Medical device active surveillance of spontaneous reports: A literature review of signal detection methods

2020 ◽  
Vol 29 (4) ◽  
pp. 369-379
Author(s):  
Gary Chung ◽  
Katherine Etter ◽  
Andrew Yoo
Keyword(s):  
Literature Review ◽  
Signal Detection ◽  
Medical Device ◽  
Active Surveillance ◽  
Detection Methods ◽  
Spontaneous Reports

scholarly journals Application of Association Rules Analysis in Mining Adverse Drug Reaction Signals

2021 ◽  
Vol 11 (22) ◽  
pp. 10828
Author(s):  
Jianxiang Wei ◽  
Jimin Dai ◽  
Yingya Zhao ◽  
Pu Han ◽  
Yunxia Zhu ◽  
...  
Keyword(s):  
Data Mining ◽  
Signal Detection ◽  
Association Rules ◽  
Public Health Problem ◽  
Detection Methods ◽  
Drug Risk ◽  
Spontaneous Reports ◽  
Optimal Thresholds ◽  
Data Source ◽  
Association Rules Analysis

Adverse drug reactions (ADRs) are increasingly becoming a serious public health problem. Spontaneous reporting systems (SRSs) are an important way for many countries to monitor ADRs produced in the clinical use of drugs, and they are the main data source for ADR signal detection. The traditional signal detection methods are based on disproportionality analysis (DPA) and lack the application of data mining technology. In this paper, we selected the spontaneous reports from 2011 to 2018 in Jiangsu Province of China as the research data and used association rules analysis (ARA) to mine signals. We defined some important metrics of the ARA according to the two-dimensional contingency table of ADRs, such as Confidence and Lift, and constructed performance evaluation indicators such as Precision, Recall, and F1 as objective standards. We used experimental methods based on data to objectively determine the optimal thresholds of the corresponding metrics, which, in the best case, are Confidence = 0.007 and Lift = 1. We obtained the average performance of the method through 10-fold cross-validation. The experimental results showed that F1 increased from 31.43% in the MHRA method to 40.38% in the ARA method; this was a significant improvement. To reduce drug risk and provide decision making for drug safety, more data mining methods need to be introduced and applied to ADR signal detection.

scholarly journals Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis (Preprint)

2018 ◽  
Author(s):  
Marie-Laure Kürzinger ◽  
Stéphane Schück ◽  
Nathalie Texier ◽  
Redhouane Abdellaoui ◽  
Carole Faviez ◽  
...  
Keyword(s):  
Signal Detection ◽  
Predictive Value ◽  
Empirical Bayes ◽  
Geometric Mean ◽  
Area Under The Curve ◽  
Detection Methods ◽  
Operating Characteristics ◽  
Web Based ◽  
Spontaneous Reports ◽  
Reporting Systems

BACKGROUND While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate reporting (SDRs). OBJECTIVE This study aimed (1) to assess the consistency of SDRs detected from patients’ medical forums in France compared with those detected from the traditional reporting systems and (2) to assess the ability of SDRs in identifying earlier than the traditional reporting systems. METHODS Messages posted on patients’ forums between 2005 and 2015 were used. We retained 8 disproportionality definitions. Comparison of SDRs from the forums with SDRs detected in VigiBase was done by describing the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, receiver operating characteristics curve, and the area under the curve (AUC). The time difference in months between the detection dates of SDRs from the forums and VigiBase was provided. RESULTS The comparison analysis showed that the sensitivity ranged from 29% to 50.6%, the specificity from 86.1% to 95.5%, the PPV from 51.2% to 75.4%, the NPV from 68.5% to 91.6%, and the accuracy from 68% to 87.7%. The AUC reached 0.85 when using the metric empirical Bayes geometric mean. Up to 38% (12/32) of the SDRs were detected earlier in the forums than that in VigiBase. CONCLUSIONS The specificity, PPV, and NPV were high. The overall performance was good, showing that data from medical forums may be a valuable source for signal detection. In total, up to 38% (12/32) of the SDRs could have been detected earlier, thus, ensuring the increased safety of patients. Further enhancements are needed to investigate the reliability and validation of patients’ medical forums worldwide, the extension of this analysis to all possible drugs or at least to a wider selection of drugs, as well as to further assess performance against established signals.

scholarly journals One size does not fit all: a summary of signal detection methods

2021 ◽  
Vol 2 (3) ◽  
pp. 4-6
Author(s):  
Dr. Rajrajeshwari R. Patil ◽  
Dr. Vivek Singh
Keyword(s):  
Adverse Events ◽  
Signal Detection ◽  
Health Care Professionals ◽  
Quantitative Methods ◽  
Detection Methods ◽  
Universal Method ◽  
Spontaneous Reports ◽  
Safety Alert ◽  
The Right ◽  
Safety Signals

The selection of an appropriate signal detection method is pivotal in the identification process of safety signals in pharmacovigilance. Nevertheless, the early detection of safety signals is even more important to prevent the occurrence of another thalidomide tragedy in humans. Spontaneous reports, follow-up studies, scientific literature, preclinical & clinical studies, are valuable sources of adverse events; but on the other hand, these reported adverse events are extremely diverse, hence comprehending this can result in formulating the right signal detection and evaluation strategies. Broadly, signal detection methods fall into two categories: qualitative and quantitative, each having its significance; while the quantitative methods help to handle the voluminous data during signal detection, the qualitative one does its part to pick the rare signals. Hence, there is no single universal method that would be a perfect fit to identify safety signals from all data sources or for all types of adverse events. Further, the signal detection process involves a series of steps right from signal detection to its final assessment & submission, to regulatory authorities confirming a signal as a 'possible safety alert'. Finally, the completed task of finding a confirmed safety alert would be meaningless if it does not reach the end-users of the drug concerned. Therefore, effective communication to health care professionals, patients including clinical trial subjects, pharmaceutical companies, and other stakeholders is equally important.

scholarly journals Early Detection Methods for Silicosis in Australia and Internationally: A Review of the Literature

2021 ◽  
Vol 18 (15) ◽  
pp. 8123
Author(s):  
Emma K. Austin ◽  
Carole James ◽  
John Tessier
Keyword(s):  
Early Detection ◽  
Literature Review ◽  
Detection Method ◽  
Detection Methods ◽  
X Rays ◽  
Review Of The Literature ◽  
Occupational Lung Disease ◽  
Work Related ◽  
Growing Body ◽  
Future Work

Pneumoconiosis, or occupational lung disease, is one of the world’s most prevalent work-related diseases. Silicosis, a type of pneumoconiosis, is caused by inhaling respirable crystalline silica (RCS) dust. Although silicosis can be fatal, it is completely preventable. Hundreds of thousands of workers globally are at risk of being exposed to RCS at the workplace from various activities in many industries. Currently, in Australia and internationally, there are a range of methods used for the respiratory surveillance of workers exposed to RCS. These methods include health and exposure questionnaires, spirometry, chest X-rays, and HRCT. However, these methods predominantly do not detect the disease until it has significantly progressed. For this reason, there is a growing body of research investigating early detection methods for silicosis, particularly biomarkers. This literature review summarises the research to date on early detection methods for silicosis and makes recommendations for future work in this area. Findings from this review conclude that there is a critical need for an early detection method for silicosis, however, further laboratory- and field-based research is required.

scholarly journals Development of an Automated Device for the Procedure of Blood Transfusion in Newborns

2020 ◽  
Vol 3 (3) ◽  
pp. 279-287
Author(s):  
Patrícia Quariguazy da Frota ◽  
Josiane Dantas Viana Barbosa ◽  
Paulo Roberto Freitas Neves
Keyword(s):  
Blood Transfusion ◽  
Literature Review ◽  
Medical Device ◽  
Neonatal Jaundice ◽  
Maternal Antibodies ◽  
Volume Replacement ◽  
Hemolytic Disease ◽  
Transfusion Therapy ◽  
Erythrocyte Hemolysis ◽  
First Choice

Hemolytic disease of the newborn, also known as hemolytic disease of the fetus and newborn, HDN, HDFN, is a problem of fetal erythrocyte hemolysis. This may happen due to the sensitization of maternal antibodies through the placental route. It is the pathology most frequently found in neonatal patients. Approximately 98% of maternal alloimmunization cases by erythrocyte antigens are due to the RhD factor. Phototherapy is the first choice in the treatment of neonatal jaundice. Blood transfusion is the therapy instituted for the treatment of severe neonatal disease. This study aimed to develop an automated device for performing the blood transfusion procedure. The method was developed in four stages: (1) Literature review about the search for theoretical references based on scientific articles and textbooks on transfusion therapy in the newborn; (2) Elaboration of the device consisted of items related to its assembly and structuring; (3) Operation of the medical device, including specific schedules related to the execution of the procedure; (4) Performing tests with simulating the purpose of volume replacement in the total cycle performed in the exsanguine transfusion procedure. The results showed that it was possible to assemble, reproduce, and implement the automation of the device developed for the exsanguine transfusion procedure in a practical. Also, the procedure presented security and effectiveness in the clinical treatment related to HDN.  

Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations

2014 ◽  
Vol 143 (10) ◽  
pp. 2018-2042 ◽  
Author(s):  
V. RODRÍGUEZ-PRIETO ◽  
M. VICENTE-RUBIANO ◽  
A. SÁNCHEZ-MATAMOROS ◽  
C. RUBIO-GUERRI ◽  
M. MELERO ◽  
...  
Keyword(s):  
Public Health ◽  
Systematic Review ◽  
Early Detection ◽  
Literature Review ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Detection Methods ◽  
Surveillance Systems ◽  
Animal Populations ◽  
Globalized World

SUMMARYIn this globalized world, the spread of new, exotic and re-emerging diseases has become one of the most important threats to animal production and public health. This systematic review analyses conventional and novel early detection methods applied to surveillance. In all, 125 scientific documents were considered for this study. Exotic (n = 49) and re-emerging (n = 27) diseases constituted the most frequently represented health threats. In addition, the majority of studies were related to zoonoses (n = 66). The approaches found in the review could be divided in surveillance modalities, both active (n = 23) and passive (n = 5); and tools and methodologies that support surveillance activities (n = 57). Combinations of surveillance modalities and tools (n = 40) were also found. Risk-based approaches were very common (n = 60), especially in the papers describing tools and methodologies (n = 50). The main applications, benefits and limitations of each approach were extracted from the papers. This information will be very useful for informing the development of tools to facilitate the design of cost-effective surveillance strategies. Thus, the current literature review provides key information about the advantages, disadvantages, limitations and potential application of methodologies for the early detection of new, exotic and re-emerging diseases.

Efficient Signal Detection Methods for High Mobility OFDM System with Transmit Diversity

2018 ◽  
Vol 44 (3) ◽  
pp. 1769-1778
Author(s):  
Jyoti P. Patra ◽  
Poonam Singh
Keyword(s):  
Signal Detection ◽  
High Mobility ◽  
Transmit Diversity ◽  
Detection Methods ◽  
Ofdm System
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