BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)adm...BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine learning.METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation.RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory rate.CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.展开更多
Objective: The aim was to evaluate the frequency of prolonged fevers and to determine their etiologies. Methods: We carried out a cross-sectional study extending from the period of 2009 to 2013 in the Internal Medicin...Objective: The aim was to evaluate the frequency of prolonged fevers and to determine their etiologies. Methods: We carried out a cross-sectional study extending from the period of 2009 to 2013 in the Internal Medicine department of the “G” Point University Hospital in Bamako. Included were all records of hospitalized patients with a central temperature greater than 37°C in the morning and 37°C in the evening, resting for 15 minutes, fasting for more than 2 hours, and absence of antipyretic treatment. We include all the patients of the study period with fever greater than 37.5°C in the morning and 37.8°C in the evening, resting for 15 minutes, fasting for more than 2 hours, and absence of antipyretic treatment, which have more than 21 days and measured on several occasions. The data were collected on a survey sheet. Data entry and analysis was done on SPSS software. Results: We recorded 243 fever cases out of 2155 hospitalizations, a prevalence rate of 11.2%. There were 128 men and 115 women with an average age of 43 years (range, 15 to 84 years), a modal class of 37 to 47 years, and a sex ratio of 1.11. The infectious etiologies accounted for 81% followed by neoplastic causes 09.6% and inflammatory 01.2% of cases. HIV infection was found in 26.4% of patients, malaria 13.5% and urinary tract infections 10.2%). Gram negative bacilli 88% consisted mainly of Escherichia coli (56%) and Klebsiella pneumoniae (20%).展开更多
This is a prospective and descriptive study carried out at the gynecology and obstetrics department of the reference health center of Fana from 01 May 2019 to 30 November or 7 months. The main objective was to study t...This is a prospective and descriptive study carried out at the gynecology and obstetrics department of the reference health center of Fana from 01 May 2019 to 30 November or 7 months. The main objective was to study the role of blood transfusion in the management of obstetric emergencies. During the study period we recorded 434 cases of obstetric emergencies of which 116 cases required an emergency blood transfusion or 26.73%. The most frequently found indications for blood transfusion are hemorrhages of the immediate postpartum 46.6% followed by severe malaria on pregnancy 27.6%. Blood remains the most prescribed and available Labile blood product in the department. Maternal prognosis was improved in 92.2%.展开更多
Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from ...Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from the rapidity and accuracy of the detection of physiological health indicators.However,long-term contact with equipment has many adverse effects.The purpose of this study was to improve the accuracy of HRV detection via noncontact equipment,thus enabling HRV to be assessed in various scenarios.Methods:A novel deep learning approach was proposed for measuring heartbeats through camera videos.First,we performed facial segmentation and divided the face into 16 grid cells with different light balance scores.After the trend is filtered by the Hamming window,a transformer-based neural network is used to further filter the signal.Finally,heart rate(HR)and HRV are estimated.Results:We used 1 million synthetic data points for pretraining and a public dataset in combination with a dataset that we constructed for task training.The final results were obtained on a test dataset that we constructed.The accuracy for HR with a low light balance score(0.867-0.983)was greater than that with a high score(0.667-0.750).Our method had higher accuracy in estimating HR than traditional filtering methods(0.167-0.417)and state-of-the-art neural network filtering methods(0.783-0.917)did.The root mean square error of the HRV from the time domain was the lowest,and the correlation index score was the highest for the HRV from the frequency domain estimated by our method compared with those estimated by two neural networks.Conclusions:Light balance,large sample training,and two-stage training can improve the accuracy of HRV estimation.展开更多
Rat nerve growth factor and total flavonoids from hawthorn leaf contribute to the recovery of neurological function after spinal cord injury,including traumatic,non-traumatic spinal cord injuries.However,it remains ch...Rat nerve growth factor and total flavonoids from hawthorn leaf contribute to the recovery of neurological function after spinal cord injury,including traumatic,non-traumatic spinal cord injuries.However,it remains challenging to efficiently deliver nerve growth factor and total flavonoids from hawthorn leaf to spinal cord injury sites,ensure their sustained release,and minimize further damage.In the present study,we chose a biocompatible and biodegradable gelatin as the substrate,which was crosslinked with the natural biological crosslinker genipin to form a gelatin-genipin hydrogel carrier for the slow release of nerve growth factor and total flavonoids from hawthorn leaf in spinal cord injury sites.The prepared gelatin-genipin hydrogel had good injectable properties and photothermal effects.Furthermore,when the hydrogel with 2%genipin,200 ng/mL nerve growth factor,and 320μg/mL total flavonoids from hawthorn leaf was combined with near infrared irradiation,there was a slow release of total flavonoids from hawthorn leaf and nerve growth factor,reduced oxidative stress,an improved inflammatory microenvironment,and accelerated angiogenesis and axonal regeneration via inhibition of the nuclear factor kappa-B signaling pathway,thereby promoting recovery from spinal cord injury.Collectively,our results indicate that this new hydrogel may improve the prognosis of spinal cord injury,and may represent a new strategy for treating spinal cord injury.展开更多
目的:探索全球关于外泌体在眼科中研究、热点及趋势,以期为今后该领域的相关研究提供理论依据和建设性的参考,促进该研究领域的深入发展。方法:检索中国知网(CNKI)数据库、Web of Science(WOS)核心合集数据库以及PubMed数据库自建库至20...目的:探索全球关于外泌体在眼科中研究、热点及趋势,以期为今后该领域的相关研究提供理论依据和建设性的参考,促进该研究领域的深入发展。方法:检索中国知网(CNKI)数据库、Web of Science(WOS)核心合集数据库以及PubMed数据库自建库至2024-05-20已发表的关于外泌体在眼科中的研究相关文献,并通过CiteSpace 6.3.R1和VOSviewer等软件对发文国家、发文机构、研究作者、高频关键词、爆点关键词及时间线等内容进行可视化分析。结果:纳入中文文献37篇,英文文献548篇。全球发文量位于前5位的国家分别为美国(130)、中国(80)、韩国(24)、英国(20篇)和日本(19篇),国外前3位发文机构分别为University of California System、Duke University(杜克大学)、Harvard University,国内前3位发文机构分别为青岛大学、暨南大学附属第一医院眼科、北京师范大学体育与运动学院。中英文高频关键词和爆点关键词的分析结果显示,全球外泌体在眼科的研究热点中文高频词主要集中在干眼、细胞外囊泡、间充质干细胞、间充质干细胞来源外泌体、眼表疾病、眼表炎症、生物标志物、视网膜保护、免疫性眼病、葡萄膜炎、退行性眼病、黄斑变性、糖尿病视网膜病变、新生血管、甲状腺相关眼病、青光眼等方面;英文高频词主要集中在dry eye、dry eye disease、delivery、regenerative medicine、uveal melanoma、protein及transplantation等方面,外泌体在眼科的研究从最初的基础生物学研究,逐步向眼部疾病发病机制的探索以及作为新兴的诊断和治疗手段方向过渡。结论:近5 a来外泌体在眼科领域的研究迅速开展,外泌体作为新的生物标志物或潜在治疗靶点,在眼科疾病中的发病机制和临床应用前景成为主流研究热点,其在眼科疾病的诊断、治疗和预防将是外泌体未来新的研究方向。展开更多
基金supported by the National Key Research and Development Program of China(2021YFC2500803)the CAMS Innovation Fund for Medical Sciences(2021-I2M-1-056).
文摘BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine learning.METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation.RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory rate.CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.
文摘Objective: The aim was to evaluate the frequency of prolonged fevers and to determine their etiologies. Methods: We carried out a cross-sectional study extending from the period of 2009 to 2013 in the Internal Medicine department of the “G” Point University Hospital in Bamako. Included were all records of hospitalized patients with a central temperature greater than 37°C in the morning and 37°C in the evening, resting for 15 minutes, fasting for more than 2 hours, and absence of antipyretic treatment. We include all the patients of the study period with fever greater than 37.5°C in the morning and 37.8°C in the evening, resting for 15 minutes, fasting for more than 2 hours, and absence of antipyretic treatment, which have more than 21 days and measured on several occasions. The data were collected on a survey sheet. Data entry and analysis was done on SPSS software. Results: We recorded 243 fever cases out of 2155 hospitalizations, a prevalence rate of 11.2%. There were 128 men and 115 women with an average age of 43 years (range, 15 to 84 years), a modal class of 37 to 47 years, and a sex ratio of 1.11. The infectious etiologies accounted for 81% followed by neoplastic causes 09.6% and inflammatory 01.2% of cases. HIV infection was found in 26.4% of patients, malaria 13.5% and urinary tract infections 10.2%). Gram negative bacilli 88% consisted mainly of Escherichia coli (56%) and Klebsiella pneumoniae (20%).
文摘This is a prospective and descriptive study carried out at the gynecology and obstetrics department of the reference health center of Fana from 01 May 2019 to 30 November or 7 months. The main objective was to study the role of blood transfusion in the management of obstetric emergencies. During the study period we recorded 434 cases of obstetric emergencies of which 116 cases required an emergency blood transfusion or 26.73%. The most frequently found indications for blood transfusion are hemorrhages of the immediate postpartum 46.6% followed by severe malaria on pregnancy 27.6%. Blood remains the most prescribed and available Labile blood product in the department. Maternal prognosis was improved in 92.2%.
基金National Natural Science Foundation of China,Grant/Award Number:72204169Department of Science and Technology of Sichuan Province,Grant/Award Number:2021YFS0393。
文摘Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from the rapidity and accuracy of the detection of physiological health indicators.However,long-term contact with equipment has many adverse effects.The purpose of this study was to improve the accuracy of HRV detection via noncontact equipment,thus enabling HRV to be assessed in various scenarios.Methods:A novel deep learning approach was proposed for measuring heartbeats through camera videos.First,we performed facial segmentation and divided the face into 16 grid cells with different light balance scores.After the trend is filtered by the Hamming window,a transformer-based neural network is used to further filter the signal.Finally,heart rate(HR)and HRV are estimated.Results:We used 1 million synthetic data points for pretraining and a public dataset in combination with a dataset that we constructed for task training.The final results were obtained on a test dataset that we constructed.The accuracy for HR with a low light balance score(0.867-0.983)was greater than that with a high score(0.667-0.750).Our method had higher accuracy in estimating HR than traditional filtering methods(0.167-0.417)and state-of-the-art neural network filtering methods(0.783-0.917)did.The root mean square error of the HRV from the time domain was the lowest,and the correlation index score was the highest for the HRV from the frequency domain estimated by our method compared with those estimated by two neural networks.Conclusions:Light balance,large sample training,and two-stage training can improve the accuracy of HRV estimation.
基金Guangxi Science and Technology Base and Talent Special Project,No.GuiKeAD24010037(to SZ)Guangxi Health Commission Self-Funded Research Project,No.Z-A20241029(to YL).
文摘Rat nerve growth factor and total flavonoids from hawthorn leaf contribute to the recovery of neurological function after spinal cord injury,including traumatic,non-traumatic spinal cord injuries.However,it remains challenging to efficiently deliver nerve growth factor and total flavonoids from hawthorn leaf to spinal cord injury sites,ensure their sustained release,and minimize further damage.In the present study,we chose a biocompatible and biodegradable gelatin as the substrate,which was crosslinked with the natural biological crosslinker genipin to form a gelatin-genipin hydrogel carrier for the slow release of nerve growth factor and total flavonoids from hawthorn leaf in spinal cord injury sites.The prepared gelatin-genipin hydrogel had good injectable properties and photothermal effects.Furthermore,when the hydrogel with 2%genipin,200 ng/mL nerve growth factor,and 320μg/mL total flavonoids from hawthorn leaf was combined with near infrared irradiation,there was a slow release of total flavonoids from hawthorn leaf and nerve growth factor,reduced oxidative stress,an improved inflammatory microenvironment,and accelerated angiogenesis and axonal regeneration via inhibition of the nuclear factor kappa-B signaling pathway,thereby promoting recovery from spinal cord injury.Collectively,our results indicate that this new hydrogel may improve the prognosis of spinal cord injury,and may represent a new strategy for treating spinal cord injury.
文摘目的:探索全球关于外泌体在眼科中研究、热点及趋势,以期为今后该领域的相关研究提供理论依据和建设性的参考,促进该研究领域的深入发展。方法:检索中国知网(CNKI)数据库、Web of Science(WOS)核心合集数据库以及PubMed数据库自建库至2024-05-20已发表的关于外泌体在眼科中的研究相关文献,并通过CiteSpace 6.3.R1和VOSviewer等软件对发文国家、发文机构、研究作者、高频关键词、爆点关键词及时间线等内容进行可视化分析。结果:纳入中文文献37篇,英文文献548篇。全球发文量位于前5位的国家分别为美国(130)、中国(80)、韩国(24)、英国(20篇)和日本(19篇),国外前3位发文机构分别为University of California System、Duke University(杜克大学)、Harvard University,国内前3位发文机构分别为青岛大学、暨南大学附属第一医院眼科、北京师范大学体育与运动学院。中英文高频关键词和爆点关键词的分析结果显示,全球外泌体在眼科的研究热点中文高频词主要集中在干眼、细胞外囊泡、间充质干细胞、间充质干细胞来源外泌体、眼表疾病、眼表炎症、生物标志物、视网膜保护、免疫性眼病、葡萄膜炎、退行性眼病、黄斑变性、糖尿病视网膜病变、新生血管、甲状腺相关眼病、青光眼等方面;英文高频词主要集中在dry eye、dry eye disease、delivery、regenerative medicine、uveal melanoma、protein及transplantation等方面,外泌体在眼科的研究从最初的基础生物学研究,逐步向眼部疾病发病机制的探索以及作为新兴的诊断和治疗手段方向过渡。结论:近5 a来外泌体在眼科领域的研究迅速开展,外泌体作为新的生物标志物或潜在治疗靶点,在眼科疾病中的发病机制和临床应用前景成为主流研究热点,其在眼科疾病的诊断、治疗和预防将是外泌体未来新的研究方向。
