Infection Control and Hospital Epidemiology最新文献

{"title":"Development and implementation of a quality improvement framework for the prevention hospital-onset bacteremia and fungemia.","authors":"Gregory Schrank, Surbhi Leekha, Mya Brady, Amber Thomas, Ayda Soltanian Tiranchi, Gwen Robinson, Elise Martin, Graham Snyder","doi":"10.1017/ice.2026.10455","DOIUrl":"https://doi.org/10.1017/ice.2026.10455","url":null,"abstract":"<p><strong>Objective: </strong>Develop and implement a framework for reviewing hospital-onset bacteremia and fungemia (HOB) events to identify quality improvement opportunities.</p><p><strong>Design: </strong>Prospective, observational study.</p><p><strong>Setting: </strong>Six hospitals (3 academic and 3 community) associated with two health systems.</p><p><strong>Participants: </strong>Clinical team members involved in the care of patients with eligible HOB events.</p><p><strong>Methods: </strong>The Joint Commission Patient Safety Event Taxonomy was adapted to develop a framework for HOB, eliciting potential contributing factors in four categories: general infection prevention, infection-site-specific, system, and human factors. From 9/2022 to 4/2024, HOB events identified from hospital blood culture databases were selected using convenience sampling to a target enrollment of 75 events, limiting inclusion of events associated with neutropenia or central line infections. Multidisciplinary case reviews were performed, and the framework was refined using feedback from the first 17 reviews. We summarized HOB sources, contributing factors, and improvement opportunities using descriptive analyses.</p><p><strong>Results: </strong>Seventy-four HOB case reviews were analyzed, evenly distributed between academic and community hospitals, and 42% occurred in an ICU setting. A median of 3 care team members (IQR 2-4) participated in each review. At least one infection-site-specific factor was identified in 48% of case reviews, representing 63% of HOB events with a known source of infection. 50% of cases identified a general infection prevention factor, 35% a system factor, and 34% a human factor. 57% of the cases had an actionable finding.</p><p><strong>Conclusions: </strong>HOB events have diverse causes and elements of preventability, and multidisciplinary review can generate actionable findings beyond the current guideline-defined measures.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-8"},"PeriodicalIF":2.9,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative artificial intelligence for surgical site infection surveillance.","authors":"Shatha Alshanqeeti, Aileen de Guzman, Mary K Riley, K C Coffey, Kathrine E Goodman, Anthony D Harris, Jonathan Baghdadi, Lisa Pineles, Westyn Branch-Elliman, Daniel J Morgan","doi":"10.1017/ice.2026.10429","DOIUrl":"https://doi.org/10.1017/ice.2026.10429","url":null,"abstract":"<p><strong>Background: </strong>Surgical site infection (SSI) surveillance can be time consuming and resource intensive. This study investigates the potential of generative artificial intelligence (GenAI) to augment the detection and classification of SSIs.</p><p><strong>Methods: </strong>A case control study of patients with SSI following spine surgery at one US hospital. SSIs were classified into superficial, deep, and organ space. All SSIs were confirmed by infection prevention (IP) experts as they occurred from October, 2023 to September, 2025 and matched 1:1 by year to surgeries deemed non-SSI. A secure GenAI was used to determine if patients had an SSI based on standardized prompts and clinical data. IP nurses used GenAI output to review cases with the ability to ask GenAI questions within the data provided or independently open the medical record. We compared GenAI determinations to initial IP nurses' determinations.</p><p><strong>Results: </strong>A total of 555 patients had spine surgeries. All 16 SSIs were matched by year to 16 non-SSI. All SSIs were correctly identified by GenAI (sensitivity 100%, 16/16) and only 1 non-SSI was incorrectly identified as SSI (specificity 93.7%, 15/16). Although GenAI accurately identified all SSI cases, it was discordant with original review at classifying the level of infection in 37.5% (6/16) of cases. Upon final IP physician review, GenAI was correct in 66.7% (4/6) of discordant cases (often determining \"organ space infections\" rather than \"deep\"). Median time to complete GenAI assisted SSI reviews was 9 minutes (IQR 7-21).</p><p><strong>Conclusion: </strong>GenAI is a promising tool to assist in SSI surveillance following spinal surgery that could improve efficiency.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-4"},"PeriodicalIF":2.9,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can machine learning support infection control measures by predicting carbapenemase-producing Enterobacterales colonization at admission?","authors":"Shuk-Ching Wong, Edwin Kwan-Yeung Chiu, Jonathan Daniel Ip, Simon Yung-Chun So, Kelvin Hei-Yeung Chiu, Edmond Siu-Keung Ma, Kwok-Yung Yuen, Vincent Chi-Chung Cheng","doi":"10.1017/ice.2026.10440","DOIUrl":"https://doi.org/10.1017/ice.2026.10440","url":null,"abstract":"<p><strong>Background: </strong>Early identification of patients with carbapenemase-producing Enterobacterales (CPE) colonization is crucial for infection control; however, microbiological testing may delay detection and be costly. Machine learning may enhance predictive analytics for timely identification of at-risk patients.</p><p><strong>Methods: </strong>Four machine learning models: Decision Tree, Random Forest, Gradient Boosting, and XGBoost, were used to predict CPE colonization within 48 hours of admission using microbiological and demographic data. Model performance was assessed through sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Uniform Manifold Approximation and Projection (UMAP) evaluated topological separability of CPE-positive cases and CPE-negative controls.</p><p><strong>Results: </strong>From January 1, 2015 to December 31, 2024, 453,372 fecal specimens were submitted for CPE screening, with 194,917 (43.0%) collected within 48 hours of admission, comprising 3,328 CPE-positive cases (1.7%) and 191,589 CPE-negative controls. The Gradient Boosting classifier showed the best performance, achieving an AUROC of 0.598, sensitivity of 54.4%, and specificity of 59.1%. Demographic factors (age ≥ 75 and male sex), history of hospitalization, and known CPE colonization in the past year, and admission specialty (general medicine and general surgery) were consistently included in all models as top predictors. UMAP revealed significant overlap between CPE-positive and CPE-negative patients, indicating challenges in differentiating the risk profiles.</p><p><strong>Conclusions: </strong>This study highlights the complexities of using machine learning to predict CPE colonization within 48 hours of admission. The low AUROC values suggest that the models may not effectively predict CPE colonization at the patient level, potentially due to inherent rarity of events and overlapping risk profiles.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-10"},"PeriodicalIF":2.9,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation and assessment of a postreprocessing endoscope surveillance program at the University of Kentucky, 2019-2024.","authors":"Court Desmond, Faith Fursman, Derek Forster, Julie A Ribes, Sandra L Mills, Kimberly Blanton, Kevin Hatton, Rachel Howard, David Olafsson, Sean McTigue, Nicholas Van Sickels, Sherese Hinton, Deborah R Flomenhoft, Takaaki Kobayashi","doi":"10.1017/ice.2026.10449","DOIUrl":"https://doi.org/10.1017/ice.2026.10449","url":null,"abstract":"<p><p>We evaluated an endoscope surveillance culture program at a tertiary academic center from 2019-2024. Postreprocessing culture positivity was highest for esophagogastroduodenoscopy (25.9%). Carbapenem-resistant organism matches between endoscope and patient isolates occurred in 5% of positive cultures.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":2.9,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147672911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of a large language model integrated within the electronic medical record for the evaluation of surgical site infections - Northern California, 2025.","authors":"Eugenia Miranti, Timothy Keyes, Alvaro Ayala, Nerissa Ambers, Gina Newman, Elmer de Leon, Erika Paola Viana-Cardenas, Wajeeha Tariq, Mindy Sampson, Jorge L Salinas","doi":"10.1017/ice.2026.10432","DOIUrl":"https://doi.org/10.1017/ice.2026.10432","url":null,"abstract":"<p><p>Our study evaluated a large language model (gpt-4o-mini) for surgical site infection (SSI) adjudication, achieving 100% sensitivity but 69.4% specificity. While reducing the manual screening workload by 66%, the agent generated many false positives, underscoring the need for refined models to improve specificity without compromising accuracy.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-3"},"PeriodicalIF":2.9,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147672860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthcare-associated <i>Pneumocystis jirovecii</i> transmission in the era of universal masking and distancing.","authors":"Florence Durocher, Simon Frédéric Dufresne, Philippe Jean Dufresne, Xavier Marchand-Senécal","doi":"10.1017/ice.2026.10446","DOIUrl":"https://doi.org/10.1017/ice.2026.10446","url":null,"abstract":"<p><strong>Objective: </strong><i>Pneumocystis jirovecii</i> pneumonia is a serious opportunistic infection in immunocompromised individuals. Despite recognized person-to-person transmission and healthcare-associated outbreaks, optimal infection control strategies remain unclear. The COVID-19 pandemic led to the implementation of universal masking and physical distancing in hospitals, providing a unique setting to observe <i>P. jirovecii</i> transmission under stringent \"droplet precaution\"-like conditions. This study investigated healthcare-associated <i>P. jirovecii</i> transmission between June 2020 and November 2021.</p><p><strong>Design: </strong>Retrospective cohort study.</p><p><strong>Setting: </strong>One tertiary-care hospital in Montréal, QC, Canada.</p><p><strong>Patients: </strong>All patients with <i>P. jirovecii</i> pneumonia at our institution during that period.</p><p><strong>Methods: </strong>Cases were identified via laboratory data and chart review. <i>P. jirovecii</i>-positive samples underwent genotyping using multilocus sequence typing. A transmission map was constructed based on shared genotypes and spatiotemporal overlap of hospital visits within a defined window of potential exposure.</p><p><strong>Results: </strong>Twenty-eight <i>P. jirovecii</i> pneumonia cases were identified. Genotyping succeeded at providing a distinct sequence type (ST) in 21 cases, revealing 7 patients with shared genotypes (3 with ST52, 2 with STX7, 2 with ST19). The transmission map of 12 patients with shared or unknown genotypes revealed 34 same-day and 34 within-one-day contacts, exclusively within outpatient clinics and imaging facilities. Three spatiotemporal clusters of plausible healthcare-associated transmission were identified despite universal masking.</p><p><strong>Conclusion: </strong>The occurrence of plausible healthcare-associated <i>P. jirovecii</i> transmission despite stringent universal masking suggests that traditional \"droplet precautions\" alone may be insufficient to prevent spread, supporting airborne transmission. Infection prevention strategies may need to be expanded in high-risk settings and should account for airborne transmission.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-6"},"PeriodicalIF":2.9,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147672899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latent tuberculosis infection screening and treatment outcomes in healthcare workers in Irish hospitals: a multi-centre cohort study.","authors":"Melva Tan, Zainab Albaggal, Ciara Anderson, Daragh McGee, Cian Carey, Aoife Hehir, Dominick P Natin, Maria Lenehan, Brian McCullagh, Lorraine Dolan, Eleanor Cronin, Noirin Noonan, Michelle Coleman, Anne Marie McLaughlin, Eileen Sykes, John Gallagher, Sarah O'Beirne, Deborah Moriarty, Grant Jeffrey, Eoin Feeney, Colm Bergin, Catherine Fleming, Arthur Jackson, Joseph Keane, Carlos Mejia-Chew, Liam Townsend","doi":"10.1017/ice.2026.10439","DOIUrl":"https://doi.org/10.1017/ice.2026.10439","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate factors associated with positive LTBI screening among HCWs and predictors of treatment initiation and completion across hospital sites in Ireland.</p><p><strong>Design: </strong>Multicentre retrospective cohort study.</p><p><strong>Setting: </strong>Five hospital sites in Ireland.</p><p><strong>Participants: </strong>N = 755 healthcare workers (HCWs).</p><p><strong>Methods: </strong>Evaluation of latent tuberculosis infection (LTBI) by interferon gamma release assay in HCWs from high-incidence countries during 2023, identified via occupational health records. IGRA positivity rates, linkage to treatment and treatment outcomes were recorded. Demographic and occupational factors associated with these outcomes were investigated.</p><p><strong>Results: </strong>There were n = 755 HCWs from high-incidence TB countries identified via occupational health records eligible for LTBI screening. 719 underwent IGRA testing, of whom 93 (13%) were positive. Age > 50 was associated with IGRA positivity (OR 5.71; 95% CI 1.79-18.17; <i>P</i> = .003). In addition to these n = 93 HCWs, two additional sites provided treatment outcomes for n = 164 HCWs, and a further n = 58 IGRA-positive HCWs were referred to Site 1. Among these 313 IGRA-positive HCWs, 50% initiated therapy, with substantial variation across sites (27%-88%). Multivariable analysis showed study site, but not demographic factors, predicted treatment initiation (<i>P</i> < .001). Common reasons for non-initiation included treatment refusal and non-attendance. Treatment completion was high (82%) and was not associated with study site.</p><p><strong>Conclusions: </strong>LTBI prevalence among HCWs in Ireland was lower than international estimates. While treatment initiation was low, completion was high. Treatment initiation varied by site, driven by institutional rather than individual factors. A standardised national programmatic approach is needed for HCWs within the LTBI cascade of care.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-8"},"PeriodicalIF":2.9,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147672924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of positive donor blood cultures on solid organ transplant recipient outcomes.","authors":"Edith Ford, Cassandra Votruba, Christopher Saling, Holenarasipur Vikram, Dan Ilges","doi":"10.1017/ice.2026.10454","DOIUrl":"https://doi.org/10.1017/ice.2026.10454","url":null,"abstract":"<p><strong>Objective: </strong>To define the incidence of donor-derived infection (DDI) in recipients of solid organ transplant (SOT) from donors with positive blood cultures and to assess the impact of shorter versus longer duration of targeted preemptive antibiotic therapy (PAT).</p><p><strong>Design: </strong>Retrospective, single-center, cohort study.</p><p><strong>Setting: </strong>Mayo Clinic Arizona.</p><p><strong>Patients: </strong>Recipients transplanted between 1/1/2019 and 7/1/2024 who received an organ from a donor with positive blood cultures.</p><p><strong>Methods: </strong>The primary outcome was incidence of DDI. Secondary outcomes included duration of PAT and incidence of donor blood culture contamination.</p><p><strong>Results: </strong>Among 199 SOT recipients from 167 unique donors with positive blood cultures, two recipients developed confirmed DDI within 30 days of SOT. Both cases were gram negative bacillary bacteremia not treated in donors and occurred immediately posttransplant prior to adequate recipient PAT. Six-month graft survival and recipient survival were 96.5% and 97.5% respectively. 139 recipients (69.8%) received PAT for a median duration of 7 days. There was no difference in rate of infections between recipients provided with ≤7 days versus 8-14 days of PAT for donor blood cultures; however, recipients who received 8-14 days had more <i>Clostridioides difficile</i> infections (CDIs) within 60 days of SOT (7.7% vs 1.5% ≤ 7 days, <i>P</i> = .040) and were more often discharged on intravenous antibiotics (32.3% vs 11.3%, <i>P</i> < .001).</p><p><strong>Conclusion: </strong>We observed a low rate of DDI following receipt of organs from donors with positive blood cultures. DDI occurred in cases without adequate donor/recipient treatment. Longer durations of targeted PAT resulted in more CDI and intravenous antibiotics on discharge.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-6"},"PeriodicalIF":2.9,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147645145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential for misclassification of community-acquired respiratory virus infections as healthcare-associated respiratory virus infections at a pediatric healthcare system.","authors":"Zachary M Most, Trish M Perl, Michael Sebert","doi":"10.1017/ice.2026.10450","DOIUrl":"https://doi.org/10.1017/ice.2026.10450","url":null,"abstract":"<p><p>During a period of universal admission respiratory virus testing, many events (5%-14%) that might have been classified as healthcare-associated respiratory viral infections (HARVI) during routine operations were found to be community-acquired. These findings emphasize unique challenges for HARVI surveillance and the impact that testing strategies have on reported rates.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-4"},"PeriodicalIF":2.9,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147645129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort.","authors":"Anna Caterina Leucci, Elena Sasdelli, Luana Caselli, Elisa Fabbri, Elena Berti, Costanza Vicentini, Carla Maria Zotti, Katrien Latour, Enrico Ricchizzi","doi":"10.1017/ice.2026.10413","DOIUrl":"https://doi.org/10.1017/ice.2026.10413","url":null,"abstract":"<p><strong>Objectives: </strong>To estimate the incidence of healthcare-associated infections (HAIs) in Italian long-term care facilities (LTCFs) and to evaluate whether an artificial intelligence (AI) approach, through unsupervised machine learning (ML), could stratify residents into clinically distinct groups with differing susceptibility to HAIs.</p><p><strong>Design: </strong>Prospective cohort study with 12-month follow-up.</p><p><strong>Setting: </strong>24 LTCFs in Italy, participating in the European Centre for Disease Prevention and Control 12-month longitudinal study on HAIs in LTCFs, 2022-2023.</p><p><strong>Participants: </strong>395 residents enrolled across the participating LTCFs.</p><p><strong>Methods: </strong>Incidence measures of HAIs (rate and ratio) were estimated, using generalized estimating equations. A hierarchical cluster analysis based on residents' clinical and demographic characteristics was implemented as an unsupervised ML approach.</p><p><strong>Results: </strong>Overall, 75 HAIs per 100 residents (95% CI, 70.3-78.3) and 0.23 HAIs per 1,000 resident-days (95% CI, 0.11-0.76) were estimated. Respiratory tract infections (29.5%, 95% CI 24.2-31.1), COVID-19 (26.3%, 95% CI 22.1-28.4), and urinary tract infections (15%, 95% CI 11.0-35.4) were the most frequent. Clustering identified two reproducible resident groups: Group 1 (39%), more independent and cognitively preserved, with fewer comorbidities and lower infection incidence; and Group 2 (61%), more dependent and clinically complex, with higher incidence of HAIs. Cluster stability was high (mean ARI = 0.83).</p><p><strong>Conclusions: </strong>This study confirms the high burden of HAIs in Italian LTCFs and provides exploratory evidence that AI-based clustering can identify reproducible HAI susceptibility profiles in a setting where such approaches have been scarcely applied.</p>","PeriodicalId":13663,"journal":{"name":"Infection Control and Hospital Epidemiology","volume":" ","pages":"1-8"},"PeriodicalIF":2.9,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147633309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}