Objective:To analyze the different clinical features of patients with early-onset(EO-NMOSDs)and late-onset neuromyelitis optica spectrum diseases(LO-NMOSDs).Methods:A total of 51patients with neuromyelitis optica spec...Objective:To analyze the different clinical features of patients with early-onset(EO-NMOSDs)and late-onset neuromyelitis optica spectrum diseases(LO-NMOSDs).Methods:A total of 51patients with neuromyelitis optica spectrum disease who were diagnosed in our hospital for the first time from January 2015 to December 2022 were included in the First Affiliated Hospital of Hainan Medical College and divided into 22 cases in the EO-NMOSDs group and 29 cases in the LO-NMOSDs group according to whether the age of onset was 50 years old.The basic data,Extended Disability Status Scale(EDSS)score,blood and cerebrospinal fluid test indicators of the two groups were statistically analyzed.Results:There were no significant differences in demographic characteristics,clinical features and serum AQP-4 antibody positivity rate between the two groups(all P>0.05),and there were significant differences in triglycerides(TG),low-density lipoprotein(LDL),apolipoprotein A(APOA),apolipoprotein B(APOB)and lipoprotein a(P=0.010,P=0.048,P=0.014,P=0.061,P=0.001,respectively),and cerebrospinal fluid LDH,There were significant differences between microprotein quantification and EDSS score(P=0.018,P=0.034,P=0.025,respectively),and the level of microprotein quantification in cerebrospinal fluid of LO-NMOSDs had a certain correlation with the degree of disability(r=0.52,P<0.03).Conclusion:LO-NMOSDs and EO-NMOSDs group patients have similar demographic characteristics,serum AQP-4 antibody positive rate and clinical features,but compared with EO-NMOSDs,patients in LO-NMOSDs group are prone to abnormal lipid metabolism,higher trace proteins in cerebrospinal fluid and more likely to be disabled,and among LO-NMOSDs,the higher the trace protein in the cerebrospinal fluid,the more severe the disability status of patients.展开更多
Objective:To screen risk factors for epilepsy after acute ischaemic stroke based on meta-analysis and cohort study and to establish a predictive model.Methods:Computer searches of MEDLINE,Embase,Cochrane library,Web o...Objective:To screen risk factors for epilepsy after acute ischaemic stroke based on meta-analysis and cohort study and to establish a predictive model.Methods:Computer searches of MEDLINE,Embase,Cochrane library,Web of Scinence,PubMed,CNKI,and WanFang Data data were conducted to collect literature on epilepsy after in acute ischemic stroke,from database creation to September 1,2022.The RRs and their 95%confidence intervals(CI)for risk factors for post stroke epilepsy were extracted for each study,and pooled estimates of the RRs and 95%CIs for each study were generated using either a random-effects model or a fixed-effects model.Beta coefficients for each risk factor were calculated based on the combined RR and their corresponding 95%CIs.The beta coefficients were multiplied by 10 and rounded.Results:Ten articles were identified for final inclusion in this meta-analysis,with a total of 141948 cases and 3702 cases of post stroke epilepsy.The risk factors included in the final risk prediction model were infarct size(RR 4.67,95%CI 1.41~15.47;P=0.01),stroke recuRRence(RR 2.48,95%CI 2.01~3.05;P<0.00001),stroke etiology(RR 1.70,95%CI 1.34~2.15;P<0.00001),stroke severity(RR 1.70,95%CI 1.34~2.15;P<0.00001),and stroke risk.stroke severity(RR 1.53,95%CI 1.39~1.70;P<0.00001),NIHSS score(RR 2.91,95%CI 1.64~5.61;P=0.0003),early-onset epilepsy(RR 5.62,95%CI 5.08~6.22;P<0.00001),cortical lesions(RR 3.83.95%CI 2.23~6.58;P<0.00001),total anterior circulation infarction(RR 18.94,95%CI 10.38~34.57;P<0.00001),partial anterior circulation infarction(RR 4.39,95%CI 2.29~8.40;P<0.00001),cardiovascular events(RR 1.78,95%CI 1.59~1.99;P<0.00001).Conclusion:Based on a systematic review and meta-analysis,we developed a simple risk prediction model for late epilepsy in baseline ischemic stroke that integrates clinical risk factors,including infarct size,stroke recurrence,stroke etiology,stroke severity,NIHSS score,early onset epilepsy,cortical lesions,stroke subtype,and cardiovascular events.展开更多
基金Hainan Clinical Medicine Center Construction Project(2021)Hainan Provincial Excellent Talent Team(QRCBT202121)Key R&D Plan of Hainan Province(ZDYF2022SHFZ109)。
文摘Objective:To analyze the different clinical features of patients with early-onset(EO-NMOSDs)and late-onset neuromyelitis optica spectrum diseases(LO-NMOSDs).Methods:A total of 51patients with neuromyelitis optica spectrum disease who were diagnosed in our hospital for the first time from January 2015 to December 2022 were included in the First Affiliated Hospital of Hainan Medical College and divided into 22 cases in the EO-NMOSDs group and 29 cases in the LO-NMOSDs group according to whether the age of onset was 50 years old.The basic data,Extended Disability Status Scale(EDSS)score,blood and cerebrospinal fluid test indicators of the two groups were statistically analyzed.Results:There were no significant differences in demographic characteristics,clinical features and serum AQP-4 antibody positivity rate between the two groups(all P>0.05),and there were significant differences in triglycerides(TG),low-density lipoprotein(LDL),apolipoprotein A(APOA),apolipoprotein B(APOB)and lipoprotein a(P=0.010,P=0.048,P=0.014,P=0.061,P=0.001,respectively),and cerebrospinal fluid LDH,There were significant differences between microprotein quantification and EDSS score(P=0.018,P=0.034,P=0.025,respectively),and the level of microprotein quantification in cerebrospinal fluid of LO-NMOSDs had a certain correlation with the degree of disability(r=0.52,P<0.03).Conclusion:LO-NMOSDs and EO-NMOSDs group patients have similar demographic characteristics,serum AQP-4 antibody positive rate and clinical features,but compared with EO-NMOSDs,patients in LO-NMOSDs group are prone to abnormal lipid metabolism,higher trace proteins in cerebrospinal fluid and more likely to be disabled,and among LO-NMOSDs,the higher the trace protein in the cerebrospinal fluid,the more severe the disability status of patients.
基金This study was supported by Hainan Provincial Key Research and Development Plan(ZDYF2021SHFZ092,ZDYF2022SHFZ109),Hainan Provincial Natural Science Foundation(822RC832)Hainan Provincial Clinical Medical Center(2021)Epilepsy Research Innovation Team of Hainan Medical College(2022)。
文摘Objective:To screen risk factors for epilepsy after acute ischaemic stroke based on meta-analysis and cohort study and to establish a predictive model.Methods:Computer searches of MEDLINE,Embase,Cochrane library,Web of Scinence,PubMed,CNKI,and WanFang Data data were conducted to collect literature on epilepsy after in acute ischemic stroke,from database creation to September 1,2022.The RRs and their 95%confidence intervals(CI)for risk factors for post stroke epilepsy were extracted for each study,and pooled estimates of the RRs and 95%CIs for each study were generated using either a random-effects model or a fixed-effects model.Beta coefficients for each risk factor were calculated based on the combined RR and their corresponding 95%CIs.The beta coefficients were multiplied by 10 and rounded.Results:Ten articles were identified for final inclusion in this meta-analysis,with a total of 141948 cases and 3702 cases of post stroke epilepsy.The risk factors included in the final risk prediction model were infarct size(RR 4.67,95%CI 1.41~15.47;P=0.01),stroke recuRRence(RR 2.48,95%CI 2.01~3.05;P<0.00001),stroke etiology(RR 1.70,95%CI 1.34~2.15;P<0.00001),stroke severity(RR 1.70,95%CI 1.34~2.15;P<0.00001),and stroke risk.stroke severity(RR 1.53,95%CI 1.39~1.70;P<0.00001),NIHSS score(RR 2.91,95%CI 1.64~5.61;P=0.0003),early-onset epilepsy(RR 5.62,95%CI 5.08~6.22;P<0.00001),cortical lesions(RR 3.83.95%CI 2.23~6.58;P<0.00001),total anterior circulation infarction(RR 18.94,95%CI 10.38~34.57;P<0.00001),partial anterior circulation infarction(RR 4.39,95%CI 2.29~8.40;P<0.00001),cardiovascular events(RR 1.78,95%CI 1.59~1.99;P<0.00001).Conclusion:Based on a systematic review and meta-analysis,we developed a simple risk prediction model for late epilepsy in baseline ischemic stroke that integrates clinical risk factors,including infarct size,stroke recurrence,stroke etiology,stroke severity,NIHSS score,early onset epilepsy,cortical lesions,stroke subtype,and cardiovascular events.
