Objective To propose strategies for developing clinical predictive models,aiming to assist researchers in conducting standardized clinical prediction model studies.Methods Literature review was conducted to summarize the operational steps and content for developing clinical predictive models.Then,a methodological framework was summarized and refined through expert consultation.Results The 11-step methodological framework for developing clinical predictive models was obtained by synthesizing the experience of 456 clinical predictive modeling studies and expert consultation,and the details were analyzed and elaborated.Conclusions This study presents methodological strategies and recommendations for the development of clinical predictive models,intended to serve as a guide for researchers.

Objective To construct and validate a risk prediction model for poor inhalation in chronic obstructive pulmonary disease(COPD)patients receiving inhaler therapy,providing a decision support tool for personalized prevention of poor inhalation.Methods A cross-sectional study was conducted to collect data related to COPD patients receiving inhaler therapy,forming a dataset.The dataset was randomly divided into a training set and a test set in a ratio of 4∶1.Four different methods for missing value imputation,3 methods for variable feature selection,and 18 machine learning algorithms were employed to successfully construct 216 models on the training set.The monte carlo simulation method was used for resampling in the test set to validate the models,with the area under curve(AUC),accuracy,precision,recall,and F1 score used to evaluate model performance.The optimal model was selected to build the poor inhalation prediction platform.Results A study involving 308 patients with COPD found that 135(43.8%)were at risk of adverse inhalation.Using 33 predictor variables,216 risk prediction models were developed.Of these models,the ensemble learning algorithm yielded the highest average AUC of 0.844,with a standard deviation of 0.058[95%CI=(0.843,0.845)].The differences in predictive performance among the 216 models were statistically significant(P＜0.01).Under the ensemble learning algorithm,adherence to inhaler use(38.087 4%),inhaler satisfaction(25.680 1%),literacy(24.031 3%),number of inhalers(5.482 3%),age(4.204 5%)and number of acute exacerbations in the past year(2.184 7%)contributed most to the predictive model.The model exhibited superior performance,with an AUC of 0.869 3,an accuracy of 83.87%,a precision of 86.96%,a recall of 74.07%,and an F1 score of 0.8.Conclusion This study has developed a predictive model for poor inhalation risk in COPD inhaler therapy patients using machine learning algorithms,which exhibits strong predictive capabilities and holds potential clinical application value.

In order to understand the prevalence of Akabane disease(AKAD)in Guizhou Province and the molecular characteristics of the isolates,the whole-genome sequence of a strain of Akabane virus(AKAV)from a bovine AKAD-positive sample was determined and analyzed.The genotype and genetic variation of the strain were also explored.Based on the conserved S sequence,a fluores-cence quantitative PCR(qPCR)detection method was established and applied for the investigation of AKAV infection status in four large-scale beef cattle farms of Guizhou.Results showed that the S,M and L fragments of the bovine strain were highly homologous to the Tianjin strain(TJ2016/China/2016)and the Australian strain(JaLAB39/Australia/1959),where they were in the same evolutionary branch and belonged to genotype Ⅱ.Sensitivity assay found that the lowest detection limit was 2.5 X 101 copies/μL.Specificity assay showed the established method detected only AKAV with no amplification on bovine bluetongue virus(BLUV),Pasteurella multocida(PM),bovine infectious rhinotracheitis virus(IBRV)and bovine Mycoplasma bovis.The variation coefficients of inter-and intra batches in the repeatability test were both lower than 2.26％.These findings illus-trated that the established qPCR method had high sensitivity,good specificity and repeatability.A total of 298 serum samples from 4 large-scale beef cattle farms in Qianxi City and Huangping County of Guizhou Province were collected and tested for AKAV by the method.Out of 298 sam-ples,25 positive samples(25/298)were detected as positive with a positive rate of 8.39％.In sum-mary,this work provided the reference data for a deep understanding of the molecular prevalence of AKAV in Guizhou Province and laid foundation for the prevention and control of AKAD.

Objective:To evaluate the predictive value of a risk prediction model guided by the ratio of respiratory rate to diaphragm thickening fraction (RR/DTF) for noninvasive-invasive mechanical ventilation transition timing in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), through ultrasound evaluation of diaphragm movement indicators.Methods:Sixty-four patients diagnosed with AECOPD and undergoing non-invasive ventilation (NIV), who were admitted to the department of critical care medicine of the First Affiliated Hospital of Jinzhou Medical University from January 2022 to July 2023 were enrolled. They were divided into NIV successful group and NIV failure group based on the outcome of NIV within 24 hours. Clinical indicators such as RR/DTF, diaphragmatic excursion (DE), tidal volume (VT), respiratory rate (RR), pH value, partial pressure of carbon dioxide (PaCO 2), and sputum excretion disorder were compared between the two groups after 2 hours of NIV. The factors influencing NIV failure were included in binary Logistic regression analysis, and an RR/DTF oriented risk prediction model was established. Receiver operator characteristic curve (ROC curve) analysis was used to assess the predictive value of this model for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients. Results:Among 64 patients with AECOPD, with 43 in the NIV successful group and 21 in the NIV failure group. There were no statistically significant differences in baseline data such as age, gender, body mass index (BMI), oxygenation index (P/F), smoking history, and acute physiological and chronic health evaluation Ⅱ (APACHEⅡ) between the two groups of patients, indicating comparability. Compared to the NIV successful group, the NIV failure group showed a significantly increase in RR/DTF, RR, PaCO 2, and sputum retention, while VT and DE were significantly decreased [RR/DTF (%): 1.00±0.18 vs. 0.89±0.22, RR (bpm): 21.64±3.13 vs. 19.62±2.98, PaCO 2 (mmHg, 1 mmHg≈0.133 kPa): 70.82±8.82 vs. 65.29±9.47, sputum retention: 57.1% vs. 30.2%, VT (mL): 308.09±14.89 vs. 324.48±23.82, DE (mm): 19.91±2.94 vs. 22.05±3.30, all P < 0.05]. Binary Logistic regression analysis showed that RR/DTF [odds ratio ( OR) = 147.989, 95% confidence interval (95% CI) was 3.321-595.412, P = 0.010], RR ( OR = 1.296, 95% CI was 1.006-1.670, P = 0.045), VT ( OR = 0.966, 95% CI was 0.935-0.999, P = 0.044), PaCO 2 ( OR = 1.086, 95% CI was 1.006~1.173, P = 0.035), and sputum retention ( OR = 4.533, 95% CI was 1.025-20.049, P = 0.046) were independent risk factors for predicting NIV failure in AECOPD patients. ROC curve analysis showed that the area under the curve (AUC) of 0.713 with a 95% CI of 0.587-0.839 ( P = 0.005). The sensitivity was 72.73%, the specificity was 88.10%, the Youden index was 0.394, and the optimal cut-off value was 0.87. Conclusion:The RR/DTF risk prediction model has good predictive value for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients.

OBJECTIVES: Shelter hospital was an alternative way to provide large-scale medical isolation and treatment for people with mild coronavirus disease 2019 (COVID-19). Due to various reasons, patients admitted to the large shelter hospital was reported high level of psychological distress, so did the healthcare workers. This study aims to introduce a comprehensive and multifaceted psychosocial crisis intervention model. METHODS: The psychosocial crisis intervention model was provided to 200 patients and 240 healthcare workers in Wuhan Wuchang shelter hospital. Patient volunteers and organized peer support, client-centered culturally sensitive supportive care, timely delivery of scientific information about COVID-19 and its complications, mental health knowledge acquisition of non-psychiatric healthcare workers, group activities, counseling and education, virtualization of psychological intervention, consultation and liaison were exhibited respectively in the model. Pre-service survey was done in 38 patients and 49 healthcare workers using the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Patient Health Questionnaire 2-item (PHQ-2) scale, and the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (PC-PTSD-5). Forty-eight healthcare workers gave feedback after the intervention. RESULTS: The psychosocial crisis intervention model was successfully implemented by 10 mental health professionals and was well-accepted by both patients and healthcare workers in the shelter hospital. In pre-service survey, 15.8% of 38 patients were with anxiety, 55.3% were with stress, and 15.8% were with depression; 16.3% of 49 healthcare workers were with anxiety, 26.5% were with stress, and 22.4% were with depression. In post-service survey, 62.5% of 48 healthcare workers thought it was very practical, 37.5% thought more practical; 37.5% of them thought it was very helpful to relief anxiety and insomnia, and 27.1% thought much helpful; 37.5% of them thought it was very helpful to recognize patients with anxiety and insomnia, and 29.2% thought much helpful; 35.4% of them thought it was very helpful to deal with patients' anxiety and insomnia, and 37.5% thought much helpful. CONCLUSIONS Psychological crisis intervention is feasible, acceptable, and associated with positive outcomes. Future tastings of this model in larger population and different settings are warranted.
Humans ; COVID-19 ; Sleep Initiation and Maintenance Disorders ; Crisis Intervention ; Psychosocial Intervention ; SARS-CoV-2 ; Mental Health ; Depression/epidemiology* ; Health Personnel/psychology* ; Anxiety/etiology*

Objective:To establish a risk prediction model dominated by diaphragm thickening fraction (DTF) and intra-abdominal pressure (IAP) monitoring, and to explore the predictive value of the model for weaning failure in patients with severe acute pancreatitis (SAP).Methods:A prospective research was conducted. Sixty-three patients undergoing invasive mechanical ventilation treatment who diagnosed with SAP admitted to intensive care unit of the First Affiliated Hospital of Jinzhou Medical University from August 2020 to October 2021 were enrolled. The spontaneous breathing trial (SBT) was carried out when the clinical weaning criteria was met. The stable cardiovascular status, good pulmonary function, no chest and abdominal contradictory movement, and adequate oxygenation were defined as successful weaning. Otherwise, it was defined as failure weaning. The clinical indicators such as SBT 30-minure DTF, IAP, tidal volume (VT), respiratory rate (RR), body mass index (BMI), and blood lactic acid (Lac) were compared between the weaning success group and the weaning failure group. The indicators with statistically significant differences in the single-factor analysis were included in the secondary multivariable Logistic regression analysis to establish a risk prediction model. The correlation between the DTF and IAP at 30 minutes of SBT was analyzed. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of the risk prediction model for SAP patient withdrawal failure at 30 minutes of SBT.Results:Finally, 63 patients with SAP were enrolled. Among the 63 patients, 42 were successfully weaned and 21 failed. There were no significant differences in age, gender, and oxygenation index (PaO 2/FiO 2), sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score at admission between the two groups, indicating that the data in the two groups were comparable. Compared with the weaning success group, IAP, RR, BMI and Lac at 30 minutes of SBT in the weaning failure group were significantly increased [IAP (mmHg, 1 mmHg≈0.133 kPa): 14.05±3.79 vs. 12.12±3.36, RR (times/min): 25.43±8.10 vs. 22.02±5.05, BMI (kg/m 2): 23.71±2.80 vs. 21.74±3.79, Lac (mmol/L): 5.27±1.69 vs. 4.55±1.09, all P < 0.05], while DTF and VT were significantly decreased [DTF: (29.76±3.45)% vs. (31.86±3.67)%, VT (mL): 379.00±98.74 vs. 413.60±33.68, both P < 0.05]. Secondary multivariable Logistic regression analysis showed that DTF [odds ratio ( OR) = 0.758, 95% confidence interval (95% CI) was 0.584-0.983, P = 0.037], IAP ( OR = 1.276, 95% CI was 1.025-1.582, P = 0.029), and RR ( OR = 1.145, 95% CI was 1.014-1.294, P = 0.029) were independent risk factors for SBT withdrawal failure in 30 minutes in SAP patients. The above risk factors were used to establish the risk prediction model of aircraft withdrawal failure at 30 minutes of SBT: Logit P = -0.237-0.277×DTF+0.242×IAP+0.136×RR. Pearson correlation analysis showed that SBT 30-minute DTF was significantly correlated with IAP in SAP patients, and showed a significant positive correlation ( r = 0.313, P = 0.012). The ROC curve analysis results showed that area under the ROC curve (AUC) of the risk prediction model for SAP patient withdrawal failure at 30 minutes of SBT was 0.716, 95% CI was 0.559-0.873, P = 0.003, with the sensitivity of 85.7% and the specificity of 78.6%. Conclusions:DTF, IAP and RR were independent risk factors for SBT withdrawal failure in 30 minutes in SAP patients. The DTF and IAP monitoring-oriented risk prediction model based on the above three variables has a good predictive value for weaning failure in patients with SAP.

Unlike healthy, non-transformed cells, the proteostasis network of cancer cells is taxed to produce proteins involved in tumor development. Cancer cells have a higher dependency on molecular chaperones to maintain proteostasis. The chaperonin T-complex protein ring complex (TRiC) contains eight paralogous subunits (CCT1-8), and assists the folding of as many as 10% of cytosolic proteome. TRiC is essential for the progression of some cancers, but the roles of TRiC subunits in osteosarcoma remain to be explored. Here, we show that CCT4/TRiC is significantly correlated in human osteosarcoma, and plays a critical role in osteosarcoma cell survival. We identify a compound anticarin-β that can specifically bind to and inhibit CCT4. Anticarin-β shows higher selectivity in cancer cells than in normal cells. Mechanistically, anticarin-β potently impedes CCT4-mediated STAT3 maturation. Anticarin-β displays remarkable antitumor efficacy in orthotopic and patient-derived xenograft models of osteosarcoma. Collectively, our data uncover a key role of CCT4 in osteosarcoma, and propose a promising treatment strategy for osteosarcoma by disrupting CCT4 and proteostasis.

Coagulometer, known as blood coagulation analyzer, is a product that can provide accurate test results for medical diagnosis and treatment analysis by detecting a series of items closely related to thrombosis and hemostasis in coagulation reaction. On the basis of previous traditional methods, and with our deep understanding about the principles of hemagglutination detection, we propose a hemagglutination detection method by using the dual-magnetic circuit beads method. Then, the corresponding hemagglutination detection module is designed. The coagulation time of plasma can be measured by detecting the movement of the magnetic beads when the magnetic field intensity is appropriate. The activated partial thromboplastin time(APTT) of plasma is tested when the most suitable magnetic field intensity is found. The results preliminarily show that this blood coagulation test method is valid and the corresponding test module has a potential value in business.
Blood Coagulation ; Blood Coagulation Tests ; Magnetic Phenomena ; Magnetics ; Partial Thromboplastin Time

Objective:To investigate the expressions of miR-20a-5p and lysine (K) demethylase 6B (KDM6B) in osteosarcoma tissues and the effects of miR-20a-5p targeting KDM6B on the proliferation, migration and invasion of osteosarcoma cells and tumor growth.Methods:The clinicopathological and paracancerous tissues of 20 patients with osteosarcoma admitted to the First Affiliated Hospital of Chinese Medical University from January 2017 to March 2019 were collected. Quantitative real-time PCR (qRT-PCR) was used to detect the expression levels of miR-20a-5p and KDM6B mRNA in tissues. The osteosarcoma MG63 cells were divided into control group, mimic NC group, miR-20a-5p mimic group, and NC+ empty vector group, miR-20a-5p+ empty vector group, miR-20a-5p+ KDM6B group. The expression levels of miR-20a-5p and KDM6B mRNA of all groups were detected by qRT-PCR. Western blotting was used to detect the expression level of KDM6B. CCK-8 assay, cell scratch test and Transwell test were used to detect cell proliferation, migration and invasion ability. According to the random number table method, nude mice were divided into NC+ empty vector group, miR-20a-5p+ empty vector group and miR-20a-5p+ KDM6B group, with 5 mice in each group. Tumor growth ability was detected by tumor xenograft nude mouse models.Results:The relative expression level of miR-20a-5p mRNA in osteosarcoma tissues was 0.55±0.27, and that in paracancerous tissues was 1.22±0.28, with a statistically significant difference ( t=7.701, P<0.001). The relative expression level of KDM6B mRNA in osteosarcoma tissues was 1.66±0.19, and that in paracancerous tissues was 1.00±0.15, with a statistically significant difference ( t=12.219, P<0.001). After transfection of miR-20a-5p, KDM6B mRNA and protein expression levels decreased with the increase of miR-20a-5p expression level. After miR-20a-5p transfection for 48 h, the cell proliferation abilities of the blank control group, mimic NC group and miR-20a-5p mimic group were 0.83±0.04, 0.81±0.03 and 0.52±0.01 ( F=89.655, P<0.001), compared with the blank control group and mimic NC group, the cell proliferation ability was significantly inhibited in the miR-20a-5p mimic group (both P<0.001). The cell proliferation abilities of NC+ empty vector group, miR-20a-5p+ empty vector group and miR-20a-5p+ KDM6B group were 0.83±0.05, 0.52±0.01 and 0.67±0.05 ( F=43.919, P<0.001), compared with the NC+ empty vector group, the cell proliferation ability was significantly inhibited in the miR-20a-5p+ empty vector group ( P<0.001); compared with the miR-20a-5p+ empty vector group, the cell proliferation ability of miR-20a-5p+ KDM6B group increased significantly ( P<0.001). The scratch healing rates of the blank control group, mimic NC group and miR-20a-5p mimic group were (32.51±2.73)%, (30.26±3.22)% and (13.52±1.77)% ( F=46.314, P<0.001), compared with the control group and the mimic NC group, the scratch healing rate of the miR-20a-5p mimic group was significantly decreased (both P<0.001). The scratch healing rates of NC+ empty vector group, miR-20a-5p+ empty vector group and miR-20a-5p+ KDM6B group were (31.34±3.11)%, (12.15±1.64)% and (28.93±2.89)% ( F=47.511, P<0.001), compared with the NC+ empty vector group, the scratch healing rate of the miR-20a-5p+ empty vector group was significantly decreased ( P<0.001); compared with the miR-20a-5p+ empty vector group, the scratch healing rate of miR-20a-5p+ KDM6B group was significantly increased ( P=0.001). The numbers of transmembrane cells in the blank control group, mimic NC group and miR-20a-5p mimic group were 114±16, 108±11 and 42±6 ( F=36.282, P<0.001), compared with the control group and mimic NC group, the number of transmembrane cells of the miR-20a-5p mimic group was significantly decreased (both P<0.001). The numbers of transmembrane cells in the NC+ empty vector group, miR-20a-5p+ empty vector group and miR-20a-5p+ KDM6B group was 143±11, 39±4 and 139±12 ( F=112.120, P<0.001), compared with the NC+ empty vector group, the number of transmembrane cells of the miR-20a-5p+ empty vector group was significantly decreased ( P<0.001); compared with the miR-20a-5p+ empty vector group, the number of transmembrane cells of the miR-20a-5p+ KDM6B group was increased significantly ( P<0.001). The tumor volumes of mice for 21 d in the NC+ empty vector group, miR-20a-5p+ empty vector group and miR-20a-5p+ KDM6B group were (1 667.50±250.40) mm 3, (129.20±21.00) mm 3 and (775.41±77.51) mm 3 respectively, with a statistically significant difference ( F=77.651, P<0.001). The tumor weights of the 3 groups were (1.35±0.18) g, (0.12±0.01) g and (0.61±0.03) g respectively, with a statistically significant difference ( F=104.191, P<0.001). Conclusion:The expression of miR-20a-5p is significantly decreased in osteosarcoma tissues, and the expression of KDM6B is significantly increased in osteosarcoma tissues. Overexpression of miR-20a-5p may inhibit the proliferation, migration and invasion of osteosarcoma cells and tumor growth by targeting to reduce the expression of KDM6B.

Objective:To investigate the understanding of microsurgery education for clinical medical students, and the education methods for microsurgery courses in 8 schools.Methods:The questionnaire was designed around four aspects: the learning status of Chinese medical students in microsurgery learning, the impact of microsurgery learning on future career choices, the current situation of opening microsurgery courses in 8 medical schools, and the opinions and suggestions on improving microsurgery learning in China. Electronic and paper questionnaires were combined to evaluate the condition of understanding microsurgery among 1 000 medical students from Peking University Health Science Center and other 7 schools. Then, the validity of the collected questionnaires was reviewed. SPSS 19.0 were applied for data analysis.Results:A total of 808 valid questionnaires were collected (recovery rate=80.8%). Respondents' understanding of microsurgery remained at the level of "just heard" (2.18±2.83), and 98.41% (795/808) of the students believed that microsurgery related disciplines would bring certain help to their future careers. Male students more recognized the impact of microsurgery learning on future career than female students [(6.19±2.36) vs. (5.76±2.09), P< 0.05)]. In these 8 investigated universities, only Shanghai Jiao Tong University School of Medicine and Zhongshan School of Medicine of Sun Yat-sen University conducted a microsurgery course, while 80.01% (531/663) of the students in the other 6 universities wanted to set microsurgery courses. Microsurgery operation observation (86.82%, 701/808), animal models for microsurgery practical training (82.95%, 670/808), and online theory courses (43.18%, 349/808) were able to increase the interest in microsurgery learning for students. Conclusion:Microsurgery course can bring many benefits to medical students, and it is urgent for domestic medical colleges to carry out microsurgery related courses.