Clinical and Experimental Emergency Medicine最新文献

{"title":"Integrating the interpretable machine learning Score for Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-day mortality.","authors":"Yvonne Wong Qi Feng, Yohei Okada, Stephanie Fook-Chong, Yilin Ning, Kenneth Boon Kiat Tan, Marcus Eng Hock Ong","doi":"10.15441/ceem.25.253","DOIUrl":"10.15441/ceem.25.253","url":null,"abstract":"<p><strong>Objective: </strong>This study integrated a machine learning-based Score for Emergency Risk Prediction (SERP), developed using objective mortality endpoints, with the Patient Acuity Category Scale (PACS) and evaluated its predictive performance in clinical use.</p><p><strong>Methods: </strong>This single-center, retrospective cohort study included all emergency department (ED) patients from a large tertiary hospital between January 1, 2018, and December 31, 2019. Using a reclassification framework, SERP was incorporated into PACS to derive two enhanced triage models. PACS+ model 1 down-triaged patients with low predicted 30-day mortality risk and up-triaged those with high risk. PACS+ model 2 up-triaged only high-risk patients, whereas lowrisk patients retained their original category. Predictive performance in the test cohort was assessed using the area under the receiver operating characteristic curve (AUC) and decision curve analysis.</p><p><strong>Results: </strong>The derivation cohort included 97,188 ED visits, and the test cohort included 97,212 ED visits. In the derivation set, the mean age of the patients was 58.97±18.41 years, and 47,993 (49.4%) were female. Overall, 19.9%, 57.4%, 22.5%, and 0.2% of patients were triaged to PACS categories P1-P4, respectively. The 30-day mortality rate was 2.8% in the derivation set and 2.7% in the test cohort. For 30-day mortality prediction, PACS+ model 1 (AUC, 0.828; 95% confidence interval [CI], 0.820-0.836) and PACS+ model 2 (AUC, 0.812; 95% CI, 0.805-0.818) outperformed PACS (AUC, 0.722; 95% CI, 0.714-0.729). PACS+ model 1 consistently achieved greater net benefit across the range of clinical thresholds.</p><p><strong>Conclusion: </strong>Integrating machine learning-based SERP with PACS improved 30-day mortality prediction in ED triage.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":"292-302"},"PeriodicalIF":3.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654677/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147608214","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":"Comparison of manual palpation, 2D carotid ultrasound, and end-tidal carbon dioxide for detecting return of spontaneous circulation.","authors":"Akin Gullu, Sukru Kockan, Emre Sanci, Erdem Aydin, Ahmet Emir Sari, Asim Enes Ozbek, Huseyin Cahit Halhalli","doi":"10.15441/ceem.25.113","DOIUrl":"10.15441/ceem.25.113","url":null,"abstract":"<p><strong>Objective: </strong>Healthcare providers frequently spend excessive time attempting to identify a pulse and may have difficulty accurately confirming its presence. Point-of-care carotid artery ultrasonography has been suggested as a potential alternative to manual palpation. This study aimed to evaluate the effectiveness of manual palpation, 2D carotid ultrasonography, and rapid increases in end-tidal carbon dioxide (EtCO2) levels for determining the return of spontaneous circulation (ROSC) in patients with cardiac arrest presenting to an emergency department.</p><p><strong>Methods: </strong>This was a single-center, prospective, observational study. Nontraumatic adult patients in cardiopulmonary arrest who were brought to the emergency department were included. After cardiac arrest was identified, the following data were recorded: initial arrest rhythm, ultrasonographic and manual pulse assessments, EtCO2 levels, resuscitation duration, and post-ROSC vital signs. The team leader's judgment was used for ROSC adjudication and served as the reference standard.</p><p><strong>Results: </strong>The investigation included 88 patients who underwent a total of 642 cycles of cardiopulmonary resuscitation. The area under the curve (AUC) values for 2D carotid ultrasonography, EtCO2, and manual palpation were 0.974, 0.802, and 0.862, respectively (all P<0.001). In pairwise AUC comparisons, ultrasonography differed significantly from manual palpation (P=0.001) and EtCO2 (P<0.001), whereas manual palpation and EtCO2 did not differ significantly (P=0.167). Bedside ultrasonography for detecting a carotid pulse had a sensitivity of 93.8% and a specificity of 100%.</p><p><strong>Conclusion: </strong>These findings suggest that 2D carotid ultrasonography can be effectively used to detect a pulse in patients with cardiopulmonary arrest.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":"13 3","pages":"311-317"},"PeriodicalIF":3.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654665/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149165482","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":"Management of breakthrough cancer pain in the emergency department.","authors":"Shin Ahn","doi":"10.15441/ceem.26.308","DOIUrl":"10.15441/ceem.26.308","url":null,"abstract":"","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":"13 3","pages":"258-262"},"PeriodicalIF":3.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170153","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":"The current evidence of 'peer-led' cardiopulmonary resuscitation training: a scoping review.","authors":"Jeremy Pallas, Phillip Newton, Ginger Chu","doi":"10.15441/ceem.26.098","DOIUrl":"https://doi.org/10.15441/ceem.26.098","url":null,"abstract":"<p><strong>Objective: </strong>To explore and map existing evidence relating to peer-led cardiopulmonary resuscitation (CPR) training across any population or setting.</p><p><strong>Methods: </strong>A scoping review was conducted using Joanna Briggs Institute methodology with reporting aligned to PRISMA-ScR. MEDLINE, EMBASE, CINAHL, Scopus, and the Cochrane Library were searched for studies published to August 2025, supplemented by citation searching. Two reviewers independently screened titles, abstracts, and full texts, with disagreements resolved by a third reviewer. Data were extracted using a standardised form and summarised narratively.</p><p><strong>Results: </strong>Out of 511 unique search results, 37 studies were included. Most were conducted in schools or health professional education settings, with few focusing on the wider adult community population. Four peer-training models (horizontal, near-peer, cascade, and self-regulated) were identified. Across diverse study designs and outcome measures, peer-led training frequently achieved similar educational outcomes to professional instructor-led training. Evidence on community-level implementation and patient-centred outcomes was limited.</p><p><strong>Conclusion: </strong>Peer-led CPR training was supported by a largely heterogeneous evidence base demonstrating similar educational outcomes to traditional instruction. Research was concentrated in educational settings, with limited evaluation of community-wide implementation. Further rigorous, standardised studies are needed to clarify effectiveness, sustainability, and the role of peer-led training in expanding CPR training capacity in the broader community.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599764","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":"Artificial Intelligence-Assisted Triage in Emergency Departments: A Scoping Review of Clinical Applications, Outcomes, and Implementation Challenges.","authors":"Rohman Hikmat, Yadi Supriyadi, Farisha Noor, Roxsana Devi Tumanggor, Milya Novera, Sukardin Sukardin, Fitri Mailani","doi":"10.15441/ceem.26.283","DOIUrl":"https://doi.org/10.15441/ceem.26.283","url":null,"abstract":"<p><strong>Objective: </strong>Emergency department (ED) triage determines patient prioritization, early risk recognition, and allocation of limited resources. Artificial intelligence (AI) has been explored to support triagerelated decision-making, but the evidence remains heterogeneous. This scoping review aimed to map applications of AI-assisted triage in EDs and summarize reported outcomes, safety, equity, and implementation challenges.</p><p><strong>Methods: </strong>This scoping review followed Arksey and O'Malley's framework. Scopus, PubMed, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and manual searching were used. Original empirical studies published in English between 2015 and 2026 were included if they evaluated AI tools supporting ED triage, risk stratification, resource prediction, or patient-flow decision-making.</p><p><strong>Results: </strong>Of 1,865 records identified, 27 studies met the inclusion criteria. Included studies used machine learning, deep learning, natural language processing (NLP), artificial neural networks, interpretable machine learning, AI-informed decision-support systems, and large language models (LLMs). AI was applied to acuity classification, admission prediction, intensive care unit (ICU) admission prediction, mortality prediction, sepsis detection, waiting-time estimation, and patient-flow optimization. Conventional machine learning and NLP models generally reported promising predictive performance, particularly when structured triage variables were combined with unstructured clinical text. However, fewer studies evaluated prospective validation, workflow integration, measurable clinical and operational impact, equity, or post-deployment monitoring. Evidence on LLMs remains preliminary, with concerns about undertriage, inconsistency, hallucination, local adaptability, and the need for supervised use.</p><p><strong>Conclusion: </strong>AI-assisted triage may support ED decision-making and patient-flow management. Future implementation should prioritize supervised human-AI collaboration, prospective validation, explainability, fairness assessment, clinician training, workflow integration, and continuous monitoring.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599803","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":"A rare cause of acute hydrocephalus: postoperative cervical CSF collection.","authors":"Yusuke Miyazaki, Hiroki Takeda, Tetsuya Takahashi","doi":"10.15441/ceem.26.030","DOIUrl":"https://doi.org/10.15441/ceem.26.030","url":null,"abstract":"","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599653","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":"Pilot Evaluation of a Novel Artificial Intelligence (AI) Heart Rate Variability (HRV)-Guided Risk Stratification for Chest Pain in the Emergency Department: A Randomized Controlled Trial.","authors":"Yiteng Wang, Ruiqi Li, Yogeswary Pasupathi, Yiling Chan, Priscilla Isabel Birthylon, Stephanie Fook-Chong, Helen Zhang, Swee Han Lim, Kenneth Tan Boon Kiat, Pamela Isa Basilio-Razon","doi":"10.15441/ceem.26.035","DOIUrl":"https://doi.org/10.15441/ceem.26.035","url":null,"abstract":"<p><strong>Background: </strong>Heart rate variability (HRV) analysis powered by artificial intelligence (AI) offers a rapid, non-invasive, and objective approach for acute coronary syndrome (ACS) risk stratification in the emergency department (ED). The objective of this study was to evaluate the feasibility and impact of aiTriage™, an AI HRV-guided tool for chest pain triage, compared with standard care.</p><p><strong>Methods: </strong>In this single-blinded randomized controlled trial, 560 ED patients with suspected ACS underwent 5- minute ECG monitoring for HRV analysis, which generated a 0-100 risk score and triage recommendations (high, medium, or low risk). Patients were randomized to standard care (control) or an HRV-guided protocol (intervention). Physicians in the control group were blinded to HRV results.</p><p><strong>Results: </strong>Of 426 analysed patients (mean age 54 ± 13 years, 35% female, 16.2% prior MI), the HRV-guided protocol reduced hospital admissions (50.2% vs 61.1%; risk difference -10.9 percentage points, 95% CI: -20.1 to -1.8) and serial cardiac enzyme testing (32.1% vs 41.7%; risk difference -9.6 percentage points, 95% CI: -18.4 to -0.9) compared with standard care. Among discharged patients, the median ED length of stay was 20 minutes shorter in the intervention group (95% CI: -45 minutes to 3 minutes). The overall 30-day MACE rate was 9.5%, with no events among discharged patients.</p><p><strong>Conclusion: </strong>A rapid AI HRV-guided risk stratification tool was feasible to deploy, and has potential to reduce serial cardiac enzyme testing, ED LOS and hospital admissions. An adequately powered RCT is needed to confirm these findings and assess clinical safety. This trial is registered at ClinicalTrials.gov (NCT07074808).</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599735","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":"Impact of the Resident Physician Staffing Disruptions on Outcomes of Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Observational Study.","authors":"Dong Eun Lee, Yun Jeong Kim, Yeonjoo Cho, Jae Yun Ahn, Sungbae Moon, Jae Hyuk Lee, Dowon Lee, Jung Ho Kim, Sang-Hun Lee, Hyun Wook Ryoo","doi":"10.15441/ceem.26.081","DOIUrl":"https://doi.org/10.15441/ceem.26.081","url":null,"abstract":"<p><strong>Objective: </strong>In February 2024, following the announcement of new government healthcare policies, over 90% of resident physicians in South Korea submitted their resignations. This unprecedented staffing disruption raised concerns regarding its potential impact on the care of critically ill patients, particularly those with out-of-hospital cardiac arrest (OHCA). This study evaluated the effect of resident physician staffing disruptions on in-hospital management and outcomes of patients with OHCA.</p><p><strong>Methods: </strong>We conducted a multicenter retrospective observational study of adult patients (≥18 years) with OHCA of medical etiology in a metropolitan city during two periods: a comparison period (March 1-December 31, 2023) and a staffing disruption period (March 1-December 31, 2024). The primary outcomes were survival to hospital discharge and favorable neurologic outcome, defined as a Cerebral Performance Category score of 1-2. Multivariable logistic regression was used to assess the association between study period and outcomes.</p><p><strong>Results: </strong>A total of 1,516 patients were included (736 in the comparison period and 780 in the staffing disruption period). Baseline characteristics and rates of in-hospital interventions, including percutaneous coronary intervention, targeted temperature management, and extracorporeal membrane oxygenation, were similar between groups. The adjusted odds ratios for favorable neurologic outcome and survival to discharge during the staffing disruption period were 1.05 (95% CI, 0.64-1.74) and 1.26 (95% CI, 0.85-1.88), respectively.</p><p><strong>Conclusion: </strong>Short-term outcomes of patients with OHCA were not significantly affected by resident physician staffing disruptions. These findings suggest that emergency care for OHCA may have been preserved during the observed period.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599740","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":"Lactate-to-Albumin Ratio for Predicting Post-Contrast Acute Kidney Injury After Contrast-Enhanced CT in the Emergency Department.","authors":"Mehmet Yortanlı, Betül Çiğdem Yortanlı, Ekrem Taha Sert, Kamil Kokulu","doi":"10.15441/ceem.26.099","DOIUrl":"https://doi.org/10.15441/ceem.26.099","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the association between the lactate-to-albumin ratio (LAR) and the development of post-contrast acute kidney injury (PC-AKI) in patients undergoing intravenous contrast-enhanced computed tomography (CT) in the emergency department (ED), and to compare its discriminative performance with other biomarker ratios.</p><p><strong>Methods: </strong>This retrospective observational study included adult patients who underwent contrastenhanced CT in a tertiary ED between January 2022 and January 2025. Patients with available baseline and 48-72-hour post-contrast serum creatinine measurements were analyzed. LAR, blood urea nitrogen-to-albumin ratio (BAR), C-reactive protein-to-albumin ratio (CAR), and neutrophil-tolymphocyte ratio (NLR) were calculated using laboratory values obtained at ED presentation. Logistic regression analyses were performed, and receiver operating characteristic curves were constructed.</p><p><strong>Results: </strong>A total of 695 patients were included, and PC-AKI occurred in 43 (6.2%). Patients with PCAKI were older and had higher hemoglobin, creatinine, blood urea nitrogen, C-reactive protein, and lactate levels, as well as lower albumin and estimated glomerular filtration rate values (all p<0.05). LAR, BAR, CAR, and NLR differed between groups. In multivariable analysis, LAR (OR=3.898; 95% CI: 2.799-5.430; p<0.001), BAR (OR=1.635; 95% CI: 1.171-2.283; p=0.004), and NLR (OR=1.820; 95% CI: 1.359-2.438; p<0.001) were associated with PC-AKI. LAR showed an area under the curve of 0.854, with a sensitivity of 88.4% and a negative predictive value of 98.9% at a cut-off of >0.51.</p><p><strong>Conclusion: </strong>LAR measured at ED presentation was associated with the development of PC-AKI following contrast-enhanced CT and demonstrated higher discriminative performance compared with other evaluated ratios. These findings suggest that LAR may be useful for risk stratification in this clinical context.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599773","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":"Association between bystander type and successful bystander-delivered shocks in urban Tokyo, Japan.","authors":"Minami Torai, Kasumi Shirasaki, Tasuku Hada, Katsuhiro Horie, Yu Watanabe, Nozomi Toya, Shutaro Isokawa, Yohei Okada, Norio Otani","doi":"10.15441/ceem.26.119","DOIUrl":"https://doi.org/10.15441/ceem.26.119","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the association between bystander type and successful bystanderdelivered shocks among out-of-hospital cardiac arrest (OHCA) patients with an initial shockable rhythm.</p><p><strong>Methods: </strong>This single-center, retrospective observational study included non-traumatic adult OHCA patients with witnessed and an initial shockable rhythm who were transported to our hospital between April 2013 and June 2024. The term \"successful bystander-delivered shocks\" was defined as use of an automated external defibrillator by a bystander before emergency medical services arrival. Bystanders were categorized as family members, lay bystanders, on-duty staff, or healthcare professionals. On-duty staff were defined as persons working at the scene at the time of OHCA, and lay bystanders as non-staff passers-by . The primary outcome was successful bystander-delivered shocks . Multivariable logistic regression analyses were performed.</p><p><strong>Results: </strong>285 patients were included. Median age was 59 [49-69] years, 254 (89.1%) were male, and 184 (64.6%) received bystander-initiated cardiopulmonary resuscitation. The bystander was a family member in 54 cases, a lay bystander in 79 cases, on-duty staff in 131 cases, and a healthcare professional in 21 cases. Successful bystander-delivered shocks differed markedly by bystander type: 3.7% among family members, 36.7% among lay bystanders, 59.5% among on-duty staff, and 76.2% among healthcare professionals. In multivariable logistic regression, the adjusted odds ratios for successful bystander-delivered shocks by bystander type were on-duty staff, 2.29 [1.26-4.17]; healthcare professionals, 6.26 [1.96-19.9]; and family members, 0.08 [0.02-0.36], compared with lay bystanders.</p><p><strong>Conclusion: </strong>OHCA patients for whom the rescuing bystander was on-duty staff or a healthcare professional were significantly more likely to receive successful bystanderdelivered automated external defibrillator shocks than those rescued by lay bystanders.</p>","PeriodicalId":10325,"journal":{"name":"Clinical and Experimental Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148599723","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}