Diagnostic strategy and timing of intervention in infected necrotizing pancreatitis: an international expert survey and case vignette study

AbstractBackgroundThe optimal diagnostic strategy and timing of intervention in infected necrotizing pancreatitis is subject to debate. We performed a survey on these topics amongst a group of international expert pancreatologists.MethodsAn online survey including case vignettes was sent to 118 international pancreatologists. We evaluated the use and timing of fine needle aspiration (FNA), antibiotics, catheter drainage and (minimally invasive) necrosectomy.ResultsThe response rate was 74% (N = 87). None of the respondents use FNA routinely, 85% selectively and 15% never. Most respondents (87%) use a step-up approach in patients with infected necrosis. Walled-off necrosis (WON) is considered a prerequisite for endoscopic drainage and percutaneous drainage by 66% and 12%, respectively. After diagnosing infected necrosis, 55% routinely postpone invasive interventions, whereas 45% proceed immediately to intervention. Lack of consensus about timing of intervention was apparent on day 14 with proven infected necrosis (58% intervention vs. 42% non-invasive) as well as on day 20 with only clinically suspected infected necrosis (59% intervention vs. 41% non-invasive).DiscussionThe step-up approach is the preferred treatment strategy in infected necrotizing pancreatitis amongst expert pancreatologists. There is no uniformity regarding the use of FNA and timing of intervention in the first 2–3 weeks of infected necrotizing pancreatitis

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

Performance of a deep learning system for detection of referable diabetic retinopathy in real clinical settings

Background: To determine the ability of a commercially available deep learning system, RetCAD v.1.3.1 (Thirona, Nijmegen, The Netherlands) for the automatic detection of referable diabetic retinopathy (DR) on a dataset of colour fundus images acquired during routine clinical practice in a tertiary hospital screening program, analyzing the reduction of workload that can be released incorporating this artificial intelligence-based technology. Methods: Evaluation of the software was performed on a dataset of 7195 nonmydriatic fundus images from 6325 eyes of 3189 diabetic patients attending our screening program between February to December of 2019. The software generated a DR severity score for each colour fundus image which was combined into an eye-level score. This score was then compared with a reference standard as set by a human expert using receiver operating characteristic (ROC) curve analysis. Results: The artificial intelligence (AI) software achieved an area under the ROC curve (AUC) value of 0.988 [0.981:0.993] for the detection of referable DR. At the proposed operating point, the sensitivity of the RetCAD software for DR is 90.53% and specificity is 97.13%. A workload reduction of 96% could be achieved at the cost of only 6 false negatives. Conclusions: The AI software correctly identified the vast majority of referable DR cases, with a workload reduction of 96% of the cases that would need to be checked, while missing almost no true cases, so it may therefore be used as an instrument for triage.Comment: 15 pages, 3 figures, 2 table

Robust total retina thickness segmentation in optical coherence tomography images using convolutional neural networks

We developed a fully automated system using a convolutional neural network (CNN) for total retina segmentation in optical coherence tomography (OCT) that is robust to the presence of severe retinal pathology. A generalized U-net network architecture was introduced to include the large context needed to account for large retinal changes. The proposed algorithm outperformed qualitative and quantitatively two available algorithms. The algorithm accurately estimated macular thickness with an error of 14.0 +/- 22.1 mu m, substantially lower than the error obtained using the other algorithms (42.9 +/- 116.0 mu m and 27.1 +/- 69.3 mu m, respectively). These results highlighted the proposed algorithm's capability of modeling the wide variability in retinal appearance and obtained a robust and reliable retina segmentation even in severe pathological cases. (C) 2017 Optical Society of Americ

Automated Staging of Age-Related Macular Degeneration Using Optical Coherence Tomography

PURPOSE. To evaluate a machine learning algorithm that automatically grades age-related macular degeneration (AMD) severity stages from optical coherence tomography (OCT) scans. METHODS. A total of 3265 OCT scans from 1016 patients with either no signs of AMD or with signs of early, intermediate, or advanced AMD were randomly selected from a large European multicenter database. A machine learning system was developed to automatically grade unseen OCT scans into different AMD severity stages without requiring retinal layer segmentation. The ability of the system to identify high-risk AMD stages and to assign the correct severity stage was determined by using receiver operator characteristic (ROC) analysis and Cohen's kappa statistics (kappa), respectively. The results were compared to those of two human observers. Reproducibility was assessed in an independent, publicly available data set of 384 OCT scans. RESULTS. The system achieved an area under the ROC curve of 0.980 with a sensitivity of 98.2% at a specificity of 91.2%. This compares favorably with the performance of human observers who achieved sensitivities of 97.0% and 99.4% at specificities of 89.7% and 87.2%, respectively. A good level of agreement with the reference was obtained (kappa = 0.713) and was in concordance with the human observers (kappa = 0.775 and kappa = 0.755, respectively). CONCLUSIONS. A machine learning system capable of automatically grading OCT scans into AMD severity stages was developed and showed similar performance as human observers. The proposed automatic system allows for a quick and reliable grading of large quantities of OCT scans, which could increase the efficiency of large-scale AMD studies and pave the way for AMD screening using OCT

Clinical Characteristics of Familial and Sporadic Age-Related Macular Degeneration: Differences and Similarities

PURPOSE. We describe the differences and similarities in clinical characteristics and phenotype of familial and sporadic patients with age-related macular degeneration (AMD). METHODS. We evaluated data of 1828 AMD patients and 1715 controls enrolled in the European Genetic Database. All subjects underwent ophthalmologic examination, including visual acuity testing and fundus photography. Images were graded and fundus photographs were used for automatic drusen quantification by a machine learning algorithm. Data on disease characteristics, family history, medical history, and lifestyle habits were obtained by a questionnaire. RESULTS. The age at first symptoms was significantly lower in AMD patients with a positive family history (68.5 years) than in those with no family history (71.6 years, P = 1.9 x 10(-5)). Risk factors identified in sporadic and familial subjects were increasing age (odds ratio [OR], 1.08 per year; P = 3.0 x 10(-51), and OR, 1.15; P = 5.3 x 10(-36), respectively) and smoking (OR, 1.01 per pack year; P = 1.1 x 10(-6) and OR, 1.02; P = 0.005). Physical activity and daily red meat consumption were significantly associated with AMD in sporadic subjects only (OR, 0.49; P = 3.7 x 10(-10) and OR, 1.81; P = 0.001). With regard to the phenotype, geographic atrophy and cuticular drusen were significantly more prevalent in familial AMD (17.5% and 21.7%, respectively) compared to sporadic AMD (9.8% and 12.1%). CONCLUSIONS. Familial AMD patients become symptomatic at a younger age. The higher prevalence of geographic atrophy and cuticular drusen in the familial AMD cases may be explained by the contribution of additional genetic factors segregating within families

Clinical Characteristics of Familial and Sporadic Age-Related Macular Degeneration: Differences and Similarities

PURPOSE. We describe the differences and similarities in clinical characteristics and phenotype of familial and sporadic patients with age-related macular degeneration (AMD). METHODS. We evaluated data of 1828 AMD patients and 1715 controls enrolled in the European Genetic Database. All subjects underwent ophthalmologic examination, including visual acuity testing and fundus photography. Images were graded and fundus photographs were used for automatic drusen quantification by a machine learning algorithm. Data on disease characteristics, family history, medical history, and lifestyle habits were obtained by a questionnaire. RESULTS. The age at first symptoms was significantly lower in AMD patients with a positive family history (68.5 years) than in those with no family history (71.6 years, P = 1.9 x 10(-5)). Risk factors identified in sporadic and familial subjects were increasing age (odds ratio [OR], 1.08 per year; P = 3.0 x 10(-51), and OR, 1.15; P = 5.3 x 10(-36), respectively) and smoking (OR, 1.01 per pack year; P = 1.1 x 10(-6) and OR, 1.02; P = 0.005). Physical activity and daily red meat consumption were significantly associated with AMD in sporadic subjects only (OR, 0.49; P = 3.7 x 10(-10) and OR, 1.81; P = 0.001). With regard to the phenotype, geographic atrophy and cuticular drusen were significantly more prevalent in familial AMD (17.5% and 21.7%, respectively) compared to sporadic AMD (9.8% and 12.1%). CONCLUSIONS. Familial AMD patients become symptomatic at a younger age. The higher prevalence of geographic atrophy and cuticular drusen in the familial AMD cases may be explained by the contribution of additional genetic factors segregating within families

Genetic Association Analysis of Drusen Progression

Age-related macular degeneration is a common form of vision loss affecting older adults. The etiology of AMD is multifactorial and is influenced by environmental and genetic risk factors. In this study, we examine how 19 common risk variants contribute to drusen progression, a hallmark of AMD pathogenesis. Exome chip data was made available through the International AMD Genomics Consortium (IAMDGC). Drusen quantification was carried out with color fundus photographs using an automated drusen detection and quantification algorithm. A genetic risk score (GRS) was calculated per subject by summing risk allele counts at 19 common genetic risk variants weighted by their respective effect sizes. Pathway analysis of drusen progression was carried out with the software package Pathway Analysis by Randomization Incorporating Structure. We observed significant correlation with drusen baseline area and the GRS in the age-related eye disease study (AREDS) dataset (ρ = 0.175, P = 0.006). Measures of association were not statistically significant between drusen progression and the GRS (P = 0.54). Pathway analysis revealed the cell adhesion molecules pathway as the most highly significant pathway associated with drusen progression (corrected P = 0.02). In this study, we explored the potential influence of known common AMD genetic risk factors on drusen progression. Our results from the GRS analysis showed association of increasing genetic burden (from 19 AMD associated loci) to baseline drusen load but not drusen progression in the AREDS dataset while pathway analysis suggests additional genetic contributors to AMD risk

Global challenges for nitrogen science-policy interactions: Towards the International Nitrogen Management system (INMS) and improved coordination between multi-lateral enviornmental agreements

Human interference with the nitrogen cycle has doubled reactive nitrogen inputs to the global biosphere over the past century, leading to changes across multiple environmental issues that require urgent action. Nitrogen fertilizers and biological nitrogen fixation have allowed benefits of increased crop harvest and livestock production, while in some areas there is insufficient nitrogen to fertilize crops. Whether in excess or deficit, nitrogen losses from its inefficient use are causing a combination of freshwater and marine pollution, air pollution, alteration of climate balance, stratospheric ozone loss, biodiversity loss and reduction of soil quality. The resulting nitrogen pollution affects human health, well-being and livelihoods. Scientific efforts have begun to bring these issues together. However, there is still a high degree of fragmentation between research on the different benefits and threats of reactive nitrogen and between the respective policy frameworks, especially at the global scale. We argue that a more joined-up approach to managing the global nitrogen cycle is needed to develop the ‘gravity of common cause’ between nitrogen issues and to avoid policy trade-offs. We describe how a coherent system for science evidence provision is being developed to support policy development through the ‘International Nitrogen Management System’ (INMS). There is now a matching challenge to bring together the multiple policy agreements relevant for nitrogen as a foundation to address synergies/trade-offs and to set priorities. Based on review of existing frameworks, we outline the concept for an Interconvention nitrogen coordination mechanism. This could make a major contribution to multiple Sustainable Development Goals by stimulating the next generation of international nitrogen strategies: maximizing the benefits of efficient nitrogen use, while minimizing its many environmental threats