Computed tomography chest in COVID-19: When & why?

Relationship between imaging-derived parameters and circulating microRNAs to study the degree of lung involvement in hospitalized geriatric patients with COVID-19 pneumonia

AIM

Chest computed tomography (CT) scan is useful to evaluate the type and extent of lung lesions in coronavirus disease 2019 (COVID-19) pneumonia. This study explored the association between radiological parameters and various circulating serum-derived markers, including microRNAs, in older patients with COVID-19 pneumonia.

METHODS

A retrospective analysis was designed to study geriatric patients (≥75 years) with COVID-19 pneumonia, who underwent chest CT scan on admission, and for whom clinical data and serum samples were obtained. To quantify the extent of lung involvement, CT-score, the percentage of healthy lung (HL%), the percentage of ground glass opacity (GGO%), and the percentage of lung consolidation were assessed using computer-aided tools. The association of these parameters with two circulating microRNAs, miR-483-5p and miR-320b, previously identified as biomarkers of mortality risk in COVID-19 geriatric patients, was tested.

RESULTS

A total of 73 patients with COVID-19 pneumonia were evaluable (median age 85 years; interquartile range 82-90 years). Among chest CT-derived parameters, the percentage of lung consolidation (HR 1.08, 95% CI 1.02-1.14), CT-score (HR 1.14, 95% CI 1.03-1.25), and HL% (HR 0.97, 95% CI 0.95-0.99) emerged as significant predictors of mortality, whereas non-significant trends toward increased mortality were observed in patients with higher GGO%. We also found a significant positive association between serum miR-483-5p and GGO% (correlation coefficient 0.28; P = 0.018) and a negative association with HL% (correlation coefficient -0.27; P = 0.023).

CONCLUSIONS

Overall, the extent of lung consolidation can be confirmed as a prognostic parameter of COVID-19 pneumonia in older patients. Among various serum-derived markers, miR-483-5p can help in exploring the degree of lung involvement, due to its association with higher GGO% and lower HL%. Geriatr Gerontol Int 2024; ••: ••-••.

Post-COVID-19 Syndrome Mechanisms, Prevention and Management

As the population of patients recovering from COVID-19 grows, post COVID-19 challenges are recognizing by ongoing evidences at once. Long COVID is defined as a syndrome with a range of persistent symptoms that remain long after (beyond 12 weeks) the acute SARS-CoV-2 infection. Studies have shown that long COVID can cause multi-organ damages with a wide spectrum of manifestations. Many systems, but not limited to, including respiratory, cardiovascular, nervous, gastrointestinal, and musculoskeletal systems, are involved in long COVID. Fatigue and dyspnea are the most common symptoms of long COVID. Long COVID-19 may be driven by tissue damage caused by virus-specific pathophysiologic changes or secondary to pathological long-lasting inflammatory response because of viral persistence, immune dysregulation, and autoimmune reactions. Some risk factors like sex and age, more than five early symptoms, and specific biomarkers have been revealed as a probable long COVID predicator discussed in this review. It seems that vaccination is the only way for prevention of long COVID and it can also help patients who had already long COVID. Managing long COVID survivors recommended being in a multidisciplinary approach, and a framework for identifying those at high risk for post-acute COVID-19 must be proposed. Possible therapeutic options and useful investigation tools for follow-up are suggested in this review. In sum, as evidence and researches are regularly updated, we provide the current understanding of the epidemiology, clinical manifestation, suspected pathophysiology, associated risk factors, and treatment options of long COVID in this review.

Chest CT in COVID-19 patients: A clinical need

INTRODUCTION

The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has resulted in a global healthcare crisis. The provision of computed tomography (CT) imaging services by radiology departments for COVID-19 patients poses multiple challenges. Consequently, it is important to explore the clinical need and indications for thoracic CT and whether they subsequently alter patient management.

METHODS

We report our experience in this single-centre retrospective cohort study of all confirmed COVID-19 cases admitted during the peak of the 'Delta' variant wave in Australia, and who underwent a chest CT. Clinical indication and patient management plan pre- and post-CT were ascertained.

RESULTS

A total of 92 out of 1403 patients who were admitted with COVID-19 underwent a thoracic CT (73 CT pulmonary angiogram (CTPA), 14 CT Chest and five high-resolution CT (HRCT) studies). 72.8% of studies were to evaluate for pulmonary emboli, 16.2% for assessment of COVID-19 pneumonia complications, 5.4% for tuberculosis and 6.5% for other indications. 21 (23%) of these studies resulted in a change in management with two patients having a major change in management (thrombolysis, CT-guided aspiration). Management was altered due to diagnosis of pulmonary embolism (PE), pneumonia, cryptogenic organising pneumonia and other reasons. Of 73 CTPA studies, 11 (15%) patients had evidence of PE.

CONCLUSION

In our centre, thoracic CT in COVID-19 patients were predominantly for the evaluation of PE with other indications being for COVID-19 complications and other cardiopulmonary pathologies. 23% of studies subsequently altered patient management, suggesting there is good clinical need for CT chests for these indications.

Ultra-Low Dose CT Chest in Acute COVID-19 Pneumonia: A Pilot Study from India

The rapid increase in the number of CT acquisitions during the COVID-19 pandemic raised concerns about increased radiation exposure to patients and the resultant radiation-induced health risks. It prompted researchers to explore newer CT techniques like ultra-low dose CT (ULDCT), which could improve patient safety. Our aim was to study the utility of ultra-low dose CT (ULDCT) chest in the evaluation of acute COVID-19 pneumonia with standard-dose CT (SDCT) chest as a reference standard. This was a prospective study approved by the institutional review board. 60 RT-PCR positive COVID-19 patients with valid indication for CT chest underwent SDCT and ULDCT. ULDCT and SDCT were compared in terms of objective (noise and signal-to-noise ratio) and subjective (noise, sharpness, artifacts and diagnostic confidence) image quality, various imaging patterns of COVID-19, CT severity score and effective radiation dose. The sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of ULDCT for detecting lung lesions were calculated by taking SDCT as a reference standard. The mean age of subjects was 47.2 ± 10.7 years, with 66.67% being men. 90% of ULDCT scans showed no/minimal noise and sharp images, while 93.33% had image quality of high diagnostic confidence. The major imaging findings detected by SDCT were GGOs (90%), consolidation (76.67%), septal thickening (60%), linear opacities (33.33%), crazy-paving pattern (33.33%), nodules (30%), pleural thickening (30%), lymphadenopathy (30%) and pleural effusion (23.33%). Sensitivity, specificity and diagnostic accuracy of ULDCT for detecting most of the imaging patterns were 100% (p < 0.001); except for GGOs (sensitivity: 92.59%, specificity: 100%, diagnostic accuracy: 93.33%), consolidation (sensitivity: 100%, specificity: 71.43%, diagnostic accuracy: 93.33%) and linear opacity (sensitivity: 90.00%, specificity: 100%, diagnostic accuracy: 96.67%). CT severity score (range: 15-25) showed 100% concordance on SDCT and ULDCT, while effective radiation dose was 4.93 ± 1.11 mSv and 0.26 ± 0.024 mSv, respectively. A dose reduction of 94.38 ± 1.7% was achieved with ULDCT. Compared to SDCT, ULDCT chest yielded images of reasonable and comparable diagnostic quality with the advantage of significantly reduced radiation dose; thus, it can be a good alternative to SDCT in the evaluation of COVID-19 pneumonia.

Role of MRI in the Evaluation of Pulmonary Sequel Following COVID-19 Acute Respiratory Distress Syndrome (ARDS)

To evaluate the role of magnetic resonance imaging (MRI) chest as an alternative modality to CT chest for follow-up of patients recovered from severe COVID-19 acute respiratory distress syndrome (ARDS). A total of 25 subjects (16 [64%] men; mean age 54.84 years ± 12.35) who survived COVID-19 ARDS and fulfilled the inclusion criteria were enrolled prospectively. All the patients underwent CT and MRI chest (on the same day) at 6-weeks after discharge. MRI chest was acquired on 1.5T MRI using HASTE, BLADE, VIBE, STIR, and TRUFI sequences and evaluated for recognition of GGOs, consolidation, reticulations/septal thickening, parenchymal bands, and bronchial dilatation with CT chest as the gold standard. The differences were assessed by independent-sample t-test and Mann-Whitney U test. P-value of less than 0.05 was taken significant. There was a strong agreement (k = 0.8-1, P<0.01) between CT and MRI chest. On CT, the common manifestations were: GGOs (n=24, 96%), septal thickening/reticulations (n=24, 96%), bronchial dilatation (n=16, 64%), parenchymal bands (n=14, 56%), pleural thickening (n=8, 32%), consolidation (n=4, 16%) and crazy-paving (n=4, 16%). T2W HASTE, T2W BLADE, and T1 VIBE sequences showed 100% (95% CI, 40-100) sensitivity and 100% (95% CI, 3-100) specificity for detecting GGOs, septal thickening/reticulations, pleural thickening, consolidation, and crazy-paving. The overall sensitivity of MRI for detection of bronchial dilatation and parenchymal bands were 88.9% (95% CI, 77-100) and 92.9% (95% CI, 66-100), respectively; and specificity was 100% (95% CI, 29-100) for both findings. MRI chest, being radiation-free imaging modality can act as an alternative to CT chest in the evaluation of lung changes in patients recovered from COVID-19 pneumonia.

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.

Correlation between chest CT and RT-PCR testing in India's second COVID-19 wave: a retrospective cohort study

OBJECTIVES

To assess the diagnostic accuracy of chest CT in clinically suspected patients with COVID-19 using reverse transcriptase PCR (RT-PCR) as the reference standard and establish the correlation between CT Severity Score (CTSS) and RT-PCR results.

DESIGN AND SETTING

Retrospective cohort study. Single-centre tertiary care hospital-based study.

PARTICIPANTS

We enrolled 112 clinically suspected patients with COVID-19 between 1 April 2021 and 31 May 2021. Chest CT and RT-PCR tests were performed for all patients at a time interval of no longer than 7 days between the two tests. Patients with prior chronic respiratory illnesses were excluded. The diagnostic performance of chest CT was evaluated using RT-PCR as the reference standard. The CTSS was calculated for all patients with positive chest CT findings, and it was correlated with results of the RT-PCR assay.

MAIN OUTCOME MEASURES

The primary outcome measures were determination of the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of chest CT using RT-PCR as the standard of reference. The correlation between CTSS and RT-PCR was the secondary outcome.

RESULTS

85/112 (76%) patients tested positive on the RT-PCR whereas 91/112 (81%) had chest CT findings typical of SARS-CoV-2 infection. Chest CT had a sensitivity of 90.6% (95% CI 82.3% to 95.8%), a specificity of 48.1% (95% CI 28.7% to 68.0%), a PPV of 84.6% (95% CI 79.2% to 88.8%), an NPV of 61.9% (95% CI 43.0% to 77.8%) and an accuracy of 80.4% (95% CI 71.8% to 87.3%). There was a significant correlation between the CTSS and RT-PCR positivity (p value=0.003).

CONCLUSION

In our experience, chest CT has a good sensitivity and provides a reliable diagnostic tool for moderate-to-severe COVID-19 cases in resource limited settings.

Estimated Atherosclerotic Cardiovascular Disease Risk: Disparities and Severe COVID-19 Outcomes (from the National COVID Cohort Collaborative)

Although cardiovascular disease risk factors relate to COVID-19, the association of estimated atherosclerotic cardiovascular disease (ASCVD) risk with severe COVID-19 is not established. We examined the relation of the pooled-cohort ASCVD risk score to severe COVID-19 among 28,646 subjects from the National COVID Cohort Collaborative database who had positive SARS-CoV-2 test results from April 1, 2020 to April 1, 2021. In addition, 10-year ASCVD risk scores were calculated, and subjects were stratified into low-risk (<5%), borderline-risk (5% to <7.5%), intermediate-risk (7.5% to <20%), and high-risk (>=20%) groups. Severe COVID-19 outcomes (including death, remdesivir treatment, COVID-19 pneumonia, acute respiratory distress syndrome, and mechanical ventilation) occurring during follow-up were examined individually and as a composite in relation to ASCVD risk group across race and gender. Multiple logistic regression, adjusted for age, gender, and race, examined the relation of ASCVD risk group to the odds of severe COVID-19 outcomes. Our subjects had a mean age of 59.4 years; 14% were black and 57% were female. ASCVD risk group was directly related to severe COVID-19 prevalence. The adjusted odds ratio of the severe composite COVID-19 outcome by risk group (vs the low-risk group) was 1.8 (95% confidence interval 1.5 to 2.2) for the borderline-risk, 2.7 (2.3 to 3.2) for the intermediate-risk, and 4.6 (3.7 to 5.6) for the high-risk group. Black men and black women in the high-risk group showed higher severe COVID-19 prevalence compared with nonblack men and nonblack women. Prevalence of severe COVID-19 outcomes was similar in intermediate-risk black men and high-risk nonblack men (approximately 12%). In conclusion, although further research is needed, the 10-year ASCVD risk score in adults ages 40 to 79 years may be used to identify those who are at highest risk for COVID-19 complications and for whom more intensive treatment may be warranted.

The Assessment of COVID-19 Pneumonia in Neonates: Observed by Lung Ultrasound Technique and Correlated with Biomarkers and Symptoms

Newborns infected with SARS-CoV2 infection develop different symptoms in comparison with adults, but one thing is clear: some of the most common manifestations include cough and other respiratory symptoms that need to be evaluated. In these cases, lung ultrasound is a useful imaging technique that can evaluate the newborns’ lung damage caused by COVID-19 pneumonia and can be used for the surveillance of the patients as well, being non-irradiating and easy to use. Nineteen neonates who were confirmed as having SARS-CoV2 infection were investigated using this imaging tool, and the results were compared and correlated with their symptoms and biomarkers. The mean of LUSS was 12.21 ± 3.56 (S.D), while the 95% CI for the arithmetic mean was 10.49–13.93. The difference of an independent t-test between the LUSS for the patient who presented cough and the LUSS for the patient without cough was −4.48 with an associated p-value of p = 0.02. The Pearson’s correlation coefficient r = 0.89 (p = 0.03, 95% CI 0.0642 to 0.993) between the LUSS and IL-6 level showed a positive strong correlation. This reliable correlation between lung ultrasound score and inflammatory markers suggests that LUS could be used for monitoring inflammatory lung diseases in the future.

Association of epicardial adipose tissue with the severity and adverse clinical outcomes of COVID-19: A meta-analysis

Objectives

Epicardial adipose tissue (EAT) has been proposed to be an independent predictor of visceral adiposity. EAT measures are associated with coronary artery disease, diabetes, and chronic obstructive pulmonary disease, which are risk factors for COVID-19 poor prognosis. Whether EAT measures are related to COVID-19 severity and prognosis is controversial.

Methods

We searched 6 databases for studies until January 7, 2022. The pooled effects are presented as the standard mean difference (SMD) or weighted mean difference with 95% confidence intervals (CIs). The primary end point was COVID-19 severity. Adverse clinical outcomes were also assessed.

Results

A total of 13 studies with 2482 patients with COVID-19 were identified. All patients had positive reverse transcriptase-polymerase chain reaction results. All quantitative EAT measures were based on computed tomography. Patients in the severe group had higher EAT measures compared with the nonsevere group (SMD = 0.74, 95% CI: 0.29–1.18, P = 0.001). Patients with hospitalization requirement, requiring invasive mechanical ventilation, admitted to intensive care unit, or with combined adverse outcomes had higher EAT measures compared to their controls (all P < 0.001).

Conclusions

EAT measures were associated with the severity and adverse clinical outcomes of COVID-19. EAT measures might help in prognostic risk stratification of patients with COVID-19.

Corticosteroids for Non-severe COVID-19: Primum Non Nocere

Muthu V, Sehgal IS, Dhooria S, Prasad KT, Aggarwal AN, Agarwal R. Corticosteroids for Non-severe COVID-19: Primum Non Nocere. Indian J Crit Care Med 2022;26(3):403–404.

The Conundrum of 'Long-COVID-19': A Narrative Review

COVID-19 is an ongoing pandemic with many challenges that are now extending to its intriguing long-term sequel. 'Long-COVID-19' is a term given to the lingering or protracted illness that patients of COVID-19 continue to experience even in their post-recovery phase. It is also being called 'post-acute COVID-19', 'ongoing symptomatic COVID-19', 'chronic COVID-19', 'post COVID-19 syndrome', and 'long-haul COVID-19'. Fatigue, dyspnea, cough, headache, brain fog, anosmia, and dysgeusia are common symptoms seen in Long-COVID-19, but more varied and debilitating injuries involving pulmonary, cardiovascular, cutaneous, musculoskeletal and neuropsychiatric systems are also being reported. With the data on Long-COVID-19 still emerging, the present review aims to highlight its epidemiology, protean clinical manifestations, risk predictors, and management strategies. With the re-emergence of new waves of SARS-CoV-2 infection, Long-COVID-19 is expected to produce another public health crisis on the heels of current pandemic. Thus, it becomes imperative to emphasize this condition and disseminate its awareness to medical professionals, patients, the public, and policymakers alike to prepare and augment health care facilities for continued surveillance of these patients. Further research comprising cataloging of symptoms, longer-ranging observational studies, and clinical trials are necessary to evaluate long-term consequences of COVID-19, and it warrants setting-up of dedicated, post-COVID care, multi-disciplinary clinics, and rehabilitation centers.