This website presents the results of the work conducted by the WP2 of the Orchestra project . This is an analysis of data of over 4800 patients' hospitalized and non-hospitalized adults in France, Italy, Spain, the Netherlands and Argentina, who tested positive for SARS-CoV-2 between January 24, 2020, and March 30, 2023.
The inital analysis of the dataset, as it was available at the time, was already published and is available here: Clinical phenotypes and quality of life to define post-COVID-19 syndrome: a cluster analysis of the multinational, prospective ORCHESTRA cohort.
However, during three years of data collection and analysis, we noticed the PCS is dynamic, with symptoms fluctuating across long periods of time. Therefore, the common cross-sectional approach, that looks at the single timepoint, does not reflect well the nature of this disease.
Participants provided demographic details, acute-phase information, and symptom reports at 3, 6, 12, and 18 months post-acute disease. We meticulously recorded nine specific symptoms, including dysgeusia, ageusia, arthralgia, cough, dyspnea, fatigue/malaise, headache, memory loss, and myalgia, employing Latent Transition Analysis (LTA) to model symptom trajectories [An Introduction to Latent Class Growth Analysis and Growth Mixture Modeling].
While our current LTA maximizes data utilization, it doesn't integrate potential covariates, posing a potential bias source. Nonetheless, the diverse transition probabilities offer a nuanced analysis of patient-level recovery patterns at this stage.
Explore the full LTA model in the entire model. If you would like to use the model as a preditor of symptoms at the 3,6,12 and 18 months after the acute phase, go to Clinical algorithm.
Feel free to contact authors: Roy Gusinov, and Ania Gorska if you have any questions.