JAMA Network Open最新文献

{"title":"Error in Figure.","authors":"","doi":"10.1001/jamanetworkopen.2025.19224","DOIUrl":"10.1001/jamanetworkopen.2025.19224","url":null,"abstract":"","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2519224"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12138718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144215856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac Implantable Device Infection Surveillance Algorithm.","authors":"Hillary J Mull, Samuel W Golenbock, Dipandita Basnet Thapa, Marlena H Shin, Kimberly L Harvey, Rebecca P Lamkin, Judith Strymish, Westyn Branch-Elliman","doi":"10.1001/jamanetworkopen.2025.14079","DOIUrl":"10.1001/jamanetworkopen.2025.14079","url":null,"abstract":"","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2514079"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12142443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Burden of Alzheimer Disease and Related Dementias by Race and Ethnicity, 2020 to 2060.","authors":"Stipica Mudrazija, María P Aranda, Darrell J Gaskin, Stephanie Monroe, Patrick Richard","doi":"10.1001/jamanetworkopen.2025.13931","DOIUrl":"10.1001/jamanetworkopen.2025.13931","url":null,"abstract":"<p><strong>Importance: </strong>Alzheimer disease and related dementias (ADRD) have substantial clinical and public health consequences for individuals, families, employers, and government.</p><p><strong>Objective: </strong>To assess ADRD's economic burden on non-Latino African American, Latino, and non-Latino White adults and their caregivers, employers, and the government between 2020 and 2060.</p><p><strong>Design, setting, and participants: </strong>Population-based cross-sectional study using nationally representative data on African American, Latino, and White adults aged 50 years and older with ADRD and their unpaid caregivers from the 2014 to 2020 Medical Expenditure Panel Survey (MEPS) alongside the 2011 to 2017 National Study of Caregiving (NSOC) and 2013 Panel Study of Income Dynamics. These data were augmented with information from the US Census Bureau, Bureau of Labor Statistics, Internal Revenue Service, and other sources to estimate current and future economic burden. Two-part regression models were used to estimate medical and work-related costs for older adults, and multivariate-distance matching was used to estimate the value of unpaid care, lost wages and productivity, loss of federal income tax revenue, and financial transfers for caregivers. Data were analyzed from March 2023 to February 2025.</p><p><strong>Exposure: </strong>Older adults with ADRD and their family caregivers.</p><p><strong>Main outcomes and measures: </strong>Projected medical costs and work-related losses for persons with ADRD, and unpaid care value, forgone earnings, and lost federal income tax payments and labor productivity for caregivers.</p><p><strong>Results: </strong>Of 31 028 older adults in MEPS, 5184 (10%) were African American; 146 (<1%) American Indian or Alaska Native; 1043 (3%) Asian (Indian, Chinese, or Filipino); 5346 (10%) Latino; 690 (2%) Other Asian, Native Hawaiian, and Pacific Islander; and 18 617 (75%) were White. In the NSOC sample of 1929 older adults, there were 644 (33%) African American, 169 (9%) Latino, and 1116 (58%) White adults. The total estimated economic burden of ADRD was close to $344 billion in 2020 and was projected to increase to over $3 trillion in 2060. African American and Latino adults bore one-third ($113 billion) of it in 2020, with projections rising to $1.7 trillion by 2060, surpassing the economic burden for White adults, which was projected to grow from $231 billion to $1.4 trillion.</p><p><strong>Conclusions and relevance: </strong>The findings of this study suggest that African American and Latino older adults with ADRD and their families are likely to face disproportionately high burdens, primarily associated with unpaid caregiving. Understanding ADRD prevalence, comorbidity, inadequate care, and support policies may attenuate economic burdens for all US residents.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2513931"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12142444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency and Quality of Generative AI-Assisted Radiograph Reporting.","authors":"Jonathan Huang, Matthew T Wittbrodt, Caitlin N Teague, Eric Karl, Galal Galal, Michael Thompson, Ajay Chapa, Ming-Lun Chiu, Bradley Herynk, Richard Linchangco, Ali Serhal, J Alex Heller, Samir F Abboud, Mozziyar Etemadi","doi":"10.1001/jamanetworkopen.2025.13921","DOIUrl":"10.1001/jamanetworkopen.2025.13921","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Diagnostic imaging interpretation involves distilling multimodal clinical information into text form, a task well-suited to augmentation by generative artificial intelligence (AI). However, to our knowledge, impacts of AI-based draft radiological reporting remain unstudied in clinical settings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To prospectively evaluate the association of radiologist use of a workflow-integrated generative model capable of providing draft radiological reports for plain radiographs across a tertiary health care system with documentation efficiency, the clinical accuracy and textual quality of final radiologist reports, and the model's potential for detecting unexpected, clinically significant pneumothorax.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This prospective cohort study was conducted from November 15, 2023, to April 24, 2024, at a tertiary care academic health system. The association between use of the generative model and radiologist documentation efficiency was evaluated for radiographs documented with model assistance compared with a baseline set of radiographs without model use, matched by study type (chest or nonchest). Peer review was performed on model-assisted interpretations. Flagging of pneumothorax requiring intervention was performed on radiographs prospectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;The primary outcomes were association of use of the generative model with radiologist documentation efficiency, assessed by difference in documentation time with and without model use using a linear mixed-effects model; for peer review of model-assisted reports, the difference in Likert-scale ratings using a cumulative-link mixed model; and for flagging pneumothorax requiring intervention, sensitivity and specificity.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 23 960 radiographs (11 980 each with and without model use) were used to analyze documentation efficiency. Interpretations with model assistance (mean [SE], 159.8 [27.0] seconds) were faster than the baseline set of those without (mean [SE], 189.2 [36.2] seconds) (P = .02), representing a 15.5% documentation efficiency increase. Peer review of 800 studies showed no difference in clinical accuracy (χ2 = 0.68; P = .41) or textual quality (χ2 = 3.62; P = .06) between model-assisted interpretations and nonmodel interpretations. Moreover, the model flagged studies containing a clinically significant, unexpected pneumothorax with a sensitivity of 72.7% and specificity of 99.9% among 97 651 studies screened.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions and relevance: &lt;/strong&gt;In this prospective cohort study of clinical use of a generative model for draft radiological reporting, model use was associated with improved radiologist documentation efficiency while maintaining clinical quality and demonstrated potential to detect studies containing a pneumothorax requiring immediate intervention. This study suggests the potential f","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2513921"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12142447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimated Burden of Coccidioidomycosis.","authors":"Samantha L Williams, Kaitlin Benedict, Brendan R Jackson, Malavika Rajeev, Gail Cooksey, Irene Ruberto, Thomas Williamson, Rebecca H Sunenshine, BreAnne Osborn, Hanna N Oltean, Rebecca R Reik, Michael S Freedman, Andrej Spec, Adrienne Carey, Ilan S Schwartz, Luis Medina-Garcia, Nathan C Bahr, Rasha Kuran, Arash Heidari, George R Thompson, Royce Johnson, John N Galgiani, Tom Chiller, Mitsuru Toda","doi":"10.1001/jamanetworkopen.2025.13572","DOIUrl":"10.1001/jamanetworkopen.2025.13572","url":null,"abstract":"<p><strong>Importance: </strong>Coccidioidomycosis is an underrecognized fungal infection that can cause serious illness and constitutes a considerable public health burden. The number of cases is likely substantially higher than the nationally reported total, as surveillance does not capture patients who do not seek medical care or who are undiagnosed or misdiagnosed. Coccidioidomycosis is not reportable in all states, and cases not reported to public health entities are likewise missed. A systematic estimate of coccidioidomycosis burden is needed to raise awareness and inform public health interventions and policy.</p><p><strong>Objective: </strong>To assess the annual burden of symptomatic coccidioidomycosis in the US.</p><p><strong>Design, setting, and participants: </strong>This cross-sectional study developed models incorporating coccidioidomycosis cases reported to the National Notifiable Diseases Surveillance System from January 1 to December 31, 2019, as model inputs. Multipliers from US public health surveillance accounted for factors including health care-seeking behavior, underdiagnosis, underreporting, and in-hospital mortality. Multiplier values were sourced from a combination of literature review and expert opinion. Regional estimates were generated using endemicity levels categorized as high (Arizona and California), low (Nevada, New Mexico, Texas, Utah, and Washington), or unknown (all other states and Washington, DC). Data were accrued from January 1, 2022, to July 1, 2024, and analyzed from October 1, 2022, to September 1, 2024.</p><p><strong>Exposure: </strong>Coccidioidomycosis reported to public health surveillance entities.</p><p><strong>Main outcomes and measures: </strong>Models estimated annual incident symptomatic coccidioidomycosis cases, hospitalizations, and deaths nationally and regionally in the US.</p><p><strong>Results: </strong>A nationwide total of 273 000 (95% credible interval [CrI], 206 000-360 000) incident symptomatic coccidioidomycosis cases were estimated in 2019. High-endemic states accounted for the highest burden (125 000 [95% CrI, 94 000-165 000] cases), followed by states of unknown endemicity (103 000 [95% CrI, 66 000-155 000] cases) and low-endemic states (46 000 [95% CrI, 31 000-65 000] cases). Nationally, models estimated 23 000 annual hospitalizations (95% CrI, 18 000-28 000) and 900 annual deaths (95% CrI, 700-1100) associated with coccidioidomycosis.</p><p><strong>Conclusions and relevance: </strong>In this cross-sectional study, the estimated national burden of symptomatic coccidioidomycosis in 2019 was 10 to 18 times higher than the number of cases reported through national surveillance. Better awareness, diagnostic testing practices, and reporting are needed to improve patient outcomes and enhance our understanding of coccidioidomycosis epidemiology.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2513572"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12134948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immune Checkpoint Inhibitors for Patients With Preexisting Autoimmune Neurologic Disorders.","authors":"Kylie Fletcher, Marc Machaalani, Razane El Hajj Chehade, Amin H Nassar, Rashad Nawfal, Michael Manos, Alexander M Menzies, Frank Aboubakar-Nana, Jessica C Hassel, David J Pinato, Alexandra Johnson, Anna C Olsson-Brown, Matteo S Carlino, Andrea Malgeri, Alessio Cortellini, Aditi Singh, Kaushal Parikh, So Yeon Kim, Abdul Rafeh Naqash, Georgina V Long, Pavan Challa, Toni K Choueiri, Elad Sharon, Shailee Shah, Douglas B Johnson","doi":"10.1001/jamanetworkopen.2025.13727","DOIUrl":"10.1001/jamanetworkopen.2025.13727","url":null,"abstract":"<p><strong>Importance: </strong>Immune checkpoint inhibitors (ICIs) are efficacious in many cancer types but can produce immune-related adverse events (irAEs). As such, patients with preexisting autoimmune disorders are often excluded from clinical trials, although subsequent studies have shown that many of these patients have acceptable ICI tolerance. The safety and efficacy of ICIs among patients with preexisting neurologic autoimmune disorders (NAIDs) is not well characterized.</p><p><strong>Objective: </strong>To evaluate the safety and clinical outcomes associated with ICI therapy among patients with NAIDs.</p><p><strong>Design, setting, and participants: </strong>This multicenter retrospective cohort study included patients with cancer who were treated with ICIs between October 2013 and May 2023 and had preexisting multiple sclerosis (MS), myasthenia gravis (MG), Guillain-Barré syndrome (GBS), and other NAIDs as well as a control cohort of patients with Parkinson disease (PD).</p><p><strong>Exposure: </strong>ICI therapy.</p><p><strong>Main outcomes and measures: </strong>Demographic and clinical characteristics (neurologic disability, active or recent immunosuppression), ICI outcomes (response, progression-free survival [PFS], and overall survival [OS]), and safety outcomes (NAID exacerbation, irAEs) were collected.</p><p><strong>Results: </strong>A total of 135 patients were included; the median (range) age was 72 (40-88) years, 84 (62%) were men, and 51 (38%) were women. A total of 45 patients had MS; 18, MG; 10, GBS; 5, another NAID; and 57, PD. Exacerbations occurred most frequently in MG (12 of 18 patients [67%]), often resulting in hospitalization (6 [50%]) or death (2 [17%]), with much lower rates in the MS cohort (8 of 45 patients [18%]). Ten patients with a history of GBS tolerated ICI without exacerbations, although 1 developed a fatal case of Lambert Eaton myasthenic syndrome following ICI treatment. No differences in response rate, PFS, or OS were observed between NAID groups.</p><p><strong>Conclusions and relevance: </strong>In this cohort study of ICI use in NAIDs, patients with MG had frequent and more severe exacerbations, while those with MS had few exacerbations. No obvious differences in survival between groups were observed. ICI may be an option for many patients with appropriate oncologic indications and preexisting NAIDs.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2513727"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12138719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144215857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients.","authors":"Felix Busch, Lena Hoffmann, Lina Xu, Long Jiang Zhang, Bin Hu, Ignacio García-Juárez, Liz N Toapanta-Yanchapaxi, Natalia Gorelik, Valérie Gorelik, Gaston A Rodriguez-Granillo, Carlos Ferrarotti, Nguyen N Cuong, Chau A P Thi, Murat Tuncel, Gürsan Kaya, Sergio M Solis-Barquero, Maria C Mendez Avila, Nevena G Ivanova, Felipe C Kitamura, Karina Y I Hayama, Monserrat L Puntunet Bates, Pedro Iturralde Torres, Esteban Ortiz-Prado, Juan S Izquierdo-Condoy, Gilbert M Schwarz, Jochen G Hofstaetter, Michihiro Hide, Konagi Takeda, Barbara Peric, Gašper Pilko, Hans O Thulesius, Thomas Lindow, Israel K Kolawole, Samuel Adegboyega Olatoke, Andrzej Grzybowski, Alexandru Corlateanu, Oana-Simina Iaconi, Ting Li, Izabela Domitrz, Katarzyna Kepczynska, Matúš Mihalcin, Lenka Fašaneková, Tomasz Zatonski, Katarzyna Fulek, András Molnár, Stefani Maihoub, Zenewton A da Silva Gama, Luca Saba, Petros Sountoulides, Marcus R Makowski, Hugo J W L Aerts, Lisa C Adams, Keno K Bressem, Álvaro Aceña Navarro, Catarina Águas, Martina Aineseder, Muaed Alomar, Rashid Al Sliman, Gautam Anand, Salita Angkurawaranon, Shuhei Aoki, Samuel Arkoh, Gizem Ashraf, Yesi Astri, Sameer Bakhshi, Nuru Y Bayramov, Antonis Billis, Almir G V Bitencourt, Anetta Bolejko, Antonio J Bollas Becerra, Joe Bwambale, Andreia Capela, Riccardo Cau, Kelly R Chacon-Acevedo, Tafadzwa L Chaunzwa, Rubens Chojniak, Warren Clements, Renato Cuocolo, Victor Dahlblom, Kelienny de Meneses Sousa, Jorge Esteban Villarrubia, Vijay B Desai, Ajaya K Dhakal, Virginia Dignum, Rubens G Feijo Andrade, Giovanna Ferraioli, Shuvadeep Ganguly, Harshit Garg, Cvetanka Gjerakaroska Savevska, Marija Gjerakaroska Radovikj, Anastasia Gkartzoni, Luis Gorospe, Ian Griffin, Martin Hadamitzky, Martin Hakorimana Ndahiro, Alessa Hering, Bruno Hochhegger, Mehriban R Huseynova, Fujimaro Ishida, Nisha Jha, Lili Jiang, Rawen Kader, Helen Kavnoudias, Clément Klein, George Kolostoumpis, Abraham Koshy, Nicholas A Kruger, Alexander Löser, Marko Lucijanic, Despoina Mantziari, Gaelle Margue, Sonyia McFadden, Masahiro Miyake, Wipawee Morakote, Issa Ngabonziza, Thao T Nguyen, Stefan M Niehues, Marc Nortje, Subish Palaian, Natalia V Pentara, Rui P Pereira de Almeida, Gianluigi Poma, Mitayani Purwoko, Nikolaos Pyrgidis, Vasileios Rafailidis, Clare Rainey, João C Ribeiro, Nicolás Rozo Agudelo, Keina Sado, Julia M Saidman, Pedro J Saturno-Hernandez, Vidyani Suryadevara, Gerald B Schulz, Ena Soric, Javier Soto-Pérez-Olivares, Arnaldo Stanzione, Julian Peter Struck, Hiroyuki Takaoka, Satoru Tanioka, Tran T M Huyen, Daniel Truhn, Elon H C van Dijk, Peter van Wijngaarden, Yuan-Cheng Wang, Matthias Weidlich, Shuhang Zhang","doi":"10.1001/jamanetworkopen.2025.14452","DOIUrl":"10.1001/jamanetworkopen.2025.14452","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;The successful implementation of artificial intelligence (AI) in health care depends on its acceptance by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;To survey hospital patients to investigate their trust, concerns, and preferences toward the use of AI in health care and diagnostics and to assess the sociodemographic factors associated with patient attitudes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This cross-sectional study developed and implemented an anonymous quantitative survey between February 1 and November 1, 2023, using a nonprobability sample at 74 hospitals in 43 countries. Participants included hospital patients 18 years of age or older who agreed with voluntary participation in the survey presented in 1 of 26 languages.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Exposure: &lt;/strong&gt;Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;The primary outcome was participant responses to a 26-item instrument containing a general data section (8 items) and 3 dimensions (trust in AI, AI and diagnosis, preferences and concerns toward AI) with 6 items each. Subgroup analyses used cumulative link mixed and binary mixed-effects models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 13 806 patients participated, including 8951 (64.8%) in the Global North and 4855 (35.2%) in the Global South. Their median (IQR) age was 48 (34-62) years, and 6973 (50.5%) were male. The survey results indicated a predominantly favorable general view of AI in health care, with 57.6% of respondents (7775 of 13 502) expressing a positive attitude. However, attitudes exhibited notable variation based on demographic characteristics, health status, and technological literacy. Female respondents (3511 of 6318 [55.6%]) exhibited fewer positive attitudes toward AI use in medicine than male respondents (4057 of 6864 [59.1%]), and participants with poorer health status exhibited fewer positive attitudes toward AI use in medicine (eg, 58 of 199 [29.2%] with rather negative views) than patients with very good health (eg, 134 of 2538 [5.3%] with rather negative views). Conversely, higher levels of AI knowledge and frequent use of technology devices were associated with more positive attitudes. Notably, fewer than half of the participants expressed positive attitudes regarding all items pertaining to trust in AI. The lowest level of trust was observed for the accuracy of AI in providing information regarding treatment responses (5637 of 13 480 respondents [41.8%] trusted AI). Patients preferred explainable AI (8816 of 12 563 [70.2%]) and physician-led decision-making (9222 of 12 652 [72.9%]), even if it meant slightly compromised accuracy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions and relevance: &lt;/strong&gt;In this cross-sectional study of patient attitudes toward AI use in health care acr","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2514452"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12152705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144258077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Assisted vs Unassisted Identification of Prostate Cancer in Magnetic Resonance Images.","authors":"Jasper J Twilt, Anindo Saha, Joeran S Bosma, Anwar R Padhani, David Bonekamp, Gianluca Giannarini, Roderick van den Bergh, Veeru Kasivisvanathan, Nancy Obuchowski, Derya Yakar, Mattijs Elschot, Jeroen Veltman, Jurgen Fütterer, Henkjan Huisman, Maarten de Rooij","doi":"10.1001/jamanetworkopen.2025.15672","DOIUrl":"https://doi.org/10.1001/jamanetworkopen.2025.15672","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Importance: &lt;/strong&gt;Artificial intelligence (AI) assistance in magnetic resonance imaging (MRI) assessment for prostate cancer shows promise for improving diagnostic accuracy but lacks large-scale observational evidence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To evaluate whether use of AI-assisted assessment for diagnosing clinically significant prostate cancer (csPCa) on MRI is superior to unassisted readings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design, setting, and participants: &lt;/strong&gt;This diagnostic study was conducted between March and July 2024 to compare unassisted and AI-assisted diagnostic performance using the AI system developed within the international Prostate Imaging-Cancer AI (PI-CAI) Consortium. The study involved 61 readers (34 experts and 27 nonexperts) from 53 centers across 17 countries. Readers assessed prostate magnetic resonance images both with and without AI assistance, providing Prostate Imaging Reporting and Data System (PI-RADS) annotations from 3 to 5 (higher PI-RADS indicated a higher likelihood of csPCa) and patient-level suspicion scores ranging from 0 to 100 (higher scores indicated a greater likelihood of harboring csPCa). Biparametric prostate MRI examinations were included for 780 men from the PI-CAI study who were included in the newly-conducted observer study. All men within the PI-CAI study had suspicion of harboring prostate cancer, sufficient diagnostic image quality, and no prior clinically significant cancer findings. Disease presence was defined by histopathology, and absence was determined by 3 or more years of follow-up. The AI system was recalibrated using 420 Dutch examinations to generate lesion-detection maps, with AI scores ranging from 1 to 10, in which 10 indicates the highest likelihood of csPCa. The remaining 360 examinations, originating from 3 Dutch centers and 1 Norwegian center, were included in the observer study.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main outcomes and measures: &lt;/strong&gt;The primary outcome was diagnosis of csPCa, evaluated using the area under the receiver operating characteristic curve and sensitivity and specificity at a PI-RADS threshold of 3 or more. The secondary outcomes included analysis at alternate operating points and reader expertise.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the 360 examinations of 360 men (median age, 65 years [IQR, 62-70 years]) who were included for testing, 122 (34%) harbored csPCa. AI assistance was associated with significantly improved performance, achieving a 3.3% increase in the area under the receiver operating characteristic curve (95% CI, 1.8%-4.9%; P &lt; .001), from 0.882 (95% CI, 0.854-0.910) in unassisted assessments to 0.916 (95% CI, 0.893-0.938) with AI assistance. Sensitivity improved by 2.5% (95% CI, 1.1%-3.9%; P &lt; .001), from 94.3% (95% CI, 91.9%-96.7%) to 96.8% (95% CI, 95.2%-98.5%), and specificity increased by 3.4% (95% CI, 0.8%-6.0%; P = .01), from 46.7% (95% CI, 39.4%-54.0%) to 50.1% (95% CI, 42.5%-57.7%), at a PI-RADS score of 3 or more. Secondary analyses d","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2515672"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144284397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Silver Diamine Fluoride vs Atraumatic Restoration for Managing Dental Caries in Schools: A Cluster Randomized Clinical Trial.","authors":"Ryan Richard Ruff, Aditi Ashish Gawande, Qianhui Xu, Tamarinda Barry Godín","doi":"10.1001/jamanetworkopen.2025.13826","DOIUrl":"10.1001/jamanetworkopen.2025.13826","url":null,"abstract":"<p><strong>Importance: </strong>Dental caries is a pervasive and inequitable chronic disease stemming from a lack of access to preventive and therapeutic care. Minimally invasive interventions may be provided in schools to treat caries in children.</p><p><strong>Objective: </strong>To compare the effectiveness of silver diamine fluoride (SDF) with atraumatic restorative treatment (ART) in the control of dental caries among US schoolchildren.</p><p><strong>Design, setting, and participants: </strong>The CariedAway study was a cluster randomized clinical trial conducted from February 1, 2019, to June 1, 2023, in 48 primary schools in New York City. Participants were followed up for up to 4 years. Schools with a student population of at least 50% Black and/or Hispanic or Latino students and 80% receiving free or reduced-cost lunch were eligible. Within enrolled schools, any child with parental informed consent was eligible. Treatment was provided biannually. Analysis was restricted to children aged 5 to 13 years who completed at least 1 follow-up observation and had at least 1 tooth surface with dental caries.</p><p><strong>Interventions: </strong>Participants were randomized at the school level to receive SDF or ART.</p><p><strong>Main outcomes and measures: </strong>Any surface lesion with an International Caries Detection and Assessment System score of 5 or 6 was recorded as caries. The primary outcome was the number of carious surfaces that had a recurrence of caries. Analysis was performed on an intent-to-treat basis.</p><p><strong>Results: </strong>Of the 17 741 children eligible, 7418 were randomized (mean [SD] age at baseline, 7.6 [1.9] years; 4006 girls [54.0%]), and 1668 were analyzed (mean [SD] age at baseline, 6.8 [1.5] years; 881 girls [52.8%]; 861 in the SDF group and 807 in the ART group). The total surface-level failure in the SDF group was 38.3% (2167 of 5651 carious surfaces) compared with 45.5% (2116 of 4647) in the ART group. There were 2167 surface failures observed among SDF participants over 1372 person-years compared with 2116 ART surface failures over 1291 person-years (incidence rate ratio, 0.96 [95% CI, 0.91-1.02]). At the person level, 45.5% of SDF recipients (392 of 861) experienced at least 1 surface failure compared with 53.3% of ART recipients (430 of 807; odds ratio, 0.51 [95% CI, 0.39-0.66]). There were no significant differences in the risk of recurrent surface failure between treatments (hazard ratio, 0.92 [95% CI, 0.82-1.04]).</p><p><strong>Conclusions and relevance: </strong>In this study of treatments for caries, similar failures in surface control were observed among children receiving SDF or ART. These results support the use of secondary preventive therapies for caries in schools.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: NCT03442309.</p>","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2513826"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Paternal Preconception Metformin Use and Offspring Risk of Congenital Malformations.","authors":"Krista F Huybrechts, Loreen Straub, Ran S Rotem, Brian T Bateman, Sonia Hernández-Díaz","doi":"10.1001/jamanetworkopen.2025.15002","DOIUrl":"10.1001/jamanetworkopen.2025.15002","url":null,"abstract":"","PeriodicalId":14694,"journal":{"name":"JAMA Network Open","volume":"8 6","pages":"e2515002"},"PeriodicalIF":10.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144274925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}