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Diagnostic accuracy of endoscopic ultrasound in pancreatic neuroendocrine tumors: A systematic review and meta analysis

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World Journal of Gastroenterology 2013年第23期19卷 3678-3684页

作者： Srinivas r Puli Nikhil Kalva Matthew L Bechtold smitha r pamulaparthy Micheal D Cashman Norman C Estes richard H Pearl Fritz-Henry Volmar Sonu Dillon Michael F Shekleton David Forcione Division of Gastroenterology and Hepatology University of Illinois Peoria Campus OSF Saint Francis Medical CenterPeoria IL 61637 United States Department of Internal Medicine University of Illinois Peoria Campus OSF Saint Francis Medical CenterPeoria IL 61637 United States Division of Gastroenterology and Hepatology University of Missouri-ColumbiaColumbia MS 65212 United States Department of Surgery University of Illinois Peoria Campus OSF Saint Francis Medical CenterPeoria IL 61637 United States Interventional Endoscopy Services Gastrointestinal Unit Massachusetts General Hospital Harvard Medical SchoolBoston MA 02114 United States

AIM: To detect pancreatic neuroendocrine tumors (PNETs) has been varied. This study is undertaken to evaluate the accuracy of endoscopic ultrasound (EUS) in detecting ***: Only EUS studies confirmed by surgery or appropriate follow-up were selected. Articles were searched in Medline, Ovid journals, Medline nonindexed citations, and Cochrane Central register of Controlled Trials and Database of Systematic reviews. Pooling was conducted by both fixed and random effects model). rESULTS: Initial search identified 2610 reference articles, of these 140 relevant articles were selected and reviewed. Data was extracted from 13 studies (n = 456) which met the inclusion criteria. Pooled sensitivity of EUS in detecting a PNETs was 87.2% (95%CI: 82.2-91.2). EUS had a pooled specificity of 98.0% (95%CI: 94.3-99.6). The positive likelihood ratio of EUS was 11.1 (95%CI: 5.34-22.8) and negative likelihood ratio was 0.17 (95%CI: 0.13-0.24). The diagnostic odds ratio, the odds of having anatomic PNETs in positive as compared to negative EUS studies was 94.7 (95%CI: 37.9-236.1). Begg-Mazumdar bias indicator for publication bias gave a Kendall's tau value of 0.31 (P = 0.16), indication no publication bias. The P for χ2 heterogeneity for all the pooled accuracy estimates was > 0.10. CONCLUSION: EUS has excellent sensitivity and specificity to detect PNETs. EUS should be strongly considered for evaluation of PNETs.

关键词： Endoscopic ultrasound Ultrasound Endosonography Pancreatic mass Neuroendocrine tumors Sensitivity Specificity Positive predictive value Negative predictive value

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Hi-Z fault location identification on low voltage distribution systems using IoT-based digital twin model computation

Digital Twins and Applications

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Digital Twins and Applications 2024年第1期1卷 93-102页

作者： Balakrishna pamulaparthy Department of Electrical Engineering Indian Institute of Technology Madras(IITM)ChennaiIndia GE Grid Automation CoE Hyderabad Technology CenterHyderabadIndia

Distribution feeders carry and supply power to industrial,commercial and residential loads from the point where sub-transmission(33 kV level)ends after stepping down to suitable voltages,such as 11 kV and further down to 400/230 *** recent times,high impedance(Hi-Z)faults on distribution systems are creating unique challenges to utilities both from operational and safety *** of these Hi-Z faults occur at dis-tribution voltages of 15 kV or below,with the problem being worse at lower ***-Z fault detection technologies emerged and were developed and incorporated on embedded platforms,such as relays,reclosers and sensors,which protect and monitor distribution *** these technologies can detect Hi-Z fault on feeders,most of them cannot identify the exact location of the ***,there is no solution available in literature for detecting Hi-Z fault location on low voltage(LV)circuits like 3-phase 4-wire 400 V distribution *** this paper,we introduce a novel and a unique algorithm to identify the location of Hi-Z faults using proposed smart metres IoT data-based distribution system load flow and digital twin model representation of the ***,a case study on the standard 33 bus LV system clearly depicts the func-tionality of the proposed algorithm.

关键词： AMI digital distribution feeder GIS Hi‐Z fault identification IoT location sensor system twin

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