| 11. |
- Dong, Yi-Min, et al.
(författare)
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Development and Validation of a Nomogram for Assessing Survival in Patients With COVID-19 Pneumonia
- 2021
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Ingår i: Clinical Infectious Diseases. - : Oxford University Press. - 1058-4838 .- 1537-6591. ; 72:4, s. 652-660
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Tidskriftsartikel (refereegranskat)abstract
- Background. The outbreak of coronavirus disease 2019 (COVID-19) has spread worldwide and continues to threaten peoples' health as well as put pressure on the accessibility of medical systems. Early prediction of survival of hospitalized patients will help in the clinical management of COVID-19, but a prediction model that is reliable and valid is still lacking. Methods. We retrospectively enrolled 628 confirmed cases of COVID-19 using positive RT-PCR tests for SARS-CoV-2 in Tongji Hospital, Wuhan, China. These patients were randomly grouped into a training (60%) and a validation (40%) cohort. In the training cohort, LASSO regression analysis and multivariate Cox regression analysis were utilized to identify prognostic factors for in-hospital survival of patients with COVID-19. A nomogram based on the 3 variables was built for clinical use. AUCs, concordance indexes (C-index), and calibration curves were used to evaluate the efficiency of the nomogram in both training and validation cohorts. Results. Hypertension, higher neutrophil-to-lymphocyte ratio, and increased NT-proBNP values were found to be significantly associated with poorer prognosis in hospitalized patients with COVID-19. The 3 predictors were further used to build a prediction nomogram. The C-indexes of the nomogram in the training and validation cohorts were 0.901 and 0.892, respectively. The AUC in the training cohort was 0.922 for 14-day and 0.919 for 21-day probability of in-hospital survival, while in the validation cohort this was 0.922 and 0.881, respectively. Moreover, the calibration curve for 14- and 21-day survival also showed high coherence between the predicted and actual probability of survival. Conclusions. We built a predictive model and constructed a nomogram for predicting in-hospital survival of patients with COVID-19. This model has good performance and might be utilized clinically in management of COVID-19.
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| 12. |
- Tian, Ke, et al.
(författare)
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Blue band nonlinear optics and photodarkening in silica microdevices
- 2022
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Ingår i: Photonics Research. - 2327-9125. ; 10:9, s. 2073-2080
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Tidskriftsartikel (refereegranskat)abstract
- There are extensive studies to date on optical nonlinearities in microcavities at the near and mid-IR wavelengths. Pushing this research into the visible region is equally valuable. Here, we demonstrate a directly pumped, blue band Kerr frequency comb and stimulated Raman scattering (SRS) at 462 nm in a silica nanofiber-coupled whispering gallery microcavity system. Notably, due to the high optical intensities achieved, photodarkening is unavoidable and can quickly degrade the optical quality of both the coupling optical nanofiber and the microcavity, even at very low pump powers. Nonetheless, stable hyperparametric oscillation and SRS are demonstrated in the presence of photodarkening by taking advantage of in-situ thermal bleaching. This work highlights the challenges of silica-based, short wavelength nonlinear optics in high-quality, small mode volume devices and gives an effective method to overcome this apparent limitation, thus providing a baseline for optics research in the blue region for any optical devices fabricated from silica.
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