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- Adamo, Marianna, et al.
(författare)
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Epidemiology, pathophysiology, diagnosis and management of chronic right-sided heart failure and tricuspid regurgitation. A clinical consensus statement of the Heart Failure Association (HFA) and the European Association of Percutaneous Cardiovascular Interventions (EAPCI) of the ESC
- 2024
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Ingår i: European Journal of Heart Failure. - : WILEY. - 1388-9842 .- 1879-0844.
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Tidskriftsartikel (refereegranskat)abstract
- Right-sided heart failure and tricuspid regurgitation are common and strongly associated with poor quality of life and an increased risk of heart failure hospitalizations and death. While medical therapy for right-sided heart failure is limited, treatment options for tricuspid regurgitation include surgery and, based on recent developments, several transcatheter interventions. However, the patients who might benefit from tricuspid valve interventions are yet unknown, as is the ideal time for these treatments given the paucity of clinical evidence. In this context, it is crucial to elucidate aetiology and pathophysiological mechanisms leading to right-sided heart failure and tricuspid regurgitation in order to recognize when tricuspid regurgitation is a mere bystander and when it can cause or contribute to heart failure progression. Notably, early identification of right heart failure and tricuspid regurgitation may be crucial and optimal management requires knowledge about the different mechanisms and causes, clinical course and presentation, as well as possible treatment options. The aim of this clinical consensus statement is to summarize current knowledge about epidemiology, pathophysiology and treatment of tricuspid regurgitation in right-sided heart failure providing practical suggestions for patient identification and management.
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| 2. |
- Alkharabsheh, Khalid, et al.
(författare)
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Prioritization of god class design smell : A multi-criteria based approach
- 2022
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Ingår i: JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES. - Amsterdam : Elsevier. - 1319-1578 .- 2213-1248. ; 34:10, s. 9332-9342
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Tidskriftsartikel (refereegranskat)abstract
- Context: Design smell Prioritization is a significant activity that tunes the process of software quality enhancement and raises its life cycle.Objective: A multi-criteria merge strategy for Design Smell prioritization is described. The strategy is exemplified with the case of God Class Design Smell.Method: An empirical adjustment of the strategy is performed using a dataset of 24 open source projects. Empirical evaluation was conducted in order to check how is the top ranked God Classes obtained by the proposed technique compared against the top ranked God class according to the opinion of developers involved in each of the projects in the dataset.Results: Results of the evaluation show the strategy should be improved. Analysis of the differences between projects where respondents answer correlates with the strategy and those projects where there is no correlation should be done.
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| 3. |
- Attia, Zachi I., et al.
(författare)
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Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram
- 2021
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Ingår i: Mayo Clinic proceedings. - : ELSEVIER SCIENCE INC. - 0025-6196 .- 1942-5546. ; 96:8, s. 2081-2094
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG). Methods: A global, volunteer consortium from 4 continents identified patients with ECGs obtained around the time of polymerase chain reaction-confirmed COVID-19 diagnosis and age- and sex-matched controls from the same sites. Clinical characteristics, polymerase chain reaction results, and raw electrocardiographic data were collected. A convolutional neural network was trained using 26,153 ECGs (33.2% COVID positive), validated with 3826 ECGs (33.3% positive), and tested on 7870 ECGs not included in other sets (32.7% positive). Performance under different prevalence values was tested by adding control ECGs from a single high-volume site. Results: The area under the curve for detection of acute COVID-19 infection in the test group was 0.767 (95% CI, 0.756 to 0.778; sensitivity, 98%; specificity, 10%; positive predictive value, 37%; negative predictive value, 91%). To more accurately reflect a real-world population, 50,905 normal controls were added to adjust the COVID prevalence to approximately 5% (2657/58,555), resulting in an area under the curve of 0.780 (95% CI, 0.771 to 0.790) with a specificity of 12.1% and a negative predictive value of 99.2%. Conclusion: Infection with SARS-CoV-2 results in electrocardiographic changes that permit the artificial intelligence-enhanced ECG to be used as a rapid screening test with a high negative predictive value (99.2%). This may permit the development of electrocardiography-based tools to rapidly screen individuals for pandemic control. (C) 2021 Mayo Foundation Medical Education and Research
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| 4. |
- Menkveld, Albert J., et al.
(författare)
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Nonstandard Errors
- 2024
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Ingår i: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
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Tidskriftsartikel (refereegranskat)abstract
- In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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