Objectives: To analyze evolutionary predictors of post-COVID syndrome (PCS). Methods: This Cohort study was conducted from April 2021 to December 2023. PCS persistence was defined as a score of ≥2 points on the post-COVID-19 Functional Status (PCFS) scale (range 0-4, where higher scores indicate more limitations). Symptom clusters were identified using correspondence analysis. The association between PCS persistence and symptoms and symptom clusters were assessed using multivariable analysis, considering both the acute infection period and the baseline PCS visit variables. Results: The 112 included patients showed a mean of 6.1 symptoms (standard deviation [SD] 3.2), most commonly dyspnea (67.9%), asthenia (67.0%), fatigue (57.1%), and myalgia (49.1%). Regarding baseline functional status, 59.8% scored 2 points on the PCFS; 40.2%, 3 points; and 2.6%, 4 points. Moreover, 68.7% had depression and 83.0%, anxiety. Two symptom clusters emerged: anxiety + depression + severe PCFS, and palpitations + hyporexia + dyspnea. At a mean of 12.1 months (SD 9.2), the persistence rate was 33.9% (cumulative persistence time 20 months [SD 11.9]). Persistence was significantly associated with the absence of rhinitis (odds ratio [OR] 3.67, 95% confidence interval [CI] 1.28-10.52) during acute infection, and the presence of fatigue (OR 4.88, 95% CI 1.77-13.44) and depression (moderate: OR 4.28, 95% CI 1.05-17.44; severe: OR 10.31, 95% CI 2.60-40.90) at the baseline visit. The model multivariable demonstrated a good fit (likelihood ratio test 30.1, p < 0.001) and predictive capacity (area under the receiver operating curve 0.804). The anxiety + depression + severe PCFS cluster was significantly associated with persistence (OR 3.26, 95% CI 1.21-8.76; p = 0.012). Conclusions: A third of patients with PCS still experience significant functional impairment 20 months after onset. Persistence is associated with the absence of rhinitis during acute infection and with severe anxiety, depression, and functional impairment measured by the PCFS on detection of PCS.
