A Prediction Modeling Based on the Hospital for Special Surgery (HSS) Knee Score for Poor Postoperative Functional Prognosis of Elderly Patients with Patellar Fractures

Ying, Chenting; Guo, Chenyang; Wang, Zhenlin; Chen, Yiming; Sun, Jiahui; Qi, Xin; Chen, Yisheng; Tao, Jie

doi:10.1155/2021/6620504

Cited by 15 publications

(15 citation statements)

References 53 publications

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“…DEmiRNAs associated with BPD and those involved in the ceRNA network were used to establish a diagnostic prediction model. Along with the R language software, several machine-learning models were used to predict diagnosis, including support vector machine recursive feature elimination (SVM-RFE), lasso regression, and logistic regression analysis as previous researches [ 21 – 23 ]. We used the SVM-RFE model to evaluate the number of diagnosis-related DEmiRNAs and subsequently analysed their predictive power based on the area under the curve (AUC) values.…”

Section: Methodsmentioning

confidence: 99%

Functional Analysis of Bronchopulmonary Dysplasia-Related Neuropeptides in Preterm Infants and miRNA-Based Diagnostic Model Construction

Zhang¹,

Kong

Zhang³

et al. 2022

Computational and Mathematical Methods in Medicine

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Background. Bronchopulmonary dysplasia (BPD) has a high mortality rate. This study was aimed at identifying and analysing the risk factors associated with BPD using bioinformatic and mechanical analyses and establishing a predictive model to assess the risk of BPD in preterm infants. Methods. We identified differentially expressed RNAs via the intersection of miRNAs between datasets. Online analysis tools were used to predict genes targeted by differentially expressed miRNAs (DEmiRNAs) and to generate and visualise competing endogenous RNA (ceRNA) coexpression networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed on the DEmiRNAs. In addition, an intersection analysis was performed on mRNA and neuropeptide-related genes in the ceRNA network. DEmiRNAs associated with BPD and those involved in ceRNA networks were used to establish a diagnostic prediction model. The GSE108604 dataset was used as a validation set to verify the model. Results. A total of 26 DEmiRNAs were identified from the tracheal aspirates (TAs) of patients with BPD and healthy controls. In addition, a total of 1076 DEmRNAs were obtained from the GSE8586 dataset. Functional enrichment analysis of DEmRNAs revealed an abnormal reduction in mitochondrial-related activity and cellular responses to oxidative stress in patients with BPD. The neuropeptide-related genes OPRL1 and NPPA were found to be upregulated in BPD samples. Eventually, hsa-miR-1258, hsa-miR-298, hsa-miR-483-3p, and hsa-miR-769-5p were screened out and used to establish the prediction model. Calibration curves and detrended correspondence analysis (DCA) revealed that the model had good clinical applicability. Conclusions. The prediction model provided a simple method for individualised assessment, early diagnosis, and prevention of BPD risk in preterm infants.

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Section: Methodsmentioning

confidence: 99%

Functional Analysis of Bronchopulmonary Dysplasia-Related Neuropeptides in Preterm Infants and miRNA-Based Diagnostic Model Construction

Zhang¹,

Kong

Zhang³

et al. 2022

Computational and Mathematical Methods in Medicine

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“…The model was evaluated by plotting the receiver operating characteristic (ROC) curves. A logistic regression model was used to screen for risk factors associated with MTC transfer, and a nomogram model was constructed using the rms package as previous researches [19][20][21][22]. Both internal and external validations were performed with the original data from the training and validation sets, and the ROC curves were plotted using the rms package.…”

Section: Discussionmentioning

confidence: 99%

Preoperative Serum Calcitonin Level and Ultrasonographic Characteristics Predict the Risk of Metastatic Medullary Thyroid Carcinoma: Functional Analysis of Calcitonin-Related Genes

Fan¹,

Lv³

et al. 2022

Disease Markers

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Background. Early cervical lymph node (LN) metastasis is an important cause of poor survival in patients with medullary thyroid cancer (MTC). This study evaluated whether the preoperative serum calcitonin level in combination with ultrasonographic features of MTC can be used to assess the LN status as well as predict the risk of metastasis in patients with MTC. Methods. We retrospectively analyzed the clinical data of 95 patients with MTC, and a nomogram model was constructed and validated. Using integrated database analysis of The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), we mined pathways wherein CALCA is involved, identified calcitonin-related genes, and analyzed their functions. Results. Correlation analysis revealed a significant association between the infiltrating range, diameter, calcification, blood flow, the preoperative serum calcitonin level, and metastasis. The metastasis risk-prediction model showed great accuracy in determining the risk of metastasis in MTC (area under the curve of the receiver operating characteristic [ROC] curve: 0.979 [95% confidence interval 0.946–1.000]). Decision curve analysis (DCA) showed that the model has excellent clinical utilization potential. Significantly, CALCA, the mRNA for calcitonin, was highly expressed in thyroid cancer tissues and associated with the cytokine–cytokine receptor and neuroactive ligand-receptor interaction pathways as well as the cell-adhesion molecules. ROC curve indicated that the CNTFR, CD27, GDF6, and TSLP genes, which are related to the cytokine–cytokine receptor interaction pathway, could indicate the risk of metastasis in MTC. Conclusions. The preoperative serum calcitonin level, in combination with ultrasonographic features, can be used to predict the risk of metastasis in patients with MTC and constitute a noninvasive accurate method for preoperative diagnosis of MTC.

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“…Based on the neural network prediction model, we constructed a new logistic regression-based AD risk prediction model in order to provide a visual basis for the formulation of exercise prescription. Factors with p -values < 0.05 were further screened and used to construct a column line graph prediction model, as described previously ( Chen et al, 2020 ; Ying et al, 2021 ; Zhou et al, 2021 ). The GSE44770 dataset was used as an external dataset to validate the findings.…”

Section: Methodsmentioning

confidence: 99%

Potential Mechanism Underlying Exercise Upregulated Circulating Blood Exosome miR-215-5p to Prevent Necroptosis of Neuronal Cells and a Model for Early Diagnosis of Alzheimer’s Disease

Chen

Sun

Luo

et al. 2022

Front. Aging Neurosci.

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Exercise is crucial for preventing Alzheimer’s disease (AD), although the exact underlying mechanism remains unclear. The construction of an accurate AD risk prediction model is beneficial as it can provide a theoretical basis for preventive exercise prescription. In recent years, necroptosis has been confirmed as an important manifestation of AD, and exercise is known to inhibit necroptosis of neuronal cells. In this study, we extracted 67 necroptosis-related genes and 32 necroptosis-related lncRNAs and screened for key predictive AD risk genes through a random forest analysis. Based on the neural network Prediction model, we constructed a new logistic regression-based AD risk prediction model in order to provide a visual basis for the formulation of exercise prescription. The prediction model had an area under the curve (AUC) value of 0.979, indicative of strong predictive power and a robust clinical application prospect. In the exercise group, the expression of exosomal miR-215-5p was found to be upregulated; miR-215-5p could potentially inhibit the expressions of IDH1, BCL2L11, and SIRT1. The single-cell SCENIC assay was used to identify key transcriptional regulators in skeletal muscle. Among them, CEBPB and GATA6 were identified as putative transcriptional regulators of miR-215. After “skeletal muscle removal of load,” the expressions of CEBPB and GATA6 increased substantially, which in turn led to the elevation of miR-215 expression, thereby suggesting a putative mechanism for negative feedback regulation of exosomal homeostasis.

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A Prediction Modeling Based on the Hospital for Special Surgery (HSS) Knee Score for Poor Postoperative Functional Prognosis of Elderly Patients with Patellar Fractures

Cited by 15 publications

References 53 publications

Functional Analysis of Bronchopulmonary Dysplasia-Related Neuropeptides in Preterm Infants and miRNA-Based Diagnostic Model Construction

Functional Analysis of Bronchopulmonary Dysplasia-Related Neuropeptides in Preterm Infants and miRNA-Based Diagnostic Model Construction

Preoperative Serum Calcitonin Level and Ultrasonographic Characteristics Predict the Risk of Metastatic Medullary Thyroid Carcinoma: Functional Analysis of Calcitonin-Related Genes

Potential Mechanism Underlying Exercise Upregulated Circulating Blood Exosome miR-215-5p to Prevent Necroptosis of Neuronal Cells and a Model for Early Diagnosis of Alzheimer’s Disease

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