Drug Safety最新文献

{"title":"Comparative Risk of Acute Kidney Injury with Piperacillin-Tazobactam Plus Teicoplanin Versus Piperacillin-Tazobactam Plus Vancomycin: A Systematic Review and Meta-Analysis.","authors":"Shahd Mohammad, Haneen Ghazal, Wafaa Rahimeh, Maqsood Khan, Mosab Al Balas, Faris El-Dahiyat","doi":"10.1007/s40264-025-01611-z","DOIUrl":"https://doi.org/10.1007/s40264-025-01611-z","url":null,"abstract":"<p><strong>Background: </strong>Piperacillin-tazobactam combined with vancomycin is widely employed for broad-spectrum empiric coverage but has been increasingly associated with acute kidney injury (AKI). The comparative renal safety of substituting vancomycin with teicoplanin remains uncertain.</p><p><strong>Objective: </strong>This meta-analysis aimed to evaluate renal outcomes between piperacillin-tazobactam plus teicoplanin (TZP-TEI) versus piperacillin-tazobactam plus vancomycin (TZP-VAN).</p><p><strong>Methods: </strong>PubMed, Scopus, and Cochrane Central were searched for studies comparing TZP-TEI versus TZP-VAN in hospitalized patients. The primary outcome was AKI incidence, defined by Kidney disease: Improving global outcomes (KDIGO) or RIFLE (Risk of renal dysfunction, Injury to kidney, Failure or Loss of kidney function, and End-stage kidney disease) criteria. Data were analyzed using Review Manager, with heterogeneity assessed via the I² statistic.</p><p><strong>Results: </strong>A total of 908 patients were included from five cohort studies, four of which applied propensity-score matching (PSM), with reported ages ranging from 56.8 to 79 years. The TZP-TEI regimen was associated with a significantly reduced rate of AKI compared with TZP-VAN (odds ratio [OR] 0.52; 95% confidence interval [CI] 0.30-0.89; p = 0.02; I² = 51%). No statistically significant differences were observed between groups for AKI recovery (OR 0.68; 95% CI 0.41-1.12; p = 0.13; I² = 0%) or for 30-day all-cause mortality (OR 1.34; 95% CI 0.77-2.32; p = 0.30; I² = 0%). Subgroup analyses stratified by AKI severity (KDIGO stages 1-3 or RIFLE criteria) demonstrated consistent directionality across stages, with no significant differences observed within PSM or non-PSM cohorts.</p><p><strong>Conclusion: </strong>The TZP-TEI combination was associated with a significantly lower incidence of AKI than was TZP-VAN. Further studies are warranted to validate these findings, optimize teicoplanin dosing within the TZP-TEI combination, and inform therapeutic drug monitoring implementation in high-risk hospitalized patients.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145052440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drugs Withdrawn from the Canadian Market for Safety and Effectiveness Reasons, 1990-2024: A Cross-Sectional Study.","authors":"Joel Lexchin","doi":"10.1007/s40264-025-01612-y","DOIUrl":"10.1007/s40264-025-01612-y","url":null,"abstract":"<p><strong>Introduction: </strong>At times it is necessary to withdraw drugs after they have been approved because of lack of effectiveness or safety concerns. Health Canada does not keep a list of withdrawn drugs.</p><p><strong>Objective: </strong>The aim of this study was to generate a list of all drugs approved since 1990 and subsequently withdrawn from the Canadian market for safety or effectiveness reasons until the end of 2024. This list was used to examine trends in the number of withdrawals and the percent of new drugs that are approved but eventually withdrawn.</p><p><strong>Methods: </strong>A list of withdrawn drugs was developed based on previous published research and supplemented by examining lists of withdrawn drugs in other jurisdictions. The time, in years, was calculated between the date of approval and withdrawal. The reasons for withdrawal came from either Health Canada documents or, if unavailable, from international sources. Withdrawals for commercial reasons were not included in the analysis.</p><p><strong>Results: </strong>Of the 1094 drugs approved from January 1, 1990, to December 31, 2024, a total of 37 were withdrawn: 32 were new active substances (molecules never marketed before in any form) and five were other types of new drugs. The median time to withdrawal was 3.60 years (interquartile range 2.45-9.50). Approximately 5% of all new active substances approved in a 5-year period were eventually withdrawn over the period 1990-2009. Between 2010 and 2019, the withdrawal rate was < 2%. The most common reasons for withdrawal were cardiac and liver complications.</p><p><strong>Conclusion: </strong>As a percent of all drugs approved, relatively few drugs are withdrawn, and the number of drug withdrawals as a percent of approvals declined between 2010 and 2019.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145033069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Promise and Challenge of Large Language Models for Pharmacovigilance.","authors":"Lynette Hirschman","doi":"10.1007/s40264-025-01608-8","DOIUrl":"https://doi.org/10.1007/s40264-025-01608-8","url":null,"abstract":"","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145023103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics and Risk Factors of Medication Incidents Across Stages of Medication Management in Residential Aged Care: A Longitudinal Cohort Study of 5700 Reported Incidents.","authors":"S Sandun M Silva, Nasir Wabe, Magdalena Z Raban, Amy D Nguyen, Guogui Huang, Ying Xu, Crisostomo Mercado, Desiree C Firempong, Johanna I Westbrook","doi":"10.1007/s40264-025-01602-0","DOIUrl":"https://doi.org/10.1007/s40264-025-01602-0","url":null,"abstract":"<p><strong>Background: </strong>Problems with medication management are consistently identified as key concerns for the quality of residential aged care (RAC). Incident reports can provide valuable information on key issues related to medication management; however, few studies have explored medication incidents in RAC settings.</p><p><strong>Objectives: </strong>To investigate the characteristics of medication incidents at different stages of medication management and identify the risk factors associated with incidents.</p><p><strong>Methods: </strong>A retrospective longitudinal cohort study was conducted using medication incidence data from 25 RAC facilities in New South Wales, Australia. All medication incidents between 1 July 2014 and 31 August 2021 relating to 5709 aged care residents aged ≥ 65 years were included. The outcome measure was the medication incidence rate (IR), quantified as the number of medication incidents per 1000 resident days. A multilevel Poisson regression model was performed to identify risk factors associated with exposure to medication incidents.</p><p><strong>Results: </strong>A total of 5708 medication incidents were analysed. The overall medication IR was 1.81 per 1000 resident days (95% CI 1.76, 1.86). Of 5709 residents, 35% (n = 2016) had at least one recorded medication incident, of which 1095 (> 50%) had more than one. The majority of the incidents were associated with medication administration (3023 incidents, 53%), followed by supply (n = 1546, 27%) and monitoring the response to the medication (n = 548, 9.6%). The outcome of the incident on residents was reported in 5165 (90%) incidents, with 724 (14%) requiring the resident to be monitored by the hospital, general practitioner (GP), or staff. Respite admissions were associated with a higher risk of medication incidents including potentially harmful incidents, compared with permanent admissions (rate ratio (RR) = 1.908, 95% CI 1.646, 2.211, p < 0.01). Residents with Parkinson's disease had a 1.5-fold greater risk of a medication incident (RR = 1.586, 95% CI 1.318, 1.908) compared with residents without Parkinson's. The administration of more than five medications (polypharmacy) was associated with an increased risk of medication incidents (RR = 2.019, 95% CI 1.930, 2.111).</p><p><strong>Conclusions: </strong>Medication incidents affected more than one-third of older adults in RAC facilities. Improvement strategies should focus on medication administration, supply and monitoring, with particular attention given to respite residents and those with multimorbidity and polypharmacy.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation and Results of Active Vaccine Safety Monitoring During the COVID-19 Pandemic in the UK: A Regulatory Perspective.","authors":"Jenny Wong, Katherine Donegan, Kendal Harrison, Tahira Jan, Alison Cave, Phil Tregunno","doi":"10.1007/s40264-025-01579-w","DOIUrl":"https://doi.org/10.1007/s40264-025-01579-w","url":null,"abstract":"<p><strong>Introduction: </strong>Yellow Card Vaccine Monitor (YCVM) was established by the UK Medicines and Healthcare products Regulatory Agency (MHRA) to facilitate active monitoring of adverse drug reactions following COVID-19 vaccination and further characterise safety in populations under-represented in clinical trials.</p><p><strong>Objective: </strong>This study explored the profile of individuals registered to the YCVM platform and the suspected adverse drug reactions reported following a COVID-19 vaccination on this data platform.</p><p><strong>Methods: </strong>Using a stratified random selection approach, individuals were invited to register and actively contacted to seek further information on the vaccines received and adverse reactions they experienced. Exploratory analyses were conducted to characterise the demographics of individuals registered in the YCVM, and to summarise the adverse drug reaction data reported by recruited individuals between November 2020 and December 2022. Detailed analyses of the sub-cohort of pregnant and breastfeeding females were conducted to characterise these individuals. Data for two suspected adverse reactions, menstrual disorders and tinnitus, were extracted and analysed to demonstrate how YCVM supported regulatory assessment of these safety signals which originally arose from other data sources.</p><p><strong>Results: </strong>36,604 individuals registered, with 30,281 reporting vaccination. Median (interquartile range) follow-up was 184 days (14-367). Demographics of the recruited cohort reflected the vaccinated population and timing of invitations. 15,764 (52.1%) of those reporting vaccination reported experiencing at least one adverse reaction. However, nearly all were expected acute reactions and 4134 (13.7%) reported an event considered medically serious. The data raised no safety concerns in pregnant and breastfeeding females. Reporting of menstrual disorders appeared stimulated by media interest, as seen in spontaneous reporting systems. Data on the incidence of tinnitus were used to support regulatory action on this signal.</p><p><strong>Conclusion: </strong>Active surveillance using the YCVM provided a complementary data source for monitoring the safety of COVID-19 vaccines. However, further efforts are needed to recruit ethnic minorities. The technology developed has enhanced regulatory vigilance options and could be valuable in the future for actively monitoring the safety of innovative products used in small populations.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144946689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on \"Performance and Reproducibility of Large Language Models in Named Entity Recognition: Considerations for the Use in Controlled Environments\".","authors":"Théophile Tiffet, Diva Beltramin, Béatrice Trombert-Paviot, Cédric Bousquet","doi":"10.1007/s40264-025-01592-z","DOIUrl":"https://doi.org/10.1007/s40264-025-01592-z","url":null,"abstract":"","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144946523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging Large Language Models in Extracting Drug Safety Information from Prescription Drug Labels.","authors":"Undina Gisladottir, Michael Zietz, Sophia Kivelson, Yutaro Tanaka, Gaurav Sirdeshmukh, Kathleen LaRow Brown, Nicholas P Tatonetti","doi":"10.1007/s40264-025-01594-x","DOIUrl":"10.1007/s40264-025-01594-x","url":null,"abstract":"<p><strong>Introduction: </strong>Adverse drug reactions (ADRs), including those resulting from drug interactions, remain a leading cause of morbidity and mortality. Structured product labels (SPLs) serve as a primary source for drug safety information. Having machine-readable product labels, including adverse reactions (ARs) and drug interactions, readily available would allow researchers to streamline medication safety studies. However, extracting this information is complex and requires the use of natural language processing (NLP) methods.</p><p><strong>Objective: </strong>In this study, we explored the application of generative language models in the extraction of drug safety information from SPLs.</p><p><strong>Methods: </strong>We compared multiple generative LLMs (GPT, Llama, and Mixtral) to two baseline methods in the task of extracting adverse reactions (ARs) from SPLs. We explored various factors, such as prompting strategies and term complexity, that impact the performance of these models in the extraction of ARs. Finally, we explored the generative models' capacity to extract drug interactions from a separate section of SPLs without additional fine-tuning or training, demonstrating their flexibility and adaptability for information retrieval.</p><p><strong>Results: </strong>We found that generative language models, specifically GPT-4, are able to match or exceed the performance of previous state-of-the-art models without additional training or fine-tuning. Additionally, we found that the specific SPL section, surrounding context, and complexity of the AR term impacted the extraction performance. Finally, we demonstrated the generalizability of these models by applying them to a separate task of extracting drug names from the drug interaction section where curated training data are not available.</p><p><strong>Conclusion: </strong>Generative language models demonstrate significant potential for automating drug safety information extraction from SPLs, offering a promising avenue for improving post-market surveillance and reducing ADRs. Future work should focus on refining prompting strategies and expanding the models' capabilities to handle increasingly complex and nuanced drug safety information.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144946749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authors' response to Tiffet et al.'s comment on \"Performance and Reproducibility of Large Language Models in Named Entity Recognition: Considerations for the Use in Controlled Environments\".","authors":"Juergen Dietrich, André Hollstein","doi":"10.1007/s40264-025-01590-1","DOIUrl":"https://doi.org/10.1007/s40264-025-01590-1","url":null,"abstract":"","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144946545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Reliability of Detecting Drug-Drug Interactions that Increase the Risk of Gestational Diabetes in Adverse Event Reporting Systems.","authors":"Robiyanto Robiyanto, Jim W Barrett, Lovisa Sandberg, Boukje C Raemaekers, G Niklas Norén, Catharina C M Schuiling-Veninga, Eelko Hak, Eugène P van Puijenbroek","doi":"10.1007/s40264-025-01607-9","DOIUrl":"https://doi.org/10.1007/s40264-025-01607-9","url":null,"abstract":"<p><strong>Background: </strong>Adverse event reporting systems are an important source of safety signals for drug use in pregnancy, but their usefulness in the identification of potential drug-drug interactions (DDIs) remains unclear.</p><p><strong>Objective: </strong>Our objective was to explore the reliability of signal detection for pharmacokinetic DDIs during pregnancy in adverse event reporting systems, focusing on potential interactions between antipsychotics (APs) or antidepressants (ADs) and drugs modifying cytochrome P450 (CYP450) activity, increasing the occurrence of gestational diabetes mellitus (GDM).</p><p><strong>Methods: </strong>Reports related to the use of drugs during pregnancy were identified in VigiBase, the World Health Organization (WHO) global database of adverse event reports. Potential interacting drugs were selected based on WHO Drug Standardised Drug Groupings for CYP450 isoenzymes involved in the metabolic pathway of the AP or AD of interest. We conducted statistical interaction analysis using the omega disproportionality measure and including concomitant medication to identify potential DDIs, followed by a case series review for supporting evidence. Evaluation was subjective by author consensus.</p><p><strong>Results: </strong>Of the 30 drug-drug-event combinations considered, statistical signals emerged for escitalopram, citalopram, and sertraline and the simultaneous use of CYP2D6 inhibitors with a higher relative reporting rate of GDM. However, case series review of reports did not support the existence of these DDIs because of uncertainties regarding the actual timing of medication use reported as concomitant.</p><p><strong>Conclusion: </strong>Statistical signals of DDIs between ADs and potential interacting drugs during pregnancy were identified but not pursued further after case reviews. Uncertainty around medication use and event timing affected the reliability of the outcomes. These findings highlight the need to validate signals using detailed report data and stress the importance of accurate medication reporting.</p>","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144946778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Adverse Event Follow-Up in Advancing the Knowledge of Medicines and Vaccines Safety: A Scoping Review.","authors":"Vijay Kara, Florence Van Hunsel, Andrew Bate, Eugène van Puijenbroek","doi":"10.1007/s40264-025-01553-6","DOIUrl":"10.1007/s40264-025-01553-6","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction and objective: &lt;/strong&gt;Adverse events (AEs) associated with medication and vaccine use are of significant concern in pharmacovigilance (PV), necessitating robust detection, documentation, and reporting mechanisms. The primary objective of this scoping review is to understand and evaluate the concept, implementation, frequency, and value of \"follow-up\" in the context of AE assessment. Secondary objectives include providing an overview of various definitions of \"follow-up,\" describing the requirements and studies evaluating follow-up methods, and assessing how often follow-up is undertaken in assessing an AE, by whom, and its value.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This scoping review followed the 2018 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews. The protocol was registered on the Open Science Framework (OSF). The review included peer-reviewed literature and regulatory guidelines, the search strategy involved querying MEDLINE (via PubMed) and Embase for publications indexed from January 2013 to December 2023. The Rayyan&lt;sup&gt;®&lt;/sup&gt; collaborative review platform was used to manage duplicates and select eligible studies. Data extraction was performed using a standardized template, and the extracted data were summarized descriptively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The search yielded 4,428 articles, with 23 studies meeting the inclusion criteria. Methods for follow-up varied among the studies, with digital tools such as emails, online surveys, and SMS utilized in 22% of the studies, achieving response rates ranging from 29 to 31%. Telephone follow-up was employed in 17% of studies, showing higher response rates between 62 and 89%. In settings with limited digital access, home visits were conducted in 9% of studies; only one study reported a response rate which was 74%. The nature of the follow-up approach was diverse: 35% of studies conducted open-ended follow-up, where no pre-determined AEs were specified, whilst 22% of studies focused on specific AEs or outcomes; the remaining 43% had other reasons such as deduplication, assessing informativeness, characterizing unlisted adverse drug reactions (ADRs) or were related to studies evaluating follow-up methods. The initiation of follow-up activities, including methodological research, was driven by academia in 30% of studies, PV centers in 44%, and marketing authorization holders (MAHs) in 26%. Consent practices varied across the studies: 39% of studies did not pre-consent individuals prior to requesting follow-up, while 31% secured consent to contact prior to follow-up, and the other 30% related to studies evaluating follow-up methods.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Despite the use of follow-up across all PV organizations, and existing regulatory guidance, there is a dearth of scientific research on the topic. While rates of follow-up were quoted between 19 and 100% there is inconsistency in the use of the term, a","PeriodicalId":11382,"journal":{"name":"Drug Safety","volume":" ","pages":"977-991"},"PeriodicalIF":3.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144109794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}