Spectrum of CT appearance and CT severity index of COVID-19 pulmonary infection in correlation with age, sex, and PCR test: an Iraqi experience

Evaluation of the value of chest CT severity score in assessment of COVID-19 severity and short-term prognosis

Background

Evaluations have shown that the severity of pulmonary involvement is very important in the mortality rate of patients with coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the value of chest CT severity score in assessment of COVID-19 severity and short-term prognosis.

Materials and Methods

This study was a cross-sectional study with a sample size of 197 patients, including all patients admitted to Rasoul Akram Hospital, with positive polymerase chain reaction, to investigate the relationship between computed tomography (CT) severity score and mortality. The demographic data and CT scan findings (including the pattern, side, and distribution of involvement), co-morbidities, and lab data were collected. Finally, gathered data were analyzed by SPSS-26.

Results

119 (60.4%) patients were male, and 78 (39.6%) were female. The mean age was 58.58 ± 17.3 years. Totally, 61 patients died; of those, 41 (67.2%) were admitted to the intensive care unit (ICU), so there was a significant relation between death and ICU admission (P value = 0.000). Diabetes was the most common co-morbidity, followed by hypertension and IHD. There was no significant relation between co-morbidities and death (P value = 0.13). The most common patterns of CTs were interlobular septal thickening and ground glass opacities, and a higher CT severity score was in the second week from the onset of symptoms, which was associated with more mortality (P value < 0.05).

Conclusion

Our study showed that a patient with a higher CT severity score of the second week had a higher risk of mortality. Also, association of the CT severity score, laboratory data, and symptoms could be applicable in predicting the patient's condition.

A Systematic Review of the Relationship between Chest CT Severity Score and Laboratory Findings and Clinical Parameters in COVID-19 Pneumonia

The COVID-19 virus has infected millions of people and became a global pandemic in 2020. The efficacy of laboratory and clinical parameters in the diagnosis and monitoring of COVID-19 has been established. The CT scan has been identified as a crucial tool in the prognostication of COVID-19 pneumonia. Moreover, it has been proposed that the CT severity score can be utilized for the diagnosis and prognostication of COVID-19 disease severity and exhibits a correlation with laboratory findings such as inflammatory markers, blood glucose levels, and clinical parameters such as endotracheal intubation, oxygen saturation, mortality, and hospital admissions. Nevertheless, the correlation between the CT severity score and clinical or laboratory parameters has not been firmly established. The objective of this study is to provide a comprehensive review of the aforementioned association. This review used a systematic approach to collate and assess the existing literature that investigates the correlation between CT severity score and laboratory and clinical parameters. The search was conducted using Embase Ovid, MEDLINE Ovid, and PubMed databases, covering the period from inception to 20 May 2023. This review identified 20 studies involving more than 8000 participants of varying designs. The findings showed that the CT severity score is positively associated with laboratory and clinical parameters in COVID-19 patients. The findings indicate that the CT severity score exhibits a satisfactory level of prognostic accuracy in predicting mortality among patients with COVID-19.

Automated diagnosis of COVID-19 using radiological modalities and Artificial Intelligence functionalities: A retrospective study based on chest HRCT database

Background and Objective

The spread of coronavirus has been challenging for the healthcare system's proper management and diagnosis during the rapid spread and control of the infection. Real-time reverse transcription-polymerase chain reaction (RT-PCR), though considered the standard testing measure, has low sensitivity and is time-consuming, which restricts the fast screening of individuals. Therefore, computer tomography (CT) is used to complement the traditional approaches and provide fast and effective screening over other diagnostic methods. This work aims to appraise the importance of chest CT findings of COVID-19 and post-COVID in the diagnosis and prognosis of infected patients and to explore the ways and means to integrate CT findings for the development of advanced Artificial Intelligence (AI) tool-based predictive diagnostic techniques.

Methods

The retrospective study includes a 188 patient database with COVID-19 infection confirmed by RT-PCR testing, including post-COVID patients. Patients underwent chest high-resolution computer tomography (HRCT), where the images were evaluated for common COVID-19 findings and involvement of the lung and its lobes based on the coverage region. The radiological modalities analyzed in this study may help the researchers in generating a predictive model based on AI tools for further classification with a high degree of reliability.

Results

Mild to moderate ground glass opacities (GGO) with or without consolidation, crazy paving patterns, and halo signs were common COVID-19 related findings. A CT score is assigned to every patient based on the severity of lung lobe involvement.

Conclusion

Typical multifocal, bilateral, and peripheral distributions of GGO are the main characteristics related to COVID-19 pneumonia. Chest HRCT can be considered a standard method for timely and efficient assessment of disease progression and management severity. With its fusion with AI tools, chest HRCT can be used as a one-stop platform for radiological investigation and automated diagnosis system.

The value of chest X-ray and CT severity scoring systems in the diagnosis of COVID-19: A review

Coronavirus disease 2019 (COVID-19) is caused by a coronavirus family member known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The main laboratory test to confirm the quick diagnosis of COVID-19 infection is reverse transcription-polymerase chain reaction (RT-PCR) based on nasal or throat swab sampling. A small percentage of false-negative RT-PCR results have been reported. The RT-PCR test has a sensitivity of 50-72%, which could be attributed to a low viral load in test specimens or laboratory errors. In contrast, chest CT has shown 56-98% of sensitivity in diagnosing COVID-19 at initial presentation and has been suggested to be useful in correcting false negatives from RT-PCR. Chest X-rays and CT scans have been proposed to predict COVID-19 disease severity by displaying the score of lung involvement and thus providing information about the diagnosis and prognosis of COVID-19 infection. As a result, the current study provides a comprehensive overview of the utility of the severity score index using X-rays and CT scans in diagnosing patients with COVID-19 when compared to RT-PCR.

Development and validation of prognostic scoring system for COVID-19 severity in South India

BACKGROUND

Development of a prediction model using baseline characteristics of COVID-19 patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring system for predicting the COVID-19 severity in South India.

METHODS

We undertook this retrospective cohort study among COVID-19 patients reporting to Hindu Mission Hospital, India. Multivariable logistic regression using the LASSO procedure was used to select variables for the model building, and the nomogram scoring system was developed with the final selected model. Model discrimination, calibration, and decision curve analysis (DCA) was performed.

RESULTS

In total, 35.1% of the patients in the training set developed severe COVID-19 during their follow-up period. In the basic model, nine variables (age group, sex, education, chronic kidney disease, tobacco, cough, dyspnea, olfactory-gustatory dysfunction [OGD], and gastrointestinal symptoms) were selected and a nomogram was built using these variables. In the advanced model, in addition to these variables (except OGD), C-reactive protein, lactate dehydrogenase, ferritin, D-dimer, and CT severity score were selected. The discriminatory power (c-index) for basic model was 0.78 (95%CI: 0.74-0.82) and advanced model was 0.83 (95%CI: 0.79-0.87). DCA showed that both the models are beneficial at a threshold probability around 10-95% than treat-none or treat-all strategies.

CONCLUSION

The present study has developed two separate prognostic-scoring systems to predict the COVID-19 severity. This scoring system could help the clinicians and policymakers to devise targeted interventions and in turn reduce the COVID-19 mortality in India.

COVID-19 Infection in Chronic Kidney Disease Patients in Bulgaria: Risk Factors for Death and Acute Kidney Injury

Regarding COVID-19 infection, Bulgaria has one of the lowest rates of vaccination in Europe, and its COVID-19-related mortality rate has been one of the highest in the European Union. Chronic kidney disease (CKD)-COVID-19 patients are at higher risk of developing acute kidney injury (AKI) and death after hospital admission. This single-center prospective cohort study from Bulgaria included 120 in-patient COVID-19 subjects of whom 70 had CKD and 50 normal renal function. Diabetes mellitus, hypertension, obesity, and cardiovascular disease were statistically more prevalent in the CKD group as compared to the non-CKD group. At admission, D-dimer, creatinine, and urea levels were significantly higher in the CKD group, whereas estimated glomerular-filtration rate was significantly lower as compared to the non-CKD patients. During hospitalization, 23 patients (19.1%) died, of which 19 were in the CKD group (p-value = 0.0096); in addition, 38 developed AKI (31.6%), of which 31 were in the CKD group (p-value = 0.0006). Using binary logistic regression, being male, having experienced AKI, and not having been treated with remdesivir were independent risk factors for COVID-19-induced mortality. Regarding risk of AKI, having had COVID-19-related symptoms for more than 6 days before admission, having CKD at baseline, and having not received remdesivir therapy were independent predictive factors for developing AKI after admission.

Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system

Background

It is important to determine the correlation of the CO-RADS classification and computed tomography (CT) patterns of the lung with laboratory data. To investigate the relationship of CO-RADS categories and CT patterns with laboratory data in patients with a positive RT-PCR test. We also developed a structured total CT scoring system and investigated its correlation with the total CT scoring system.

Method

The CT examinations of the patients were evaluated in terms of the CO-RADS classification, pattern groups and total CT score. Structured total CT score values were obtained by including the total CT score values and pattern values in a regression analysis. The CT data were compared according to the laboratory data.

Results

A total of 198 patients were evaluated. There were significant differences between the CO-RADS groups in terms of age, ICU transfer, oxygen saturation, creatinine, LDH, D-dimer, high-sensitivity cardiac troponin-T (hs-TnT), CRP, structured total CT score values, and total CT score values. A significant difference was also observed between the CT pattern groups and oxygen saturation, creatinine and CRP values. When the structured total CT score values and total CT score values were compared they were observed to be correlated.

Conclusions

Creatinine can be considered as an important marker for the CO-RADS and pattern classifications in lung involvement. LDH can be considered as an important marker of parenchymal involvement, especially bilateral and diffuse involvement. The structured total CT scoring system is a new system that can be used as an alternative.

Relationship of Computed Tomography Severity Score With Patient Characteristics and Survival in Hypoxemic COVID-19 Patients

Background

Computed tomography (CT) scans and CT severity scores (CTSS) are widely used to assess the severity and prognosis in coronavirus disease 2019 (COVID-19). CTSS has performed well as a predictor in differentiating severe from non-severe cases. However, it is not known if CTSS performs similarly in hospitalized severe cases with hypoxia at admission.

Methods

We conducted a retrospective comparative study at a COVID-care center from Western India between 25th April and 31st May 2021, enrolling all consecutive severe COVID-19 patients with hypoxemia (peripheral oxygen saturation < 94%). Neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), interleukin-6 (IL-6), lactate dehydrogenase (LDH), D-dimer, ferritin, and CT thorax were done within 24h of admission before being initiated on any anti-COVID-19 therapy. CTSS was calculated by visual assessment and categorized into three severity categories and was correlated with laboratory markers and overall survival (OS). Statistical analysis was done using John's Macintosh Project (JMP) 15.0.0 ver. 3.0.0 (Cary, North Carolina).

Results

The median age of the study population (n-298) was 59 years (24-95) with a male preponderance (61.41%, n=183). The 15 and 30-day survivals were 67.64% and 59.90%, respectively. CTSS did not correlate with age, gender, time from vaccination, symptoms, or comorbidities but had a significant though weak correlation with LDH (p=0.009), D-dimer (p=0.006), and NLR (p=0.019). Comparing demographic and laboratory aspects using CT severity categories, only NLR (p=0.0146) and D-dimer (p=0.0006) had significant differences. The 15d-OS of mild, moderate, and severe CT categories were 88.62%, 70.39%, and 52.62%, respectively, while 30d-OS of three categories were 59.08%, 63.96%, and 49.12%, respectively.

Conclusion

Among hospitalized severe COVID-19 patients with hypoxemia at admission, CT severity categories correlate well with outcomes but not inflammatory markers at admission.

Clinicodemographic profile, intensive care unit utilization and mortality rate among COVID-19 patients admitted during the second wave in Bangladesh

INTRODUCTION

The second wave of COVID-19 arrived in Bangladesh in March 2021. This pilot research from a tertiary care COVID-dedicated hospital observed the clinicodemographic profile, intensive care unit (ICU) utilization, and mortality rate among COVID-19 patients admitted during the second wave.

METHODS

Reverse transcription-polymerase chain reaction or chest high-resolution computed tomography confirmed 972 COVID-19 cases included in this cross-sectional study from 24 March to 23 June 2021, recruited using convenience sampling. Data regarding clinicodemographic profile, ICU utilization and mortality rate were analyzed.

RESULTS

The mean study cohort age was 54.47±12.73 years, with most patients (48.3%) aged 41-60; 64.1% were men. Fever (77.9%) and cough (75.9%) were the most common symptoms, and hypertension (43.6%) and diabetes (42.15%) the most common comorbidities. Nearly half of patients had total lung involvement of 26%-50%, and 23.8% required ICU. Overall mortality was 16.5%, whereas the mortality rate among ICU admitted patients was 56.1%. The most important predictors of mortality were older age, chronic renal illness, the proportion of lung involvement and ICU requirement.

CONCLUSIONS

We found higher mortality and ICU utilization rate and greater total lung involvement during the second wave. The mortality rate among the elderly and ICU patients was also higher than earlier.

Severity of COVID-19 Infection Using Chest Computed Tomography Severity Score Index Among Vaccinated and Unvaccinated COVID-19-Positive Healthcare Workers: An Analytical Cross-Sectional Study

Introduction: Coronavirus disease 2019 (COVID-19) vaccines protect against severe illness. However, data on post-vaccination COVID-19 breakthrough infections are limited.

Methods: An analytical cross-sectional study was conducted from May 2021 to July 2021 among 2043 COVID-19-positive healthcare workers who were divided into a vaccinated group (n=1010) and an unvaccinated group (n=1033). A pre-tested questionnaire was circulated among the healthcare workers using Google Forms. Chest computed tomography (CT) severity score was the primary outcome variable analyzed using coGuide.

Results: The average age of the study population was less than 45 years in both groups (43.05 ± 13.02 years). Most respondents (62%) were males. Hypertension (39%) and diabetes (33%) were the most common underlying diseases. Significant differences in age and cardiac disease were observed between the two groups (p = 0.07 and p <0.001, respectively). However, the difference was insignificant (p >0.05) for gender, hypertension, and diabetes. Most unvaccinated respondents had an increased CT severity score, and the difference between the studies groups was significant (p <0.001). Of the 1,010 vaccinated individuals, 382 (37.82%) received the only first vaccination dose, and 628 (62.18%) received both doses. The CT severity score decreased after receiving both vaccination doses, and the difference between CT severity score and vaccination status was significant (p <0.001).

Conclusion: COVID-19 was mild in the vaccinated group. Chest CT severity score index can be considered an efficient tool in predicting prognosis and monitoring disease in patients with COVID-19 in India.

Can initial chest CT scan predict status and clinical outcomes of COVID-19 infection? A retrospective cohort study

Background

We aimed to investigate the association of initial chest CT scan findings with status and adverse outcomes of COVID-19 (including ICU admission, mortality, and disease severity).

This retrospective cohort study was performed in three hospitals in Babol, northern Iran, between February and March 2020. Cases were confirmed by real-time polymerase chain reaction (RT-PCR). Clinical and paraclinical data of the patients were collected from their medical records. CT severity score (CSS) was calculated by a senior radiologist. Disease severity was determined based on the World Health Organization criteria.

Results

In total, 742 patients were included, of whom 451 (60.8%) were males and 291 (39.2%) were females. The mean age was 56.59 ± 14.88 years old. Also, 523 (70.5%) were RT-PCR-positive. Ground glass opacity was directly associated with RT-PCR positivity (odds ratio [OR] = 2.07). Also, RT-PCR-positive cases had significantly a higher CSS than RT-PCR-negative cases (p = 0.037). In patients confirmed with COVID-19, peribronchovascular distribution of lesions, number of zones involved, and CSS were associated with increased risk of ICU admission (OR = 2.93, OR = 2.10, and OR = 1.14, respectively), mortality (OR = 2.30, OR = 1.35, and OR=1.08, respectively), severe disease (OR = 2.06, OR = 1.68, and OR = 1.10, respectively), and critical disease (OR = 4.62, OR = 3.21, and OR = 1.23, respectively). Also, patients who had consolidation were at a higher risk of severe disease compared with those who did not (OR = 4.94).

Conclusion

Initial chest CT scan can predict COVID-19 positivity, ICU admission, mortality, and disease severity, specifically through CSS.

COVID-19 Infection Clinical Profile, Management, Outcome, and Antibody Response in Kidney Transplant Recipients: A Single Centre Experience

INTRODUCTION

Experience of COVID-19 in kidney transplant recipients (KTRs) with clinical presentation, management, factors influencing mortality, and antibody response is limited. Material and Methods. A retrospective data of COVID-19 in KTRs was collected and analyzed. The mortality rate, risk factors, and antibody response were primary objectives, while the clinical presentation, laboratory indicators, and pharmacological management were secondary objectives.

RESULTS

The 67 KTRs with polymerase chain reaction (PCR) confirmed COVID-19 infection reported between 1 May 2020 and 31 December 2020; 61.2% of patients were hospitalized; and 20.9% needed ventilation. The overall mortality was 26.9%, while blood group A had 50% mortality. The treatment options and used were steroids (100%), convalescent plasma (32.8%), ivermectin (58.2%), doxycycline (55.2%), remdesivir (34.3%), tocilizumab (10.4%), antibiotics (61.2%), anti-fungals (26.9%), low molecular weight heparin (45.3%), and oral anti-coagulants (26.9%). Anti-nucleosides (mycophenolate or azathioprine) were discontinued in 76.1% and calcineurin inhibitors (CNI) in 26.9%. Significant mortality (p < 0.001) was observed in patients presenting with SpO2 <94 needing ICU care, ventilation, dialysis/acute kidney injury (AKI), and empirical therapies like convalescent plasma and remdesivir. The age of survivors versus nonsurvivors was not significantly different (p=0.02). The positive blood culture, low serum albumin, high TLC, high blood urea, interleukin-6, and CT severity score ≥15 were statistically significant in nonsurvivors. Overall mortality, mortality of hospitalized patients, and mortality of ventilated patients was 27%, 44%, and 100%, respectively. The median value of SARS-CoV-2 (COVID-19) IgG antibody was 68.60 (IQR, 28.5-94.25) AU/ml in more than 90% of survivors.

CONCLUSION

KTRs with COVID-19, needing ICU care, dialysis and ventilation support had poor outcomes. Recovered patients mounted adequate antibody response.

Demographic profile and outcome of patients admitted to a COVID dedicated hospital in Bangladesh during the second wave

In December 2019, with pneumonia-like clinical manifestations, a new severe acute respiratory syndrome coronavirus 2 emerged and quickly escalated into a pandemic. Since the first case detected in early March of last year, 8668 have died with an infection mortality rate of 1.52%, as of March 20, 2021. Bangladesh has been struck by the 2nd wave from mid-march 2021. As data on the second wave are sparse, the present study observed the demographic profile, symptoms, and outcomes of Coronavirus Disease 2019 (COVID-19) patients during this wave.The study was conducted at Sheikh Russel National Gastroliver Institute on 486 admitted cases during the 2nd wave of COVID-19 in Bangladesh (March 24-April 24, 2021) using a cross-sectional study design and a convenient sampling technique.Out of 486 cases, 306 (62.9%) were male, and 180 were female, with a mean age of 53.47 ± 13.86. The majority of patients (32.5%) were between the ages of 51 and 60. While fever and cough being the predominant symptoms (>70% cases), the most common co-morbidities were hypertension (41.4) and diabetes mellitus (39.4). Intensive care unit utilization rate was 25%, and a half of the patients had 51% to 70% tomographic lung involvement with an overall mortality rate of 19.3%. Older age, chronic renal disease, percentage of lung involvement, and intensive care unit necessity were important mortality determinants.The present study gives an insight into the demographic profiles and outcomes of admitted patients with COVID-19 during the second wave at a covid dedicated hospital in Bangladesh.