OBJECTIVE To investigate the clinical efficacy and safety of dupilumab in patients with severe asthma-chronic obstructive pulmonary disease （COPD） overlap （ACO）. METHODS A retrospective analysis was conducted on 150 patients with severe ACO treated at Nantong Third People’s Hospital during Jan. 2022-Dec. 2023. Patients were divided into the control group [conventional therapy with inhaled corticosteroids （ICS）+long-acting beta-2 agonists （LABA）+long-acting muscarinic anticholinergic （LAMA）， n＝90] and the observation group （conventional therapy plus dupilumab， n＝60） based on different treatment regimens. Propensity score matching （PSM） was performed at a ratio of 1.5∶1. Symptom control scores [Asthma Control Test （ACT） score， COPD Assessment Test （CAT） score] and pulmonary function parameters [forced vital capacity （FVC）， forced expiratory volume in 1 second （FEV1）， the FEV1 in percentage of predicted value （FEV1%pred）， the ratio of FEV1 and FVC （FEV1/FVC）， peak expiratory flow （PEF） and maximal mid-expiratory flow （MMEF）] before treatment and at 1， 3， and 12 months after treatment， as well as the levels of biomarkers [peripheral blood eosinophil （EOS） count， immunoglobulin E （IgE）， C-reactive protein （CRP）， fractional exhaled nitric oxide （FeNO）]， annual acute exacerbation frequency， quality-of-life scores [Asthma Quality of Life Questionnaire （AQLQ） score， St George’s Respiratory Questionnaire （SGRQ） score， and Medical Outcomes Study 36-item Short Form Health Survey （SF-36） score] before treatment and 12 months after treatment， and the occurrence of adverse reactions were compared. RESULTS After PSM， 120 patients were included， involving 72 cases in the control group and 48 cases in the observation group. Compared with before treatment， both groups showed significant improvements in ACT scores at 1， 3， and 12 months after treatment， FVC， FEV1， FEV1%pred （except at 3 months after treatment in the control group）， （except at 3 months after treatment in the control group）， PEF （except at 3 and 12 months after treatment in the control group） and MMEF （including at 1 month after treatment in the observation group） at 3 and 12 months after treatment， as well as AQLQ and SF-36 scores at 12 months after treatment （P＜0.05）. CAT scores at 1， 3 and 12 months after treatment， annual acute exacerbation frequency and SGRQ score at 12 months after treatment， FeNO levels at 12 months after treatment in the control group， as well as EOS count， IgE， CRP and FeNO levels at 12 months after treatment in the observation group were significantly reduced （P＜0.05）. The improvements of above indicators in the observation group were mostly greater than in the control group （P＜0.05）. The incidence of adverse reactions did not differ significantly between the two groups （P＞0.05）. CONCLUSIONS Dupilumab provides superior efficacy over conventional therapy in improving clinical symptoms， pulmonary function， and quality of life， while reducing biomarker levels in patients with severe ACO， with a comparable safety profile to standard therapy.

Objective To develop a risk prediction model for pulmonary infections in elderly patients with COPD complicated by respiratory failure, and to validate its predictive performance. Methods From January 2022 to September 2023, a cohort of 269 elderly patients with COPD complicated by respiratory failure was selected to serve as the modeling group. Based on the incidence of lung infections, these patients were split into two groups: one with 47 cases of infection and the other with 222 cases of no infection. Clinical data from both groups were compared, and multivariate logistic regression analysis was applied to identify influencing factors and establish a risk prediction model. Additionally, 104 elderly patients with COPD complicated by respiratory failure, recruited between October 2023 and December 2024, were used for external validation of the predictive performance of the model. Results Among the 269 patients, 47 cases developed pulmonary infections, with an incidence rate of 17.47%. A total of 63 pathogenic bacteria strains were detected, with a relatively high proportion being Gram-negative bacteria (73.02%). The duration of hospitalization, IFN-γ, TNF-α, CRP, and PaO2 are factors influencing pulmonary infections in elderly patients with COPD complicated by respiratory failure. For the modeling group, the AUC was 0.975, with a sensitivity of 0.928, a specificity of 0.729, and a maximum Youden index of 0.209. For the validation group, the AUC was 0.958, with a sensitivity of 0.880 and a specificity of 0.522. The H-L test results showed that for the modeling group, χ²=1.1154, and for the validation group, χ²=3.6654, with both P-values being greater than 0.05. Conclusion The duration of hospitalization, IFN-γ, TNF-α, CRP, and PaO₂ are factors influencing pulmonary infections in elderly patients with COPD complicated by respiratory failure. The risk prediction model developed based on these factors demonstrates good predictive performance.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective:To investigate the association between cognitive impairment and manifestation of interictal electroencephalogram (EEG) in epilepsy patients, and the early assessment significance of the Grand Total Electroencephalography (GTE) score.Methods:A totall of 100 patients with primary epilepsy admitted to the Department of Neurology of the Affiliated Hospital of Yangzhou University were continuously collected from January 2019 to January 2024, and they were classified according to the latest version of the epilepsy classification by the International League Against Epilepsy in 2017. General information of all research subjects was recorded, including age, gender, educational level, etc. The disease details of epilepsy patients were recorded, including seizure duration, severity, seizure precursors, post seizure status, and use of anti-seizure medications (ASM). The survey scales and questionnaires used included the interictal GTE, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale, Hamilton Depression Scale, National Hospital Seizure Severity Scale (NHS3), Status Epilepticus Severity Score (STESS). All research subjects were classified into normal cognitive (NC) group, mild cognitive impairment (MCI) group, and dementia group according to MoCA score. Comparisons among multiple groups and pairwise comparisons were conducted. The correlation between 2 variables was analyzed using Spearman rank correlation analysis, and multiple linear regression analysis was employed to screen variables that have an impact on cognitive impairment. The receiver operating characteristic curve was plotted to determine the optimal cut-off point for predicting cognitive impairment in epilepsy.Results:According to the MoCA score, there were 32 (32%) patients in the NC group, 49 (49%) patients in the MCI group, and 19 (19%) patients in the dementia group. There were statistically significant differences in age [(26.31±10.01) years, (43.96±16.19) years, (57.68±16.83) years,respectively; F=29.440, P<0.001], education ( χ2=28.894, P<0.001), ASM ( χ2=11.258, P<0.017), STESS score [2.00(1.75, 2.25), 2.00(2.00, 3.00), 3.50(2.75, 4.25),respectively; H=12.646, P=0.002], STESS score>2 ( χ2=10.075, P=0.006), frequency of rhythmic background activity ( H=17.429, P<0.001), diffuse slow activity ( H=42.033, P<0.001), reactivity of the rhythmic background activity ( H=15.206, P<0.001), paroxysmal activity ( H=25.279, P<0.001), sharp wave activity ( H=15.492, P<0.001) and total GTE score [1 (1, 3), 6 (2, 8), 8 (7, 11),respectively; H=47.871, P<0.001] among the 3 groups. A significant negative correlation was observed between cognitive level (MoCA scores) and total GTE score ( ρ=-0.766, P<0.001), frequency of rhythmic background activity ( ρ=-0.520, P<0.001), diffuse slow activity ( ρ=-0.734, P<0.001), reactivity of the rhythmic background activity ( ρ=-0.438, P<0.001), paroxysmal activity ( ρ=-0.566, P<0.001), and sharp wave activity ( ρ=-0.407, P<0.001). The results of multiple linear regression analysis indicated that total GTE score ( t=-5.566, P<0.001), diffuse slow activity ( t=-2.548, P=0.014), reactivity of the rhythmic background activity ( t=-3.891, P<0.001), paroxysmal activity ( t=-3.139, P=0.003), age ( t=-5.493, P<0.001), education ( t=3.379, P=0.001), and STESS ( t=-2.183, P=0.033) were independent risk factors for cognitive impairment. In evaluating the cognitive impairment of epilepsy patients, the GTE score had a certain sensitivity (75.0%) and specificity (93.8%), with an optimal critical point value of 5. Conclusions:The interictal EEG of patients with poorer cognitive function is mainly characterized by an increase in slow waves and a decrease in overall background. The increase in slow waves, poor background responsiveness, paroxysmal activity and a high total GTE score may be important factors in predicting the outcome of cognitive impairment in epilepsy.

Objective:To analyze postictal electroencephalographic(EEG) characteristics of patients with status epilepticus (SE) based on the score of grand total electroencephalography (GTE), and explore the relationship between electroencephalographic characteristics of SE and clinical prognosis.Methods:A total of 110 SE patients were enrolled in the Department of Neurology, the Affiliated Hospital of Yangzhou University from September 1, 2021 to September 1, 2023. EEG and GTE scores were performed in all patients after seizures (0-2 days after the cessation of SE). After one year of discharge, the medication and seizure status of patients were followed up by phone or outpatient visits. The seizure outcomes were recorded according to the international league against epilepsy (ILAE) seizure outcome classification, with favorable outcomes defined as good prognosis group ( n=54) and unfavorable outcomes defined as poor prognosis group ( n=56). SPSS 27.0 software was used for statistical analysis. Binary Logistic regression analysis was employed to screen impact variables of prognosis. The receiver operating characteristic(ROC) curve was plotted to determine the optimal cut-off point for predicting prognosis in epilepsy. Results:There were statistically significant differences in the total GTE score(2(1, 4), 8(5, 10); Z=-6.837, P<0.001), diffuse slow activity(0(0, 1), 2(0, 2); Z=-6.495, P<0.001), reactivity of the rhythmic background activity(0(0, 0), 0(0, 1); Z=-2.705, P=0.007), paroxysmal activity(0(0, 0), 1.5(0, 3.0); Z=-4.420, P<0.001), focal disturbances(0(0, 0), 0(0, 0); Z=-2.130, P=0.033), and sharp wave activity(0(0, 2), 2(2, 3); Z=-5.714, P<0.001)between the good prognosis group and poor prognosis group. The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity and total GTE score (all P<0.05). The differences in EEG results between SE patients with clear and unknown causes were statistically significant in terms of paroxysmal activity and focal disturbances(both P<0.05). The results of binary Logistic regression analysis showed that independent factors associated with the prognosis of SE included medication adherence ( B=-0.496, OR=0.609, 95% CI=0.395-0.940, P=0.025), diffuse slow activity( B=1.580, OR=4.854, 95% CI=1.586-14.855, P=0.006), sharp wave activity( B=0.824, OR=2.280, 95% CI=1.210-4.297, P=0.011), and total GTE score ( B=0.561, OR=1.753, 95% CI=1.360-2.259, P<0.001). In evaluating the prognosis of SE, the GTE score had a certain sensitivity (74.6%) and specificity (85.1%), with a optimal cut-off point of 6. Conclusions:The differences in EEG results among SE patients with different types of epileptic seizures were statistically significant in terms of frequency of rhythmic background activity, diffuse slow activity, reactivity of rhythmic background activity. The appearance of diffuse slow activity and sharp wave activity in the electroencephalogram of SE patients indicates poor prognosis, and the total GTE score≥6 may be a strong predictor of poor prognosis. However, good medication adherence is a protective factor for epilepsy recurrence.

Objective: The active components and potential targets were predicted and confirmed to explore the possible mechanism of Wenpi decoction on ulcer colitis. Methods: The traditional Chinese medicine integrated pharmacology platform (TCMIP) was used to construct the decoction-target-disease target network, and the key nodes were analyzed and screened. The function and pathway enrichment analysis were conducted to explore the biological processes, which Wenpi decoction may be involved in the treatment of ulcerative colitis. Results: The study showed that there were 455 active ingredients and 3044 targets in Wenpi decoction. The 434 targets and multiple biological processes and metabolic pathways were involved, such as chemokine signaling pathways, estrogen signaling pathway, thyroid hormone signaling pathway, MAPK signaling pathway, and PI3K/Akt signaling pathway. These targets and pathways were consistent with the pathogenesis of ulcerative colitis reported in the literature. In addition, Wenpi decoction was potential to be applied in the treatment of tumor, endocrine and metabolic diseases. Conclusions This study provided a scientific basis for further studies on the mechanism of Wenpi decoction in the treatment for ulcer colitis.

Objective To evaluate the effect of levosimendan on prognosis and circulation disorders of sepsis patients. Methods With the guidance of these following Chinese or English key words, such as sepsis, severe sepsis, septic shock, simendan, levosimendan, etc., some of Chinese and foreign published literatures on randomized controlled trials (RCTs) concerning the effects of levosimendan on the prognosis and circulatory function of septic patients were searched through China National Knowledge Infrastructure (CNKI) internet, VIP and Wanfang Databases, China Biomedicine Database (CMB), Pubmed in American National library, Holland Medical Abstract Database (Embase), Cochrane Library, etc databases, from the creation of above various databases to May 2017. The quality of the collected RCTs was evaluated by modified Jadad score; Revman 5.3 software was used to carry out Meta analysis; the publication bias was assessed by the funnel plots. Results A total of 18 RCTs, 9 in Chinese and 9 in English, but only half of the literatures were of high quality, and the other 9 of low quality, containing 688 cases in control group and 704 cases in experimental group were ultimately enrolled in this analysis. The Meta analyses showed that there was no statistical significant difference in the mortality between the experimental group and the control group [relative risk (RR) = 0.92, 95% confidence interval (95%CI) = 0.80 - 1.06, P = 0.27]; compared with control group, the time of stay in ICU was shortened [mean difference (MD) = -2.02, 95%CI = -2.90 to -1.13, P < 0.000 01], cardic output index was increased (MD = 0.63, 95%CI = 0.39 - 0.87, P < 0.000 01), and blood lactate level was decreased (MD = -1.37, 95%CI = -1.51 to-1.23, P < 0.000 01) in the experimental group, being significantly improved after levosimendan therapy. The funnel map evaluation showed that there might be a certain bias in the publication of the literature. Conclusion Levosimendan can improve circulatory disorders and reduce the time of stay in ICU for septic patients, but can not reduce their mortality.