Diagnosis最新文献

{"title":"Solutions to reduce healthcare costs and improve outcomes in diagnostics: safety nets, optimized navigation, and decision support.","authors":"Sierra Stingl Sauter, Reza A Jarral, Yan Wang, Nirav R Shah, Robert M Kaplan, Robert Rebitzer, Victoria G Woo, Stephanie Peters, Terry Platchek, Arnold Milstein","doi":"10.1515/dx-2026-0074","DOIUrl":"https://doi.org/10.1515/dx-2026-0074","url":null,"abstract":"<p><strong>Objectives: </strong>Diagnostic error is common, harmful, and costly, yet most health systems lack active interventions to improve diagnostic safety. This study aimed to identify scalable care models that advance diagnostic excellence while reducing costs for healthcare systems across diverse delivery and reimbursement environments.</p><p><strong>Methods: </strong>We employed a multi-method care model development framework that integrated: (1) a literature review of 1,632 sources, (2) 19 semi-structured expert interviews, (3) in-depth analysis of four exemplar programs, and (4) four iterative refinement cycles with a 12-member cross-institutional expert panel. Candidate interventions were evaluated by diagnostic failure points, potential net cost savings, operational feasibility, stakeholder value alignment, and payment-model fit.</p><p><strong>Results: </strong>We identified three highest value care model archetypes. (1) Diagnostic safety nets identify patients with abnormal findings lacking appropriate follow-up and re-engage them before harm escalates. (2) Optimized navigation routes patients to the right level of care through risk stratification and selective specialist input. (3) Decision support strengthens diagnostic reasoning at the point of care through evidence-based diagnostic tools. These archetypes differed in infrastructure requirements and financial attractiveness across payment models, with diagnostic safety nets most broadly attractive across both fee-for-service and risk-bearing environments.</p><p><strong>Conclusions: </strong>This framework introduces three diagnostic improvement archetypes that health systems can use to select and sequence interventions based on local failure points, operational feasibility, and reimbursement context. By linking intervention choice to real-world implementation conditions, the framework offers a pragmatic approach for advancing diagnostic excellence across diverse care delivery settings.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148789334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of sleep on resident clinical reasoning: a scoping review.","authors":"Vincent F Capaldi, Youssouf Aidara, Brendan Flores, Jinbum Dupont, Eungjae Kim, Guido Simonelli, Steven Durning, Eulho Jung","doi":"10.1515/dx-2026-0024","DOIUrl":"https://doi.org/10.1515/dx-2026-0024","url":null,"abstract":"<p><p>Residency training is an essential part of medical education, characterized by long work hours, high cognitive demands, and insufficient sleep. Given the ACGME duty-hour reforms and the ongoing debate over work-hour restrictions, we conducted a scoping review on the relationship between sleep and clinical reasoning learning and performance in graduate medical education, using the Arksey and O'Malley framework (between 2003 and Dec 2024). Our review aimed to: (1) identify and map the existing literature linking sleep and clinical reasoning learning and performance in medical residents, (2) examine the methodological approaches used to assess sleep and clinical reasoning learning and performance, and (3) identify gaps in research to inform future studies. Studies were included if they studied physicians in residency training and examined both a sleep-related exposure (e.g. fatigue, sleep deprivation, shift work) and an educational outcome related to clinical reasoning (the cognitive steps up to and including establishing a diagnosis and management plan). We identified 4,309 articles initially, with 31 studies meeting final inclusion criteria, across a wide range of medical specialties. Clinical reasoning learning and performance assessments were heterogeneous, encompassing diagnostic accuracy, medical errors, decision-making speed, technical skill performance, and patient safety outcomes. Sleep measures varied, with most studies relying on self-reported sleep measures. Studies overall reported that insufficient sleep negatively impacts clinical reasoning learning and performance, particularly among junior residents. Residency programs should consider tailored evidence-based learning strategies and scheduling adjustments to ensure adequate rest, particularly for junior trainees.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148789339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving diagnostic safety - where should healthcare organizations start? CERC suggestions and our own.","authors":"Andrew P J Olson, Carl T Berdahl, Taro Shimizu, Mark L Graber","doi":"10.1515/dx-2026-0147","DOIUrl":"https://doi.org/10.1515/dx-2026-0147","url":null,"abstract":"<p><p>Research over the past decades has established diagnostic errors to be the foremost patient safety challenge in health care today; the harm related to diagnostic errors is unacceptably high. We now understand where, when, and why these errors arise, and a wide range of interventions to improve diagnostic safety and quality are now being proposed, focusing on both the system-related, and personal, cognitive aspects of the diagnostic process. Stanford University's Clinical Excellence Research Center (CERC) has done a great service to the field by convening an expert panel to provide consensus recommendations on economically-beneficial interventions that would have the greatest clinical impact. The CERC report identified these 3 areas as the top priorities: 1 - Optimizing patient navigation and care coordination; 2 - Providing clinicians with decision support resources; and 3 - Creating diagnostic 'safety nets' to close the loop on abnormal, critical test results. Although the CERC recommendations represent state-of-the-art, authoritative advice, we believe there are 3 other interventions that have comparable financial and clinical impact profiles: 1 - Finding and learning from diagnostic errors; 2 - Improving clinical reasoning; and 3 - Promoting patient engagement. Healthcare organizations have an obligation to begin improving diagnostic safety and quality, and both the CERC recommendations and our own represent excellent options that should be considered for immediate adoption.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148789427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing diagnostic safety: addressing knowledge gaps for using human factors tools in the safe and effective use of AI - a proposed research agenda.","authors":"Emily S Patterson, Grayson L Baird, David Bates, Jeff Brady, Kenneth R Catchpole, Linda Gangai, Mark Graber, Ayse P Gurses, Charles E Kahn, Elizabeth A Krupinski, Soundar Kumara, Chris Mamrol, Kristen E Miller, Timothy J Mosher, Sarah E Parker, Mary D Patterson, Susan Shelmerdine, Joshua Streit, Charlotte van Sassen, Michael H Kanter, Melissa Carraway, Michael A Bruno","doi":"10.1515/dx-2026-0082","DOIUrl":"https://doi.org/10.1515/dx-2026-0082","url":null,"abstract":"<p><strong>Introduction: </strong>Identify knowledge gaps in applying artificial intelligence in clinical settings, using medical imaging as a primary use case to enhance diagnostic efficacy, efficiency, and patient and provider safety.</p><p><strong>Methods: </strong>We convened a two-day workshop with 18 interdisciplinary experts from three countries. Experts represented quality and patient safety, human factors and systems engineering, radiology and other medical specialties, nursing, medical informatics, cognitive and perceptual psychology, psychometrics and statistics, and machine learning, drawn from academia, industry, health systems, and government.</p><p><strong>Results: </strong>We identified by consensus six major knowledge-gap domains, with specific research questions for each domain: development, validation, integration and sustainability; redesign of existing healthcare systems; human and team augmentation; deployment of adaptive-learning \"Foundation Models;\" and balancing innovation, standardization, and regulatory oversight.</p><p><strong>Conclusions: </strong>We recommend employing a multidisciplinary collaborative approach in future research to leverage transformational AI capabilities anticipated in the next 5-7 years for each of the identified knowledge-gap domains, including ensuring that clinical AI supports diagnostic decision-making, integrates into clinical workflows, and mitigates risks related to automation bias, overreliance, fragmentation of care, and unintended consequences.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148711837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The CODEX action incubator: a consensus-driven approach to identify and implement diagnostic excellence measures in the context of artificial intelligence.","authors":"Benjamin Rosner, Molly Hammer, Aaron Tabacco, Julia Adler-Milstein, Sumant R Ranji","doi":"10.1515/dx-2026-0112","DOIUrl":"https://doi.org/10.1515/dx-2026-0112","url":null,"abstract":"<p><p>Diagnostic errors are a substantial source of patient harm. As artificial intelligence (AI) integrates into clinical workflows, opportunities are emerging to assess their impacts on diagnostic excellence (DxEx). The Coordinating Center for Diagnostic Excellence (CODEX) at the University of California San Francisco established the Action Incubator to translate research advances in DxEx into tangible strategies for improving diagnosis. The September 2025 in-person inaugural Action Incubator convened 30 multidisciplinary stakeholders representing health systems, patient advocacy, industry, and policy groups. Through structured discussions and breakout sessions, participants identified AI scribes as a near-term, scalable use case for evaluating AI's impact on diagnosis not only because of their widespread adoption, but - as supported by cognitive load theory - because of their potential to reduce cognitive burden and allow clinicians to focus more on diagnosis. A modified Delphi process was used to prioritize candidate measures based on feasibility, and impact. Participants generated 17 candidate measures of AI scribe impact on DxEx. Consensus was reached on two priority metrics as functions of AI scribe usage rates by primary care physicians: (1) Timely follow-up of abnormal test results related to breast and colorectal cancer screening and (2) Patient-reported diagnostic experience. Participating health systems will pilot these measures using electronic health record audit logs and patient surveys. The first CODEX Action Incubator developed a pragmatic, consensus-driven framework for measuring the impact of AI on DxEx. Future annual Action Incubators will take up timely, actionable topics related to DxEx.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148711852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The inherited diagnosis and diagnostic error: a case report.","authors":"Matthias Blume","doi":"10.1515/dx-2026-0101","DOIUrl":"https://doi.org/10.1515/dx-2026-0101","url":null,"abstract":"<p><strong>Objectives: </strong>We describe a case of diagnostic error arising from unquestioned acceptance of a longstanding, inherited diagnosis.</p><p><strong>Case presentation: </strong>A patient developed CSF hypotension syndrome following minor trauma. A sacral cyst on imaging was attributed to a Tarlov cyst documented incidentally a decade earlier. Despite progressive symptoms, exhausted conservative therapy, and a radiological report explicitly questioning the diagnosis, the recommended post-myelography CT was twice deferred. The correct diagnosis - a meningomyelocele causing a traumatic CSF leak - was eventually established through external specialist consultation and treated surgically.</p><p><strong>Conclusions: </strong>Diagnostic momentum, a non-integrated radiological correction signal, and the low cognitive accessibility of rare alternative possibilities combined to delay recognition of the meningomyelocele. Clinicians should not consider prior diagnostic labels as invariably true or well established. Many of these were simply never fully verified or confirmed over time, and these 'inherited' diagnoses are a risk factor for diagnostic error.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148711792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic concordance and delayed recognition: a case of atypical Kaposi sarcoma.","authors":"Hunter Cohn, Jeannie Hennessy, Kaitlin Schupp, Stephanie Cotell","doi":"10.1515/dx-2026-0009","DOIUrl":"https://doi.org/10.1515/dx-2026-0009","url":null,"abstract":"<p><strong>Objectives: </strong>Accurate diagnosis depends on concordance among clinical findings, histopathologic features, and patient context; when these elements diverge, even well-characterized diseases may evade timely recognition.</p><p><strong>Case presentation: </strong>We report a case of Kaposi sarcoma (KS) in a 47-year-old woman who presented with a chronic, unilateral, non-violaceous eruption of the left lower extremity. Serial clinical evaluations and biopsies demonstrated dermal fibrosis, vascular congestion, and hemosiderin deposition without the classic histopathologic features typically associated with KS, leading to repeated interpretation as reactive or stasis-related disease. Despite progressive clinical findings, apparent concordance between benign-appearing clinical and histologic features delayed diagnostic reassessment. Ultimately, expert dermatopathology consultation with immunohistochemical staining confirmed KS in the setting of previously unrecognized HIV infection.</p><p><strong>Conclusions: </strong>This case illustrates how atypical disease biology, false reassurance from partial concordance, fragmented care, and social determinants of health can disrupt diagnostic synthesis and obscure evolving malignancy. When disease behavior contradicts initial interpretations, deliberate reassessment and longitudinal integration of data across encounters and specialties are essential to avoid delayed diagnosis, particularly in patients facing barriers to longitudinal continuity of care.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical reasoning research priorities for advancing diagnostic safety: researcher and patient perspectives.","authors":"Roni Matin, Ashley N D Meyer, Hardeep Singh, Andrew P J Olson, David A Cook, Laura Zwaan","doi":"10.1515/dx-2026-0018","DOIUrl":"https://doi.org/10.1515/dx-2026-0018","url":null,"abstract":"<p><strong>Objectives: </strong>This study used both researcher and patient perspectives to identify high-priority research questions related to clinical reasoning.</p><p><strong>Methods: </strong>This study integrates findings from two previously published research prioritization exercises aimed at advancing the science of diagnostic safety, focusing on questions relevant to clinical reasoning. In Study 1 (April 2019), 97 researchers submitted 177 unique research questions that could be useful \"to reduce patient harm in the diagnosis process\". In Study 2 (November 2019), 41 patients/caregivers/advocates submitted 84 unique research questions on the same topic. In an in-person meeting, a subset of these participants identified 81 of these questions as high-priority (51 from Study 1; 30 from Study 2). For the current study, five investigators identified questions that focused on clinical reasoning, first independently and then by consensus. They then categorized the clinical reasoning questions into inductively identified themes.</p><p><strong>Results: </strong>Twenty-nine of the 81 high-priority research questions addressed clinical reasoning and were categorized into 5 themes: understanding clinical reasoning and cognition (12 questions), decision support/technology (6 questions), team-based decision making (5 questions), how to learn from cases/scenarios (3 questions), and patient engagement (3 questions). Questions addressed a range of basic/foundational science and clinical applications, and involved individuals, teams, and/or systems.</p><p><strong>Conclusions: </strong>Identification of high-priority clinical reasoning research questions can help medical educators, clinicians, researchers, and funders catalyze research and discovery of interventions to improve clinical reasoning and ultimately improve patient outcomes.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148618819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidating behavioral and environmental barriers to clinicians' engagement in endometriosis diagnostic practices: a mixed-methods scoping review.","authors":"Allyson C Bontempo, Aleena Saleem, Lauren E Lee, Kristine Schmitz, Julia P Grimes, Ibiyonu Lawrence, Payal Chowdhary, Danielle Flood, Neha Bhagat, Jessica Opoku-Anane","doi":"10.1515/dx-2026-0067","DOIUrl":"https://doi.org/10.1515/dx-2026-0067","url":null,"abstract":"<p><p>Endometriosis is an estrogen-dependent chronic systemic inflammatory disease that affects 10 % of people assigned female at birth. Despite its prevalence, mean diagnostic delay is 4-11 years. Although much research has involved patients, much less work has involved clinicians. Moreover, the studies that do exist have not been guided by a public health framework. Accordingly, this review leverages PRECEDE-PROCEED Model (PPM) Phase 3 to synthesize published studies on behavioral and environmental barriers to clinicians' engagement in endometriosis diagnostic practices. Five databases were searched. Studies that examined behavioral (e.g., knowledge, beliefs, attitudes) and environmental (e.g., lack of resources, lack of reinforcement) barriers to clinicians' engagement in endometriosis diagnostic practices, per the National Academy of Medicine, were included. Three investigators independently screened studies and extracted data, which were synthesized according to PPM Phase 3. Thirty-one studies were included. The most frequently reported barrier was lack of knowledge. Additional barriers included beliefs about and attitudes towards patients with endometriosis and/or their preferences that diverged from extant literature. For example, some clinicians believed that disclosing a diagnosis could trigger anxiety for patients, purportedly leading clinicians to withhold it as a diagnostic possibility. Environmental barriers (time constraints, lack of training, lack of access to obstetrician/gynecologists) also existed. Given the prevalence of endometriosis and complications, addressing diagnostic delay for endometriosis is critical. Solutions include not just more clinician education and training but interventions targeting clinician beliefs and attitudes, as knowledge alone is insufficient for behavior change. These changes must be considered within the environmental barriers discussed.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148583797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The diagnostic yield of gastroscopy in the evaluation of asymptomatic patients with iron deficiency anemia.","authors":"Ahmad Mahamid, Randa Taher Natour, Amir Mari, Majd Khader, Rawi Hazzan, Oren Gal, Fadi Abu Baker","doi":"10.1515/dx-2025-0154","DOIUrl":"https://doi.org/10.1515/dx-2025-0154","url":null,"abstract":"<p><strong>Objectives: </strong>The diagnostic value of upper endoscopy (EGD) in asymptomatic patients with iron deficiency anemia (IDA) remains uncertain, given the low prevalence of upper gastrointestinal (GI) malignancy.</p><p><strong>Methods: </strong>We performed a retrospective cohort study comparing asymptomatic patients with laboratory-confirmed IDA to asymptomatic controls referred for pre-bariatric endoscopy. Between-group comparisons assessed demographic, procedural, and endoscopic features. Diagnostic yield was evaluated for clinically significant findings (CSFs) and histologically confirmed malignancy. Diagnostic efficiency was expressed as the number needed to investigate (NNTI). Predictors of CSF and malignancy were identified by multivariable logistic regression, and receiver operating characteristic (ROC) analysis determined optimal age cutoffs.</p><p><strong>Results: </strong>Among 6,185 IDA patients and 2,010 controls, endoscopic pathology was significantly more frequent in the anemia group. Major CSFs were detected in 8.2 % of IDA patients vs. 2.9 % of controls (p<0.0001), while malignancy occurred in 1.3 vs. 0.1 % (p<0.0001). Diagnostic efficiency was superior in IDA (NNTI˜12 for CSF; <100 for malignancy) compared with controls (>30 and >1,000, respectively). In adjusted models, IDA and age ≥50 years independently predicted CSFs and malignancy, whereas female sex was inversely associated. ROC analysis identified optimal age thresholds of approximately 60 years for CSFs and 65 years for malignancy.</p><p><strong>Conclusions: </strong>Among asymptomatic patients with IDA, EGD demonstrated a substantially higher yield of CSFs and upper gastrointestinal malignancy than in asymptomatic controls, particularly among older individuals. These findings provide a large real-world benchmark for the isolated diagnostic yield of EGD and may inform future risk-stratified approaches to IDA evaluation.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}