Objective To investigate the current status and development of electronic health records (EHR) at home and abroad to grasp the development trends of EHR, so as to point out the direction of the development and relevant research on EHR. Methods Based on the Web of Science citation database and the principle of bibliometrics, we analyzed the retrieved literature in aspects of publication date, language, country/region, institution, author, etc. Results A total of 1 262 eligible studies were identified. The number of articles on EHR increased rapidly from only 2 in 1995 to 218 in 2012. In terms of country/region, the United States ranked the top in all countries (763 articles, accounting for 60.46%). In terms of institution, Harvard University ranked the top (135 articles, accounting for 10.70%). In terms of journal, the Journal of the American Medical Informatics Association ranked the top (106 articles, accounting for 8.40%). In terms of authors, David W. Bates ranked the top (45 articles, accounting for 3.57%). In terms of subject type, health care sciences services and medical informatics were mainly focused on. Conclusion The research on EHR has become a global hot spot and relevant bibliometrics will contribute to the timely and correctly grasp the whole picture of its development trends and main research direction.
Objective To investigate the plasma levels of soluble Fas receptor ( sFas) , soluble Fas ligand ( sFas-L) and matrix metalloproteinase-7 ( MMP-7) and their correlation with disease severity as well as the prognosis of septic patients.Methods The plasma levels of sFas, sFas-L, sFas / sFas-L ratio and MMP-7 were measured by enzyme-linked immunosorbent assay and compared between32 patients with sepsis and 24 age and sex matched healthy controls. Based on the 28-day outcome, the patients were divided into a survival group and a death group. The difference in sFas, sFas-L, sFas/ sFas-L ratio and MMP-7 between the survival group and the death group were compared.Results Compared with the healthy control group, the concentration of plasma sFas, sFas-L and MMP-7 were significantly increased in the septic patients ( P lt; 0. 01) . Elevated plasma sFas and sFas-L were both positive correlated with the APACHEⅡ score and SOFA score. Although a modest negative correlation was found between plasma MMP-7 and APACHEⅡ score and SOFA score, but this correlation did not reach statistical significance ( P gt;0. 05) . The septic patients who died had significantly higher sFas-L level and lower sFas / sFas-L ratio as compared with those who survived ( P lt;0. 05) . Conclusion Plasma sFas, sFas-L and MMP-7 are associated with the disease severity and can serve as potential markers for predicting the outcome in septic patients.
Heart failure is a disease that seriously threatens human health and has become a global public health problem. Diagnostic and prognostic analysis of heart failure based on medical imaging and clinical data can reveal the progression of heart failure and reduce the risk of death of patients, which has important research value. The traditional analysis methods based on statistics and machine learning have some problems, such as insufficient model capability, poor accuracy due to prior dependence, and poor model adaptability. In recent years, with the development of artificial intelligence technology, deep learning has been gradually applied to clinical data analysis in the field of heart failure, showing a new perspective. This paper reviews the main progress, application methods and major achievements of deep learning in heart failure diagnosis, heart failure mortality and heart failure readmission, summarizes the existing problems and presents the prospects of related research to promote the clinical application of deep learning in heart failure clinical research.
ObjectiveTo summarize the current application status and research progress of extracellular volume (ECV) fraction based on imaging examinations in pancreatic diseases. MethodThe literature relevant to research was summarized, including the clinical studies of the ECV fraction that based on computed tomography and magnetic resonance imaging in pancreatic inflammation, neoplastic lesions, fibrosis, and other diseases. ResultsBiopsy of pancreas was technically challenging due to its unique anatomical location. The ECV fraction was the quantitative index of extracellular matrix that played a regulatory role in the process of tumor proliferation and invasion. And the production of collagen fibers and the deposition of extracellular matrix could increase the extracellular space in the progression of tissue fibrosis. Therefore, the ECV fraction obtained based on imaging examination could not only avoid invasive examination, but also reflect the status of tumor microenvironment and evaluate the degree of tissue fibrosis. The ECV fraction had the potential to serve as a novel quantitative imaging evaluation index for pancreatic diseases. ConclusionsAccording to the current research status and progress of ECV fraction in pancreatic-related diseases, ECV fraction is increasingly being utilized as a non-invasive biomarker across various pancreatic-related conditions. It holds the potential to predict tumor grading, degree of fibrosis, post-chemotherapy response, cancer patient survival, etc. Consequently, it exhibits promising prospects for clinical application research.
This article carries out a comprehensive review on otorhinolaryngologic-head and neck informatics, focusing on the definition, content and characteristics of otorhinolaryngologic informatics as well as the application of computer, communication and information technology in otorhinolaryngology-head and neck surgery. Otorhinolaryngologic informatics is the future development direction of otorhinolaryngology-head and neck surgery.
ObjectiveTo systematically review the diagnostic value of automatic breast volume scanner (ABVS) and handheld ultrasound (HHUS) for benign and malignant breast lesions.MethodsPubMed, EMbase, Web of Science, Biosis Preview, The Cochrane Library, WanFang Data, CNKI, VIP and SinoMed databases were electronically searched to collect studies on HHUS versus ABVS for benign and malignant breast lesions from inception to May 31st, 2019. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, and then, meta-analysis was performed by using Meta-Disc software.ResultsA total of 24 studies were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio for HHUS were 0.83 (95%CI 0.82 to 0.85), 0.81 (95%CI 0.79 to 0.82), 19.71 (95%CI 14.93 to 26.01), 4.05 (95%CI 3.49 to 4.69), 0.22 (95%CI 0.18 to 0.26), and for ABVS were 0.90 (95%CI 0.89 to 0.92), 0.88 (95%CI 0.87 to 0.89), 76.86(95%CI 55.13 to 107.17), 7.40 (95%CI 6.07 to 9.04), 0.11 (95%CI 0.09 to 0.14), respectively. The areas under the summary receiver operating characteristic curves in the differentiation of benign and malignant breast lesions were 0.88 and 0.96 for ABVS and HHUS, respectively.ConclusionThe current evidence shows that ABVS has higher value than HHUS in the diagnosis of benign and malignant breast tumor. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify above conclusion.