37.52 bit/min. This system was awarded third prize in the Visual BCI Innovation Application Development competition at the 2024 World Robot Contest, validating its effectiveness. In conclusion, this study has developed a portable, multifunctional SSVEP online decoding system, providing an effective approach for human-computer interaction in smart healthcare.
Objective To understand the incidence of frailty in maintenance hemodialysis (MHD) patients, and to explore the correlation and influencing factors of frailty in MHD patients, so as to provide some basis for the intervention of frailty in MHD patients. Methods Patients who underwent MHD in the Department of Nephrology of West China Hospital of Sichuan University from January to March 2021 were selected. Frail scale and Pittsburgh Sleep Quality Index (PSQI) were used for evaluation, and the influencing factors of frail in patients with MHD and its correlation with frail were analyzed. Results A total of 141 patients with MHD were included, including 57 cases without frailty (40.43%), 71 cases in early frailty (50.35%), and 13 cases in frailty (9.22%). 54 cases (38.30%) had very good sleep quality, 56 cases (39.72%) had good sleep quality, 24 cases (17.02%) had average sleep quality, and 7 cases (4.96%) had very poor sleep quality. The frailty of MHD patients was positively correlated with age (rs=0.265, P=0.002), PSQI (rs=0.235, P=0.005) and magnesium (rs=0.280, P=0.001). Logistic regression analysis showed that the influencing factors of MHD patients’ frailty were gender [odds ratio (OR) =4.321, 95%confidence interval (CI) (1.525, 12.243), P=0.006], PSQI [OR=1.110, 95%CI (1.009, 1.222), P=0.032], magnesium [OR=122.072, 95%CI (4.752, 3 135.528), P=0.004], hypertension [OR=0.112, 95%CI (0.023, 0.545), P=0.007] and other diseases [OR=0.102, 95%CI (0.019, 0.552), P=0.008]. Conclusions The incidence of frailty in MHD patients is high. Gender, PSQI, magnesium, hypertension and other diseases are the influencing factors of frailty in MHD patients, and there is a correlation between frailty and sleep. It is suggested that renal medical staff should pay more attention to the assessment of MHD frailty and sleep, and carry out multi-disciplinary personalized intervention to improve the quality of life of MHD patients.
Objective To explore the relationship between uric acid (UA) level and cardiovascular disease in patients with OSAHS and its clinical significance. Methods The electronic medical record system of the First hospital of Lanzhou University was used to collect 475 subjects who completed polysomnography (PSG) during hospitalization from January 2019 to May 2020. According to the Guidelines for the Diagnosis and Treatment of Obstructive Sleep Apnea Hypopnea Syndrome (Basic Version), the patients were divided into four group: control group [apnea-hypopnea index (AHI) <5 times/h, n=96], mild group (5≤AHI≤15 times/h, n=130), moderate group (15<AHI≤30 times/h, n=112), and severe group (AHI>30 times/h, n=137). The age, gender, body mass index (BMI), smoking history, drinking history, hypertension, diabetes mellitus, cardiovascular disease and biochemical indexes [including triglyceride, total cholesterol, high density lipoprotein cholesterol, low density lipoprotein cholesterol, glucose, UA, blood urea nitrogen (BUN), serum creatinine, lactate dehydrogenase, homocysteine], PSG indexes were observed and compared among the four groups, and the differences were compared by appropriate statistical methods. Binary logistic regression model was used to evaluate the correlation between various risk factors and cardiovascular disease. Results There were statistically significant differences in age, gender, BMI, drinking history, hypertension and cardiovascular disease among the 4 groups (P<0.05). The levels of UA and BUN in mild, moderate and severe groups were higher than those in the control group, with statistical significance (P<0.05). With the increasing of OSAHS severity, the level of UA increased. There was statistical significance in the incidence of cardiovascular disease among the four groups (P<0.05), and the highest incidence of arrhythmia was found among the four groups. And the incidence of cardiovascular disease increases with the increasing of OSAHS severity. Binary Logistic regression analysis showed that the risk factors for cardiovascular disease in OSAHS patients were age, UA and BUN (P<0.05). Conclusions The occurrence of cardiovascular disease in OSAHS patients is positively correlated with the severity of OSAHS. The level of UA can be used as an independent risk factor for cardiovascular disease in OSAHS patients. Therefore, reducing the level of UA may have positive significance for the prevention and control of the prevalence and mortality of cardiovascular disease in OSAHS patients.