BackgroundPostoperative cognitive dysfunction （POCD） is a common complication in elderly patients after surgery， and has a great impact on postoperative rehabilitation of patients. ObjectiveTo explore the effect of mindfulness-based therapy on cognitive function and sleep quality in elderly patients after surgery under local anesthesia， so as to provide references for reducing their incidence risk of POCD and improving sleep quality. MethodsThe simple random sampling method was utilized to select 78 elderly patients who underwent surgery under local anesthesia in The Third Hospital of Mianyang from March 2022 to March 2023. Participants were assigned into study group and control group， each with 39 cases. All patients were subjected to conventional treatment and nursing interventions， and study group added mindfulness-based therapy on this basis. Mini-Mental State Examination （MMSE） was administered to patients on 1 day before surgery， and on the 1^st， 3^rd and 5^th day after surgery. Pittsburgh Sleep Quality Index （PSQI） was employed on 1 day before surgery and on the 3^rd day after surgery. ResultsMMSE scores revealed a significant time effect， group effect and time×group interaction effect （F=78.251， 197.071， 371.915， P<0.05）. Analysis of simple effect denoted that study group scored higher on MMSE on the 1^st， 3^rd and 5^th day after surgery compared with control group， with statistical significance （t=-3.579， -1.764， -0.253， P<0.05）. Study group reported lower incidence rates of POCD on the 1^st， 3^rd and 5^th day after surgery compared with control group， with statistical significance （χ²=2.631， 3.471， 5.135， P<0.05）. On the 3^rd day after surgery，study group scored lower on PSQI than control group（P<0.05）， and PSQI total score， sleep latency， subjective sleep quality， daytime dysfunction and hypnotic drug use factor scores of study group were lower than baseline， with statistical significance（F=43.175， 12.594， 11.092， 4.579， 3.514， P<0.01）. ConclusionMindfulness-based therapy may have certain value in reducing incidence of POCD and improving sleep quality in elderly patients who underwent surgery under local anesthesia.

Objective: To investigate the epidemiological characteristics of varicella outbreaks in primary and middle schools, and to establish a risk predictive model, so as to provide scientific guidance for the prevention of varicella outbreaks in schools. Methods: Based on a nested case-control study, primary and middle schools in 4 districts of Shanghai (Yangpu District and Jingan District) and Hangzhou (Xiaoshan District and Linping District) from January to December 2023 were selected to observe the status of varicella outbreaks. Associated factors of varicella outbreaks were investigated and used for establishing the predictive model, which was evaluated by the Hosmer-Lemeshow(H-L) goodness of fit test, receiver operating characteristic (ROC) curve, Calibration curve, decision curve analysis (DCA). Results: A total of 98 varicella outbreaks were included, with 195 schools without varicella outbreaks during the same period as controls. Eight factors, including the availability of warm water in restroom, availability of hand soap in restroom, average class size, duration of student attendance at school per day, presence of a fulltime school doctor, hesitancy of the school principal towards varicella vaccination, and rates of first and second doses of varicella vaccination, were identified as potential factors for school varicella outbreaks, with statistically significant differences (χ2/Z=10.01, 20.49, 17.43, 9.74, 32.17, 6.60, 2.20, 3.39, P<0.05). The 8 variables above were employed to construct a risk predictive model, and Hosmer-Lemeshow goodness of fit test yielded a χ2 value of 5.863 (P>0.05); the area under the ROC curve (AUC) was 0.846 (95%CI=0.799-0.893); Calibration curve analysis indicated good consistency between predicted and actual values of the model. DCA demonstrated favorable predictive performance of the model over a wide range. Conclusions The predictive model for school varicella outbreaks demonstrates satisfactory accuracy and efficacy. It suggested to make good use of this prediction model and take relevant measures to reduce the risk of varicella transmission in schools.

Objective: Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery. Methods: We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3–12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum). Results: The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004–1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67. Conclusion Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Objective: Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery. Methods: We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3–12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum). Results: The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004–1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67. Conclusion Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Objective: Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery. Methods: We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3–12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum). Results: The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004–1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67. Conclusion Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Objective: Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery. Methods: We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3–12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum). Results: The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004–1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67. Conclusion Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Objective: Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery. Methods: We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3–12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum). Results: The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004–1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67. Conclusion Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Objective:To investigate the prevalence and predictors of delayed function independence (DFI) in patients with acute vertebrobasilar artery occlusion (VBAO) achieved successful recanalization after endovascular therapy.Methods:Patients with acute VBAO received endovascular treatment in the Departments of Neurology, the First Affiliated Hospital of University of Science and Technology and General Hospital of Eastern Theater Command, PLA from December 2015 to December 2018 were retrospectively enrolled. The demographic, clinical, laboratory and imaging data were collected. Early functional independence (EFI) was defined as the modified Rankin Scale score 0-2 at discharge, and DFI was defined as the modified Rankin Scale score 0-2 at 90 d after discharge for non-EFI patients. Multivariate logistic regression analysis was used to determine the independent predictors of DFI. Results:A total of 122 patients with acute VBAO were included. Their age was 61.8±11.9 years old and 91 (74.6%) were male. The median Glasgow Coma Scale (GCS) score was 7, the median National Institutes of Health Stroke Scale (NIHSS) score was 26.5, and the median posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) score was 9. Twenty-four patients (20.0%) had EFI; of the 98 patients with non-EFI, 18 (18.4%) had DFI. Multivariate logistic regression analysis showed that male (odds ratio [ OR] 0.038, 95% confidence interval [ CI] 0.002-0.658; P=0.025), cardiogenic embolism ( OR 0.116, 95% CI 0.023-0.579; P=0.009), baseline NIHSS score ( OR 1.136, 95% CI 1.040-1.242; P=0.005) and lung infection ( OR 6.089, 95% CI 1.451-25.562; P=0.014) were the independent predictors of DFI. Conclusions:Nearly 1/5 of the non-EFI patients have DFI. Male, cardiogenic embolism, lower baseline NIHSS score and without pulmonary infection are the independent predictors of DFI.

Recent advancement in natural language processing (NLP) and medical imaging empowers the wide applicability of deep learning models. These developments have increased not only data understanding, but also knowledge of state-of-the-art architectures and their real-world potentials. Medical imaging researchers have recognized the limitations of only targeting images, as well as the importance of integrating multimodal inputs into medical image analysis. The lack of comprehensive surveys of the current literature, however, impedes the progress of this domain. Existing research perspectives, as well as the architectures, tasks, datasets, and performance measures examined in the present literature, are reviewed in this work, and we also provide a brief description of possible future directions in the field, aiming to provide researchers and healthcare professionals with a detailed summary of existing academic research and to provide rational insights to facilitate future research.
Humans ; Natural Language Processing ; Surveys and Questionnaires

Objective:To establish a long-term mortality rate prediction model for patients aged 60 years and over with atrial fibrillation and coronary heart disease using the machine learning method, and identify the corresponding risk factors of mortality.Methods:In this retrospective cohort study, a total of 329(11 cases lost of follow-up)patients with 183 males(55.6%)and 146 females(44.4%), aged(77.8±7.3)years, and 142 patients aged 80 years or older(43.2%)were selected in our hospitals from January 2013 to March 2015.And their clinical data on atrial fibrillation and coronary heart disease were analyzed.They were divided into the death group(151 cases)and the survival group(167 cases)according to the survival outcome.In addition, 60 patients aged 60 years and over admitted to our hospitals from April to July 2015 with atrial fibrillation and coronary heart disease were selected as external data validation set.The clinical data included age, gender, body mass index, diagnosis, co-morbidity, laboratory indicators, electrocardiogram, echocardiogram, treatment data.These patients were followed up for at least 6 years, and the main adverse cardiovascular and cerebrovascular events(MACCE), including death, were recorded.Finally, the data of the enrolled patients were randomly divided into the training set and the test set according to the ratio of 9∶1, Different models were established to predict the long-term mortality of patients with atrial fibrillation and coronary heart disease by machine learning algorithm.The optimal model was established by substituting external data(60 cases)into the model for verification and comparison.The top 20 risk factors for mortality were determined by Shapley additive explanation(SHAP)algorithm.Results:A total of 329 hospitalized patients were included in this study, the overall median follow-up time was 77.0 months(95% CI: 54.0~84.0), 11 cases lost during follow-up(3.3%), and 151 cases died(45.9%). The analysis found that the areas under the ROC curve for a support vector machine(SVM)model, k-Nearest Neighbor(KNN)model, decision tree model, random forest model, ADABoost model, XGBoost model and logistic regression model were 0.76, 0.75, 0.75, 0.91, 0.86, 0.85 and 0.81, respectively.The random forest model had the highest prediction efficiency, with the accuracy of 0.789 and F1 value of 0.806, which was better than the logistic regression model[the Area Under Receiver Operating Characteristic Curve(AUC): 0.91 vs.0.81, P<0.05]. D-dimer, age, number of MACCE, left ventricular ejection fraction, serum albumin level, anemia, New York Heart Association(NYHA)grade, history of old myocardial infarction, estimated glomerular filtration rate(eGFR)and resting heart rate were important risk factors for predicting long-term mortality. Conclusions:The random forest model based on machine learning method can predict the long-term mortality of patients with atrial fibrillation and coronary heart disease aged 60 years and over, have a good identification ability.Its accuracy is higher than that of the traditional Logistic regression model.Reducing the long-term mortality and improving the long-term outcomes can be achieved by intervening on D-dimer levels, correcting hypoproteinemia and anemia, improving cardiac function and controlling resting ventricular rates.