In order to fully explore the neural oscillatory coupling characteristics of patients with mild cognitive impairment (MCI), this paper analyzed and compared the strength of the coupling characteristics for 28 MCI patients and 21 normal subjects under six different-frequency combinations. The results showed that the difference in the global phase synchronization index of cross-frequency coupling under δ-θ rhythm combination was statistically significant in the MCI group compared with the normal control group (P = 0.025, d = 0.398). To further validate this coupling feature, this paper proposed an optimized convolutional neural network model that incorporated a time-frequency data enhancement module and batch normalization layers to prevent overfitting while enhancing the robustness of the model. Based on this optimized model, with the phase locking value matrix of δ-θ rhythm combination as the single input feature, the diagnostic accuracy of MCI patients was (95.49 ± 4.15)%, sensitivity and specificity were (93.71 ± 7.21)% and (97.50 ± 5.34)%, respectively. The results showed that the characteristics of the phase locking value matrix under the combination of δ-θ rhythms can adequately reflect the cognitive status of MCI patients, which is helpful to assist the diagnosis of MCI.
Objective To analyze the trend of standardized infection ratio (SIR) of surgical site infection (SSI) in small bowel surgery, objectively evaluate the effect of infection control, and provide evidence-based strategies for SSI prevention. Methods According to Centers for Disease Control and Prevention (CDC) / National Healthcare Safety Network (NHSN) surveillance definitions for specific types of infections and the monitoring methods of SSI events published by NHSN, the SSI and related risk factors of adult inpatients undergoing small bowel surgery in Yichang Central People’s Hospital between January 1, 2016 and December 31, 2022 were prospectively monitored. The inpatients undergoing small bowel surgery that meets the definition of International Classification of Diseases, 10th Revision Clinical Modifications/Procedure Coding System (ICD-10-CM/PCS), a multivariate binary logistic regression model was used to calculate the predicted infections in each year, the model included the risk factors for small bowel surgery in NHSN Complex Admission/Readmission (A/R) SSI Model with 7 years of surveillance data as the baseline. The SIR was calculated by dividing the number of observed SSI by the number of predicted SSI in each year. The Mid-P method was used to test the difference of SIR compared to the previous year, and the linear regression model was used to analyze the trend of SIR. Results A total of 2 436 patients were included, with 48 cases of deep incision infection and 49 cases of organ/cavity infection, and the overall incidence rate of infection was 4.0%. From 2016 to 2022, there were 151, 244, 222, 260, 320, 408, and 831 patients who underwent small bowel surgery, respectively. The Mid-P test showed that there was a significant difference in SIR from 2016 to 2019 (P<0.05), and there was an increase in 2018 compared with 2017. There was no significant difference in SIR compared to the previous year from 2019 to 2022 (P>0.05), and there was no significant difference in the trend of SIR of SSI (P=0.065). Conclusions From January 1, 2017, to December 31, 2022, advances have been made in SSI control practices of small bowel surgery in six consecutive years, except for 2018, but there was no annual downward trend from 2020 to 2022. The use of SIR provides a new approach for evaluating the quality of infection control.
Traditional classifiers, such as support vector machine and Bayesian classifier, require data normalization for removing experimental batch effects, which limit their applications at the individual level. In this paper, we aim to build a classifier to distinguish lung cancer and non-cancer lung tissues (pneumonia and normal lung tissues). We identified gene pairs as signatures to build a classifier based on the within-sample relative expression orderings of gene pairs in a particular type of tissues (cancer or non-cancer). Using multiple independent datasets as the training data, including a total of 197 lung cancer cases and 189 non-cancer cases, we identified three gene pairs. Classifying a sample by the majority voting rule, the average accuracy reached 95.34% in the training data. Using multiple independent validation datasets, including a total of 251 lung cancer samples and 141 non-cancer samples without data normalization, the average accuracy was as high as 96.78%. The rank-based signature is robust against experimental batch effects and can be used to diagnose lung cancer using samples measured by different laboratories at the individual level.
Intravitreal drug injection is a treatment for common chronic fundus diseases such as age-related macular degeneration and diabetic retinopathy. The “14th Five-Year” National Eye Health Plan (2021-2025) recommends focusing on fundus diseases and improve the management mode of patients with chronic eye diseases. Therefore, it is imperative to explore how to further optimize the service process of intravitreal injection under the premise of guaranteeing patients' medical safety, to promote medical service efficiency and standardized management level and improve the medical experience of patients. Based on the quality control standard of vitreous cavity injection for retinopathy in China, Chinese fundus disease and related field experts developed the present expert consensus on the establishment of a one-stop intravitreal injection model and the management of its organization after a serious, comprehensive, and complete discussion, focusing on a standardized operation process, quality control, and safety management, providing more references for establishing a suitable intravitreal injection management model for ophthalmology and promoting the development of diagnostic and treatment models for fundus disease in China.