The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE ...The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.展开更多
AIM To investigate the incidence of disadvantageous events by using the Global Trigger Tool in an intensive care unit(ICU).METHODS A retrospective descriptive study was performed in a 12-bed university ICU in the city...AIM To investigate the incidence of disadvantageous events by using the Global Trigger Tool in an intensive care unit(ICU).METHODS A retrospective descriptive study was performed in a 12-bed university ICU in the city of Medellin, Colombia. Clinical charts of hospitalized patients were reviewed, between January 1 and December 31, 2016, with the following inclusion criteria: subjects aged over 18 years, with at least 24 h of hospitalization and who had a complete medical history that could be accessed. Interventions: Trained reviewers conducted a retros pective examination of medical charts searching for clue events that elicit investigation, in order to detect an unfavorable event. Measurements: Information was processed through SPSS softwareversion 21; for numerical variables, the mean was reported with standard deviation(SD). Percentages were calculated for qualitative variables. RESULTS Two hundred and forty-four triggers occurred, with 82.4% of subjects having presented with at least one and an average of 3.37 (SD 3.47). A total of 178 adverse events (AEs) took place in 48 individuals, with an incidence of 52.1%. On average, four events per patient were recorded, and for each unfortunate event, 1.98 triggers were presented. The most frequent displeasing issues were: pressure ulcers(17.6%), followed by complications or reactions to medical devices(4.3%), and lacerations or skin defects(3.7%); the least frequent was delayed diagnosis or treatment (0.56%). Thirty-eight point four percent of mishap events caused temporary damage that required intervention, and 48.9% of AEs were preventable. Comparison between AEs and admission diagnoses found that hypertension and sepsis were the only diagnoses that had statistical significance (P = 0.042 and 0.022, respectively).CONCLUSION Almost half of the unfavorable issues were classified as avoidable, which leaves a very wide field of work in terms of preventative activities.展开更多
This study discussed the water sector as a critical infrastructural element in Jordan where the sector is exposed to the extreme events. The exposure of the country to extreme events has initiated this study. Such eve...This study discussed the water sector as a critical infrastructural element in Jordan where the sector is exposed to the extreme events. The exposure of the country to extreme events has initiated this study. Such events are Pollution accidents, flooding, draughts, overexploitation, failure in electricity supply, climate changes, earthquakes, landslides, failure of dams, failure of wastewater treatment plants, failure of desalination plants, sabotage, fire, water theft, migration and demographic changes (immigration and urban migration), relations to neighboring countries, epidemics, and others. These extreme events are discussed in this article and the results show that failures in the water infrastructure and water supply, in Jordan, with its water sector situation have rigorous percussions on the country’s health, food supply, economy, societal stability, the built environment, and on other water-related issues. The study concludes that developing national programs to protect the water infrastructure in the water-fragile country has become very crucial to reach a robust and resilient water sector which not only means providing the inhabitants with quantitatively sufficient and qualitatively healthy water but also aims to incorporate guaranteeing social, economic and political stability.展开更多
Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients a...Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.展开更多
There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorr...There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform.For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system.Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena.Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system,there is evidence that it depends on the time series of the average force of the system.展开更多
Introduction: A lot of literature is available on critical incidents and near misses but specialty based critical incidents are very scanty. Aim: In this audit, we aimed to report critical incident and near misses dur...Introduction: A lot of literature is available on critical incidents and near misses but specialty based critical incidents are very scanty. Aim: In this audit, we aimed to report critical incident and near misses during conduct of obstetric anesthesia over a period of two years. Methodology: Critical incident forms were collected, entered, analyzed and categorized on the basis of American Standards Association (ASA), phase of incidents, system involved, and type of errors, outcome and action taken. Human error was further categorized on the basis of their contributing factor marked in form. Results: During the reporting period, 5511 anaesthetics were administered and 55 reports were received out of which 53 reports were included in analysis. Fifty three reports were divided into 33 critical incidents and 20 near misses. Out of 33 critical incidents, 54.5% involved CVS system and musculoskeletal system, followed by neuromuscular (n = 5), drug related (n = 4), airway/respiratory system (n = 2), central nervous system (n = 2) and renal system (n = 1). Forty five incidents possess no untoward effect while 7 led to minor and only one to severe physiological disturbance. Human errors were (n = 30) 57% reports and failure to check was the main contributory factor. Conclusion: Critical incidents reporting needs to be introduced in sub-specialties at departmental, national and international level. Checking of equipment, medication and anesthesia machine must be part of regular checks in elective and emergency cases.展开更多
目的分析急诊科危重症患者院内转运不良事件风险因素,构建风险预测模型。方法采用方便抽样法选取2021年10月至2023年2月某院急诊科进行院内转运的870例危重症患者的临床资料,采用单因素和多因素Logistic回归分析建立风险预测模型,以受...目的分析急诊科危重症患者院内转运不良事件风险因素,构建风险预测模型。方法采用方便抽样法选取2021年10月至2023年2月某院急诊科进行院内转运的870例危重症患者的临床资料,采用单因素和多因素Logistic回归分析建立风险预测模型,以受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under curve,AUC)评价模型预测效果。结果英国国家早期预警评分(national early warning score,NEWS)、血氧饱和度、急诊B超、血管活性药物、机械通气是急诊科危重症患者发生病情不良事件的独立风险因素;血氧饱和度、携氧装置、Ⅲ类管路、护工参与转运是技术不良事件的独立风险因素(均P<0.05)。AUC分别为0.813,0.756。结论构建的急诊科危重症患者院内转运不良事件风险预测模型具有一定的参考价值。展开更多
Floods caused by extreme weather events and climate change have increased in occurrence and severity all over the world,resulting in devastation and disruption of activities.Researchers and policy practitioners have i...Floods caused by extreme weather events and climate change have increased in occurrence and severity all over the world,resulting in devastation and disruption of activities.Researchers and policy practitioners have increasingly paid attention to the role of critical infrastructure(CI)in disaster risk reduction,flood resilience and climate change adaptation in terms of its backbone functions in maintaining societal services in hazard attacks.The analysed city in this study,Xinxiang(Henan province,China),was affected by an extreme flood event that occurred on 17–23 July 2021,which caused great socio-economic losses.However,few studies have focused on medium-sized cities and the flood cascading effects on CI during this event.Therefore,this study explores the damages caused by this flooding event with links to CI,such as health services,energy supply stations,shelters and transport facilities(HEST infrastructure).To achieve this,the study first combines RGB(red,green blue)composition and supervised classification for flood detection to monitor and map flood inundation areas.Second,it manages a multiscenario simulation and evaluates the cascading effects on HEST infrastructure.Diverse open-source data are employed,including Sentinel-1 synthetic aperture radar(SAR)data and Landsat-8 OIL data,point-of-interest(POI)and OpenStreetMap(OSM)data.The study reveals that this extreme flood event has profoundly affected croplands and villagers.Due to the revisiting period of Sentinel-1 SAR data,four scenarios are simulated to portray the retreated but‘omitted’floodwater:Scenario 0 is the flood inundation area on 27 July,and Scenarios 1,2 and 3 are built based on this information with a buffer of 50,100 and 150 m outwards,respectively.In the four scenarios,as the inundation areas expand,the affected HEST infrastructure becomes more clustered at the centre of the core study area,indicating that those located in the urban centre are more susceptible to flooding.Furthermore,the affected transport facilities assemble in the north and east of the core study area,implying that transport facilities located in the north and east of the core study area are more susceptible to flooding.The verification of the flood inundation maps and affected HEST infrastructure in the scenario simulation support the series method adopted in this study.The findings of this study can be used by flood managers,urban planners and other decision makers to better understand extreme historic weather events in China,improve flood resilience and decrease the negative impacts of such events on HEST infrastructure.展开更多
文摘The SHRP2 Naturalistic Driving Study was used to evaluate the impact of various work zone and driver characteristics on back of queue safety critical events (crash, near-crash, or conflicts) The model included 43 SCE and 209 “normal” events which were used as controls. The traces included representing 209 unique drivers. A Mixed-Effects Logistic Regression model was developed with probability of a SCE as the response variable and driver and work zone characteristics as predictor variables. The final model indicated glances over 1 second away from the driving task and following closely increased risk of an SCE by 3.8 times and 2.9 times, respectively. Average speed was negatively correlated to crash risk. This is counterintuitive since in most cases, it is expected that higher speeds are related to back of queue crashes. However, most queues form under congested conditions. As a result, vehicles encountering a back of queue would be more likely to be traveling at lower speeds.
文摘AIM To investigate the incidence of disadvantageous events by using the Global Trigger Tool in an intensive care unit(ICU).METHODS A retrospective descriptive study was performed in a 12-bed university ICU in the city of Medellin, Colombia. Clinical charts of hospitalized patients were reviewed, between January 1 and December 31, 2016, with the following inclusion criteria: subjects aged over 18 years, with at least 24 h of hospitalization and who had a complete medical history that could be accessed. Interventions: Trained reviewers conducted a retros pective examination of medical charts searching for clue events that elicit investigation, in order to detect an unfavorable event. Measurements: Information was processed through SPSS softwareversion 21; for numerical variables, the mean was reported with standard deviation(SD). Percentages were calculated for qualitative variables. RESULTS Two hundred and forty-four triggers occurred, with 82.4% of subjects having presented with at least one and an average of 3.37 (SD 3.47). A total of 178 adverse events (AEs) took place in 48 individuals, with an incidence of 52.1%. On average, four events per patient were recorded, and for each unfortunate event, 1.98 triggers were presented. The most frequent displeasing issues were: pressure ulcers(17.6%), followed by complications or reactions to medical devices(4.3%), and lacerations or skin defects(3.7%); the least frequent was delayed diagnosis or treatment (0.56%). Thirty-eight point four percent of mishap events caused temporary damage that required intervention, and 48.9% of AEs were preventable. Comparison between AEs and admission diagnoses found that hypertension and sepsis were the only diagnoses that had statistical significance (P = 0.042 and 0.022, respectively).CONCLUSION Almost half of the unfavorable issues were classified as avoidable, which leaves a very wide field of work in terms of preventative activities.
文摘This study discussed the water sector as a critical infrastructural element in Jordan where the sector is exposed to the extreme events. The exposure of the country to extreme events has initiated this study. Such events are Pollution accidents, flooding, draughts, overexploitation, failure in electricity supply, climate changes, earthquakes, landslides, failure of dams, failure of wastewater treatment plants, failure of desalination plants, sabotage, fire, water theft, migration and demographic changes (immigration and urban migration), relations to neighboring countries, epidemics, and others. These extreme events are discussed in this article and the results show that failures in the water infrastructure and water supply, in Jordan, with its water sector situation have rigorous percussions on the country’s health, food supply, economy, societal stability, the built environment, and on other water-related issues. The study concludes that developing national programs to protect the water infrastructure in the water-fragile country has become very crucial to reach a robust and resilient water sector which not only means providing the inhabitants with quantitatively sufficient and qualitatively healthy water but also aims to incorporate guaranteeing social, economic and political stability.
基金Supported by The Agency for Healthcare Research and Quality,No.R18HS02420-01
文摘Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11575072 and 11675096)the Fundamental Research Funds for the Central Universities,China(Grant No.GK201702001)the FPALAB-SNNU,China(Grant No.16QNGG007)
文摘There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform.For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system.Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena.Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system,there is evidence that it depends on the time series of the average force of the system.
文摘Introduction: A lot of literature is available on critical incidents and near misses but specialty based critical incidents are very scanty. Aim: In this audit, we aimed to report critical incident and near misses during conduct of obstetric anesthesia over a period of two years. Methodology: Critical incident forms were collected, entered, analyzed and categorized on the basis of American Standards Association (ASA), phase of incidents, system involved, and type of errors, outcome and action taken. Human error was further categorized on the basis of their contributing factor marked in form. Results: During the reporting period, 5511 anaesthetics were administered and 55 reports were received out of which 53 reports were included in analysis. Fifty three reports were divided into 33 critical incidents and 20 near misses. Out of 33 critical incidents, 54.5% involved CVS system and musculoskeletal system, followed by neuromuscular (n = 5), drug related (n = 4), airway/respiratory system (n = 2), central nervous system (n = 2) and renal system (n = 1). Forty five incidents possess no untoward effect while 7 led to minor and only one to severe physiological disturbance. Human errors were (n = 30) 57% reports and failure to check was the main contributory factor. Conclusion: Critical incidents reporting needs to be introduced in sub-specialties at departmental, national and international level. Checking of equipment, medication and anesthesia machine must be part of regular checks in elective and emergency cases.
文摘目的分析急诊科危重症患者院内转运不良事件风险因素,构建风险预测模型。方法采用方便抽样法选取2021年10月至2023年2月某院急诊科进行院内转运的870例危重症患者的临床资料,采用单因素和多因素Logistic回归分析建立风险预测模型,以受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under curve,AUC)评价模型预测效果。结果英国国家早期预警评分(national early warning score,NEWS)、血氧饱和度、急诊B超、血管活性药物、机械通气是急诊科危重症患者发生病情不良事件的独立风险因素;血氧饱和度、携氧装置、Ⅲ类管路、护工参与转运是技术不良事件的独立风险因素(均P<0.05)。AUC分别为0.813,0.756。结论构建的急诊科危重症患者院内转运不良事件风险预测模型具有一定的参考价值。
基金This research is co-funded by the National Youth Science Fund Project of the National Natural Science Foundation of China(52108050)the Guangdong Basic and Applied Basic Research Foundation(2023A1515011653)+2 种基金the Guangzhou Science and Technology Program(202201010503)the State Key Laboratory of Subtropical Building Science at South China University of Technology(2022ZB08)the China Postdoctoral Science Foundation(2021M701238).
文摘Floods caused by extreme weather events and climate change have increased in occurrence and severity all over the world,resulting in devastation and disruption of activities.Researchers and policy practitioners have increasingly paid attention to the role of critical infrastructure(CI)in disaster risk reduction,flood resilience and climate change adaptation in terms of its backbone functions in maintaining societal services in hazard attacks.The analysed city in this study,Xinxiang(Henan province,China),was affected by an extreme flood event that occurred on 17–23 July 2021,which caused great socio-economic losses.However,few studies have focused on medium-sized cities and the flood cascading effects on CI during this event.Therefore,this study explores the damages caused by this flooding event with links to CI,such as health services,energy supply stations,shelters and transport facilities(HEST infrastructure).To achieve this,the study first combines RGB(red,green blue)composition and supervised classification for flood detection to monitor and map flood inundation areas.Second,it manages a multiscenario simulation and evaluates the cascading effects on HEST infrastructure.Diverse open-source data are employed,including Sentinel-1 synthetic aperture radar(SAR)data and Landsat-8 OIL data,point-of-interest(POI)and OpenStreetMap(OSM)data.The study reveals that this extreme flood event has profoundly affected croplands and villagers.Due to the revisiting period of Sentinel-1 SAR data,four scenarios are simulated to portray the retreated but‘omitted’floodwater:Scenario 0 is the flood inundation area on 27 July,and Scenarios 1,2 and 3 are built based on this information with a buffer of 50,100 and 150 m outwards,respectively.In the four scenarios,as the inundation areas expand,the affected HEST infrastructure becomes more clustered at the centre of the core study area,indicating that those located in the urban centre are more susceptible to flooding.Furthermore,the affected transport facilities assemble in the north and east of the core study area,implying that transport facilities located in the north and east of the core study area are more susceptible to flooding.The verification of the flood inundation maps and affected HEST infrastructure in the scenario simulation support the series method adopted in this study.The findings of this study can be used by flood managers,urban planners and other decision makers to better understand extreme historic weather events in China,improve flood resilience and decrease the negative impacts of such events on HEST infrastructure.
