We reported a case of eosinophilic meningoencephalitis,presenting with symptoms such as depression,headache and memory decline.Physical examination revealed mental tension,slightly slurred speech,and cognitive decline.Laboratory tests indicated a significant increase in eosinophils in both peripheral blood and cerebrospinal fluid,suggesting eosinophilic meningoencephalitis.After treatment with glucocorticoids and cognitive function improvement measures,the patient's symptoms improved.Here,we summarized its clinical features,laboratory examination,diagnosis and treatment.Then,we discussed the pathogenesis,treatment and differential diagnosis of eosinophilia manifested as meningoencephalitis.In order to improve clinicians'understanding of eosinophilia complicated with meningoencephalitis and provide reference for clinical diagnosis and treatment of these diseases.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Objective To explore the value of 18F-flortaucipir tau PET combined with APOE ε4 genotype status for diagnosing mild cognitive impairment(MCI).Methods A total of 213 MCI patients(MCI group)and 402 healthy controls(HC group)were selected from Alzheimer's disease neuroimaging initiative(ADNI)database.The neuropsychological information,APOE ε4 gene carrier status,tau PET and high-resolution structural MRI data were recorded.The random forest algorithm was used to screen the most informative brain regions of tau PET for diagnosing MCI,and the efficacy of tau PET for distinguishing MCI with or without APOE ε4 gene and HC were compared.Results Amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus in turn were the important brain regions of tau PET for diagnosing MCI.The accuracy and the area under the curve(AUC)of tau PET standardized uptake value ratio(SUVR)model for identifying MCI with APOE ε4 gene and HC was 86.68％and 0.784,respectively,both higher than those for identifying MCI and HC,as well as MCI without APOE e4 gene and HC(with accuracy of 70.57％and 75.05％,and AUC of 0.711 and 0.609).Conclusion 18F-flortaucipir tau PET SUVR model established based on amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus could be used to diagnosing MCI.Combining with APOE ε4 gene could further improve its efficacy.

OBJECTIVE: To investigate the current status of early pain and agitation management in critically ill patients in Guizhou Province. METHODS: A retrospective study was performed using data collected from a quality control activity conducted between April and June 2021 in non-provincial public hospitals with general intensive care unit (ICU) in Guizhou Province. Hospital-level data included hospital name and grade, ICU staffing, and number of ICU beds. Patient-level data included characteristics of patients treated in the general ICU on the day of the survey (e.g., age, sex, primary diagnosis), as well as pain and agitation assessments and the types of analgesic and sedative medications administered within 24 hours of ICU admission. RESULTS: A total of 947 critically ill ICU patients from 145 hospitals were included, among which 104 were secondary-level hospitals and 41 were tertiary-level hospitals. Within 24 hours of ICU admission, 312 (32.9%) critically ill patients received pain assessments, and 277 (29.3%) received agitation assessments. Among the pain assessment tools, the critical care pain observation tool (CPOT) was used in 44.2% (138/312) of critically ill ICU patients, with a significantly higher usage rate in tertiary hospitals compared to secondary hospitals [52.3% (69/132) vs. 38.3% (69/180), P < 0.05]. The Richmond agitation-sedation scale (RASS) was used in 93.8% (260/277) of critically ill ICU patients for agitation assessment, with no significant difference between hospital levels. Among the 947 critically ill patients, 592 (62.5%) received intravenous analgesics within 24 hours, with remifentanil being the most commonly used [42.9% (254/592)]; 510 (53.9%) received intravenous sedatives, with midazolam being the most frequently used [60.8% (310/510)]. Mechanical ventilation data were available for 932 critically ill patients, of whom 579 (62.1%) received mechanical ventilation and 353 (37.9%) did not. Compared with non-ventilated patients, ventilated patients had significantly higher rates of analgesic and sedative use [analgesics: 77.9% (451/579) vs. 38.8% (137/353); sedatives: 71.8% (416/579) vs. 25.8% (91/353); both P < 0.05]. In terms of analgesic selection, ventilated patients were more likely to receive strong opioids than non-ventilated patients [85.8% (95/137) vs. 69.3% (387/451), P < 0.05]. For sedatives, ventilated patients preferred midazolam [66.6% (277/416)], whereas non-ventilated patients more often received dexmedetomidine [45.1 (41/91)]. Blood pressure within 24 hours of ICU admission were available for 822 critically ill patients, of whom 245 (29.8%) had hypotension and 577 (70.2%) did not. Compared with non-hypotensive patients, hypotensive patients had significantly higher rates of analgesic and sedative use [analgesics: 74.7% (183/245) vs. 59.8% (345/577); sedatives: 65.7% (161/245) vs. 51.3% (296/577); both P < 0.05], but there was no significant difference in the choice of analgesic or sedative agents between the two groups. CONCLUSIONS The proportion of critically ill ICU patients in Guizhou Province who received standardized pain and agitation assessments was relatively low. The most commonly used assessment tools were CPOT and RASS, while remifentanil and midazolam were the most frequently used analgesic and sedative agents, respectively. Secondary-level hospitals had a lower rate of using standardized pain assessment tools compared to tertiary-level hospitals. Mechanical ventilation and hypotension were associated with the use of analgesic and sedative medications.
Humans ; Critical Illness ; Intensive Care Units ; Analgesics/therapeutic use* ; Hypnotics and Sedatives/therapeutic use* ; Retrospective Studies ; China ; Pain Measurement ; Pain Management ; Female ; Male ; Critical Care ; Middle Aged

Objective To explore the value of 18F-flortaucipir tau PET combined with APOE ε4 genotype status for diagnosing mild cognitive impairment(MCI).Methods A total of 213 MCI patients(MCI group)and 402 healthy controls(HC group)were selected from Alzheimer's disease neuroimaging initiative(ADNI)database.The neuropsychological information,APOE ε4 gene carrier status,tau PET and high-resolution structural MRI data were recorded.The random forest algorithm was used to screen the most informative brain regions of tau PET for diagnosing MCI,and the efficacy of tau PET for distinguishing MCI with or without APOE ε4 gene and HC were compared.Results Amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus in turn were the important brain regions of tau PET for diagnosing MCI.The accuracy and the area under the curve(AUC)of tau PET standardized uptake value ratio(SUVR)model for identifying MCI with APOE ε4 gene and HC was 86.68％and 0.784,respectively,both higher than those for identifying MCI and HC,as well as MCI without APOE e4 gene and HC(with accuracy of 70.57％and 75.05％,and AUC of 0.711 and 0.609).Conclusion 18F-flortaucipir tau PET SUVR model established based on amygdala,parahippocampal gyrus,entorhinal cortex,posterior cingulate gyrus,inferior temporal gyrus,fusiform gyrus and middle temporal gyrus could be used to diagnosing MCI.Combining with APOE ε4 gene could further improve its efficacy.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the influencing factors of cognitive impairment in non-dialysis patients with chronic kidney disease(CKD).Methods A total of 60 hospitalized non-dialysis patients with CKD in the Department of Nephrology of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from September 2022 to September 2023 were enrolled as research objects.According to the estimated glomerular filtration rate(eGFR),they were divided into stage 1 to 2 of CKD group[eGFR ≥60 mL/(min·1.73 m2)]with 23 cases,the stage 3 of CKD group[eGFR 30～＜60 mL/(min·1.73 m2)]with 20 cases,and stage 4 to 5 of CKD group[eGFR＜30 mL/(min·1.73 m2)]with 17 cases.The Montreal Cognitive Assessment Scale(MoCA)was used to evaluate the cognitive function of the patients.Basic data and common clinical laboratory in-dicators on hospital admission were collected to analyze the differences in cognitive function levels under different renal function statuses and to explore the influencing factors of cognitive impairment.Results The incidence rates of cognitive impairment in the stage 1 to 2 of CKD group,stage 3 of CKD group,and stage 4 to 5 of CKD group were 47.8％,85.0％,and 94.1％respectively,the median MoCA scored 26,24 and 20 respectively,with statistically significant between-group differ-ences(P＜0.05).Cognitive function was significantly negatively correlated with age(r=-0.634,P＜0.001),blood urea nitrogen(BUN)(r=-0.574,P＜0.001),serum creatinine(Cr)(r=-0.417,P＜0.001),cystatin C(Cys-C)(r=-0.327,P=0.011),serum β2-microglobulin(β2-MG)(r=-0.259,P=0.046),and N-terminal pro-brain natriuretic peptide(NT-proBNP)(r=-0.474,P＜0.001),and was significantly positively correlated with hemoglobin(HB)(r=0.401,P=0.001)and eGFR(r=0.485,P＜0.001).Multivariate Logistic regression analysis showed that age(P=0.006)and NT-proBNP(P=0.041)were influencing factors of cognitive im-pairment in non-dialysis patients with CKD.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),sensitivity,and specificity of age for prediction were 0.860,0.864 and 0.812 respectively,the AUC,sensitivity,and specificity of NT-proBNP for pre-diction were 0.808,0.795 and 0.875 respectively,and the combined prediction of age and NT-proBNP had an AUC,sensitivity,and specificity of 0.893,0.955,and 0.750,respectively.Conclusion As renal function deteriorates,the incidence rate and severity of cognitive impairment in non-dialysis patients with CKD tend to increase.Advanced age,renal function deterioration,high NT-proBNP level,and anemia are associated with the occurrence of cognitive impairment in non-di-alysis patients with CKD,among which age and NT-proBNP are influencing factors for cognitive im-pairment.

We reported a case of eosinophilic meningoencephalitis,presenting with symptoms such as depression,headache and memory decline.Physical examination revealed mental tension,slightly slurred speech,and cognitive decline.Laboratory tests indicated a significant increase in eosinophils in both peripheral blood and cerebrospinal fluid,suggesting eosinophilic meningoencephalitis.After treatment with glucocorticoids and cognitive function improvement measures,the patient's symptoms improved.Here,we summarized its clinical features,laboratory examination,diagnosis and treatment.Then,we discussed the pathogenesis,treatment and differential diagnosis of eosinophilia manifested as meningoencephalitis.In order to improve clinicians'understanding of eosinophilia complicated with meningoencephalitis and provide reference for clinical diagnosis and treatment of these diseases.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.