Pulmonary Sequelae in Patients After Recovery From Coronavirus Disease 2019: A Follow-Up Study With Chest CT

Long COVID in Children, Adults, and Vulnerable Populations: A Comprehensive Overview for an Integrated Approach

Long COVID affects both children and adults, including subjects who experienced severe, mild, or even asymptomatic SARS-CoV-2 infection. We have provided a comprehensive overview of the incidence, clinical characteristics, risk factors, and outcomes of persistent COVID-19 symptoms in both children and adults, encompassing vulnerable populations, such as pregnant women and oncological patients. Our objective is to emphasize the critical significance of adopting an integrated approach for the early detection and appropriate management of long COVID. The incidence and severity of long COVID symptoms can have a significant impact on the quality of life of patients and the course of disease in the case of pre-existing pathologies. Particularly, in fragile and vulnerable patients, the presence of PASC is related to significantly worse survival, independent from pre-existing vulnerabilities and treatment. It is important try to achieve an early recognition and management. Various mechanisms are implicated, resulting in a wide range of clinical presentations. Understanding the specific mechanisms and risk factors involved in long COVID is crucial for tailoring effective interventions and support strategies. Management approaches involve comprehensive biopsychosocial assessments and treatment of symptoms and comorbidities, such as autonomic dysfunction, as well as multidisciplinary rehabilitation. The overall course of long COVID is one of gradual improvement, with recovery observed in the majority, though not all, of patients. As the research on long-COVID continues to evolve, ongoing studies are likely to shed more light on the intricate relationship between chronic diseases, such as oncological status, cardiovascular diseases, psychiatric disorders, and the persistent effects of SARS-CoV-2 infection. This information could guide healthcare providers, researchers, and policymakers in developing targeted interventions.

Thymic Hyperplasia and COVID-19 Pulmonary Sequelae: A Bicentric CT-Based Follow-Up Study

This study aimed to investigate the role of the thymus in influencing long-term outcomes of COVID-19 by comparing the thymic appearance in patients with and without COVID-19 pulmonary sequelae at chest computed tomography (CT). A total of 102 adult patients previously hospitalized for COVID-19 underwent a follow-up chest CT three months after discharge. Pulmonary sequelae and thymic appearance were independently assessed by two experienced radiologists. The thymus was detectable in 55/102 patients (54%), with only 7/55 (13%) having any kind of pulmonary sequelae, compared to 33 out of 47 (70%, p < 0.001) in patients without thymic visibility, as confirmed in age-stratified analysis and at logistic regression analysis, where thymic involution had a 9.3 odds ratio (95% CI 3.0–28.2, p < 0.001) for the development of pulmonary sequelae. These results support the hypothesis that thymic reactivation plays a protective role against adverse long-term outcomes of COVID-19.

Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach

BACKGROUND

Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic-like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters.

METHODS

140 COVID survivors examined around 112 days post-diagnosis, along with 105 uninfected, non-smoking healthy controls, were studied. Their demographic data and CT scans at full inspiration and expiration were analyzed using a combined imaging and modeling approach. A subject-specific CT-based computational model analysis was utilized to predict airway resistance and particle deposition among C1 and C2 subjects. The cluster-specific structure and function relationships were explored.

RESULTS

In C1 subjects, distinctive features included airway narrowing, a reduced homothety ratio of daughter over parent branch diameter, and increased airway resistance. Airway resistance was concentrated in the distal region, with a higher fraction of particle deposition in the proximal airways. On the other hand, C2 subjects exhibited airway dilation, an increased homothety ratio, reduced airway resistance, and a shift of resistance concentration towards the proximal region, allowing for deeper particle penetration into the lungs.

CONCLUSIONS

This study revealed unique mechanistic phenotypes of airway resistance and particle deposition in the two post-COVID-19 clusters. The implications of these findings for inhaled drug delivery effectiveness and susceptibility to air pollutants were explored.

Comparison of Long COVID-19 Caused by Different SARS-CoV-2 Strains: A Systematic Review and Meta-Analysis

Although many studies of long COVID-19 were reported, there was a lack of systematic research which assessed the differences of long COVID-19 in regard to what unique SARS-CoV-2 strains caused it. As such, this systematic review and meta-analysis aims to evaluate the characteristics of long COVID-19 that is caused by different SARS-CoV-2 strains. We systematically searched the PubMed, EMBASE, and ScienceDirect databases in order to find cohort studies of long COVID-19 as defined by the WHO (Geneva, Switzerland). The main outcomes were in determining the percentages of long COVID-19 among patients who were infected with different SARS-CoV-2 strains. Further, this study was registered in PROSPERO (CRD42022339964). A total of 51 studies with 33,573 patients was included, of which three studies possessed the Alpha and Delta variants, and five studies possessed the Omicron variant. The highest pooled estimate of long COVID-19 was found in the CT abnormalities (60.5%; 95% CI: 40.4%, 80.6%) for the wild-type strain; fatigue (66.1%; 95% CI: 42.2%, 89.9%) for the Alpha variant; and ≥1 general symptoms (28.4%; 95% CI: 7.9%, 49.0%) for the Omicron variant. The pooled estimates of ≥1 general symptoms (65.8%; 95% CI: 47.7%, 83.9%) and fatigue were the highest symptoms found among patients infected with the Alpha variant, followed by the wild-type strain, and then the Omicron variant. The pooled estimate of myalgia was highest among patients infected with the Omicron variant (11.7%; 95%: 8.3%, 15.1%), compared with those infected with the wild-type strain (9.4%; 95%: 6.3%, 12.5%). The pooled estimate of sleep difficulty was lowest among the patients infected with the Delta variant (2.5%; 95%: 0.2%, 4.9%) when compared with those infected with the wild-type strain (24.5%; 95%: 17.5%, 31.5%) and the Omicron variant (18.7%; 95%: 1.0%, 36.5%). The findings of this study suggest that there is no significant difference between long COVID-19 that has been caused by different strains, except in certain general symptoms (i.e., in the Alpha or Omicron variant) and in sleep difficulty (i.e., the wild-type strain). In the context of the ongoing COVID-19 pandemic and its emerging variants, directing more attention to long COVID-19 that is caused by unique strains, as well as implementing targeted intervention measures to address it are vital.