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  1. 641
  2. 642

    The Richness of Italian Historical Demography by Marco Breschi, Alessio Fornasin, Matteo Manfredini

    Published 2020-12-01
    Subjects: “…Longitudinal databases…”
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  3. 643

    The Richness of Italian Historical Demography by Marco Breschi, Alessio Fornasin, Matteo Manfredini

    Published 2020-12-01
    Subjects: “…Longitudinal databases…”
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    Article
  4. 644
  5. 645
  6. 646
  7. 647

    The Richness of Italian Historical Demography by Marco Breschi, Alessio Fornasin, Matteo Manfredini

    Published 2020-12-01
    Subjects: “…longitudinal databases…”
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    Article
  8. 648

    The Richness of Italian Historical Demography by Marco Breschi, Alessio Fornasin, Matteo Manfredini

    Published 2020-12-01
    Subjects: “…Longitudinal databases…”
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    Article
  9. 649
  10. 650
  11. 651

    The Richness of Italian Historical Demography by Marco Breschi, Alessio Fornasin, Matteo Manfredini

    Published 2020-12-01
    Subjects: “…Longitudinal databases…”
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    Article
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  17. 657

    A LASSO-derived clinical score to predict severe acute kidney injury in the cardiac surgery recovery unit: a large retrospective cohort study using the MIMIC database by Qi Guo, Jingjing Huang, Yuewei Li, Hongwei Li, Jingfeng Wang, Yong Xie, Tucheng Huang, Wanbing He, Wenyu Lv, Jieping Huang, Yangxin Chen

    Published 2022-06-01
    “…Objectives We aimed to develop an effective tool for predicting severe acute kidney injury (AKI) in patients admitted to the cardiac surgery recovery unit (CSRU).Design A retrospective cohort study.Setting Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database, consisting of critically ill participants between 2001 and 2012 in the USA.Participants A total of 6271 patients admitted to the CSRU were enrolled from the MIMIC-III database.Primary and secondary outcome Stages 2–3 AKI.Result As identified by least absolute shrinkage and selection operator (LASSO) and logistic regression, risk factors for AKI included age, sex, weight, respiratory rate, systolic blood pressure, diastolic blood pressure, central venous pressure, urine output, partial pressure of oxygen, sedative use, furosemide use, atrial fibrillation, congestive heart failure and left heart catheterisation, all of which were used to establish a clinical score. …”
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  18. 658

    Evaluation of disparities in hospitalisation outcomes for deaf and hard of hearing patients with COVID-19: a multistate analysis of statewide inpatient databases from Florida, Maryland, New York and Washington by Hiraku Kumamaru, Loren G Miller, Rie Sakai-Bizmark, Dennys Estevez, Emily H Marr, Jong Hyon Lee, Frank Wu

    Published 2025-01-01
    “…Objective Investigate whether deaf or hard of hearing (D/HH) patients with COVID-19 exhibited different hospitalisation outcomes compared with hearing patients with COVID-19.Design Cohort studySetting Statewide Inpatient Databases for Florida, Maryland, New York and Washington, for the year 2020.Participants Records of patients aged 18–64 years with COVID-19Primary outcomes and measures Differences in in-hospital death, 90-day readmission, length of stay, hospitalisation cost, hospitalisation cost per day, intensive care unit (ICU) or coronary care unit (CCU) utilisation and ventilation use were evaluated. …”
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  19. 659

    Hepatitis associated with immune checkpoint inhibitors-based combinations of other therapies: A real-world pharmacovigilance analysis based on the FDA adverse event reporting system (FAERS) database by Zhaohui Li, Zixiang Zhou, Nan Zhang, Binhe Tian, Xiangqi Chen, Haitao Zhao, Hanping Wang

    Published 2024-11-01
    “…Patients and methods A total of 587,016 NSCLC reports were extracted from FAERS database spanning from the first quarter of 2013 to the second quarter of 2023. …”
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  20. 660

    Comparing survival outcomes of localized tumor destruction, sublobar resection, and pulmonary lobectomy in stage IA non-small cell lung cancer: a study from the SEER database by Lin Cheng, Sheng-Wei Li, Xiao-Guang Li

    Published 2025-02-01
    “…Methods In the Surveillance, Epidemiology, and End Results (SEER) database (2000–2021), we included patients with pathologically confirmed stage IA non-small cell lung cancer who were treated with LTD, SR, or PL. …”
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