Long coronavirus disease 2019 (COVID-19)-a postacute consequence of severe acute respiratory syndrome coronavirus 2 infection-manifests with a broad spectrum of relapsing and remitting or persistent symptoms as well as varied levels of organ damage, which may be asymptomatic or present as acute events such as heart attacks or strokes and recurrent infections, hinting at complex underlying pathogenic mechanisms. Central to these symptoms is vascular dysfunction rooted in thrombotic endothelialitis. We review the scientific evidence that widespread endothelial dysfunction (ED) leads to chronic symptomatology. We briefly examine the molecular pathways contributing to endothelial pathology and provide a detailed analysis of how these cellular processes underpin the clinical picture. Noninvasive diagnostic techniques, such as flow-mediated dilation and peripheral arterial tonometry, are evaluated for their utility in identifying ED. We then explore mechanistic, cellular-targeted therapeutic interventions for their potential in treating ED. Overall, we emphasize the critical role of cellular health in managing Long COVID and highlight the need for early intervention to prevent long-term vascular and cellular dysfunction.

Computed tomography (CT) is a critical tool for the diagnosis of pneumonia caused by SARS-CoV-2. The Delta and Omicron variants show distinct clinical features, but the radiological differences between pneumonia caused by these variants have not been extensively studied in patients with oxygen-dependent pneumonia.

To compare the radiological and clinical features of pneumonia in patients hospitalized with oxygen-dependent SARS-CoV-2 infection caused by the Delta and Omicron variants.

We performed a retrospective single-center study, including patients hospitalized with oxygen-dependent SARS-CoV-2 pneumonia between October 2021 and February 2022. Clinical and radiological data were collected and compared between patients infected with the Delta variant and those with the Omicron variant. CT scans were reviewed by a radiologist and a pulmonologist blinded to clinical and variant information.

A total of 135 patients with the Delta variant and 48 with the Omicron variant were included. Patients infected with Omicron were older (median age 75 years [68-83.2] vs 69 years [62-77.5], p = 0.004), more immunocompromised (52 % vs. 25 %, p < 0.001), and had higher vaccination rates (73 % vs. 51 %, p = 0.009). Radiologically, ground-glass opacities were present in 95 % of patients. There were no significant differences in the degree of lung involvement, type of lesions and their predominance. Unilateral lung involvement was more common in Omicron-infected patients (8.3 % vs 0.74 %, p = 0.02).

While Omicron oxygen-dependent pneumonia occurred in older and more comorbid patients, its clinical and radiological features were largely indistinguishable from those caused by the Delta variant, except for a higher rate of unilateral lung involvement.

Coronavirus disease 2019 (COVID-19) pneumonia has had catastrophic effects worldwide. Radiology, in particular computed tomography (CT) imaging, has proven to be valuable in the diagnosis, prognostication, and longitudinal assessment of those diagnosed with COVID-19 pneumonia. This article will review acute and chronic pulmonary radiologic manifestations of COVID-19 pneumonia with an emphasis on CT and also highlighting histopathology, relevant clinical details, and some notable challenges when interpreting the literature.

The coronavirus disease (COVID-19) pandemic is a global health emergency, and SARS-CoV-2 pneumonia poses significant challenges to health systems worldwide. Renal transplant recipients (RTRs) are a special group and are more vulnerable to viral pneumonia. However, few studies have elucidated the risk factors of SARS-CoV-2 pneumonia in RTRs infected with COVID-19. This study aimed to build a risk prediction model for SARS-CoV-2 pneumonia among RTRs based on demographic and clinical information.

We conducted a prospective cohort study among 383 RTRs (age ≥ 18 years) diagnosed with COVID-19 from December 21, 2022, to March 26, 2023. Patients' demographic and clinical information was collected through a questionnaire survey combined with electronic medical records. A stepwise logistic regression model was established to test the predictors of SARS-CoV-2 pneumonia. We assessed the diagnostic performance of the model by calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) and calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test.

Our study showed that the incidence of SARS-CoV-2 pneumonia among RTRs was 31.1%. Older age (OR = 2.08-3.37,95%CI:1.05-7.23), shorter post-transplantation duration (OR = 0.92,95% CI: 0.87,0.99), higher post-transplant Charlson Comorbidity Index (CCI) (OR = 1.84, 95%CI: 1.14,2.98), pulmonary infection history (OR = 3.44, 95%CI: 1.459, 8.099, P = 0.005), fatigue (OR = 2.11, 95%CI: 1.14, 3.90), cough (OR = 2.03, 95%CI: 1.08, 3.81), and lower estimated glomerular filtration rate (eGFR) at COVID-19 diagnosis (OR = 0.98, 95%CI:0.97,0.99) predicted a higher risk for SARS-CoV-2 pneumonia. The model showed good diagnostic performance with Chi-Square = 10.832 (P > 0.05) and AUC = 0.839 (P < 0.001).

Our study showed a high incidence of SARS-CoV-2 pneumonia among RTRs, and we built a risk prediction model for SARS-CoV-2 pneumonia based on patients' demographic and clinical characteristics. The model can help identify RTRs infected with COVID-19 at high risk of SARS-CoV-2 pneumonia to inform timely, targeted, and effective prevention and intervention efforts.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, fast-spreading, and insidious. Most patients present with normal findings on lung computed tomography (CT). The current study aimed to develop and validate a tracheal CT radiomics model to predict Omicron variant infection.

In this retrospective study, a radiomics model was developed based on a training set consisting of 157 patients with an Omicron variant infection and 239 healthy controls between 1 January and 30 April 2022. A set of morphological expansions, with dilations of 1, 3, 5, 7, and 9 voxels, was applied to the trachea, and radiomic features were extracted from different dilation voxels of the trachea. Logistic regression (LR), support vector machines (SVM), and random forests (RF) were developed and evaluated; the models were validated on 67 patients with the Omicron variant and on 103 healthy controls between 1 May and 30 July 2022.

Logistic regression with 12 radiomic features extracted from the tracheal wall with dilation of 5 voxels achieved the highest classification performance compared with the other models. The LR model achieved an area under the curve of 0.993 (95% confidence interval [CI]: 0.987-0.998) in the training set and 0.989 (95% CI: 0.979-0.999) in the validation set. Sensitivity, specificity, and accuracy of the model for the training set were 0.994, 0.946, and 0.965, respectively, whereas those for the validation set were 0.970, 0.952, and 0.959, respectively.

The tracheal CT radiomics model reliably identified the Omicron variant of SARS-CoV‑2, and may help in clinical decision-making in future, especially in cases of normal lung CT findings.

Background The post-pandemic phase of the coronavirus infectious disease that emerged in 2019 (COVID-19) has necessitated updates in radiology, with emerging evidence suggesting tracheobronchial wall thickness as a potential new diagnostic marker. Purpose To evaluate the accuracy of chest computed tomography (CT) scans in identifying COVID-19 by assessing tracheobronchial wall thickness in mid-2023. Material and methods A retrospective review was conducted on 60 patients who underwent thoracoabdominal CT and the severe acute respiratory syndrome coronavirus (SARS-CoV-2) antigen tests during emergency visits between June and August 2023. Tracheobronchial wall thickness was measured using a 4-point scale (1=no thickening, 2=mild, 3=moderate, 4=significant). Lung assessment employed the COVID-19 Reporting and Data System (CO-RADS). Patients were classified based on antigen test results. The Mann-Whitney U test and Fisher's exact test compared characteristics and CT findings. Diagnostic performance was evaluated using the area under the receiver operating characteristic curves (AUC). Results The SARS-CoV-2-positive group showed significantly thicker tracheobronchial walls (median 1.5 mm vs. 1.2 mm, P < 0.001), especially in the trachea's membranous wall (median 1.2 mm vs. 0.9 mm, P < 0.001) and higher scores (median 3 vs. 2, P < 0.001). CO-RADS scores showed no significant difference. Quantitative and qualitative wall thickness assessments demonstrated high diagnostic value, with AUCs of 0.90 and 0.94, and accuracies of 85% and 87%, respectively. Conclusion Tracheobronchial wall thickness on chest CT exhibited high diagnostic accuracy, establishing it as a reliable marker for COVID-19 detection in mid-2023.

Rice (Oryza sativa L.) cultivation using direct seeding is susceptible to chilling stress, particularly during seed germination and early seedling growth in the early season of a double cropping system. Alternatively, seed priming with various plant growth-promoting hormones is an effective technique to promote rapid and uniform emergence under chilling stress. Therefore, we evaluated the impact of gibberellin A3 (GA3) and brassinolide (BR) priming on rice seed emergence, examining their proteomic responses under low-temperature conditions. Results indicated that GA3 and BR increased the seed germination rate by 22.67% and 7.33% at 72 h and 35% and 15% at 96 h compared to the control (CK), respectively. Furthermore, proteomic analysis identified 2551, 2614, and 2592 differentially expressed proteins (DEPs) in GA, BR, and CK, respectively. Among them, GA exhibited 84 upregulated and 260 downregulated DEPs, while BR showed 112 upregulated and 102 downregulated DEPs, and CK had 123 upregulated and 81 downregulated DEPs. Notably, under chilling stress, both GA3 and BR are involved in peroxide metabolism, phenylpropanoid biosynthesis, and inositol phosphate metabolism, enhancing antioxidant capacity and providing energy substances for germination. In addition, GA3 triggers the specific regulation of stress responsive protein activation, GTP activation, and ascorbic acid biosynthesis and promotes the stability and integrity of cell membranes, as well as the synthesis of cell walls, providing physical defense for seeds to resist low temperatures. At the same time, BR triggers specific involvement in ribosome synthesis and amino acid synthesis, promoting biosynthetic ability and metabolic regulation to maintain plant life activities under low-temperature stress. Furthermore, the various genes' expression (OsJ_16716, OsPAL1, RINO1) confirmed GA3 and BR involved in peroxide metabolism, phenylpropanoid biosynthesis, and inositol phosphate metabolism, enhancing antioxidant capacity and providing energy substances for germination. This study provides valuable insights into how rice seed embryo responds to and tolerates chilling stress with GA3 seed priming.

To identify clinical characteristics and risk factors for pulmonary involvements in asymptomatic and mildly symptomatic patients infected with SARS-CoV-2 Omicron variant by chest imaging analysis.

Detailed data and chest computed tomography (CT) imaging features were retrospectively analyzed from asymptomatic and mildly symptomatic patients infected with Omicron between 24 April and 10 May 2022. We scored chest CT imaging features and categorized the patients into obvious pulmonary involvements (OPI) (score > 2) and not obvious pulmonary involvements (NOPI) (score ≤ 2) groups based on the median score. The risk factors for OPI were identified with analysis results visualized by nomogram.

In total, 339 patients were included (145 were male and 194 were female), and the most frequent clinical symptoms were cough (75.5%); chest CT imaging features were mostly linear opacities (42.8%). Pulmonary involvements were more likely to be found in the left lower lung lobe, with a significant difference in the lung total severity score of the individual lung lobes (p < 0.001). Logistic regression analysis revealed age stratification [odds ratio (OR) = 1.92, 95% confidence interval (CI) (1.548-2.383); p < 0.001], prolonged nucleic acid negative conversion time (NCT) (NCT > 8d) [OR = 1.842, 95% CI (1.104-3.073); p = 0.019], and pulmonary diseases [OR = 4.698, 95% CI (1.159-19.048); p = 0.03] as independent OPI risk factors.

Asymptomatic and mildly symptomatic patients infected with Omicron had pulmonary involvements which were not uncommon. Potential risk factors for age stratification, prolonged NCT, and pulmonary diseases can help clinicians to identify OPI in asymptomatic and mildly symptomatic patients infected with Omicron.

Coronavirus disease 2019 (COVID-19) pneumonia has had catastrophic effects worldwide. Radiology, in particular computed tomography (CT) imaging, has proven to be valuable in the diagnosis, prognostication, and longitudinal assessment of those diagnosed with COVID-19 pneumonia. This article will review acute and chronic pulmonary radiologic manifestations of COVID-19 pneumonia with an emphasis on CT and also highlighting histopathology, relevant clinical details, and some notable challenges when interpreting the literature.

Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), manifests as persistent and often debilitating symptoms enduring well beyond the initial COVID-19 infection. This disease is especially worrying in children since it can seriously alter their development. Presently, a specific diagnostic test or definitive biomarker set for confirming long COVID is lacking, relying instead on the protracted presence of symptoms post-acute infection.

We measured the levels of 13 biomarkers in 105 saliva samples (49 from children with long COVID and 56 controls), and the Pearson correlation coefficient was used to analyse the correlations between the levels of the different salivary biomarkers. Multivariate logistic regression analyses were performed to determine which of the 13 analysed salivary biomarkers were useful to discriminate between children with long COVID and controls, as well as between children with mild and severe long COVID symptoms.

Pediatric long COVID exhibited increased oxidant biomarkers and decreased antioxidant, immune response, and stress-related biomarkers. Correlation analyses unveiled distinct patterns between biomarkers in long COVID and controls. Notably, a multivariate logistic regression pinpointed TOS, ADA2, total proteins, and AOPP as pivotal variables, culminating in a remarkably accurate predictive model distinguishing long COVID from controls. Furthermore, total proteins and ADA1 were instrumental in discerning between mild and severe long COVID symptoms.

This research sheds light on the potential clinical utility of salivary biomarkers in diagnosing and categorizing the severity of pediatric long COVID. It also lays the groundwork for future investigations aimed at unravelling the prognostic value of these biomarkers in predicting the trajectory of long COVID in affected individuals.

As the long-term consequences of coronavirus disease 2019 (COVID-19) have not been defined, it is necessary to explore persistent symptoms, long-term respiratory impairment, and impact on quality of life over time in COVID-19 survivors. In this prospective cohort study, convalescent individuals diagnosed with COVID-19 were followed-up 2 and 3 years after discharge from hospital. Participants completed an in-person interview to assess persistent symptoms and underwent blood tests, pulmonary function tests, chest high-resolution computed tomography, and the 6-min walking test. There were 762 patients at the 2-year follow-up and 613 patients at the 3-year follow-up. The mean age was 60 years and 415 (54.5%) were men. At 3 years, 39.80% of the participants had at least one symptom; most frequently, fatigue, difficulty sleeping, joint pain, shortness of breath, muscle aches, and cough. The participants experienced different degrees of pulmonary function impairment, with decreased carbon monoxide diffusion capacity being the main feature; results remained relatively stable over the 2-3 years. Multiple logistic regression analysis demonstrated that female sex and smoking were independently associated with impaired diffusion capacity. A subgroup analysis based on disease severity was performed, indicating that there was no difference in other parameters of lung function except forced vital capacity at 3-year follow-up. Persistent radiographic abnormalities, most commonly fibrotic-like changes, were observed at both timepoints. At 3 years, patients had a significantly improved Mental Component Score compared with that at 2 years, with a lower percentage with anxiety. Our study indicated that symptoms and pulmonary abnormalities persisted in COVID-19 survivors at 3 years. Further studies are warranted to explore the long-term effects of COVID-19 and develop appropriate rehabilitation strategies.

To investigate potential differences in clinical and computed tomography (CT) features between patients with the SARS-CoV-2 Omicron variant and the original strain.

This retrospective study included 69 hospitalized patients infected with Omicron variant from November to December 2022, and 96 hospitalized patients infected with the original strain from February to March 2020 in Chongqing, China. The clinical features, CT manifestations, degrees of lung involvement in different stages on CT, and imaging changes after the reverse-transcription polymerase chain reaction (RT-PCR) results turned negative were compared between the two groups.

For clinical features, patients with Omicron were predominantly old people and females, without manifestation of any clinical symptoms, who had low serum levels of C-reactive protein and procalcitonin. Shorter interval from symptoms onset to initial CT scan was observed in Omicron patients compared to patients with the original strain (all P < 0.05). For CT features, patients with Omicron were more likely to present with round-like opacities and tree-in-bud pattern (all P < 0.05), but less likely to exhibit a diffuse distribution, patchy and linear opacities, as well as vascular enlargement pattern (all P < 0.05). The Omicron group was more susceptible to exhibiting lower CT involvement scores in each stage (all P < 0.05) and imaging progression after the RT-PCR results turned negative (P < 0.001).

Patients infected with the Omicron variant exhibited less severe changes on chest CT compared to those infected with the original strain. Furthermore, imaging progression under low viral load conditions was more common in patients with Omicron than in those with the original strain.

Significant changes were observed in the lung imaging of hospitalised COVID-19 patients from 2020 to 2023, with the emergence of more signs of co-infection https://bit.ly/3TaQlJ2.

The Omicron variant of COVID-19 is less severe than the ancestral strain, leading to the potential for deaths in patients infected with the virus but who die of other causes. This study evaluated the difference in rates of pneumonia among patients who died with SARS-CoV-2 infection in the ancestral vs Omicron eras.

We identified patients who died within 30days of a positive SARS-CoV-2 test, from March 2020 through December 2022; variants were assigned based on the prevalent variant in the US at that time. We also obtained a control group from patients who died within 30days of a negative SARS-CoV-2 test in January 2022. The first CT after the test was reviewed in a blinded fashion and assigned a category from the RSNA Consensus Reporting Guidelines. The primary outcome was the difference in rates of positive (typical or indeterminate) COVID-19 findings in the ancestral vs Omicron eras.

A total of 598 patients died during the ancestral era and 400 during the Omicron era, and 347 decedents comprised the control group. The rate of positive COVID-19 findings was 67/81 (83%) in the ancestral era and 43/81 (53%) in the Omicron era (P < .001), an absolute difference of 30% (95% CI 16%-43%). The rate of positive findings in the control group was 23/76 (30%).

During the Omicron era, 30% fewer SARS-CoV-2-associated deaths were associated with COVID-19 pneumonia and were caused either by nonpulmonary effects of the infection or were unrelated to the infection.

To investigate the frequency of pneumonia and chest computed tomography (CT) findings in patients with coronavirus disease 2019 (COVID-19) during the fifth Delta variant-predominant and sixth Omicron variant-predominant waves of the COVID-19 pandemic in Okinawa, Japan. A survey on chest CT examinations for patients with COVID-19 was conducted byhospitals with board-certified radiologists who provided treatment for COVID-19 pneumonia in Okinawa Prefecture. Data from 11 facilities were investigated. Indications for chest CT; number of COVID-19 patients undergoing chest CT; number of patients with late-onset pneumonia, tracheal intubation, and number of deaths; and COVID-19 Reporting and Data System classifications of initial chest CT scans were compared by the chi-squared test between the two pandemic waves (Delta vs. Omicron variants). A total of 1944 CT scans were performed during the fifth wave, and 1178 were performed during the sixth wave. CT implementation rates, which were the number of patients with COVID-19 undergoing CT examinations divided by the total number of COVID-19 cases in Okinawa Prefecture during the waves, were 7.1% for the fifth wave and 2.1% for the sixth wave. The rates of tracheal intubation and mortality were higher in the fifth wave. Differences between the distributions of the CO-RADS classifications were statistically significant for the fifth and sixth waves (p < 0.0001). In the fifth wave, CO-RADS 5 (typical of COVID-19) was most common (65%); in the sixth wave, CO-RADS 1 (no findings of pneumonia) was most common (50%). The finding of "typical for other infection but not COVID-19" was more frequent in the sixth than in the fifth wave (13.6% vs. 1.9%, respectively). The frequencies of pneumonia and typical CT findings were higher in the fifth Delta variant-predominant wave, and nontypical CT findings were more frequent in the sixth Omicron variant-predominant wave of the COVID-19 pandemic in Okinawa, Japan.

We investigated different computed tomography (CT) features between Omicron-variant and original-strain SARS-CoV‑2 pneumonia to facilitate the clinical management.

Medical records were retrospectively reviewed to select patients with original-strain SARS-CoV‑2 pneumonia from February 22 to April 22, 2020, or Omicron-variant SARS-CoV‑2 pneumonia from March 26 to May 31, 2022. Data on the demographics, comorbidities, symptoms, clinical types, and CT features were compared between the two groups.

There were 62 and 78 patients with original-strain or Omicron-variant SARS-CoV‑2 pneumonia, respectively. There were no differences between the two groups in terms of age, sex, clinical types, symptoms, and comorbidities. The main CT features differed between the two groups (p = 0.003). There were 37 (59.7%) and 20 (25.6%) patients with ground-glass opacities (GGO) in the original-strain and Omicron-variant pneumonia, respectively. A consolidation pattern was more frequently observed in the Omicron-variant than original-strain pneumonia (62.8% vs. 24.2%). There was no difference in crazy-paving pattern between the original-strain and Omicron-variant pneumonia (16.1% vs. 11.6%). Pleural effusion was observed more often in Omicron-variant pneumonia, while subpleural lesions were more common in the original-strain pneumonia. The CT score in the Omicron-variant group was higher than that in the original-strain group for critical-type (17.00, 16.00-18.00 vs. 16.00, 14.00-17.00, p = 0.031) and for severe-type (13.00, 12.00-14.00 vs 12.00, 10.75-13.00, p = 0.027) pneumonia.

The main CT finding of the Omicron-variant SARS-CoV‑2 pneumonia included consolidations and pleural effusion. By contrast, CT findings of original-strain SARS-CoV‑2 pneumonia showed frequent GGO and subpleural lesions, but without pleural effusion. The CT scores were also higher in the critical and severe types of Omicron-variant than original-strain pneumonia.

To investigate the computed tomography (CT) findings of SARs-CoV-2 Omicron variant in relation to respiratory viral loads determined by cycle threshold values in reverse-transcription polymerase chain reaction (RT-PCR).

From October 2022 to November 2022, 74 hospitalized patients with Omicron were included in this retrospective study. The radiological features, CT involvement scores in relation to the respiratory viral load, and factors associated with imaging progression (IP) after the RT-PCR results turned negative were analyzed.

The most common CT patterns of Omicron were multiple round-like or patchy ground-glass opacity (GGO) or mixed GGO in the peripheral or diffuse areas. The grading of CT involvement scores exhibited an inverse pattern compared to viral loads from day 1 to day 8 and from day 13 to day 20 after diagnosis. Among the 65 patients with complete imaging data, 45 (69.23%) showed IP with clinical warning indicators of disease exacerbation negative in 34 and positive in 11. Patients with IP were older than those with non-IP (NIP); the erythrocyte sedimentation rates, procalcitonin levels, and D-dimer levels on admission of patients with IP were significantly higher than those of patients with NIP, whereas the immunoglobulin (Ig) G antibody level on admission and CT involvement score on initial CT of patients with IP were significantly lower than those of patients with NIP (all P < 0.05).

For patients with Omicron, the IP of lung abnormalities is common when the viral load decreases. Under these circumstances, paying attention to clinical warming indicators of disease progression may contribute to better patient management and the mitigation of severe pneumonia.

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case-control study involving mild-to-moderate COVID-19 patients treated with corticosteroids was conducted from 4 September 2021, to 30 August 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale. Serial abnormality scores for consolidation and pleural effusion on CXR were obtained using a commercial AI-based software based on days from the onset of symptoms. Amongst the 258 participants included in the analysis, 147 (57%) were male. Multivariable logistic regression analysis revealed that high pleural effusion score at 6-9 days from onset of symptoms (adjusted odds ratio of (aOR): 1.022, 95% confidence interval (CI): 1.003-1.042, p = 0.020) and consolidation scores up to 9 days from onset of symptoms (0-2 days: aOR: 1.025, 95% CI: 1.006-1.045, p = 0.010; 3-5 days: aOR: 1.03 95% CI: 1.011-1.051, p = 0.002; 6-9 days: aOR; 1.052, 95% CI: 1.015-1.089, p = 0.005) were associated with an unfavorable corticosteroid response. AI-generated scores could help intervene in the use of corticosteroids in COVID-19 patients who would not benefit from them.

Survivors of SARS-CoV-2 pneumonia often develop persistent respiratory symptom and interstitial lung abnormalities (ILAs) after infection. Risk factors for ILA development and duration of ILA persistence after SARS-CoV-2 infection are not well described in immunocompromised hosts, such as cancer patients.

We conducted a prospective cohort study of 95 patients at a major cancer center and 45 patients at a tertiary referral center. We collected clinical and radiographic data during the index hospitalization for COVID-19 pneumonia and measured pneumonia severity using a semi-quantitative radiographic score, the Radiologic Severity Index (RSI). Patients were evaluated in post-COVID-19 clinics at 3 and 6 months after discharge and underwent comprehensive pulmonary evaluations (symptom assessment, chest computed tomography, pulmonary function tests, 6-min walk test). The association of clinical and radiological factors with ILAs at 3 and 6 months post-discharge was measured using univariable and multivariable logistic regression.

Sixty-six (70%) patients of cancer cohort had ILAs at 3 months, of whom 39 had persistent respiratory symptoms. Twenty-four (26%) patients had persistent ILA at 6 months after hospital discharge. In adjusted models, higher peak RSI at admission was associated with ILAs at 3 (OR 1.5 per 5-point increase, 95% CI 1.1-1.9) and 6 months (OR 1.3 per 5-point increase, 95% CI 1.1-1.6) post-discharge. Fibrotic ILAs (reticulation, traction bronchiectasis, and architectural distortion) were more common at 6 months post-discharge.

Post-COVID-19 ILAs are common in cancer patients 3 months after hospital discharge, and peak RSI and older age are strong predictors of persistent ILAs.

This study aimed to compare the clinical picture of COVID-19 in the initial and later period of Omicron dominance and to identify populations still at risk. A retrospective comparison of the clinical data of 965 patients hospitalized during the early period of Omicron's dominance (EO, January-June 2022) with 897 patients from a later period (LO, July 2022-April 2023) from the SARSTer database was performed. Patients hospitalized during LO, compared to EO, were older, had a better clinical condition on admission, had a lower need for oxygen and mechanical ventilation, had less frequent lung involvement in imaging, and showed much faster clinical improvement. Moreover, the overall mortality during EO was 14%, higher than that in LO-9%. Despite the milder course of the disease, mortality exceeding 15% was similar in both groups among patients with lung involvement. The accumulation of risk factors such as an age of 60+, comorbidities, lung involvement, and oxygen saturation <90% resulted in a constant need for oxygen in 98% of patients, an 8% risk of mechanical ventilation, and a 30% mortality rate in the LO period. Multiple logistic regression revealed lower odds of death during the LO phase. Despite the milder course of infections caused by the currently dominant subvariants, COVID-19 prophylaxis is necessary in people over 60 years of age, especially those with comorbidities, and in the case of pneumonia and respiratory failure.

This study is the first study in which demographic, laboratory data, and outcomes of coronavirus disease-2019 (COVID-19) patients due to the circulating SARS-CoV-2 infections caused by different variants (Alpha, Delta, and Omicron) are compared in Iran.

We conducted a retrospective study of confirmed hospitalized COVID-19 cases from April 9, 2021, to May 22, 2022. Demographic data and laboratory findings were extracted from patients' electronic medical records on the first day of admission to the hospital. All patients were followed up for outcomes related to COVID-19 including intensive care unit (ICU) admission and mortality rate.

Of 760 confirmed hospitalized COVID-19 cases, 362, 298, and 100 represented patients during waves 4-6, respectively. During the Omicron wave, hospitalized patients were older than the other two waves and had a lower median level of C-reactive protein (CRP), alanine transaminase (ALT), aspartate transaminase (AST), and erythrocyte sedimentation rate (ESR). The median length of hospital stay during waves 4-6 was 5 days (interquartile range [IQR]: 4.0-8.0), 7 days (IQR: 6.0-11), and 6 days (IQR: 5.0-9.0), respectively (p < 0.001). The rate of ICU admission during waves 4-6 significantly increased.

Although the Omicron variant caused less severe disease, in older patients who were hospitalized due to Omicron infection, longer hospital and ICU stays were reported, which could be attributed to their old age. In particular, elderly patients are more vulnerable to severe COVID-19; otherwise, as expected, other laboratory parameters and clinical outcomes were in accordance with differences in pathogenicity and infectivity of these variants.

The evolving mutants of SARS-CoV-2 have made the COVID-19 pandemic sustained for over 3 years. In 2022, BA.4 and BA.5 were the Omicron variants dominating the spread globally. Although COVID-19 was no longer a Public Health Emergency of International Concern (PHEIC) as announced by WHO, the SARS-CoV-2 variants remain a challenge to global healthcare under the circumstances of withdrawal and loosening of personal protective behavior in the post-quarantine era. This study aims to acknowledge the clinical characteristics caused by Omicron BA.4/BA.5 in COVID-19 naive people and analyze possible factors affecting disease severities.

In this retrospective study, we report and analyze the clinical features of 1820 COVID-19 patients infected with the BA.4/BA.5 Omicron variants of SARS-CoV-2 during a local outbreak that occurred in Macao SAR, China, from June to July 2022.

A total of 83.5% of patients were symptomatic eventually. The most common symptoms were fever, cough, and sore throat. Hypertension, dyslipidemia, and diabetes mellitus were the leading comorbidities. There were significantly more elderly patients (p < 0.001), more patients with comorbidity (p < 0.001) and more patients without vaccination or not completing the series (p < 0.001) in the "Severe to Critical" group. All deceased patients were elderly with at least three comorbidities and were partial to totally dependent in their daily lives.

Our data are consistent with a milder disease caused by BA.4/5 Omicron variants in the general population, while patients with old age and comorbidities have developed severe to critical diseases. Complete vaccination series and booster doses are effective strategies to reinforce protection against severe diseases and avoid mortality.

Background Differences in the clinical and radiological characteristics of SARS-CoV-2 Omicron subvariants have not been well studied. Purpose To compare clinical disease severity and radiologically severe pneumonia in patients with COVID-19 hospitalized during a period of either Omicron BA.1/BA.2 or Omicron BA.5 subvariant predominance. Materials and Methods This multicenter retrospective study, included patients registered in the Korean Imaging Cohort of COVID-19 database who were hospitalized for COVID-19 between January and December 2022. Publicly available relative variant genome frequency data were used to determine the dominant periods of Omicron BA.1/BA.2 subvariants (January 17 to June 20, 2022) and the Omicron BA.5 subvariant (July 4 to December 5, 2022). Clinical outcomes and imaging pneumonia outcomes based on chest radiography and CT were compared among predominant subvariants using multivariable analyses adjusted for covariates. Results Of 1916 confirmed patients with COVID-19 (mean age, 72 years ± 16 [SD]; 1019 males), 1269 were registered during the Omicron BA.1/BA.2 subvariant dominant period and 647 during the Omicron BA.5 subvariant dominant period. Patients in the BA.5 group showed lower odds of high-flow O₂ requirement (adjusted odds ratio [OR], 0.75 [95% CI: 0.57, 0.99]; P = .04), mechanical ventilation (adjusted OR, 0.49 [95% CI: 0.34, 0.72]; P < .001]), and death (adjusted OR, 0.47 [95% CI: 0.33, 0.68]; P <.001) than those in the BA.1/BA.2 group. Additionally, the BA.5 group had lower odds of severe pneumonia on chest radiographs (adjusted OR, 0.68 [95% CI: 0.53, 0.88]; P = .004) and higher odds of atypical pattern pneumonia on CT images (adjusted OR, 1.81 [95% CI: 1.26, 2.58]; P = .001) than the BA.1/BA.2 group. Conclusions Patients hospitalized during the period of Omicron BA.5 subvariant predominance had lower odds of clinical and pneumonia severity than those hospitalized during the period of Omicron BA.1/BA.2 predominance, even after adjusting for covariates. See also the editorial by Hammer in this issue.

In December 2022, there was a large Omicron epidemic in Hangzhou, China. Many people were diagnosed with Omicron pneumonia with variable symptom severity and outcome. Computed tomography (CT) imaging has been proven to be an important tool for COVID-19 pneumonia screening and quantification. We hypothesized that CT-based machine learning algorithms can predict disease severity and outcome in Omicron pneumonia, and we compared its performance with the pneumonia severity index (PSI)-related clinical and biological features.

Our study included 238 patients with the Omicron variant who have been admitted to our hospital in China from 15 December 2022 to 16 January 2023 (the first wave after the dynamic zero-COVID strategy stopped). All patients had a positive real-time polymerase chain reaction (PCR) or lateral flow antigen test for SARS-CoV-2 after vaccination and no previous SARS-CoV-2 infections. We recorded patient baseline information pertaining to demographics, comorbid conditions, vital signs, and available laboratory data. All CT images were processed with a commercial artificial intelligence (AI) algorithm to obtain the volume and percentage of consolidation and infiltration related to Omicron pneumonia. The support vector machine (SVM) model was used to predict the disease severity and outcome.

The receiver operating characteristic (ROC) area under the curve (AUC) of the machine learning classifier using PSI-related features was 0.85 (accuracy = 87.40%, p < 0.001) for predicting severity while that using CT-based features was only 0.70 (accuracy = 76.47%, p = 0.014). If combined, the AUC was not increased, showing 0.84 (accuracy = 84.03%, p < 0.001). Trained on outcome prediction, the classifier reached the AUC of 0.85 using PSI-related features (accuracy = 85.29%, p < 0.001), which was higher than using CT-based features (AUC = 0.67, accuracy = 75.21%, p < 0.001). If combined, the integrated model showed a slightly higher AUC of 0.86 (accuracy = 86.13%, p < 0.001). Oxygen saturation, IL-6, and CT infiltration showed great importance in both predicting severity and outcome.

Our study provided a comprehensive analysis and comparison between baseline chest CT and clinical assessment in disease severity and outcome prediction in Omicron pneumonia. The predictive model accurately predicts the severity and outcome of Omicron infection. Oxygen saturation, IL-6, and infiltration in chest CT were found to be important biomarkers. This approach has the potential to provide frontline physicians with an objective tool to manage Omicron patients more effectively in time-sensitive, stressful, and potentially resource-constrained environments.

To meta-analyze diagnostic performance measures of standardized typical CT findings for COVID-19 and examine these measures by region and national income.

MEDLINE and Embase were searched from January 2020 to April 2022 for diagnostic studies using the Radiological Society of North America (RSNA) classification or the COVID-19 Reporting and Data System (CO-RADS) for COVID-19. Patient and study characteristics were extracted. We pooled the diagnostic performance of typical CT findings in the RSNA and CO-RADS systems and interobserver agreement. Meta-regression was performed to examine the effect of potential explanatory factors on the diagnostic performance of the typical CT findings.

We included 42 diagnostic performance studies with 6777 PCR-positive and 9955 PCR-negative patients from 18 developing and 24 developed countries covering the Americas, Europe, Asia, and Africa. The pooled sensitivity was 70% (95% confidence interval [CI]: 65%, 74%; I² = 92%), and the pooled specificity was 90% (95% CI 86%, 93%; I² = 94%) for the typical CT findings of COVID-19. The sensitivity and specificity of the typical CT findings did not differ significantly by national income and the region of the study (p > 0.1, respectively). The pooled interobserver agreement from 19 studies was 0.72 (95% CI 0.63, 0.81; I² = 99%) for the typical CT findings and 0.67 (95% CI 0.61, 0.74; I² = 99%) for the overall CT classifications.

The standardized typical CT findings for COVID-19 provided moderate sensitivity and high specificity globally, regardless of region and national income, and were highly reproducible between radiologists.

Standardized typical CT findings for COVID-19 provided a reproducible high diagnostic accuracy globally.

Standardized typical CT findings for COVID-19 provide high sensitivity and specificity. Typical CT findings show high diagnosability regardless of region or income. The interobserver agreement for typical findings of COVID-19 is substantial.

Pulmonary function can be impaired as a long-term consequence of SARS-CoV-2 infection. The aim of this study was to evaluate the effect of SARS-CoV-2 infection on pulmonary function, exercise tolerance, and muscle strength in healthy middle-aged military outpatients according during the period of infection.

A cross-sectional study was carried out from March 2020 to November 2022 at the Military Hospital "Celio" (Rome, Italy). If someone had a diagnosis of SARS-CoV-2 infection certified by molecular nasal swab and if they performed pulmonary function tests, diffusion of carbon monoxide (DL'co), a six Minute Walk Test (6MWT), a Handgrip (HG) Test, and a One Minute Sit to Stand Test (1'STST). The included subjects were divided into two groups, A and B, according to the period of infection: A) from March 2020 to August 2021 and B) from September 2021 to October 2022.

One hundred fifty-three subjects were included in the study: 79 in Group A and 74 in Group B. Although the values were within the normal range, Group A had smaller FVC, FEV_1, and DL'co compared to Group B. Group A also walked a shorter distance at the 6MWT and performed fewer repetitions in the 1'STS test compared to Group B. In both groups, the DL'co (%predicted) correlated with the 6MWT distance (R² = 0.107, p < 0.001), the number of repetitions of the 1'STST (R² = 0.086, p = 0.001), and the strength at the HG test (R² = 0.08, p < 0.001).

This study shows that the SARS-CoV-2 infection in healthy middle-aged military outpatients was more severe in the first waves than in the later ones and that, in healthy and physically fit individuals, even a marginal reduction in resting respiratory test values can have a major impact on exercise tolerance and muscles strength. Moreover, it shows that those infected more recently had symptoms related to the upper respiratory tract infection compared to those of the first waves.

Background The SARS-CoV-2 Omicron variant has a higher infection rate than previous variants but results in less severe disease. However, the effects of Omicron and vaccination on chest CT findings are difficult to evaluate. Purpose To investigate the effect of vaccination status and predominant variant on chest CT findings, diagnostic scores, and severity scores in a multicenter sample of consecutive patients referred to emergency departments for proven COVID-19. Materials and Methods This retrospective multicenter study included adults referred to 93 emergency departments with SARS-CoV-2 infection according to a reverse-transcriptase polymerase chain reaction test and known vaccination status between July 2021 and March 2022. Clinical data and structured chest CT reports, including semiquantitative diagnostic and severity scores following the French Society of Radiology-Thoracic Imaging Society guidelines, were extracted from a teleradiology database. Observations were divided into Delta-predominant, transition, and Omicron-predominant periods. Associations between scores and variant and vaccination status were investigated with χ² tests and ordinal regressions. Multivariable analyses evaluated the influence of Omicron variant and vaccination status on the diagnostic and severity scores. Results Overall, 3876 patients were included (median age, 68 years [quartile 1 to quartile 3 range, 54-80]; 1695 women). Diagnostic and severity scores were associated with the predominant variant (Delta vs Omicron, χ² = 112.4 and 33.7, respectively; both P < .001) and vaccination status (χ² = 243.6 and 210.1; both P < .001) and their interaction (χ² = 4.3 [P = .04] and 28.7 [P < .001], respectively). In multivariable analyses, Omicron variant was associated with lower odds of typical CT findings than was Delta variant (odds ratio [OR], 0.46; P < .001). Two and three vaccine doses were associated with lower odds of demonstrating typical CT findings (OR, 0.32 and 0.20, respectively; both P < .001) and of having high severity score (OR, 0.47 and 0.33, respectively; both P < .001), compared with unvaccinated patients. Conclusion Both the Omicron variant and vaccination were associated with less typical chest CT manifestations of COVID-19 and lesser extent of disease. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Yoon and Goo in this issue.

The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We propose a new paradigm for medical AI, which we refer to as generalist medical AI (GMAI). GMAI models will be capable of carrying out a diverse set of tasks using very little or no task-specific labelled data. Built through self-supervision on large, diverse datasets, GMAI will flexibly interpret different combinations of medical modalities, including data from imaging, electronic health records, laboratory results, genomics, graphs or medical text. Models will in turn produce expressive outputs such as free-text explanations, spoken recommendations or image annotations that demonstrate advanced medical reasoning abilities. Here we identify a set of high-impact potential applications for GMAI and lay out specific technical capabilities and training datasets necessary to enable them. We expect that GMAI-enabled applications will challenge current strategies for regulating and validating AI devices for medicine and will shift practices associated with the collection of large medical datasets.

The effect of vitamin D status on adult COVID-19 pneumonia induced by Delta variant remains to be further explored.

A longitudinal, real-world cohort study was performed. Artificial intelligence (AI) was used to identify and measure pneumonia lesions. All cases with pneumonia were divided into the vitamin D deficiency (VDD) and control groups according to serum 25-hydroxyvitamin D concentration. Lesion dynamics were observed within six time periods after the onset of pneumonia.

A total of 161 cases were included, of which 101 (63%) were male and 46 (29%) presented with pneumonia. The median age and baseline 25-hydroxyvitamin D concentrations were 37 years and 21 ng/ml, respectively. Age, fibrinogen, and SARS-CoV-2 IgG titer on admission were independent predictors for the onset of pneumonia. After the onset of pneumonia, patients in the VDD group (n = 18) had higher percentage of fever (33 vs. 7.1%; p = 0.04) than those in the control group (n = 28); the interval of pneumonia resolution was longer (28 vs. 21 days; p = 0.02); lesions progressed more rapidly (p = 0.01) within 3 to 7 days and improved more slowly (p = 0.007) within more than 28 days; notably, simultaneous interleukin-6 (18.7 vs. 14.6 pg/ml; p = 0.04) levels were higher, and cycle thresholds for N gene (22.8 vs. 31.3; p = 0.04) and ORF1ab gene (20.9 vs. 28.7; p = 0.03) were lower within 3 to 7 days.

Vitamin D status may have effects on the progression and resolution, but not the onset of Delta variant-induced pneumonia in adults. Computed tomography image diagnosis system based on AI may have promising applications in the surveillance and diagnosis of novel SARS-CoV-2 variant-induced pneumonia.

Background Few reports have evaluated the effect of the SARS-CoV-2 variant and vaccination on the clinical and imaging features of COVID-19. Purpose To evaluate and compare the effect of vaccination and variant prevalence on the clinical and imaging features of infections by the SARS-CoV-2. Materials and Methods Consecutive adults hospitalized for confirmed COVID-19 at three centers (two academic medical centers and one community hospital) and registered in a nationwide open data repository for COVID-19 between August 2021 and March 2022 were retrospectively included. All patients had available chest radiographs or CT images. Patients were divided into two groups according to predominant variant type over the study period. Differences between clinical and imaging features were analyzed with use of the Pearson χ2 test, Fisher exact test, or the independent t test. Multivariable logistic regression analyses were used to evaluate the effect of variant predominance and vaccination status on imaging features of pneumonia and clinical severity. Results Of the 2180 patients (mean age, 57 years ± 21; 1171 women), 1022 patients (47%) were treated during the Delta variant predominant period and 1158 (53%) during the Omicron period. The Omicron variant prevalence was associated with lower pneumonia severity based on CT scores (odds ratio [OR], 0.71 [95% CI: 0.51, 0.99; P = .04]) and lower clinical severity based on intensive care unit (ICU) admission or in-hospital death (OR, 0.43 [95% CI: 0.24, 0.77; P = .004]) than the Delta variant prevalence. Vaccination was associated with the lowest odds of severe pneumonia based on CT scores (OR, 0.05 [95% CI: 0.03, 0.13; P < .001]) and clinical severity based on ICU admission or in-hospital death (OR, 0.15 [95% CI: 0.07, 0.31; P < .001]) relative to no vaccination. Conclusion The SARS-CoV-2 Omicron variant prevalence and vaccination were associated with better clinical outcomes and lower severe pneumonia risk relative to Delta variant prevalence. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Little in this issue.

The emergence of the severe acute respiratory syndrome coronavirus 2 omicron variant has been triggering the new wave of coronavirus disease 2019 (COVID-19) globally. However, the risk factors and outcomes for radiological abnormalities in the early convalescent stage (1 month after diagnosis) of omicron infected patients are still unknown.

Patients were retrospectively enrolled if they were admitted to the hospital due to COVID-19. The chest computed tomography (CT) images and clinical data obtained at baseline (at the time of the first CT image that showed abnormalities after diagnosis) and 1 month after diagnosis were longitudinally analyzed. Uni-/multi-variable logistic regression tests were performed to explore independent risk factors for radiological abnormalities at baseline and residual pulmonary abnormalities after 1 month.

We assessed 316 COVID-19 patients, including 47% with radiological abnormalities at baseline and 23% with residual pulmonary abnormalities at 1-month follow-up. In a multivariate regression analysis, age ≥ 50 years, body mass index ≥ 23.87, days after vaccination ≥ 81 days, lymphocyte count ≤ 1.21 × 10^-9/L, interleukin-6 (IL-6) ≥ 10.05 pg/mL and IgG ≤ 14.140 S/CO were independent risk factors for CT abnormalities at baseline. The age ≥ 47 years, presence of interlobular septal thickening and IL-6 ≥ 5.85 pg/mL were the independent risk factors for residual pulmonary abnormalities at 1-month follow-up. For residual abnormalities group, the patients with less consolidations and more parenchymal bands at baseline could progress on CT score after 1 month. There were no significant changes in the number of involved lung lobes and total CT score during the early convalescent stage.

The higher IL-6 level was a common independent risk factor for CT abnormalities at baseline and residual pulmonary abnormalities at 1-month follow-up. There were no obvious radiographic changes during the early convalescent stage in patients with residual pulmonary abnormalities.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mainly infects the upper respiratory tract. This study aimed to determine whether the probability of pulmonary infection and the cycle threshold (Ct) measured using the fluorescent polymerase chain reaction (PCR) method were related to pulmonary infections diagnosed via computed tomography (CT).

To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values, as determined via PCR.

The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2 Omicron variant infections were retrospectively collected and categorized into low (< 25), medium (25.00-34.99), and high (≥ 35) Ct groups. The characteristics of chest CT images in each group were statistically analyzed.

The PCR Ct values ranged from 13.36 to 39.81, with 99 patients in the low, 155 in the medium, and 77 in the high Ct groups. Six abnormal chest CT signs were detected, namely, focal infection, patchy consolidation shadows, patchy ground-glass shadows, mixed consolidation ground-glass shadows, subpleural interstitial changes, and pleural changes. Focal infections were less frequent in the low Ct group than in the medium and high Ct groups; these infections were the most common sign in the medium and high Ct groups. Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups. The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.

The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARS-CoV-2 varied depending on the Ct values. Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.

This article reviews the radiologic and pathologic findings of the epithelial and endothelial injuries in COVID-19 pneumonia to help radiologists understand the fundamental nature of the disease. The radiologic and pathologic manifestations of COVID-19 pneumonia result from epithelial and endothelial injuries based on viral toxicity and immunopathologic effects. The pathologic features of mild and reversible COVID-19 pneumonia involve nonspecific pneumonia or an organizing pneumonia pattern, while the pathologic features of potentially fatal and irreversible COVID-19 pneumonia are characterized by diffuse alveolar damage followed by fibrosis or acute fibrinous organizing pneumonia. These pathologic responses of epithelial injuries observed in COVID-19 pneumonia are not specific to SARS-CoV-2 but rather constitute universal responses to viral pneumonia. Endothelial injury in COVID-19 pneumonia is a prominent feature compared with other types of viral pneumonia and encompasses various vascular abnormalities at different levels, including pulmonary thromboembolism, vascular engorgement, peripheral vascular reduction, a vascular tree-in-bud pattern, and lung perfusion abnormality. Chest CT with different imaging techniques (eg, CT quantification, dual-energy CT perfusion) can fully capture the various manifestations of epithelial and endothelial injuries. CT can thus aid in establishing prognosis and identifying patients at risk for deterioration.

A patient with severe COVID-19 pneumonia requiring ICU admission and prolonged hospital stay is presented. The infection resulted in long term morbidity, functional decline and abnormal chest CT findings. Mechanisms for long term lung injury post COVID-19 infection, imaging appearances and role of imaging in follow-up are discussed.

We investigated whether COVID-19 leads to persistent impaired pulmonary function, fibrotic-like abnormalities or psychological symptoms 12 months after discharge and whether severely ill patients (ICU admission) recover differently than moderately ill patients.

This single-centre cohort study followed adult COVID-19 survivors for a period of one year after discharge. Patients underwent pulmonary function tests 6 weeks, 3 months and 12 months after discharge and were psychologically evaluated at 6 weeks and 12 months. Computed tomography (CT) was performed after 3 months and 12 months.

66 patients were analysed, their median age was 60.5 (IQR: 54-69) years, 46 (70%) patients were male. 38 (58%) patients had moderate disease and 28 (42%) patients had severe disease. Most patients had spirometric values within normal range after 12 months of follow-up. 12 (23%) patients still had an impaired lung diffusion after 12 months. Impaired pulmonary diffusion capacity was associated with residual CT abnormalities (OR 5.1,CI-95: 1.2-22.2), shortness of breath (OR 7.0, CI-95: 1.6-29.7) and with functional limitations (OR 5.8, CI-95: 1.4-23.8). Ground-glass opacities resolved in most patients during follow-up. Resorption of reticulation, bronchiectasis and curvilinear bands was rare and independent of disease severity. 81% of severely ill patients and 37% of moderately ill patients showed residual abnormalities after 12 months (OR 8.1, CI-95: 2.5-26.4). A minority of patients had symptoms of post-traumatic stress disorder, anxiety, depression and cognitive failure during follow-up.

Some patients still had impaired lung diffusion 12 months after discharge and fibrotic-like residual abnormalities were notably prevalent, especially in severely ill patients.

Coronavirus disease-2019 (COVID-19) pneumonia has diverse clinical manifestations, which have shifted throughout the pandemic. Formal classifications include presymptomatic infection and mild, moderate, severe, and critical illness. Social risk factors are numerous, with Black, Hispanic, and Native American populations in the United States having suffered disproportionately. Biological risk factors such as age, sex, underlying comorbid burden, and certain laboratory metrics can assist the clinician in triage and management. Guidelines for classifying radiographic findings have been proposed and may assist in prognosis. In this article, we review the risk factors, clinical course, complications, and imaging findings of COVID-19 pneumonia.

In the 3rd year of the SARS-CoV-2 pandemic, much has been learned about the long-term effects of COVID-19 pneumonia on the lungs. Approximately one-third of patients with moderate-to-severe pneumonia, especially those requiring intensive care therapy or mechanical ventilation, have residual abnormalities at chest CT 1 year after presentation. Abnormalities range from parenchymal bands to bronchial dilation to frank fibrosis. Less is known about the long-term pulmonary vascular sequelae, but there appears to be a persistent, increased risk of venothromboembolic events in a small cohort of patients. Finally, the associated histologic abnormalities resulting from SARS-CoV-2 infection are similar to those seen in patients with other causes of acute lung injury.