Objective:Early and accurate identification of large vessel occlusion(LVO)acute ischemic stroke(AIS)patients is critically important for stroke management.Practicable scales with simple items can facilitate prehospita...Objective:Early and accurate identification of large vessel occlusion(LVO)acute ischemic stroke(AIS)patients is critically important for stroke management.Practicable scales with simple items can facilitate prehospital paramedics distinguishing LVO-AIS patients with high efficiency and help to avoid unnecessary and costly delays.The current study aims to develop a screening tool to predict AIS-LVO patients based on prehospital available data.Method:A total of 251 suspected stroke patients who were transported to the emergency department of our hospital via emergency medical services were consecutively enrolled from August,2020 to January,2022.Data including demographic information,medical history,clinical manifestations,and vital signs were collected.A multivariate logistic regression model was developed based on statistically significant variables selected from univariate analysis.Result:Forty-two patients(16.7%)were diagnosed as LVO-AIS based on imaging validation at admission.A comprehensive model was developed with past medical history factors such as atrial fibrillation and coronary heart disease,vital signs such as systolic blood pressure,and prominent symptoms and signs such as gaze palsy,facial paralysis,and dysarthria.The model showed better diagnostic performance in terms of area under the receiver operating characteristic curves(0.884,95%CI,0.830-0.939),which was higher than other common prehospital prediction scales such as the Face,Arm,Speech,Time test(FAST),the Field Assessment Stroke Triage for Emergency Destination(FAST-ED)scale,and the Gaze-Face-Arm-Speech-Time test(G-FAST).Calibration curve analysis,decision curve analysis,and clinical impact curve analysis further validated the reliability,net benefit,and potential clinical impact of the prediction model,respectively.Conclusion:We conducted a prediction model based on prehospital accessible factors including past history of atrial fibrillation and coronary heart disease,systolic blood pressure,and signs such as gaze palsy,facial palsy,and dysarthria.The prediction model showed good diagnostic power and accuracy for identification of the high-risk patients with LVO and may become an effective tool for the LVO recognition in prehospital settings.Future studies are warranted to refine and validate the model further in order to enhance the accuracy and objectivity of clinical judgments.展开更多
Brain diseases,mainly including acute brain injuries,neurodegenerative diseases,and mental disorders,have posed a significant threat to human health worldwide.Due to the limited regenerative capability and the existen...Brain diseases,mainly including acute brain injuries,neurodegenerative diseases,and mental disorders,have posed a significant threat to human health worldwide.Due to the limited regenerative capability and the existence of the blood–brain barrier,the brain was previously thought to be separated from the rest of the body.Currently,various cross-talks between the central nervous system and peripheral organs have been widely described,including the brain-gut axis,the brain-liver axis,the brain-skeletal muscle axis,and the brain-bone axis.Moreover,several lines of evidence indicate that leveraging systemic biology intervention approaches,including but not limited to lifestyle interventions,exercise,diet,blood administration,and peripheral immune responses,have demonstrated a significant influence on the progress and prognosis of brain diseases.The advancement of innovative proteomic and transcriptomic technologies has enriched our understanding of the nuanced interplay between peripheral organs and brain diseases.An array of novel or previously underappreciated blood-derived factors have been identified to play pivotal roles in mediating these communications.In this review,we provide a comprehensive summary of blood-to-brain communication following brain diseases.Special attention is given to the instrumental role of blood-derived signals,positing them as significant contributors to the complex process of brain diseases.The insights presented here aim to bridge the current knowledge gaps and inspire novel therapeutic strategies for brain diseases.展开更多
基金sponsored by National Natural Science Foundation of China(No.82101389 and 81971114)Beijing Nova Program(No.20230484286)General Project of Science and Technology of Beijing Municipal Education Commission(No.KM202110025018).
文摘Objective:Early and accurate identification of large vessel occlusion(LVO)acute ischemic stroke(AIS)patients is critically important for stroke management.Practicable scales with simple items can facilitate prehospital paramedics distinguishing LVO-AIS patients with high efficiency and help to avoid unnecessary and costly delays.The current study aims to develop a screening tool to predict AIS-LVO patients based on prehospital available data.Method:A total of 251 suspected stroke patients who were transported to the emergency department of our hospital via emergency medical services were consecutively enrolled from August,2020 to January,2022.Data including demographic information,medical history,clinical manifestations,and vital signs were collected.A multivariate logistic regression model was developed based on statistically significant variables selected from univariate analysis.Result:Forty-two patients(16.7%)were diagnosed as LVO-AIS based on imaging validation at admission.A comprehensive model was developed with past medical history factors such as atrial fibrillation and coronary heart disease,vital signs such as systolic blood pressure,and prominent symptoms and signs such as gaze palsy,facial paralysis,and dysarthria.The model showed better diagnostic performance in terms of area under the receiver operating characteristic curves(0.884,95%CI,0.830-0.939),which was higher than other common prehospital prediction scales such as the Face,Arm,Speech,Time test(FAST),the Field Assessment Stroke Triage for Emergency Destination(FAST-ED)scale,and the Gaze-Face-Arm-Speech-Time test(G-FAST).Calibration curve analysis,decision curve analysis,and clinical impact curve analysis further validated the reliability,net benefit,and potential clinical impact of the prediction model,respectively.Conclusion:We conducted a prediction model based on prehospital accessible factors including past history of atrial fibrillation and coronary heart disease,systolic blood pressure,and signs such as gaze palsy,facial palsy,and dysarthria.The prediction model showed good diagnostic power and accuracy for identification of the high-risk patients with LVO and may become an effective tool for the LVO recognition in prehospital settings.Future studies are warranted to refine and validate the model further in order to enhance the accuracy and objectivity of clinical judgments.
基金supported by the National Natural Science Foundation of China(82071466,82371470,82071468,and 82201618)the“Sail Plan”Key Medical Specialty(ZYLX202139)+2 种基金the“Mission”Talent Project of Beijing Municipal Administration of Hospitals(SML20150802)the Beijing Municipal Science and Technology Project(Z181100001918026)the Project for Innovation and Development of Beijing Municipal Geriatric Medical Research Center(11000023T000002036320)。
文摘Brain diseases,mainly including acute brain injuries,neurodegenerative diseases,and mental disorders,have posed a significant threat to human health worldwide.Due to the limited regenerative capability and the existence of the blood–brain barrier,the brain was previously thought to be separated from the rest of the body.Currently,various cross-talks between the central nervous system and peripheral organs have been widely described,including the brain-gut axis,the brain-liver axis,the brain-skeletal muscle axis,and the brain-bone axis.Moreover,several lines of evidence indicate that leveraging systemic biology intervention approaches,including but not limited to lifestyle interventions,exercise,diet,blood administration,and peripheral immune responses,have demonstrated a significant influence on the progress and prognosis of brain diseases.The advancement of innovative proteomic and transcriptomic technologies has enriched our understanding of the nuanced interplay between peripheral organs and brain diseases.An array of novel or previously underappreciated blood-derived factors have been identified to play pivotal roles in mediating these communications.In this review,we provide a comprehensive summary of blood-to-brain communication following brain diseases.Special attention is given to the instrumental role of blood-derived signals,positing them as significant contributors to the complex process of brain diseases.The insights presented here aim to bridge the current knowledge gaps and inspire novel therapeutic strategies for brain diseases.
基金supported by the National Natural Science Foundation of China(82027802,82171304,82071466,81771260,81871022,82071468,and 82201618)“Sail Plan”Key Medical Specialty(ZYLX202139)+2 种基金“Mission”Talent Project of Beijing Municipal Administration of Hospitals(SML20150802)Beijing Municipal Science and Technology Project(Z181100001918026)Technological Innovation and Service Capability Construction Project From Beijing Municipal Commission of Education(11000023T000002157177)。