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Both qualitative and quantitative study produces some satisfactory results which help to make the proposed approach trustworthy so that it can be reliably adapted in the real-world scenarios. The proposed approach initially performs a superpixel-based clustering using the proposed superpixel computation method which significantly reduces the computational overhead for the further clustering process by reducing a large amount of spatial information. Therefore, radiological images can be conveniently explicated with the application of the proposed method and the proposed approach is also helpful in the easy interpretation of the radiological images.

The proposed work neither claims that the suggested approach is cent percent accurate in determining the COVID infection nor claims that it can be a replacement of the RT-PCR test but, the proposed method can help detect some common characteristics from the CT scan images, that can help to isolate some suspected patients from the rest of the community.

The proposed approach is helpful for the early screening of the COVID besides being a significant contribution to the image segmentation literature. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

The authors would like to express their gratitude and thank the editors, anonymous reviewers, and referees for their valuable comments and suggestions which are helpful in further improvement of this research work. The dedicated graphics memory is not utilized for any kind of processing purposes.

The system in which the experiments are carried out is equipped with the Microsoft Windows 7 64 bit operating system. It is not at all essential to use the Matlab environment to implement the proposed approach. We have chosen Matlab due to the availability of some inbuilt functions which are helpful to reduce the coding complexity.

Still, any other languages or platforms can be used to implement the same. It is assumed that there are no manual annotations available and the proposed approach is capable to process the images without having any prior knowledge. The final segmented images are constructed by assigning the superpixel to their corresponding cluster centers. These segmented images are helpful to interpret different features from these radiological images. Appl Soft Comput. Published online Feb 3. Author information Article notes Copyright and License information Disclaimer.

All rights reserved. Elsevier hereby grants permission to make all its COVIDrelated research that is available on the COVID resource centre – including this research content – immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source.

Abstract Due to the absence of any specialized drugs, the novel coronavirus disease or COVID is one of the biggest threats to mankind Although the RT-PCR test is the gold standard to confirm the presence of this virus, some radiological investigations find some important features from the CT scans of the chest region, which are helpful to identify the suspected COVID patients. Introduction Automated computer-aided systems prove their effectiveness and real-life applicability in various scenarios.

Table 1 Some of the related literatures and their brief overview. The calibrated source-to-background curves are used to determine the volume using the iterative thresholding procedure. One major drawback of the system is that it cannot effectively measure small volumes. Wiemker et. This work proposes a divergence theorem and histogram-based Ct image segmentation approach. This approach is can effectively and optimally isolate the lung nodules from the CT scan images.

In this context, the optimality is defined in terms of the mean gradient of the iso-surface and the sphericity. Asari et. This algorithm is consisting of two stages where the first stage employs a global thresholding approach and in the second phase, the differential region growing is used to extract the gastrointestinal lumen from the endoscopic images.

The dynamic hill-clustering approach is used to ascertain the effectiveness of the termination criteria and to look after the growth process. Yu-qian et. Traditional gradient-based edge detection approaches are susceptible to noise and therefore, this approach proposes a novel approach to detect edges of the lung CT scan images using mathematical morphology.

This approach is tested on the CT images which are corrupted with the salt-and-pepper noise and its efficiency is proved by comparing this approach with some of the other standard approaches.

It is observed that this approach can efficiently reduce the effect of noise and also can generate precise edges. Falcao et. This approach is highly dependent on the user intervention to efficiently determine the segmented regions and to define the objects.

This approach is found to be 3 to 15 times faster compared to manual tracing. This approach can be applied almost independently to the applications. One main problem associated with this method is the difficulties associated with the choice of slabs and orthogonal slices which has a serious impact on the efficiency of this approach. Pan et. The proposed approach addresses the problem of discontinuous edges and dependency on the initialization which are associated with the traditional edge detection approaches.

In this work, the intensity of the gradient images is modeled as the concentration of the nutrients and the property of the bacteria Escherichia coli. The edges are highlighted as the paths of the bacteria. Although this approach performs well and comparative study shows the effectiveness of the proposed approach still, one problem of this approach is not very robust to noise. Noise can lead to crumpled edges.

This approach is not also suitable to handle overlapped cells. Ji et. Traditional fuzzy C-means clustering approach does not consider the spatial information and less robust to noise. This work proposes a modification which is known as the weighted image patch-based FCM. In this work, pixels are replaced with the weighted patches which is helpful to incorporate spatial information in the segmentation process.

It is helpful to increase the reliability of the overall segmentation process but it also increases the computational overhead drastically. Agrawal et. This work proposes a novel hybrid approach which is based on the genetic algorithm and the bacterial foraging algorithm. The combination of these two approaches is used to optimize the objective function of the fuzzy c-means clustering. The final cluster centers are obtained using a method called optimum boundary point detection.

This approach cannot determine the optimal number of clusters automatically and produces inaccurate results if the predefined clusters and the actual number of clusters differ. This approach is based on intuitionistic fuzzy set theory and it is known as the intuitionistic fuzzy C means clustering. In this work, a novel objective function which is known as intuitionistic fuzzy entropy is incorporated with the traditional fuzzy C-means clustering. This approach is applied to different CT scan images to prove its efficiency.

Miao et. This approach can be divided into two phases where the first phase incorporates a dictionary learning method to handle the noise.

In the second phase, this dictionary learning approach is hybridized with the Improved fuzzy c-means clustering approach. The proposed approach is not efficient for medical images with inhomogeneous intensity distribution. Open in a separate window. A brief overview of the artificial cell swarm optimization procedure This is a recently developed metaheuristic procedure that is inspired by the artificial cell division procedure.

The incorporated modifications are listed below [47] : i. The artificial cells are not depending on the current state to participate in the cell division process.

Fuzzy C-means clustering based on type 2 fuzzy system The proposed approach adopts the type 2 fuzzy logic-based clustering approach to effectively model and handle the random uncertainties. A point with higher uncertainty has a lesser impact on the overall clustering process and vice-versa. It helps to achieve more realistic results.

Proposed method of superpixel computation The ever-growing technology allows us to increase the quality of the image acquisition hardware.

Table 3 Details of the CT scan images under test. Proposed superpixel coupled fuzzy ACSO approach-based segmentation The conventional fuzzy C-means clustering approach often overlooks some important spatial information that can be costly in terms of the segmentation performance.

Dataset description CT scan images of the chest region are collected from the COVID positive patients from different geographic regions. Experimental results The experiments are performed in the MatLab Ra on a computer that is equipped with an Intel i3 processor and 4 GB main memory. Table 4 Performance evaluation of different approaches using Davies—Bouldin index The highlighted values indicates acceptable values. Image Id Algorithm No. Table 5 Performance evaluation of different approaches using Xie—Beni index The highlighted values indicates acceptable values.

Table 6 Performance evaluation of different approaches using Dunn index The highlighted values indicates acceptable values. Table 8 Comparison of the proposed approach with the active contour method. Study of the convergence rate The rate of convergence is an important parameter to be studied. Analysis of the complexity The time complexity is an important aspect that is to be analyzed.

Discussion 6. Threats to validity The obtained results indicate that the proposed approach is suitable for real-life scenarios and also performs efficiently. Limitations Although the proposed approach is efficient enough to segment the CT scan images automatically and produces realistic segmented outcomes still, some important drawbacks can be observed in this proposed approach that can be addressed in the subsequent works. Conclusion This article proposes a novel, simple and elegant solution that uses some of the important features of the chest CT scan images to screen the COVID suspected patients easily and at an early phase which can be considered as an effective tool to reduce the drastic spread of this virus.

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments The authors would like to express their gratitude and thank the editors, anonymous reviewers, and referees for their valuable comments and suggestions which are helpful in further improvement of this research work.

Software setup The system in which the experiments are carried out is equipped with the Microsoft Windows 7 64 bit operating system. References 1. Kim T. Learning full pairwise affinities for spectral segmentation. IEEE Trans. Pattern Anal. Chakraborty S. In: Chakraborty S. IGI Global; An overview of biomedical image analysis from the deep learning perspective.

Object Recognit. Motion Detect. Video Process. A study on different edge detection techniques in digital image processing; pp. Libbrecht M. Machine learning applications in genetics and genomics. Tang C. IEEE Int. BIBE Interrelated two-way clustering: An unsupervised approach for gene expression data analysis; pp. In: Appl. IGI GLobal; An advanced approach to detect edges of digital images for image segmentation.

Expert Syst. Multi-Objective Optim. Springer Singapore; Singapore: Application of multiobjective optimization techniques in biomedical image segmentation—A study; pp.

Springer; An optimized intelligent dermatologic disease classification framework based on IoT; pp. Hore S. An integrated interactive technique for image segmentation using stack based seeded region growing and thresholding. IEEE; Contrast optimization using elitist metaheuristic optimization and gradient approximation for biomedical image enhancement; pp. Opto-Electronics Appl. Optronix An integrated method for automated biomedical image segmentation.

Mesejo P. A survey on image segmentation using metaheuristic-based deformable models: State of the art and critical analysis. Soft Comput. Chen X. IEEE Rev. In: Adv. Metaheuristic Comput. Dey N. Intelligent computing in medical imaging: A study; pp. Campadelli P. Notes Comput. Including Subser. Notes Artif. Notes Bioinformatics Springer Verlag; Liver segmentation from CT scans: A survey; pp. Litjens G. A survey on deep learning in medical image analysis.

Image Anal. Jentzen W. Segmentation of PET volumes by iterative image thresholding. Wiemker R. Optimal thresholding for 3D segmentation of pulmonary nodules in high resolution CT.

Asari K. A fast and accurate segmentation technique for the extraction of gastrointestinal lumen from endoscopic images. Zhao Y. IEEE Eng. Medical images edge detection based on mathematical morphology; pp. A 3D generalization of user-steered live-wire segmentation.

Pan Y. Cell image segmentation using bacterial foraging optimization. No measurements can encompass the complexity of a disorder, but lactic acid can approach that goal 3 Indeed lactic acidosis is the most frequent metabolic acidosis and many causes are reported for lactate increase, not only hypoxia: the higher the lactate concentration, the worse the outcome.

The initial values have a prognostic significance, but serial measurements are more valuable for prognosis. Conductivity-based Hematocrit Ht estimations have limitations. Abnormal protein concentration will change plasma conductivity. Low protein concentration, resulting from dilution of blood with protein-free electrolyte solution during surgery, will result in erroneously low Ht value. In any situation, to correctly interpret BGA results history should be always considered: reasons for presentation, information concerning events, environment, trauma, medications, poisons, toxins and an accurate physical examination should be carefully collected.

Acute respiratory distress syndrone: the berlin definition, Ranieri MV et al. Conductivity-based Hematocrit measurement during cardiopulmonary bypass.

Steinfelder-Visccher J et al. The knowledge that has been garnered so far on severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 infection is that humoral immunity encompasses the generation of immunoglobulins of most classes against surface viral antigens, which mostly involve the spike protein, the nucleocapsid protein, but also envelope and membrane proteins.

Since the spike protein is the anchor that the virus uses for penetrating the host cells through biding with its natural host cells receptors, it can be assumed that antibodies binding to spike protein of SARS-CoV-2, and especially to its receptor binding domain, would retain stronger neutralizing potency against the virus. Serological testing has been conventionally defined as a diagnostic procedure used for detecting an immune response against an infectious agent.

The diagnostic sensitivity stratified according to the assay methodology is highly variable. Additionally important drawbacks of rapid serological tests include the facts that the information provided by the companies is concerning because often lacks details, its quality is considerably variegated among different devices, several claims are vague, there is a lack of transparency along with the fact that human aspects are not been adequately addressed for purpose of alleviating the risk of inappropriately using the device.

The risk of misinterpreting tests results by patients when rapid kits are used for self-diagnosis is another aspect that must be considered. This was mostly due to objective difficulties encountered by the patients in reading and interpreting the results of the strips. Important considerations for implementing point-of-care serology testing thus include i usage of well-validated tests, evaluated against a gold standard; ii performance characteristics – thus encompassing sensitivity, specificity, positive and negative predictive values or cross-reaction with other coronaviruses – shall be tested using serum samples collected from patients infected with SARS-CoV-2, with other respiratory viruses including seasonal coronaviruses and also from healthy controls; iii adequate training of healthcare workers is needed iv and, finally, IV provisions must be in place, encompassing the capture of testing data for individual patient records and surveillance purposes, and the participation to external quality assessment schemes, to systematically monitor the quality of this type of testing.

At the heart of society 4. It is in these sectors that, lately, the greatest investments have been made in digital transformation aimed at exploiting -through data-all the new present and emerging technologies, from the Internet of Things IoT to Artificial Intelligence AI.

The exploitation of Big Data, in fact, constitutes the starting point and the indispensable resource for the development of innovative and precision medicine, providing scientific, organizational and infrastructural support to promote research and accelerate preclinical and clinical studies.

However, this development, having increased the number of subjects holding health-related data, the speed of transmission of such data and the quantity of information electronically stored often not on national territory , has determined an exponential increase in the danger of data processing from the point of view of confidentiality and an increased possibility of damaging the dignity and fundamental freedoms of the individual.

This has led to an increased sensitivity of the European legislator and, subsequently, of the national legislator, towards the protection of such data and related protections. In addition to the General Data Protection Regulation, which has revolutionized the way of conceiving the data economy, it is, in fact, being evaluated by European institutions the first draft of the Artificial Intelligence Act, which will be the real springboard for the massive and regulated use of algorithms, especially in healthcare.

To be precise, this last mentioned regulation will only define the limits to the use of algorithmic systems already widely in use. AIFA, through this guide, has described some case studies, showing some workflows that represent the regulations impacted depending on the type of system used and paying particular attention to the compliance related to the treatment of data and the related profiles of cybersecurity.

Ad oggi sono operativi circa 72 Drive-Through-Difesa. I contributi, forniti da ciascuna Forza Armata, sono diretti e coordinati fin dalla prima ora dal Comando Operativo di vertice Interforze COI per mezzo di una Sala Operativa dedicata, composta da personale interforze. In the last couple of decades, Laboratory Medicine has made giant steps forward in terms of innovative technology and has made major scientific breakthroughs in the medical field as a whole.

Indeed, a plethora of both in vitro and in vivo assays and tests in biological fluids of the human hydrodynamic system are now available. The importance, for clinical purposes, of novel metabolic processes and protein cross-talk mechanisms is being increasingly recognized.

The increased survival period of sick, elderly people, plus the therapeutic aspects of precision medicine, in which the drugs selected resulted in a series of direct approaches to altered target molecules, have made it difficult to identify the most effective molecules to use as biomarkers in most of this population scenario. Therefore, it seems that Laboratory Medicine does not need to increase further value in the contribution to the care of fragile individuals, and in people affected by chronic degenerative diseases.

Notwithstanding all these premises, and the increase in Clinical Laboratory testing, which is, and will continue in the future to be an indispensable ally of medical care, the correct diagnosis of a single or of multiple diseases occurring in a single individual will benefit enormously from this Discipline, if some steps forward will be made.

I believe that the enormous amount of knowledge now accumulating in the field of Laboratory Medicine will revolutionize, not only the medical care of people, but, in the various areas of the medical scenario, also the field of Laboratory Medicine Science itself and the practice deriving from it. In other words, we should all begin to be mindful of our state of health as early as about 20—25 years of age, when most auxological aspects have been reached, and sexual maturity completed.

Therefore, also healthy people should be monitored as well as patients, which should be one of the tenets of preventive medicine. Having said that, I must now say that chronological age is practically meaningless in calculating health status. This, of course, applies much more to multimorbidity; in fact, once identified them, measures can be made to eradicate or to delay the start or the progression of each illness, therefore determining a better state of health during the progression of chronological age.

The revolution I am talking about is to look at each individual when they are enjoying still normal health, as mentioned above. This approach may be considered too costly, but in effect it is much less costly than waiting for the appearance of an overt disease, which must then be treated for decades, frequently with very expensive drugs and tests laboratory and imaging.

This will also support the joining of Preventive Medicine to effective Individualized Medicine. Salvatore F. The shift of the paradigm between ageing and diseases. Clin Chem. Lab Med. During the second wave, the validation of SARS-CoV-2 antigen rapid diagnostic tests RDT has substantially changed testing strategies globally, since results were available within 30 min, reducing turnaround time and therefore exposure risk. Recently, validated self-tests for SARS-CoV-2 based on the nasopharyngeal swab NPS or saliva have prompted for the empowerment of the general population in the fight against the spread of infectious.

Swabbing is a complex task requiring training and competency assessment, and thus they are performed by trained nurses or physicians. Recently, Tsang et al. The Authors concluded that saliva and nasal swabs are clinically acceptable alternatives to commonly used nasopharyngeal swabs.

Saliva is a matrix elective for self-collection, and molecular testing is reliable but require laboratory instrumentation to be performed. Indeed, antigen determination on salivary samples is still under debate [2].

Most of the errors occur in the preanalytical phase, with relatively few analytical and post-analytical errors. Some issues arising during the pre-analytical phase of SARS-CoV-2 diagnostics regards: the time of swab, swabbing practice, sample handling and conservation and RNA extraction.

NPS should be taken at the time of symptom onset when the highest viral load occurs in COVID, thus not the day immediately before and not too far from possible close contact with positive subjects. Differently, sample preparation is a crucial factor for antigen testing, and centrifuged vs. In conclusion, self-testing could be of aid in the screening programs for reducing viral spread, but other alternatives are possible, such as self-collection of samples with analytical tests performed in clinical laboratories.

These required the optimization of pre-analytical steps to reduce the impact on results. Woloshin, S. Basso, D. In a broad and complex territory such as that of ULSS 6 Euganea, composed of five local health districts with a population of about Information is sent in real time to central laboratory using IT middleware, where data are validated and historicized. Historicized data can be consulted and downloaded like other laboratory exams.

Results: the project involved patients. From January 1st to June 30th the average frequency of determinations per patient was about 30 days, while the average number of determinations per patient was about 7,5. This model simplifies management of both patients in IHC and followed by RMC, allowing easier access to the determination of PT-INR, with more constant therapy control and significant improvement of life quality. Ovarian cancer is the seventh most frequent malignancy in the female population worldwide and the leading cause of death among gynecological cancers.

In Italy, about new cases were registered in The availability of a guide in the diagnostic paths is a requirement for general practitioners and specialists of other disciplines that arises from the need to guarantee the most appropriate, less demanding, more useful and less expensive diagnostic path.

The purpose of PDTAs is to increase the quality of perceived and effectively delivered care, improving outcomes and promoting patient safety through the use of the right resources needed. The surgical approach plays a fundamental and essential role in the treatment program and the absent tumor residue has been defined as the only tumor residue associated with optimal survival curves and also the antiblastic chemotherapy, that always follows surgery in advanced ovarian cancer, gets better results after optimal surgery.

The first network of reference and dissemination of PDTAs is constituted by general medicine. Indeed, we cannot ignore sharing with the entire regional network of general practitioner, who will thus know who to send the patient with suspicion or already ascertained diagnosis of ovarian cancer, for an adequate diagnostic and therapeutic path, allowing feedback on the conditions and clinical-therapeutic pathways for individual patients.

In addition, information and reference relationships with voluntary associations and patient associations must be encouraged. They constitute a fundamental asset in the creation and development of information, health culture of primary and secondary prevention and support in home care or in assistance facilities even to the terminally ill.

Scarone , V. Dovere, C. Traverso, F. Background: The emergency caused by the Covid pandemic has forced the reformulation of the operating methods of the Health System, turning the spotlight on the need for greater interaction between hospital and territory. This aspect is even more evident in patients needing for a more strict followup as those under antithrombotic therapy TAO , making clear the essential usefulness of digital tools and of new organizative models.

Each patient was asked for an email address and signed consent to the computerized management of TAO therapy and forwarding of health documents. Results: In order to monitor the expected results, the following indicators were evaluated: number of incoming phone calls; number of treatment plans issued for DOAC; time in range for patients in AVK; number of complications recorded in the period under review April —April Conclusions: The new organization, based on digital support of clinical monitoring, has received high appreciation from patients and consequently a greater compliance with the therapy protocol.

This management model has allowed an effective control both of the number and severity of adverse events, while the reduction of outpatient access has allowed to drastically reduce the infectious risk.

In addition, e-mailing of reports and treatment plans allowed an optimization of human resources. Lorubbio 1 , F. Baldelli 1 , E. Bromo 5 , G. Caldarelli 4 , C. Donnini 1 , S. Fabbroni 1 , A. Fanelli 1 , M. Fantacci 2 , L.

Gasbarri 1 , M. Mazzi 4 , A. Periccioli 3 , P. Pugliano 4 , C. Rapini 2 , A. Rebuffat 3 , A. Sereni 1 , M. Sorini 1 , E. Tripodo 1 , A. Ognibene 1. The use of information and communication technologies ICT and E-Health can contribute to a reorganization by moving the focus of health care from the hospital to the territory.

The aim of the present project is to evaluate of the complete blood count CBC test and the peripheral blood smear through digital images, shared and available to the team of the 12 TSE laboratories. During implementation, the image analyzers and the staining adopted were compared, together with the quality indicators QI to support the new flows implemented between the peripheral laboratories and the Hub laboratory. The Passing-Bablok and Bland-Altman plot analysis performed for comparison of all elements of the blood count test, provided excellent results between the technologies and the different cell staining used data not shown.

The organization proposed in the project improves the analytical quality, harmonises the reporting and interpretation of analytical data, promotes uniform training, preparing for continuous professional comparison. Pelagalli 1,2 , A. Giovannelli 1,2 , C. Calabrese 1,2 , S. Sarubbi 1,2 , M. Minieri 1,2 , M. Nuccetelli 1,2 , M. Pieri 1,2 , S. Bernardini 1,2. Sepsis is an infectious disease the etiology can be viral or bacterial with hight mortality, threatening human health.

The aim of this study is to use leucocyte counts neutrophils and monocytes that are activated from pathogenic virus or bacteria and others morphological change with Mindray BCplus platform to diagnose sepsis early, quickly, conveniently and at low cost. A total EDTA-k2 anticoagulant venous whole blood samples were collected: 70 control patients blood donors with a normal complete count blood and negative VES, and samples hospitalized at the emergency department with symptoms attributable to sepsis with PCT request.

All data was divided in 4 groups: control group, group where sepsis cannot be confirmed, group with confirmed sepsis diagnosis and a group with sepsis from SARS-CoV-2 infection. The roc curves highlight acceptable sensitivity and specificity values for some haematological parameters and suggest a possible cut-off.

The BC plus can help the diagnosis of sepsis upon the admission to the emergency department using some morphological positional parameters. Pecoraro 1 , T. Pirotti 1 , T. Trenti 1 , M. Plebani 2. However, their immunological significance are currently undefined. There are many methods available for the detection of specific Abs whit suboptimal diagnostic accuracy and relatively high throughput capacity and less stringent specimen requirements compared to RNA-based assays.

We conduct a retrospective study analyzing with a big data analysis all samples collected between 11 March and 30 September All serum samples received at the laboratory were processed using qualitative and commercially available rapid lateral flow immunoassay tests for nCoV IgG and IgM.

Positive results were confirmed using a chemiluminescent method. Subjects with a positive result were contacted from the Department of Public Health for further tests viral RNA research or subsequent serological tests for definitive diagnosis.

A total of 69, serological tests in 42, subjects and , oropharyngeal or nasopharyngeal swabs in 88, subjects were performed. Of the subjects with IgG negative and IgM positive results, a positivity was confirmed in 1. Subsequent serological testing confirmed IgG positivity in 8 subjects 1. Conversely, in subjects with IgG positive and IgM negative results, a positivity was confirmed in 7. Scaglione , C. Nardelli, M. Setaro, E. The impairment of this pathway is a common characteristic of many tumors and it is frequently observed in breast and ovarian cancer.

Samples were then pooled and sequenced on NextSeq Dx platform Illumina. Sequencing files were quality checked, analyzed and processed using our dedicated bioinformatics pipeline.

In this workflow, LGAs profiles were calculated using whole genome sequencing data at low coverage 0. The HRD score was then estimated by measuring the level of agreement in the segmentation profiles of each samples. PLoS One, Gallagher, R. Schulze, C. J Patient Saf, The lack of staff trained in PV is one of the most serious limiting factors affecting the development of PV in resource-constrained settings. Previous experiences suggest that blending learning programmes can be implemented in resource-limited countries to train health care professionals HCP with remarkable gains in terms of knowledge acquisition.

Methods: We developed the blended-courses integrated with a Train of Trainers scheme [1]. Two e-learning courses were made available on a web-based application, together with a manual on how to combine the e-learning courses together with face-to-face interactions. The blended course were given in Tanzania, Eswatini and Nigeria. Results: In the three countries 95 participants were trained Table 1.

All participants completed the two courses and the mean score of the post-test was significantly greater than on the pre-test Table 1.

In the second level, the participants from the first training were training others. The majority of respondents to questionnaires have been satisfied, declared they felt more involved in PV and reported at least an ADR after the training both in the first and second level.

The trends of reporting increased in the twelve months after the training if compared to the previous twelve months: vs and vs ICSRs were reported to Vigibase for Tanzania and Eswatini National Agency respectively. Conclusion: Our results demonstrated that a blended course can reach an important number of participants and improve their knowledge. It is difficult to establish how much of the increase of reports was attributed to the blended learning training.

Alammary A. Blended learning models for introductory programming courses: a systematic review. Plos one. The views and opinions of authors expressed herein do not necessarily state or reflect those of EDCTP. Introduction: Considering data from the literature in favor of active educational intervention to teach pharmacovigilance, we describe an innovative model of distance learning clinical reasoning sessions CRS of pharmacovigilance with 3rd year medical French students.

Objective: The three main objectives were to identify the elements necessary for the diagnosis of an adverse drug reaction, report an adverse drug reaction and perform drug causality assessment.

Methods: The training was organized in 3 stages. First, students practiced clinical reasoning CRS by conducting fictive pharmacovigilance telehealth consultations. Second, students wrote a medical letter summarizing the telehealth consultation and analyzing the drug causality assessment. This letter was sent to the teacher for a graded evaluation. In the third stage was a debriefing course with all the students. Results: Of the third-year medical students enrolled in this course, participated in the distance learning CRS.

The evaluation received feedback from students, with an average score of 8. The qualitative evaluation had only positive feedback. The students appreciated the different format of the teaching, with the possibility to be active. Conclusion: Through distance CRS of pharmacovigilance, medical students’ competences to identify and report adverse drug reactions were tested.

The students experienced the pharmacovigilance skills necessary to detect adverse drug reactions in a manner directly relevant to patient care. The overall evaluation of the students is in favor of this type of method.

Methods: This research used a qualitative inductive methodology through thematic analysis. The first step was to identify, through a literature review, current practices for herbal pharmacovigilance. Based on the findings a semi-structured interview guide was designed, and purposive sampling was used to recruit the interview participants. By using a snowballing technique more potential participants were reached. Most of these recommendations are applicable worldwide, while some are limited to certain regions.

Tong, A. Consolidated criteria for reporting qualitative research COREQ : a item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19 6 , — Introduction: Although medical cannabis MC has been available in Canada since , lack of recognition of MC as a drug has restricted patient access.

The Quebec College of Physicians, between and , authorized MC use only within a research framework. Follow-up ended due to either MC discontinuation, loss to follow-up, 3 years follow-up, or end of data collection May , 6 months after the last patient in. Data were collected at inclusion and at follow-up visits every 3 months for the first 2 years, then at least once per year in the third year.

MC mode of administration ingestion, inhalation, other , and cannabinoid content ratio tetrahydrocannabinol THC -dominant, cannabidiol CBD -dominant, or balanced were documented. Results: 2, patients were enrolled in the registry mean age Over follow-up, 3. Reports included a total of AEs average 1. The most common PTs were dizziness Conclusion: There were no new safety concerns identified in the Registry, although notable differences in AE profile between modes of administration and cannabinoid content ratios should be considered by health professionals.

Further work identifying and managing risk factors for AEs is warranted to maintain a favorable risk-benefit ratio for MC. Introduction: Dengue is one of top ten global health threats and is a serious burden in the Philippines. Dengvaxia immunization program was launched on April for children 9—year-olds in three regions with high statistics of dengue, hospitalization, and deaths.

This was coincidentally the campaign period for national elections. Use of vaccine, once available, was part of a strategy to control epidemic. Current measures were inadequate. What started as vaccine-vigilance information sparked a public outcry. This led to a series of parliamentary investigations, traditional and social media misinformation and disinformation vilifying the health decision makers and the company, and criminal charges filed against over 20 individuals by the state over alleged unproven vaccine caused deaths.

Despite attempts to correct these narratives by a few health professionals, the damage to institution, the program, the product, and individuals have been done. The consequences of such actions of emotional approach without understanding the science have resulted in creating general vaccine rejection, hesitancy, other outbreaks such as measles, lowered confidence even with recent COVID vaccines.

Objective: This abstract aim to describe the situation at that time in the Philippines and extract lessons that will inform better risk communications during crisis. Results: Some of the important lessons learned are in risk management and communications. Adverse health product information should be announced with circumspect considering the level of health literacy and risk appreciation in a country.

Partisan politics interfered with poorly understood science, fueled by imprudent comments by officials and health professionals who spoke out of turn, amplified by the media and created chaos.

The fear was so palpable that enlightened health professionals refused to provide countervailing facts. Reinstating the vaccine would be perceived as the government had back-pedaled on a mistake. In the meantime, the drama contributed to vaccination hesitancy and outbreaks. Conclusion: Public health decisions are policy and regulatory decisions anchored in ethical and utilitarian principles.

Edillo et al. Economic Cost and Burden of Dengue in the Philippines. Vannice, et al Mendoza, Dayrit, Valenzuela. Dengue researcher faces charges in vaccine fiasco. Lasco et. Medical populism and immunisation programmes: Illustrative examples and consequences for public health.

Trolleyology and the Dengue Vaccine Dilemma. Dayrit, Mendoza, Valenzuela The importance of effective risk communication and transparency: lessons from the dengue vaccine controversy in the Philippines. Dengue vaccination: a more balanced approach is needed. Introduction: Vaccines are vital tools to control epidemic and pandemic diseases, such as COVID, demonstrating safety and effectiveness.

However, rare adverse events of special interest AESIs following vaccination arise with every new emerging pathogen vaccine program.

Adversomics, a set of technologies that measure the inventory of molecules e. The International Network of Special Immunization Services INSIS brings together vaccine safety, public health, and systems biology experts in middle- and high-income countries to investigate the causes of, and identify strategies to mitigate AESIs following vaccination insisvaccine.

Brighton Collaboration case definitions and harmonized protocols will be employed to collect detailed clinical data and serial blood samples suitable for adversomics e.

Integration of clinical and biological data will enable comparisons of analyte levels and immune responses within groups over time and between cases and controls. Global collaboration across five continents will ensure adequate sample size. Conclusion: INSIS-led studies will provide insight into pathways triggered in these AESIs and susceptible populations to inform vaccine development strategies to reduce the potential to trigger pathways involved in AESIs, risk-benefit assessment, and personalized vaccination strategies.

Introduction: During the covid 19 period, several countries needed to set up or develop their pharmacovigilance systems, unfortunately containment and the closure of borders prevented the organisation of classic training sessions. Objective: The objective of this work is to present the pharmacovigilance simulation game developed by CAPM, RCC and the results of its pilot use with pharmacovigilants from 10 French-speaking African countries.

The game is based on good practices in Pharmacovigilance PV , and inspired by the different WHO guidelines, the experience of the Moroccan PV center, and behaviors consensually considered as the norm in PV.

In fact, they are put in a real-life situation to choose actions and strategies for the development of a PV center and must be able to optimize the human and material resources at their disposal to make their center shine within their national health system but also at the level of the international PV network.

Better understand the challenges and outlooks linked to the creation and management of a PV center. Put into practice the theoretical concepts in causality assessment, signal detection and risk minimization actions.

During the game, within 10 levels, participants have to set up a PV center following WHO pharmacovigilance indicators: a practical manual for the assessment of pharmacovigilance systems as structural indicators, process indicators and outcome indicators, and following the pharmacovigilance process from collecting data, analyzing them, detecting signals, and setting up national technical pharmacovigilance committee to discuss about safety signals and risk minimization actions to put in place.

Conclusion: The use of the game by the pharmacovigilantes during the pilot phase gave good feedback on the ease of use and the effectiveness of the game in capacity building in pharmacovigilance.

University of Huddersfield, Huddersfield, pp. Introduction: Pharmacovigilance has traditionally been a reactive science with a significant dependence on spontaneous adverse event reporting. The pandemic on the other hand has accelerated application of novel technologies and approaches to engaging with the patient, remote connected care at their home and dependence on technologies to supplement regular communication channels.

Telemedicine is evolving rapidly and playing a key role in clinical interventions. Objective: Digital Health and novel technologies offer a significant opportunity to enhance pharmacovigilance thru proactive patient monitoring, risk communication, personalized care plans and access to real world data.

Leveraging such approaches will not only lead to early detection of risks but also to personalized interventions and improved patient outcomes. Educational material which is more interactive, visual and multi-dimensional can replace paper or text based risk communication material. This could provide early signal detection in individual patients and enable proactive patient level pharmacovigilance.

Educational and risk related material can be dynamically updated based on patient preferences, interactions and profiles. Machine learning approaches which link material with outcome can enhance impact of pharmacovigilance methods and tools.

In order to utilize the full potential of such options it is critical that the regulatory framework is updated to enable such approaches which complement traditional PV and can drive efficiencies and higher effectiveness in the risk communication process. Collaboration within the network of industry and regulators is essential to further such research and maximize the impact on value for patients, HCPs and sponsors. Introduction: Large amounts of data associated with safety issues are generated along the entire lifetime of drugs, from its infancy as preclinical leads, through its adolescence as clinical candidates, all the way up to its adulthood as marketed drugs exposed to the human population.

Across the different stages in the life of a drug, some of the data collected initially may be confirmed and consolidated with data at an advanced stage, whereas other data may not be translated, and in some cases may even contradict, those safety signals that are ultimately observed in the human population. Collecting and properly integrating such an heterogenous pool of data is a complex and tedious task. But even if one manages to put all data together, the construction of useful models to anticipate and detect drug safety signals remains a challenge.

Objective: The presentation will cover our efforts to connect data from in vitro safety pharmacology, preclinical toxicology, clinical safety and post-marketing spontaneous reports for over 9, small molecule drugs, combination drugs, and biologics. A novel consensus approach using various statistical and machine learning methods to anticipate side effects of potential safety concern, detect adverse drug reaction signals and perform pharmacovigilance analyses will be introduced.

Use case application examples to individual drugs and drug classes will be discussed. Methods: Our consensus approach to post-marketing surveillance integrates four different methodologies based on detection of prior safety markers, identification of class reactions, statistical projection of disproportionalities based on reporting frequencies and velocities, and machine learning models of translational safety data. Results: Results on the validation of our approach to anticipating adverse drug reactions of safety concern to the population at the postmarketing stage based on i in vitro safety pharmacology data, ii preclinical toxicology data, iii clinical safety data and iv the first sample of 25 postmarketing spontaneous reports will be presented.

Based on data available in each case, the performance of the different methods varies for different drugs, drug classes, and side effects. A discussion on performances in selected use cases will be included. As an example, the analysis of long-term PARP inhibition on circadian patterns and its dependence on the reporting bias by consumers will be discussed.

Conclusion: Integration and modelling of the large amount of translational safety data currently available from all phases of drug discovery, development and post-marketing to anticipate and follow adverse drug reactions opens an avenue to a whole new perspective in pharmacovigilance. Introduction: Psychedelics are unique psychoactive chemicals that can change consciousness by acting on 5-HT2A receptors [].

There is limited knowledge concerning the online interest in psychedelics that we can extrapolate via trends websites. Objective: We aim to examine the online information-seeking behavior concerning the most popular psychedelics, including cannabis—a quasi-psychedelic—in the European Union EU members of interest and the UK before and during the pandemic. Methods: We designed a “dictionary” of terms to extract online search data from Google Trends concerning psychedelics and cannabis from Jan to 1-Jan We conducted a triple Holt-Winters exponential smoothing—additive model—for time series analysis to infer seasonality [4, 5].

We utilized hierarchical clustering—an unsupervised machine learning method—to explore clusters of countries concerning the spatial geographic mapping of these chemicals. We also implemented—a t-test—for comparing the slope difference of two trends before versus during the pandemic. Results: There was an evident seasonal pattern for cannabis, NBOMe, and psilocybin in almost all nations of interest. Similar patterns existed in France and the UK, while those in Germany, Sweden, and Romania had relatively shorter periodicity.

Analysis of slopes and hierarchical clustering conveyed differentiated patterns concerning the temporal and spatial mapping, respectively, while contrasting the two periods before versus during the pandemic. Conclusion: Cannabis and psychedelics follow somewhat a consistent pattern concerning seasonality across Europe; some correlate with the seasonal harvesting of mushrooms, and others with public holidays, including Christmas, the new year holiday, or school breaks.

The pandemic influenced some significant changes concerning the online interest in the EU and the UK; nonetheless, we should rely on more rigorous longitudinal and experimental study designs—possessing a superior level of evidence—to confirm the causal relationship. However, these patterns might be insightful for decision-makers and regulatory authorities—like the EMCDDA—to prognosticate and prevent addiction catastrophes. Understanding and using time series analyses in addiction research.

Carhart-Harris RL. How do psychedelics work?. Current Opinion in Psychiatry. Novel psychoactive substances: types, mechanisms of action, and effects. British Medical Journal. Robust forecasting with exponential and Holt—Winters smoothing.

Journal of Forecasting. Gardner Jr ES. Exponential smoothing: The state of the art—Part II. International Journal of Forecasting. Introduction: Continuous monitoring of the safety profile of drugs is one of the critical processes of pharmacovigilance.

As medical literature might be valuable source of safety data, especially for rare, unlisted, serious cases, all MAHs are obliged to medical literature monitoring MLM in all marketing countries [1].

This approach can be changed through modern automation techniques. Objective: To develop and test a tool for automated monitoring of local literature and enhance drug safety data identification. Methods: Modern programming approaches were used to create PV platform, intended for automated literature screening.

GAMP 5 recommendations were used to prove the validation status. Results: We developed a tool—DrugCard PV platform which screens local medical sources for updates on a weekly basis.

Till May we added around local journals originated from 10 countries that cover different therapeutic areas. Our tool automatically searches for defined keywords drug trade names, active substances in published articles. Different file formats can be screened including text, pdfs, images etc. In case a new issue of a journal is published—a PV specialist will receive an email notification.

The mandatory features of a validated computerized system, like audit trail, logs, reports are also present here. Instead of manual reading of the whole journal issue the user only should read a separate article, analyze whether there is a valuable safety data and label it depending on the content.

PV specialists may work together inside the platform and provide a quality check for labeled articles. Our pilot study of how a new tool may improve the efficiency revealed interesting results.

Despite the dramatically decreased amount of time needed, the number of identified ICRSs from literature increased. During the abovementioned pilot study of automated local literature monitoring lasting 2 months, 31 safety cases were identified valid and non-valid ICSRs. This is much more than usual rate of safety cases finding. It offers increasing efficiency in safety information identification with less time spent on routine activities.

Certificate of copyright in Ukraine. Hyperacute toxicity is a recent newly described entity, albeit incompletely characterized [3]. We selected reports with available information to calculate a plausible time-to-onset. Events of interest were classified into fulminant within 7 days and hyper-acute cases within 21 days, i.

Cases were described in terms of demographic and clinical features: age, gender, anticancer regimen combination vs monotherapy , therapeutic indications, seriousness hospitalization , case fatality rate CFR, namely the proportion of cases where death was reported as outcome , co-reported symptoms, co-reported irAEs.

The Immune-Adversome was estimated considering events as nodes and co-reporting as links. Hyperacute cases 18, represented Monotherapy was reported in the majority of cases Pyrexia, diarrhea, fatigue, dyspnea were the most frequently reported symptoms. Hyperacute myocarditis was reported in Among fulminant cases, most frequent irAEs were interstitial lung disease , colitis , hypothyroidism , and myocarditis Other co-occurring irAEs were colitis-hepatitis-thyroiditis, and arthritis and psoriasis.

Our network approach may complement traditional disproportionality analyses in pharmacovigilance for a more effective signal detection technique, thus supporting regulatory and clinical monitoring, especially in complex scenario such as oncology.

Target Oncol ; — Oncologist ; — Hyperacute toxicity with combination ipilimumab and anti-PD1 immunotherapy. Eur J Cancer ; — Introduction: The prolongation of the QT interval is a serious and potentially fatal adverse reaction that has led to the discontinuation of many drugs including some opioids. Data mining on pharmacovigilance databases can detect signals that identify early the risk associated with some drugs.

Results: A total of drug-reaction pairs was found in opioid reports. Analysis of individual opioids show significant signals for QT prolongation for each drug. The temporal evolution of the different signals according to the number of reports included from to shows early significant positivization of signals in the first 6 to 12 months. Underlying mechanism is unknown, but it seems to be linked to hERG channel blocking.

We propose the evaluation of the trend of change in the confidence intervals of the disproportionality parameters as a measure that can predict the occurrence of clinical events at the population level and a posible usefull strategy to minimize adverse reactions. Introduction: Language and speech are increasingly debated as potential markers for diagnosing and monitoring patients with affective and psychotic disorders 1—3. However, many neglected factors may confound communicative atypicalities.

A comprehensive list of potential confounding drugs will support the design of robust communicative marker studies. Objective: We aim at identifying a list of drugs potentially associated with speech and language disorders, within psychotic and affective disorders. Within the FAERS, we considered separately 3 populations psychotic, affective and non-neuropsychiatric disorders , to account for the confounding role of different underlying conditions.

Robustness analyses were performed to account for the biases. Results: We identified a list of potential expected and 91 unexpected confounding medications for the identification of communication markers of affective and psychotic disorders e. We developed also a MedDRA query proposal for speech and language conditions, formalization of possible biases, and related analyses to account for them.

Conclusion: We provided a list of medications to be accounted for in future studies of communicative bio-behavioral markers in affective and psychotic disorders. The methodological procedure we developed does not simply facilitate future investigations of communicative biomarkers in other conditions, more crucially it provides a case-study in more rigorous procedures for digital phenotyping in general.

Insel TR. Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope Investigative Otolaryngology. Voice patterns in schizophrenia: A systematic review and Bayesian meta-analysis. Schizophr Res. Introduction: The comparison of safety profiles for products recently on the market is difficult. There is a lack of methodology for quantifying the potential differences between products that have the same indication.

Objective: Provide the tools to quantify the differences in spontaneous reporting between two products. An Euclidian distance from the EBGM to the diagonal line measures the deviation from what would have been expected under the null assumption of similar safety profiles. As the deviation does not capture the statistical uncertainty around the estimate, we propose as measure of the deviation the minimal distance of the four Euclidian distances calculated from each of the credibility intervals around the EBGM post Product A and Product B.

A visualization capturing the global trend of the most substantial differences in reporting was generated. Conclusion: This relatively simple method can provide quantification of the differences in reporting and could help prioritize one product over the other for some population subgroups.

Introduction: The application of text mining approaches to identify adverse events AEs from electronic health records EHRs is a growing area of interest in pharmacovigilance research. In veterinary medicine, the majority of EHRs consist of unstructured clinical narratives, hence the development of appropriate methods for identifying AEs of interest is an important step in the research process. Identifying renal disease poses a specific challenge as the event may be described in narrative form or implied by reported test results or the use of renal disease specific medications.

In this study we developed regular expressions regexes to identify relevant mentions of renal disease in veterinary free text clinical narratives. Objective: To develop a method for identifying veterinary patients with renal disease in free text clinical narratives. Methods: Using VeDDRA terminology as a starting point, we used an iterative approach to develop a series of regexes which were then applied to a random sample of 10, clinical narratives.

In order to measure precision, clinical narratives containing a match to the regexes were reviewed against a case definition by two independent reviewers and disagreement was settled by consensus. Terms in the final regex were derived from three sources—VeDDRA, a word embedding model and expert opinion. To determine recall, the final regex was applied to a sample of consults where the main presenting complaint was deemed to be renal disease by a veterinary clinician.

Expanding this terminology using a word embedding model improved the PPV to 0. Following changes suggested by a veterinary expert, the PPV of the final regex was improved to 0. When the regex was divided into three components, the PPV for these individual portions was mentions of renal disease 0. When compared against the veterinary clinician validated sample of renal disease consults recall was 0. Conclusion: The developed regex can be used to identify animals with renal disease, with mentions of renal disease treatment being the most specific indicator of clinical disease.

This method can be employed to filter potential cases of interest from large datasets for use in observational studies. Introduction: We use AI in our everyday lives probably without even realising it. There are many discussions about the use of AI in PV and the potential innovation that it could bring but given the conservative nature of our business and having to work in a highly regulated environment, how can we build confidence to get us over that barrier.

Will having the regulators use the same AI make us more comfortable or will legislation be necessary to drive us forward?

Objective: Explore why PV has lagged behind with AI technology that is commonplace in other parts of our lives and business. Aspects of AI, such as machine learning, are used in areas such as early disease prediction, clinical diagnosis, outcome prediction and prognosis evaluation, personalized treatments, drug discovery, manufacturing, clinical trial research, and more.

In our personal lives, services like Amazon and Google use AI to understand and target their customers and we accept that as normal. The objective of this presentation is to explore the reluctance of accepting AI in PV and how we can move towards overcoming those obstacles. We will look at some real-life practical examples where AI in PV has worked and what it took to get there. Conclusion: We will show that the practical application of AI is achievable and has been achieved in the high volume environment of a regulatory authority.

Many of the AI features used by the RA, and the lessons learned from that project, can also be applied in industry, so why are we waiting? Introduction: Access to case narratives during signal assessment is crucial to provide a more complete picture of the cases [1], however patient confidentiality needs to be considered. Sharing of narratives while preserving privacy requires de-identification—the removal or replacement of personal identifiers.

Automating this task can help with increasing data load. To ensure patient confidentiality throughout the full pharmacovigilance process, the narratives should be de-identified early in the process. Person names—one of the more common identifiers in case narratives—can lead to in- direct identification of patients but are challenging to recognise in free text.

Objective: To develop and evaluate a method for automated de-identification of names in case narratives. Methods: We use an ensemble of BERT [2]—a state-of-the-art language model using deep-neural network—combined with hand-engineered rules for detecting names.

Our model is trained on i2b2 deidentification challenge data [3] combined with unprocessed data from the Yellow Card system[4] provided by the MHRA. Because names are rare in the Yellow Card data, the training dataset is prepared using active learning through an independent model.

Model testing is done on a separate, manually annotated dataset. Evaluation of the deidentification is guided by: 1 how often clinically relevant information is removed and 2 how identifiable the narratives that the model fails to completely de-identify are. We define three categories of identifiability: a Directly identifiable, where subject identification is very likely with the leaked information e.

Results: Out of the 71 narratives with names and initials, only 12 contained occurrences missed by the system. Manual evaluation found only one directly and one indirectly identifiable narrative due to leaks. It should be noted that the leaked direct identifier was a foreign, non-English name.

A single narrative may contain multiple occurrences of names, the table presents results per occurrence. Conclusion: Automated de-identification of names is possible without compromising clinically relevant information.

Our method can recognise and mask a vast majority of names and most initials while leaving most of the information untouched.

Qualitative evaluation shows that the rare leaks that occur tend not to make cases identifiable. Clinical stories are necessary for drug safety. Clin Med. J Biomed Inform.

Medicines and Healthcare products Regulatory Agency. The Yellow Card scheme: guidance for healthcare professionals, patients and the public [Internet].

Introduction: Metronidazole is a nitroimidazole antibacterial drug that is mostly used to treat anaerobic bacteria and protozoa infections. The adverse side effects of metronidazole include gastrointestinal upset, metallic taste, urticaria, headache, peripheral neuropathy. Metronidazole-induced pancreatitis has been rarely described in the literature so far. Objective: We report a rare case of an acute pancreatitis associated with metronidazole which occurred as a result of a prescription error.

Methods: This case was reported in February to The National Centre of Pharmacovigilance and evaluated according to the updated French method of causality assessment.

Results: A year-old male patient with a past medical history of chronic viral hepatitis B treated with entecavir since , presented to the surgery department with an acute onset of a severe epigastric pain radiating through to the back associated with hepatic colic with nausea and vomiting.

On exam, he had severe epigastric tenderness. Relative negatives in the history included, no lithiasis, no known drug allergies, and no alcohol consumption.

Patient symptoms and lipase improved within 3 days after metronidazole withdrawl and initiation of supportive care. Conclusion: The likelihood of metronidazole as the incriminating agent was likely in front of a suggestive delay and favorable outcome after the drug withdrawl. It was suggested a the possible dose-response mechanism between metronidazole use and occurrence of pancreatitis, and this case draw attention to the possible acute pancreatitis associated with metronidazole due to a prescription error.

Metronidazole-associated pancreatitis. Introduction: The possibilities of using current scientific principles to create tools to help give efficiency and help to nurses thereby reducing stress and the potential for errors. Also enable patients to maintain independence and less outside contact as technology is used to expand the reach of telehealth.

Solutions will be adaptable for independent use by the sight, hearing and mentally challenged. The 1st hurdle is to make it easier for patients and staff to accomplish what they have to do safely and consistently. Objective: To simplify the taking of all drugs and supplements using IoT technology.

This a paradigm shift from the many efforts to mitigate the challenges of the many aspects of drug delivery. Here medication is always kept in the labelled, legal safety of the original dispensed container until consumed. Safety concerns of pre-pouring will no longer exist. Authentic real-tine medication usage data will be available. ISoP and other safety management organizations will be able to execute many tasks with precision. Methods: The innovation is a multi-compartment device that holds a medication container in each compartment.

The device has a display that resides in the lid or may be at the front of a drawer type or wall mounted unit. The concept of assigned location forms the basis for these innovations. Stored instructions for many aspects of care and follow-up resides in the device and will be communicated via the display appropriately.

It can be connected to a larger display, cellphone or other mobile device. Medicine containers are scanned to capture dosing instructions. The assigned location lights up.

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A cluster separation measure. With note prot. Operating methods 5. Analysis of individual opioids show significant signals for QT prolongation for each drug. IEEE Int. A total EDTA-k2 anticoagulant venous whole blood samples were collected: 70 control patients blood donors with a normal complete count blood and negative VES, and samples hospitalized at the emergency department with symptoms attributable to sepsis with PCT request.❿
 
 

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