The COVID-19 pandemic has reshaped health and medical care in dramatic and subtle ways. Some of the less noticeable changes can only be revealed by analysis of millions of data, such as patient records, medical records, and clinical encounter reports.
Shoot these alone Datapoint It may provide an appetizing anecdote. When analyzed together, it can provide a bird’s-eye view of interesting interactions, reveal important trends, and provide them to clinicians and the general public. health Valuable clues that experts can inform both prevention and intervention.
Marinka Zitnik, assistant professor of biomedical informatics at Harvard Medical School’s Bravatnik Institute, uses data science and machine learning techniques to gather insights into disease onset and progression, treatment outcomes, and response to treatment.
Zitnik’s latest survey, survey published on October 5th Nature Computational ScienceAnalyze patterns of adverse dosing events before and during Pandemic..
In this study, Zitnik and co-author HMS postdoctoral fellow Xiang Zhang and Harvard University graduate researcher Marissa Sumathipala used more than 1.4 million medical reports on 2821 drugs.
Researchers found that the frequency of 54 adverse events increased during the pandemic, but overall, the number of adverse medication events decreased slightly. In addition, the analysis revealed a clear gender and age difference in possible adverse events.
The results have important implications for safe drug use and are a better way to stratify patients by risk profile to prevent or at least minimize medical inequality in emergencies. Researchers say they can tell.
Zitnik discussed her findings with Harvard Medicine News.
HMNews: What did you set out to achieve in this study?
Zitnik: Adverse events from drug use Prescription drugs More than 110,000 people died in the United States in 2019. The main motivation behind our study was to understand how the pandemic and the consequent confusion challenged the ability of the medical system to ensure the use of safe medicines. I wanted to know if there were worsening inequality between different patient groups and if there were any adverse events that would have been above or below what would have been expected if the pandemic had not occurred.
To answer these questions, we looked at patterns of drug-induced adverse events dating back seven years before the pandemic.I examined each past trend drag And each adverse event captured in the database to predict what is expected in 2o20. Next, I compared that forecast with what I actually saw in 2020. The difference between expectations and occurrences provided clues about the effects of the pandemic.
HMNews: What were some of the key discoveries?
Zitnik: First, we found that there was considerable variability in drug adverse events before and during the pandemic. We identified 64 types of adverse events with significantly altered patterns compared to pre-pandemic levels. To my surprise, 54 out of 64 adverse events increased during the pandemic. Why is this amazing? Such reports may be expected to decline due to restricted access to the medical system and the inability of patients to go to the hospital to report adverse events. That was certainly the case.
The total amount of reported adverse drug events decreased by 4.4% compared to pre-pandemic levels. The surprising part was that 54 harmful drug events increased in incidence during the pandemic. Second, it was found that during a pandemic, the pre-pandemic gender difference due to the side effects of the drug worsened. Compared to pre-pandemic levels, women suffered more adverse events than men, and their gender differences were found to persist across all age groups.
That was amazing to me. With access to such data, one can only imagine what the differences were between ethnic and racial groups. Third, clinical differences associated with drug side effects were found between age groups. Side effects such as anxiety and insomnia are increasing disproportionately in women and the elderly, suggesting that these are at-risk patient groups.
In summary, you can identify adverse events that change a particular risk, or adverse events that change risk due to external disruption, in this case COVID-19.
HMNews: What are the benefits of using big data and computational analysis to study changes in public health emergencies?
Zitnik: Many of the observations we made and the conclusions we reached were possible only because of the vast amount of data we analyzed. From January 2013 to September 2020, we mined more than 10 million reports from the National Adverse Event Reporting Database and surveyed the full range of approved medicines.
There are numerous previous studies on drug adverse events from the laboratory environment that focus on the molecular properties of drugs during pre-approval clinical trials. Patient safety studies conducted during the pandemic were also very limited, limited to a small number of drugs, a small number of reports, and a narrow time range for the treatment of COVID-19 or related conditions.
This extensive data analysis has enabled us to unravel these complex dependencies between pandemic effects, drug effects, and patient characteristics. This allowed us to identify changes in the status of adverse events in public health emergencies. This allowed us to see how these changes occur in different patient populations, as defined by gender, age, and other demographics.
An example is shown below. The drug remdesivir, which was on the market before the pandemic and was reused to treat COVID-19, was associated with the risk of hypoxia or hypoxia levels. Hypoxia has been reported as a new adverse event in a clinical trial of remdesivir for the treatment of COVID-19, but was previously unknown. Therefore, in this case, our analysis is how algorithmic models used on a population scale can identify otherwise rare and subtle events that do not appear until a large number of people start taking the drug. Is emphasized.
Such analysis helps with pharmacological vigilance for treatment, including treatments that are given urgent approval or converted to COVID-19, as in the case of remdesivir. Obviously, this type of population size analysis is not provided to clarify the cause behind the observation and the reason behind what.
However, this approach is valuable because it is a system-wide survey that allows you to zoom out to see the trees in the forest. What if we look at the size of the whole country, the United States, take different medicines, look at real patients with different illnesses, and capture all these complex interdependencies? I wanted to understand. Variables that include non-medical factors such as age, gender, and place of residence.
HMNews: What’s the next step?
Zitnik: What I’m most excited about is that this work provides a blueprint for how COVID-19 can be compared to other public health emergencies. I am very interested in comparing the impact of COVID-19 on safe drug use with the impact of an opioid crisis or hurricane or wildfire emergency that could also disrupt access to health care.
Is there anything I learned from COVID-19 that could be transferred to other public health emergencies? Can you develop forecast guidance for public health authorities based on these? Such insights inform drug prescribing practices and ensure patient safety by flagging individuals or groups of patients who may be at increased risk of adverse events in the event of a public health emergency. Expected to help improve.
These insights provide guidelines for identifying patients who may be disproportionately affected by certain preventable inequality and for identifying communities to contact public health professionals. You can design a tool that can automatically ask for the type of adverse event you are experiencing, a major challenge during a pandemic, that patients are using without necessarily coming to the hospital. The number of medicines.
In the long run, this type of large-scale analysis may break away from the universal approach and provide sufficient detailed data to help stratify the risk of side effects by patients based on a broad range. Characteristic.
Xiang Zhang et al, Population identification of different adverse events before and during a pandemic, Nature Computational Science (2021). DOI: 10.1038 / s43588-021-00138-4
Harvard Medical School
Quote: The adverse effects of drugs during the COVID-19 pandemic (October 14, 2021) are from https://medicalxpress.com/news/2021-10-adverse-drug-effects-covid-pandemic.html October 2021 Obtained on the 14th.
This document is subject to copyright. No part may be reproduced without written permission, except for fair transactions for personal investigation or research purposes. The content is provided for informational purposes only.
Adverse drug effects during the COVID-19 pandemic Source link Adverse drug effects during the COVID-19 pandemic
The post Adverse drug effects during the COVID-19 pandemic appeared first on California News Times.