Background: The long-term evolution of COVID-19 in patients hospitalized during the pandemic's first wave remains largely unexplored. This study aimed to identify COVID-19 pulmonary phenotypes and their longitudinal patterns over a 12-month follow-up.
Methods: COVID-19 patients discharged from Pisa University Hospital (Italy) between March-September 2020, were evaluated at T3, T12, and T24 months post-discharge. Assessments included spirometry, lung volumes, DLCO, and chest CT for those with persistent pneumonia signs (PS). Latent transition analysis (LTA) identified COVID-19 phenotypes and longitudinal patterns based on PS and lung function (PFTs). Risk factors for these patterns were evaluated using multinomial logistic regression.
Results: Of 307 discharged patients, 175, 136, and 33 were followed-up at T3, T12, and T24, respectively. At T12, 21.6% had impaired DLCO, 4.4% a restrictive ventilatory pattern, and 31,6% still had PS, persisting until T24. LTA identified three cross-sectional phenotypes at both T3 and T12 (no PS with normal PFTs; PS with normal PFTs; PS with impaired PFTs), and four longitudinal patterns from T3 to T12: persistence of no PS with normal PFTs (47.9%); resolution of both PS and PFTs (15.4%); persistent PS (36.7%), either with (11%) or without (25.7%) impaired PFTs. The last two patterns correlated significantly with longer hospitalization, more comorbidities, and severe COVID-19.
Conclusions: In our cohort of COVID-19 patients hospitalized during the pandemic's first wave, we observed distinct pulmonary phenotypes and longitudinal recovery patterns. More comorbidities and severe acute disease correlated with worse progression up to 24 months, suggesting long-term monitoring for such patients.
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http://dx.doi.org/10.1016/j.rmed.2025.107952 | DOI Listing |
Importance: "SuperAgers" are oldest-old adults (ages 80+) whose memory performance resembles that of adults in their 50s to mid-60s. Factors underlying their exemplary memory are underexplored in large, racially diverse cohorts.
Objective: To determine the frequency of genotypes in non-Hispanic Black and non-Hispanic White SuperAgers compared to middle-aged (ages 50-64), old (ages 65-79), and oldest-old (ages 80+) controls and Alzheimer's disease (AD) dementia cases.
The long-term effects of repeated COVID-19 vaccinations on adaptive immunity remain incompletely understood. Here, we conducted a comprehensive three-year longitudinal study examining T cell and antibody responses in 78 vaccinated individuals without reported symptomatic infections. We observed distinct dynamics in Spike-specific humoral and cellular immune responses across multiple vaccine doses.
View Article and Find Full Text PDFAging Cell
January 2025
MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Metabolomics and epigenomics have been used to develop 'ageing clocks' that assess biological age and identify 'accelerated ageing'. While metabolites are subject to short-term variation, DNA methylation (DNAm) may capture longer-term metabolic changes. We aimed to develop a hybrid DNAm-metabolic clock using DNAm as metabolite surrogates ('DNAm-metabolites') for age prediction.
View Article and Find Full Text PDFCardiovasc Diabetol
January 2025
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Background: Type 2 diabetes (T2D) has been linked to changes in DNA methylation levels, which can, in turn, alter transcriptional activity. However, most studies for epigenome-wide associations between T2D and DNA methylation comes from cross-sectional design. Few large-scale investigations have explored these associations longitudinally over multiple time-points.
View Article and Find Full Text PDFRespir Med
January 2025
Pulmonary Unit, Cardiothoracic and Vascular Department, Pisa University Hospital, Pisa, Italy; Department of Surgical, Medical, and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy.
Background: The long-term evolution of COVID-19 in patients hospitalized during the pandemic's first wave remains largely unexplored. This study aimed to identify COVID-19 pulmonary phenotypes and their longitudinal patterns over a 12-month follow-up.
Methods: COVID-19 patients discharged from Pisa University Hospital (Italy) between March-September 2020, were evaluated at T3, T12, and T24 months post-discharge.
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