[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-437198-105":59,"doc-detail-437198-en":129},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":122,"head_meta":124,"extra_data":126,"updated_unix":128},105,"en","pitfalls-in-comparing-mechanical-circulatory-support-devices-using-administrative-datasets-epidemiology-of-the-diseased-population","Pitfalls in Comparing Mechanical Circulatory Support Devices Using Administrative Datasets - Epidemiology of the Diseased Population","","High-risk percutaneous coronary intervention (HRPCI) patients receiving percutaneous ventricular assist devices (pLVAD) or intra-aortic balloon pumps (IABP) were evaluated using the PREMIER Healthcare Database. The study quantified limitations of administrative-dataset comparisons by applying propensity scores derived from 87 preprocedural variables and propensity matching to balance cohorts. It examined overlap in treatment propensity, counts of excluded/discounted patients after matching, and differences in baseline demographics, comorbidities, and cardiac disease severity between unmatched and matched groups.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/pitfalls-in-comparing-mechanical-circulatory-support-devices-using-administrative-datasets-epidemiology-of-the-diseased-population/437198/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/pitfalls-in-comparing-mechanical-circulatory-support-devices-using-administrative-datasets-epidemiology-of-the-diseased-population/437198.png","ImageObject",300,407,{"name":92,"@type":93},"Stanley","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-29",true,{"@type":101,"interactionType":102,"userInteractionCount":14},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What administrative data approach does the study use to compare pLVAD and IABP in HRPCI?","Question",{"text":111,"@type":112},"It uses observational data from the PREMIER Healthcare Database and estimates propensity scores from 87 preprocedural variables, followed by propensity score matching to compare cohorts.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"How does the study handle confounding when comparing device groups?",{"text":116,"@type":112},"It assesses differences with standardized mean differences after generating propensity scores and matching, then analyzes how patient selection and overlap vary by propensity score level.",{"name":118,"@type":109,"acceptedAnswer":119},"What impact does propensity matching have on which patients are included or excluded?",{"text":120,"@type":112},"After matching, 3363 patients were included (847 IABP to 416 pLVAD), with many patients excluded from the pLVAD group and fewer excluded from the IABP group, leading to notable baseline differences in excluded patients.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},437198,1790725596,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":81,"language":138,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":67,"update_tm":142,"read_time":39},2336477405376,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Journal of the Society for Cardiovascular Angiography & Interventions 4 (2025) 103998  \nResearch Letter  \nPitfalls in Comparing Mechanical Circulatory Support Devices Using Administrative Datasets: Epidemiology of the Diseased Population  \nTayyab Shah, MD a, b, Chantal Holy, MSc, PhD c, Ali Almedhychy, MDd, Jeffrey W. Moses, MD e, f, Helen Parise, ScD a, Alejandro Lemor, MD g, William W. O’Neill, MD h, Alexandra J. Lansky, MD a, *  \na Yale Cardiovascular Research Group, Yale School of Medicine, New Haven, Connecticut; b Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; c Johnson & Johnson, New Brunswick, New Jersey; d Johnson & Johnson, Danvers, Massachusetts; e Division of Cardiology, NewYork-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York; f Division of Cardiology, St. Francis Hospital & Heart Center, Roslyn, New York; g Division of Cardiology, University of Mississippi Medical Center, Jackson, Mississippi; h Division of Cardiology, Henry Ford Hospital System, Detroit, Michigan  \nIntroduction  \nBoth Impella, a percutaneous ventricular assist device (pLVAD), and intra-aortic balloon pump (IABP) provide hemodynamic support for patients undergoing high-risk percutaneous coronary intervention (HRPCI) .1 In light of limited randomized data directly comparing these devices,2 observational studies leveraging administrative health datasets, such as the PREMIER Healthcare Database, have sought to evaluate their relative efficacy.3–5 This study assesses the limitations of such analyses using a contemporary PREMIER cohort.  \nMaterials and methods  \nPatients undergoing their first elective HRPCI (defined as PCI with pLVAD or IABP) between 2018 and April 2024 who received pLVAD (5A0221D/5A0211D) or IABP (5A02210/5A02110) on the same day as the procedure (but not both), did not have cardiogenic shock on admission (R57.0), and did not receive surgery on the index admission were identified in the PREMIER Healthcare Database. We calculated propensity scores using logistic regression of 87 independent preprocedural variables (demographic characteristics, comorbidities, hospital characteristics, and admission/presentation characteristics) present in more than 1% of included patients, with standardized mean differences (SMDs) between the 2 arms exceeding 0.01. Variablerate propensity score matching without replacement using a caliper width of 0.03 was performed to match patients in the IABP arm to those in the pLVAD arm . In this study, we compared characteristics among the unmatched and matched groups and  \nidentify which patients are excluded/discounted after matching. The full details of the methods and results of the propensity matched analysis have been published separately.6 SMDs were used to assess differences between cohorts. All analyses were conducted using R version 4.2.2 and RStudio (2024.04.1 Build 748) . This study was reviewed by the New England Institutional Review Board and deemed exempt from review.  \nResults  \nIn total, 4781 patients (3859 pLVAD and 922 IABP) met eligibility criteria. Patients in the pLVAD arm were older (73 ± 10.5 vs 71 ± 10.2 years) had higher Elixhauser comorbidity scores (5.3 vs 5.0) and underwent more multivessel revascularization. After generating propensity scores for treatment with pLVAD, there was overlap among patients in the IABP and pLVAD arms for the intermediate scores; however, patients with lower scores almost exclusively received IABP, while those with higher scores almost exclusively received pLVAD (Figure 1) . A total of 3363 patients were matched (847 IABP to 416 pLVAD), meaning 1443 were excluded from the pLVAD group, while only 75 were excluded from the IABP group. Compared with patients excluded from the IABP arm, patients excluded from the pLVAD arm were older (74 ± 10.6 vs 68 ± 9.7 years), had higher Elixhauser comorbidity scores (mean, 5.7 vs 4.6), and had more comorbidities including diabe","cbCaia94FrHtmG7y","https://ap.wps.com/l/cbCaia94FrHtmG7y","pdf",2640149,"English","# Introduction\n# Materials and methods\n# Results","[{\"question\":\"What administrative data approach does the study use to compare pLVAD and IABP in HRPCI?\",\"answer\":\"It uses observational data from the PREMIER Healthcare Database and estimates propensity scores from 87 preprocedural variables, followed by propensity score matching to compare cohorts.\"},{\"question\":\"How does the study handle confounding when comparing device groups?\",\"answer\":\"It assesses differences with standardized mean differences after generating propensity scores and matching, then analyzes how patient selection and overlap vary by propensity score level.\"},{\"question\":\"What impact does propensity matching have on which patients are included or excluded?\",\"answer\":\"After matching, 3363 patients were included (847 IABP to 416 pLVAD), with many patients excluded from the pLVAD group and fewer excluded from the IABP group, leading to notable baseline differences in excluded patients.\"}]","Pitfalls in Comparing Mechanical Circulatory Support Devices Using Administrative Datasets - Epidemiology of the Diseased Population | PDF",1790680600]