The authors raise several concerns with the interim phase 3 trial data reported for the Sputnik V COVID-19 vaccine. They found inconsistencies in the reported data, including discrepancies in the numbers of participants between tables and figures. Additionally, the authors question the highly coincidental efficacy results reported across age groups and find issues with lack of access to the full trial protocol and raw data. They invite investigators to make the full data publicly available for independent scrutiny.
Disease Network is the science that has emerged to diagnose a disease from a network aspect
specifically. Networks are the group that interconnect to each others similarly disease networks are
the one that reveal concelled connection among apparently independent biomedical entities like
physiologic process, signaling receptors, in addition to genetic code, also they prove to exists
intitutive in addition to powerful way to learn/discover or diagnose a disease.Due to these networks,
we can now consume the elderly drugs and its method to learn/discover the new drug
accordingly.Example- Colchicine is used in gout but after repurposing it is also used in mediterranean
fever. This is because there are many factors that affect the body during mediterranean fever and
gout, we know that gout is a form of arthritis that causes pain in joints also mediterranean fever is the
one which is accompanied by pain in joints, therefore colchicine is used as a repurposed drug again.In
repurposing of medicines or drugs we first analyse the change in symptoms and identify the target
organ and accorgingly we produce a drug that is compatible with pharmacokinetics of the body. As
the availablity of transcriptomic,proteomic and metabolomic data sources are increasing day by day it helps in classification of disease .Also there are some networks reffered to as complex networks which can be called as collection of linked junctions/ nodes
Avoidable Patient Harm and Resulting Liability Arete-Zoe, LLC
Avoidable Patient Harm and Resulting Liability
What would it take to improve our insight into the cost of avoidable patient harm?
Medications are the most frequent cause of adverse events in clinical settings.
Some of the most devastating drug-related injuries include Steven-Johnson Syndrome, drug-related liver injury or bone marrow failure. These events, however rare, are among those that are very expensive to treat and often leave long-lasting damage.
The substantial consequences of adverse drug events are hospital admissions and readmissions, prolonged hospital stay, additional therapeutic interventions and increased demand on staff. For the patient, in addition to all the misery and pain they suffer, adverse drug events mean time away from work, loss of income and additional medical expenses.
Survival guide to stem cell research and therapiesArete-Zoe, LLC
Survival guide to stem cell research and therapies provides comprehensive guidance to publicly available resource materials, libraries and registries for people who are interested in understanding currently available treatment options involving human stem cells.
Potential: The first section explains how stem cells are currently used in research, drug testing, and therapy, and how they have to be manipulated before transfer to make any treatments possible.
Classification: Origin and ability of stem cells to differentiate into different cell types determine how different types of stem cells are typically used.
Clinical Research: In this section, we will introduce the two most important registries of clinical trials: NIH registry ClinicalTrials gov and WHO International Clinical Trials Registry Platform. A project is part of this section to give students the opportunity to get hands-on experience with collecting and collating relevant information from registries and libraries, and interpretation of the findings. Real-time interactive sessions are included to allow students to ask questions and offer additional guidance.
Patient Demand: In this section, we briefly introduce challenges relating to marketing claims, objective outcome measures, advertising strategies, and patient autonomy.
Regulatory and Legal Framework: Stem cell therapies are regulated differently in various countries around the world. In this section, we will focus on regulations that govern stem cell research and therapies in the U.S. and in the European Union. Policies on stem cell research are driven by ethical concerns relating to research that utilizes human embryos. China recently announced new ethical guidelines and new rules for its stem cell clinics, regulating both trials and treatments.
Professional Societies: The last section explains the role of professional societies in stem cell research and therapies.
Presentation at Advanced Intelligent Systems for Sustainable Development (AISSD 2021) 20-22 August 2021 organized by the scientific research group in Egypt with Collaboration with Faculty of Computers and AI, Cairo University and the Chinese University in Egypt
Disease Network is the science that has emerged to diagnose a disease from a network aspect
specifically. Networks are the group that interconnect to each others similarly disease networks are
the one that reveal concelled connection among apparently independent biomedical entities like
physiologic process, signaling receptors, in addition to genetic code, also they prove to exists
intitutive in addition to powerful way to learn/discover or diagnose a disease.Due to these networks,
we can now consume the elderly drugs and its method to learn/discover the new drug
accordingly.Example- Colchicine is used in gout but after repurposing it is also used in mediterranean
fever. This is because there are many factors that affect the body during mediterranean fever and
gout, we know that gout is a form of arthritis that causes pain in joints also mediterranean fever is the
one which is accompanied by pain in joints, therefore colchicine is used as a repurposed drug again.In
repurposing of medicines or drugs we first analyse the change in symptoms and identify the target
organ and accorgingly we produce a drug that is compatible with pharmacokinetics of the body. As
the availablity of transcriptomic,proteomic and metabolomic data sources are increasing day by day it helps in classification of disease .Also there are some networks reffered to as complex networks which can be called as collection of linked junctions/ nodes
Avoidable Patient Harm and Resulting Liability Arete-Zoe, LLC
Avoidable Patient Harm and Resulting Liability
What would it take to improve our insight into the cost of avoidable patient harm?
Medications are the most frequent cause of adverse events in clinical settings.
Some of the most devastating drug-related injuries include Steven-Johnson Syndrome, drug-related liver injury or bone marrow failure. These events, however rare, are among those that are very expensive to treat and often leave long-lasting damage.
The substantial consequences of adverse drug events are hospital admissions and readmissions, prolonged hospital stay, additional therapeutic interventions and increased demand on staff. For the patient, in addition to all the misery and pain they suffer, adverse drug events mean time away from work, loss of income and additional medical expenses.
Survival guide to stem cell research and therapiesArete-Zoe, LLC
Survival guide to stem cell research and therapies provides comprehensive guidance to publicly available resource materials, libraries and registries for people who are interested in understanding currently available treatment options involving human stem cells.
Potential: The first section explains how stem cells are currently used in research, drug testing, and therapy, and how they have to be manipulated before transfer to make any treatments possible.
Classification: Origin and ability of stem cells to differentiate into different cell types determine how different types of stem cells are typically used.
Clinical Research: In this section, we will introduce the two most important registries of clinical trials: NIH registry ClinicalTrials gov and WHO International Clinical Trials Registry Platform. A project is part of this section to give students the opportunity to get hands-on experience with collecting and collating relevant information from registries and libraries, and interpretation of the findings. Real-time interactive sessions are included to allow students to ask questions and offer additional guidance.
Patient Demand: In this section, we briefly introduce challenges relating to marketing claims, objective outcome measures, advertising strategies, and patient autonomy.
Regulatory and Legal Framework: Stem cell therapies are regulated differently in various countries around the world. In this section, we will focus on regulations that govern stem cell research and therapies in the U.S. and in the European Union. Policies on stem cell research are driven by ethical concerns relating to research that utilizes human embryos. China recently announced new ethical guidelines and new rules for its stem cell clinics, regulating both trials and treatments.
Professional Societies: The last section explains the role of professional societies in stem cell research and therapies.
Presentation at Advanced Intelligent Systems for Sustainable Development (AISSD 2021) 20-22 August 2021 organized by the scientific research group in Egypt with Collaboration with Faculty of Computers and AI, Cairo University and the Chinese University in Egypt
The slides from the keynote given by Dr. Dan Malone RPh, PhD at the First International Drug-Drug Interaction Knowledge Representation Workshop on October 6th 2014 (http://icbo14.com/sessions/drug-drug-interaction-knowledge-representation-workshop/). Posted with his permission.
Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardi...Richard Boyce, PhD
A presentation of a new adverse drug event evidence base (Laertes - http://goo.gl/nZSqVw) within a standard framework for clinical research (OHDSI - www.ohdsi.org) made at the American Medical Informatics Association Joint Summits on Translational Research on 3/26/2015
The value of real-world evidence for clinicians and clinical researchers in t...Arete-Zoe, LLC
In the midst of a rapidly spreading global pandemic, real-world evidence can offer invaluable insight into the most promising treatments, risk factors, and not only predict but suggest how to improve outcomes. Despite overwhelming news coverage, significant knowledge gaps regarding COVID-19 persist. The current uncertainties regarding incidence and the case fatality rate can only be addressed by widespread testing. But the paucity of testing, and diversity of approaches implemented in different countries, particularly among the general asymptomatic public, perpetuates a lack of understanding about spread and infectivity. The essential indicators that would describe the pandemic more accurately can be obtained using real-world data (RWD). To that purpose, we designed a data collection tool to collect data from hospitals that treat COVID-19 patients. The captured data will enhance our understanding of the COVID-19 pandemic, identify risk factors relevant for triage, relate to other similar seasonal infections and gain insight into the safety and efficacy of experimental and off-label therapies. Knowledge derived from a focused data collection effort will enable clinicians to adjust rapidly clinical protocols and discontinue interventions that turn out to be ineffective or harmful. By deploying our elegantly designed survey to capture routine clinical indicators, we avoid placing an additional burden on practitioners. Systematically generating real-world evidence can decrease the time to insight compared to randomized clinical trials, improving the odds for patients in rapidly changing conditions.
Initial progress on the journey toward an open source potential drug-drug int...Richard Boyce, PhD
Presentation given at the 33rd VistA Community Meeting - George Mason University focusing on progress towards and open source potential drug interaction knowledge base
The Opioid Epidemic: An Important Auditor UpdatePYA, P.C.
PYA Tampa Office Managing Principal Angie Caldwell and Consulting Senior Manager Sarah Bowman addressed “The Opioid Epidemic: An Important Auditor Update” in their presentation. They:
Provided an overview of the scope of the opioid crisis, emerging trends in opioid abuse, and recent regulatory activity.
Analyzed key internal control risk areas to prevent drug diversion.
Reviewed specific examples of monitoring for fraud and abuse related to the opioid epidemic.
Clinical Research Informatics Year-in-ReviewPeter Embi
Peter Embi's 2018 Clinical Research Informatics Year-in-Review. Presented as closing Keynote address at the 2018 AMIA Informatics Summit in San Francisco, CA.
Discuss about Al, machine learning, and the hype cycle
Discuss the knowledge-based classification of proteins
Discuss applications of AI/ML to drug discovery
Different Stages of Medical Device Development and Drug Development: PepgraDi...PEPGRA Healthcare
The difference between medical device product development and pharmaceuticals that are supposed to be launched are based on industry composition where above 80% small and medium-sized companies require medical devices and large multinational organizations seek new medicines. Pepgra gives you the different stages of Medical Device Development and Drug Development, some are:
1. Lead discovery optimization
2. Pre-clinical Research
3.. Clinical Research
4. Post- Market safety monitoring
Continue Reading: https://bit.ly/3ryCQC4
Youtube: https://www.youtube.com/watch?v=cYz_BOArGhA
If you need any further information, then please contact via
Email us: sales.cro@pepgra.com
Whatsapp: +91 9884350006
Cell centered database for immunology and cancer research feb252016Ann-Marie Roche
Determining the cellular mechanisms of diseases is a crucial requirement for understanding the causes and progression of diseases, predicting outcomes, and developing new treatments. Often relevant information, e.g. what cells are involved in a disease or what effects does a drug have on cells, is scattered across many papers and journals, which makes it difficult for researchers to be sure they have a complete picture. Using Elsevier’s automated text mining technology, we have created a new cell-centered database consisting of 850 000 facts captured from more than 24 million PubMed abstracts and 3.5 million full text articles for use in Pathway Studio. This database focused primarily on cellular aspects of immunology and immuno-oncology can be used to summarize and visualize published research, and to analyze experimental data.
Learn how to use Pathway Studio to explore biomarkers and brain regions. With the addition of highly sophisticated visualization tools, users can interactively explore the vast number of connections created to help unravel disease biology. In addition, an innovative new taxonomy based on brain region identifications will be presented. Together, these innovations can be applied to rapidly increase the knowledge of diseases based on published findings.
Breaking news hit early this week regarding potential problems with Johnson & Johnson’s one-shot COVID vaccine, causing the FDA and the CDC to recommend pausing the administration of the vaccine until further investigation can be completed. On top of canceled or rescheduled vaccine appointments, this news left many people wondering what this means for the overall vaccine administration efforts and what changes they could expect to see...
De-Risking the Phase II to Phase III Advancement Decision: Sound Science, Cri...lisanatanson
Lisa presented an analysis of Phase II program metrics comparing those of drugs that failed late in development (Phase III or filing) versus those that ultimately gained U.S. licensure. Findings indicate that late failures conducted fewer Phase II trials with lower median patient enrollment and advanced on weaker efficacy evidence.
The slides from the keynote given by Dr. Dan Malone RPh, PhD at the First International Drug-Drug Interaction Knowledge Representation Workshop on October 6th 2014 (http://icbo14.com/sessions/drug-drug-interaction-knowledge-representation-workshop/). Posted with his permission.
Piloting a Comprehensive Knowledge Base for Pharmacovigilance Using Standardi...Richard Boyce, PhD
A presentation of a new adverse drug event evidence base (Laertes - http://goo.gl/nZSqVw) within a standard framework for clinical research (OHDSI - www.ohdsi.org) made at the American Medical Informatics Association Joint Summits on Translational Research on 3/26/2015
The value of real-world evidence for clinicians and clinical researchers in t...Arete-Zoe, LLC
In the midst of a rapidly spreading global pandemic, real-world evidence can offer invaluable insight into the most promising treatments, risk factors, and not only predict but suggest how to improve outcomes. Despite overwhelming news coverage, significant knowledge gaps regarding COVID-19 persist. The current uncertainties regarding incidence and the case fatality rate can only be addressed by widespread testing. But the paucity of testing, and diversity of approaches implemented in different countries, particularly among the general asymptomatic public, perpetuates a lack of understanding about spread and infectivity. The essential indicators that would describe the pandemic more accurately can be obtained using real-world data (RWD). To that purpose, we designed a data collection tool to collect data from hospitals that treat COVID-19 patients. The captured data will enhance our understanding of the COVID-19 pandemic, identify risk factors relevant for triage, relate to other similar seasonal infections and gain insight into the safety and efficacy of experimental and off-label therapies. Knowledge derived from a focused data collection effort will enable clinicians to adjust rapidly clinical protocols and discontinue interventions that turn out to be ineffective or harmful. By deploying our elegantly designed survey to capture routine clinical indicators, we avoid placing an additional burden on practitioners. Systematically generating real-world evidence can decrease the time to insight compared to randomized clinical trials, improving the odds for patients in rapidly changing conditions.
Initial progress on the journey toward an open source potential drug-drug int...Richard Boyce, PhD
Presentation given at the 33rd VistA Community Meeting - George Mason University focusing on progress towards and open source potential drug interaction knowledge base
The Opioid Epidemic: An Important Auditor UpdatePYA, P.C.
PYA Tampa Office Managing Principal Angie Caldwell and Consulting Senior Manager Sarah Bowman addressed “The Opioid Epidemic: An Important Auditor Update” in their presentation. They:
Provided an overview of the scope of the opioid crisis, emerging trends in opioid abuse, and recent regulatory activity.
Analyzed key internal control risk areas to prevent drug diversion.
Reviewed specific examples of monitoring for fraud and abuse related to the opioid epidemic.
Clinical Research Informatics Year-in-ReviewPeter Embi
Peter Embi's 2018 Clinical Research Informatics Year-in-Review. Presented as closing Keynote address at the 2018 AMIA Informatics Summit in San Francisco, CA.
Discuss about Al, machine learning, and the hype cycle
Discuss the knowledge-based classification of proteins
Discuss applications of AI/ML to drug discovery
Different Stages of Medical Device Development and Drug Development: PepgraDi...PEPGRA Healthcare
The difference between medical device product development and pharmaceuticals that are supposed to be launched are based on industry composition where above 80% small and medium-sized companies require medical devices and large multinational organizations seek new medicines. Pepgra gives you the different stages of Medical Device Development and Drug Development, some are:
1. Lead discovery optimization
2. Pre-clinical Research
3.. Clinical Research
4. Post- Market safety monitoring
Continue Reading: https://bit.ly/3ryCQC4
Youtube: https://www.youtube.com/watch?v=cYz_BOArGhA
If you need any further information, then please contact via
Email us: sales.cro@pepgra.com
Whatsapp: +91 9884350006
Cell centered database for immunology and cancer research feb252016Ann-Marie Roche
Determining the cellular mechanisms of diseases is a crucial requirement for understanding the causes and progression of diseases, predicting outcomes, and developing new treatments. Often relevant information, e.g. what cells are involved in a disease or what effects does a drug have on cells, is scattered across many papers and journals, which makes it difficult for researchers to be sure they have a complete picture. Using Elsevier’s automated text mining technology, we have created a new cell-centered database consisting of 850 000 facts captured from more than 24 million PubMed abstracts and 3.5 million full text articles for use in Pathway Studio. This database focused primarily on cellular aspects of immunology and immuno-oncology can be used to summarize and visualize published research, and to analyze experimental data.
Learn how to use Pathway Studio to explore biomarkers and brain regions. With the addition of highly sophisticated visualization tools, users can interactively explore the vast number of connections created to help unravel disease biology. In addition, an innovative new taxonomy based on brain region identifications will be presented. Together, these innovations can be applied to rapidly increase the knowledge of diseases based on published findings.
Breaking news hit early this week regarding potential problems with Johnson & Johnson’s one-shot COVID vaccine, causing the FDA and the CDC to recommend pausing the administration of the vaccine until further investigation can be completed. On top of canceled or rescheduled vaccine appointments, this news left many people wondering what this means for the overall vaccine administration efforts and what changes they could expect to see...
De-Risking the Phase II to Phase III Advancement Decision: Sound Science, Cri...lisanatanson
Lisa presented an analysis of Phase II program metrics comparing those of drugs that failed late in development (Phase III or filing) versus those that ultimately gained U.S. licensure. Findings indicate that late failures conducted fewer Phase II trials with lower median patient enrollment and advanced on weaker efficacy evidence.
An evaluation of community pharmacists’ readiness to implement the Falsified ...RavinaBarrett
Pharmacies are not FMD compliant and limited practical help and support seems available. A lack of resources, knowledge, competency, training and confidence makes this a difficult directive to implement successfully. Improved patient safety is anticipated, but difficult to quantify.
This paper helps in foreseeing diabetes by applying data mining strategy. The revelation of information
from clinical datasets is significant so as to make powerful medical determination. The point of data mining is to
extricate information from data put away in dataset and produce clear and reasonable depiction of examples. Diabetes
is an interminable sickness and a significant general wellbeing challenge around the world. Utilizing data mining
techniques by taking hba1c test data to help individuals to predict diabetes has increase significant fame. In this paper,
six classification models are used to classify a diabetic or non-diabetic patient and male and female patients. The
dataset utilized is gathered from a Diagnostics and research laboratory Liaquat university of medical and health
sciences Jamshoro, which gathers the data of patients with diabetes, without diabetes by taking blood sample of patient
and performing hba1c. We utilized Weka tool for the analysis diabetes, no-diabetic examination. Out of six
classification algorithms, four algorithms depict hundred percent accuracy on train and test data.
KEY WORDS: Data mining, Diabetes, HbA1c, Classification models, Weka.
An AI-based Decision Platform built using unified data model, incorporating systems biology topics for unit analysis using semi-supervised learning models
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
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These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
CDSCO and Phamacovigilance {Regulatory body in India}NEHA GUPTA
The Central Drugs Standard Control Organization (CDSCO) is India's national regulatory body for pharmaceuticals and medical devices. Operating under the Directorate General of Health Services, Ministry of Health & Family Welfare, Government of India, the CDSCO is responsible for approving new drugs, conducting clinical trials, setting standards for drugs, controlling the quality of imported drugs, and coordinating the activities of State Drug Control Organizations by providing expert advice.
Pharmacovigilance, on the other hand, is the science and activities related to the detection, assessment, understanding, and prevention of adverse effects or any other drug-related problems. The primary aim of pharmacovigilance is to ensure the safety and efficacy of medicines, thereby protecting public health.
In India, pharmacovigilance activities are monitored by the Pharmacovigilance Programme of India (PvPI), which works closely with CDSCO to collect, analyze, and act upon data regarding adverse drug reactions (ADRs). Together, they play a critical role in ensuring that the benefits of drugs outweigh their risks, maintaining high standards of patient safety, and promoting the rational use of medicines.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Hemodialysis: Chapter 3, Dialysis Water Unit - Dr.Gawad
Sputnik, su The Lancet la lettera che contesta i dati della sperimentazione
1. Correspondence
Submissions should be
made via our electronic
submission system at
http://ees.elsevier.com/
thelancet/
www.thelancet.com Published online May 12, 2021 https://doi.org/10.1016/S0140-6736(21)00899-0 1
Data discrepancies and
substandard reporting
of interim data of
SputnikV phase 3 trial
Restricted access to data hampers
trust in research. Access to data
underpinning study findings is
imperative to check and confirm
the findings claimed. It is even more
serious if there are apparent errors
and numerical inconsistencies in
the statistics and results presented.
Regrettably, this seems to be what is
happening in the case of the Sputnik V
phase 3 trial.1
Several experts3,4
found proble
matic data in the published
phase 1/2 results.2
We have made
multiple independent requests for
access to the raw dataset, but these
were never answered. Despite publicly
denying some problems, formal
corrections were made to the Article,2
thus addressing some concerns.5
Notwithstanding the previous issues
and lack of transparency, the interim
results from the phase 3 trial of the
Sputnik V vaccine1
again raise serious
concerns.
We have a serious concern regarding
the availability of the data from
which the investigators draw their
conclusions. The investigators state
that data will not be shared before the
trial is completed, and then only by
approval of stakeholders, including a
so-called security department. Data
sharing is one of the cornerstones of
research integrity; it should not be
conditional and should follow the
FAIR principles.
The second concern pertains to the
trial protocol, as already described in
an open letter by the Russian Society
for Evidence-Based Medicine.3
The
Sputnik V investigators mention that
three interim analyses were added
to the study on Nov 5, 2020,1
but
this change was not recorded on
ClinicalTrials.gov (NCT04530396).
Unfortunately, the full study protocol
has not been made publicly available,
so the rationale behind this change
or the type I error rate adjustment,
if any, is not known. According
to the ClinicalTrials.gov record
NCT04530396, the primary outcome
was changed on Sept 17, 2020.
Initially, the primary outcome was to
be assessed after the first dose, but the
evaluation was postponed to after the
second dose. The presented primary
result (efficacy of 91·6%) is dependent
on this change, but the reasons for the
change have not been made public.
Moreover, the latest ClinicalTrials.
gov record (Jan 22, 2021) defines
the primary outcome inconsistently:
“Primary Outcome Measures: per
centage of trial subjects...after the first
dose...based on the percentage...after
the second dose”.
Besidesthese protocol amendments,
the definition of the primary outcome
is unclear in the Article,1
where it says
that when COVID-19 was suspected,
participants were assessed with
“COVID-19 diagnostic protocols,
including PCR testing”. Here, we lack
some crucial information, such as
the clinical parameters determining
suspected COVID-19, what diagnostic
protocols were used, when the PCR
testing was done, what specific
method was used, or how many
amplification cycles were used. The
way cases of suspected COVID-19 were
defined could have led to bias in PCR
testing used to assess the number of
confirmed COVID-19 cases, which is
crucial for the efficacy determination.
A final point of concern about
the study protocol relates to the
enrolment and randomisation
of patients. According to the trial
profile in figure 1 of the Article,1
35 963 individuals were screened and
21 977 individuals were randomised.
The ClinicalTrials.gov record for
NCT04530396 (Jan 20, 2021)
mentions that 33 758 patients were
enrolled. We would expect that this
last figure should be equal to either
the number of participants screened
or randomised. Moreover, there is no
information about what caused the
exclusion of 13 986 participants, as per
the trial profile.
The third concern relates to
the data reported and numerical
results. We found the following
data inconsistencies: (1) in
figure 2 of the Article,1
data for the
vaccinated group on day 20 refer
to more individuals than at day 10,
as if there was either information
missing for 100 participants at
day 10, or participants were enrolled
after day 10 (figure 2 was formally
corrected on Feb 20, 2021, but the
correction statement did not state the
reasons leading to such correction);
and (2) in table S1 of the appendix,1
the number of participants reported
for the different vaccinated age
cohorts do not add up to the reported
total (n=338 vs n=342). With such
inconsistencies, we question the
accuracy of the reported data.
A very peculiar result of the major
subgroup analysis of the primary
outcome caught our attention. The
vaccine efficacy was said to be high
for all age groups. The reported
percentages were 91·9% in the
18–30-year age group, 90·0% in the
31–40-year age group, 91·3% in
the 41–50-year age group, 92·7% in
the 51–60-year age group, and 91·8%
in participants older than 60 years. We
checked the homogeneity of vaccine
efficacy across age groups (interaction
tests): the p value of the Tarone-
adjusted Breslow-Daytest was 0·9963,
and the p value of a non-asymptotic
test was 0·9956,6
indicating a
very low probability of observing a
homogeneity this good if the actual
homogeneity is perfect. By applying
18 other homogeneity tests (six in
table 1, seven in table S6, six in table 2
of the Article1
), we could not find other
major abnormality in the overall
distribution of p values (appendix).
We also found some highly
coincidental results reported in table
S3 of the appendix. In particular,
two upper confidence limit values for
two different distributions (placebo
group at baseline for unstimulated and
For the FAIR principles see
https://www.go-fair.org/fair-
principles/
See Online for appendix
Published Online
May 12, 2021
https://doi.org/10.1016/
S0140-6736(21)00899-0
2. Correspondence
2 www.thelancet.com Published online May 12, 2021 https://doi.org/10.1016/S0140-6736(21)00899-0
3 VlassovV, Rebrova O, AksenovV. Commentary
on the publication of preliminary results of the
Sputnik-V vaccine phase 3 trial. Feb 5, 2021.
http://osdm.org/english/2021/02/06/
a-commentary-on-the-publication-of-
preliminary-results-of-the-sputnik-v-vaccine-
phase-3-trial/ (accessed Feb 18, 2021).
4 Bucci E, Andreev K, Björkman A, et al.
Safety and efficacy of the Russian COVID-19
vaccine: more information needed. Lancet
2020; 396: e53
5 Logunov DY, Dolzhikova IV,Tukhvatullin AI,
Shcheblyakov DV. Safety and efficacy of the
Russian COVID-19 vaccine: more information
needed—Authors’ reply. Lancet 2020;
396: e54–55.
6 Sangnawakij P, Böhning D, Holling H.
On the exact null-distribution of a test for
homogeneity of the risk ratio in meta-analysis
of studies with rare events. J Stat Comput Simul
2021; 91: 420–34.
antigen-stimulated measures) both
equal 0·708. Of course, this is possible,
but we call once more for access to
the data from which the statistics
originate for close scrutiny.
In line with our earlier concerns
with the phase 1/2 results4
and
the substandard reporting of the
phase 3 interim results,1
we invite
the investigators once more to
make publicly available the data on
which their analyses rely. Access to
the protocol, its amendments, and
the individual patient records is
paramount, as much for clarification
as for open discussion of all the issues.
We also invite the Editors of
The Lancet to clarify the consequences
of further denying access to the data
needed for assessing the results
presented, should the authors still
deny it.
EMB is the owner of Resis Srl. All other authors
declare no competing interests. Code to test the
homogeneity of vaccine efficacy across age groups
is available on the Open Science Framework,
https://osf.io/sudxe/
*Enrico M Bucci, Johannes Berkhof,
André Gillibert, Gowri Gopalakrishna,
Raffaele A Calogero, Lex M Bouter,
Konstantin Andreev, Florian Naudet,
VasiliyVlassov
enrico.bucci@temple.edu
Sbarro Institute,Temple University Department of
Biology, Philadelphia, 19122 PA, USA (EMB);
Department of Epidemiology and Data Science,
Amsterdam University Medical Centers,
Amsterdam, Netherlands (JB, GG, LMB);
Department of Biostatistics, CHU Rouen, Rouen,
France (AG); Department of Molecular
Biotechnology and Health Sciences, University of
Turin,Turin, Italy (RAC); Department of Philosophy,
Faculty of Humanities,Vrije Universiteit Amsterdam
(LMB); Department of Molecular Biosciences,
Howard Hughes Medical Institute, Northwestern
University, Evanston, IL, USA (KA); Centre
Hospitalier Universitaire de Rennes, Université de
Rennes, Rennes, France (FN); Higher School of
Economics University, Moscow, Russia (VV)
1 Logunov DY, Dolzhikova IV,
Shcheblyakov DV, et al. Safety and efficacy of
an rAd26 and rAd5 vector-based heterologous
prime-boost COVID-19 vaccine: an interim
analysis of a randomised controlled phase 3
trial in Russia. Lancet 2021; 397: 671–81.
2 Logunov DY, Dolzhikova IV, Zubkova OV, et al.
Safety and immunogenicity of an rAd26 and
rAd5 vector-based heterologous prime-boost
COVID-19 vaccine in two formulations:
two open, non-randomized phase 1/2 studies
from Russia. Lancet 2020; 396: 887–97.