Prevalence and risk of COVID-19 in patients with rheumatic diseases: a systematic review and meta-analysis.

OBJECTIVES: COVID-19 pandemic has already had a tremendous impact on the process of human society; the survival of mankind and the healthy living environment deterioration with the influence will last for many years. This meta-analysis aims to assess the risk of COVID-19 in patients with rheumatic diseases. METHODS: PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical Database (CBM) were systematically searched with no language restriction up to July 5, 2021. The pooled rates were synthesized by fixed effect model or random effect model depending on heterogeneity. RESULTS: A total of 83 articles were included in this meta-analysis. The incidence of COVID-19 in patient with rheumatic diseases was 0.0190 (95% CI: 0.0136-0.0252), and the hospitalization rate, intensive care unit admission rate, mechanical ventilation rate, and case fatality rate of patients with rheumatic diseases infected with COVID-19 were 0.4396 (95% CI: 0.3899-0.4898), 0.0635 (95% CI: 0.0453-0.0836), 0.0461 (95% CI: 0.0330-0.0609), and 0.0346 (95% CI: 0.0218-0.0493), respectively. CONCLUSIONS: Our research shows that patients with rheumatic diseases have great risk of COVID-19. Differences in COVID-19 incidence, hospitalization rates, and mortality rates in regions were statistically significant. We still need to pay attention to the risk of COVID-19 in patients with rheumatic diseases. KEY POINTS: • Although the risk of COVID-19 in patients with rheumatic diseases has been discussed in previous meta-analysis, their research directions were inconsistent, and few studies focus on prevalence or serious outcomes of COVID-19 in patient with rheumatic diseases, while the quality of these articles was variable. • The incidence of COVID-19 and serious clinical outcomes in patients with rheumatic diseases were still high along with differential risks in most regions. • The use of glucocorticoids and conventional synthetic disease-modifying antirheumatic drugs did not affect the hospitalization rate and mortality in rheumatism patients with COVID-19.

CT radiomics facilitates more accurate diagnosis of COVID-19 pneumonia: compared with CO-RADS.

BACKGROUND: Limited data was available for rapid and accurate detection of COVID-19 using CT-based machine learning model. This study aimed to investigate the value of chest CT radiomics for diagnosing COVID-19 pneumonia compared with clinical model and COVID-19 reporting and data system (CO-RADS), and develop an open-source diagnostic tool with the constructed radiomics model. METHODS: This study enrolled 115 laboratory-confirmed COVID-19 and 435 non-COVID-19 pneumonia patients (training dataset, n = 379; validation dataset, n = 131; testing dataset, n = 40). Key radiomics features extracted from chest CT images were selected to build a radiomics signature using least absolute shrinkage and selection operator (LASSO) regression. Clinical and clinico-radiomics combined models were constructed. The combined model was further validated in the viral pneumonia cohort, and compared with performance of two radiologists using CO-RADS. The diagnostic performance was assessed by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). RESULTS: Eight radiomics features and 5 clinical variables were selected to construct the combined radiomics model, which outperformed the clinical model in diagnosing COVID-19 pneumonia with an area under the ROC (AUC) of 0.98 and good calibration in the validation cohort. The combined model also performed better in distinguishing COVID-19 from other viral pneumonia with an AUC of 0.93 compared with 0.75 (P = 0.03) for clinical model, and 0.69 (P = 0.008) or 0.82 (P = 0.15) for two trained radiologists using CO-RADS. The sensitivity and specificity of the combined model can be achieved to 0.85 and 0.90. The DCA confirmed the clinical utility of the combined model. An easy-to-use open-source diagnostic tool was developed using the combined model. CONCLUSIONS: The combined radiomics model outperformed clinical model and CO-RADS for diagnosing COVID-19 pneumonia, which can facilitate more rapid and accurate detection.

Clinico-Radiological Features and Outcomes in Pregnant Women with COVID-19 Pneumonia Compared with Age-Matched Non-Pregnant Women.

PURPOSE: To investigate the clinico-radiological findings and outcomes in pregnant women with COVID-19 pneumonia compared to age-matched non-pregnant women. METHODS: A retrospective case-controlled study was conducted to review clinical and CT data of 21 pregnant and 19 age-matched non-pregnant women with COVID-19 pneumonia. Four stages of CT images were analyzed and compared based on the time interval from symptom onset: stage 1 (0-6 days), stage 2 (7-9 days), stage 3 (10-16 days), and stage 4 (>16 days). The initial and follow-up data were analyzed and compared. RESULTS: Compared with age-matched non-pregnant women, initial absence of fever (13/21, 62%) and normal lymphocyte count (11/21, 52%) were more frequent in pregnant group. The predominant patterns of lung lesions were pure ground-glass opacity (GGO), GGO with consolidation or reticulation, and pure consolidation in both groups. Pure consolidation on chest CT was more common at presentation in pregnant cases. Pregnant women progressed with a higher consolidation frequency compared with non-pregnant group in stage 2 (95% vs 82%). Improvement was identified in stages 3 and 4 for both groups, but consolidation was still more frequent for pregnant women in stage 4. Most patients (38/40, 95%) were grouped as mild or common type. The length of hospitalization between the two groups was similar. CONCLUSION: Pregnant women with COVID-19 pneumonia did not present typical clinical features, while developing a relatively more severe disease at imaging with a slower recovery course and experiencing similar outcomes compared with the non-pregnant women.

Clinical and CT imaging features of the COVID-19 pneumonia: Focus on pregnant women and children.

BACKGROUND: The ongoing outbreak of COVID-19 pneumonia is globally concerning. We aimed to investigate the clinical and CT features in the pregnant women and children with this disease, which have not been well reported. METHODS: Clinical and CT data of 59 patients with COVID-19 from January 27 to February 14, 2020 were retrospectively reviewed, including 14 laboratory-confirmed non-pregnant adults, 16 laboratory-confirmed and 25 clinically-diagnosed pregnant women, and 4 laboratory-confirmed children. The clinical and CT features were analyzed and compared. FINDINGS: Compared with the non-pregnant adults group (n = 14), initial normal body temperature (9 [56%] and 16 [64%]), leukocytosis (8 [50%] and 9 [36%]) and elevated neutrophil ratio (14 [88%] and 20 [80%]), and lymphopenia (9 [56%] and 16 [64%]) were more common in the laboratory-confirmed (n = 16) and clinically-diagnosed (n = 25) pregnant groups. Totally 614 lesions were detected with predominantly peripheral and bilateral distributions in 54 (98%) and 37 (67%) patients, respectively. Pure ground-glass opacity (GGO) was the predominant presence in 94/131 (72%) lesions for the non-pregnant adults. Mixed consolidation and complete consolidation were more common in the laboratory-confirmed (70/161 [43%]) and clinically-diagnosed (153/322 [48%]) pregnant groups than 37/131 (28%) in the non-pregnant adults (P = 0·007, P < 0·001). GGO with reticulation was less common in 9/161 (6%) and 16/322 (5%) lesions for the two pregnant groups than 24/131 (18%) for the non-pregnant adults (P = 0·001, P < 0·001). The pulmonary involvement in children with COVID-19 was mild with a focal GGO or consolidation. Twenty-three patients underwent follow-up CT, revealing progression in 9/13 (69%) at 3 days whereas improvement in 8/10 (80%) at 6-9 days after initial CT scans. INTERPRETATION: Atypical clinical findings of pregnant women with COVID-19 could increase the difficulty in initial identification. Consolidation was more common in the pregnant groups. The clinically-diagnosed cases were vulnerable to more pulmonary involvement. CT was the modality of choice for early detection, severity assessment, and timely therapeutic effects evaluation for the cases with epidemic and clinical features of COVID-19 with or without laboratory confirmation. The exposure history and clinical symptoms were more helpful for screening in children versus chest CT.