The Role of Computed Tomography in the Management of Hospitalized Patients With COVID-19.

The emergence of SARS-CoV-2 at the end of 2019 sparked the beginning of the COVID-19 pandemic. Even though it was a novel virus, the workup of suspected COVID-19 included standard protocols used for the investigation of similar respiratory infections and pneumonia. One of the most important diagnostic tests in this regard is computed tomography (CT). CT scans have a high sensitivity in diagnosing COVID-19, and many of the characteristic imaging findings of COVID-19 are used in its diagnosis. The role of CT in COVID-19 management is expanding as more and more hospital practices adopt regular CT use in both the initial workup and continued care of COVID-19 patients. CT has helped hospitalists diagnose complications such as pulmonary embolism, subcutaneous emphysema, pneumomediastinum, pneumothoraces, and nosocomial pneumonia. Although mainly used as a diagnostic tool, the prognostic role of CT in COVID-19 patients is developing. In this review, we explore the role of CT in the management of hospitalized patients with COVID-19, specifically elucidating its use as a diagnostic and prognostic modality, as well as its ability to guide hospital decision-making regarding complex cases. We will highlight important time points when CT scans are used: the initial encounter, the time at admission, and during hospitalization.

Clinical, Biochemical, and Radiological Presentation of RT-PCR-Positive vs RT-PCR-Negative SARS-CoV-2 Pneumonia Requiring ICU Care: An Observational, Cross-Sectional, Single-Center Study in Kalaburagi, Kalyana Karnataka.

Introduction Studies have reported similar clinical, biochemical, and radiological features between real-time polymerase chain reaction (RT-PCR)-positive and RT-PCR-negative patients. Therefore, the present study aims to assess differences in RT-PCR-positive versus RT-PCR-negative patients' characteristics. Methods We prospectively included 70 consecutive patients with typical coronavirus disease 2019 (COVID-19)-like clinical features who were either RT-PCR-positive or negative, requiring admission to the intensive care unit. The patients were classified into positive and negative RT-PCR groups and evaluated for clinical features, comorbidities, laboratory findings, and radiologic features. Results Fifty-seven point one percent (57.1%; 40/70) were RT-PCR positive, and 42.9% (30/70) were RT-PCR negative patients. The respiratory rate was higher among negative patients (P = 0.02), whereas the mean duration of fever was longer (3.34 vs 2.5; P = 0.022) among positive patients. At presentation, RT-PCR-negative patients had lower saturation of peripheral oxygen (SpO2) (near significant P = 0.058). Evaluation of co-morbidities revealed no differences. The neutrophil/lymphocyte ratio (NLR) (4.57 vs 6.52; P = 0.048), C-reactive protein (CRP) (9.97 vs 22.7; P = 0.007), and serum ferritin (158 vs 248.52; P = 0.010) were higher in patients who tested negative for RT-PCR. Thrombocytopenia (2.42 vs 1.76; P = 0.009), D-dimer levels (408.91 vs 123.06; P = 0.03), and interleukin (IL-6) levels (219.3 vs 80.81; P = 0.04) were significantly elevated among RT-PCR positive patients. The percentage of lung involvement in negative cases was 42.29+/-22.78 vs 36.21+/-21.8 in positive cases (P=0.23). The CT severity score was similar in both cohorts. Conclusion Both RT-PCR-positive and negative patients have similar clinical, biochemical, and radiological features. Considering that we are amidst a pandemic, it is advisable to have a similar approach irrespective of the RT-PCR report and triage and isolate accordingly. We recommend an RT-PCR-negative intensive care unit (ICU) ward and that the treating physician take a call on the management with a holistic approach driven clinically by the laboratory findings and helped by radiological findings. Stressing only on the RT-PCR report for management can be counterproductive.

Computed tomography findings and clinical manifestations in different clinical types of coronavirus disease 2019

OBJECTIVE: Since the coronavirus disease 2019 (COVID-19) outbreak in Wuhan in 2019, the virus has spread rapidly. We investigated the clinical and computed tomography (CT) characteristics of different clinical types of COVID-19. MATERIALS AND METHODS: We retrospectively analyzed clinical and chest CT findings of 89 reverse transcription polymerase chain reaction confirmed cases from five medical centers in China. All the patients were classified into the common (n = 65), severe (n = 18), or fatal (n = 6) type. CT features included lesion distribution, location, size, shape, edge, density, and the ratio of lung lesions to extra-pulmonary lesions. A COVID-19 chest CT analysis tool (uAI-discover-COVID-19) was used to calculate the number of infections from the chest CT images. RESULTS: Fatal type COVID-19 is more common in older men, with a median age of 65 years. Fever was more common in the severe and fatal type COVID-19 patients than in the common type patients. Patients with fatal type COVID-19 were more likely to have underlying diseases. On CT examination, common type COVID-19 showed bilateral (68%), patchy (83%), ground-glass opacity (48%), or mixed (46%) lesions. Severe and fatal type COVID-19 showed bilateral multiple mixed density lesions (56%). The infection ratio (IR) increased in the common type (2.4 [4.3]), severe type (15.7 [14.3]), and fatal type (36.9 [14.2]). The IR in the inferior lobe of both lungs was statistically different from that of other lobes in common and severe type patients (P < 0.05). However, in the fatal type group, only the IR in the right inferior lung (RIL) was statistically different from that in the right superior lung(RUL), right middle lung (RML), and the left superior lung (LSL) (P < 0.05). CONCLUSION: The CT findings and clinical features of the various clinical types of COVID-19 pneumonia are different. Chest CT findings have unique characteristics in the different clinical types, which can facilitate an early diagnosis and evaluate the clinical course and severity of COVID-19.

Manual severity evaluation methods for novel coronavirus pneumonia based on computed tomography imaging

Computed tomography (CT) examination plays an indispensable role in the diagnosis of coronavirus disease-2019 (COVID-19). Many studies have evaluated the severity of COVID-19 based on CT images, with the severity of COVID-19 being evaluated either manually or by using artificial intelligence. In this review, the recently reported methods for manually evaluating COVID-19 severity based on CT images are summarized and divided into three categories: evaluation based on the extent of abnormalities;evaluation based on the characteristics of abnormalities;and evaluation based on both the extent and characteristics of abnormalities.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

Epidemiological features and dynamic changes in blood biochemical indices for COVID-19 patients in Hebi.

BACKGROUND: Millions of people have died of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and retrospective studies of the disease in local regions are necessary. AIM: To characterize the epidemiological features and dynamic changes in blood biochemical indices for SARS-CoV-2-infected patients in Hebi, a representative city with a large floating population in North China. METHODS: From January 25 to February 10, 2020, the clinical data of patients who tested positive for SARS-CoV-2 by quantitative real-time polymerase chain reaction in Hebi city (China) were evaluated at admission, and laboratory data for hematologic parameters, inflammatory indices, coagulation function indices, liver function indices, blood lipid indices, renal function indices, myocardial enzyme activities and five blood biochemical markers of immunity were evaluated at admission, upon hospitalization and before discharge. RESULTS: Sixteen confirmed COVID-19 patients developed pneumonia but were cured after adequate treatment. Fever and fatigue were the common symptoms. The most common laboratory abnormalities of patients at admission were leukopenia, eosinopenia, decreased percentage of eosinophils, elevated high sensitivity C-reactive protein and fibrinogen levels, hypoalbuminemia, mildly increased aspartate transferase activity and levels of bilirubin, and increased levels of ß2-microglobulin. Importantly, aggravated liver dysfunction was detected in most patients, which may be partially attributed to virus infection as well as medicinal treatment. CONCLUSION: This study provides several potential diagnostic markers and dynamic biochemical indices of disease progression to better prevent, diagnose and treat COVID-19 infection.

Human Umbilical Cord Mesenchymal Stromal Cell Treatment of Severe COVID-19 Patients: A 3-Month Follow-Up Study Following Hospital Discharge.

Previously, we demonstrated the therapeutic effects of human umbilical cord mesenchymal stromal cells (hUC-MSCs) in severe coronavirus disease 2019 (COVID-19) patients. In this 3-month follow-up study, we examined discharged patients who had received hUC-MSC therapy to assess the safety of this therapy and the health-related quality of life (HRQL) of these patients. The follow-up cohort consisted of 28 discharged severe COVID-19 patients who received either the standard treatment (the control group) or the standard treatment plus hUC-MSC therapy. We examined liver function, kidney function, pulmonary function, coagulation, tumor markers, and vision. We also conducted electrocardiography (ECG) analysis, let the patients answer the St. George's Respiratory Questionnaire (SGRQ), and performed computed tomography (CT) imaging for assessing the lung changes. No obvious adverse effects were observed in the hUC-MSC group after 3 months. Measurements of blood routine index, C-reactive protein and procalcitonin, liver and kidney function, coagulation, ECG, tumor markers, and vision were almost within the normal ranges in both the treatment and control groups. Forced expiratory volumes in 1 s (FEV1) (% of predicted) were 71.88% ± 8.46% and 59.45% ± 27.45% in the hUC-MSC and control groups (P < 0.01), respectively, and FEV1/forced vital capacity (FEV1/FVC) ratios were 79.95% ± 8.00% and 58.97% ± 19.16% in the hUC-MSC and control groups, respectively (P < 0.05). SGRQ scores were lower in the hUC-MSC group than in the control group (15.25 ± 3.69 vs. 31.9 ± 8.78, P < 0.05). The rate of wheezing in the hUC-MSC group was also significantly lower than that in the control group (37.5% vs. 75%, P < 0.05). There were no significant differences in CT scores between the two groups (0.60 ± 0.88 vs. 1.00 ± 1.31, P = 0.917). Overall, the intravenous transplantation of hUC-MSCs accelerated partial pulmonary function recovery and improved HRQL, indicating relative safety and preliminary efficacy of this treatment for patients with severe COVID-19.

Non-Infectious Diseases Compatible With COVID-19 Pneumonia.

While the definitive diagnosis of the coronavirus disease 19 (COVID-19) is mainly made by the polymerase chain reaction (PCR), some PCR-negative cases are diagnosed typically by a computed tomography (CT) scan's radiology. However, there are many different infectious and non-infectious diseases that have radiology like COVID-19. We are presenting a case of a patient having symptoms and a CT scan radiology comparable to that of COVID-19 and also having eosinophilia. The patient was initially diagnosed and treated as a COVID-19 patient. The patient stated that she had always complained of having dyspnea and cough, but it had increased even more in the past few days. Her thorax CT revealed bilateral ground-glass opacities with upper lobe predominance, which was reported as highly compatible with COVID-19 by radiologists. COVID-19 PCR result was negative twice. In laboratory results, eosinophil count was 2,850/mm3 and total Ig was 768 IU/mL. However, when the laboratory values and the radiological findings were combined with the patient's history, COVID-19 was excluded and the chronic eosinophilic pneumonia was accepted as a diagnosis. Clinicians more focused on COVID-19 while questioning the patients and while evaluating the laboratory and the radiological findings make it easier to miss other infectious and non-infectious diseases. Assessing the complete blood count result, focusing on the lymphocyte value, also makes it easy to skip eosinophilia.

Serum Amyloid A is a biomarker of severe Coronavirus Disease and poor prognosis.

BACKGROUND: To explore the significance of SAA in evaluating the severity and prognosis of COVID-19. METHODS: A total of 132 patients with confirmed COVID-19 who were admitted to a designated COVID-19 hospital in Wuhan, China from January 18, 2020 to February 26, 2020 were collected. The dynamic changes of blood SAA, CRP, PCT, WBC, Lymphocyte (L), PLT, CT imaging, and disease progression were studied. All patients completed at least twice laboratory data collection and clinical condition assessment at three time points indicated for this study; The length of hospital stay was longer than 14 days prior to February 26, 2020. RESULTS: COVID-19 patients had significantly increased SAA and CRP levels, while L count decreased, and PCT, WBC, and PLT were in the normal range. As disease progressed from mild to critically severe, SAA and CRP gradually increased, while L decreased, and PLT, WBC, and PCT had no significant changes; ROC curve analysis suggests that SAA/L, CRP, SAA, and L count are valuable in evaluating the severity of COVID-19 and distinguishing critically ill patients from mild ones; Patients with SAA consistently trending down during the course of disease have better prognosis, compared with the patients with SAA continuously rising; The initial SAA level is positively correlated with the dynamic changes of the serial CT scans. Patient with higher initial SAA level are more likely to have poor CT imaging. CONCLUSIONS: SAA and L are sensitive indicators in evaluating the severity and prognosis of COVID-19. Monitoring dynamic changes of SAA, combined with CT imaging could be valuable in diagnosis and treatment of COVID-19.