Journal of Intensive Care Medicine最新文献

{"title":"Acute Esophageal Necrosis Associated with Alcoholic Ketoacidosis A Case Report.","authors":"Laurin Egli, Alexa Hollinger, Anne Leuppi-Taegtmeyer, Martin Siegemund","doi":"10.1177/08850666251341813","DOIUrl":"10.1177/08850666251341813","url":null,"abstract":"<p><p>Acute esophageal necrosis (AEN) is a rare condition associated with ischemia of the esophagus, corrosive injury by gastric fluids and reduced mucosal defense. It is also referred to as \"Black Esophagus\" or \"Gurvit's syndrome\". Its clinical presentation is most notable for upper gastrointestinal bleeding with signs and symptoms such as abdominal or epigastric pain, nausea, vomiting, dysphagia and fever. AEN is diagnosed via esophagogastroduodenoscopy, where the cardinal finding is a circumferential black discoloration of the esophagus, usually most pronounced in the distal esophagus. The lesion usually stops abruptly at the gastroesophageal junction. AEN is usually seen in older men with multiple comorbidities (eg, cardiovascular disease, diabetes mellitus) and follows a triggering event (eg, sepsis, diabetic ketoacidosis). We describe the case of a 28-year-old man presenting with acute esophageal necrosis associated with alcoholic ketoacidosis after excessive alcohol consumption, prolonged starvation and self-reported increased intake of venlafaxine and quetiapine.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"686-690"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Combined Model of Vital Signs and Serum Biomarkers Outperforms Shock Index in the Prediction of Hemorrhage Control Interventions in Surgical Intensive Care Unit Patients.","authors":"John P Forrester, Manuel Beltran Del Rio, Cristine H Meyer, Samuel P R Paci, Ella R Rastegar, Timmy Li, Maria G Sfakianos, Eric N Klein, Matthew E Bank, Daniel M Rolston, Nathan A Christopherson, Daniel Jafari","doi":"10.1177/08850666241312614","DOIUrl":"10.1177/08850666241312614","url":null,"abstract":"<p><p>BackgroundDistinguishing surgical intensive care unit (ICU) patients with ongoing bleeding who require hemorrhage control interventions (HCI) can be challenging. Guidelines recommend risk-stratification with clinical variables and prediction tools, however supporting evidence remains mixed.MethodsThis retrospective study evaluated adult patients admitted to the surgical ICU with concern for ongoing hemorrhage under our institution's \"Hemorrhage Watch\" (HW) protocol and aimed to derive a clinical prediction model identifying those needing HCI with serial vital signs (VS) and serum biomarkers. The HW protocol included ICU admission followed by a 3-h observation period with VS monitoring every 15 min and hourly biomarkers. The primary outcome was the need for HCI (operative and endovascular interventions) within nine hours of ICU arrival. Secondary outcomes included in-hospital mortality, blood transfusions, and ICU and hospital length-of-stay. A clinical prediction model was developed by utilizing the variables most associated with HCI in a best subsets regression, which was subsequently internally validated using a Bootstrap algorithm.Results305 patients were identified for inclusion and 18 (5.9%) required HCI (3 operative, 15 endovascular). The median age was 70 years (IQR 54, 83), 60% had traumatic injuries, and 73% were enrolled from the emergency department. Blood product transfusion and mortality were similar between the HCI and no-HCI groups. Our analysis demonstrated that a model based on the minimum hemoglobin (9.9 vs 8.1 g/dL), minimum diastolic (57 vs 53 mm Hg) and systolic blood pressures (105 vs 90 mm Hg), and minimum respiratory rate (15 vs 18) could predict HCI with an area under the Receiver Operating Characteristics curve (AUROC) of 0.87, outperforming the Shock Index (SI) (AUROC = 0.64).ConclusionsIn this study of surgical ICU patients with concern for ongoing bleeding, a prediction model using serial VS and biomarkers outperformed the SI and may help identify those requiring HCI.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"632-641"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143382693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survival of Patients with Solid Tumours and Sepsis Admitted to Intensive Care in a Tertiary Oncology Centre: A Retrospective Analysis.","authors":"Sam S Smith, Luke Edwards, Timothy Wigmore, Shaman Jhanji, David B Antcliffe, Kate C Tatham","doi":"10.1177/08850666241312621","DOIUrl":"10.1177/08850666241312621","url":null,"abstract":"<p><p>IntroductionSepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Patients with cancer are at risk of developing sepsis and requiring intensive care unit (ICU) admission. We aimed to assess survival of patients with a solid tumour admitted to ICU as an emergency with sepsis, and to identify predictors of 90-day survival at admission.Materials and MethodsWe conducted a retrospective cohort survival analysis. We identified adults with a solid tumour admitted to ICU with sepsis between 01/01/2011 and 31/12/2020 at a tertiary oncology centre with two hospitals (London and Surrey, UK). We defined sepsis using the Sepsis-3 definition. The primary outcome was 90-day survival. We used the parametric accelerated failure time model for multivariate analysis to generate acceleration factors (AF).Results625 patients were identified and the 90-day survival rate was 59.5%(353/593).Multivariate analysis identified the presence of localized (AF 0.13, 95% CI 0.06-0.25) or regionalized disease (AF 0.21, 95% CI 0.12-0.36) compared to distant metastatic disease, unplanned surgery on the day of admission (AF 0.15, 95% CI 0.07-0.31), lactate (AF 1.25 95% CI 1.15-1.35), Sequential Organ Failure Assessment Score (AF 1.19, 95% CI 1.12-1.27), previous radiotherapy (AF 1.89, 95% CI 1.14-3.125), previous systemic anti-cancer treatment (excluding hormonal therapy) (AF 1.49, 95% CI 0.93-2.38), bacteraemia (AF 0.47, 95% CI 0.27-0.81) and serum albumin (AF 0.94, 95% CI 0.91-0.98) as independent predictors of 90-day survival.ConclusionsThis study of solid tumour patients admitted to ICU is one of the largest providing survival data to inform clinicians and patients. This data provides information on factors that should be considered when deliberating the possible outcome of ICU admission for a patient with solid malignancy and sepsis and highlights that the presence of cancer itself should not limit ICU admission for sepsis.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"642-650"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12095884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143052821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anticoagulation Monitoring Strategies During Extracorporeal Membrane Oxygenation (ECMO) Therapy - Differences Between Simultaneously Obtained Coagulation Tests: A Retrospective Single-Center Cohort Study.","authors":"Alexander C Reisinger, Nikolaus Schneider, Marco Koellinger, Stefan Hatzl, Gerald Hackl, Reinhard Raggam, Dirk von Lewinski, Florian Posch, Philipp Eller","doi":"10.1177/08850666241313357","DOIUrl":"10.1177/08850666241313357","url":null,"abstract":"<p><p>IntroductionDuring extracorporeal membrane oxygenation (ECMO) systemic anticoagulation with unfractionated heparin (UFH) is standard-of-care. However, there is uncertainty regarding optimal anticoagulation monitoring strategies.MethodsWe retrospectively investigated venovenous and venoarterial ECMO patients at the medical ICUs at the Medical University of Graz, Austria. We analyzed the correlation and concordance of R-time in thromboelastography (TEG), activated partial thromboplastin time (aPTT), and anti-Xa activity. The proportion within target range, the association of coagulation parameters above or below target range (aPTT 54-72 s; equals 1.5-2× upper limit of normal (ULN), anti-Xa activity 0.2-0.5 U/mL, and R-time in assays without heparinase 675-900 s; equals 1.5-2× ULN) with mortality, bleeding events and thrombotic complications were investigated.ResultsWe analyzed 671 clusters of simultaneously performed coagulation tests in 85 ECMO cases that fulfilled inclusion criteria. Median age of patients was 57 years and 32% were female. There were poor correlations between the three coagulation tests and the proportion of discordance was 46%. Within the target range were 21% of R-time, 15% of aPTT, and 44% of anti-Xa activity measurements. Singular and multiple bleeding events occurred in 25 and 32 patients, respectively. The most common bleeding locations were catheter and cannula insertion sites followed by pulmonary hemorrhage. In VA-ECMO, anti-Xa activity was associated (OR 1.03 [1.01-1.06], p = 0.005) and correlated with bleeding events (spearman rho 0.49, p = 0.002; point biserial 0.49, p = 0.001). aPTT level below target range was associated with reduced mortality (OR 0.98 [0.97-0.99], p = 0.024). Thrombotic events occurred in six patients with no association of coagulation tests.ConclusionThere was a high rate of discordance and poor correlation between aPTT, anti-Xa activity and R-time in TEG in ECMO patients. We found high rates of bleeding events and in VA-ECMO an association with elevated anti-Xa activity levels.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"651-659"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143255816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Practical Guide to Biostatistics Used in the <i>Journal of Intensive Care Medicine</i>.","authors":"Emma Kar, Asahi Murata, Chase Irwin, Eric vanSonnenberg","doi":"10.1177/08850666251318692","DOIUrl":"10.1177/08850666251318692","url":null,"abstract":"<p><p>IntroductionBiostatistics is an increasing focus in both the United States Medical Licensing exams (USMLE) and medical school curricula. Nonetheless, literature has documented that it is poorly understood among both practicing physicians and physician trainees. Our purpose is to narrow this knowledge gap by offering readers a \"how-to\" guide that both supplements essential biostatistics knowledge and assists in constructing research projects.MethodsIn Part II of our tandem manuscripts, we expand our Part I biostatistics analysis of research articles in the <i>Journal of Intensive Care Medicine (JICM)</i> with explanations and practical use of biostatistics, addressing the most common statistical terms and tests used in the <i>JICM</i>.ResultsUnderstanding biostatistics requires interpreting the type of study, type of data collected, statistical tests available for all types of data, and results of the statistical tests.ConclusionGaining proficiency in biostatistics will improve the precision of evidence-based medical outcomes, helping close the current knowledge gap among practicing physicians and trainees.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"669-676"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143467955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Updated Review of Radiologic Imaging and Intervention for Acute Pancreatitis and Its Complications.","authors":"Joshua Willis, Eric vanSonnenberg","doi":"10.1177/08850666241234596","DOIUrl":"10.1177/08850666241234596","url":null,"abstract":"<p><p>This is a current update on radiologic imaging and intervention of acute pancreatitis and its complications. In this review, we define the various complications of acute pancreatitis, discuss the imaging findings, as well as the timing of when these complications occur. The various classification and scoring systems of acute pancreatitis are summarized. Advantages and disadvantages of the 3 primary radiologic imaging modalities are compared. We then discuss radiologic interventions for acute pancreatitis. These include diagnostic aspiration as well as percutaneous catheter drainage of fluid collections, abscesses, pseudocysts, and necrosis. Recommendations for when these interventions should be considered, as well as situations in which they are contraindicated are discussed. Fortunately, acute pancreatitis usually is mild; however, serious complications occur in 20%, and admission of patients to the intensive care unit (ICU) occurs in over 10%. In this paper, we will focus on the imaging and interventional radiologic aspects for the serious complications and patients admitted to the ICU.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"588-597"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139983070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing Data Misinterpretation in Recent Meta-Analysis.","authors":"Kristin Alm-Kruse, Jo Kramer-Johansen","doi":"10.1177/08850666251341255","DOIUrl":"10.1177/08850666251341255","url":null,"abstract":"","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"691-692"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12095878/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Statistics Utilized in Primary Articles in the <i>Journal of Intensive Care Medicine</i>: A Prelude to Practical Pedagogy in Biostatistics.","authors":"Asahi Murata, Emma Kar, Chase Irwin, Eric vanSonnenberg","doi":"10.1177/08850666251318683","DOIUrl":"10.1177/08850666251318683","url":null,"abstract":"<p><p>BackgroundBiostatistics is an increasing focus in current medical school curricula. This study evaluated the statistical methods utilized in a high-impact factor medical Journal to develop a guide to those statistics that can be applied to facilitate the interpretation of data for practicing physicians, fellows, residents, and medical students.MethodsIn Part 1 of our tandem manuscripts, the 100 most recent primary articles from February 2021 to December 2021 were analyzed from the <i>Journal of Intensive Care Medicine</i>. The evaluation consisted of study temporality, study design, types of descriptor variables, and types of statistical tests.ResultsRetrospective studies were most common (75/100, 75%), followed by prospective studies (23/100, 23%). The most popular designs were cohort (82/100, 82%), followed by case series (9/100, 9%), randomized control trials (4/100, 4%), and case-control (3/100, 3%). The most commonly utilized descriptor variables were frequency and proportion (100/100, 100%), followed by median (74/100, 74%) and mean (71/100, 71%). The chi-square test was the most frequently used statistical test (59/100, 59%), while logistic regression (48/100, 48%), Mann-Whitney-U (46/100, 46%), and two-sample independent t-test (40/100, 40%) also were popular.ConclusionThis review revealed that retrospective and cohort studies were utilized most frequently. The chi-square test was used in the majority of studies, while logistic regression was also popular. This information can help determine areas in which supplemental training will be most beneficial to improve the understanding of statistical methods in medical journals by practicing physicians, fellows, residents, and medical students. As an outgrowth of this study, we have developed a practical guide to relevant statistical methods, serving as Part 2 of these tandem manuscripts.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"660-668"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143976068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Approach for Sepsis Risk Assessment in Ischemic Stroke Patients.","authors":"Fengkai Mao, Leqing Lin, Dongcheng Liang, Weiling Cheng, Ning Zhang, Ji Li, Siming Wu","doi":"10.1177/08850666241308195","DOIUrl":"10.1177/08850666241308195","url":null,"abstract":"<p><p>BackgroundIschemic stroke is a critical neurological condition, with infection representing a significant aspect of its clinical management. Sepsis, a life-threatening organ dysfunction resulting from infection, is among the most dangerous complications in the intensive care unit (ICU). Currently, no model exists to predict the onset of sepsis in ischemic stroke patients. This study aimed to develop the first predictive model for sepsis in ischemic stroke patients using data from the MIMIC-IV database, leveraging machine learning techniques.MethodsA total of 2238 adult patients with a diagnosis of ischemic stroke, admitted to the ICU for the first time, were included from the MIMIC-IV database. The outcome of interest was the development of sepsis. Model development adhered to the TRIPOD guidelines. Feature selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression, identifying 28 key variables. Multiple machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, decision trees, and XGBoost, were trained and internally validated. Performance metrics were assessed, and XGBoost was selected as the optimal model. The SHAP method was used to interpret the XGBoost model, revealing the impact of individual features on predictions. The model was also deployed on a user-friendly platform for practical use in clinical settings.ResultsThe XGBoost model demonstrated superior performance in the validation set, achieving an area under the curve (AUC) of 0.863 and offering greater net benefit compared to other models. SHAP analysis identified key factors influencing sepsis risk, including the use of invasive mechanical ventilation on the first day, excessive body weight, a Glasgow Coma Scale verbal score below 3, age, and elevated body temperature (>37.5 °C). A user interface had been developed to enable clinicians to easily access and utilize the model.ConclusionsThis study developed the first machine learning-based model to predict sepsis in ischemic stroke patients. The model exhibited high accuracy and holds potential as a clinical decision support tool, enabling earlier identification of high-risk patients and facilitating preventive measures to reduce sepsis incidence and mortality in this population.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"598-610"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142950235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Associated with the Initiation of Renal Replacement Therapy in Patients on VV-ECMO: A Case-Control Study.","authors":"Robayo-Amortegui Henry, Quecano-Rosas Cesar, Perez-Garzon Michel, Muñoz-Claros Conny, Poveda-Henao Claudia","doi":"10.1177/08850666241309852","DOIUrl":"10.1177/08850666241309852","url":null,"abstract":"<p><strong>Summary: </strong>Acute Kidney Injury (AKI) is a common complication in patients with Acute Respiratory Distress Syndrome (ARDS) receiving VV-ECMO support, carrying a high risk of progression to Renal Replacement Therapy (RRT). Both AKI and RRT are linked to an increased risk of mortality. This study aims to evaluate the risk factors associated with the need for RRT in patients undergoing VV-ECMO.</p><p><strong>Methods: </strong>This is a retrospective case-control study involving patients on VV-ECMO therapy admitted to the intensive care unit (ICU) between 2019 and 2023. Patients on VV ECMO support, with or without RRT, were included and their severity scores and associated mortality were calculated. A multivariate logistic regression analysis was performed to assess the variable RRT using odds ratios (OR) with their corresponding confidence intervals (CI) for the outcome variables.</p><p><strong>Results: </strong>A total of 192 subjects were included, with a mortality rate of 39.6%. Of these, 68.7% were male, with an average ICU stay of 25.1 days and a need for RRT in 19.7% of cases. The multivariate analysis independently associated the use of vasopressors with RRT norepinephrine OR 5.61 (95% CI, 1.64-19.1) and vasopressin OR 4.64 (95% CI, 2.15-10.0)). An increase in creatinine levels before ECMO support is associated with an increased risk OR 2.21 (95% CI 1.54-3.18), and 24 h after ECMO support, the risk rises further adjusted odds ratio (AOR) 3.32 (95% IC 1.55-7.09). The accuracy of severity scores presented weak discrimination and similar behavior, except for DEOx for the primary outcome, with an AUC of 0.79 (95% CI, 0.72-0.87), and APACHE II with an AUC of 0.68 (95% CI, 0.59-0.78).</p><p><strong>Conclusions: </strong>The prediction of RRT in patients on VV-ECMO support was superior for DEOx, which is influenced by the use of vasopressors, creatinine levels, and platelet transfusion prior to cannulation. This could be useful for predicting early interventions in this patient population.</p>","PeriodicalId":16307,"journal":{"name":"Journal of Intensive Care Medicine","volume":" ","pages":"623-631"},"PeriodicalIF":3.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143006818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}