Taking Xiaochaihu Decoction as an example,the application differences of classical prescriptions in modern medical context and Chinese medicine practice are compared and analyzed from the aspects of clinical application scope,understanding of pre-scription connotation,dosage specification,dosage form and decoction method.Strategies to solve the differences in efficacy are pro-posed:integrating the wisdom of classical prescriptions and reshaping the framework of Chinese medicine diagnosis and treatment;transforming the results of modern pharmacology and exploring the principles of classical prescriptions;controlling drug quality stand-ards and exploring new uses and dosages of classical prescriptions;keeping pace with the times in Chinese medicine decoction and strengthening management and control to ensure efficacy.It is believed that combining the essence of Chinese medicine with modern technology can make the application of classical prescriptions maintain traditional characteristics while meeting modern clinical require-ments.This can not only improve the adaptability of classical prescriptions to modern complex diseases,but also provide a reference for the modernization of traditional medicine.

Taking Xiaochaihu Decoction as an example,the application differences of classical prescriptions in modern medical context and Chinese medicine practice are compared and analyzed from the aspects of clinical application scope,understanding of pre-scription connotation,dosage specification,dosage form and decoction method.Strategies to solve the differences in efficacy are pro-posed:integrating the wisdom of classical prescriptions and reshaping the framework of Chinese medicine diagnosis and treatment;transforming the results of modern pharmacology and exploring the principles of classical prescriptions;controlling drug quality stand-ards and exploring new uses and dosages of classical prescriptions;keeping pace with the times in Chinese medicine decoction and strengthening management and control to ensure efficacy.It is believed that combining the essence of Chinese medicine with modern technology can make the application of classical prescriptions maintain traditional characteristics while meeting modern clinical require-ments.This can not only improve the adaptability of classical prescriptions to modern complex diseases,but also provide a reference for the modernization of traditional medicine.

Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.

OBJECTIVE: To explore the implementation effect of hour-1 bundle for sepsis patients based on crisis resource management (CRM) system. METHODS: A historical control study was conducted. The hour-1 bundle for sepsis based on CRM was used to train 24 nurses in the emergency department from October 2022 to March 2023. Clinical data of sepsis patients admitted to the emergency department of the First People's Hospital of Zunyi from April 2022 to September 2023 were collected. The patients were divided into three groups based on different stages of CRM system construction: control group (before construction, from April to September in 2022), improvement group (during construction, from October 2022 to March 2023) and observation group (after construction, from April to September in 2023). The baseline data, implementation rate of hour-1 bundle [including blood culture, antibiotic usage, blood lactic acid (Lac) detection, fluid resuscitation, hypertensors usage], identification and diagnosis time, and prognosis parameters [including correction rate of hypoxemia, intensive care unit (ICU) occupancy rate, and 28-day survival rate]. Sepsis cognition survey and non-technical skill (NTS) evaluation of nurses in emergency department were conducted before and after training. RESULTS: Finally 43 cases were enrolled in the control group, improvement group and observation group, respectively. There was no statistically significant difference in baseline data including the gender, age, primary site, heart rate, systolic blood pressure, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, mechanical ventilation ratio among the three groups with comparability. With the gradual improvement of the CRM system, the implementation rate of 1-hour bundle was gradually increased, and the implementation rate in the control group, improvement group and observation group were 65.12% (28/43), 74.42% (32/43) and 88.37% (38/43), respectively, with statistically significant difference (P < 0.05). It was mainly reflected in the completion rate of blood culture, antibiotic usage rate, Lac detection rate and hypertensors usage rate within 1 hour, which were significantly higher in the observation group than those in the control group [completion rate of blood culture: 90.70% (39/43) vs. 62.79% (27/43), antibiotic usage rate: 88.37% (38/43) vs. 60.47% (26/43), Lac detection rate: 93.02% (40/43) vs. 72.09% (31/43), hypertensors usage rate: 88.37% (38/43) vs. 60.47% (26/43), all P < 0.05]. The fluid resuscitation rates within 1 hour in the three groups were all over 90%, with no statistically significant difference among the three groups. The recognition and diagnosis time in the observation group was significantly shorter than that in the control group and the improvement group (hours: 0.41±0.15 vs. 0.61±0.21, 0.51±0.18, both P < 0.05), the correction rate of hypoxemia and 28-day survival rate were significantly higher than those in the control group [correction rate of hypoxemia: 95.35% (41/43) vs. 74.42% (32/43), 28-day survival rate: 83.72% (36/43) vs. 60.47% (26/43), both P < 0.05], and ICU occupancy rate was significantly lower than that in the control group [72.09% (31/43) vs. 93.02% (40/43), P < 0.05]. After training in the CRM system, the score of the sepsis awareness survey questionnaire for emergency department nurses was significantly increased as compared with before training (60.42±5.29 vs. 44.17±9.21, P < 0.01), and NTS also showed significant improvement. CONCLUSION CRM plays a significant role in promoting the implementation of sepsis hour-1 bundle, which can improve the implementation rate of hour-1 bundle and NTS of medical staff, effectively improve patients' hypoxemia, reduce patients' ICU occupancy rate and 28-day risk of death.
Humans ; Sepsis/therapy* ; Emergency Service, Hospital ; Patient Care Bundles ; Intensive Care Units ; Female ; Male ; Middle Aged

Objective:To explore the clinical characteristics of patients with metastatic gastric tumor and to differentiate them from those with primary malignant gastric tumors.Methods:This study retrospectively analyzed the clinical data of 21 patients with metastatic gastric tumor confirmed by gastroscopy biopsy and pathology.The clinical manifestations,gastroscopy characteristics,pathological results,and the time interval between the diagnosis of primary malignant tumor and the confirmation of gastric metastasis were summarized.Results:The patient primarily exhibited symptoms related to gastric involvement;gastroscopy findings resembled those of primary malignant tumors of the stomach;pathological results were consistent with primary malignant tumors;the time interval between the diagnosis of primary cancer and the confirmation of metastatic gastric tumor varied significantly,ranging from up to 18 years to simultaneous detection.Conclusion:Metastatic gastric tumors are similar to primary malignant tumors of the stomach in terms of clinical manifestations and endoscopic features,making clinical differentiation challenging.The main approach for distinguishing them is based on pathological examination.

Objective:To explore the clinical characteristics of patients with metastatic gastric tumor and to differentiate them from those with primary malignant gastric tumors.Methods:This study retrospectively analyzed the clinical data of 21 patients with metastatic gastric tumor confirmed by gastroscopy biopsy and pathology.The clinical manifestations,gastroscopy characteristics,pathological results,and the time interval between the diagnosis of primary malignant tumor and the confirmation of gastric metastasis were summarized.Results:The patient primarily exhibited symptoms related to gastric involvement;gastroscopy findings resembled those of primary malignant tumors of the stomach;pathological results were consistent with primary malignant tumors;the time interval between the diagnosis of primary cancer and the confirmation of metastatic gastric tumor varied significantly,ranging from up to 18 years to simultaneous detection.Conclusion:Metastatic gastric tumors are similar to primary malignant tumors of the stomach in terms of clinical manifestations and endoscopic features,making clinical differentiation challenging.The main approach for distinguishing them is based on pathological examination.

Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.

Objective To investigate the predictive value of lactate/albumin ratio(LAR),interleukin-6(IL-6)and CD4+T lymphocyte count in 28-day mortality in patients with severe pneumonia and sepsis.Methods A total of 73 patients with severe pneumonia and sepsis admitted to the Respiratory Intensive Care Unit(RICU)of Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2022 to June 2023 were enrolled and divided into the survival group(n=43)and the death group(n=30)according to their 28-day outcomes.The clinical data of the patients were collected from their electronic medical records,including age,gender,comorbidities with hypertension,diabetes,and coronary artery heart disease(CHD),as well as sequential organ failure assessment(SOFA)score,acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score,mean arterial pressure(MAP),confusion,uremia,respiratory rate,blood pressure,age ≥65 years(CURB-65)score,total bilirubin(Tbil),serum creatinine(Scr),platelet count(PLT),white blood cell(WBC)count,procalcitonin(PCT),and C-reactive protein(CRP)at admission to RICU.On the 1st,3rd,and 7th day after admission to RICU,the patients'arterial blood was drawn,and the lactate level was detected by a fully automated blood gas analyzer.The peripheral venous blood was drawn,and the serum albumin and IL-6 levels were detected by enzyme-linked immunosorbent assay,and the CD4+T lymphocyte subset count was measured by flow cytometry.The LAR of patients on the 1st,3rd and 7th day was calculated.The clinical data of the patients and the LAR,IL-6 level and CD4+T lymphocyte count on the 1st,3rd,and 7th day were compared between the two groups.The influencing factors of 28-day mortality in patients with severe pneumonia and sepsis were analyzed by logistic regression,and the predictive value of each influencing factor on the 28-day mortality in patients with severe pneumonia and sepsis was evaluated by the receiver operating characteristic(ROC)curve.Results There was no significant difference in gender,age,proportions of comorbidities with hypertension,diabetes and CHD,length of stay in RICU,and Tbil,MAP,PLT,Scr,WBC,PCT and CRP at admission to RICU(P＞0.05).The APACHE Ⅱ and CURB-65 scores of the patients in the death group were significantly higher than those in the survival group(P＜0.05).On the 1st,3rd and 7th day,the CD4+T lymphocyte count in the death group was significantly lower than that in the survival group,while the SOFA score was significantly higher than that in the survival group(P＜0.05).On the first day,there was no significant difference in the LAR and IL-6 level be-tween the death group and the survival group(P＞0.05).However,on the 3rd and 7th day,the LAR and IL-6 level in the death group were significantly higher than those in the survival group(P＜0.05).The LAR,IL-6 level and SOFA score on the 3rd and 7th day in the survival group were significantly lower than those on the 1st day,and these indicators on the 7th day were sig-nificantly lower than those on the 3rd day(P＜0.05);the CD4+T lymphocyte count on the 3rd and 7th day was significantly higher than that on the 1st day(P＜0.05),while it showed no significant difference on the 7th and 3r day(P＞0.05).The IL-6 level on the 7th day in the death group was significantly lower than that on the 1st and 3rd day(P＜0.05),while there was no significant difference in IL-6 level on the 1st day compared with the 3r day(P＞0.05);moreover,there was no significant difference in LAR,CD4+T lymphocyte count and SOFA score between each time point(P＞0.05).Pearson correlation analy-sis showed that on the 3rd day,the LAR and IL-6 level were significantly positively correlated with the SOFA score in patients with severe pneumonia and sepsis(r=0.385,0.394;P＜0.05).On the 7th day,the LAR and IL-6 level were also significantly positively correlated with the SOFA score(r=0.418,0.402;P＜0.05).On the 3 rd and 7 th day,CD4+T lymphocyte count was significantly negatively correlated with the SOFA score(r=-0.451,-0.454;P＜0.05).Logistic regression analysis showed that the APACHE Ⅱ score,LAR,IL-6 level and CD4+T lymphocyte count on the 3rd day,and the IL-6 level and CD4+T lym-phocyte count on the 7th day were the influencing factors for 28-day mortality in patients with severe pneumonia and sepsis(P＜0.05).The ROC curve showed that the APACHE Ⅱ score,LAR,IL-6 level and CD4+T lymphocyte count on the 3rd day and the combination of the three,IL-6 level and CD4+T lymphocyte count on the 7th day and the combination of the two had certain predictive value for the 28-day mortality in patients with severe pneumonia and sepsis(P＜0.05).The area under the ROC curve(AUC)of LAR,IL-6 level and CD4+T lymphocyte count on the 3rd day combined to predict 28-day mortality in patients with severe pneumonia and sepsis was 0.891,and the AUC of APACHE Ⅱ score for predicting 28-day mortality in pa-tients with severe pneumonia and sepsis was 0.769.The AUC values of LAR,IL-6 level and CD4+T lymphocyte count on the 3rd day for predicting 28-day mortality in patients with severe pneumonia and sepsis were 0.795,0.757 and 0.770,respective-ly,and the AUC values of IL-6 level and CD4+T lymphocyte count on the 7th day and their combination for predicting 28-day mortality in patients with severe pneumonia and sepsis were 0.743,0.802 and 0.888,respectively.Conclusion The 3-day LAR,IL-6 level and CD4+T lymphocyte count,and the 7-day IL-6 level and CD4+T lymphocyte count after admission are re-lated to the 28-day mortality in patients with severe pneumonia and sepsis.The combined LAR,IL-6 level and CD4+T lympho-cyte count on the 3rd day can better assess the severity and prognosis of patients.

ObjectiveThis study aims to explore risk factors for the development of major adverse cardiovascular and cerebrovascular events （MACCEs） in middle-aged and elderly patients with type 2 diabetes mellitus complicated with stable angina pectoris （T2DM-SAP） based on real-world clinical data in traditional Chinese medicine （TCM）， so as to develop a COX proportional risk prediction model and visualize the predicted results using a nomogram. MethodBased on the clinical scientific research information sharing system， the medical records of 586 T2DM-SAP patients （45-94 years old） were collected from January 2012 to December 2019， including age， gender， course of disease， major medical history， laboratory examination， tongue image， pulse image， TCM syndrome， and major treatment drugs. MACCE outcome indicators of patients were obtained by telephone follow-up and re-hospitalization records. The data was divided into a training set and a validation set according to 7∶3. In the training set， COX univariate analysis was used to determine the risk factors for MACCE in T2DM-SAP patients， and then variables were screened by forward-backward stepwise regression method， so as to establish a MACCE risk prediction model and construct a nomogram. The predictive efficacy of the model was reflected by the C-index， receiver operating characteristic （ROC） curve， calibration map， and clinical decision curve. ResultThe history of cerebrovascular disease ［Hazard ratio （HR）=1.983， 95% confidence interval （CI，1.314-2.993）］， low-density lipoprotein （LDL-C/mmol·L^-1）≥4.1［HR=2.683， 95%CI（1.461-4.925）］， dull red tongue ［HR=1.955， 95%CI（1.273-3.002）］， dull purple tongue ［HR=4.214， 95%CI（2.017-8.803）］， white thick coating ［HR=3.030， 95%CI（1.634-9.293）］， thin and weak pulse ［HR=2.233， 95%CI（1.283-3.888）］， and syndrome of wind-phlegm blocking collaterals ［HR=2.007， 95%CI（1.179-3.418）］ were found to be risk factors in middle-aged and elderly T2DM-SAP patients. Insulin ［HR=0.604， 95%CI（0.399-0.914）］， glycosidase inhibitor ［HR=0.627， 95%CI（0.409-0.962）］， and TCM treatment ［HR=0.328， 95%CI（0.214-0.503）］ were protective factors in middle-aged and elderly T2DM-SAP patients. The prediction model was constructed based on the above risk factors. The C-index of the model was 0.818 （95% CI 0.777 -0.859） in the training set and 0.814 （95% CI 0.773-0.855） in the validation set， and the change of C-index over time was plotted. The AUC of patients for 5， 10， 15 years in the training set was 0.71， 0.67， and 0.61. The AUC of patients for 5， 10， and 15 years in the validation set was 0.60， 0.68， and 0.63， respectively. The calibration map and clinical decision curves of 5， 10， 15 years were drawn in the training set and the validation set， respectively. The model was well calibrated and clinically effective. ConclusionThe history of cerebrovascular disease， LDL， dull red tongue， dull purple tongue， white thick coating， thin and weak pulse， and syndrome of wind-phlegm blocking collaterals are risk factors for MACCE in middle-aged and elderly T2DM-SAP patients， and insulin， glycosidase inhibitors， TCM treatment are protective factors for MACCE in middle-aged and elderly T2DM-SAP patients. A clinical prediction model is established accordingly. This model has good discrimination， calibration degree， and clinical effectiveness and provides a scientific basis for the prevention and treatment of MACCE in middle-aged and elderly T2DM-SAP patients.

The amount of data generated by the human experience in medical cases of classic formulas is large and the research value is high， but how to extract valuable information from these massive data is an important problem of researches on classical formulas. It is concluded that there are many problems in the current study of human experience in classical formulas， such as large amount of data， uneven quality， weak extrapolation and clinical application， which seriously affected the evidence strength of human experience in classical formulas and the contribution to experience accumulation and theoretical support. Therefore， from the structural perspective of the research questions， this paper proposed the research ideas of human experience in medical cases of classic formulas： firstly， according to the characteristics of traditional Chinese medicine （TCM） cases， based on the PICO model， which refers parti-cipants （P）， intervention （I）， comparisons （C）， and outcomes （O）， a TCM medical record evaluation tool in line with the evidence-based concept was constructed to evaluate the quality of medical cases； secondly， constructing a standardized database of human experience in classical formulas and using data mining algorithms to explore the deep relationship hidden in human experience； finally， the clinical value evaluation is carried out to verify the effectiveness of the diagnosis and treatment rules of classical formulas to achieve clinical transformation.