CT Severity Score Research Articles

Pulmonary Thromboembolism on CT Pulmonary Angiography of Covid-19 Patients and Its Correlation to CT Severity Score, D-dimer, and Ferritin Levels: A Prospective and Retrospective Study

Pulmonary Thromboembolism on CT Pulmonary Angiography of Covid-19 Patients and Its Correlation to CT Severity Score, D-dimer, and Ferritin Levels: A Prospective and Retrospective Study

ETIOLOGY, CLINICAL PROFILE, ASSESSMENT AND COMPARISON OF SCORING SYSTEMS IN PATIENTS DIAGNOSED WITH ACUTE PANCREATITIS IN A TERTIARY CARE CENTRE

Background:Acute pancreatitis is a sudden inammation of the pancreas with an incidence 13–45 /1,00,000. A Bedside Index for Severity in Acute Pancreatitis (BISAP) has recently been proposed as an accurate and simple method for early identication of persistent organ failure and mortality. CT, as used to aid the diagnosis and staging of acute pancreatitis, has greatly improved and has changed the clinical management of this condition. 50 patients who came Methods: with acute abdomen and diagnosed with acute pancreatitis were selected satisfying inclusion and exclusion criteria. BISAP score and CT severity index was calculated and compared. Results: Out of 50 patients mild, moderate and severe acute pancreatitis was identied in 35, 9 and 6 patients respectively based on CT severity score index(CTSI). Out of 50 cases,47 had BISAP score < 3 and 3 had >3.BISAP score as a predictor of prognosis has a signicant relation as evident by the data in our study (p value<0.05).BISAP score and CTSI are used for severity assessment of acute pancreatitis, both these scoring systems showed positive correlation in assessing the severity. Early evaluation of the Conclusion: severity of acute pancreatitis is essential to allow the clinician to predict the patient's clinical course, estimate prognosis, and determine the need for admission to the intensive care unit. BISAP score is relatively simple & accurate in predicting the clinical severity of Acute Pancreatitis with a prognostic accuracy of BISAP similar to CTSI.

Early Prediction and HRCT Evaluation of Post Covid-19 Related Lung Fibrosis.

Early detection of post-COVID-19-related lung fibrosis is very important for the early introduction of treatment and to minimize morbidity and mortality. The aim of this study is the early detection and evaluation of post-COVID-19 fibrosis by high-resolution computed tomography (HRCT). This prospective study included 115 patients irrespective of age and sex, who tested positive for the SARS-CoV-2 by nasopharyngeal swab (RT PCR), admitted to the Dhaka North City Corporation (DNCC) dedicated COVID-19 hospital, Dhaka, and discharged after recovery. Patients went through a chest HRCT scan at least once during their hospital stay and another scan during follow-up after hospital discharge and 8 to 12 weeks of negative RT-PCR report. Among 100 patients 23 patients had >50% of total lung involvement by visual assessment. Thirty-three patients had 25% to 50% of total lung volume involvement. Twenty-seven patients had less than 25% of total lung involvement, whereas 17 patients had no visual fibrotic change on the follow-up HRCT scan. A statistical association was found between age, gender, smoking, and severe form of lung fibrosis (P < .05). Patients with mild CT severity score (⩽8) had a very good prognosis. Patients who were admitted to the hospital for more than 15 days were more prone to developing moderate and severe forms of fibrosis. Patients who received at least 2 doses of the COVID-19 vaccine had less severe forms of fibrosis as well as more cases of complete radiological recovery. On the HRCT scan, most of the patients had bilateral, peripheral (68%), and predominant mid & lower lobar parenchymal involvement. Early detection and HRCT evaluation of post-COVID-19 related lung fibrosis is very crucial for early management and introduction of anti-fibrotic drugs.

Correlation among semiquantitative High‐Resolution Computed Tomography severity scores and clinical and biochemical parameters in COVID‐19, is it really effective?

Correlation among semiquantitative High‐Resolution Computed Tomography severity scores and clinical and biochemical parameters in COVID‐19, is it really effective?

Development and validation of a predictive scoring system for in-hospital mortality in COVID-19 Egyptian patients: a retrospective study

SARS-CoV-2 virus has rapidly spread worldwide since December 2019, causing COVID-19 disease. In-hospital mortality is a common indicator for evaluating treatment outcomes. Therefore, the developing and validating a simple score system from observational data could assist in modulating the management procedures. A retrospective cohort study included all data records of patients with positive PCR for SARS-CoV-2. The factors that associated with mortality were analyzed, then allocation of potential predictors of mortality was executed using different logistic regression modeling, subsequently scoring system was developed from the most weighted predictors. The mortality rate of patients with COVID-19 pneumonia was 28.5% and 28.74%, respectively. The most significant factors that affected in-hospital mortality were old age (> 60 years), delay in hospital admission (> 4 days), high neutrophil/lymphocyte ratio “NLR” (> 3); higher computed tomography severity score; and CT-SS (> 20), in addition to using remdesivir and tocilizumab in the treatment protocol (P < 0.001 for all). The validity of the newly performed score was significant; the AUC was 85%, P < 0.001, and its prognostic utility was good; the AUC was 75%, P < 0.001. The prognostic utility of newly developed score system (EGY.Score) was excellent and could be used to adjust the treatment strategy of highly at-risk patients with COVID-19 pneumonia.

Co-Relation Between Androgenetic Alopecia and Severity of COVID-19 Disease - A Cross-Sectional Study

Objective: To find the correlation between the degree of androgenetic alopecia and the severity of COVID-19 disease.&#x0D; Study Design: Cross-sectional study.&#x0D; Place and Duration of the Study: Dermatology department, PEMH, Rawalpindi Pakistan from Feb to Aug 2021.&#x0D; Methodology: A total of 227 patients (male and female) of COVID-19 admitted in a Corona ward of Pak Emirates Military Hospital, Rawalpindi, Pakistan were selected randomly. The degree of androgenetic alopecia was assessed with the help of using the Hamilton-Norwood Scale (HNS) for men and the Ludwig Scale (LS) for women, and the severity of COVID-19 was graded based on CT severity score (CTSS).&#x0D; Results: Out of the total, 161 (71%) were male, and 66 (29%) were female. Out of 161 males, 31 (19.2%) had no alopecia, and 130 (80.7%) had some degree of alopecia. Out of patients with alopecia, 33 had moderate alopecia, and 97 had severe alopecia. Out of 66 females, 32 (48.5%) had no alopecia, while 34 (51.5%) had some degree of alopecia.&#x0D; Conclusion: High frequency of androgenetic alopecia in severely ill-hospitalized patients of COVID-19 suggests that androgen has a vital role in the disease severity of COVID-19.

The Relationship Between Chest Computed Tomography Severity Scores and Demographic Features, Laboratory Parameters and Mortality in Patients with COVID-19

The Relationship Between Chest Computed Tomography Severity Scores and Demographic Features, Laboratory Parameters and Mortality in Patients with COVID-19

COVID-19 chest CT and laboratory features of B.1.617.2 (Delta variant) vs B.1.1.7 (Alpha variant) surge: a single center case-control study.

To assess clinical, laboratory and radiological differences between Delta and Alpha SARS-CoV-2 variants. Twenty SARS-CoV-2 patients admitted from 30th of August to 30th of October 2021 (period with estimated highest prevalence of Delta variant circulation in Italy) were enrolled. Patients were matched in a 1:1 ratio with same gender and same age +/- 2 years controls admitted from 1st of September 2020 to 30th of January 2021 (predominant circulation of Alpha variant). Chest computed tomography (CT) were retrospectively evaluated. Main clinical parameters, radiological and laboratory findings were compared between two groups. Patients with probable Delta variant had significantly higher CT severity scores, lower PaO2/FiO2 ratio and higher C-reactive protein and lactate dehydrogenase levels at admission. On multivariate analysis, probable Delta variant infection was associated with higher CT severity score. Ground glass opacities and crazy paving patterns were more frequently noticed than consolidation, with the latter being more frequent in Delta cohort, even though not significantly. According to prevalent imaging pattern, the consolidation one was significantly associated with pregnancy (p=0.008). Patients admitted during predominance of Delta variant circulation had a more severe lung involvement compared to patients in infected when Alpha variant was predominant. Despite imaging pattern seems to be not influenced by viral variant and other clinical variables, the consolidative pattern was observed more frequently in pregnancy.

Chest CT Severity Score in COVID-19 Patients: Comparison between Diabetic and Non-Diabetic Patients

Chest CT Severity Score in COVID-19 Patients: Comparison between Diabetic and Non-Diabetic Patients

A RETROSPECTIVE STUDY OF PREDICTORS OF MORTALITY IN PATIENTS WITH COVID-19 ADMITTED AT A TERTIARY CARE HOSPITAL.

Background: COVID-19 is associated with huge morbidity and mortality in India. Identication of factors associated with mortality would make a difference in the management of COVID-19 infection-related illness. To eval Objective: uate the risk factors which can predict the outcome in covid 19 survivors and non survivors including patient characteristics, comorbidities, laboratory abnormalities and modes of oxygenation and ventilation among 200 patients with COVID-19 infection admitted to a tertiary care hospital fullling inclusion and exclusion criteria. All the data collected were coded and entered in Microsoft Excel sheet which was re-checked and analyzed using SPSS statistical software version 25. Results: Out of 200 cases, 126(63%) patients were male while 74(37%) patients were female. The overall case-fatality rate among admitted cases was 24(12%) [In non -survivors males (12.7%) and females (0.8%)]. The Univariate analysis showed that more patients in the deceased group had respiratory rate of &gt;30 cycles/min(p&lt;0.001) spo2 75 +/- 13 (p&lt;0.001), Patient who had pulse rate 96+/-19 (p=0.003) found to be signicantly associated. The Mean ± SD of white blood cell count, NLR, SGOT, APTT, S.Bilirubin , Total protein ,Albumin, Creatinine ,RBS, Trop I. CRP, D dimer, LDH ,Ferritin, IL6 ,PCT were statistically signicant and affecting mortality. In non-survived patients needed higher mode of oxygenation .out of 13 patients who required NIV on admission ,15 patients survived and 8 patient non-survived(P=0.002). out of 13 patients who required invasive ventilation, 5 patients survived and 8 patients non survived (p=0.001). Those who received more days of oxygenation they are not survived (6.25±4.19 P=0.001) and those who had prolonged ventilatory days also not survived (4.46±3.50 P=&lt;0.001). Those who had admitted in ICU for mean days of 5±3.60 (p= &lt;0.001) also not survived. All above differences were found to be statistically signicant. There was no signicant difference in the age, gender, clinical features, preexisting comorbidities between the two groups (p&gt;0.05). Multivariate analysis using binary logistic regression was done to nd out independent factors associated with mortality. Logistic regression performed for signicant variables found in the univariate analysis showed higher HRCT CT severity score associated higher odds of death. Conclusion: The higher HRCT CT severity score associated higher odds of death. Lab markers such as raised TLC, NLR, CRP, LDH, ferritin, Ddimer, SGOT, APTT, Sodium, Creatinine, IL6, PCT and low albumin were associated with worse outcomes in COVID-19 illness.

Chest CT in covid-19 pneumonia's follow-up: A 30 patients case series.

Lung abnormalities do not fully resolve in all Covid-19 survivors and may progress to fibrosis. Understanding post-COVID lung changes helps identify patients susceptible of post-COVID-19 sequelae. We analyzed scannographic residual lung abnormalities and the full resolution percentage on intermediate- and long-term follow-up (3 months or more). Data from 30 RT-PCR positive COVID-19 patients undergoing at least one follow-up chest CT at Ibn Sina Hospital, with a minimal time interval of 3 months between the RT-PCR and the CT performance were gathered retrospectively. The following elements were analyzed: (1) lung opacities, (2) distribution, (3) dominant lung opacity, (4) Sub-pleural bands, (5) Interlobular septal thickening, (6) Vascular dilatation, (7) Bronchiectasis, (8) Honey combing, (9) Architectural distortion, (10) mosaic attenuation, and (11) Additional findings: Enlarged lymph nodes, Pleural and Pericardial fluid. To evaluate the degree of lung opacification, a score founded on visual evaluation of the lung involvement's percentage was employed. Patients were then subdivided into two categories: (1) no residual opacities and (2) remaining pulmonary opacities. 30 patients were enrolled. The age ranged between 40 and 87 years. CT was indicated for symptoms or functional impairment. The time range between the positive RT-PCR and Follow-up CT varied between 3 and 12 months. CT severity score ranged between o and 23. Residual lung opacities were present in 24 cases (80%). The dominant lung opacities were Ground glass (46.7%), and linear/curvilinear opacities (23.3%). Signs of fibrosis were present in 9 patients (30%). CT abnormalities following Covid-19 pneumonia's prevalence varies based on the extent of the original lung affection and the time gap since the acute phase. Residual anomalies' effects on respiratory physiology, symptoms, and quality of living are unknown. Maintained monitoring of COVID-19 survivors with clinical examination, iterative pulmonary function tests, and HRCT is advised.

Is a high chest CT severity score a risk factor for an increased incidence of long-term neuroimaging findings after COVID-19?

ObjectivesWe aimed to determine the incidences of neuroimaging findings (NIF) and investigate the relationship between the course of pneumonia severity and neuroimaging findings. Materials and methodsOur study was a retrospective analysis of 272 (>18 years) COVID-19 patients who were admitted between “March 11, 2021, and September 26, 2022". All patients underwent both chest CT and neuroimaging. The patient's chest CTs were evaluated for pneumonia severity using a severity score system (CT-SS). The incidence of NIF was calculated. NIF were categorized into two groups; neuroimaging positive (NIP) and neuroimaging negative (NIN). Consecutive CT-SS changes in positive and negative NIF patients were analyzed. ResultsThe median age of total patients was 71; IQR, 57-80. Of all patients, 56/272 (20.6%) were NIP. There was no significant relationship between NIP and mortality (p = 0.815) and ICU admission (p = 0.187). The incidences of NIF in our patients were as follows: Acute-subacute ischemic stroke: 47/272 (17.3%); Acute spontaneous intracranial hemorrhage: 13/272 (4.8%); Cerebral microhemorrhages: 10/272 (3.7%) and Cerebral venous sinus thrombosis: 3/25 (10.7%). Temporal change of CT-SSs, there was a statistically significant increase in the second and third CT-SSs compared to the first CT-SS in both patients with NIP and NIN. ConclusionOur results showed that since neurological damage can be seen in the late period and neurological damage may develop regardless of pneumonia severity.

Echocardiographic Assessment of Right Ventricular Function in COVID-19 Recovered Patients at a Tertiary Care Hospital

Objective: To detect residual RV dysfunction on a right ventricle focused Transthoracic Echocardiography (TTE) in COVID-19 infection survivors with lung involvement.&#x0D; Study Design: Analytical Cross sectional study design.&#x0D; Place and Duration of Study: Combined Military Hospital Abbottabad Pakistan, Feb 2022 to Apr 2022.&#x0D; Methodology: 87 patients who had suffered from and survived COVID-19 infection with definite involvement on CT scans of the chest were studied after discharge. Echocardiography was done to determine the RV anatomical and functional parameters to determine the relationship between extent of lung involvement and transthoracic echocardiographic parameters.Data was entered in Microsoft excel and exported to SPSS v 23 for analysis. &#x0D; Results: The initial sample size was of 87 patients. Due to suboptimal ECHO studies 7 cases were excluded. Males represented 62.5% (n=50) and females 37.5% (n=30). The ages ranged from 27 to 80 years, mean 53.08±12.77 years. Based on the CT severity score severe infections were 61.3 %(n=49) and mild 38.8% (n=31). The CTSS ranged from 6 to 30 with a mean of (17.74±7.13). In our study we found that on TTE, there was a statistically significant difference in 2 of the anatomical parameters; RVOT PLAX (RVOT diameter in Parasternal long axis view) [27.4 vs 28.3; p=0.02], RVOT-Dis (Distal RVOT dia) [22.8 vs 24; p=0.01]. In addition, there was a statistically significant difference in all the functional parameters of RV function TDI S vel (Systolic Tissue Doppler Velocity of the Tricuspid Annulus by Tissue doppler imaging) [7 vs4.9; p&lt;0.0001], RIMPPW (Right Ventricular Index of Myocardial Performance by Pulse wave doppler) [0.46 vs0.38; p&lt;0.0001], RIMP-TDI (Right Ventricular Index of Myocardial Performance by Tissue doppler imaging) [0.57 vs 0.48; p&lt;0.0001]. RV-FAC (RV-Fractional Area Change) was statistically insignificant. [42.8% vs 43.2%; p=0.6].&#x0D; Conclusion: Our study showed that in patients with definite lung involvement on chest CT scans, functional echocardiographic parameters of Right ventricular function were affected in line with the severity of lung involvement.

Role of Tocilizumab in Combating Cytokine Storm in Moderate &amp; Severe Covid 19 Patients: Retrospective Observational Study

Background: The wide spread of COVID-19 disease and mortality associated with it as never seen before urged the medical research field to formulate and investigate the efficacy of various new drugs alongside with the existing drugs.&#x0D; Objective: To evaluate the potential benefits of Tocilizumab (TCZ) in addition to the Standard of Care (SoC) in reducing mortality in moderate &amp; severely ill COVID 19.&#x0D; Methodology: Study population is sorted by 1:1 matching depending on the High-Resolution Computed Tomography (HRCT) Chest CT Severity Score. Outcome is measured as deaths, discharge with or without Long Term Oxygen Therapy (LTOT) along with clinical improvement of the patient measured using 9 points ordinary scale score of WHO and length of stay in Intensive Care Unit (ICU) post administration &amp; levels of inflammatory markers (CRP, IL 6) on day of administration- baseline (D0), 1- &amp; 3-days post administration (D+1 &amp; D+3). The group received TCZ+SoC is considered as Test Group and the group received only SoC as Control Group.&#x0D; Results: Deaths and discharge with LTOT were slightly higher in test group with OR 1.68 &amp; 1.63 respectively. Clinical improvement in terms of 9-point ordinary scale score &amp; difference in the levels of CRP &amp; IL 6 was insignificant in both the groups. No difference in post administration ICU stay is observed between the groups.&#x0D; Conclusions: Our study concludes no marked benefits with the addition of TCZ to the SoC in treating moderate and severe COVID 19 patients.

A Multi-centric Evaluation of Deep Learning Models for Segmentation of COVID-19 Lung Lesions on Chest CT Scans

Background: Chest computed tomography (CT) scan is one of the most common tools used for the diagnosis of patients with coronavirus disease 2019 (COVID-19). While segmentation of COVID-19 lung lesions by radiologists can be time-consuming, the application of advanced deep learning techniques for automated segmentation can be a promising step toward the management of this infection and similar diseases in the future. Objectives: This study aimed to evaluate the performance and generalizability of deep learning-based models for the automated segmentation of COVID-19 lung lesions. Patients and Methods: Four datasets (2 private and 2 public) were used in this study. The first and second private datasets included 297 (147 healthy and 150 COVID-19 cases) and 82 COVID-19 subjects. The public datasets included the COVID19-P20 (20 COVID-19 cases from 2 centers) and the MosMedData datasets (50 COVID-19 patients from a single center). Model comparisons were made based on the Dice similarity coefficient (DSC), receiver operating characteristic (ROC) curve, and area under the curve (AUC). The predicted CT severity scores by the model were compared with those of radiologists by measuring the Pearson’s correlation coefficients (PCC). Also, DSC was used to compare the inter-rater agreement of the model and expert against that of 2 experts on an unseen dataset. Finally, the generalizability of the model was evaluated, and a simple calibration strategy was proposed. Results: The VGG16-UNet model showed the best performance across both private datasets, with a DSC of 84.23% ± 1.73% on the first private dataset and 56.61% ± 1.48% on the second private dataset. Similar results were obtained on public datasets, with a DSC of 60.10% ± 2.34% on the COVID19-P20 dataset and 66.28% ± 2.80% on a combined dataset of COVID19-P20 and MosMedData. The predicted CT severity scores of the model were compared against those of radiologists and were found to be 0.89 and 0.85 on the first private dataset and 0.77 and 0.74 on the second private dataset for the right and left lungs, respectively. Moreover, the model trained on the first private dataset was examined on the second private dataset and compared against the radiologist, which revealed a performance gap of 5.74% based on DSCs. A calibration strategy was employed to reduce this gap to 0.53%. Conclusion: The results demonstrated the potential of the proposed model in localizing COVID-19 lesions on CT scans across multiple datasets; its accuracy competed with the radiologists and could assist them in diagnostic and treatment procedures. The effect of model calibration on the performance of an unseen dataset was also reported, increasing the DSC by more than 5%.

A SINGLE-CENTRE RETROSPECTIVE AND OBSERVATIONAL INVESTIGATION ON THE MANIFESTATIONS OF COVID-19 ON CHEST HRCT IN THEPOPULATION OF ANDHRA PRADESH, INDIA

Background: The clinical symptoms of COVID-19 in conjunction with chest high resolution computed tomography (HRCT) can give quick screening and determine the disease's severity. HRCT plays an important role in the evaluation and clinical management of COVID-19, which would benet from a more comprehensive overview of its clinical diagnosis and therapy. To dene the spectrum of HRCT results in Objective: COVID 19 individuals with symptoms and to connect HRCT ndings with clinical symptoms of the disease. A retrospective r Methods: esearch of 1513 COVID patients recently diagnosed with COVID-19 and positive RT-PCR test ndings; both sexes were included from the middle of March to the end of May 2021. The patients were separated into three age groups and their HRCT CT severity scores (CTSS) were evaluated. Different age groups' clinical symptoms were connected with the derived CTSS. Results: The average age of the patients was 50.14 percent, with 34% falling between the ages of 35 and 54. The majority of them had fever, cough, dyspnea, myalgia, and headache, but other symptoms like sore throat, diarrhoea, nausea, anosmia, and chest discomfort were less common. In the current study, clinical characteristics had the strongest relationship with moderate CTSS. HRCT ndings include ground-glass opacity (GGO), consolidation, bronchovascular thickening, crazy paving look, subpleural bands/brosis, and bronchiectasis. In moderate and severe patient groups, the CTSS link with lung lobe distribution and gender was highly signicant. Bilateral lung distribution changes (83.6%) were more common in group 2 than central and peripheral distribution changes (70.5%), with lower lobe involvement in both genders. Conclusion: HRCT helps identify COVID-19's pulmonary symptoms in diagnosis and treatment. Imaging patterns depending on infection duration help understand pathophysiology and predict illness development and effects. This study may link clinical symptoms to CTSS and COVID-19 pulmonary changes. It could mean understanding the following wave's features and management. HRCT chest detects early parenchymal abnormalities, measures disease severity in all symptomatic patients, and diagnoses COVID infection regardless of RT-PCR status.

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.

Study of thymus volume and density in COVID-19 patients: Is there a correlation in terms of pulmonary CT severity score?

BackgroundThymus has a pivotal role in combating infectious diseases. Although some reviews have been published about its critical role in COVID-19, there is not enough research. In this study, the size and density of thymus related to computed tomography pulmonary severity score (CT-SS) were researched.ResultsA total of 196 patients were analyzed with a mean age of 52.54 ± 18.78 years; 97 (49.5%) of them were RT-PCR (−) and 99 (50.5%) were RT-PCR (+). Within RT-PCR (+) group 62 (62.6%) of them had pneumonia with a mean CT-SS of 9.37 ± 8.83; within RT-PCR (−) group 20 (20.6%) of them had pneumonia with the mean CT-SS of 12.00 ± 10.18. CT-SS had moderate negative correlation with thymus volume and thymus maximum diameter in patients having nodular-type thymus (R = −0.591, P = 0.02; R = −0.515, P = 0.049, respectively). Homogenous fat infiltration was more commonly seen in RT-PCR (−) group while reticular and nodular types were commonly seen in RT-PCR (+) group (p = 0.015). The mean volume and maximum diameter of thymus were statistically significantly higher in RT-PCR (+) group (p = 0.027 and p = 0.048, respectively).ConclusionThis study showed the higher thymic volume and maximum diameter and more involution in COVID-19 patients. CT-SS had a moderate negative correlation with thymus volume and thymus maximum diameter. Pneumonia was more frequent in COVID patients, but mean CT-SS of the non-COVID cases was higher.

Point-of-care Lung Ultrasound, Lung CT and NEWS to Predict Adverse Outcomes and Mortality in COVID-19 Associated Pneumonia.

Introduction: The appraisal of disease severity and prediction of adverse outcomes using risk stratification tools at early disease stages is crucial to diminish mortality from coronavirus disease 2019 (COVID-19). While lung ultrasound (LUS) as an imaging technique for the diagnosis of lung diseases has recently gained a leading position, data demonstrating that it can predict adverse outcomes related to COVID-19 is scarce. The main aim of this study is therefore to assess the clinical significance of bedside LUS in COVID-19 patients who presented to the emergency department (ED). Methods: Patients with a confirmed diagnosis of SARS-CoV-2 pneumonia admitted to the ED of our hospital between March 2021 and May 2021 and who underwent a 12-zone LUS and a lung computed tomography scan were included prospectively. Logistic regression and Cox proportional hazard models were used to predict adverse events, which was our primary outcome. The secondary outcome was to discover the association of LUS score and computed tomography severity score (CT-SS) with the composite endpoints. Results: We assessed 234 patients [median age 59.0 (46.8-68.0) years; 59.4% M), including 38 (16.2%) in-hospital deaths for any cause related to COVID-19. Higher LUS score and CT-SS was found to be associated with ICU admission, intubation, and mortality. The LUS score predicted mortality risk within each stratum of NEWS. Pairwise analysis demonstrated that after adjusting a base prediction model with LUS score, significantly higher accuracy was observed in predicting both ICU admission (DBA -0.067, P = .011) and in-hospital mortality (DBA -0.086, P = .017). Conclusion: Lung ultrasound can be a practical prediction tool during the course of COVID-19 and can quantify pulmonary involvement in ED settings. It is a powerful predictor of ICU admission, intubation, and mortality and can be used as an alternative for chest computed tomography while monitoring COVID-19-related adverse outcomes.

A Study on Correlation of Hematological Parameters with Computed Tomography Severity Score in COVID-19 Patients in a Tertiary Care Center

A Study on Correlation of Hematological Parameters with Computed Tomography Severity Score in COVID-19 Patients in a Tertiary Care Center