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1.
BMC Infect Dis ; 21(1): 774, 2021 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-34372792

RESUMO

BACKGROUND: The severity of COVID-19 associates with the clinical decision making and the prognosis of COVID-19 patients, therefore, early identification of patients who are likely to develop severe or critical COVID-19 is critical in clinical practice. The aim of this study was to screen severity-associated markers and construct an assessment model for predicting the severity of COVID-19. METHODS: 172 confirmed COVID-19 patients were enrolled from two designated hospitals in Hangzhou, China. Ordinal logistic regression was used to screen severity-associated markers. Least Absolute Shrinkage and Selection Operator (LASSO) regression was performed for further feature selection. Assessment models were constructed using logistic regression, ridge regression, support vector machine and random forest. The area under the receiver operator characteristic curve (AUROC) was used to evaluate the performance of different models. Internal validation was performed by using bootstrap with 500 re-sampling in the training set, and external validation was performed in the validation set for the four models, respectively. RESULTS: Age, comorbidity, fever, and 18 laboratory markers were associated with the severity of COVID-19 (all P values < 0.05). By LASSO regression, eight markers were included for the assessment model construction. The ridge regression model had the best performance with AUROCs of 0.930 (95% CI, 0.914-0.943) and 0.827 (95% CI, 0.716-0.921) in the internal and external validations, respectively. A risk score, established based on the ridge regression model, had good discrimination in all patients with an AUROC of 0.897 (95% CI 0.845-0.940), and a well-fitted calibration curve. Using the optimal cutoff value of 71, the sensitivity and specificity were 87.1% and 78.1%, respectively. A web-based assessment system was developed based on the risk score. CONCLUSIONS: Eight clinical markers of lactate dehydrogenase, C-reactive protein, albumin, comorbidity, electrolyte disturbance, coagulation function, eosinophil and lymphocyte counts were associated with the severity of COVID-19. An assessment model constructed with these eight markers would help the clinician to evaluate the likelihood of developing severity of COVID-19 at admission and early take measures on clinical treatment.


Assuntos
COVID-19 , Biomarcadores , China/epidemiologia , Humanos , Estudos Retrospectivos , Medição de Risco , SARS-CoV-2
2.
BBA Clin ; 8: 7-13, 2017 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-28567338

RESUMO

A method of rapidly differentiating lung tumor from healthy tissue is extraordinarily needed for both the diagnosis and the intraoperative margin assessment. We assessed the ability of fluorescence lifetime imaging microscopy (FLIM) for differentiating human lung cancer and normal tissues with the autofluorescence, and also elucidated the mechanism in tissue studies and cell studies. A 15-patient testing group was used to compare FLIM results with traditional histopathology diagnosis. Based on the endogenous fluorescence lifetimes of the testing group, a criterion line was proposed to distinguish normal and cancerous tissues. Then by blinded examined 41 sections from the validation group of other 16 patients, the sensitivity and specificity of FLIM were determined. The cellular metabolism was studied with specific perturbations of oxidative phosphorylation and glycolysis in cell studies. The fluorescence lifetime of cancerous lung tissues is consistently lower than normal tissues, and this is due to the both decrease of reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) lifetimes. A criterion line of lifetime at 1920 ps can be given for differentiating human lung cancer and normal tissues.The sensitivity and specificity of FLIM for lung cancer diagnosis were determined as 92.9% and 92.3%. These findings suggest that NADH and FAD can be used to rapidly diagnose lung cancer. FLIM is a rapid, accurate and highly sensitive technique in the judgment during lung cancer surgery and it can be potential in earlier cancer detection.

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