Antimicrobial stewardship & healthcare epidemiology : ASHE最新文献

{"title":"Can we rely on artificial intelligence to guide antimicrobial therapy? A systematic literature review.","authors":"Sulwan AlGain, Alexandre R Marra, Takaaki Kobayashi, Pedro S Marra, Patricia Deffune Celeghini, Mariana Kim Hsieh, Mohammed Abdu Shatari, Samiyah Althagafi, Maria Alayed, Jamila I Ranavaya, Nicole A Boodhoo, Nicholas O Meade, Daniel Fu, Mindy Marie Sampson, Guillermo Rodriguez-Nava, Alex N Zimmet, David Ha, Mohammed Alsuhaibani, Boglarka S Huddleston, Jorge L Salinas","doi":"10.1017/ash.2025.47","DOIUrl":"https://doi.org/10.1017/ash.2025.47","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) has the potential to enhance clinical decision-making, including in infectious diseases. By improving antimicrobial resistance prediction and optimizing antibiotic prescriptions, these technologies may support treatment strategies and address critical gaps in healthcare. This study evaluates the effectiveness of AI in guiding appropriate antibiotic prescriptions for infectious diseases through a systematic literature review.</p><p><strong>Methods: </strong>We conducted a systematic review of studies evaluating AI (machine learning or large language models) used for guidance on prescribing appropriate antibiotics in infectious disease cases. Searches were performed in PubMed, CINAHL, Embase, Scopus, Web of Science, and Google Scholar for articles published up to October 25, 2024. Inclusion criteria focused on studies assessing the performance of AI in clinical practice, with outcomes related to antimicrobial management and decision-making.</p><p><strong>Results: </strong>Seventeen studies used machine learning as part of clinical decision support systems (CDSS). They improved prediction of antimicrobial resistance and optimized antimicrobial use. Six studies focused on large language models to guide antimicrobial therapy; they had higher prescribing error rates, patient safety risks, and needed precise prompts to ensure accurate responses.</p><p><strong>Conclusions: </strong>AI, particularly machine learning integrated into CDSS, holds promise in enhancing clinical decision-making and improving antimicrobial management. However, large language models currently lack the reliability required for complex clinical applications. The indispensable role of infectious disease specialists remains critical for ensuring accurate, personalized, and safe treatment strategies. Rigorous validation and regular updates are essential before the successful integration of AI into clinical practice.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e90"},"PeriodicalIF":0.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11986881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-center retrospective evaluation of a polymerase chain reaction-based pneumonia panel on antibiotic therapy optimization at a community hospital.","authors":"Luke Manda, Anthony Wasielewski, Nishika Patel, Timothy P Gauthier","doi":"10.1017/ash.2025.57","DOIUrl":"https://doi.org/10.1017/ash.2025.57","url":null,"abstract":"<p><p>The implementation of a polymerase chain reaction-based pneumonia panel was associated with actionable results in 87% of 384 cases. In a population of mostly elderly non-intensive care unit patients with sputum samples, opportunities for antibiotic stewardship included streamlining for atypical bacteria, <i>Pseudomonas aeruginosa</i>, and methicillin-resistant <i>Staphylococcus aureus</i> coverage, with occasional opportunities to escalate antibiotic therapy.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e91"},"PeriodicalIF":0.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11986877/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healing soles: a microbiology-driven electronic health record-algorithm and order set to decrease antipseudomonal use in diabetic foot infections, a retrospective, observational, quasi-experimental study.","authors":"Antoinette Marie Acbo, Naida Koura-Mola, Terrence McSweeney, Hongkai Bao, Mei Chang, Kelsie Cowman, Priya Nori, Yi Guo","doi":"10.1017/ash.2025.59","DOIUrl":"10.1017/ash.2025.59","url":null,"abstract":"<p><strong>Background: </strong>Antipseudomonal antibiotics are commonly prescribed for diabetic foot infections (DFI) at our institution despite a low local prevalence of <i>Pseudomonas aeruginosa</i>. A multidisciplinary team implemented a DFI electronic health record (EHR)-embedded treatment algorithm and order set.</p><p><strong>Methods: </strong>This multi-center, quasi-experimental study evaluated adults on antibiotics admitted for DFI to vascular surgery or medical units pre- and post-implementation of an EHR-embedded treatment algorithm and order set. Exclusion criteria: duplicate patients, concomitant infection, transfer from an outside hospital. Primary endpoint: antipseudomonal use among included patients (DOT/1000 DFI days present). Secondary outcomes: empiric antipseudomonal use, length of stay, 30-day readmission, mortality, amputation, and <i>Clostridioides difficile</i> infection. Patient demographics, diagnostics, treatments, and outcomes were evaluated.</p><p><strong>Results: </strong>Two hundred ten patients were included with 70 patients included in each group. The post-algorithm group had lower antipseudomonal DOT/1000 DFI days present compared to the pre-intervention group (360 vs 503, <i>P</i> < 0.001). The post-order set group had the lowest antipseudomonal use (347 vs 503, <i>P</i> < 0.001). Empiric antipseudomonal use decreased from 85.7% pre-intervention to 72% post-algorithm and 68.5% post-order set. Collectively, 30-day mortality was < 5%. Amputation during and within 30 days of hospitalization was similar in the pre-intervention (48.6%), post-algorithm (30%), and post-order set (41.4%) groups. Methicillin-susceptible <i>Staphylococcus aureus</i> and <i>Streptococcus</i> spp. were most frequently isolated. Wound cultures were not collected in 24.3%, 22.9%, and 40% of the pre-intervention, post-algorithm, and post-order set group.</p><p><strong>Conclusions: </strong>EHR-embedded clinical decision-making tools reduce antipseudomonal use for DFI treatment without increasing 30-day mortality or amputation.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e89"},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the evolution of <i>Acinetobacter baumannii</i> and <i>Pseudomonas aeruginosa</i> resistance during the COVID-19 era.","authors":"Emine Sehmen, Esmeray Mutlu Yılmaz, Sevim Yetkin Pusa, Metin Özdemir, Yavuz Yiğit","doi":"10.1017/ash.2025.46","DOIUrl":"10.1017/ash.2025.46","url":null,"abstract":"<p><strong>Aim: </strong>In our study, we aim to compare the resistance profiles of <i>Acinetobacter baumannii</i> and <i>Pseudomonas aeruginosa</i> isolates from intensive care unit (ICU) patients before and during the COVID-19 pandemic.</p><p><strong>Materials: </strong>The study involved adult patients monitored in the ICUs of a secondary-level hospital from January 2019 to December 2022. Isolates of <i>A. baumannii</i> and <i>P. aeruginosa</i> were obtained from blood, urine, and respiratory samples. Identification and antibiotic susceptibility tests were conducted using the disk diffusion method and the VITEK 2 system.</p><p><strong>Results: </strong>The average age of the patients was 61.3 ± 21.9 years (range: 18-95), with a majority of 1306 (51.6%) being male. During the pandemic, <i>A. baumannii</i> isolates showed a significant increase in resistance rates for several antibiotics compared to the pre-pandemic period: imipenem (96% vs 35.1%), amikacin (84.1% vs 14.4%), ciprofloxacin (96.9% vs 36.9%), trimethoprim-sulfamethoxazole (66.4% vs 27%), and ceftazidime (96.5% vs 33.3%) (all with <i>P</i> < .001). However, there was no significant change in colistin resistance rates in these isolates (0.9% vs 0%; <i>P</i> = .307). Similarly, <i>Pseudomonas aeruginosa</i> isolates exhibited significant increases in resistance rates during the pandemic compared to the pre-pandemic period: imipenem (51.5% vs 18.8%; <i>P</i> < .001), colistin (4.9% vs 0.6%; <i>P</i> = .009), amikacin (23.5% vs 4.4%; <i>P</i> < .001), ciprofloxacin (53.3% vs 13.8%; <i>P</i> < .001), and ceftazidime (39.2% vs 12.7%; <i>P</i> < .001).</p><p><strong>Conclusion: </strong>Our results demonstrate a significant increase in antibiotic resistance levels in <i>Acinetobacter</i> and <i>Pseudomonas</i> strains associated with hospital-acquired infections or colonization during the COVID-19 pandemic.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e88"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in intravenous antimicrobial start rates in outpatient hemodialysis centers, United States, 2012-2021.","authors":"W Wyatt Wilson, Hannah Hua, Qunna Li, Minn M Soe, Ibironke W Apata, Lu Meng, Jeneita M Bell, Emily McDonald, Jonathan R Edwards, Sarah Kabbani, Shannon Novosad","doi":"10.1017/ash.2025.37","DOIUrl":"10.1017/ash.2025.37","url":null,"abstract":"<p><p>Using National Healthcare Safety Network data, an interrupted time series of intravenous antimicrobial starts (IVAS) among hemodialysis patients was performed. Annual adjusted rates decreased by 6.64% (January 2012-March 2020) and then further decreased by 8.91% until December 2021. IVAS incidence trends have decreased since 2012, including during the early COVID-19 pandemic.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e87"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of core elements of antibiotic stewardship in long-term care facilities-National Healthcare Safety Network, 2019-2022.","authors":"Angelina Luciano, Sarah Kabbani, Melinda M Neuhauser, Ti Tanissha McCray, Lindsay Robinson, Theresa Rowe, Katryna A Gouin","doi":"10.1017/ash.2025.31","DOIUrl":"10.1017/ash.2025.31","url":null,"abstract":"<p><p>In 2022, uptake of all seven Core Elements of Antibiotic Stewardship were reported by 83% of US long-term care facilities. Though 98% of facilities reported access to an electronic health record, less than one-third utilized it for tracking antibiotic use, suggesting opportunities to leverage electronic data for automated reporting.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e86"},"PeriodicalIF":0.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transition to electronic medical records improves efficiency and reach of antimicrobial stewardship service in an Australian tertiary hospital setting.","authors":"George P Drewett, Danni Miatke, Mani Suleiman, Taksh Singh Mann, Bruce Lin, Saliya Hewagama","doi":"10.1017/ash.2025.58","DOIUrl":"10.1017/ash.2025.58","url":null,"abstract":"<p><p>We examined the effect of transition to electronic medical records on the antimicrobial stewardship service (AMS) in our healthcare service, finding significant increases (<i>P</i> < 0.001) in the number and type of prescribed restricted antimicrobials identified for review, number of patients seen, and AMS intervention significance post transition.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e85"},"PeriodicalIF":0.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"(Re)Moving the needle: a retrospective, quasi-experimental assessment of the impact of a treatment guideline on oral antibiotic prescribing for orthopedic infections.","authors":"Russell J Benefield, Chanah K Becker, Julie Gray, Heather Cummins, Laura K Certain","doi":"10.1017/ash.2025.52","DOIUrl":"10.1017/ash.2025.52","url":null,"abstract":"<p><strong>Objective: </strong>Despite many reports of similar effectiveness between oral and intravenous antibiotics for bone and joint infections, prescribing practice has been slow to change in the United States. We sought to determine if implementing an intravenous-to-oral treatment guideline could increase prescribing of oral antibiotic regimens at our center.</p><p><strong>Design: </strong>Retrospective, quasi-experimental study.</p><p><strong>Setting: </strong>Single US academic medical center.</p><p><strong>Patients: </strong>Patients with bone or joint infections managed by Infectious Disease providers from September 2020 to December 2022.</p><p><strong>Intervention: </strong>An intravenous-to-oral treatment guideline for patients with bone and joint infections.</p><p><strong>Methods: </strong>The prescribing rates of fully oral antibiotic regimens before and after implementation of the guideline were compared. Additionally, variables independently associated with oral antibiotic prescribing were identified by logistic regression.</p><p><strong>Results: </strong>There were 450 patients included: 213 before and 237 after implementation of the guideline. Oral antibiotic prescribing significantly increased following implementation of the treatment guideline to 59% from 33% of patients (difference 25.8%, 95% CI [16.7%, 34.4%]. In multivariable analysis, the post-intervention phase was associated with a significantly greater likelihood of oral antibiotic prescribing (aOR 2.89 [1.90, 4.45]). Other variables independently associated with oral antibiotic prescribing included male sex (aOR 1.88 [1.20, 2.98]), prosthetic joint infection (aOR 0.29 [0.17, 0.47]), and infection with <i>Enterobacterales</i> (aOR 2.86 [1.45, 5.92]), methicillin-sensitive <i>Staphylococcus aureus</i> [aOR 0.41 [0.26, 0.65]), or coagulase-negative staphylococci (aOR 0.34 [0.18, 0.62]).</p><p><strong>Conclusions: </strong>Implementation of a treatment guideline resulted in a significant increase in oral antibiotic prescribing. Antimicrobial stewardship programs should implement similar interventions to improve outpatient antibiotic utilization.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e84"},"PeriodicalIF":0.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951238/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A persistent sink reservoir as a potential source of <i>Pseudomonas aeruginosa</i> infections in pediatric oncology patients.","authors":"LaTasha Richards, Craig Gilliam, Jessica Brazelton, Heather L Glasgow, Randall T Hayden, Hana Hakim","doi":"10.1017/ash.2025.54","DOIUrl":"10.1017/ash.2025.54","url":null,"abstract":"<p><strong>Objective: </strong>Outbreaks of <i>Pseudomonas aeruginosa</i> infections have been linked to water-related sources. We describe the investigation of a suspected outbreak of five <i>P. aeruginosa</i> infections in pediatric oncology patients in 2021 that triggered a retrospective review and prospective monitoring of additional cases, environmental sampling, and bacterial genomic analysis.</p><p><strong>Setting and patients: </strong>Pediatric oncology center.</p><p><strong>Methods: </strong>Medical records of patients with <i>P. aeruginosa</i> were reviewed and staff were interviewed to identify common exposures. Environmental samples were cultured for <i>P. aeruginosa.</i> Patient and environmental isolates underwent whole genome sequencing and core genome multi-locus sequence typing (cgMLST) and sequences were added to a previously existing library of <i>P. aeruginosa</i> clinical isolates collected in 2017 and onwards to determine strain relatedness.</p><p><strong>Findings: </strong>During 2019-2022, 82 patients with 110 episodes of <i>P. aeruginosa</i> infections were identified and 132 isolates of <i>P. aeruginosa</i> were sequenced. Twenty-three environmental samples were collected, of which two grew <i>P. aeruginosa</i> in culture. CgMLST demonstrated four multi-patient isolate clusters but no genetic relatedness among the isolates from the patients in the suspected outbreak. Two sink-derived isolates from 2021 were genetically related to patient-derived isolates from 2018 and 2017.</p><p><strong>Conclusions: </strong>Sequencing revealed there is no common source or linkage between the isolates of the suspected <i>P. aeruginosa</i> outbreak in 2021. However, it revealed genetic relatedness of previous patient strains to later strains collected from hospital sinks, suggesting persistent colonization of a reservoir with <i>P. aeruginosa.</i></p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e82"},"PeriodicalIF":0.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three stages of laboratory stewardship in improving appropriate <i>Clostridioides difficile</i> testing in a community-based setting.","authors":"Michael S Wang, Gretchen Zimmerman, Theres Klein, Bethany Stibbe, Monica Rykse, Samuel Ballard, Naveen Vijayam, Joe Brown, Khateeb Raza, Shannon Beckman, Andrew M Skinner","doi":"10.1017/ash.2025.55","DOIUrl":"10.1017/ash.2025.55","url":null,"abstract":"<p><strong>Objective: </strong>Assess the efficacy of staged interventions aimed to reduce inappropriate <i>Clostridioides difficile</i> testing and hospital-onset <i>C. difficile</i> infection (HO-CDI) rates.</p><p><strong>Design: </strong>Interrupted time series.</p><p><strong>Setting: </strong>Community-based.</p><p><strong>Methods/interventions: </strong>National Healthcare Safety Network (NHSN) <i>C. difficile</i> metrics from January 2019 to November 2022 were analyzed after three interventions at a community-based healthcare system. Interventions included: (1) an electronic medical record (EMR) based hard stop requiring confirming ≥3 loose or liquid stools over 24 h, (2) an infectious diseases (ID) review and approval of testing >3 days of hospital admission, and (3) an infection control practitioner (ICP) reviews combined with switching to a reverse two-tiered clinical testing algorithm.</p><p><strong>Results: </strong>After all interventions, the number of <i>C. difficile</i> tests per 1,000 patient-days (PD) and HO-CDI cases per 10,000 PD decreased from 20.53 to 6.92 and 9.80 to 0.20, respectively. The EMR hard stop resulted in a (28%) reduction in the CDI testing rate (adjusted incidence rate ratio ((aIRR): 0.72; 95% confidence interval [CI], 0.53 to 0.96)) and ID review resulted in a (42%) reduction in the CDI testing rate (aIRR: 0.58; 95% CI, 0.42-0.79). Changing to the reverse testing algorithm reduced reported HO-CDI rate by (95%) (cIRR: 0.05; 95% CI; 0.01-0.40).</p><p><strong>Conclusions: </strong>Staged interventions aimed at improving diagnostic stewardship were effective in overall reducing CDI testing in a community healthcare system.</p>","PeriodicalId":72246,"journal":{"name":"Antimicrobial stewardship & healthcare epidemiology : ASHE","volume":"5 1","pages":"e81"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}