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1.
Diabetes Obes Metab ; 22(8): 1443-1454, 2020 08.
Article in English | MEDLINE | ID: covidwho-647644

ABSTRACT

AIM: To explore whether coronavirus disease 2019 (COVID-19) patients with diabetes and secondary hyperglycaemia have different clinical characteristics and prognoses than those without significantly abnormal glucose metabolism. MATERIALS AND METHODS: We retrospectively analysed 166 COVID-19 patients at Tongji Hospital (Wuhan) from 8 February to 21 March 2020. Clinical characteristics and outcomes (as of 4 April 2020) were compared among control (group 1), secondary hyperglycaemia (group 2: no diabetes history, fasting plasma glucose levels of ≥7.0 mmol/L once and HbA1c values <6.5%) and patients with diabetes (group 3). RESULTS: Compared with group 1, groups 2 and 3 had higher rates of leukocytosis, neutrophilia, lymphocytopenia, eosinopenia and levels of hypersensitive C-reactive protein, ferritin and d-dimer (P < .05 for all). Group 2 patients had higher levels of lactate dehydrogenase, prevalence of liver dysfunction and increased interleukin-8 (IL-8) than those in group 1, and a higher prevalence of increased IL-8 was found in group 2 than in group 3 (P < .05 for all). The proportions of critical patients in groups 2 and 3 were significantly higher compared with group 1 (38.1%, 32.8% vs. 9.5%, P < .05 for both). Groups 2 and 3 had significantly longer hospital stays than group 1, which was nearly 1 week longer. The composite outcomes risks were 5.47 (1.56-19.82) and 2.61 (0.86-7.88) times greater in groups 2 and 3 than in group 1. CONCLUSIONS: Hyperglycaemia in both diabetes and secondary hyperglycaemia patients with COVID-19 may indicate poor prognoses. There were differences between patients with secondary hyperglycaemia and those with diabetes. We recommend that clinicians pay more attention to the blood glucose status of COVID-19 patients, even those not diagnosed with diabetes before admission.


Subject(s)
Betacoronavirus , Coronavirus Infections/blood , Diabetes Mellitus/virology , Hyperglycemia/virology , Pneumonia, Viral/blood , Adult , Aged , Blood Glucose/analysis , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/mortality , Diabetes Mellitus/blood , Diabetes Mellitus/mortality , Female , Glycated Hemoglobin A/analysis , Hospitalization/statistics & numerical data , Humans , Hyperglycemia/blood , Hyperglycemia/mortality , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/mortality , Prognosis , Retrospective Studies
2.
Chin J Acad Radiol ; : 1-6, 2020 May 11.
Article in English | MEDLINE | ID: covidwho-232587

ABSTRACT

Purpose: To explore lung involvement in patients with coronavirus disease-19 (COVID-19) using quantitative computed tomography (QCT). Methods: A total of 52 patients with COVID-19 who were admitted to three hospitals in China from January 23, 2020 to February 1, 2020 were retrospectively analyzed using QCT. The accuracy of QCT segmentation was assessed. The relationship between the time from symptom onset to initial CT and QCT parameters acquired on the initial CT were explored. Results: First, the ability of QCT to detect and segment lesions was investigated and it was unveiled that results of segmentation of the majority of cases (42/52) were satisfactory and for 8 out of 52 patients, the images depicted lesions with miss-segmentation; besides, 2 out of 52 cases had negative finding on chest CT achieved by both radiologists and QCT. QCT-related parameters showed to have a relationship with the time from symptom onset to initial CT. In the early-stage (0-3 days), the percentage of lung involvement was 4%, with a mean density of - 462 ± 99 HU. The peak density of lesions appeared at the range of - 500 to - 700 HU on density histogram. In the intermediate-stage (4-6 days), the mean percentage of lung involvement noticeably increased compared with that in early stage (7%, p < 0.05). In late stage (7-14 days), the percentage of lung involvement decreased to 5%. The mean density of lesions was the highest (- 430 ± 80), and heterogeneity density distribution showed a dual-peak on density histogram. Conclusion: COVID-19 can be promptly detected by QCT. In addition, the QCT-related parameters can highly facilitate assessment of pulmonary involvement.

3.
Lancet Infect Dis ; 2020 Apr 22.
Article in English | MEDLINE | ID: covidwho-102013
4.
Chin J Acad Radiol ; : 1-10, 2020 Mar 18.
Article in English | MEDLINE | ID: covidwho-47416

ABSTRACT

COVID-19 has become a public health emergency due to its rapid transmission. The appearance of pneumonia is one of the major clues for the diagnosis, progress and therapeutic evaluation. More and more literatures about imaging manifestations and related research have been reported. In order to know about the progress and prospective on imaging of COVID-19, this review focus on interpreting the CT findings, stating the potential pathological basis, proposing the challenge of patients with underlying diseases, differentiating with other diseases and suggesting the future research and clinical directions, which would be helpful for the radiologists in the clinical practice and research.

5.
Lancet Infect Dis ; 20(5): 559-564, 2020 05.
Article in English | MEDLINE | ID: covidwho-14167

ABSTRACT

BACKGROUND: In December, 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China. The number of affected pregnant women is increasing, but scarce information is available about the clinical features of COVID-19 in pregnancy. This study aimed to clarify the clinical features and obstetric and neonatal outcomes of pregnant patients with COVID-19. METHODS: In this retrospective, single-centre study, we included all pregnant women with COVID-19 who were admitted to Tongji Hospital in Wuhan, China. Clinical features, treatments, and maternal and fetal outcomes were assessed. FINDINGS: Seven patients, admitted to Tongji Hospital from Jan 1, to Feb 8, 2020, were included in our study. The mean age of the patients was 32 years (range 29-34 years) and the mean gestational age was 39 weeks plus 1 day (range 37 weeks to 41 weeks plus 2 days). Clinical manifestations were fever (six [86%] patients), cough (one [14%] patient), shortness of breath (one [14%] patient), and diarrhoea (one [14%] patient). All the patients had caesarean section within 3 days of clinical presentation with an average gestational age of 39 weeks plus 2 days. The final date of follow-up was Feb 12, 2020. The outcomes of the pregnant women and neonates were good. Three neonates were tested for SARS-CoV-2 and one neonate was infected with SARS-CoV-2 36 h after birth. INTERPRETATION: The maternal, fetal, and neonatal outcomes of patients who were infected in late pregnancy appeared very good, and these outcomes were achieved with intensive, active management that might be the best practice in the absence of more robust data. The clinical characteristics of these patients with COVID-19 during pregnancy were similar to those of non-pregnant adults with COVID-19 that have been reported in the literature. FUNDING: National Natural Science Foundation of China, Hubei Provincial Natural Science Foundation of China.


Subject(s)
Betacoronavirus , Coronavirus Infections/complications , Pneumonia, Viral/complications , Pregnancy Complications, Infectious , Pregnancy Outcome , Adult , China , Coronavirus Infections/diagnostic imaging , Female , Humans , Pandemics , Pneumonia, Viral/diagnostic imaging , Pregnancy , Tomography, X-Ray Computed
6.
J Pharm Anal ; 2020 Mar 06.
Article in English | MEDLINE | ID: covidwho-4449

ABSTRACT

Purpose: To examine the feasibility of using a computer tool for stratifying the severity of Coronavirus Disease 2019 (COVID-19) based on computed tomography (CT) images. Materials and methods: We retrospectively examined 44 confirmed COVID-19 cases. All cases were evaluated separately by radiologists (visually) and through an in-house computer software. The degree of lesions was visually scored by the radiologist, as follows, for each of the 5 lung lobes: 0, no lesion present; 1, <1/3 involvement; 2, >1/3 and < 2/3 involvement; and 3, >2/3 involvement. Lesion density was assessed based on the proportion of ground-glass opacity (GGO), consolidation and fibrosis of the lesions. The parameters obtained using the computer tool included lung volume (mL), lesion volume (mL), lesion percentage (%), and mean lesion density (HU) of the whole lung, right lung, left lung, and each lobe. The scores obtained by the radiologists and quantitative results generated by the computer software were tested for correlation. A Chi-square test was used to test the consistency of radiologist- and computer-derived lesion percentage in the right/left lung, upper/lower lobe, and each of the 5 lobes. Result: The results showed a strong to moderate correlation between lesion percentage scores obtained by radiologists and the computer software (r ranged from 0.7679 to 0.8373, P < 0.05), and a moderate correlation between the proportion of GGO and mean lesion density (r = -0.5894, P < 0.05), and proportion of consolidation and mean lesion density (r = 0.6282, P < 0.05). Computer-aided quantification showed a statistical significant higher lesion percentage for lower lobes than that assessed by the radiologists (χ2 = 8.160, P = 0.004). Conclusions: Our experiments demonstrated that the computer tool could reliably and accurately assess the severity and distribution of pneumonia on CT scans.

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