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Journal of Healthcare Engineering
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  This is an Open Access Journal Open Access journal
ISSN (Print) 2040-2295 - ISSN (Online) 2040-2309
Published by Hindawi Homepage  [339 journals]
  • Comprehensive Diagnostic Medical System Based on Notch1 Signaling Pathway
           to Inhibit the Growth of Small-Cell Lung Carcinoma

    • Abstract: With the gradual application of big data and other technologies to the medical field, more and more people tend to get online medical services. This article mainly studies the comprehensive diagnostic medical system based on Notch1 signaling pathway to inhibit the growth of small-cell lung carcinoma. In the experiment, we used the rapid thawing method to recover the cells and took the logarithmic growth phase cells for cell passage. We calculated the cell concentration and diluted the cells according to the experimental requirements. According to the standard curve, the corresponding sample protein concentration was calculated; at the same time, the Trizol method was used to extract the total RNA, the NanoDrop8000 spectrophotometer was used to determine the RNA concentration, and the RNA quality was detected by agarose gel electrophoresis. We used immunohistochemical staining to complete the staining of lung cancer cells. Finally, black box testing was used to test the functional modules of the system. Experimental data show that the accuracy rate of data obtained by the system reaches 98%, which greatly facilitates doctors and patients. The results show that the system has good ease of use and reliability and improves the diagnosis and treatment of hospital patients.
      PubDate: Thu, 19 May 2022 18:05:02 +000
       
  • Guidewire-Assisted Reduction Technology Combined with Postural Reduction
           Improves the Success Rate of Internal Vein Catheterisation

    • Abstract: Objective. To investigate the value of guidewire-assisted reduction technology (which increases the stiffness of a catheter through the use of a guidewire, thereby protecting the puncture point and distal vein from breakage) combined with postural reduction for malpositioned catheters in the internal jugular vein during peripherally inserted central venous catheter catheterisation. Methods. From January 2015 to August 2020, we used ultrasound to perform guided puncture and monitoring. We identified the tip of the catheter as malpositioned in the internal jugular vein in 99 patients during the catheterisation process. These patients were divided randomly into a control group and an experimental group. In the control group, 43 cases received guidewire-assisted reduction technology, while in the experimental group, 56 patients received guidewire-assisted reduction technology combined with an upright posture. This study compared the efficacy of these two methods. Results. The results showed that 30 catheters were reduced successfully in the control group, with a success rate of 69.8%. In the experimental group, 53 cases were successfully reduced, with a success rate of 94.6%. The catheter reduction success rate in the experimental group was significantly higher than in the control group; this was a statistically significant difference ().Conclusion. Guidewire-assisted reduction technology combined with postural reduction can improve the success rate of the reduction of malpositioned catheters in the internal jugular vein.
      PubDate: Tue, 17 May 2022 14:50:01 +000
       
  • Cervical Lesion Classification Method Based on Cross-Validation Decision
           Fusion Method of Vision Transformer and DenseNet

    • Abstract: Objective. In order to better adapt to clinical applications, this paper proposes a cross-validation decision-making fusion method of Vision Transformer and DenseNet161. Methods. The dataset is the most critical acetic acid image for clinical diagnosis, and the SR areas are processed by a specific method. Then, the Vision Transformer and DenseNet161 models are trained by the fivefold cross-validation method, and the fivefold prediction results corresponding to the two models are fused by different weights. Finally, the five fused results are averaged to obtain the category with the highest probability. Results. The results show that the fusion method in this paper reaches an accuracy rate of 68% for the four classifications of cervical lesions. Conclusions. It is more suitable for clinical environments, effectively reducing the missed detection rate and ensuring the life and health of patients.
      PubDate: Sat, 14 May 2022 16:50:02 +000
       
  • Predicting the Kidney Graft Survival Using Optimized African Buffalo-Based
           Artificial Neural Network

    • Abstract: A variety of receptor and donor characteristics influence long-and short-term kidney graft survival. It is critical to predict the effectiveness of kidney transplantation to optimise organ allocation. This would allow patients to choose the best accessible kidney donor and the optimal immunosuppressive medication. Several studies have attempted to identify factors that predispose to graft rejection, but the results have been contradictory. As a result, the goal of this paper is to use the African buffalo-based artificial neural network (AB-ANN) approach to uncover predictive risk variables related to kidney graft. These two feature selection approaches combine to provide a novel hybrid feature selection technique that could select the most important elements to improve prediction accuracy. The feature analysis revealed that clinical features have varied effects on transplant survival. The collected data is processed in both training and testing methods. The prediction model's performance, in terms of accuracy, precision, recall, and F-measure, was examined, and the results were compared with those of other existing systems, including naive Bayesian, random forest, and J48 classifier. The results suggest that the proposed approach can forecast graft survival in kidney recipients' next visits in a creative manner and with more accuracy compared with other classifiers. This proposed method is more efficient for predicting kidney graft survival. Incorporating those clinical tools into outpatient clinics’ everyday workflows could help physicians make better and more personalised decisions.
      PubDate: Sat, 14 May 2022 16:50:01 +000
       
  • Multiparametric Magnetic Resonance Imaging Information Fusion Using Graph
           Convolutional Network for Glioma Grading

    • Abstract: Accurate preoperative glioma grading is essential for clinical decision-making and prognostic evaluation. Multiparametric magnetic resonance imaging (mpMRI) serves as an important diagnostic tool for glioma patients due to its superior performance in describing noninvasively the contextual information in tumor tissues. Previous studies achieved promising glioma grading results with mpMRI data utilizing a convolutional neural network (CNN)-based method. However, these studies have not fully exploited and effectively fused the rich tumor contextual information provided in the magnetic resonance (MR) images acquired with different imaging parameters. In this paper, a novel graph convolutional network (GCN)-based mpMRI information fusion module (named MMIF-GCN) is proposed to comprehensively fuse the tumor grading relevant information in mpMRI. Specifically, a graph is constructed according to the characteristics of mpMRI data. The vertices are defined as the glioma grading features of different slices extracted by the CNN, and the edges reflect the distances between the slices in a 3D volume. The proposed method updates the information in each vertex considering the interaction between adjacent vertices. The final glioma grading is conducted by combining the fused information in all vertices. The proposed MMIF-GCN module can introduce an additional nonlinear representation learning step in the process of mpMRI information fusion while maintaining the positional relationship between adjacent slices. Experiments were conducted on two datasets, that is, a public dataset (named BraTS2020) and a private one (named GliomaHPPH2018). The results indicate that the proposed method can effectively fuse the grading information provided in mpMRI data for better glioma grading performance.
      PubDate: Tue, 10 May 2022 12:35:00 +000
       
  • The Biomechanics Effect of Hamstring Flexibility on the Risk of
           Osgood-Schlatter Disease

    • Abstract: Background. The relationship between hamstring flexibility and the risk of OSD continues to be a debate, and whether hamstring stretching exercises should be considered as one of the conservative treatments of OSD is still unclear. Objectives. To investigate the relationship between hamstring flexibility and the risk of OSD by assessing the changes of loading on the tibial tuberosity caused by the changes of hamstring optimal lengths. Methods. Experimental data of a young adult running at 4 m/s were used, which were collected by an eight-camera motion capture system together with an instrumented treadmill. Muscle forces were estimated in OpenSim when hamstring optimal lengths changed in the range of 70–130% of the control case in 5% increments. The force and accumulated force of quadriceps muscle were calculated to evaluate the impact of hamstring optimal lengths on the loading on tibial tuberosity. The changes in muscle forces throughout the gait cycle were compared by using statistical parametric mapping (SPM). The average peak force and accumulated force of five gait cycles were compared. Results. Although the maximum force of the quadriceps muscle was slightly affected by changes in hamstring optimal lengths, the accumulated force of quadriceps muscle increased by 21.97% with hamstring optimal lengths decreased by 30% of the control case. The increase of the muscle force mainly occurred in the early stance phase and terminal swing phase (). However, when hamstring optimal lengths were longer than the control, it had a little effect on accumulated force of quadriceps muscle. Conclusions. The results of this study indicate that a shorter hamstring optimal length, which means lack of flexibility, can cause a high accumulated force on tibial tuberosity, thus increasing the risk of OSD. Hamstring stretching exercise is only effective for people with lack of hamstring flexibility.
      PubDate: Mon, 09 May 2022 10:35:00 +000
       
  • Data Confidentiality in Healthcare Monitoring Systems Based on Image
           Steganography to Improve the Exchange of Patient Information Using the
           Internet of Things

    • Abstract: Recently, with the availability of fast and reliable Internet, the distance between a patient and a doctor is becoming unimportant. Physicians will be able to request the medical images of their patients regardless of the geographical area. However, a lot of challenges face such successful implementation. To facilitate remote diagnosis, patient electronic medical record (EMR), including medical images, that originates in one system needs to be exchanged either within the same organization or across different organizations. Steganography is the practice of concealing a secret message inside a cover medium. In this paper, steganography will be used to embed the patient’s personal information securely and imperceptibly in their medical images to enhance confidentiality in case of a distant diagnosis. The security of the medical data is improved to maintain confidentiality and integrity using IoT. The least significant bit of the approximate coefficient of integer wavelet transform is proposed. The distortion between the cover image and stego-image is obtained by measuring the mean square error and PSNR, and normalized cross-correlation is utilized to estimate the degree of closeness between the cover image and stego-image.
      PubDate: Fri, 06 May 2022 07:50:00 +000
       
  • Study of Hospitalization Costs in Patients with Cerebral Ischemia Based on
           E-CHAID Algorithm

    • Abstract: Background. The aging of the population has led to a rapid increase in the prevalence of most neurological diseases between 1990 and 2016, with a growth rate of up to 117%, which has put enormous pressure on medical insurance funds. As one of the core diseases of disease diagnosis grouping, the hospitalization cost composition and grouping research of patients with cerebral ischemic disease can help to determine scientific payment standards and reduce the economic burden of patients. Aim. We aimed to understand the cost composition and influencing factors of hospitalized patients with cerebral ischemic diseases and to identify a reasonable cost grouping scheme. Methods. The data come from the homepage of medical records of inpatients with cerebral ischemia in a tertiary hospital in Sichuan Province from 2018 to 2020. After cleaning the data, a total of 5,204 pieces of data were obtained. Nonparametric tests and gamma regression models were used to explore the influencing factors of hospitalization costs. Taking the influencing factors as the predictor variables and the hospitalization cost as the target variable, the exhaustive Chi-squared automatic interaction detector (E-CHAID) algorithm was used to form the costs grouping, and the payment standard of the hospitalization cost for each group was determined. The rationality of cost grouping was evaluated by coefficient of variation (CV) and Kruskal–Wallis H test. Results. From 2018 to 2020, the average hospital stay of 5,204 inpatients with cerebral ischemic disease was 10.70 days, and the average hospitalization cost was 17,206.09 RMB yuan. Among the hospitalization costs, diagnosis costs and drug costs accounted for the highest proportion, accounting for 41.18% and 22.38%, respectively, in 2020. Gender, age, admission route, comorbidities and complications, super length of stay (>30 days), and discharge mode had significant effects on hospitalization costs (P 
      PubDate: Mon, 02 May 2022 11:05:00 +000
       
  • LSGDM with Biogeography-Based Optimization (BBO) Model for Healthcare
           Applications

    • Abstract: Several studies aimed at improving healthcare management have shown that the importance of healthcare has grown in recent years. In the healthcare industry, effective decision-making requires multicriteria group decision-making. Simultaneously, big data analytics could be used to help with disease detection and healthcare delivery. Only a few previous studies on large-scale group decision-making (LSDGM) in the big data-driven healthcare Industry 4.0 have focused on this topic. The goal of this work is to improve healthcare management decision-making by developing a new MapReduce-based LSDGM model (MR-LSDGM) for the healthcare Industry 4.0 context. Clustering decision-makers (DM), modelling DM preferences, and classification are the three stages of the MR-LSDGM technique. Furthermore, the DMs are subdivided using a novel biogeography-based optimization (BBO) technique combined with fuzzy C-means (FCM). The subgroup preferences are then modelled using the two-tuple fuzzy linguistic representation (2TFLR) technique. The final classification method also includes a feature extractor based on long short-term memory (LSTM) and a classifier based on an ideal extreme learning machine (ELM). MapReduce is a data management platform used to handle massive amounts of data. A thorough set of experimental analyses is carried out, and the results are analysed using a variety of metrics.
      PubDate: Sat, 30 Apr 2022 16:25:09 +000
       
  • Identification and Validation of a Gene Signature for Lower-Grade Gliomas
           Based on Pyroptosis-Related Genes to Predict Survival and Response to
           Immune Checkpoint Inhibitors

    • Abstract: Pyroptosis plays a critical role in the immune response to immune checkpoint inhibitors (ICIs) by mediating the tumor immune microenvironment. However, the impact of pyroptosis-related biomarkers on the prognosis and efficacy of ICIs in patients with lower-grade gliomas (LGGs) is unclear. An unsupervised clustering analysis identified pyroptosis-related subtypes (PRSs) based on the expression profile of 47 pyroptosis-related genes in The Cancer Genome Atlas-LGG cohort. A PRS gene signature was established using univariate Cox regression, random survival forest, least absolute shrinkage and selection operator, and stepwise multivariable Cox regression analyses. The predictive power of this signature was validated in the Chinese Glioma Genome Atlas database. We also investigated the differences between high- and low-risk groups in terms of the tumor immune microenvironment, tumor mutation, and response to target therapy and ICIs. The PRS gene signature comprised eight PRS genes, which independently predicted the prognosis of LGG patients. High-risk patients had a worse overall survival than did the low-risk patients. The high-risk group also displayed a higher proportion of M1 macrophages and CD8+ T cells and higher immune scores, tumor mutational burden, immunophenoscore, IMmuno-PREdictive Score, MHC I association immune score, and T cell-inflamed gene expression profile scores, but lower suppressor cells scores, and were more suitable candidates for ICI treatment. Higher risk scores were more frequent in patients who responded to ICIs using data from the ImmuCellAI website. The presently established PRS gene signature can be validated in melanoma patients treated with real ICI treatment. This signature is valuable in predicting prognosis and ICI treatment of LGG patients, pending further prospective verification.
      PubDate: Sat, 30 Apr 2022 16:25:09 +000
       
  • A Low-Cost Multistage Cascaded Adaptive Filter Configuration for Noise
           Reduction in Phonocardiogram Signal

    • Abstract: Phonocardiogram (PCG), the graphic recording of heart signals, is analyzed to determine the cardiac mechanical function. In the recording of PCG signals, the major problem encountered is the corruption by surrounding noise signals. The noise-corrupted signal cannot be analyzed and used for advanced processing. Therefore, there is a need to denoise these signals before being employed for further processing. Adaptive Noise Cancellers are best suited for signal denoising applications and can efficiently recover the corrupted PCG signal. This paper introduces an optimal adaptive filter structure using a Sign Error LMS algorithm to estimate a noise-free signal with high accuracy. In the proposed filter structure, a noisy signal is passed through a multistage cascaded adaptive filter structure. The number of stages to be cascaded and the step size for each stage are adjusted automatically. The proposed Variable Stage Cascaded Sign Error LMS (SELMS) adaptive filter model is tested for denoising the fetal PCG signal taken from the SUFHS database and corrupted by Gaussian and colored pink noise signals of different input SNR levels. The proposed filter model is also tested for pathological PCG signals in the presence of Gaussian noise. The simulation results prove that the proposed filter model performs remarkably well and provides 8–10 dB higher SNR values in a Gaussian noise environment and 2-3 dB higher SNR values in the presence of colored noise than the existing cascaded LMS filter models. The MSE values are improved by 75–80% in the case of Gaussian noise. Further, the correlation between the clean signal and its estimate after denoising is more than 0.99. The PSNR values are improved by 7 dB in a Gaussian noise environment and 1-2 dB in the presence of pink noise. The advantage of using the SELMS adaptive filter in the proposed filter model is that it offers a cost-effective hardware implementation of Adaptive Noise Canceller with high accuracy.
      PubDate: Sat, 30 Apr 2022 04:05:01 +000
       
  • Enhanced Laterality Index: A Novel Measure for Hemispheric Asymmetry

    • Abstract: During sleep, the two hemispheres display asymmetries in their activation pattern. Various hemispheric asymmetry measures have been utilized in existing works. Nevertheless, all these measures have one common problem that they would merely take one representative quantity into account when evaluating the functional asymmetry. However, there is a complex series of information exchanges between the two cerebral hemispheres, and only considering one quantity inevitably leads to one-sided or even incorrect conclusions. Consequently, to address the limitation of conventional laterality indices, we propose the so-called enhanced laterality index (ELI), which considers multiple measures of functional asymmetries. Normal sleep and obstructive sleep apnea electroencephalograms (EEGs) from 21 subjects collected in the clinical acquisition system are applied, and two representative quantities are considered simultaneously in this paper. We measure the signal complexity by using fuzzy entropy, and the signal strength is evaluated by calculating EEG energy. The difference of ELI is demonstrated by the comparison with the traditional laterality index (LI) in evaluating the functional asymmetry during sleep.
      PubDate: Fri, 29 Apr 2022 10:35:01 +000
       
  • Evaluation of the Effect of Comprehensive and Targeted Surveillance on
           Nosocomial Infections in Nephrology Patients

    • Abstract: The article summarizes the control strategy by discussing the risk factors of nosocomial infections in the nephrology department. A survey of hospitalized patients from January 2020 to December 2020 showed that there are six types of bacteria that can cause infections. The age of the patient, the risk of invasive surgery, the low use of antibiotics, and age are all independent factors that affect the risk of nosocomial infections in the patient. The more antibiotics used, the better the infection prevention effect. Among the many risk factors for patient infection, bacterial infection is the main risk factor. Klebsiella pneumoniae infection rate was the highest, 33.98%; Staphylococcus aureus infection rate was the lowest, 6.80%. Therefore, the nephrology department should focus on strengthening the prevention of Klebsiella pneumoniae infection, and implement early prevention and management interventions for various risk factors.
      PubDate: Fri, 29 Apr 2022 10:35:01 +000
       
  • Software Application toward Accessible Hearing Care Assessment: Gap in
           Noise Test

    • Abstract: Currently, several methods are being applied to assess auditory temporal resolution in a controlled clinical environment via the measurements of gap detection thresholds (GDTs). However, these methods face two issues: the relatively long time required to perform the gap detection test in such settings and the potential of inaccessibility to such facilities. This article proposes a fast, affordable, and reliable application-based method for the determination of GDT either inside or outside the soundproof booth. The proposed test and the acoustic stimuli were both developed using the MATLAB® programming platform. GDT is determined when the subject is able to distinguish the shortest silent gap inserted randomly in one of two segments of white noise. GDTs were obtained from 42 normal-hearing subjects inside and outside the soundproof booth. The results of this study indicated that average GDTs measured inside the booth (5.12 ± 1.02 ms) and outside (4.78 ± 1.16 ms) were not significantly different. The measured GDTs were also comparable to that reported in the literature. In addition, the GDT screening time of the proposed method was approximately 5 minutes, a screening time that is much less than that reported by the literature. Data show that the proposed application was fast and reliable to screen GDT compared to the standard method currently used in clinical settings.
      PubDate: Fri, 29 Apr 2022 09:35:01 +000
       
  • Design and Implementation of Obstetric Central Monitoring System Based on
           Medical Image Segmentation Algorithm

    • Abstract: At present, the incidence of emergencies in obstetric care environment is gradually increasing, and different obstetric wards often have a variety of situations. Therefore, it can provide great help in clinical medicine to give early warning and plan coping plans according to different situations. This paper studied an obstetrics central surveillance system based on a medical image segmentation algorithm. Images obtained by central obstetrics monitoring are segmented, magnified in detail, and image features are extracted, collated, and trained. The normal distribution rule is used to classify the features, which are included in the feature library of the obstetric central monitoring system. In the gray space of the medical image, the statistical distribution of gray features of the medical image is described by the mixture model of Rayleigh distribution and Gaussian distribution. In the gray space of the medical image, Taylor series expansion is used to describe the linear geometric structure of medicine. The eigenvalues of Hessian matrix are introduced to obtain high-order multiscale features of medicine. The multiscale feature energy function is introduced into Markov random energy objective function to realize medical image segmentation. Compared with other segmentation algorithms, the accuracy and sensitivity of the proposed algorithm are 87.98% and 86.58%, respectively, which can clearly segment small medical features.
      PubDate: Thu, 28 Apr 2022 07:50:00 +000
       
  • An Improved Multitask Learning Model with Matching Network and Its
           Application in Traditional Chinese Medicine Syndrome Recommendation

    • Abstract: Multitask learning (MTL) is an open and challenging problem in various real-world applications, such as recommendation systems, natural language processing, and computer vision. The typical way of conducting multitask learning is establishing some global parameter sharing mechanism among all tasks or assigning each task an individual set of parameters with cross-connections between tasks. However, for most existing approaches, the raw features are abstracted step by step, semantic information is mined from input space, and matching relation features are not introduced into the model. To solve the above problems, we propose a novel MMOE-match network to model the matches between medical cases and syndrome elements and introduce the recommendation algorithm into traditional Chinese medicine (TCM) study. Accurate medical record recommendation is significant for intelligent medical treatment. Ranking algorithms can be introduced in multi-TCM scenarios, such as syndrome element recommendation, symptom recommendation, and drug prescription recommendation. The recommendation system includes two main stages: recalling and ranking. The core of recalling and ranking is a two-tower matching network and multitask learning. MMOE-match combines the advantages of recalling and ranking model to design a new network. Furtherly, we try to take the matching network output as the input of multitask learning and compare the matching features designed by the manual. The data show that our model can bring significant positive benefits.
      PubDate: Tue, 26 Apr 2022 10:20:00 +000
       
  • Application of Digital Games for Speech Therapy in Children: A Systematic
           Review of Features and Challenges

    • Abstract: Introduction. Treatment of speech disorders during childhood is essential. Many technologies can help speech and language pathologists (SLPs) to practice speech skills, one of which is digital games. This study aimed to systematically investigate the games developed to treat speech disorders and their challenges in children. Methods. A comprehensive search was conducted in four databases, including Medline (through PubMed), Scopus, Web of Science, and IEEE Xplore, to retrieve English articles published by July 14, 2021. The articles in which a digital game was developed to treat speech disorders in children were included in the study. Then, the features of the designed games and their challenges were extracted from the studies. Results. After reviewing the full texts of 69 articles and assessing them in terms of inclusion and exclusion criteria, 27 articles were included in the systematic review. In these articles, 59.25% of the games had been developed in English language and children with hearing impairments had received much attention from researchers compared to other patients. Also, the Mel-Frequency Cepstral Coefficients (MFCC) algorithm and the PocketSphinx speech recognition engine had been used more than any other speech recognition algorithm and tool. In terms of the games, 48.15% had been designed in a way that children could practice with the help of their parents. The evaluation of games showed a positive effect on children’s satisfaction, motivation, and attention during speech therapy exercises. The biggest barriers and challenges mentioned in the studies included sense of frustration, low self-esteem after several failures in playing games, environmental noise, contradiction between games levels and the target group’s needs, and problems related to speech recognition. Conclusion. The results of this study showed that the games positively affect children’s motivation to continue speech therapy, and they can also be used as the SLPs’ aids. Before designing these tools, the obstacles and challenges should be considered, and also, the solutions should be suggested.
      PubDate: Mon, 25 Apr 2022 09:50:01 +000
       
  • Prediction Model of Adverse Effects on Liver Functions of COVID-19 ICU
           Patients

    • Abstract: SARS-CoV-2 is a recently discovered virus that poses an urgent threat to global health. The disease caused by this virus is termed COVID-19. Death tolls in different countries remain to rise, leading to continuous social distancing and lockdowns. Patients of different ages are susceptible to severe disease, in particular those who have been admitted to an ICU. Machine learning (ML) predictive models based on medical data patterns are an emerging topic in areas such as the prediction of liver diseases. Prediction models that combine several variables or features to estimate the risk of people being infected or experiencing a poor outcome from infection could assist medical staff in the treatment of patients, especially those that develop organ failure such as that of the liver. In this paper, we propose a model called the detecting model for liver damage (DMLD) that predicts the risk of liver damage in COVID-19 ICU patients. The DMLD model applies machine learning algorithms in order to assess the risk of liver failure based on patient data. To assess the DMLD model, collected data were preprocessed and used as input for several classifiers. SVM, decision tree (DT), Naïve Bayes (NB), KNN, and ANN classifiers were tested for performance. SVM and DT performed the best in terms of predicting illness severity based on laboratory testing.
      PubDate: Mon, 25 Apr 2022 06:05:00 +000
       
  • An Immunity-Associated lncRNA Signature for Predicting Prognosis in
           Gastric Adenocarcinoma

    • Abstract: Background. Gastric adenocarcinoma (GAD) is one of the most common tumors in the world and the prognosis is still very poor. Objective. We sought to identify reliable prognostic biomarkers for the progression of GAD and the sensitivity to drug therapy. Method. The RNA sequencing data of GAD was downloaded from the Cancer Genome Atlas (TCGA) database and used for analysis. Differentially expressed, immune-related lncRNA (DEIRlncRNA) was characterized by differential analysis and correlation analysis. Univariate Cox regression analysis was used to identify DEIRlncRNA associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis allowed us to determine a signature composed of eight IRlncRNAs. Based on this signature, we further performed gene set enrichment analysis (GSEA) and somatic mutation analysis to evaluate the ability of this signature to predict prognosis. Results. In total, 72 immune-related lncRNAs (DEIRlncRNAs) with prognostic value were identified. These lncRNAs were used to construct a model containing eight immune-related lncRNAs (8-IRlncRNAs). Based on this risk model, we divided GAD patients into high-risk and low-risk groups. The analysis showed that the prognosis of the two groups was different and that the high-risk group had worse overall survival (OS). Immune cell infiltration analysis showed that the proportion of memory B cells increased in the high-risk group while the proportion of macrophages M1, T cells, CD4 memory-activated cells, and T cell follicular helpers decreased. GSEA results showed that 8-IRlncRNA was significantly enriched in tumorigenesis pathways such as myc. The results of somatic mutation analysis showed that the CDH1 gene was significantly mutated in the high-risk group. Conclusion. A prognostic signature of 8-IRlncRNAs in GAD was established and this signature was able to predict the prognosis of GAD patients.
      PubDate: Mon, 25 Apr 2022 04:35:01 +000
       
  • Factors of Parents-Reported Readiness for Hospital Discharge in Children
           with Acute Leukemia: A Cross-Sectional Study

    • Abstract: Aim. The aim of this study is to investigate the existing status and to explore the influencing factors of parents-reported readiness for hospital discharge in children with acute leukemia (AL) in China and to propose optimizing pathways and recommendations of discharge readiness for clinical reference. Methods. A cross-sectional survey was conducted for the 122 children with AL who were discharged from the Second Affiliated Hospital and Yuying Children’s Hospital, Wenzhou Medical University; their parents were investigated by using the modified Chinese version of Readiness for Hospital Discharge Scale (RHDS) and Quality of Discharge Teaching Scale (QDTS). Data were collected between September 2020 and May 2021.Univariate analysis and multivariate logistic regression analysis were performed to explore the influencing factors of readiness for hospital discharge. Results. The 122 children with AL included 52 females and 70 males with mean age 6.08 years. The total RHDS score was 7.7 ± 1.2, and 68.9% of the participants had high readiness for hospital discharge (RHDS score >7). The total QDTS score was 7.6 ± 2.0. Parent marital status (OR = 4.86, 95% CI: 1.31–18.05), education status (OR = 3.86, 95% CI: 1.18–12.55), family per capita monthly income (OR = 1.08, 95% CI: 1.01–2.99), and high QDTS (OR = 1.56, 95% CI: 1.11–2.68) were risk factors for high RHDS. Conclusions. Our data suggest parents of children with AL had high readiness for hospital discharge and had the ability to take care of their children after discharge. Parental marital status, education status, QDTS score, and family per capita monthly income were independently associated with high RHDS.
      PubDate: Fri, 22 Apr 2022 05:05:00 +000
       
  • Expression of CX3CL1 and CCL28 in Spinal Metastases of Lung Adenocarcinoma
           and Their Correlation with Clinical Features and Prognosis

    • Abstract: Lung adenocarcinoma is the most common non-small-cell lung cancer. In this paper, we aim to investigate the expression of chemokine ligand 1 (cx3cl1) and chemokine ligand 28 (CCL28) in spinal metastases of lung adenocarcinoma and their correlation with clinical features and prognosis. We analyzed the clinical data of 40 patients with lung adenocarcinoma and spinal metastases who underwent surgery in our hospital from January 2018 to January 2021 retrospectively. The expression levels of cx3cl1 and CCL28 in bone metastases were detected by immunohistochemistry, and the staining results were sorted and classified. Combined with the follow-up results and clinicopathological data, we statistically analyzed the expression of cx3cl1 and CCL28 in spinal bone metastases and their correlation with prognosis. Among the 40 patients with spinal metastasis of lung adenocarcinoma, 7 cases were strongly positive for cx3cl1, 25 cases were moderately positive, and 8 cases were weakly positive and negative. CCL28 was strongly positive in 9 cases, moderately positive in 26 cases, weakly positive and negative in 5 cases. The expression of cx3cl1 was correlated with ECOG score (P = 0.005) and visceral organ metastasis (P = 0.004), but not with age, sex, and the number of bone metastases (P > 0.05). The expression of CCL28 was correlated with ECOG score (P = 0.022) and visceral organ metastasis (P = 0.003), but not with age, sex, and the number of bone metastases (P > 0.05). The OS of patients with strong cx3cl1 positive was significantly shorter than that of patients with medium positive and weak positive (P 
      PubDate: Thu, 21 Apr 2022 15:20:01 +000
       
  • The Value of Python Programming in General Education and Comprehensive
           Quality Improvement of Medical Students Based on a Retrospective Cohort
           Study

    • Abstract: Objective. A retrospective cohort study was conducted to analyze the application value of Python programming in general education and comprehensive quality improvement of medical students. Methods. A retrospective analysis was made on the application value of Python programming in the general education classroom of medical students from September 2020 to July 2021 by undergraduate students majoring in anesthesia in grade 2020, imaging in grade 2019, clinical in grade 2020, and laboratory sciences in grade 2020 in our university. A hundred students who used Python programming in general education class were divided into study group and control group. The teaching satisfaction, medical knowledge and lifelong learning ability, clinical skills, medical service ability, disease prevention, health promotion ability, interpersonal communication ability, and information management and research ability were compared between the two groups. Results. In a comparison of teaching satisfaction between the two groups, the study group was very satisfied in 89 cases, satisfactory in 10 cases, and general in 1 case, and the satisfaction rate was 100.00%; the control group was very satisfied in 54 cases, satisfactory in 23 cases, general in 13 cases, and dissatisfied in 10 cases, and the satisfaction rate was 90.00%. The teaching satisfaction in the study group was higher than that in the control group, and the difference was statistically significant (). Compared with the control group, medical knowledge ability (basic knowledge, general education, and professional knowledge) and lifelong learning ability (learning concept and professional learning attitude) in the research group were significantly higher than those in the research group (). The scores of clinical skills (medical history analysis, basic diagnosis, treatment techniques, and disease analysis) and medical service ability (first aid ability, comprehensive analysis ability, and disease analysis ability) in the study group were significantly higher than those in the control group (). In terms of the ability of disease prevention and health promotion, the scores of disease prevention (health guidance, health education, and self-care) and health promotion ability (cooperative participation in diagnosis and treatment, guidance of medical and health work, and rational use of health resources) in the study group were higher than those in the control group, and the difference was statistically significant (). In the comparison of interpersonal communication ability, the scores of listening, expression, understanding, trust, medical terminology, and communication ability in the study group were higher than those in the control group, and the difference was statistically significant (). Comparing information management with research ability, the scores of information management ability (searching information, screening information, and sorting information) and research ability (arrangement ability, planning ability, and execution ability) in the research group were higher than those in the control group, and the data difference was statistically significant ().Conclusion. The application of the Python programming method in general education and comprehensive quality improvement of medical students can effectively improve medical students’ teaching satisfaction and medical knowledge such as lifelong learning ability, clinical skills, medical service ability, disease prevention, health promotion ability, interpersonal communication ability, and information management and research ability, which has a positive impact on the improvement of comprehensive quality.
      PubDate: Thu, 21 Apr 2022 14:35:00 +000
       
  • A Retrospective Analysis of Metagenomic Next Generation Sequencing (mNGS)
           of Cerebrospinal Fluid from Patients with Suspected Encephalitis or
           Meningitis Infections

    • Abstract: We determined the clinical value of metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) for the diagnosis of patients with suspected encephalitis or meningitis infection. Clinical data were collected and retrospectively analyzed from patients with suspected cases of encephalitis or meningitis who presented at four hospitals in Ningbo from January 1st, 2019 to December 31st, 2020. Of a total of 66 suspected cases, 41 (62.12%) were diagnosed with central nervous system infections, which included 18 cases (27.27%) of viral infection, 13 cases (19.70%) of bacterial infection, 3 cases (4.55%) of Mycobacterium tuberculosis, 5 cases (7.58%) of fungal infection, and 2 cases (3.03%) of Rickettsia infection. From these cases, mNGS identified 25 (37.88%) true-positive cases, 8 (12.12%) false-positive cases, 20 (30.30%) true-negative cases, and 13 (19.70%) false-negative cases. The sensitivity of mNGS was 65.79% with a specificity of 71.43%. The positive rate was higher compared with traditional methods (37.88% vs. 24.39%). The results indicate that mNGS technology is a more sensitive method for detecting suspected infectious encephalitis or meningitis compared with traditional pathogen detection methods.
      PubDate: Thu, 21 Apr 2022 12:20:01 +000
       
  • Correlation Analysis of Magnetic Resonance Imaging Characteristics and
           Prognosis of Invasive Pituitary Adenomas in Neurosurgery Hospitals

    • Abstract: The incidence of pituitary adenoma is second only to glioma and meningioma, and its incidence ranks third among intracranial tumors. Most pituitary adenomas are benign and noninvasive tumors, but invasive pituitary adenomas pose a great threat to human health. In order to explore the risk factors that affect the clinical aggressive behavior of patients with pituitary adenoma, analyze the correlation between different classification methods and clinical aggressive behavior, and lay the foundation for early judgment and individualized treatment of clinical aggressive behavior of patients with pituitary adenoma. We conducted statistical research on patients who were treated for pituitary adenomas in the city’s Yangzhou Hongquan Hospital. The results of the study showed that six patients in this study showed aggressiveness in the clinical symptomatic outcome, six patients showed aggressiveness in the serological outcome, and seven patients showed aggressiveness in imaging. In the multimodal classification, the clinical aggressiveness of pituitary adenomas in the invasion + atypical group was significantly higher than that in other groups, and the difference was statistically significant (). The correlation analysis of magnetic resonance imaging features and prognosis of invasive pituitary adenomas were verified to be feasible for the treatment of patients.
      PubDate: Thu, 21 Apr 2022 10:20:01 +000
       
  • A Study on the Role of Intelligent Medical Simulation Systems in Teaching
           First Aid Competence in Anesthesiology

    • Abstract: Anesthesiology is a subject with strong practicality and application. Undergraduate anesthesiology teaching needs to strike a balance between theoretical knowledge, clinical skill training, and clinical thinking development. Clinical probation and practice are an important part of undergraduate anesthesia teaching. Traditional clinical teaching uses real patients for demonstration and training, but as patients become more self-protective and less cooperative, there are not enough patients for clinical skill training. Simulation is to teach medical scenes in real life under the control of standardized technical guidelines and parameters. Since then, with the rapid development of computer technology, simulation technology and simulation teaching have been greatly developed and are more and more used in clinical teaching, skill evaluation, and scientific research. This study explores the effective methods of clinical teaching in anesthesiology by comparing the effectiveness of traditional teaching methods and simulation teaching methods in undergraduate clinical teaching. It is difficult to combine theory and practice in first aid, which does not allow them to directly receive and deal with emergency medical treatment and resuscitation. In China’s current medical environment and patients’ high demand for medical services, it is imperative to vigorously carry out simulated medical education. In the eastern part of Inner Mongolia, according to the advantages of teaching hospitals, our hospital took the lead in carrying out the simulation education project, which is still in the exploratory stage and not systematic enough. This study will help us to better carry out simulation teaching and improve the clinical skills of medical students in the future. Methods. The student group and class took the advanced simulator training as the experimental group, applied the advanced integrated simulator and other systems of the Norwegian company, referred to the international guidelines for cardiopulmonary resuscitation and cardiovascular first aid in 2005, and practiced in the emergency department during the clinical internship and “emergency clinical simulation training” course. The course includes basic life support, advanced life support, and comprehensive training of CPR (cardiopulmonary resuscitation) and endotracheal intubation. Results. The passing rate of simulated first aid practice was 94.4%; 100% of the students think it is necessary to set up the course, 91% of the students think it is practical, 91% of the students think the course content is reasonable and perfect, and 77%–100% of the students think the course has improved their first aid operation ability, comprehensive application of knowledge, and clinical thinking ability. Conclusion. Carrying out the course of “clinical simulated first aid training” through the advanced simulator system can effectively improve the interns’ clinical first aid operation ability, teamwork ability, and self-confidence, improve the students’ clinical thinking and judgment ability, and improve the service level to patients.
      PubDate: Thu, 21 Apr 2022 08:05:02 +000
       
  • Antitumor Activity of lncRNA NBAT-1 via Inhibition of miR-4504 to Target
           to WWC3 in Oxaliplatin-Resistant Colorectal Carcinoma

    • Abstract: Background. Increasing evidence shows that dysfunction of noncoding RNAs is implicated in cancer. Neuroblastoma associated transcript 1 (NBAT-1) has been identified as a tumor suppressive lncRNA that is aberrantly expressed in cancers. However, the function and the underlying mechanisms of the NBAT-1 in colorectal carcinoma (CRC) remain unknown. Methods. Gene expression was detected by RT-qPCR. The influence of NBAT-1 on CRC was evaluated by the cell counting kit-8 (CCK-8) assay and an in vivo xenograft mouse model. The possible binding of NBAT-1 to miRNAs was predicted via the miRDB online tool and confirmed by a dual-luciferase reporter assay. Protein expression was detected by western blot. Results. NBAT-1 expression was significantly decreased in CRC tissues, especially in patients with oxaliplatin (OXA) resistance. NBAT-1 inhibited OXA-resistant CRC cell proliferation in vitro and tumor growth in vivo. The mechanism study revealed that NBAT-1 functioned as a competing endogenous RNA (ceRNA) of miR-4504. NBAT-1 bound miR-4504 and decreased miR-4504 expression in CRC cells. Furthermore, WW-and-C2-domain-containing protein family member 3 (WWC3) was identified as a target of miR-4504. Downregulation of NBAT-1 promoted miR-4504 expression and reduced the level of WWC3. Inhibition of WWC3 by NBAT-1 depletion inactivated Hippo signalling by inhibiting the phosphorylation of large tumor suppressor kinase 1 (LATS1) and yes-associated protein (YAP). Consistently, knockdown of NBAT-1 suppressed the expression of YAP transcriptional targets. Conclusions. These findings demonstrated that lncRNA NBAT-1 suppresses OXA-resistant CRC cell growth via inhibition of miR-4504 to regulate the WWC3/LATS1/YAP axis.
      PubDate: Thu, 21 Apr 2022 08:05:02 +000
       
  • Construction and Implementation of Procedural Nursing System for General
           Surgery Laparoscopic Surgery Based on Deep Learning

    • Abstract: In order to explore the construction and implementation effect of a procedural nursing system for laparoscopic surgery in general surgery based on deep learning, this article selects 150 cases of laparoscopic surgery patients admitted to our hospital from January 2020 to January 2021 for research. According to the time of enrollment, the control set and the study set were included in order, with 75 cases in each set. The control set was given routine nursing methods, and the research set was given the management of programmed nursing system based on deep learning. The nursing quality, pain, postoperative recovery, and incidence of complications were compared between the two sets. Logistic regression multivariate analysis of the risk factors for postoperative complications in patients undergoing laparoscopic surgery in general surgery was performed. Based on deep learning, the construction of the procedural nursing system for laparoscopic surgery in general surgery is applied to the nursing management of general surgery laparoscopic surgery, which can improve the quality of care and the VAS score of the patient's pain level, and reduce the incidence of complications. Underlying diseases and routine nursing are risk factors for complications of general surgery laparoscopic surgery, suggesting that corresponding prevention and control work should be done in the procedural nursing of general surgery laparoscopic surgery based on deep learning.
      PubDate: Thu, 21 Apr 2022 08:05:02 +000
       
  • Effect of Different Doses of Propofol on Pulmonary Function and
           Inflammatory Response in Patients with Lung Ischemia Reperfusion Injury
           Induced by One-Lung Ventilation Based on Big Data Analysis

    • Abstract: Objective. To analyze the effect of different doses of propofol on pulmonary function and inflammatory response in patients with lung ischemia reperfusion injury (LIRI) induced by one-lung ventilation (OLV) based on big data analysis. Methods. A retrospective study was performed on 105 patients who underwent lobectomy in our hospital (January 2018 to January 2022). According to the doses of propofol, they were split into low-dose group (LDG), middle-dose group (MDG), and high-dose group (HDG), which received the continuous micropump infusion of propofol at the doses of 2 mg/(kg·h), 5 mg/(kg·h), and 10 mg/(kg·h) after induction, respectively, with 35 cases in each group. The indexes, such as the pulmonary function and inflammatory factors of patients, at different times were compared. The logistic regression analysis was performed according to the occurrence of LIRI. Results. With no notable difference at T0 among the three groups (), the Cdyn levels significantly decreased at T1 () and gradually increased at T2. The Cdyn levels at T1 and T2 were remarkably higher in HDG and MDG than in LDG (). With no notable differences at T0 and T1 among the three groups (), the PA-aO2 levels and RI values at T2 in MDG and HDG were lower compared with LDG (). The RI values at T1 and T2 in HDG were higher compared with MDG, with no obvious difference (). The OI levels at T1 and T2 in HDG were lower compared with the other two groups (), and the OI levels at T1, T2, and T3 in LDG were higher compared with MDG, with no obvious difference (). The TNF-α and ICAM-1 levels at T1 and T2 in MDG and HDG were lower compared with LDG, with no obvious difference between MDG and HDG (). Compared with LDG, the MDG and HDG at T1 and T2 had lower MDA levels () and higher SOD levels (). Logistic regression analysis showed that Cdyn, PA-aO2, and OLV time were independent risk factors for LIRI in patients undergoing lobectomy. Conclusion. Propofol has a good protective effect on lung function in patients with OLV-induced LIRI. Appropriately increasing the dose of propofol can effectively improve the local cerebral hypoxia and lung compliance of patients and reduce the inflammatory response and oxidative stress response, with 5 mg/(kg·h) as the clinical reference. Preoperative assessment and preparation should be made for patients, close attention should be paid to risk factors, such as Cdyn and PA-aO2, and OLV time should be controlled.
      PubDate: Thu, 21 Apr 2022 08:05:01 +000
       
  • Knowledge Discovery-Based Analysis of Health Factors of Urinary Infections
           in Elderly Cardiology Inpatients

    • Abstract: A set of semantic similarity calculation methods combining full-text text and domain knowledge topics is proposed for the current study of entity association relations such as disease–gene in medical texts combined with topics in knowledge discovery, which is insufficient to reveal the deep semantic association relations of medical domain knowledge at topic level. Taking urinary infections in elderly inpatients as the research subject, word embedding representation of word vectors and topic vectors is performed by the TWE model, and similarity calculation is performed by combining text and domain knowledge topics based on Siamese Network framework. The urinary microbiological culture results of both groups were dominated by Escherichia coli, accounting for 34.65% and 47.92%, respectively; the use of antimicrobial drugs in the symptomatic urinary infection group was 94.19% higher than that in the asymptomatic bacteriuria group, 77.27% (  = 8.158, ).
      PubDate: Thu, 21 Apr 2022 08:05:01 +000
       
  • Expression and Related Mechanisms of miR-100 and TRIB2 in COPD Patients

    • Abstract: Background. Chronic obstructive pulmonary disease (COPD) is one of the most common chronic respiratory diseases in the world. COPD is a general term for a class of lung diseases, including emphysema, chronic bronchitis, and refractory asthma. It is characterized by irreversible airflow obstruction and chronic tracheal inflammation. Objective. This study aimed to investigate the expression and related mechanisms of miR-100 and TRIB2 in patients with COPD. Methods. We collected the serum of patients admitted to our hospital and healthy volunteers undergoing physical examination at the same time, pulmonary fibroblasts were purchased for the experiments, miR-100 was overexpressed, and TRIB2 expression was inhibited in cells. The miR-100 and TRIB2 expression levels in serum and cells were detected by qRT-PCR and Western blot, cell proliferation and apoptosis were detected by CCK-8 and flow cytometry, and the relationship between miR-100 and TRIB2 was explored by the dual-luciferase report. Results. The miR-100 expression in the serum of the COPD group was expressed normally, while the TRIB2 expression was expressed abnormally . The AUC of serum miR-146a and TRIB2 for COPD diagnosis were 0.965 and 0.954, respectively. Overexpressing miR-100 and inhibiting the TRIB2 expression could decrease cell proliferation and increase apoptosis rate. According to the dual-luciferase report, miR-100 and TRIB2 had a targeted regulatory relationship. Rescue experiments showed that overexpressing TRIB2 could reverse the changes of cell proliferation and apoptosis caused by overexpression of miR-100. Conclusion. miR-100 and TRIB2 were expressed abnormally in serum of COPD patients, and miR-100 could inhibit proliferation of pulmonary fibroblasts and promote their apoptosis.
      PubDate: Thu, 21 Apr 2022 08:05:01 +000
       
 
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