| 1. |
- Mercuri, E., et al.
(författare)
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Safety and effectiveness of ataluren: comparison of results from the STRIDE Registry and CINRG DMD Natural History Study
- 2020
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Ingår i: Journal of Comparative Effectiveness Research. - : Becaris Publishing Limited. - 2042-6305 .- 2042-6313. ; 9:5, s. 341-360
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Strategic Targeting of Registries and International Database of Excellence (STRIDE) is an ongoing, multicenter registry providing real-world evidence regarding ataluren use in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD). We examined the effectiveness of ataluren + standard of care (SoC) in the registry versus SoC alone in the Cooperative International Neuromuscular Research Group (CINRG) Duchenne Natural History Study (DNHS), DMD genotype-phenotype/-ataluren benefit correlations and ataluren safety. Patients & methods: Propensity score matching was performed to identify STRIDE and CINRG DNHS patients who were comparable in established disease progression predictors (registry cut-off date, 9 July 2018). Results & conclusion: Kaplan-Meier analyses demonstrated that ataluren + SoC significantly delayed age at loss of ambulation and age at worsening performance in timed function tests versus SoC alone (p <= 0.05). There were no DMD genotype-phenotype/ataluren benefit correlations. Ataluren was well tolerated. These results indicate that ataluren + SoC delays functional milestones of DMD progression in patients with nmDMD in routine clinical practice. ClinicalTrials.gov identifier: NCT02369731. ClinicalTrials.gov identifier: NCT02369731.
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| 2. |
- Schiller, D, et al.
(författare)
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The Human Affectome
- 2024
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Ingår i: Neuroscience and biobehavioral reviews. - 1873-7528. ; 158, s. 105450-
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Tidskriftsartikel (refereegranskat)
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| 3. |
- 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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| 4. |
- 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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| 5. |
- Reps, J. M., et al.
(författare)
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Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study
- 2021
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Ingår i: JMIR Medical Informatics. - : JMIR Publications Inc.. - 2291-9694. ; 9:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the "prediction model risk of bias assessment" criteria, and it has not been externally validated. Objective: The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases. Methods: We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia. Results: The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68. Conclusions: Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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| 6. |
- Armengaud, J., et al.
(författare)
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The Importance Of Naturally Attenuated Sars-Cov-2 In The Fight Against Covid-19
- 2020
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Ingår i: Environmental Microbiology. - : Wiley. - 1462-2912 .- 1462-2920. ; 22:6, s. 1997-2000
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Tidskriftsartikel (refereegranskat)abstract
- The current SARS-CoV-2 pandemic is wreaking havoc throughout the world and has rapidly become a global health emergency. A central question concerning COVID-19 is why some individuals become sick and others not. Many have pointed already at variation in risk factors between individuals. However, the variable outcome of SARS-CoV-2 infections may, at least in part, be due also to differences between the viral subspecies with which individuals are infected. A more pertinent question is how we are to overcome the current pandemic. A vaccine against SARS-CoV-2 would offer significant relief, although vaccine developers have warned that design, testing, and production of vaccines may take a year if not longer. Vaccines are based on a handful of different designs (1), but the earliest vaccines were based on live, attenuated virus. As has been the case for other viruses during earlier pandemics, SARS-CoV-2 will mutate and may naturally attenuate over time (2). What makes the current pandemic unique is that, thanks to state-of-the-art nucleic acid sequencing technologies, we can follow in detail how SARS-CoV-2 evolves while it spreads. We argue that knowledge of naturally emerging attenuated SARS-CoV-2 variants across the globe should be of key interest in our fight against the pandemic. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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| 7. |
- Jin, Shoko, et al.
(författare)
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The wide-field, multiplexed, spectroscopic facility WEAVE : Survey design, overview, and simulated implementation
- 2024
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Ingår i: Monthly notices of the Royal Astronomical Society. - : Oxford University Press. - 0035-8711 .- 1365-2966. ; 530:3, s. 2688-2730
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Tidskriftsartikel (refereegranskat)abstract
- WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, saw first light in late 2022. WEAVE comprises a new 2-deg field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366-959nm at R similar to 5000, or two shorter ranges at . After summarizing the design and implementation of WEAVE and its data systems, we present the organization, science drivers, and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for similar to 3 million stars and detailed abundances for similar to 1.5 million brighter field and open-cluster stars; (ii) survey similar to 0.4 million Galactic-plane OBA stars, young stellar objects, and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey similar to 400 neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionized gas in z < 0.5 cluster galaxies; (vi) survey stellar populations and kinematics in field galaxies at 0.3 less than or similar to z less than or similar to 0.7; (vii) study the cosmic evolution of accretion and star formation using >1 million spectra of LOFAR-selected radio sources; and (viii) trace structures using intergalactic/circumgalactic gas at z > 2. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.
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| 8. |
- Carraminana, Albert, et al.
(författare)
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Rationale and Study Design for an Individualized Perioperative Open Lung Ventilatory Strategy in Patients on One-Lung Ventilation (iPROVE-OLV)
- 2019
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Ingår i: Journal of Cardiothoracic and Vascular Anesthesia. - : W B SAUNDERS CO-ELSEVIER INC. - 1053-0770 .- 1532-8422. ; 33:9, s. 2492-2502
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The aim of this clinical trial is to examine whether it is possible to reduce postoperative complications using an individualized perioperative ventilatory strategy versus using a standard lung-protective ventilation strategy in patients scheduled for thoracic surgery requiring one-lung ventilation. Design: International, multicenter, prospective, randomized controlled clinical trial. Setting: A network of university hospitals. Participants: The study comprises 1,380 patients scheduled for thoracic surgery. Interventions: The individualized group will receive intraoperative recruitment maneuvers followed by individualized positive end-expiratory pressure (open lung approach) during the intraoperative period plus postoperative ventilatory support with high-flow nasal cannula, whereas the control group will be managed with conventional lung-protective ventilation. Measurements and Main Results: Individual and total number of postoperative complications, including atelectasis, pneumothorax, pleural effusion, pneumonia, acute lung injury; unplanned readmission and reintubation; length of stay and death in the critical care unit and in the hospital will be analyzed for both groups. The authors hypothesize that the intraoperative application of an open lung approach followed by an individual indication of high-flow nasal cannula in the postoperative period will reduce pulmonary complications and length of hospital stay in high-risk surgical patients. (C) 2019 Published by Elsevier Inc.
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