Applying the principle 'First Do No Harm' during the pandemic.
Ontology highlight
ABSTRACT:
SUBMITTER: Katheria AC
PROVIDER: S-EPMC7753430 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeConflicting information on potential benefits of drugs as well as reports on hypothetical harm of commonly used drugs in COVID-19 treatment have challenged clinicians and healthcare systems. We analyzed the change in ambulatory drug utilization before, during, and after the first wave of the pandemic in 2020.MethodsWe explored dispensing data of nearly 19 000 pharmacies at the expense of the statutory health insurance funds covering 88% of Germany's population. We analyzed utilization of publicly discussed drugs with conflicting information. Drug utilization as number of packages dispensed per week from January to June 2020, reflecting 314 million claims, was compared with 2019.ResultsUtilization of hydroxychloroquine increased +110% during March 2020 and then slightly decreased until week April 13-19. Renin-angiotensin-aldosterone system inhibitors and simvastatin/atorvastatin increased, +78% and +74%, respectively, and subsequently decreased below 2019 levels. Utilization of azithromycin and all systemic antibiotics decreased continuously from March 2-8 until June to levels considerably lower compared to 2019 (June 22-28: azithromycin: -55%, all systemic antibiotics: -27%). Pneumococcal vaccines utilization initially increased +373%, followed by supply shortages. Paracetamol utilization showed an initial increase of +111%, mainly caused by an increase of over-the-counter dispensings.ConclusionsApart from the pandemic itself, the data suggest that dissemination of misinformation and unsound speculations as well as supply shortages influenced drug prescribing, utilization, and purchasing behavior. The findings can inform post-pandemic policy to prevent unfounded over- and underprescribing and off-label use as well as drug shortages during a public health crisis.
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Project description:The determination of food freshness along manufacturer-to-consumer transportation lines is a challenging problem that calls for cheap, simple, reliable, and nontoxic sensors inside food packaging. We present a novel approach for oxygen sensing in which the exposure time to oxygen-rather than the oxygen concentration per se-is monitored. We developed a nontoxic hybrid composite-based sensor consisting of graphite powder (conductive filler), clay (viscosity control filler) and linseed oil (the matrix). Upon exposure to oxygen, the insulating linseed oil is oxidized, leading to polymerization and shrinkage of the matrix and hence to an increase in the concentration of the electrically conductive graphite powder up to percolation, which serves as an indicator of food spoilage. In the developed sensor, the exposure time to oxygen (days to weeks) is obtained by measuring the electrical conductivity though the sensor. The sensor functionality could be tuned by changing the oil viscosity, the aspect ratio of the conductive filler, and/or the concentration of the clay, thereby adapting the sensor to monitoring the quality of food products with different sensitivities to oxygen exposure time (e.g., fish vs grain).
| S-EPMC7471990 | biostudies-literature
Project description:Anti-vaccination attitudes have been an issue since the development of the first vaccines. The increasing use of social media as a source of health information may contribute to vaccine hesitancy due to anti-vaccination content widely available on social media, including Twitter. Being able to identify anti-vaccination tweets could provide useful information for formulating strategies to reduce anti-vaccination sentiments among different groups. This study aims to evaluate the performance of different natural language processing models to identify anti-vaccination tweets that were published during the COVID-19 pandemic. We compared the performance of the bidirectional encoder representations from transformers (BERT) and the bidirectional long short-term memory networks with pre-trained GLoVe embeddings (Bi-LSTM) with classic machine learning methods including support vector machine (SVM) and naïve Bayes (NB). The results show that performance on the test set of the BERT model was: accuracy = 91.6%, precision = 93.4%, recall = 97.6%, F1 score = 95.5%, and AUC = 84.7%. Bi-LSTM model performance showed: accuracy = 89.8%, precision = 44.0%, recall = 47.2%, F1 score = 45.5%, and AUC = 85.8%. SVM with linear kernel performed at: accuracy = 92.3%, Precision = 19.5%, Recall = 78.6%, F1 score = 31.2%, and AUC = 85.6%. Complement NB demonstrated: accuracy = 88.8%, precision = 23.0%, recall = 32.8%, F1 score = 27.1%, and AUC = 62.7%. In conclusion, the BERT models outperformed the Bi-LSTM, SVM, and NB models in this task. Moreover, the BERT model achieved excellent performance and can be used to identify anti-vaccination tweets in future studies.
| S-EPMC8069687 | biostudies-literature
Project description:This study explored patterns of abuse, self-harm and thoughts of suicide/self-harm in the UK during the first month of the COVID-19 pandemic using data from the COVID-19 Social Study (n=44 775), a non-probability sample weighted to population proportions. The reported frequency of abuse, self-harm and thoughts of suicide/self-harm was higher among women, Black, Asian and minority ethnic (BAME) groups and people experiencing socioeconomic disadvantage, unemployment, disability, chronic physical illnesses, mental disorders and COVID-19 diagnosis. Psychiatric medications were the most common type of support being used, but fewer than half of those affected were accessing formal or informal support.
| S-EPMC7360935 | biostudies-literature
Project description:BackgroundPrior to the COVID-19 pandemic, cannabis use social practices often involved sharing prepared cannabis (joints/blunts/cigarettes) and cannabis-related paraphernalia. Previous studies have demonstrated that sharing paraphernalia for cannabis, tobacco, and crack cocaine is a risk factor for respiratory viral and bacterial infections. Although COVID-19 is a respiratory viral infection that spreads through droplets and airborne transmission, it is unclear if many individuals adopted harm reduction practices around sharing cannabis. This study: quantifies the prevalence of sharing prepared non-medical cannabis and cannabis-related paraphernalia reported before and during the pandemic; assesses changes in sharing of non-medical cannabis from before to during the pandemic; assess the association between frequency of non-medical cannabis use and sharing of cannabis during the pandemic; and describes how respondents obtained their cannabis and the reasons for changing their cannabis use during the pandemic to explain differences in sharing patterns.MethodsThis cross-sectional study used data collected from an anonymous, US-based web survey on cannabis-related behaviors from August to September 2020 (n = 1833). Participants were included if they reported using a mode of inhalation for non-medical cannabis consumption. We calculated proportional changes in sharing cannabis before/during the COVID-19 pandemic. Associations between frequency of cannabis use and cannabis sharing during the COVID-19 pandemic were assessed using logistic regression analysis.ResultsOverall, 1,112 participants reported non-medical cannabis use; 925 (83.2%) reported a mode of cannabis inhalation. More respondents reported no sharing during (24.9%) than before the pandemic (12.4%; p < 0.01); less respondents shared most of the time (19.5% before; 11.2% during; p < 0.01) and always during the pandemic (5.2% before; 3.1% during; p < 0.01). After adjusting for covariates, the odds of any sharing during the pandemic for those who reported ≥ weekly cannabis use was 0.53 (95% CI 0.38, 0.75) compared to those who reported ≤ monthly.ConclusionsSharing of prepared cannabis and cannabis-related paraphernalia decreased during the COVID-19 pandemic compared to before the pandemic. This finding suggests potential risk mitigation strategies taken by participants for COVID-19 prevention either directly through behavior change or indirectly through adherence to COVID-19 prevention recommendations. Harm reduction messaging around sharing of cannabis during surges of COVID-19 or other respiratory infections may provide benefit in reducing infection among those who use cannabis, especially as cannabis use in the USA continues to increase.
| S-EPMC9957690 | biostudies-literature
Project description: Not available
| S-EPMC7258628 | biostudies-literature
Project description:BACKGROUND:The widespread death and disruption caused by the COVID-19 pandemic has revealed deficiencies of existing institutions regarding the protection of human health and well-being. Both a lack of accurate and timely data and pervasive misinformation are causing increasing harm and growing tension between data privacy and public health concerns. OBJECTIVE:This aim of this paper is to describe how blockchain, with its distributed trust networks and cryptography-based security, can provide solutions to data-related trust problems. METHODS:Blockchain is being applied in innovative ways that are relevant to the current COVID-19 crisis. We describe examples of the challenges faced by existing technologies to track medical supplies and infected patients and how blockchain technology applications may help in these situations. RESULTS:This exploration of existing and potential applications of blockchain technology for medical care shows how the distributed governance structure and privacy-preserving features of blockchain can be used to create "trustless" systems that can help resolve the tension between maintaining privacy and addressing public health needs in the fight against COVID-19. CONCLUSIONS:Blockchain relies on a distributed, robust, secure, privacy-preserving, and immutable record framework that can positively transform the nature of trust, value sharing, and transactions. A nationally coordinated effort to explore blockchain to address the deficiencies of existing systems and a partnership of academia, researchers, business, and industry are suggested to expedite the adoption of blockchain in health care.
| S-EPMC7511222 | biostudies-literature
Project description:Ancient Yersinia pestis genomes from across Western Europe reveal early diversification during the First Pandemic (541–750)
| PRJEB29991 | ENA
Project description:ObjectiveTo identify the prevalence and predictors of (a) thoughts of suicide or self-harm among healthcare workers during the COVID-19 pandemic and (b) help-seeking among those healthcare workers with thoughts of suicide or self-harm.MethodAnalysis of data from the Australian COVID-19 Frontline Healthcare Workers Study, an online survey of healthcare workers conducted during the second wave of the COVID-19 pandemic in Australia. Outcomes of interest were thoughts of suicide or self-harm as measured through the Patient Health Questionnaire for depression and help-seeking behaviours.ResultsOverall, 819 (10.5%) of 7795 healthcare workers reported thoughts of suicide or self-harm over a 2-week period. Healthcare workers with these thoughts experienced higher rates of depression, anxiety, post-traumatic stress disorder and burnout than their peers. In multivariable models, the odds of suicide or self-harm thoughts were higher among workers who had friends or family infected with COVID-19 (odds ratio = 1.24, 95% confidence interval = [1.06, 1.47]), were living alone (odds ratio = 1.32, 95% confidence interval = [1.06, 1.64]), younger (⩽30 years cf. >50 years; odds ratio = 1.70, 95% confidence interval = 1.36-2.13), male (odds ratio = 1.81, 95% confidence interval = [1.49, 2.20]), had increased alcohol use (odds ratio = 1.58, 95% confidence interval = [1.35, 1.86]), poor physical health (odds ratio = 1.62, 95% confidence interval = [1.36, 1.92]), increased income worries (odds ratio = 1.81, 95% confidence interval = [1.54, 2.12]) or prior mental illness (odds ratio = 3.27, 95% confidence interval = [2.80, 3.82]). Having dependent children was protective (odds ratio = 0.75, 95% confidence interval = [0.61, 0.92]). Fewer than half (388/819) of the healthcare workers who reported thoughts of suicide or self-harm sought professional support. Healthcare workers with thoughts of suicide or self-harm were more likely to seek support if they were younger (⩽30 years cf. >50 years; odds ratio = 1.78, 95% confidence interval = [1.13, 2.82]) or had prior mental health concerns (odds ratio = 4.47, 95% confidence interval = [3.25, 6.14]).ConclusionOne in 10 Australian healthcare workers reported thoughts of suicide or self-harm during the pandemic, with certain groups being more vulnerable. Most healthcare workers with thoughts of suicide or self-harm did not seek professional help. Strong and sustained action to protect the safety of healthcare workers, and provide meaningful support, is urgently needed.
| S-EPMC9679314 | biostudies-literature
Project description:OBJECTIVES:The objectives of this study were to assess if targeted investigation for tumor-specific mutations by ultradeep DNA sequencing of peritoneal washes of ovarian cancer patients after primary surgical debulking and chemotherapy, and clinically diagnosed as disease free, provides a more sensitive and specific method to assess actual treatment response and tailor future therapy and to compare this "molecular second look" with conventional cytology and histopathology-based findings. METHODS/MATERIALS:We identified 10 patients with advanced-stage, high-grade serous ovarian cancer who had undergone second-look laparoscopy and for whom DNA could be isolated from biobanked paired blood, primary and recurrent tumor, and second-look peritoneal washes. A targeted 56 gene cancer-relevant panel was used for next-generation sequencing (average coverage, >6500×). Mutations were validated using either digital droplet polymerase chain reaction (ddPCR) or Sanger sequencing. RESULTS:A total of 25 tumor-specific mutations were identified (median, 2/patient; range, 1-8). TP53 mutations were identified in at least 1 sample from all patients. All 5 pathology-based second-look positive patients were confirmed positive by molecular second look. Genetic analysis revealed that 3 of the 5 pathology-based negative second looks were actually positive. In the 2 patients, the second-look mutations were present in either the original primary or recurrent tumors. In the third, 2 high-frequency, novel frameshift mutations in MSH6 and HNF1A were identified. CONCLUSIONS:The molecular second look detects tumor-specific evidence of residual disease and provides genetic insight into tumor evolution and future recurrences beyond standard pathology. In the precision medicine era, detecting and genetically characterizing residual disease after standard treatment will be invaluable for improving patient outcomes.
| S-EPMC5839702 | biostudies-literature