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| 2. |
- Sen, P, et al.
(författare)
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Vaccine hesitancy decreases in rheumatic diseases, long-term concerns remain in myositis: a comparative analysis of the COVAD surveys
- 2023
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Ingår i: Rheumatology (Oxford, England). - : Oxford University Press (OUP). - 1462-0332 .- 1462-0324. ; 62:10, s. 3291-3301
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveCOVID-19 vaccines have a favorable safety profile in patients with autoimmune rheumatic diseases (AIRDs) such as idiopathic inflammatory myopathies (IIMs); however, hesitancy continues to persist among these patients. Therefore, we studied the prevalence, predictors and reasons for hesitancy in patients with IIMs, other AIRDs, non-rheumatic autoimmune diseases (nrAIDs) and healthy controls (HCs), using data from the two international COVID-19 Vaccination in Autoimmune Diseases (COVAD) e-surveys.MethodsThe first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups.ResultsWe analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, P < 0.001). However, concerns/fear over long-term safety had increased (OR: 3.6; 95% CI: 2.9, 4.6, P < 0.01). We noted with concern greater skepticism over vaccine science among patients with IIMs than AIRDs (OR: 1.8; 95% CI: 1.08, 3.2, P = 0.023) and HCs (OR: 4; 95% CI: 1.9, 8.1, P < 0.001), as well as more long-term safety concerns/fear (IIMs vs AIRDs – OR: 1.9; 95% CI: 1.2, 2.9, P = 0.001; IIMs vs HCs – OR: 5.4 95% CI: 3, 9.6, P < 0.001). Caucasians [OR 4.2 (1.7–10.3)] were likely to be more hesitant, while those with better PROMIS physical health score were less hesitant [OR 0.9 (0.8–0.97)].ConclusionVaccine hesitancy has decreased from 2021 to 2022, long-term safety concerns remain among patients with IIMs, particularly in Caucasians and those with poor physical function.
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| 3. |
- Burn, E., et al.
(författare)
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Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19. Detailed knowledge of the characteristics of COVID-19 patients helps with public health planning. Here, the authors use routinely-collected data from seven databases in three countries to describe the characteristics of >30,000 patients admitted with COVID-19 and compare them with those admitted for influenza in previous years.
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| 4. |
- Ibanez, L., et al.
(författare)
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Multi-ancestry GWAS reveals excitotoxicity associated with outcome after ischaemic stroke
- 2022
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Ingår i: Brain. - : Oxford University Press (OUP). - 0006-8950 .- 1460-2156. ; 145:7, s. 2394-2406
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Tidskriftsartikel (refereegranskat)abstract
- During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6 h of stroke onset and NIHSS at 24 h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24 h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke. Ibanez et al. perform a multi-ancestry meta-analysis to investigate the genetic architecture of early stroke outcomes. Two of the eight genome-wide significant loci identified-ADAM23 and GRIA1-are involved in synaptic excitability, suggesting that excitotoxicity contributes to neurological instability after ischaemic stroke.
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| 5. |
- Lane, J. C. E., et al.
(författare)
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Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study
- 2020
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Ingår i: Lancet Rheumatology. - : Elsevier BV. - 2665-9913. ; 2:11
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Tidskriftsartikel (refereegranskat)abstract
- Background Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis. Methods In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I-2 value was less than 0.4. Findings The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Selfcontrolled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1.65 [95% CI 1.12-2.44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2.19 [95% CI 1.22-3.95]), chest pain or angina (1.15 [1.05-1.26]), and heart failure (1.22 [1.02-1.45]). Interpretation Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment. Copyright (c) 2020 The Author(s). Published by Elsevier Ltd.
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| 6. |
- Williams, R. D., et al.
(författare)
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Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network
- 2022
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. Methods: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. Results: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. Conclusions: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use. © 2022, The Author(s).
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| 7. |
- Reyes, C., et al.
(författare)
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Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study
- 2021
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Ingår i: Bmj Open. - : BMJ. - 2044-6055. ; 11:12
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Tidskriftsartikel (refereegranskat)abstract
- Objective To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients. Design and setting This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020. Participants Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days. Outcomes Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported. Results We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension. Conclusions COVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.
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| 10. |
- Kostka, Kristin, et al.
(författare)
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Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS.
- 2022
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Ingår i: Clinical epidemiology. - 1179-1349. ; 14, s. 369-384
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Tidskriftsartikel (refereegranskat)abstract
- Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.
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