Long COVID is the persistence of one or more COVID-19 symptoms after the initial viral infection, and there is evidence supporting its association with lung damage. In this systematic review, we provide an overview of lung imaging and its findings in long COVID patients. A PubMed search was performed on 29 September 2021, for English language studies in which lung imaging was performed in adults suffering from long COVID. Two independent researchers extracted the data. Our search identified 3130 articles, of which 31, representing the imaging findings of 342 long COVID patients, were retained. The most common imaging modality used was computed tomography (CT) (N = 249). A total of 29 different imaging findings were reported, which were broadly categorized into interstitial (fibrotic), pleural, airway, and other parenchymal abnormalities. A direct comparison between cases, in terms of residual lesions, was available for 148 patients, of whom 66 (44.6%) had normal CT findings. Although respiratory symptoms belong to the most common symptoms in long COVID patients, this is not necessarily linked to radiologically detectable lung damage. Therefore, more research is needed on the role of the various types of lung (and other organ) damage which may or may not occur in long COVID.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has led to the death of almost 7 million people, however, with a cumulative incidence of 0.76 billion, most people survive COVID-19. Several studies indicate that the acute phase of COVID-19 may be followed by persistent symptoms including fatigue, dyspnea, headache, musculoskeletal symptoms, and pulmonary functional-and radiological abnormalities. However, the impact of COVID-19 on long-term health outcomes remains to be elucidated. Aims: The Precision Medicine for more Oxygen (P4O2) consortium COVID-19 extension aims to identify long COVID patients that are at risk for developing chronic lung disease and furthermore, to identify treatable traits and innovative personalized therapeutic strategies for prevention and treatment. This study aims to describe the study design and first results of the P4O2 COVID-19 cohort. Methods: The P4O2 COVID-19 study is a prospective multicenter cohort study that includes nested personalized counseling intervention trial. Patients, aged 40–65 years, were recruited from outpatient post-COVID clinics from five hospitals in The Netherlands. During study visits at 3–6 and 12–18 months post-COVID-19, data from medical records, pulmonary function tests, chest computed tomography scans and biological samples were collected and questionnaires were administered. Furthermore, exposome data was collected at the patient’s home and state-of-the-art imaging techniques as well as multi-omics analyses will be performed on collected data. Results: 95 long COVID patients were enrolled between May 2021 and September 2022. The current study showed persistence of clinical symptoms and signs of pulmonary function test/radiological abnormalities in post-COVID patients at 3–6 months post-COVID. The most commonly reported symptoms included respiratory symptoms (78.9%), neurological symptoms (68.4%) and fatigue (67.4%). Female sex and infection with the Delta, compared with the Beta, SARS-CoV-2 variant were significantly associated with more persisting symptom categories. Conclusions: The P4O2 COVID-19 study contributes to our understanding of the long-term health impacts of COVID-19. Furthermore, P4O2 COVID-19 can lead to the identification of different phenotypes of long COVID patients, for example those that are at risk for developing chronic lung disease. Understanding the mechanisms behind the different phenotypes and identifying these patients at an early stage can help to develop and optimize prevention and treatment strategies.

Background: Despite the evidence for validity of body image pictogram (BIP) to discriminate overweight, obese, and normal individuals, there is little evidence on the probable effect of socio-demographic variables on its validity. To investigate the effects of socioeconomic status (SES), age, ethnicity, and educational level on the validity of BIP to discriminate normal weight, overweight, and obese people. Methods: We used the Pars Cohort Study (PCS) data. Stunkard’s BIP score was used as test measure. Participants were classified as normal (body mass index [BMI]<25), overweight (BMI=25 to 29.9), and obese (BMI≥29.9) based on their BMI (kg/m2 ). Area under curve (AUC) and its 95% CI were estimated and compared. Optimal cutoff points and their sensitivity, specificity, and likelihood ratio were reported. Results: A total of 9232 participants with a female/male ratio of 1.03 were included. The prevalence of overweight and obesity was 37.4% and 18.2%, respectively. Regardless of socio-demographic levels, the optimal cut-points to discriminate normal BMI from overweight, and overweight from obese participants were BIP score of four and five, respectively. Estimated AUC correlated with ethnicity (P<0.001) for both genders, and with SES for females (P<0.05). Conclusion: Although BIP may be a valid measure to categorize the general adult population into normal, overweight and obese, its validity depends on SES and ethnicity. BIP may be available as a proxy measure for BMI categories in socio-demographically homogeneous populations but not in heterogeneous populations.

Background: While some long-term effects of COVID-19 are respiratory in nature, a non-respiratory effect gaining attention has been a decline in hemoglobin, potentially mediated by inflammatory processes. In this study, we examined the correlations between hemoglobin levels and inflammatory biomarkers and evaluated the association between hemoglobin and fatigue in a cohort of Long-COVID patients. Methods: This prospective cohort study in the Netherlands evaluated 95 (mostly hospitalized) patients, aged 40–65 years, 3–6 months post SARS-CoV-2 infection, examining their venous hemoglobin concentration, anemia (hemoglobin < 7.5 mmol/L in women and <8.5 mmol/L in men), inflammatory blood biomarkers, average FSS (Fatigue Severity Score), demographics, and clinical features. Follow-up hemoglobin was compared against hemoglobin during acute infection. Spearman correlation was used for assessing the relationship between hemoglobin concentrations and inflammatory biomarkers, and the association between hemoglobin and fatigue was examined using logistic regression. Results: In total, 11 (16.4%) participants were suffering from anemia 3–6 months after SARS-CoV-2 infection. The mean hemoglobin value increased by 0.3 mmol/L 3–6 months after infection compared to the hemoglobin during the acute phase (p-value = 0.003). Whilst logistic regression showed that a 1 mmol/L greater increase in hemoglobin is related to a decrease in experiencing fatigue in Long-COVID patients (adjusted OR 0.38 [95%CI 0.13–1.09]), we observed no correlations between hemoglobin and any of the inflammatory biomarkers examined. Conclusion: Our results indicate that hemoglobin impairment might play a role in developing Long-COVID fatigue. Further investigation is necessary to identify the precise mechanism causing hemoglobin alteration in these patients.

Background: The incidence of severe asthma exacerbations (SAE) requiring a pediatric intensive care unit (PICU) admission during the coronavirus disease 2019 (COVID‐19) pandemic (and its association with public restrictions) is largely unknown. We examined the trend of SAE requiring PICU admission before, during, and after COVID‐19 restrictions in Amsterdam, the Netherlands, and its relationship with features such as environmental triggers and changes in COVID‐19 restriction measures.Methods: In this single‐center, retrospective cohort study, all PICU admissions of children aged ≥2 years for severe asthma at the Amsterdam UMC between 2018 and 2022 were included. The concentrations of ambient fine particulate matter (PM_2.5) and pollen were obtained from official monitoring stations.Results: Between January 2018 and December 2022, 228 children were admitted to the PICU of the Amsterdam UMC for SAE. While we observed a decrease in admissions during periods of more stringent restriction, there was an increase in the PICU admission rate for SAE in some periods following the lifting of restrictions. In particular, following the COVID‐19 restrictions in 2021, we observed a peak incidence of admissions from August to November, which was higher than any other peak during the indicated years. No association with air pollution or pollen was observed.Conclusion: We hypothesize that an increase in clinically diagnosed viral infections after lockdown periods was the reason for the altered incidence of SAE at the PICU in late 2021, rather than air pollution and pollen concentrations.

Background – The incidence of pediatric asthma exacerbations during the COVID-19 pandemic has been evaluated; however, the incidence of severe acute asthma (SAA) requiring a Pediatric Intensive Care Unit (PICU) admission is unknown. Furthermore, we examined several factors which might influence this incidence, such as environmental triggers or changes in COVID-19 lockdown regulations. Methods – In this single-center, retrospective cohort study running from 2018 to 2021, all PICU admissions for SAA of children above two years of age at a tertiary hospital in the Netherlands were included. Information on potential asthma triggers during the pandemic, including viral infections, concentrations of ambient fine particulate matter (PM2.5) and pollen index were evaluated. Results – In total, 168 children were included in this study. While we observed a decrease in PICU admissions for SAA during lockdown periods, there was an increase in the admission rates in the periods without a lockdown, with the highest peak from August to November of 2021. This peak in the fall of 2021 did not align with pollen or ambient PM2.5 concentrations (r _s =-0.04 for pollen and r _s =0.23 for PM2.5). Discussion – COVID-19 lockdowns influenced the admission rates for SAA at the PICU both during and after the lockdowns in the Netherlands. We hypothesize that an increase in viral infections after lockdown periods was the reason for the altered incidence of SAA at the PICU in late 2021, rather than air pollution and pollen concentrations.