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Size 1. Title BIOS 6. Title La - internal speakers do not switch off when headset is plugged in - General Information. Title Wiederherstellung installierter Software, Betriebsanleitung de - Manuals. Size 3. In March , Microsoft announced that it would display notifications informing users on Windows 7 devices of the upcoming end of extended support for the platform, and direct users to a website urging them to upgrade to Windows 10 or purchase new hardware.
This dialog will be similar to the previous Windows 10 upgrade prompts, but will not explicitly mention Windows Privacy advocates and other critics have expressed concern regarding Windows 10's privacy policies and its collection and use of customer data. Users can opt out from most of this data collection, [] [] but telemetry data for error reporting and usage is also sent to Microsoft, and this cannot be disabled on non-Enterprise editions of Windows Rock Paper Shotgun writer Alec Meer argued that Microsoft's intent for this data collection lacked transparency, stating that "there is no world in which 45 pages of policy documents and opt-out settings split across 13 different settings screens and an external website constitutes 'real transparency'.
The Russian government had passed a federal law requiring all online services to store the data of Russian users on servers within the country by September or be blocked. But Microsoft is held to a different standard than other companies".
The Microsoft Services agreement reads that the company's online services may automatically "download software updates or configuration changes, including those that prevent you from accessing the Services, playing counterfeit games, or using unauthorized hardware peripheral devices. In September , Microsoft hid the option to create a local account during a fresh installation if a PC is connected to the internet. This move was criticized by users who did not want to use an online Microsoft account.
In late-July , Windows Defender began to classify modifications of the hosts file that block Microsoft telemetry servers as being a severe security risk. From Wikipedia, the free encyclopedia. This is the latest accepted revision , reviewed on 20 December This article is about the operating system for personal computers. For the related now discontinued operating system for mobile devices, see Windows 10 Mobile. For the series of operating systems produced from to , see Windows 9x.
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Retrieved May 14, Retrieved September 10, PC World. March 16, StatCounter Global Stats. Retrieved June 15, Retrieved April 1, Retrieved December 10, Retrieved July 30, January 6, Retrieved May 2, Houston Chronicle. Hearst Corporation. Archived from the original on July 22, The Verge. Vox Media. Retrieved May 26, Retrieved April 22, Retrieved April 7, Retrieved September 30, The Start menu is coming back to Windows".
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FLAC files all on its own". PC Games Hardware in German. May 5, Retrieved April 11, DirectX Developer Blog. Archived from the original on October 4, Retrieved October 3, October 3, March 21, Retrieved June 20, PC Perspective. Archived from the original on September 5, Retrieved August 22, May 13, Retrieved May 13, Retrieved February 3, May 2, February 3, Retrieved March 11, April 21, Retrieved April 23, Retrieved March 8, Retrieved October 1, October June 21, Retrieved June 22, Conde Nast Digital.
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March 19, Retrieved March 19, Retrieved August 13, July 31, Windows 10 blog. Microsoft Corporation. October 12, 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. The container is placed within the compartment and receives an alert at dosing times. The compartment stays lit until the nurse picks up and replaces the container. Video may be activated. Biometric access ensures identity and pill count and time are automatically recorded.
Results: Feasibility indicates that the must touch to silent feature is a powerful feature that aids adherence. Also the timing methods that ensures safe dosing separation helps to ensure all doses are taken in a given day even if late taking a dose.
Relative time rather than time of day dosing is used. Conclusion: Believed to be unsolvable, these discoveries will open the door to the science of individual ingestion by effortlessly notifying and guiding individuals in the consumption and effects of medicines and other items for a safer and healthier life experience. Powerful data will be generated for use by ISoP. Introduction: The Summary of Product Characteristics for Ceftriaxone states that as with all beta-lactam antibacterial agents, serious and occasionally fatal hypersensitivity reactions have been reported [1].
However, the frequency is stated as unknown. Out of 46 reports to Ceftriaxone in the Uganda ADR database, 7 of these are of anaphylactic reactions, and one of them was fatal for the paediatric patient. It is not clear in cases of injurious or fatal drug effects who should bear the liability.
Objective: To present a case study of a successful legal resolution of a fatal medication error to Ceftriaxone with the involvement of the regulator. Methods: This is a retrospective case report. Results: A one-and-a-half-year-old male child was diagnosed with septicaemia with diarrhoea and admitted to a hospital.
Day one treatment with Ceftriaxone was stopped due to a reaction of difficulty in breathing. A switch to Ciprofloxacin happened and the patient began to improve. Due to a weekend staff shift change, the change to ciprofloxacin was not noted resulting in re-administration of ceftriaxone and anaphylaxis that caused the death of the patient despite all efforts to resuscitate.
National Drug Authority performed a causality assessment of the serious adverse event and found that administration of Ceftriaxone was related to the outcome of death. However, it was noted that this was a medication error with no malice aforethought and therefore the health care provider was not liable.
Publication of these results can aid in encouraging reporting rates among patients and providers. Ceftriaxone 1g Powder for solution for injection. Accessed March 9, General characteristics, economic burden, causative drugs and medical errors associated with medical damage litigation involving severe cutaneous adverse drug reactions in China. Journal of Clinical Pharmacy and Therapeutics. Liability associated with prescribing medications. Primary care companion to the Journal of clinical psychiatry.
Bhatt AD. Drug-related problems and adverse drug events: negligence, litigation and prevention. The Journal of the Association of Physicians of India. PMID: Physicians' liability for adverse drug reactions. Southern Medical Journal.
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