American journal of epidemiology最新文献

{"title":"The impact of statistical adjustment for assay performance on inferences from SARS-CoV-2 serological surveillance studies.","authors":"Jiacheng Chen, Yuan Yu, Sheila F O'Brien, Carmen L Charlton, Steven J Drews, Jane M Heffernan, Amber M Smith, Yu Nakagama, Yasutoshi Kido, David L Buckeridge, W Alton Russell","doi":"10.1093/aje/kwaf157","DOIUrl":"https://doi.org/10.1093/aje/kwaf157","url":null,"abstract":"<p><p>Choice of immunoassay influences population seroprevalence estimates. Post-hoc adjustments for assay performance could improve comparability of estimates across studies and enable pooled analyses. We assessed post-hoc adjustment methods using data from 2021-2023 SARS-CoV-2 serosurveillance studies in Alberta, Canada: one that tested 124,008 blood donations using Roche immunoassays (SARS-CoV-2 nucleocapsid total antibody and anti-SARS-CoV-2 S) and another that tested 214,780 patient samples using Abbott immunoassays (SARS-CoV-2 IgG and anti-SARS-CoV-2 S). Comparing datasets, seropositivity for antibodies against nucleocapsid (anti-N) diverged after May 2022 due to differential loss of sensitivity as a function of time since infection. The commonly used Rogen-Gladen adjustment did not reduce this divergence. Regression-based adjustments using the assays' semi-quantitative results produced more similar estimates of anti-N seroprevalence and rolling incidence proportion (proportion of individuals infected in recent months). Seropositivity for antibodies targeting SARS-CoV-2 spike protein was similar without adjustment, and concordance was not improved when applying an alternative, functional threshold. These findings suggest that assay performance substantially impacted population inferences from SARS-CoV-2 serosurveillance studies in the Omicron period. Unlike methods that ignore time-varying assay sensitivity, regression-based methods using the semi-quantitative assay resulted in increased concordance in estimated anti-N seropositivity and rolling incidence between cohorts using different assays.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A spatial framework for selecting sentinel sites for drug and alcohol related early warning for the United States.","authors":"Suparna Das, De Layna Goulding, Kacie Rubalcava, Kathleen Aarvig","doi":"10.1093/aje/kwaf158","DOIUrl":"https://doi.org/10.1093/aje/kwaf158","url":null,"abstract":"<p><strong>Objective: </strong>The absence of a robust early warning system in the U.S. remains a pressing issue, particularly for preventing overdose-related epidemics in vulnerable areas. This research provides a timely framework for selecting sentinel sites for drug- and alcohol-related early warning. The system, once in place, will be crucial for informing and implementing timely and effective interventions for overdose prevention. The sentinel strategy-specifically, the selection of hospital sites for the Drug Abuse Warning Network (DAWN) national overdose surveillance system-is a step toward addressing this urgent need.</p><p><strong>Data and methods: </strong>Sentinel counties were selected using a geographic framework based on a modified version of the CDC's Social Vulnerability Index (SVI), incorporating measures of overall vulnerability, drug-related mortality, and alcohol-related mortality. Principal component analysis (PCA) was applied for data reduction and composite scoring. Mortality data were obtained from the CDC WONDER Multiple Cause of Death (MCOD) database, while nonfatal overdose data came from the U.S. Department of Transportation's NHTSA opioid overdose tracker. Data on High Intensity Drug Trafficking Areas (HIDTAs) were included to assess overlap with vulnerable counties. The American Hospital Association (AHA) data on DAWN-eligible hospitals and emergency department (ED) visits were used to identify potential hospital sites within selected sentinel counties for the DAWN early warning system.</p><p><strong>Results: </strong>Principal component analysis of standardized county-level indicators revealed significant geographic disparities in overdose vulnerability. Counties in West Virginia, New Mexico, southern Texas, the Dakotas, and Alaska exhibited high social vulnerability. Drug-related mortality was highest in West Virginia, while alcohol-related mortality was elevated in New Mexico and South Dakota. Vulnerable counties overlapped with HIDTA regions in Arizona, New Mexico, Texas, Florida, South Dakota, Kentucky, and West Virginia, with additional overlap in southern California. Nonfatal overdose rates from NHTSA were also elevated in many of these counties, supporting their designation as potential sentinel counties for early warning.</p><p><strong>Conclusion: </strong>Vulnerable, high-risk counties with elevated drug- and alcohol-related mortality may be key drivers of the ongoing overdose epidemic in the U.S. These counties are geographically dispersed, underscoring the need for a targeted spatial strategy. Sentinel hospitals can be selected within these high-risk areas to detect emerging drug trends, novel substances, and evolving slang terms. This framework strengthens the application of spatial epidemiology in surveillance and offers a replicable approach for site selection in regions where resource constraints limit active surveillance.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring modifiable neighborhood risk factors for fatal opioid overdose: A case-control study in two US cities.","authors":"Elizabeth D Nesoff, Christopher Morrison, Douglas J Wiebe, Silvia S Martins","doi":"10.1093/aje/kwaf152","DOIUrl":"https://doi.org/10.1093/aje/kwaf152","url":null,"abstract":"<p><p>To explore associations between physical and social neighborhood factors and fatal opioid overdose, we remotely visited 2018-2019 fatal opioid overdose locations in New York City (n=2867) and Chicago (n=1677) via Google Street View and used a reliable and valid tool to assess 65 street block characteristics. We compared these locations to a proportional sample of blocks with no 2018-2019 overdoses (New York City n=2093; Chicago n=1148). We used logistic regression to explore associations between block characteristics and odds of an overdose event, controlling for neighborhood-level covariates (poverty, segregation). For both cities, blocks had significantly increased odds (p<0.05) of being overdose case sites if they had apartment buildings, bus stops, street trash, traffic calming features, and warning signs. New York City blocks also had significantly increased overdose odds if they had multifamily homes, commercial businesses, poor sidewalk maintenance, and loitering, and significantly decreased odds if they had single family homes, row homes, and security alarm signs. Chicago blocks with significantly increased overdose odds had vacant lots, abandoned buildings, alleys, restaurants, and adults on the street and significantly decreased odds with landscaping. Findings support neighborhood social and physical characteristics as important risk factors for fatal opioid overdose over and above sociodemographics.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing observational research on arts and health:theory-informed approaches using the RADIANCE framework.","authors":"Daisy Fancourt, Jessica K Bone","doi":"10.1093/aje/kwaf149","DOIUrl":"https://doi.org/10.1093/aje/kwaf149","url":null,"abstract":"<p><p>In the last decade, there has been increasing observational research into the impacts of arts and cultural engagement on health, drawing on the surprisingly rich phenotyping of these behaviours in observational studies. This, alongside a broader growing evidence base, has led to recent calls from the World Health Organisation for the arts to be formally recognised as a health behaviour. However, access to the arts is not equitable, so a key challenge in observational research is disentangling any causal effects from this social gradient in engagement. In this paper, we consider five of the key methodological challenges in epidemiological research on arts and health and propose solutions by combining causal inference approaches with a new theoretical framework on the determinants of arts and cultural engagement (RADIANCE), which uses a socio-ecological approach to identify multi-level factors influencing patterns of arts behaviours. We end with recommendations for researchers incorporating questions on arts and cultural engagement within the design of longitudinal cohort studies.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immortal time bias from selection: a principal stratification perspective.","authors":"Bronner P Gonçalves, Etsuji Suzuki","doi":"10.1093/aje/kwaf146","DOIUrl":"https://doi.org/10.1093/aje/kwaf146","url":null,"abstract":"<p><p>Immortal time bias due to post-treatment definition of eligibility criteria can affect experimental and observational studies, and yet, in contrast to the extensive literature on the classical form of immortal time bias, it has seldom been the focus of methodological discussions. Here, we propose an account of eligibility-related immortal time bias that uses the principal stratification framework to explain the non-comparability of treatment arms (or exposure groups) conditional on selection. In particular, we show that the statistical estimand that conditions on observed eligibility after time zero of follow-up can be interpreted using partially overlapping principal strata. Further, we show that, under this perspective, as the timing of eligibility approaches time zero of follow-up, the probabilities of the outcome for eligible individuals monotonically approach the corresponding unconditional (in absence of selection) expected potential outcomes under different treatment levels. Our study provides a potential outcomes-based explanation of eligibility-related immortal time bias, and indicates that, in addition to the target trial emulation framework, principal effects might, for some studies, be useful causal estimands.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating administrative measures of school quality as mediators of the relationship between attending a segregated school and cognitive function among older Black individuals: The STAR Study.","authors":"Sirena Gutierrez, Rachel A Whitmer, Marilyn D Thomas, Kristen M George, Rachel Peterson, Lisa L Barnes, Isabel E Allen, M Maria Glymour, Jacqueline M Torres, Paola Gilsanz","doi":"10.1093/aje/kwaf150","DOIUrl":"https://doi.org/10.1093/aje/kwaf150","url":null,"abstract":"<p><p>Research highlights school segregation's impact on cognitive aging for older Black adults, yet the mediating role of school quality-reflecting systemic (dis)investment in segregated schools-remains unexplored. This study included 726 community-dwelling Black adults from the Study of Healthy Aging in African Americans. Participants self-reported segregated school attendance, while administrative measures of state-level school quality (term length, percent attendance, student-teacher ratio, composite z-score) were linked to their grade-specific state of residence. We estimated the extent to which associations between segregated schooling and domain-specific cognition were mediated by school quality. Sensitivity analyses examined grade-specific effects. Attending a segregated school was associated with poorer school quality (e.g., βterm-length= -1.71 [-2.52,-0.91]) and lower semantic memory (β= -0.17 [-0.32,-0.02]). The school quality composite measure mediated 30% of the overall association with semantic memory (natural indirect effect: β= -0.05 [-0.09,-0.01]; direct effect: β= -0.14 [-0.30,0.02]). Total effect estimates were imprecise for executive function and verbal episodic memory. Our results suggest that state-level (dis)investments in school quality may be an important mechanism by which school-based segregation contributes to late-life cognitive function. Interventions that target the upstream, structural drivers of school-based segregation and related disinvestments may be important strategies for reducing cognitive aging inequities.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 pandemic impact on clinical condition capture in real-world data: an assessment framework.","authors":"Yehua Wang, Yanning Wang, Earl J Morris, Nicole E Smolinski, Thuy N Thai, Almut G Winterstein","doi":"10.1093/aje/kwaf153","DOIUrl":"https://doi.org/10.1093/aje/kwaf153","url":null,"abstract":"<p><p>Background The COVID-19 pandemic has impacted healthcare utilization and, consequently, real-world data. In this study, we used analytical and data visualization approaches to untangle effects on condition measurement and true shifts in the patient population seeking healthcare. Methods We used MerativeTM MarketScan® 2018-2020 commercial claims data to develop 24 monthly cohorts of patients aged ≥18 years with 12 months baseline enrollment and an encounter for diabetes, cancer, hypertension, depression, myocardial infarction (MI), atrial fibrillation (Afib), or urinary tract infections (UTI) as the index condition in a given month. We compared monthly prevalence of each condition in 2020 vs. 2019. We then imposed 3, 6, and 12-month look-back periods (LBP) to capture comorbidities grouped by Clinical Classifications Software Refined (CCSR) or summarized in the Charleson Comorbidity Index (CCI) and conducted similar 2020 versus 2019 prevalence comparisons. Results Changes in condition prevalence varied across conditions with strongest declines for cancer in April 2020 (-57.4%) and strongest increases for depression in December 2020 (+11.8%). The mean CCI was higher for most conditions during the spring of 2020 and this difference was accentuated by applying a longer LBP. Similar trends were found regarding the number of CCSR categories. Conclusion Pandemic-related changes in condition capture were complex, involving both increases and decreases in encounters for specific conditions and in comorbidities, along with variations in comorbidity capture dependent on look-back periods. We provided a practical approach to untangle these phenomena along with open-source algorithms and visualization tools to assess these changes and inform study design and analysis.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Stage Interrupted Time Series Analysis with Machine Learning: Evaluating the Health Effects of the 2018 Wildfire Smoke Event in San Francisco County as a Case Study.","authors":"Arnab K Dey, Yiqun Ma, Gabriel Carrasco-Escobar, Changwoo Han, François Rerolle, Tarik Benmarhnia","doi":"10.1093/aje/kwaf147","DOIUrl":"https://doi.org/10.1093/aje/kwaf147","url":null,"abstract":"<p><p>Randomized controlled trials (RCTs) are considered a key identification strategy for establishing causal relationships between exposures and outcomes. When evaluating the health impacts of extreme weather events, however, RCTs are generally infeasible due to ethical issues, costs, and the lack of a suitable control group. Quasi-experimental designs capitalizing on the timing of natural experiments, such as Interrupted Time Series (ITS), offer a valuable alternative to estimate causal effects when control groups are not available. This paper explores the application of a two-stage ITS framework that compares traditional autoregressive integrated moving average (ARIMA) models and two machine learning algorithms: Neural Network Autoregressive (NNETAR) and Prophet-Extreme Gradient Boosting (XGBoost). As a case study, we assess the impacts of the 2018 wildfire smoke event on respiratory hospitalizations in San Francisco County, California. We split the data into pre- and post-event periods to train and evaluate the models, perform cross-validation for hyperparameter tuning, and predict hospitalizations under the counterfactual scenario. Data and R code are provided for reproducibility. In the case study, the Prophet-XGBoost shows the best model performance and was used to generate the counterfactual trends. We estimate that the 2018 smoke event resulted in a total of 92 (95% empirical confidence interval: 24, 125) excess respiratory hospitalizations (12.5% of the observed hospitalization count during the event period). Our proposed approach offers a powerful tool for assessing the effects of extreme weather events and can be broadly applied to other epidemiological contexts, such as public health policy evaluation.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emotional and instrumental social support and older adults' depressive symptoms: Collaborative individual participant data meta-analysis of 11 population-based studies of ageing.","authors":"Suraj Samtani, Gowsaly Mahalingam, Ben C P Lam, Darren M Lipnicki, Katya Numbers, Maria Fernanda Lima-Costa, Sergio Luis Blay, Erico Castro Costa, Shifu Xiao, Steffi Reidel-Heller, Susanne Röhr, Alexander Pabst, Nikolaos Scarmeas, Mary Yannakoulia, Mary Kosmidis, Murali Krishna, Kalyanaraman Kumaran, Suzana Shahar, Tze Pin Ng, Roger Ho, Ki-Woong Kim, Ingmar Skoog, Jenna Najar, Therese Rydberg Sterner, Mary Ganguli, Chung-Chou Ho Chang, Tiffany F Hughes, Perminder S Sachdev, Henry Brodaty, For The Cohort Studies Of Memory In An International Consortium Cosmic","doi":"10.1093/aje/kwaf137","DOIUrl":"https://doi.org/10.1093/aje/kwaf137","url":null,"abstract":"<p><p>Social support is considered a protective factor against depression, but there are inconsistent findings regarding social support and depression in older adults. We aimed to clarify the association between emotional and instrumental social support and depressive symptoms in older adults cross-sectionally and longitudinally (mean follow-up = 1.96 years). We meta-analyzed raw individual participant level data from adults in mid- and late-life (N = 23,973) who completed questionnaires about physical health, mental health, and social support and completed neuropsychological assessments. These were COSMIC (Cohort Studies of Memory in an International Consortium) cohort studies carried out in Australia, Brazil, China, Germany, Greece, India, Indonesia, Singapore, South Korea, Sweden, and the United States in mostly urban settings. After controlling for depression risk factors, emotional support (B = -0.40, 95%CI: -0.60,-0.21), but not instrumental support (B = 0.17, 95%CI: -0.26,0.59), was associated with lower depressive symptoms cross-sectionally and at follow-up [emotional support (B = -0.37, 95%CI: -0.54,-0.20); instrumental support (B = 0.09, 95%CI: -0.30,0.49)]. Emotional support was associated with lower depressive scores cross-sectionally and longitudinally, while instrumental support was not associated with depressive symptoms. Our findings can help inform the nature of interventions to prevent and reduce risk of depression among older adults.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validity of diagnostic codes used to ascertain maternal injuries during pregnancy.","authors":"Asma M Ahmed, Riyan Deria, Rosalba Barojas Chavarria, Allie Sakowicz, David Stamilio, Elizabeth T Jensen","doi":"10.1093/aje/kwaf145","DOIUrl":"https://doi.org/10.1093/aje/kwaf145","url":null,"abstract":"<p><strong>Background: </strong>Previous research has relied on International Classification of Diseases (ICD) codes to define maternal injuries. However, the validity of these codes remains unclear. We aimed to validate ICD-10 codes used to ascertain maternal injuries using medical chart reviews as the gold standard.</p><p><strong>Methods: </strong>A retrospective cohort study of all births occurring at Atrium Health Wake Forest Baptist Medical Center in 2022-2023. We randomly selected 100 subjects with ICD-10-indicated injury and 100 subjects without indication of injury. Two independent reviewers, blinded to the ICD-10-based classification, conducted the chart review. We examined the validity of relevant injury-related codes (V00-Y38; S00-T79; O9A.2-O9A.4) and calculated positive predictive values (PPV) for different algorithms defined by varying the encounter type and the list of codes used.</p><p><strong>Results: </strong>The algorithm that included all injury-related ICD-10 codes without encounter type restrictions showed moderate PPV (71%, 95% confidence interval (CI): 61%-79%) and high negative predictive value (96% (90%-98%)). PPV was maximized when including codes V00-Y38 and restricting encounter type to inpatient or emergency department encounters (PPV 100% (93%-100%).</p><p><strong>Conclusions: </strong>This study characterizes the accuracy of ICD-10-based algorithms for ascertaining maternal injuries during pregnancy. These findings can help improve inference by providing bias parameters for future research.</p>","PeriodicalId":7472,"journal":{"name":"American journal of epidemiology","volume":" ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144590248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}