| 1. |
- Khatri, C, et al.
(författare)
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Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
- 2021
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
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Tidskriftsartikel (refereegranskat)abstract
- Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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| 2. |
- Ferrando, Carlos, et al.
(författare)
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Effects of oxygen on post-surgical infections during an individualised perioperative open-lung ventilatory strategy : a randomised controlled trial
- 2020
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Ingår i: British Journal of Anaesthesia. - : ELSEVIER SCI LTD. - 0007-0912 .- 1471-6771. ; 124:1, s. 110-120
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to examine whether using a high fraction of inspired oxygen (FIO2) in the context of an individualised intra- and postoperative open-lung ventilation approach could decrease surgical site infection (SSI) in patients scheduled for abdominal surgery. Methods: We performed a multicentre, randomised controlled clinical trial in a network of 21 university hospitals from June 6, 2017 to July 19, 2018. Patients undergoing abdominal surgery were randomly assigned to receive a high (0.80) or conventional (0.3) FIO2 during the intraoperative period and during the first 3 postoperative hours. All patients were mechanically ventilated with an open-lung strategy, which included recruitment manoeuvres and individualised positive end-expiratory pressure for the best respiratory-system compliance, and individualised continuous postoperative airway pressure for adequate peripheral oxyhaemoglobin saturation. The primary outcome was the prevalence of SSI within the first 7 postoperative days. The secondary outcomes were composites of systemic complications, length of intensive care and hospital stay, and 6-month mortality. Results: We enrolled 740 subjects: 371 in the high FIO2 group and 369 in the low FIO2 group. Data from 717 subjects were available for final analysis. The rate of SSI during the first postoperative week did not differ between high (8.9%) and low (9.4%) FIO2 groups (relative risk [RR]: 0.94; 95% confidence interval [CI]: 0.59-1.50; P=0.90]). Secondary outcomes, such as atelectasis (7.7% vs 9.8%; RR: 0.77; 95% CI: 0.48-1.25; P=0.38) and myocardial ischaemia (0.6% [n=2] vs 0% [n=0]; P=0.47) did not differ between groups. Conclusions: An oxygenation strategy using high FIO2 compared with conventional FIO2 did not reduce postoperative SSIs in abdominal surgery. No differences in secondary outcomes or adverse events were found.
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| 3. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 4. |
- Casas, Gemma, et al.
(författare)
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Inputs, amplification and sinks of perfluoroalkyl substances at coastal Antarctica
- 2023
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Ingår i: Environmental Pollution. - 0269-7491 .- 1873-6424. ; 338
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Tidskriftsartikel (refereegranskat)abstract
- The sources, biogeochemical controls and sinks of perfluoroalkyl substances, such as perfluoroalkyl acids (PFAAs), in polar coastal regions are largely unknown. These were evaluated by measuring a large multi-compartment dataset of PFAAs concentrations at coastal Livingston and Deception Islands (maritime Antarctica) during three austral summers. PFAAs were abundant in atmospheric-derived samples (aerosols, rain, snow), consistent with the importance of atmospheric deposition as an input of PFAAs to Antarctica. Such PFAAs deposition was unequivocally demonstrated by the occurrence of PFAAs in small Antarctic lakes. Several lines of evidence supported the relevant amplification of PFAAs concentrations in surface waters driven by snow scavenging of sea-spray aerosol-bound PFAAs followed by snow-melting. For example, vertical profiles showed higher PFAAs concentrations at lower-salinity surface seawaters, and PFAAs concentrations in snow were significantly higher than in seawater. The higher levels of PFAAs at Deception Island than at Livingston Island are consistent with the semi-enclosed nature of the bay. Concentrations of PFOS decreased from 2014 to 2018, consistent with observations in other oceans. The sink of PFAAs due to the biological pump, transfer to the food web, and losses due to sea-spray aerosols alone are unlikely to have driven the decrease in PFOS concentrations. An exploratory assessment of the potential sinks of PFAAs suggests that microbial degradation of perfluoroalkyl sulfonates should be a research priority for the evaluation of PFAAs persistence in the coming decade.
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| 5. |
- Etminani, Kobra, 1984-, et al.
(författare)
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A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimers disease, and mild cognitive impairment using brain 18F-FDG PET
- 2022
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - New York : Springer. - 1619-7070 .- 1619-7089. ; 49, s. 563-584
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimers disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimers disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare models performance to that of multiple expert nuclear medicine physicians readers. Materials and methods Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimers disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human readers on the same independent test set. The models performance was analyzed with sensitivity, specificity, precision, F1 score, receiver operating characteristic (ROC). The regional metabolic changes driving classification were visualized using uniform manifold approximation and projection (UMAP) and network attention. Results The proposed model achieved area under the ROC curve of 96.2% (95% confidence interval: 90.6-100) on predicting the final diagnosis of DLB in the independent test set, 96.4% (92.7-100) in AD, 71.4% (51.6-91.2) in MCI-AD, and 94.7% (90-99.5) in CN, which in ROC space outperformed human readers performance. The network attention depicted the posterior cingulate cortex is important for each neurodegenerative disease, and the UMAP visualization of the extracted features by the proposed model demonstrates the reality of development of the given disorders. Conclusion Using only 18F-FDG PET of the brain, a 3D deep learning model could predict the final diagnosis of the most common neurodegenerative disorders which achieved a competitive performance compared to the human readers as well as their consensus.
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| 6. |
- Fred, Mats, et al.
(författare)
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Projectification and the European Union
- 2023
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Ingår i: The projectifikation of society : A necessary debate - A necessary debate. ; , s. 61-88
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter aims to provide insight into the phenomenon of European Union projectification . The paper is conceptual in nature and draws on the results of several research projects conducted by the authors, who represent two disciplines - management and political sciences . In the article we first discuss what distinguishes EU projects from other projects . Thereafter we describe the projectification of the EU using an analytical framework based on three levels (micro, meso and macro) . The chapter ends with a discussion on consequences of EU projectification and possible directions for future research on this phenomenon . Taking a general view of the findings, we believe that it is necessary to move beyond the depoliticising tendency of seeing EU projects as neutral tools and opening this area up to broader debates on the politics of projects .
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| 7. |
- Soliman, Amira, 1980-, et al.
(författare)
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Adopting transfer learning for neuroimaging : a comparative analysis with a custom 3D convolution neural network model
- 2022
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Ingår i: BMC Medical Informatics and Decision Making. - London : BioMed Central (BMC). - 1472-6947. ; 22, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Background: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. Results: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. Conclusions: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones. © 2022, The Author(s).
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| 8. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 9. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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