CT Severity Score Research Articles

High Resolution Computed Tomography findings and Computed Tomography severity index in COVID-19 Infection Correlated with Age and Gender

Introduction: The new coronavirus disease -19 (COVID-19) is caused by SARS-CoV2 strain of coronavirus. The Computed tomography (CT) severity index is a scoring system used to assess the lung changes and involvement by COVID-19 based on approximate estimation of pulmonary involved areas. This study was done to identify the spectrum of CT chest findings and CT severity index in COVID-19 infection and its correlation with age and gender.
 Methods: Patients with COVID-19 infection with positive PCR results and positive pulmonary CT findings were included in the study. All these patients underwent high-resolution computed tomography (HRCT) of the chest. The CT scan severity score in all of these patients was calculated and the results were analyzed by SPSS version 21.
 Results: A total of 104 patients with confirmed COVID-19 infection were included in this study. There were 59 males (56.73%) and 45 females (43.3%) in this study. There was a higher chest severity score in males compared to females. However, there was no significant correlation between the age and CT chest severity score.
 Conclusion: HRCT chest can help in the early identification of the patients who need intensive care. Early admission and intensive care of the patients with high CT severity scores may help to reduce the mortality of COVID-19 patients.

Predicting ICU Length of Stay in COVID-19 Patients Using a Multivariable Model Incorporating Clinical, Laboratory, and Imaging Features

Abstract: Objective: To predict ICU length of stay (LOS) using a multivariable model incorporating clinical, and laboratory and imaging features in hospitalized COVID-19 patients, thereby stratifying patients and allocating resources accordingly. Methods: In this retrospective cohort study, 139 hospitalized patients (Aged between 3 to 99) with rRT-PCR confirmed COVID-19 pneumonia requiring intensive care, which had been discharged or deceased, were enrolled. Demographic, clinical, and laboratory findings of eligible patients were all extracted from electronic medical records and, if needed, through phone calls. Semi-quantitative CT severity score (CTSS) was calculated and assigned to each encoded patient independently and blindly. We used cox regression model to investigate the prognostic role of semi-quantitative CTSS, clinical and laboratory features to anticipate ICU-LOS. Results: 139 patients with rRT-PCR confirmed COVID-19 pneumonia (including 60 females and 79 males) with a mean age of 58.52 ± 20.58 (ranging from 3 to 99) were included. CTSS was not predictive of ICU-LOS. Additionally, CTSS of more than 11 was predictor of mortality (sensitivity, 60.3%; specificity, 58%; AUC, 0.605; 95% confidence interval, 0.508-0.702; P-value, 0.034), and CTSS of above 10 was predictor of oxygen therapy dependency (sensitivity, 70.2%; specificity, 68%; AUC, 699 /0; 95% confidence interval, 0.580-0.818; P-value, 0.002). CTSS was not significantly associated with respiratory rate and on-admission dyspnea, while it was inversely related to air-room SpO2 on the first day of admission (P <0.0001, r = -0.341). Conclusion: CTSS is capable of anticipating mortality rate and the chance of undergoing supportive oxygen therapy during ICU hospitalization, while it does not predict ICU-LOS, rate of mechanical ventilation, or corticosteroid therapy.

Chest CT Severity Score, CURB-65 Score, and Their Relationship with In-Hospital- Mortality in COVID-19 Patients

Abstract: Objective: With every new strain of the SARS-CoV-2 spreading on a fast pace across the borders, an easy-to-calculate and reliable scoring system seems invaluable to identify high-risk patients. This study aims to investigate the relationship between CT severity score (CTSS) and CURB-65 score with mortality in COVID-19 patients. Methods: This study was conducted on RT-PCR confirmed COVID-19 patients admitted to a tertiary teaching center during fifth national wave of disease in one of the early disease epicenters in the country. All enrolled patients underwent chest CT scan within first day of admission. CTSS and CURB-65 scores were calculated and assigned to patients, while radiologist was blinded to clinical and laboratory findings, and they were evaluated for their correlation with in-hospital mortality, additively and separately. Results: Total number of 216 patients (140 males) with a mean age of 56.02 ± 17.34 years (ranging from 4 to 95) were enrolled. We found no significant relationship between CURB-65 score and CTSS (correlation coefficient: 0.065; P: 0.338). CURB-65 scores above 1 was predictive of in-hospital mortality with sensitivity of 56.4% and specificity of 81.9% (P: 0), those for CTSS above 11 were 79.5% and 4 51.5%, respectively (P: 0.001). CURB-65 score >1 and CTSS >11 predicted in-hospital mortality with sensitivity and specificity of 61.5% and 79.7% (P: 0.000). CURB-65 score and CTSS had a higher sensitivity and specificity to predict mortality comparing to each of those separately, but these enhanced statistics were not significant. Conclusion: CURB-65 score is meaningfully stronger than CTSS to prognosticate in-hospital mortality in patients with COVID-19, and it is not significantly correlated with CTSS.

Predicting Mortality Rate in ICU-Admitted COVID-19 Patients Implementing Visual Semi-Quantitative CT Severity Scoring System

Abstract: Objectives: The aim of this study was to identify the clinical and laboratory features and CT scan (CT intensity score and pleural effusion) associated with COVID-19 pneumonia to evaluate the relationship between CT scan findings and mortality by comparing deceased patients with normal patients. Methods: In this retrospective case-control study, 290 ICU admitted patients with RT-PCR confirmed COVID-19 pneumonia were investigated. Totally, 150 deceased patients (with confirmed COVID-19 related death) were extracted from the COVID-19 registry of the affiliated university hospital belonging to mentioned period of time (in-hospital mortality subgroup, case), and 150 patients who survived the admission course were randomly selected from the same data set (surviving subgroup, control). Available electronic records for each patient were enlisted, including laboratory and clinical information, and their on-admission computed tomography (CT) images were reviewed. Mortality-related risk factors were compared between case and control subgroups. Results: The mean age of deceased patients (68.20±16.07) was significantly higher than that of the surviving patients (54.72± 19.50) (p <0.001). Diabetes, hypertension, and chronic kidney disease (CKD) were significantly related with higher mortality rates (62.2%, 58.7%, and 80.4% mortality in diabetic, hypertensive, and CKD patients versus 41.7%, 42.1%, and 35.9% in non-diabetics, normotensives, and patients without CKD). Additionally, the mean on-admission air-room SPO2 level in deceased patients (90%) was significantly lower than that of the survivors (93%) (p = 0.001). Lymphocyte count, neutrophil to lymphocyte ratio (NLR), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), lactate dehydrogenase (LDH), fasting blood sugar (BS), blood urea nitrogen (BUN), and Creatinine (Cr), mean CT severity score (CT-ss), and O2 supportive therapy requirement were significantly higher in the mortality subgroup (p <0.05). Pleural effusion showed no significant correlation with short-term mortality. CT-ss of >11, in isolation or in combination with above-mentioned prognosticators, was 64% or 81.4% sensitive, and 60% or of 78.6% specific, to predict mortality. Conclusions: Factors such as advanced age, underlying diseases such as diabetes, hypertension, and CKD, decreased air-room SPO2, and increased lymphocyte count, higher NLR, ESR, CRP, LDH, BS, BUN, and Cr level, as well as higher CT-ss and O2 supportive therapy, are all significantly correlated with higher mortality in ICU-admitted COVID-19 patients.

Cross-Sectional Study on Association between Inflammatory Markers and Chest Computed Tomography Severity Score in COVID-19 at Admission

Cross-Sectional Study on Association between Inflammatory Markers and Chest Computed Tomography Severity Score in COVID-19 at Admission

Correlation between D-dimer and computed tomography severity score in middle aged young adults with COVID-19 pneumonia: a retrospective study

Background: An unknown pneumonia broke out in Wuhan City in December 2019 and it was confirmed as an acute respiratory infectious disease caused by Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, formerly known as 2019-nCoV). Consumption coagulopathy, which should be obviated in order to decrease mortality, arises in disseminated intravascular coagulation with a decrease in fibrinogen and an increase in D-dimer levels. However, studies on the predictive and prognostic values of coagulation parameters in the setting of patients with COVID-19 are still limited. The objective of this retrospective study was to investigate the correlation of D-dimer and computed tomography severity score in patients with COVID-19 pneumonia.Methods: The present retrospective study was conducted among 108 subjects reported COVID RT-PCR positive admitted during the study period i.e.; January-August 2021 in the department of medicine of Rural Medical College, Loni. Pneumonia was confirmed by Computed tomography (CT) examination and coagulation test completed within 12 hr after admission were enrolled. Coagulation tests, which Fibrinogen (Fib) and D-dimer were performed. CT score was categorized into mild (0-7), moderate (8-16) and advanced grade (17-25 points).Results: The mean age of male and female was 38.52±5.34 and 35.67±3.22 years respectively, with an overall age of 37.79±4.58 years. Mean D-dimer level was 0.54±0.09, 0.91±0.22 and 1.96±0.47 mcg/ml among subjects having mild, moderate and severe CT score respectively. According to multivariate analysis, higher D-dimer (OR:3.61, p<0.01) was significantly associated with CT severity score.Conclusions: Study concluded that the D-dimer level's time point was matched to the time of CT scan, we have reasons to correlate that the D-dimer level may predict the severity of inflammation prior to coagulopathy/thrombosis.

Sequential Organ Failure Assessment Outperforms Quantitative Chest CT Imaging Parameters for Mortality Prediction in COVID-19 ARDS.

(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63–0.85), whereas CT severity scores (0.53, 95%-CI 0.40–0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34–0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64–0.89), compared to 0.55 (95%-CI 0.39–0.72) for CT severity scores and 0.51 (95%-CI 0.35–0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation.

Serum amyloid A, ferritin and carcinoembryonic antigen as biomarkers of severity in patients with COVID‑19

In view of the rapid spread of COVID-19 and the high mortality rate of severe cases, reliable risk stratifying indicators of prognosis are necessary to decrease morbidity and mortality. The aim of the present study was to evaluate the value of serum amyloid A (SAA) and carcinoembryonic antigen (CEA) as prognostic biomarkers in comparison to other predictors, including C-reactive protein (CRP) and ferritin levels. This study included 124 patients diagnosed with COVID-19, and they were assigned to one of two groups: Mild and severe, based on the severity of the infection. Radiological and laboratory investigations were performed, including evaluation of CRP, ferritin, D-Dimer, SAA and CEA levels. Significantly higher levels of CRP, ferritin, D-Dimer, SAA and CEA were observed in severe cases. SAA was significantly correlated with CRP (r=0.422, P<0.001), ferritin (r=0.574, P<0.001), CEA (r=0.514, P<0.001) and computed tomography severity score (CT-SS; r=0.691, P<0.001). CEA was correlated with CRP (r=0.441, P<0.001), ferritin (r=0.349, P<0.001) and CT-SS (r=0.374, P<0.001). Receiver operator characteristic (ROC) curves for performance of SAA, CEA, ferritin, CRP and SAA showed the highest AUC value of 0.928, with a specificity of 93.1%, and a sensitivity of 98.5% at a cut-off of 16 mg/l. The multi-ROC curve for SAA and ferritin showed 100% specificity, 100% sensitivity and 100% efficiency, with an AUC of 1.000. Thus, combining SAA and ferritin may have guiding significance for predicting COVID-19 severity. SAA alone showed the highest prognostic significance. Both SAA and CEA were positively correlated with the CT-SS. Early monitoring of these laboratory markers may thus provide significant input for halting disease progression and reducing mortality rates.

Predicting mortality rate in ICU admitted COVID-19 patients implementing visual semi-quantitative CT severity scoring system

Objectives: The aim of this study was to identify the clinical and laboratory features and CT scan (CT intensity score and pleural effusion) associated with COVID-19 pneumonia to evaluate the relationship between CT scan findings and mortality by comparing deceased patients with normal patients. Methods: In this retrospective case-control study, 290 ICU admitted patients with RT-PCR confirmed COVID-19 pneumonia were investigated. Totally, 150 deceased patients (with confirmed COVID-19 related death) were extracted from the COVID-19 registry of the affiliated university hospital belonging to mentioned period of time (in-hospital mortality subgroup, case), and 150 patients who survived the admission course were randomly selected from the same data set (surviving subgroup, control). Available electronic records for each patient were enlisted, including laboratory and clinical information, and their on-admission Computed Tomography (CT) images were reviewed. Mortality-related risk factors were compared between case and control subgroups. Results: The mean age of deceased patients (68.20 ± 16.07) was significantly higher than that of the surviving patients (54.72 ± 19.50) (p&lt;0.001). Diabetes, hypertension, and Chronic Kidney Disease (CKD) were significantly related with higher mortality rates (62.2%, 58.7%, and 80.4% mortality in diabetic, hypertensive, and CKD patients versus 41.7%, 42.1%, and 35.9% in non-diabetics, normotensives, and patients without CKD). Additionally, the mean on-admission air-room SPO2 level in deceased patients (90%) was significantly lower than that of the survivors (93%) (p = 0.001). Lymphocyte count, Neutrophil to Lymphocyte Ratio (NLR), Erythrocyte Sedimentation Rate (ESR), CReactive Protein (CRP), Lactate Dehydrogenase (LDH), Fasting Blood Sugar (BS), Blood Urea Nitrogen (BUN), and Creatinine (Cr), mean CT Severity Score (CT-ss), and O2 supportive therapy requirement were significantly higher in the mortality subgroup (p&lt;0.05). Pleural effusion showed no significant correlation with short-term mortality. CTss of &gt;11, in isolation or in combination with above-mentioned prognosticators, was 64% or 81.4% sensitive, and 60% or of 78.6% specific, to predict mortality. Conclusions: Factors such as advanced age, underlying diseases such as diabetes, hypertension, and CKD, decreased air-room SPO2 , and increased lymphocyte count, higher NLR, ESR, CRP, LDH, BS, BUN, and Cr level, as well as higher CT-ss and O2 supportive therapy, are all significantly correlated with higher mortality in ICU-admitted COVID-19 patients. Keywords: COVID-19; CT scan; CT Severity score; ICU; pneumonia.

Clinical Profile of COVID-19 Patients Admitted in a COVID Designated Hospital.

Pandemic of COVID-19 has engulfed Nepal as well. In this paper, we studied the demographic, clinical, laboratory findings as well as the treatment modalities, prognostic factors and outcome of patients admitted with COVID-19. This was an observational cross-sectional study that included all patients admitted to the General Medicine Department of College of Medical Sciences, Bharatpur, during the first wave of COVID-19 from April 2020 to February 2021 after obtaining the ethical clearance. Data analysis was done using statistical packages for social sciences version 16. A total of 119 patients with mean age of 61.5 years were admitted. They had a mean duration of onset of symptoms of 7.1 days. Commonest symptoms were fever (70.6%), cough (67.2%) and dyspnea (64.7%). Severe COVID-19 at admission with a median CT severity score of 15 was found in 49.7% of them. Total 83.2% patients required ICU care and 10.9% required mechanical ventilation. ARDS and secondary infection occurred in 17.6% each. Median length of hospital stay was 6 days. In total, 56.3% recovered 27.7% left against medical advice and 16.0% expired. Severity of COVID at admission, CT severity score at presentation and D-dimer at admission were found to be significantly associated with mortality (P<0.05).Neither of the age, duration of illness, CRP at admission nor the use of remdesivir or convalescent plasma had significant relation with the mortality (P>0.05). Severity of illness at presentation, CT severity score and D-dimer level at admission are significantly associated with mortality of the patients admitted with COVID-19.

A case report on Severe Acute Respiratory Infection

Introduction: Severe Acute Respiratory Syndrome is a zootoxic viral respiratory illness caused by the severe acute respiratory syndrome corona virus (SARS-CoV or SARS-The syndrome was the cause of the Severe Acute Respiratory Syndrome outbreak in 2002–2004. The virus was traced back to cave-dwelling horseshoe bats via Asian palm civets in late 2017 by Chinese scientists in Xizang Yi Ethnic Township, Yunnan. SARS was a rare illness; there were 8,422 cases at the end of the pandemic in June 2003, with an 11 percent case fatality rate (CFR) (CoV-1), the initial strain of the SARS corona virus species (SARSr-CoV).&#x0D; Clinical Finding: Swelling over Right. Half of face, Breathlessness.&#x0D; Diagnostic Evaluation: Blood test: Hb – 9.2gm%, Total RBC count- 3.22 millions/cu.mm, HCT- 26.6%, Total WBC count – 6600/cu.mm, Monocytes-02%, granulocytes-85%, lymphocytes-10000 /mcl. HRCT Scan OF Thorax: Multiple ill defined patchy ground glass opacities with consolidation and sepal thickening in bilateral lungs filled s/o infective etiology possibility of atypical viral pneumonia. View of covid positive PCR test; imagine grading corad-6 with CT severity score – 03\25 (Mild).&#x0D; Therapeutic Intervention: Inj.Amphotericin-B 500mg IV, Inj.Piptaz 4.4gm IV x TDS, Inj.levoflox 500 mg x OD, Inj.Clindamycin 300mg x BD, Inj.pantaprazol 40 mg x OD, Inj.Emset 4mg x TDS, Tab. limcee 500 mg x BD.&#x0D; Outcome: After Treatment, the patient shows improvement. His swelling over face decrease, and breathlessness decrease.&#x0D; Conclusion: My patient was admitted in SARI-HDU, AVBRH with complaint of swelling over face Right side, and breathlessness. After getting appropriate treatment his condition was improved.

Pneumomediastinum in COVID-19 Patients with Acute Respiratory Distress Syndrome.

Pneumomediastinum, an uncommon entity, has been on the rise with increasing cases of COVID-Acute respiratory distress syndrome. It has been unclear whether this entity represents an indicator of poor clinical outcome or not. The aims of this study were to find out the incidence of pneumomediastinum in COVID-Acute respiratory distress syndrome patients, describe their clinical characteristics and try to explain its plausible mechanisms.. A descriptive, cross-sectional study was carried out in the ICU of our hospital among 280 patients admitted with COVID-Acute respiratory distress syndrome over a period of 6 months. Demographics along with various clinical, laboratory, and radiological parameters were analyzed. Relevant statistical analyses were done to summarize our findings. The incidence of pneumomediastinum in COVID-ARDS patients was 2.8%. All patients were male, none had pulmonary co-morbidities and six of them (60%) were on invasive mechanical ventilation. All intubated patients were on lung protective mechanical ventilation. The median PEEP, peak airway pressure and plateau pressure were 10 (IQR: 4), 29 (IQR: 8) and 28 (IQR: 4) respectively. The mean CT severity score was 22.7 (SD: 1.64). Five patients died after 6.8 days (SD: 4.8) of diagnosis. The average hospital stay was of 34 days. Pneumomediastinum is a possible complication of COVID-Acute respiratory distress syndrome which could signify the disease severity and vice versa. Furthermore, it could be an indicator of relatively poor prognosis and therefore requires larger studies to establish the association.

590 ACE-I and ARBS do not influence the chest CT presentation and 1-year survival of COVID-19 patients: Italian multicentre registry

AimsA possible interference between ACE-i or ARBs with ACE-2 receptor and SARS-CoV-2 pathway has been raised. Despite data have shown no clinical impact of therapy with ACE-I or ARBs on COVID-19, these drugs are often discontinued upon hospitalization or diagnosis. To evaluate the effects of cardiovascular risk factors (CVRF) and prior outpatient therapy with RAAS inhibitors on the chest CT severity score performed within 24 h of diagnosis of SARS-CoV-2 infection (before stopping medications or starting specific therapy for COVID-19) and on 1-year survival.Methods and resultsThis is a multicentre, prospective, observational study. All admitted patients diagnosed with SARS-CoV-2 infection who performed chest CT within 24 h of arrival were consecutively enrolled from 1 March to 1 June 2020. A severity score was attributed to Chest CT by two radiologists in blind to the patient’s clinical information and a cut-off value of 19.5 was considered to define severe radiological pneumonia. A 1-year telephone follow-up was performed in order to evaluate the determinants of 1-year survival. 590 patients with a mean age of 63 ± 14 years were included. Seventy-three (12.4%) patients were treated with ACE-I, 85 (14.4%) with ARBs and 62 (10.5%) with CCB. Cox regression analysis showed that male gender (OR: 1.4; 95% CI: from 1.02 to 2.07; P = 0.035), diabetes (OR: 1.6; 95% CI: from 1.03 to 2.7; P = 0.037), age (OR: 1.02; 95% CI: from 1.008 to 1.033; P = 0.001), and obesity (OR: 3.04; 95% CI: from 1.3 to 6.7; P < 0.001) were independently associated with a severe CT score. Of note, while prior outpatient therapy with ACE-I and ARBs was not independently associated with severe CT score, therapy with CCB was independently associated with a severe CT score (OR: 1.9, 95% CI: from 1.05 to 3.4, P = 0.033). Severe chest CT severity score (OR: 1.05; 95% CI: from 1.02 to 1.08; P < 0.001), P/F ratio (OR: 0.998; 95% CI: from 0.994 to 0.998; P < 0.001), and older age (OR: 1.06; 95% CI: from 1.03 to 1.1; P < 0.001) were independently associated with mortality at 1-year follow-up. Neither ACE-I, ARBs, and CCB were associated with mortality at 1 year follow-up.ConclusionsACE-I and ARBs do not influence the chest CT presentation of COVID-19 patients at the time of diagnosis. Furthermore, ACE-I and ARBs do not influence 1-year survival of COVID-19 survivors.

Computed tomography severity scoring of COVID 19 infected young patients: Is the second wave affecting the young lungs more than the first wave in India?

We evaluated the High Resolution Computed Tomography (HRCT) findings in young patients (&lt; 40 years) infected with the COVID 19 virus and tried to find out any difference in the severity of lung involvement between the first and second wave of the pandemic and whether the notion of young population being more severely affected by the second wave holds true.Two-hundred (200) young patients (&lt;40 years) with RT PCR documented COVID infections undergoing HRCT chest at our institute were included. Group A included young patients infected in the first wave (up to 28 February 2021) while Group B included patients beyond this date. Demographic and clinical data was obtained from the medical records department. HRCT scans were retrieved from the archive and were assessed by two radiologists or CT severity scoring. The mean severity scores were calculated and any statistical difference between Group A and B was sought. CT scans of four fully vaccinated patients were also evaluated.The age and gender distribution among the two groups was comparable. A greater number of patients in group B required hospital admission compared to group A (74% VS 53%). In group A, the mean severity score was 10.1±2.1 with 34 patients (34%) in mild category, 46 patients (46%) in moderate group and 20 patients (20%) in the severe group. In group B, the mean CT severity score was 12.6±2.3 with 20 patients (20%) in mild category, 42 patients (42%) in moderate group and 38 patients (38%) in the severe group.Lung involvement in young patients in the second wave is more severe requiring more hospital admissions. Vaccinated population may well have a milder form of the disease.

Correlation Between CT Severity Scoring and Diabetes Mellitus in Patients With COVID-19 Infection.

Background and objectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), was first identified in Wuhan, China in December 2019. Since then, It has spread across multiple countries and was declared a pandemic by WHO in March 2020. Patients with underlying diabetes mellitus (DM) are deemed at-risk for developing severe COVID-19 infection. In light of this, we aimed to evaluate the correlation between DM and chest CT severity scores (CTSS) in COVID-19 patients.MethodsThis was a hospital-based descriptive, analytical retrospective study conducted at our tertiary care hospital. A quantitative severity score was calculated among 220 patients with COVID-19 infection based on the degree of lung lobe involvement on CT chest scans. Based on CTSS, the patients were classified into groups of mild, moderate, and severe lung involvement. The association between DM and CTSS was evaluated using the chi-square test.ResultsThe severity of lung involvement was higher among COVID-19 patients with a co-diagnosis of DM (29.3%) compared to those without DM (11.7%). This association of severe lung involvement with DM was statistically significant (p=0.002).ConclusionBased on our findings, diabetic patients are at an increased risk of developing the severe form of COVID-19 with a higher CT lung involvement score compared to non-diabetic patients.

Chest CT Severity Score, CURB-65 Score and Their Relationship with in-Hospital-Mortality in COVID-19 Patients

Objective: With every new strain of the SARS-CoV-2 spreading on a fast pace across the borders, an easy-to-calculate and reliable scoring system seems invaluable to identify high-risk patients. This study aims to investigate the relationship between CT Severity Score (CTSS) and CURB-65 score with mortality in COVID-19 patients. Methods: This study was conducted on RT-PCR confirmed COVID-19 patients admitted to a tertiary teaching center during fifth national wave of disease in one of the early disease epicenters in the country. All enrolled patients underwent chest CT scan within first day of admission. CTSS and CURB-65 scores were calculated and assigned to patients, while radiologist was blinded to clinical and laboratory findings, and they were evaluated for their correlation with in-hospital mortality, additively and separately. Results: Total number of 216 patients (140 males) with a mean age of 56.02 ± 17.34 years (ranging from 4 to 95) were enrolled. We found no significant relationship between CURB-65 score and CTSS (correlation coefficient: 0.065; P: 0.338). CURB-65 scores above 1 was predictive of in-hospital mortality with sensitivity of 56.4% and specificity of 81.9% (P: 0), those for CTSS above 11 were 79.5% and 4 51.5%, respectively (P: 0.001). CURB-65 score &gt;1 and CTSS &gt;11 predicted in-hospital mortality with sensitivity and specificity of 61.5% and 79.7% (P: 0.000). CURB-65 score and CTSS had a higher sensitivity and specificity to predict mortality comparing to each of those separately, but these enhanced statistics were not significant. Conclusion: CURB-65 score is meaningfully stronger than CTSS to prognosticate in-hospital mortality in patients with COVID-19, and it is not significantly correlated with CTSS.

Predicting ICU Length of Stay in COVID-19 Patients Using a Multivariable Model Incorporating Clinical, Laboratory and Imaging Features

Objective: To predict ICU Length of Stay (LOS) using a multivariable model incorporating clinical, and laboratory and imaging features in hospitalized COVID-19 patients, thereby stratifying patients and allocating resources accordingly. Methods: In this retrospective cohort study, 139 hospitalized patients (aged between 3 to 99) with rRT-PCR confirmed COVID-19 pneumonia requiring intensive care, who had been discharged or deceased, were enrolled. Demographic, clinical, and laboratory findings of eligible patients were all extracted from electronic medical records and, if needed, through phone calls. Semi-quantitative CT Severity Score (CTSS) was calculated and assigned to each encoded patient independently and blindly. We used cox regression model to investigate the prognostic role of semi-quantitative CTSS, clinical and laboratory features to anticipate ICU-LOS. Results: 139 patients with rRT-PCR confirmed COVID-19 pneumonia (including 60 females and 79 males) with a mean age of 58.52 ± 20.58 (ranging from 3 to 99) were included. CTSS was not predictive of ICU-LOS. Additionally, CTSS of more than 11 was predictor of mortality (sensitivity, 60.3%; specificity, 58%; AUC, 0.605; 95% confidence interval, 0.508 - 0.702; P-value, 0.034), and CTSS of above 10 was predictor of oxygen therapy dependency (sensitivity, 70.2%; specificity, 68%; AUC, 699/0; 95% confidence interval, 0.580 - 0.818; P-value, 0.002). CTSS was not significantly associated with respiratory rate and on-admission dyspnea, while it was inversely related to air-room SpO2 on the first day of admission (P &lt; 0.0001, r = -0.341). Conclusion: CTSS is capable of anticipating mortality rate and the chance of undergoing supportive oxygen therapy during ICU hospitalization, while it does not predict ICU-LOS, rate of mechanical ventilation, or corticosteroid therapy.

Predicting Mortality Rate in ICU-Admitted COVID-19 Patients Implementing Visual Semi-Quantitative CT Severity Scoring System

Objectives: The aim of this study was to identify the clinical and laboratory features and CT scan (CT intensity score and pleural effusion) associated with COVID-19 pneumonia to evaluate the relationship between CT scan findings and mortality by comparing deceased patients with normal patients. Methods: In this retrospective case-control study, 290 ICU admitted patients with RT-PCR confirmed COVID-19 pneumonia were investigated. Totally, 150 deceased patients (with confirmed COVID-19 related death) were extracted from the COVID-19 registry of the affiliated university hospital belonging to mentioned period of time (in-hospital mortality subgroup, case), and 150 patients who survived the admission course were randomly selected from the same data set (surviving subgroup, control). Available electronic records for each patient were enlisted, including laboratory and clinical information, and their on-admission Computed Tomography (CT) images were reviewed. Mortalityrelated risk factors were compared between case and control subgroups. Results: The mean age of deceased patients (68.20 ± 16.07) was significantly higher than that of the surviving patients (54.72 ± 19.50) (p &lt;0.001). Diabetes, hypertension, and Chronic Kidney Disease (CKD) were significantly related with higher mortality rates (62.2%, 58.7%, and 80.4% mortality in diabetic, hypertensive, and CKD patients versus 41.7%, 42.1%, and 35.9% in non-diabetics, normotensives, and patients without CKD). Additionally, the mean on-admission air-room SPO2 level in deceased patients (90%) was significantly lower than that of the survivors (93%) (p = 0.001). Lymphocyte count, Neutrophil to Lymphocyte Ratio (NLR), Erythrocyte Sedimentation Rate (ESR), C-Reactive Protein (CRP), Lactate Dehydrogenase (LDH), fasting Blood Sugar (BS), Blood Urea Nitrogen (BUN), and Creatinine (Cr), mean CT severity score (CT-ss), and O2 supportive therapy requirement were significantly higher in the mortality subgroup (p &lt;0.05). Pleural effusion showed no significant correlation with short-term mortality. CT-ss of &gt;11, in isolation or in combination with abovementioned prognosticators, was 64% or 81.4% sensitive, and 60% or of 78.6% specific, to predict mortality. Conclusions: Factors such as advanced age, underlying diseases such as diabetes, hypertension, and CKD, decreased air-room SPO2, and increased lymphocyte count, higher NLR, ESR, CRP, LDH, BS, BUN, and Cr level, as well as higher CT-ss and O2 supportive therapy, are all significantly correlated with higher mortality in ICU-admitted COVID-19 patients.

The diagnostic performance of deep-learning-based CT severity score to identify COVID-19 pneumonia.

Objective:To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagnosis of coronavirus disease 2019 (COVID-19), as compared to the reference standard reverse-transcription polymerase chain reaction (RT-PCR) test.Methods:In this retrospective analysis, data of COVID-19 suspected patients who underwent RT-PCR and chest CT examination for the diagnosis of COVID-19 were assessed. By quantifying the affected area of the lung parenchyma, severity score was evaluated for each lobe of the lung with the DL-based algorithm. The diagnosis was based on the total lung severity score ranging from 0 to 25. The data were randomly split into a 40% training set and a 60% test set. Optimal cut-off value was determined using Youden-index method on the training cohort.Results:A total of 1259 patients were enrolled in this study. The prevalence of RT-PCR positivity in the overall investigated period was 51.5%. As compared to RT-PCR, sensitivity, specificity, positive predictive value, negative predictive value and accuracy on the test cohort were 39.0%, 80.2%, 68.0%, 55.0% and 58.9%, respectively. Regarding the whole data set, when adding those with positive RT-PCR test at any time during hospital stay or “COVID-19 without virus detection”, as final diagnosis to the true positive cases, specificity increased from 80.3% to 88.1% and the positive predictive value increased from 68.4% to 81.7%.Conclusion:DL-based CT severity score was found to have a good specificity and positive predictive value, as compared to RT-PCR. This standardized scoring system can aid rapid diagnosis and clinical decision making.Advances in knowledge:DL-based CT severity score can detect COVID-19-related lung alterations even at early stages, when RT-PCR is not yet positive.

Parenchymal involvement on CT pulmonary angiography in SARS-CoV-2 Alpha variant infection and correlation of COVID-19 CT severity score with clinical disease severity and short-term prognosis in a UK cohort

AIMTo determine if there is a difference in radiological, biochemical, or clinical severity between patients infected with Alpha-variant SARS-CoV-2 compared with those infected with pre-existing strains, and to determine if the computed tomography (CT) severity score (CTSS) for COVID-19 pneumonitis correlates with clinical severity and can prognosticate outcomes.MATERIALS AND METHODSBlinded CTSS scoring was applied to 137 hospital patients who had undergone both CT pulmonary angiography (CTPA) and whole-genome sequencing of SARS-CoV-2 within 14 days of CTPA between 1/12/20–5/1/21.RESULTSThere was no evidence of a difference in imaging severity on CTPA, viral load, clinical parameters of severity, or outcomes between Alpha and preceding variants. CTSS on CTPA strongly correlates with clinical and biochemical severity at the time of CTPA, and with patient outcomes. Classifying CTSS into a binary value of “high” and “low”, with a cut-off score of 14, patients with a high score have a significantly increased risk of deterioration, as defined by subsequent admission to critical care or death (multivariate hazard ratio [HR] 2.76, p<0.001), and hospital length of stay (17.4 versus 7.9 days, p<0.0001).CONCLUSIONThere was no evidence of a difference in radiological severity of Alpha variant infection compared with pre-existing strains. High CTSS applied to CTPA is associated with increased risk of COVID-19 severity and poorer clinical outcomes and may be of use particularly in settings where CT is not performed for diagnosis of COVID-19 but rather is used following clinical deterioration.