Objectives of computerized decision support systems for mechanical ventilation are discussed. Questions considered are: Why is computerized decision support for mechanical ventilation important? What parameter(s) should be optimized? What are the differences between a single attribute and a multiattribute value function used for optimization? How is it possible to achieve optimization in clinical practice with existing ventilators? How does one solve the problem of acquiring measurement of data needed for closed loop control? The possibilities and limitations of three existing decision support systems are discussed. 1) Computerized protocols from LDS Hospital in Salt Lake City, Utah, USA. 2) Optimization Program (OPTPROG) developed jointly at the Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland and Medical Intensive Care Unit, Department of Medicine at Karolinska Institute, South Hospital, Stockholm, Department of Medical Informatics Linkoping University, Sweden. 3) Ventilator Therapy Planner (VENT-PLAN) from the Section on Medical Informatics at Stanford University, Palo Alto, California, USA. Strategies leading to an optimal computerized decision support system are proposed. These strategies include development of better measurement methods for blood gases and cardiac output, improvement of man-machine and machine-machine interaction and the selection of optimization criteria. Finally, research directed towards building quantitative, dynamic patient models based on computerized databases of mechanically ventilated patients are discussed.
{"title":"Current status of mechanical ventilation decision support systems: a review.","authors":"R Rudowski, T D East, R M Gardner","doi":"10.1023/a:1016952525892","DOIUrl":"https://doi.org/10.1023/a:1016952525892","url":null,"abstract":"<p><p>Objectives of computerized decision support systems for mechanical ventilation are discussed. Questions considered are: Why is computerized decision support for mechanical ventilation important? What parameter(s) should be optimized? What are the differences between a single attribute and a multiattribute value function used for optimization? How is it possible to achieve optimization in clinical practice with existing ventilators? How does one solve the problem of acquiring measurement of data needed for closed loop control? The possibilities and limitations of three existing decision support systems are discussed. 1) Computerized protocols from LDS Hospital in Salt Lake City, Utah, USA. 2) Optimization Program (OPTPROG) developed jointly at the Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland and Medical Intensive Care Unit, Department of Medicine at Karolinska Institute, South Hospital, Stockholm, Department of Medical Informatics Linkoping University, Sweden. 3) Ventilator Therapy Planner (VENT-PLAN) from the Section on Medical Informatics at Stanford University, Palo Alto, California, USA. Strategies leading to an optimal computerized decision support system are proposed. These strategies include development of better measurement methods for blood gases and cardiac output, improvement of man-machine and machine-machine interaction and the selection of optimization criteria. Finally, research directed towards building quantitative, dynamic patient models based on computerized databases of mechanically ventilated patients are discussed.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"157-66"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016952525892","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of automatic noninvasive blood pressure (NIBP) devices has become a common technique to monitor blood pressure intraoperatively. The usual cuff placement for these devices on the upper arm sometimes poses problems. As an alternative, many clinicians place the cuff on the ankle. This practice has not been previously investigated to determine its efficacy. The purpose of our study was to determine whether a noninvasive blood pressure cuff on the arm could be replaced by one on the ankle. We monitored 24 patients intraoperatively with two non-invasive blood pressure cuffs, one on the upper arm and one on the ankle. Systolic, diastolic, and mean pressures were obtained from each cuff placement at intervals of no shorter than 3 minutes. The time necessary to obtain the measurements and the presence of any artifact were also recorded. A total of 404 pairs of data were obtained and the systolic blood pressure ranged from 82 to 196 mm Hg. The mean and diastolic pressure readings were equivalent between the arm and ankle blood pressure readings. The systolic pressures were not equivalent, reflecting the fact that the ankle systolic blood pressure is physiologically higher than the arm systolic blood pressure. The difference between the times necessary to obtain the readings from arm or ankle was not statistically significant. Eight of the paired readings (2.0%) represented artifact, arbitrarily defined as a difference in mean blood pressure readings of 15 mm Hg between the arm and the ankle. Since the mean blood pressure readings obtained at the arm and at the ankle were statistically equivalent, we concluded that the ankle cuff placement provided a reliable alternative to the placement of the cuff on the arm.
使用自动无创血压(NIBP)装置已成为术中监测血压的常用技术。通常将这些装置放在上臂的袖带位置有时会产生问题。作为替代,许多临床医生将袖带放在脚踝上。这种做法以前没有被调查以确定其有效性。我们研究的目的是确定手臂上的无创血压袖带是否可以用脚踝上的袖带代替。我们对24例患者术中使用两个无创血压袖带进行监测,一个在上臂,一个在脚踝。收缩压、舒张压和平均压的测量间隔不短于3分钟。获得测量值所需的时间和任何人工制品的存在也被记录下来。共获得404对数据,收缩压范围为82 ~ 196 mm Hg,平均和舒张压读数在手臂和脚踝血压读数之间相等。收缩压不相等,反映了踝关节收缩压生理上高于手臂收缩压的事实。从手臂或脚踝获得读数所需的时间之间的差异没有统计学意义。8个配对读数(2.0%)代表伪影,任意定义为手臂和脚踝之间的平均血压读数相差15毫米汞柱。由于在手臂和脚踝处获得的平均血压读数在统计上是相等的,我们得出结论,脚踝袖带的放置提供了一个可靠的替代袖带在手臂上的位置。
{"title":"Ankle blood pressure measurement, an acceptable alternative to arm measurements.","authors":"F E Block, G T Schulte","doi":"10.1023/a:1016997232542","DOIUrl":"https://doi.org/10.1023/a:1016997232542","url":null,"abstract":"<p><p>The use of automatic noninvasive blood pressure (NIBP) devices has become a common technique to monitor blood pressure intraoperatively. The usual cuff placement for these devices on the upper arm sometimes poses problems. As an alternative, many clinicians place the cuff on the ankle. This practice has not been previously investigated to determine its efficacy. The purpose of our study was to determine whether a noninvasive blood pressure cuff on the arm could be replaced by one on the ankle. We monitored 24 patients intraoperatively with two non-invasive blood pressure cuffs, one on the upper arm and one on the ankle. Systolic, diastolic, and mean pressures were obtained from each cuff placement at intervals of no shorter than 3 minutes. The time necessary to obtain the measurements and the presence of any artifact were also recorded. A total of 404 pairs of data were obtained and the systolic blood pressure ranged from 82 to 196 mm Hg. The mean and diastolic pressure readings were equivalent between the arm and ankle blood pressure readings. The systolic pressures were not equivalent, reflecting the fact that the ankle systolic blood pressure is physiologically higher than the arm systolic blood pressure. The difference between the times necessary to obtain the readings from arm or ankle was not statistically significant. Eight of the paired readings (2.0%) represented artifact, arbitrarily defined as a difference in mean blood pressure readings of 15 mm Hg between the arm and the ankle. Since the mean blood pressure readings obtained at the arm and at the ankle were statistically equivalent, we concluded that the ankle cuff placement provided a reliable alternative to the placement of the cuff on the arm.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"167-71"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016997232542","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Observations on database design for improving clinical care.","authors":"T D McGhee","doi":"10.1023/a:1016974913574","DOIUrl":"https://doi.org/10.1023/a:1016974913574","url":null,"abstract":"","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"143-5"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016974913574","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Abstracts of the Seventeeth Annual Conference on Computers in Anesthesia, New Orleans, Louisiana, October 23–26, 1996","authors":"Bradley E. Smith, D. G. Hess","doi":"10.1007/BF02915840","DOIUrl":"https://doi.org/10.1007/BF02915840","url":null,"abstract":"","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 1","pages":"191-206"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/BF02915840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52606815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulators may be used in training personnel for the situations when consequences of inappropriate action could be dangerous or expensive. Mishaps and accidents in connection with the use of biomedical instrumentation are frequently a result of technical malfunction and improper use of the equipment. In the medical field, however, use of simulators is not very common. This paper reports our experiences of a development project to design the "PatSim' hands-on simulator for training anaesthesia and intensive care personnel. The simulator consists of a manikin positioned on an operation table or in a typical critical care bed. The manikin, which is controlled by a standard personal computer (PC), can be ventilated by an anaesthesia machine or a ventilator, intravenous pumps can also be connected. Any standard electrodes and transducers can be used to pick up parameters, like ECG, invasive and non-invasive blood pressure, airway pressure and CO2. Data can be displayed on any monitor or workstation. There is no need for modification or special adaptation of the medical equipment used in the simulation scenario. The manikin is capable of spontaneous breathing. Controlled from the PC, different clinical signs can be developed. In addition, typical clinical symptoms can be created during the simulated treatment period. They include laryngospasm, change of lung compliance or airway resistance, pneumothorax, leakage of the intubation tube cuff, blocking of the breathing sounds from one lung, secretion, gastric regurgitation and diuresis. During a simulation session, the trainee should be exposed to a lifelike situation. Hence, we place the manikin in a room that resembles either intensive care or operating room environment.
{"title":"PatSim--simulator for practising anaesthesia and intensive care. Development and observations.","authors":"R Arne, F Ståle, K Ragna, L Petter","doi":"10.1023/a:1016964810485","DOIUrl":"https://doi.org/10.1023/a:1016964810485","url":null,"abstract":"<p><p>Simulators may be used in training personnel for the situations when consequences of inappropriate action could be dangerous or expensive. Mishaps and accidents in connection with the use of biomedical instrumentation are frequently a result of technical malfunction and improper use of the equipment. In the medical field, however, use of simulators is not very common. This paper reports our experiences of a development project to design the \"PatSim' hands-on simulator for training anaesthesia and intensive care personnel. The simulator consists of a manikin positioned on an operation table or in a typical critical care bed. The manikin, which is controlled by a standard personal computer (PC), can be ventilated by an anaesthesia machine or a ventilator, intravenous pumps can also be connected. Any standard electrodes and transducers can be used to pick up parameters, like ECG, invasive and non-invasive blood pressure, airway pressure and CO2. Data can be displayed on any monitor or workstation. There is no need for modification or special adaptation of the medical equipment used in the simulation scenario. The manikin is capable of spontaneous breathing. Controlled from the PC, different clinical signs can be developed. In addition, typical clinical symptoms can be created during the simulated treatment period. They include laryngospasm, change of lung compliance or airway resistance, pneumothorax, leakage of the intubation tube cuff, blocking of the breathing sounds from one lung, secretion, gastric regurgitation and diuresis. During a simulation session, the trainee should be exposed to a lifelike situation. Hence, we place the manikin in a room that resembles either intensive care or operating room environment.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"147-52"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016964810485","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F E Block, K M Reynolds, T Kajaste, K Nourijelyani
The growing number of patients admitted for outpatient surgery or for same-day admission makes it difficult to obtain thorough pulmonary evaluation. We wanted to evaluate the applicability of pre-operative pulse oximetry and capnography as possible pulmonary screening tools. In this preliminary study, 200 unselected, unmedicated adult patients who were being admitted for surgery were connected to a dual parameter patient monitor (Capnomac Ultima, Datex). A standard adult clip-on finger probe was used for pulse oximetric oxygen saturation. Sidestream capnometry documented the end-tidal carbon dioxide and the capnogram which was recorded for further analysis. In these unmedicated patients, the oxygen saturation ranged from 91 to 99% and was found to be 94% or less in five percent (N = 10) of the cases. The end-tidal carbon dioxide ranged from 21 to 48 mmHg. In five percent of the cases (N = 10) it was found to be 45 mmHg or higher, reflecting elevated arterial CO2. When the shape of the capnogram was rated, it was found normal in 54% of the cases. Slow rising capnogram, indicating mild (N = 84) or moderate (N = 8) airway obstruction was detected in 42% or 4% of the cases respectively. Since pulse oximeter and end-tidal carbon dioxide values are often not measured until after sedation or after induction of anesthesia, patients with pre-operative abnormalities might escape pre-operative detection. In unmedicated patients, routine pre-operative or pre-admission determination of oxygen saturation, end-tidal carbon dioxide and the capnogram may be a valuable screening tool.
{"title":"Pre-operative oximetry and capnometry: potential respiratory screening tools.","authors":"F E Block, K M Reynolds, T Kajaste, K Nourijelyani","doi":"10.1007/BF02915835","DOIUrl":"https://doi.org/10.1007/BF02915835","url":null,"abstract":"<p><p>The growing number of patients admitted for outpatient surgery or for same-day admission makes it difficult to obtain thorough pulmonary evaluation. We wanted to evaluate the applicability of pre-operative pulse oximetry and capnography as possible pulmonary screening tools. In this preliminary study, 200 unselected, unmedicated adult patients who were being admitted for surgery were connected to a dual parameter patient monitor (Capnomac Ultima, Datex). A standard adult clip-on finger probe was used for pulse oximetric oxygen saturation. Sidestream capnometry documented the end-tidal carbon dioxide and the capnogram which was recorded for further analysis. In these unmedicated patients, the oxygen saturation ranged from 91 to 99% and was found to be 94% or less in five percent (N = 10) of the cases. The end-tidal carbon dioxide ranged from 21 to 48 mmHg. In five percent of the cases (N = 10) it was found to be 45 mmHg or higher, reflecting elevated arterial CO2. When the shape of the capnogram was rated, it was found normal in 54% of the cases. Slow rising capnogram, indicating mild (N = 84) or moderate (N = 8) airway obstruction was detected in 42% or 4% of the cases respectively. Since pulse oximeter and end-tidal carbon dioxide values are often not measured until after sedation or after induction of anesthesia, patients with pre-operative abnormalities might escape pre-operative detection. In unmedicated patients, routine pre-operative or pre-admission determination of oxygen saturation, end-tidal carbon dioxide and the capnogram may be a valuable screening tool.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"153-6"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/BF02915835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes a microcomputer system for automating the process of data collection, calculation and display of anaerobic capacity tests on an air-braked ergometer. The use of the spreadsheet Excel and associated 'Dalog' program represents an advance on current software which estimates the anaerobic capacity from work performed alone. Numerous calculations are required when air-braked, rather than friction-braked erogometers are used. Each 1 s power output collected during an all-out sprint on the ergometer is corrected against the criterion of a dynamic calibration rig and adjusted for differences in barometric pressure, ambient temperature and humidity. The Excel template features a series of macros invoked by buttons imbedded in the spreadsheet. Their selection displays various dialogue boxes which request input related to the calculation of oxygen deficit and related variables. Selecting the final macro prints a summary table and charts which include: power output, fatigue index, mechanical work performed, % aerobic contribution to work, oxygen demand, oxygen consumption and anaerobic capacity as determined by the maximal accumulated oxygen deficit.
{"title":"A macro-driven Excel template for determining the anaerobic capacity using an air-braked ergometer.","authors":"J P Finn, D A Sainsbury, R T Withers","doi":"10.1023/a:1016940211820","DOIUrl":"https://doi.org/10.1023/a:1016940211820","url":null,"abstract":"<p><p>This paper describes a microcomputer system for automating the process of data collection, calculation and display of anaerobic capacity tests on an air-braked ergometer. The use of the spreadsheet Excel and associated 'Dalog' program represents an advance on current software which estimates the anaerobic capacity from work performed alone. Numerous calculations are required when air-braked, rather than friction-braked erogometers are used. Each 1 s power output collected during an all-out sprint on the ergometer is corrected against the criterion of a dynamic calibration rig and adjusted for differences in barometric pressure, ambient temperature and humidity. The Excel template features a series of macros invoked by buttons imbedded in the spreadsheet. Their selection displays various dialogue boxes which request input related to the calculation of oxygen deficit and related variables. Selecting the final macro prints a summary table and charts which include: power output, fatigue index, mechanical work performed, % aerobic contribution to work, oxygen demand, oxygen consumption and anaerobic capacity as determined by the maximal accumulated oxygen deficit.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"179-89"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016940211820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model-driven infusion systems in anaesthesia overcome the difficulties in obtaining on-line measurements of controlled variables. A linear pharmacokinetic model for ketamine was used to achieve target blood concentrations and was implemented using a palmtop PC. Although the use of ketamine for analgesia in total intravenous anaesthesia with propofol has been reported, this is the first such application to spontaneously breathing patients. Preliminary results show this to be a useful system, which may easily be applied to other intravenous anaesthetic agents.
{"title":"Development of a pharmacokinetic model-based infusion system for ketamine analgesia.","authors":"D G Mason, C F Swinhoe, D A Linkens, C S Reilly","doi":"10.1023/a:1016990604121","DOIUrl":"https://doi.org/10.1023/a:1016990604121","url":null,"abstract":"<p><p>Model-driven infusion systems in anaesthesia overcome the difficulties in obtaining on-line measurements of controlled variables. A linear pharmacokinetic model for ketamine was used to achieve target blood concentrations and was implemented using a palmtop PC. Although the use of ketamine for analgesia in total intravenous anaesthesia with propofol has been reported, this is the first such application to spontaneously breathing patients. Preliminary results show this to be a useful system, which may easily be applied to other intravenous anaesthetic agents.</p>","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 3","pages":"139-42"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1023/a:1016990604121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Future developments with the Internet: some personal predictions.","authors":"D J Doyle","doi":"10.1007/BF02915845","DOIUrl":"https://doi.org/10.1007/BF02915845","url":null,"abstract":"","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 2","pages":"95-8"},"PeriodicalIF":0.0,"publicationDate":"1996-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/BF02915845","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In-house approach to develop a complete information management system for an anaesthesia department.","authors":"P Conze, F Schreurs, R Droh","doi":"10.1007/BF02915844","DOIUrl":"https://doi.org/10.1007/BF02915844","url":null,"abstract":"","PeriodicalId":77181,"journal":{"name":"International journal of clinical monitoring and computing","volume":"13 2","pages":"93-4"},"PeriodicalIF":0.0,"publicationDate":"1996-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/BF02915844","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"19876279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}