[ { "key": "6I4JIURX", "version": 7149, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/6I4JIURX", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/6I4JIURX", "type": "text/html" } }, "meta": { "createdByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Du et al.", "parsedDate": "2025-06", "numChildren": 0 }, "data": { "key": "6I4JIURX", "version": 7149, "itemType": "journalArticle", "title": "Advancing real-time infectious disease forecasting using large language models", "creators": [ { "creatorType": "author", "firstName": "Hongru", "lastName": "Du" }, { "creatorType": "author", "firstName": "Yang", "lastName": "Zhao" }, { "creatorType": "author", "firstName": "Jianan", "lastName": "Zhao" }, { "creatorType": "author", "firstName": "Shaochong", "lastName": "Xu" }, { "creatorType": "author", "firstName": "Xihong", "lastName": "Lin" }, { "creatorType": "author", "firstName": "Yiran", "lastName": "Chen" }, { "creatorType": "author", "firstName": "Lauren M.", "lastName": "Gardner" }, { "creatorType": "author", "firstName": "Hao ‘Frank’", "lastName": "Yang" } ], "abstractNote": "Forecasting the short-term spread of an ongoing disease outbreak poses a challenge owing to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables, and the intersection of public policy and human behavior. Here we introduce PandemicLLM, a framework with multi-modal large language models (LLMs) that reformulates real-time forecasting of disease spread as a text-reasoning problem, with the ability to incorporate real-time, complex, non-numerical information. This approach, through an artificial intelligence–human cooperative prompt design and time-series representation learning, encodes multi-modal data for LLMs. The model is applied to the COVID-19 pandemic, and trained to utilize textual public health policies, genomic surveillance, spatial and epidemiological time-series data, and is tested across all 50 states of the United States for a duration of 19 months. PandemicLLM opens avenues for incorporating various pandemic-related data in heterogeneous formats and shows performance benefits over existing models.", "publicationTitle": "Nature Computational Science", "publisher": "Nature Publishing Group", "place": "", "date": "2025-06", "volume": "5", "issue": "6", "section": "", "partNumber": "", "partTitle": "", "pages": "467-480", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Nat Comput Sci", "DOI": "10.1038/s43588-025-00798-6", "citationKey": "", "url": "https://www.nature.com/articles/s43588-025-00798-6", "accessDate": "2026-01-28T16:10:51Z", "PMID": "", "PMCID": "", "ISSN": "2662-8457", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.nature.com", "callNumber": "", "rights": "2025 The Author(s), under exclusive licence to Springer Nature America, Inc.", "extra": "", "tags": [ { "tag": "Computational models", "type": 1 }, { "tag": "Computational science", "type": 1 }, { "tag": "Infectious diseases", "type": 1 }, { "tag": "Interdisciplinary studies", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2026-01-28T16:10:51Z", "dateModified": "2026-01-28T16:10:51Z" } }, { "key": "QCZW6GJT", "version": 7068, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/QCZW6GJT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/QCZW6GJT", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/YBVDSZ6T", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "QCZW6GJT", "version": 7068, "parentItem": "YBVDSZ6T", "itemType": "attachment", "linkMode": "imported_url", "title": "ScienceDirect Snapshot", "accessDate": "2025-11-29T16:12:32Z", "url": "https://www.sciencedirect.com/science/article/pii/S009095562408070X", "note": "", "contentType": "text/html", "charset": "utf-8", "filename": "S009095562408070X.html", "md5": "eb72d663dfc1a1f8d3fe11cd61e8b3ad", "mtime": 1764432752188, "tags": [], "relations": {}, "dateAdded": "2025-11-29T16:12:32Z", "dateModified": "2025-11-29T16:12:32Z" } }, { "key": "YBVDSZ6T", "version": 7066, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/YBVDSZ6T", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/YBVDSZ6T", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "creatorSummary": "Birer-Williams et al.", "parsedDate": "2020-10-01", "numChildren": 1 }, "data": { "key": "YBVDSZ6T", "version": 7066, "itemType": "journalArticle", "title": "A New Data Repository for Pharmacokinetic Natural Product-Drug Interactions: From Chemical Characterization to Clinical Studies", "creators": [ { "creatorType": "author", "firstName": "Caroline", "lastName": "Birer-Williams" }, { "creatorType": "author", "firstName": "Brandon T.", "lastName": "Gufford" }, { "creatorType": "author", "firstName": "Eric", "lastName": "Chou" }, { "creatorType": "author", "firstName": "Marijanel", "lastName": "Alilio" }, { "creatorType": "author", "firstName": "Sidney", "lastName": "VanAlstine" }, { "creatorType": "author", "firstName": "Rachael E.", "lastName": "Morley" }, { "creatorType": "author", "firstName": "Jeannine S.", "lastName": "McCune" }, { "creatorType": "author", "firstName": "Mary F.", "lastName": "Paine" }, { "creatorType": "author", "firstName": "Richard D.", "lastName": "Boyce" } ], "abstractNote": "There are many gaps in scientific knowledge about the clinical significance of pharmacokinetic natural product–drug interactions (NPDIs) in which the natural product (NP) is the precipitant and a conventional drug is the object. The National Center for Complimentary and Integrative Health created the Center of Excellence for NPDI Research (NaPDI Center) (www.napdi.org) to provide leadership and guidance on the study of pharmacokinetic NPDIs. A key contribution of the Center is the first user-friendly online repository that stores and links pharmacokinetic NPDI data across chemical characterization, metabolomics analyses, and pharmacokinetic in vitro and clinical experiments (repo.napdi.org). The design is expected to help researchers more easily arrive at a complete understanding of pharmacokinetic NPDI research on a particular NP. The repository will also facilitate multidisciplinary collaborations, as the repository links all of the experimental data for a given NP across the study types. The current work describes the design of the repository, standard operating procedures used to enter data, and pharmacokinetic NPDI data that have been entered to date. To illustrate the usefulness of the NaPDI Center repository, more details on two high-priority NPs, cannabis and kratom, are provided as case studies.\nSIGNIFICANCE STATEMENT\nThe data and knowledge resulting from natural product–drug interaction (NPDI) studies is distributed across a variety of information sources, rendering difficulties to find, access, and reuse. 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While large language models (LLMs) can process chemical information, they operate as black boxes without transparent reasoning. Here, we present our Multi-agent Ontology System for Explainable Knowledge Synthesis (MOSES), a framework that combines automated knowledge organization with multi-agent collaboration to create an AI system for interpretable chemical knowledge reasoning. Using supramolecular chemistry as a testbed, we automatically constructed an ontology of over 10,000 classes from 52 publications and developed a multi-agent system that enables transparent knowledge retrieval and reasoning. Evaluations by human experts and LLMs show that MOSES significantly outperforms chemistry-oriented LLMs and leading general-purpose LLMs—including GPT-4.1 and o3—as well as GraphRAG-augmented GPT-4.1 models, on complex chemical questions, achieving superior scores in both direct assessments and Elo ratings. MOSES's traceable reasoning paths reveal how it constructs answers through iterative refinement rather than probabilistic generation. However, we observe an asymmetry in handling positive versus negative knowledge claims, underscoring fundamental challenges in open-world reasoning. 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2023 - Which Adverse Events and Which Drugs Are Implicated in Drug-Related Hospital Admissions A Systemati.pdf", "md5": "db27d5f7034cb3914298477795b161d4", "mtime": 1762522837762, "tags": [], "relations": {}, "dateAdded": "2025-11-07T13:40:37Z", "dateModified": "2025-11-07T13:40:37Z" } }, { "key": "JN9YY968", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/JN9YY968", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/JN9YY968", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Haerdtlein et al.", "parsedDate": "2023-01", "numChildren": 1 }, "data": { "key": "JN9YY968", "version": 7147, "itemType": "journalArticle", "title": "Which Adverse Events and Which Drugs Are Implicated in Drug-Related Hospital Admissions? A Systematic Review and Meta-Analysis", "creators": [ { "creatorType": "author", "firstName": "Annette", "lastName": "Haerdtlein" }, { "creatorType": "author", "firstName": "Elisabeth", "lastName": "Debold" }, { "creatorType": "author", "firstName": "Marietta", "lastName": "Rottenkolber" }, { "creatorType": "author", "firstName": "Anna Maria", "lastName": "Boehmer" }, { "creatorType": "author", "firstName": "Yvonne Marina", "lastName": "Pudritz" }, { "creatorType": "author", "firstName": "Faiza", "lastName": "Shahid" }, { "creatorType": "author", "firstName": "Jochen", "lastName": "Gensichen" }, { "creatorType": "author", "firstName": "Tobias", "lastName": "Dreischulte" } ], "abstractNote": "Adverse drug events (ADEs) and adverse drug reactions (ADRs) are leading causes of iatrogenic injury, which can result in emergency department (ED) visits or admissions to inpatient wards. The aim of this systematic review and meta-analysis was to provide up-to-date estimates of the prevalence of (preventable) drug-related ED visits and hospital admissions, as well as the type and prevalence of implicated ADRs/ADEs and drugs. A literature search of studies published between January 2012 and December 2021 was performed in PubMed, Medline, EMBASE, Cochrane Library, and Web of Science. Retrospective and prospective observational studies investigating acute admissions to EDs or inpatient wards due to ADRs or ADEs in the general population were included. Meta-analyses of prevalence rates were conducted using generalized linear mixed models (GLMM) with the random-effect method. Seventeen studies reporting ADRs and/or ADEs were eligible for inclusion. The prevalence rates of ADR- and ADE-related admissions to EDs or inpatient wards were estimated at 8.3% ([95% CI, 6.4–10.7%]) and 13.9% ([95% CI, 8.1–22.8%]), respectively, of which almost half (ADRs: 44.7% [95% CI: 28.1; 62.4]) and more than two thirds (ADEs: 71.0% [95% CI, 65.9–75.6%]) had been classified as at least possibly preventable. The ADR categories most frequently implicated in ADR-related admissions were gastrointestinal disorders, electrolyte disturbances, bleeding events, and renal and urinary disorders. Nervous system drugs were found to be the most commonly implicated drug groups, followed by cardiovascular and antithrombotic agents. Our findings demonstrate that ADR-related admissions to EDs and inpatient wards still represent a major and often preventable health care problem. In comparison to previous systematic reviews, cardiovascular and antithrombotic drugs remain common causes of drug-related admissions, while nervous system drugs appear to have become more commonly implicated. These developments may be considered in future efforts to improve medication safety in primary care.", "publicationTitle": "Journal of Clinical Medicine", "publisher": "Multidisciplinary Digital Publishing Institute", "place": "", "date": "2023/1", "volume": "12", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "1320", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.3390/jcm12041320", "citationKey": "", "url": "https://www.mdpi.com/2077-0383/12/4/1320", "accessDate": "2025-11-07T13:40:35Z", "PMID": "", "PMCID": "", "ISSN": "2077-0383", "archive": "", "archiveLocation": "", "shortTitle": "Which Adverse Events and Which Drugs Are Implicated in Drug-Related Hospital Admissions?", "language": "en", "libraryCatalog": "www.mdpi.com", "callNumber": "", "rights": "http://creativecommons.org/licenses/by/3.0/", "extra": "", "tags": [ { "tag": "adverse drug event", "type": 1 }, { "tag": "adverse drug reaction", "type": 1 }, { "tag": "emergency department", "type": 1 }, { "tag": "hospital admission", "type": 1 }, { "tag": "hospitalization", "type": 1 }, { "tag": "meta-analysis", "type": 1 }, { "tag": "systematic review", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2025-11-07T13:40:35Z", "dateModified": "2025-11-07T13:40:35Z" } }, { "key": "R2KRY5MK", "version": 7045, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/R2KRY5MK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/R2KRY5MK", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/YJ9LJZR6", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "R2KRY5MK", "version": 7045, "parentItem": "YJ9LJZR6", "itemType": "attachment", "linkMode": "imported_url", "title": "Full Text PDF", "accessDate": "2025-11-07T13:39:37Z", "url": "https://www.nejm.org/doi/pdf/10.1056/NEJMsa1103053", "note": "", "contentType": "application/pdf", "charset": "", "filename": "Budnitz et al. - 2011 - Emergency Hospitalizations for Adverse Drug Events in Older Americans.pdf", "md5": "b6a37f82d2244a3ef8005e5a67bdf188", "mtime": 1762522777369, "tags": [], "relations": {}, "dateAdded": "2025-11-07T13:39:37Z", "dateModified": "2025-11-07T13:39:37Z" } }, { "key": "YJ9LJZR6", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/YJ9LJZR6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/YJ9LJZR6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Budnitz et al.", "parsedDate": "2011-11-24", "numChildren": 1 }, "data": { "key": "YJ9LJZR6", "version": 7147, "itemType": "journalArticle", "title": "Emergency Hospitalizations for Adverse Drug Events in Older Americans", "creators": [ { "creatorType": "author", "firstName": "Daniel S.", "lastName": "Budnitz" }, { "creatorType": "author", "firstName": "Maribeth C.", "lastName": "Lovegrove" }, { "creatorType": "author", "firstName": "Nadine", "lastName": "Shehab" }, { "creatorType": "author", "firstName": "Chesley L.", "lastName": "Richards" } ], "abstractNote": "This national study estimated that nearly 100,000 elderly patients were hospitalized for adverse drug events annually from 2007 through 2009. Most resulted from use of common medications such as warfarin and insulin, and only 1% from medications designated as high-risk. Decreasing the number of preventable rehospitalizations by 20% by the end of 2013 is a goal of the $1 billion federal initiative Partnership for Patients, and the pursuit of this goal represents an opportunity to reduce harm to patients and reduce health care costs.1,2 Adverse drug events are a direct consequence of clinical care and a key focus of the partnership. Hospitalizations for adverse drug events are likely to increase as Americans live longer, have greater numbers of chronic conditions, and take more medications. Among adults 65 years of age or older, 40% take 5 to 9 medications and . . .", "publicationTitle": "New England Journal of Medicine", "publisher": "Massachusetts Medical Society", "place": "", "date": "2011-11-24", "volume": "365", "issue": "21", "section": "", "partNumber": "", "partTitle": "", "pages": "2002-2012", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1056/NEJMsa1103053", "citationKey": "", "url": "https://www.nejm.org/doi/full/10.1056/NEJMsa1103053", "accessDate": "2025-11-07T13:39:36Z", "PMID": "", "PMCID": "", "ISSN": "0028-4793", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Taylor and Francis+NEJM", "callNumber": "", "rights": "", "extra": "_eprint: https://www.nejm.org/doi/pdf/10.1056/NEJMsa1103053", "tags": [], "collections": [], "relations": {}, "dateAdded": "2025-11-07T13:39:36Z", "dateModified": "2025-11-07T13:39:36Z" } }, { "key": "VHNF7YG5", "version": 7043, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/VHNF7YG5", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/VHNF7YG5", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/K2MYY53V", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "VHNF7YG5", "version": 7043, "parentItem": "K2MYY53V", "itemType": "attachment", "linkMode": "linked_url", "title": "PubMed entry", "accessDate": "2025-09-30T17:44:19Z", "url": "http://www.ncbi.nlm.nih.gov/pubmed/39739457", "note": "", "contentType": "text/html", "charset": "", "tags": [], "relations": {}, "dateAdded": "2025-09-30T17:44:19Z", "dateModified": "2025-09-30T17:44:19Z" } }, { "key": "K2MYY53V", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/K2MYY53V", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/K2MYY53V", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Albert et al.", "parsedDate": "2025-03", "numChildren": 1 }, "data": { "key": "K2MYY53V", "version": 7147, "itemType": "journalArticle", "title": "Incidence of Potentially Inappropriate Prescribing: Longitudinal Investigation of Outpatient EHR Prescriptions", "creators": [ { "creatorType": "author", "firstName": "Steven M.", "lastName": "Albert" }, { "creatorType": "author", "firstName": "Xiaotong", "lastName": "Li" }, { "creatorType": "author", "firstName": "Sandra L.", "lastName": "Gill-Kane" }, { "creatorType": "author", "firstName": "Jacob", "lastName": "Lombardi" }, { "creatorType": "author", "firstName": "Krishi", "lastName": "Akenapalli" }, { "creatorType": "author", "firstName": "Richard D.", "lastName": "Boyce" } ], "abstractNote": "IMPORTANCE: The incidence of potentially inappropriate medication (PIM) prescribing among older adults is not as well studied as its prevalence. Estimates of factors associated with PIM incidence, such as patient age, sex, race-ethnicity, medication subsidy support, and comorbidity, are also limited.\nOBJECTIVE: To estimate the incidence of PIM prescribing in older adult outpatients, as well as the incidence and predictors for each PIM class, in a large outpatient electronic health records (EHR) cohort.\nDESIGN: Retrospective study of PIM prescribing among outpatients with encounters leading to prescription orders, 2015-2018, excluding prevalent cases.\nSETTING: Outpatients receiving care from a multi-site health system in western Pennsylvania.\nPARTICIPANTS: 342,405 patients, contributing 893,754 person-years of follow-up.\nMAIN OUTCOMES AND MEASURES: The incidence of PIM prescribing based on automated coding of 2019 Beers criteria. A multivariable Poisson regression model was estimated to assess the impact of age, sex, race-ethnicity, comorbidity, and medication subsidy (PACE/PACENET) on PIM risk. For each PIM class, the association between predictors and time to PIM prescribing was evaluated using proportional hazard models.\nRESULTS: The incidence rate (IR) for 1 or more PIM was 193.5 per 1000 person-years, led by short- and intermediate-acting benzodiazepines (37.6), first-generation antihistamines (32.8), and skeletal muscle relaxants (22.0). The incidence of PIM prescribing was 15% higher among white patients and 35% lower among males. High comorbidity (Charlson score ≥ 3) was associated with a 59% higher risk. Participation in the PACE/PACENET program, a medication subsidy program, was associated with an 83% increase in incidence. Each additional year of age was associated with a 1.2% reduction in incidence.\nCONCLUSIONS AND RELEVANCE: This study establishes benchmarks for the incidence of PIM prescribing in outpatients and identifies important disparities in PIM risk, which vary by PIM class.", "publicationTitle": "Journal of the American Geriatrics Society", "publisher": "", "place": "", "date": "2025-03", "volume": "73", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "728-736", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "J Am Geriatr Soc", "DOI": "10.1111/jgs.19340", "citationKey": "", "url": "", "accessDate": "", "PMID": "39739457", "PMCID": "PMC11907745", "ISSN": "1532-5415", "archive": "", "archiveLocation": "", "shortTitle": "Incidence of Potentially Inappropriate Prescribing", "language": "eng", "libraryCatalog": "PubMed", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Aged", "type": 1 }, { "tag": "Aged, 80 and over", "type": 1 }, { "tag": "Electronic Health Records", "type": 1 }, { "tag": "Female", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Inappropriate Prescribing", "type": 1 }, { "tag": "Incidence", "type": 1 }, { "tag": "Longitudinal Studies", "type": 1 }, { "tag": "Male", "type": 1 }, { "tag": "Outpatients", "type": 1 }, { "tag": "Pennsylvania", "type": 1 }, { "tag": "Potentially Inappropriate Medication List", "type": 1 }, { "tag": "Practice Patterns, Physicians'", "type": 1 }, { "tag": "Retrospective Studies", "type": 1 }, { "tag": "electronic health record", "type": 1 }, { "tag": "inappropriate prescribing", "type": 1 }, { "tag": "incidence", "type": 1 }, { "tag": "medications", "type": 1 }, { "tag": "outpatients", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2025-09-30T17:44:18Z", "dateModified": "2025-09-30T17:44:18Z" } }, { "key": "Q38UTX5B", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/Q38UTX5B", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/Q38UTX5B", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Chahine et al.", "parsedDate": "2025-07-31", "numChildren": 1 }, "data": { "key": "Q38UTX5B", "version": 7147, "itemType": "journalArticle", "title": "Prodromal features and risk of neurodegenerative disorders diagnosis in outpatients with REM sleep behavior disorder", "creators": [ { "creatorType": "author", "firstName": "Lana M.", "lastName": "Chahine" }, { "creatorType": "author", "firstName": "Anne", "lastName": "Newman" }, { "creatorType": "author", "firstName": "Richard D.", "lastName": "Boyce" }, { "creatorType": "author", "firstName": "Maria M.", "lastName": "Brooks" } ], "abstractNote": "STUDY OBJECTIVES: Individuals with isolated REM sleep behavior disorder (iRBD) are at high risk of neurodegenerative parkinsonian disorders or dementia (NPD). Determining which characteristics predict greatest risk could improve clinical care. Our objectives were to utilize electronic health record (EHR) data to apply prodromal PD research diagnostic criteria to iRBD outpatients and determine their utility for identifying iRBD cases at high vs low risk for NPD diagnosis.\nMETHODS: This was a retrospective cohort study at a tertiary care center in Western Pennsylvania. Diagnosis of iRBD was confirmed with expert manual chart review. Prodromal risk markers and signs/symptoms were determined with diagnostic codes. Multivariable Cox proportional hazards models examined a range of covariates as predictors of time to NPD diagnosis.\nRESULTS: Of 448 iRBD cases, 82 (18.30%) were diagnosed with NPD. Forty-nine (10.93%) had >80% prodromal PD probability. There was no difference in time to NPD among those who met vs did not meet >80% probability (log rank p=0.49). In a Cox model that included all assessed criteria features, risk of diagnosis was associated with male sex (HR=2.06, 95%CI 1.04-1.10), older baseline age (HR=1.07; 95%CI 1.05-1.10), and cognitive dysfunction diagnostic code (HR= 2.83, 95%CI 1.79-4.46). Time to NPD diagnosis among predicted high- vs low- risk cases was significantly different (Log-rank test p=0.012).\nCONCLUSIONS: In outpatients with iRBD, a model combining individual PD risk factors and prodromal features accurately identifies individuals at high risk for NPD diagnosis. Results demonstrate the potential of EHR data to translate research on prodromal PD to the clinic.", "publicationTitle": "Journal of clinical sleep medicine: JCSM: official publication of the American Academy of Sleep Medicine", "publisher": "", "place": "", "date": "2025-07-31", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "J Clin Sleep Med", "DOI": "10.5664/jcsm.11824", "citationKey": "", "url": "", "accessDate": "", "PMID": "40742128", "PMCID": "", "ISSN": "1550-9397", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "eng", "libraryCatalog": "PubMed", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Parkinsons disease", "type": 1 }, { "tag": "REM sleep behavior disorder", "type": 1 }, { "tag": "electronic health record data", "type": 1 }, { "tag": "risk assessment", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2025-09-30T17:40:51Z", "dateModified": "2025-09-30T17:40:51Z" } }, { "key": "AMM9TTW6", "version": 7042, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/AMM9TTW6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/AMM9TTW6", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/Q38UTX5B", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "AMM9TTW6", "version": 7042, "parentItem": "Q38UTX5B", "itemType": "attachment", "linkMode": "linked_url", "title": "PubMed entry", "accessDate": "2025-09-30T17:40:51Z", "url": "http://www.ncbi.nlm.nih.gov/pubmed/40742128", "note": "", "contentType": "text/html", "charset": "", "tags": [], "relations": {}, "dateAdded": "2025-09-30T17:40:51Z", "dateModified": "2025-09-30T17:40:51Z" } }, { "key": "NAHSL5YQ", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/NAHSL5YQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/NAHSL5YQ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Chahine et al.", "parsedDate": "2025-02", "numChildren": 1 }, "data": { "key": "NAHSL5YQ", "version": 7147, "itemType": "journalArticle", "title": "REM Sleep Behavior Disorder Diagnostic Code Accuracy and Implications in the Real-World Setting", "creators": [ { "creatorType": "author", "firstName": "Lana M.", "lastName": "Chahine" }, { "creatorType": "author", "firstName": "Deena", "lastName": "Ratner" }, { "creatorType": "author", "firstName": "Aaron", "lastName": "Palmquist" }, { "creatorType": "author", "firstName": "Gayatri", "lastName": "Dholakia" }, { "creatorType": "author", "firstName": "Anne B.", "lastName": "Newman" }, { "creatorType": "author", "firstName": "Richard D.", "lastName": "Boyce" }, { "creatorType": "author", "firstName": "Caterina", "lastName": "Rosano" }, { "creatorType": "author", "firstName": "Maria", "lastName": "Brooks" } ], "abstractNote": "BACKGROUND AND OBJECTIVES: Isolated REM sleep behavior disorder (iRBD) carries increased risk of neurodegenerative parkinsonian disorder or dementia (NPD) but is difficult to accurately screen for in the community. Health care data offer the opportunity to identify large numbers of iRBD cases among outpatients. We aimed to determine the positive predictive value (PPV) of an RBD International Classification of Disorders (ICD) code for actual iRBD based on manual review of the electronic health record (EHR), examine risk of NPD diagnosis, and explore whether a statistical model developed using selected EHR data can identify individuals with the RBD ICD code who have high probability for actual iRBD.\nMETHODS: In this retrospective cohort study, a search of the EHR at a single health care system was conducted to identify outpatients who received the ICD9 or ICD10 RBD code in 2011-2021. The EHR for each case was manually reviewed. Secondary RBD cases were excluded. Remaining cases were classified as no iRBD or actual iRBD (possible, probable, or definite). Incident cases of NPD were identified. PPV of presence of the RBD ICD code for actual iRBD was calculated. Cumulative incidence of NPD with death as a competing event was compared in those with vs without iRBD. Least absolute shrinkage and selection operator (LASSO) regression was used to build a prediction model for iRBD, and the model was validated in an independent data set.\nRESULTS: Among 1,130 cases with the RBD ICD code, 499 had secondary causes of RBD. For the remaining 628 cases, EHR review indicated no iRBD in 168 (26.8%). PPV of the RBD ICD code was 73.25%. Over a median follow-up of 4.7 years, compared with the no iRBD group, the iRBD group had a higher risk of NPD (subdistribution hazard ratio = 10.4 [95% CI 2.5-43.1]). The LASSO prediction model for iRBD had an area under the receiver operating characteristic curve of 0.844 (95% CI 0.806-0.880).\nDISCUSSION: PPV of an RBD ICD code is moderate. In the real-world setting, patients with iRBD had a high risk of incident diagnosis of NPD over 4.7 years. Results indicate feasibility of using statistical models developed using EHR data to accurately predict iRBD.", "publicationTitle": "Neurology. Clinical Practice", "publisher": "", "place": "", "date": "2025-02", "volume": "15", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "e200387", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Neurol Clin Pract", "DOI": "10.1212/CPJ.0000000000200387", "citationKey": "", "url": "", "accessDate": "", "PMID": "39524103", "PMCID": "PMC11547835", "ISSN": "2163-0402", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "eng", "libraryCatalog": "PubMed", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2025-09-30T17:40:45Z", "dateModified": "2025-09-30T17:40:45Z" } }, { "key": "R3MU7BX3", "version": 7041, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/R3MU7BX3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/R3MU7BX3", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/NAHSL5YQ", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "R3MU7BX3", "version": 7041, "parentItem": "NAHSL5YQ", "itemType": "attachment", "linkMode": "linked_url", "title": "PubMed entry", "accessDate": "2025-09-30T17:40:45Z", "url": "http://www.ncbi.nlm.nih.gov/pubmed/39524103", "note": "", "contentType": "text/html", "charset": "", "tags": [], "relations": {}, "dateAdded": "2025-09-30T17:40:45Z", "dateModified": "2025-09-30T17:40:45Z" } }, { "key": "CCB6S4LK", "version": 7039, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/CCB6S4LK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/CCB6S4LK", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/TCUWLQBR", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "CCB6S4LK", "version": 7039, "parentItem": "TCUWLQBR", "itemType": "attachment", "linkMode": "imported_url", "title": "Snapshot", "accessDate": "2025-09-30T17:36:42Z", "url": "https://journals.physiology.org/doi/10.1152/ajprenal.00184.2024", "note": "", "contentType": "text/html", "charset": "utf-8", "filename": "ajprenal.00184.html", "md5": "dd876da1963f1bf5764dd7c7be0e0f4c", "mtime": 1759253802956, "tags": [], "relations": {}, "dateAdded": "2025-09-30T17:36:42Z", "dateModified": "2025-09-30T17:36:42Z" } }, { "key": "TCUWLQBR", "version": 7147, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/TCUWLQBR", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/TCUWLQBR", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "lastModifiedByUser": { "id": 17155, "username": "hshoch", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/hshoch", "type": "text/html" } } }, "creatorSummary": "Zhang et al.", "parsedDate": "2024-10-30", "numChildren": 1 }, "data": { "key": "TCUWLQBR", "version": 7147, "itemType": "journalArticle", "title": "Transition from acute kidney injury to chronic kidney disease: mechanisms, models, and biomarkers", "creators": [ { "creatorType": "author", "firstName": "Tingfang", "lastName": "Zhang" }, { "creatorType": "author", "firstName": "Robert E.", "lastName": "Widdop" }, { "creatorType": "author", "firstName": "Sharon D.", "lastName": "Ricardo" } ], "abstractNote": "Acute kidney injury (AKI) and chronic kidney disease (CKD) are increasingly recognized as interconnected conditions with overlapping pathophysiological mechanisms. This review examines the transition from AKI to CKD, focusing on the molecular mechanisms, animal models, and biomarkers essential for understanding and managing this progression. AKI often progresses to CKD due to maladaptive repair processes, persistent inflammation, and fibrosis, with both conditions sharing common pathways involving cell death, inflammation, and extracellular matrix (ECM) deposition. Current animal models, including ischemia-reperfusion injury (IRI) and nephrotoxic damage, help elucidate these mechanisms but have limitations in replicating the complexity of human disease. Emerging biomarkers such as kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and soluble tumor necrosis factor receptors (TNFRs) show promise in early detection and monitoring of disease progression. This review highlights the need for improved animal models and biomarker validation to better mimic human disease and enhance clinical translation. Advancing our understanding of the AKI-to-CKD transition through targeted therapies and refined research approaches holds the potential to significantly improve patient outcomes.", "publicationTitle": "American Journal of Physiology-Renal Physiology", "publisher": "American Physiological Society Rockville, MD", "place": "", "date": "2024 Oct 30", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1152/ajprenal.00184.2024", "citationKey": "", "url": "https://journals.physiology.org/doi/10.1152/ajprenal.00184.2024", "accessDate": "2025-09-30T17:36:39Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "Rockville, MD", "shortTitle": "Transition from acute kidney injury to chronic kidney disease", "language": "en", "libraryCatalog": "journals.physiology.org", "callNumber": "", "rights": "Copyright © 2024 the American Physiological Society.", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2025-09-30T17:36:39Z", "dateModified": "2025-09-30T17:36:39Z" } }, { "key": "65HQXUBS", "version": 7036, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/65HQXUBS", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/65HQXUBS", "type": "text/html" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } }, "creatorSummary": "Schuemie", "numChildren": 1 }, "data": { "key": "65HQXUBS", "version": 7036, "itemType": "webpage", "title": "White Rabbit and Rabbit In A Hat", "creators": [ { "creatorType": "author", "firstName": "Martijn", "lastName": "Schuemie" } ], "abstractNote": "", "websiteTitle": "", "websiteType": "", "date": "", "publisher": "", "place": "", "DOI": "", "citationKey": "", "url": "https://ohdsi.github.io/WhiteRabbit/", "accessDate": "2025-09-30T17:07:31Z", "shortTitle": "", "language": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2025-09-30T17:07:31Z", "dateModified": "2025-09-30T17:09:03Z" } }, { "key": "IU483THW", "version": 7031, "library": { "type": "group", "id": 14236, "name": "informatics-and-drug-safety", "links": { "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/14236/items/IU483THW", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/informatics-and-drug-safety/items/IU483THW", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/14236/items/65HQXUBS", "type": "application/json" } }, "meta": { "createdByUser": { "id": 8771, "username": "boycer", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/boycer", "type": "text/html" } } } }, "data": { "key": "IU483THW", "version": 7031, "parentItem": "65HQXUBS", "itemType": "attachment", "linkMode": "imported_url", "title": "Introduction", "accessDate": "2025-09-30T17:07:31Z", "url": "https://ohdsi.github.io/WhiteRabbit/", "note": "", "contentType": "text/html", "charset": "utf-8", "filename": "WhiteRabbit.html", "md5": "3ec7e490d7f619390942637a0e431cad", "mtime": 1759252051826, "tags": [], "relations": {}, "dateAdded": "2025-09-30T17:07:31Z", "dateModified": "2025-09-30T17:07:31Z" } } ]