Short and Long-Term Trajectories of the Post COVID-19 Condition: Results from the EuCARE POSTCOVID study

Short and Long-Term Trajectories of the Post COVID-19 Condition: Results from the EuCARE POSTCOVID study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Short and Long-Term Trajectories of the Post COVID-19 Condition: Results from the EuCARE POSTCOVID study Andrea Santoro, Francesca Bai, Maria Francesca Greco, Roberta Rovito, and 20 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4419711/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 4 You are reading this latest preprint version Abstract Background Post COVID-19 condition (PCC) affects 10–40% of patients and is characterized by persisting symptoms at ≥ 4 weeks after SARS CoV-2 infection. Symptoms can last 7 or even more months. How long PCC persists and any changes in its clinical phenotypes over time require further investigation. We investigated PCC trajectories and factors associated with PCC persistence. Material and methods We included both hospitalized COVID-19 patients and outpatients from February 2020 to June 2023, who underwent at least one follow-up visit after acute infection at San Paolo Hospital, University of Milan. Follow-up visits were conducted at the post COVID-19 clinic or via telemedicine. During each follow-up examination, patients completed a short version of the WHO CRF for ongoing symptoms, the Hospital Anxiety and Depression Scale (HADS), and a screening tool for Post-Traumatic Stress Disorder (PTSD). Statistical analyses involved Chi-square, Mann-Whitney, Kruskal-Wallis tests, and logistic regression analysis. Results We enrolled 853 patients (median age 62, IQR 52–73; 41% females). 551/853 (64.6%), 152/418 (36.4%) and 21/69 (30.4%) presented PCC at median follow up of 3 (IQR 2–3), 7 (IQR 6–10) and 26 (IQR 20–33) months, respectively (p < 0.001). The main clinical phenotypes were fatigue, respiratory sequelae, brain fog and chronic pain; anosmia/dysgeusia was observed mostly in the first post-acute period. Female sex, acute disease in 2020, a longer hospital stay and no COVID-19 vaccination were associated with persistence or resolution of PCC compared to never having had PCC. Anxiety, depression and PTSD were more common in PCC patients. By fitting a logistic regression analysis, acute infection in 2020 remained independently associated with persistent PCC, adjusting for age, sex, preexisting comorbidities and disease severity (AOR 0.479 for 2021 vs 2020, 95%CI 0.253–0.908, p = 0.024; AOR 0.771 for 2022 vs 2020, 95%CI 0.259–2.297, p = 0.641; AOR 0.086 for 2023 vs 2020, 95%CI 0.086–3.830, p = 0.565). Conclusions There was a reduction in the PCC burden 7 months following the acute phase; still, one third of patients experienced long-lasting symptoms. The main clinical presentations of PCC remain fatigue, respiratory symptoms, brain fog, and chronic pain. Having had SARS CoV-2 infection during the first pandemic phases appears to be associated with persistent PCC. SARS CoV-2 long COVID Post Acute Sequelae of SARS CoV-2 Post COVID-19 condition Figures Figure 1 Background Long COVID, also referred to as Post-COVID-19 Condition (PCC), is defined by the Center for Disease Control and Prevention (CDC) as the presence of persisting symptoms four weeks after the acute SARS-CoV-2 infection [ 1 , 2 ]. It is estimated that PCC affects a substantial proportion of patients, ranging from 10–40%, placing a heavy burden on already stressed health systems [ 3 – 6 ]. Symptoms can last for months, with many studies following patients for up to one year since the acute phase, and a few others suggesting symptoms may last even longer [ 7 – 9 ]. For the sake of simplicity, symptoms can be grouped in clusters in order to identify different PCC phenotypes [ 10 , 11 ]. One study found shortness of breath and chronic fatigue as the most frequent long COVID manifestations, while female sex and severe COVID-19 infection during the acute phase were the main risk factors for developing PCC [ 12 – 14 ]. Evidence indicates a decline in PCC incidence following the surge of the Omicron variant compared to the wild-type virus, while incidence was higher with the Alpha and Delta variants [ 15 – 18 ]. A follow-up study on long-term outcomes in 242,712 COVID-19 patients showed patients infected with the Omicron variant were 88% less likely to experience lingering symptoms compared to the original viral strain [ 15 ]. Preliminary data suggest a reduction in the risk of developing long-term cardiorespiratory sequelae after Omicron infection compared to the wild-type virus, while neurological symptoms, such as depression and anxiety, continue to be prevalent [ 8 , 15 ]. It is currently unclear how long this condition persists, and whether clinical phenotypes change over time. Many factors have been associated with PCC development, most notably older age, female sex, the severity of acute infection, and prior comorbidities, while vaccination and antiviral treatment seem to play a protective role [ 19 – 25 ]. Several authors have suggested a possible role of psychological factors in the development of PCC, especially during the initial waves of the pandemic (2020–2021) due to isolation during lockdowns and fear of a new, previously unknown disease [ 26 , 27 ]. One study measured depression and anxiety levels during lockdowns, which resulted to be at quasi-clinical levels [ 21 ]. Evidence for a possible reduction in psychological symptoms with later variants is currently limited. Since the onset of the ongoing COVID-19 pandemic, healthcare professionals have encountered unprecedented challenges in the management and follow-up of patients. The implementation of lockdown measures, coupled with the surge in patient numbers and the resulting strain on health systems, necessitated novel approaches to follow-up care and the optimization of hospital resources. Additionally, the prevalence of old age and comorbidities, common characteristics in COVID-19 patients, heightened the risk of loss to follow-up. In response to these challenges, new methods of patient re-evaluation, such as telemedicine, have been introduced, benefiting both patients and healthcare providers [ 20 ]. Telemedicine employs audio and/or visual devices to facilitate communication between patients and healthcare professionals. This study presents the outcomes of a follow-up program designed for COVID-19 patients from the EuCARE POSTCOVID cohort [ 28 ], conducted from January 2020 to June 2023, employing in person evaluations and telemedicine. Our aim was to examine the trajectories of PCC and clinical outcomes over time, as well as to identify potential factors associated with PCC persistence in a cohort of both hospitalized and non-hospitalized patients. Materials and methods Study design and population The EuCARE POSTCOVID study is a retrospective and prospective cohort study including patients with at least one follow-up examination at 2–3, 6–10 and ≥ 12 months after an acute SARS CoV-2 infection. It includes 6 centers in over 3 continents and aims to investigate the long-term outcome of SARS CoV-2 infection; the study protocol has already been described elsewhere [ 28 ]. Patients included in this study have been evaluated at the post COVID service of the Clinic of Infectious Diseases, San Paolo Hospital, ASST Santi Paolo e Carlo, Milan, Italy or by telemedicine from February 2020 to June 2023. We included both hospitalized COVID-19 patients and outpatients with milder disease who were not hospitalized during the acute phase. The study flow chart is depicted in Fig. 1 . Study procedures At each visit, patients underwent blood exams and completed a condensed version of the post-COVID-19 WHO Case Report Form (CRF) to document symptoms. Following the acute phase and/or hospital discharge, we gathered data on persistent symptoms not previously experienced before COVID-19 infection. If any symptoms were reported, we investigated whether they persisted, their frequency, or if they had already resolved. Additionally, patients completed the Hospital Anxiety and Depression Scale (HADS-A/D) to assess symptoms of anxiety and depression and a screening tool for Post-Traumatic Stress Disorder (PTSD). The HADS-A/D includes 7 questions each for anxiety and depression. A total HADS score between 8 and 10 indicates "possible" cases, while scores of 11 or more denote "probable" cases for both anxiety and depression. Scores higher than 10 were utilized to identify symptoms of anxiety and depression. The Post-traumatic Stress Disorder Checklist-5 (PCL-5) is a 20-item self-report measure assessing the 20 DSM-5 symptoms of PTSD, with a 5-point scale for each symptom. A total symptom severity score ranging from 0 to 80 can be obtained, and a cut-off of 31–33 was considered indicative of PTSD[ 10 ]. The primary outcome was the proportion of participants who were diagnosed with PCC, as defined by the CDC definition: the presence of ≥ 1 symptom 4 or more weeks after the acute infection, either at entry in the cohort (2–3 months after the acute infection) or at any of the follow-up visits. We also focused on the main symptoms clusters of PCC as previously identified [ 11 , 29 ]: fatigue, respiratory symptoms, brain fog/central nervous symptoms, chronic pain and anosmia/dysgeusia. A list of symptoms included in each PCC phenotype is provided in Supplementary table 1 . This study has been approved by the Ethics Committee Milano Area 1 (n 1869, 01/08/2022) and all patients have signed an informed consent. Statistical analyses Categorical variables are presented as absolute numbers and percentages, quantitative variables as median and interquartile range (IQR). The proportion of patients diagnosed with PCC and the main PCC phenotypes at each time point have been compared by Chi-square test. Among patients with at least two follow up examinations, we compared those who had never experienced PCC, those who resolved PCC, and those with persistent PCC at the last available follow-up using Chi-square test and non-parametric Kruskal-Wallis test. For patients diagnosed with PCC at the first follow-up (2–3 months post-acute phase), we examined factors associated with the persistence of PCC versus its resolution using Chi-square test and non-parametric Mann-Whitney test. Finally, by fitting a multivariable logistic regression analysis adjusted for possible confounders, we explored factors associated with ongoing PCC at the last available follow-up in comparison to those who had never experienced PCC or had recovered from it. Statistical analyses were performed by SPSS (version 29) and STATA software (version 14). Results Study population Three medical evaluations were conducted in total (Figure 1). Patients were evaluated at 2-3 months after the acute phase and then followed up at 6-10 months and more than 12 months. Initially, 853 patients underwent a first follow-up assessment at 3 months post-acute phase (IQR 2-3), and thus were included in our study. The median age was 62 years (IQR 52-73), with the majority being men (59% males, 41% females). Most patients were evaluated in 2020 and 2021 (66.7% and 19.3% respectively); accordingly, only 12.5% of the cohort had been vaccinated before SARS CoV-2 infection. The cohort includes 766 hospitalized COVID-19 patients (89.8%) and a smaller subset of individuals (87, 10.2%) who experienced a mild acute illness and were not hospitalized. Regarding disease severity during the acute phase, approximately one third of patients received treatment with a reservoir mask (RM), high-flow nasal cannula (HFNC), or continuous positive airway pressure (CPAP), while 8% of patients required admission to the intensive care unit (ICU) (Table 1). Of 853 patients, 418 individuals (49%) also completed follow-up evaluations at 7 months (IQR 6-10); 69 patients (17%) were followed up at a median of 26 months (IQR 20-33). 26/853 (3%), 218/418 (52%) and 58/59 (84%) evaluations were performed by telemedicine. The missing patients included those who were lost to follow-up (18 at the second follow-up visit, 157 at the third), those with ongoing scheduled appointments, or those yet to be contacted to schedule a visit. Additionally, 3 patients (0.35%) died after the first evaluation. PCC and main phenotypes over time Interestingly, we observed a reduction in the proportion of symptomatic patients over time: PCC was present in 551 out of 853 patients (64.6%) at the first medical evaluation; at the second visit, 152 out of 418 patients (36.4%) still had PCC symptoms, and finally, PCC persisted in 21 out of 69 patients (30.4%) at the third medical evaluation (p<0.001). In our cohort of patients, we identified five main clinical phenotypes of PCC: fatigue, respiratory sequelae, brain fog, chronic pain and anosmia/dysgeusia (table 2). The clinical presentation of PCC varied through time: while anosmia/dysgeusia was the most prominent symptom at the first follow-up (211/551 patients, 38.3%), it became less common at the second evaluation and was present in only 1/21 PCC patients (4.8%) at the third follow up, making it the less represented symptom cluster in the long term. Fatigue and respiratory symptoms were present in approximately 1 in 4 patients (123/551, 22.3% and 143/551, 25.9% of patients, respectively) at the first follow up visit. The frequency of these symptoms increased with each subsequent evaluation. For fatigue, it was present in 62 out of 152 cases (40.7%) at the second visit and in 13 out of 21 cases (61.9%) at the third visit. Similarly, respiratory sequelae were found in 75 out of 152 cases (49.3%) at the second visit and in 11 out of 21 cases (52.4%) at the third visit, making them the most common manifestations of PCC after long-term follow-up. The percentage of PCC patients suffering from chronic pain and brain fog, which were fairly uncommon manifestations 3 months after the acute phase (49/551, 8.9% and 29/551, 5.3% respectively), increased significantly at the last evaluation (10/21, 47.6% and 5/21, 23.8%). Comparison among patients who had never had PCC, patients who had recovered from PCC and patients with ongoing PCC A total of 418 patients, representing 49% of the initial 853-patient cohort, underwent a second medical evaluation. Subsequently, we proceeded to compare patients who had never developed PCC, patients who had recovered from PCC symptoms, and patients with persistent PCC at the last available follow-up (Table 3). Female sex, having had the acute infection in 2020, a longer hospital stay, and lack of COVID-19 vaccination were positively associated with PCC (either persistent or resolved) when compared to patients who never developed PCC. Additionally, psychological symptoms such as anxiety, depression, and PTSD were more common among patients with PCC, with PTSD reaching statistical significance. Notably, no statistically significant association was found between PCC and other commonly cited risk factors in current literature, such as obesity, the number of preexisting comorbidities and the maximum grade of oxygen therapy during the acute phase. Comparison between patients with resolved PCC and ongoing PCC We also analyzed a total of 308 patients who were diagnosed with PCC at the entry in the cohort and had at least two follow-up visits. Among these, 198/308 (64.3%) no longer had PCC symptoms at subsequent evaluations, while 110/308 (35.7%) had persistent PCC at a median follow up of 8 months (IQR 6-15) (table 4). We compared these two groups to identify factors associated with PCC persistence over time. We observed that female sex and lack of COVID-19 vaccination were positively associated with PCC persistence. Additionally, while not reaching statistical significance, psychological symptoms such as anxiety, depression, and PTSD were also observed more frequently in patients with persistent PCC. Factors associated with PCC persistence over time Finally, we examined factors associated with ongoing PCC (compared to those who never had PCC or had resolved symptoms at the last available follow-up) using logistic regression analysis. Having had acute SARS CoV-2 infection in 2020 remained independently associated with persistent PCC, even after adjusting for age, sex, preexisting comorbidities, and the severity of acute disease (AOR 0.479 for 2021 vs 2020, 95%CI 0.253-0.908, p=0.024; AOR 0.771 for 2022 vs 2020, 95%CI 0.259-2.297, p=0.641; AOR 0.086 for 2023 vs 2020, 95%CI 0.086-3.830, p=0.565). Discussion In our cohort, primarily consisting of unvaccinated, hospitalized patients and a smaller sample of outpatients during the early stages of the pandemic, we observed a reduction in the percentage of PCC over the follow-up period. According to the CDC definition [ 1 ], over two-thirds of patients exhibited PCC symptoms at the initial 2–3-month follow-up, a proportion that decreased progressively with subsequent visits, with one-third of patients still experiencing PCC at a long follow- up of 2 years or more. While anosmia/dysgeusia is prevalent in the first post-acute period, fatigue, respiratory sequelae, and to a lesser extent, brain fog emerged as the predominant long-term PCC phenotypes, in accordance with what described in other cohorts [ 30 – 33 ]. Similar data have already been published showing a reduction of ear, nose and throat (ENT) symptoms over time but a possible long-term persistence of chronic fatigue [ 3 , 34 , 35 ]. Fatigue, observed in half of our patients, shares several similarities with myalgic encephalomyelitis [ 36 ], a condition that follows several infections, defined by chronic fatigue that lasts at least six months and is associated with brain fog, sleep disorders, post-exertional malaise and orthostatic intolerance [ 37 , 38 ]. Similar to PCC, the diagnosis of myalgic encephalomyelitis is primarily clinical and requires the exclusion of differential diagnoses. Thus far, the pathogenetic mechanisms of myalgic encephalomyelitis remain poorly understood, and there is no specific treatment available apart from cognitive and motor rehabilitation therapies, which have been extensively studied [ 39 ]. Due to the overlap in symptoms and therapeutic approaches, myalgic encephalomyelitis is now acknowledged as one of the potential manifestations of PCC. Accurate identification and management of these patients could significantly improve their quality of life [ 40 ]. While these findings underscore the ongoing significance of PCC, with potentially millions of people still suffering from it, delineating whether these symptoms are exclusively attributable to long COVID remains complex [ 23 , 41 ]. While certain manifestations may have a clear correlation with acute SARS-CoV-2 infection in the early post-acute phase, numerous confounding factors may emerge over time. For example, factors such as fatigue, cognitive difficulties, and anxiety tend to increase with age, as do comorbidities. This complicates the attribution of PCC outcomes solely to the viral infection rather than to other ensuing concomitant factors. Moreover, many PCC symptoms closely resemble those of other post-viral syndromes and poorly defined conditions like chronic fatigue syndrome, underscoring the imperative for a more precise and concise definition of long-term PCC [ 42 ]. Consistent with existing literature, female sex, prolonged hospitalization, and lack of COVID-19 vaccination were positively associated with PCC among patients with at least two follow-up visits [ 13 , 14 , 19 – 21 , 43 – 45 ]. In our unadjusted analysis and in almost all previous studies investigating long COVID, females were characterized by a higher risk of PCC, possibly due to a higher prevalence of psychological issues and/or hormonal factors yet to be understood [ 43 , 46 , 47 ]. A recent study investigated the impact of sex and gender on PCC and found that socio-economic factors, as well as stress levels, income, being females and living alone and lower education, were predictors of PCC and may partially explain the higher incidence of PCC in women [ 12 ]. Even though few of the patients in our cohort had been vaccinated before infection, unvaccinated patients were found to be at higher risk of PCC, as well documented by various observational studies and meta-analyses [ 19 , 20 , 45 ]. We also observed that PCC persists over time, particularly among patients infected in the first waves of the pandemic. This association may partly stem from the psychological toll of lockdown measures, social distancing, and the fear surrounding a novel disease and might also explain the association with psychological issues as well as anxiety, depression and PTSD in the long-term follow up. The reduction in PCC persistence was displayed only for the comparison between the two first calendar period (2021 vs 2020), while we didn’t observe any reduction in most recent years (2022 and 2023) compared to 2020; this could be due to different reasons, including the small sample size mainly in the last years, the possible protective effect of COVID-19 vaccination in reducing the burden of PCC symptoms [ 48 , 49 ], but also the reduction in PCC incidence following the infection with most recent variants. In fact, a reduction of PCC after Omicron infection compared to the Wuhan strain has also been reported by other authors and by other analyses in the EuCARE POSTCOVID study [ 15 , 16 , 50 ]. This study has some limitations. Our study design may introduce a possible selection bias that precludes definitive conclusions regarding PCC incidence rates, as patients returning for follow-up visits inherently have a higher risk of exhibiting PCC symptoms, while many others, who were lost to follow-up, were likely asymptomatic or followed up in other long COVID centers. Similarly, our study fails to definitively ascertain the potential protective effects of vaccines and antiviral therapies, which were introduced after the majority of our patients had already been enrolled. Given that most of our patients were unvaccinated, hospitalized during the acute phase and with mild to moderate symptoms, the generalizability of our findings might be limited. Finally, we haven’t a control group of patients without COVID-19 to be followed up over time to ascertain the incidence of symptoms associated with PCC; this will be the focus of our future Despite these limitations, our data suggest a potential decrease in the burden of PCC over time along with an evolving clinical phenotype, with fatigue and respiratory sequelae emerging prominently, alongside, albeit to a lesser extent, anxiety and depression-related symptoms. This underscores the potential role of psychological support in managing these patients and highlights the necessity for further long-term investigations. Declarations Acknowledgements We are thankful to all the patients who participated in the study and their families. We would like to thank all the staff of the Clinic of Infectious Diseases and Tropical Medicine, San Paolo Hospital, ASST Santi Paolo e Carlo, Department of Health Sciences, University of Milan who cared for the patients and all the colleagues involved in the EuCARE project. The preliminary results have been submitted as abstract at the 16 th Italian Conference on AIDS and Antiviral Research (ICAR). Funding This research received the contribution of the EuCARE Project funded by the European Union´s Horizon Europe Research and Innovation Programme under Grant Agreement No 101046016. Author contribution GM and FB developed the question research and the study protocol. AS, FB and MS helped with patients’ recruitment. JFM, CCM, ASL, MMS, FCS, MI, DJ, ES, AA, CT, JARQ, CM, IF and FI participated in EuCARE POSTCOVID study. LB, KP, EV helped in psychological tests and interpretation. AS, FB, MG, RR and GM helped in analyzing and interpreting the data. AS, FB, and GM contributed to the final data interpretation and the writing of the manuscript. All authors contributed to the editing of the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate The study will be conducted in accordance with the Declaration of Helsinki, ICH-GCP, and relevant national legal and regulatory requirements. The Ethics Committee Area A Milan and the Ethics Committee at each clinical research site have approved the study protocol, informed consent forms, and participant information materials before the beginning of the study commences (version 1.1; 08/02/2022). Each enrolled subjects sign an informed consent for study participation and personal data handling before enrollment. The confidentiality of all study participants will be protected, and all data will be kept confidential and stored in accordance with regulatory laws. Data dissemination will only occur in anonymous form, and personal information will not be released without the patient's written consent. Conflict of interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References CDC: Long-Term Effects of COVID-19. Centers for Disease Control and Prevention. . In . Available at https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects.html; 2020 Nov 13. Soriano JB, Murthy S, Marshall JC, Relan P, Diaz JV, Condition WCCDWGoP-C-: A clinical case definition of post-COVID-19 condition by a Delphi consensus . Lancet Infect Dis 2022, 22 (4):e102-e107. 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Tables Table 1 Study population characteristics Characteristics Study population N 853 Age, median (IQR) 62 (52-73) Females, n (%) 346 (40.6%) Comorbidities, n (%) 323 (37.9%) Obesity, n (%) 151/545 (17.7%) COVID-19 vaccination before infection, n (%) 107 (12.5%) Calendar period, n (%): 2020 2021 2022 2023 569 (66.7%) 165 (19.3%) 97 (11.4%) 22 (2.6%) Setting, n (%): Outpatients Hospital admission 87 (10.2%) 766 (89.8%) Antiviral treatment, n (%): NMV/r RDV mAb N 166 20 (12%) 112 (67.5%) 34 (20.5%) Steroid therapy, n (%) 284/375 (75.7%) Interstitial pneumonia, n (%) 565/643 (87.9%) Oxygen therapy, n (%): None NC/VM RM/HFNC/cPAP NIV/OTI 215 (25.2%) 285 (33.4%) 285 (33.4%) 68 (8%) Legend : Quantitative variables are presented as median and Interquartile Range, categorical variables as absolute numbers and percentages. Comorbidities, at least one comorbidity; obesity, Body Mass Index >30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation. Table 2: PCC phenotypes over time PCC 1 st follow up N 551 PCC 2 nd follow up N 152 PCC 3 rd follow up N 21 p values PCC phenotypes: Fatigue 123 (22.3%) 62 (40.7%) 13 (61.9%) <0.001 Respiratory sequelae 143 (25.9%) 75 (49.3%) 11(52.4%) <0.001 Brain fog 29 (5.3%) 48 (31.6%) 5 (23.8%) <0.001 Chronic pain 49 (8.9%) 49 (32.3%) 10 (47.6%) <0.001 Anosmia/Dysgeusia 211 (38.3%) 24 (15.8%) 1 (4.8%) <0.001 Legend : Phenotypes of Post COVID-19 condition: fatigue (fatigue, post exertional malaise; respiratory sequelae: dyspnea, cough, shortness of breath, chest pain; brain fog: headache, cognitive deficits; chronic pain: joint, muscle and bone pain; anosmia/dysgeusia). PCC, Post COVID-19 condition. Table 3: Comparison among patients who had never had PCC, patients with resolved and patients with persistent PCC Characteristics Study population N 418 Never PCC N 82 (19.6%) Resolved PCC N 133 (31.8%) Persistent PCC N 203 (48.6%) p value Age, median (IQR) 59 (52-71) 64 (51-73) 59 (50-68) 60 (53-72) 0.174 Females, n (%) 164 (39.2%) 36 (43.9%) 62 (46.6%) 66 (32.5%) 0.022 Comorbidities, n (%) 146 (34.9%) 27 (32.9%) 48 (36.1%) 71 (35%) 0.894 Obesity, n (%) 92/314 (29%) 10/44 (23%) 27/86 (31%) 55/184 (30%) 0.885 COVID-19 vaccination before infection, n (%) 37/366 (10.1%) 12 (19.7%) 15 (14.2%) 10 (5%) 0.001 Calendar period, n (%): 2020 2021 2022 2023 287 (69%) 98 (23.6%) 24 (5.8%) 7 (1.7%) 32 (39.5%) 39 (48.1%) 8 (9.9%) 2 (2.3%) 73 (55.3%) 44 (33.3%) 12 (9.1%) 3 (2.3%) 182 (89.7%) 15 (7.4%) 4 (2%) 2 (1%) <0.001 Setting, n (%): Outpatients Hospital admission 27 (6.5%) 391 (93.5%) 10 (12.2%) 72 (87.8%) 5 (2.5%) 198 (97.5%) 12 (9%) 121 (91%) 0.004 Lenght of hospital stay, days, median (IQR) 27 (22-36) 18 (7.7-24) 29 (23-35) 28 (21-39) <0.001 Interstitial pneumonia, n (%) 286/324 (88%) 44/53 (83%) 91/101 (90%) 151/170 (89%) 0.409 Oxygen therapy, n (%): None NC/VM RM/HFNC/cPAP NIV/OTI 96 (23%) 143 (34.2%) 151 (36.1%) 28 (6.7%) 24 (29.3%) 25 (30.5%) 31 (37.8%) 2 (2.4%) 30 (22.6%) 43 (32.3%) 49 (36.8%) 11 (8.3%) 42 (20.7%) 75 (36.9%) 71 (35%) 15 (7.4%) 0.444 Months from the acute phase, median (IQR) 8 (6-15) 8 (6-16) 10 (6-21) 7 (6-11) 0.015 HADS/A, n (%) 41/295 (13.9%) 1/28 (3.6%) 20/88 (22.7%) 20/179 (11.2%) 0.009 HADS/D, n (%) 25/293 (8.5%) 1/28 (3.6%) 13/86 (15.1%) 11/179 (6.1%) 0.031 PSTD, n (%) 68/216 (31.5%) 0/18 (0%) 30/66 (45.5%) 38/132 (28.8%) <0.001 Legend : Comparison among patients who had never had PCC, patients with resolved and patients with persistent PCC at the last available follow up. Quantitative data are expressed as median, interquartile range, categorical data as absolute numbers, percentages (p values by Chi-square and Kruskal-Wallis test). PCC, Post COVID-19 condition. Comorbidities, at least one comorbidity; obesity, Body Mass Index >30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation. HADS/A-D, Hospital Anxiety and Depression scale; a score above 11 was considered pathological. PSTD, screening tool for post-traumatic stress disorders (PCL-5, a score above 33 was considered pathological). Table 4 Factors associated with PCC persistence Characteristics Study population N 308 Non PCC N 198 (64.3%) PCC N 110 (35.7%) p value Age, median (IQR) 60 (51-72) 58 (50-68) 61 (53-72) 0.103 Females, n (%) 117 (38%) 62 (31.3%) 55 (50%) 0.001 Comorbidities, n (%) 112 (36.4%) 70 (35.4%) 42 (38.2%) 0.621 Obesity, n (%) 76/255 (29.8%) 53 (29.1%) 23 (31.5%) 0.968 COVID-19 vaccination before infection, n (%) 23/287 (8%) 9/195 (4.6%) 14/92 (15.2%) 0.004 Calendar period, n (%): 2020 2021 2022 2023 251 (81.8%) 39 (12.7%) 13 (4.2%) 5 (1.3%) 181 (91.4%) 12 (6.1%) 3 (1.5%) 3 (1%) 70 (64.2%) 27 (24.8%) 10 (9.2%) 2 (1.8%) <0.001 Setting, n (%): Outpatients Hospital admission 12 (3.9%) 296 (96.1%) 3 (1.5%) 195 (98.5%) 9 (8.2%) 101 (91.8%) 0.004 Interstitial pneumonia, n (%) 226/254 (89%) 148/167 (88.6%) 78/87 (89.7%) 0.803 Oxygen therapy, n (%): None NC/VM RM/HFNC/cPAP NIV/OTI 64 (20.8%) 111 (36%) 107 (34.7%) 26 (8.4%) 40 (20.2%) 74 (37.4%) 69 (34.8%) 15 (7.6%) 24 (21.8%) 37 (33.6%) 38 (34.5%) 11 (10%) 0.836 Months from the acute phase, median (IQR) 8 (6-15) 10 (6-19) 7 (6-11) 0.098 HADS/A, n (%) 39/263 (14.8%) 20/178 (11.2%) 19/85 (22.4%) 0.018 HADS/D, n (%) 23/261 (8.8%) 11 (6.2%) 12 (14.5%) 0.035 PSTD, n (%) 67/195 (34.4%) 38/131 (29%) 29/64 (45.3%) 0.024 Legend: Among patients diagnosed with PCC at entry in the cohort (at the first follow up examination after the acute phase), comparison between patients who resolved PCC and patients with persistent PCC. Quantitative data are expressed as median, interquartile range, categorical data as absolute numbers, percentages (p values by Chi-square and Kruskal-Wallis test). PCC, Post COVID-19 condition. Comorbidities, at least one comorbidity; obesity, Body Mass Index >30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation. HADS/A-D, Hospital Anxiety and Depression scale; a score above 11 was considered pathological. PSTD, screening tool for post-traumatic stress disorders (PCL-5, a score above 33 was considered pathological). Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 27 May, 2024 Editor assigned by journal 27 May, 2024 Submission checks completed at journal 21 May, 2024 First submitted to journal 14 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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13:54:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4419711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4419711/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-025-10805-w","type":"published","date":"2025-04-29T15:57:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57937756,"identity":"41455864-6df9-4049-85ad-6321822b8ec0","added_by":"auto","created_at":"2024-06-07 17:43:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35604,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy flow chart\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegend\u003c/strong\u003e: 843 patients were followed up at 3, 2-3 months after acute COVID-19 disease. Of these, 418 patients were followed up also at 7, IQR 6-10 months and 69 patients also at 26, IQR 20-33 months. Loss to follow up: patients that didn’t keep an appointment or didn’t answer to phone call to schedule next appointments; to be contacted/ongoing: patients with a next scheduled appointment or patients still to be phone contacted. PCC, post COVID-19 condition.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4419711/v1/2cb129138f0d42bc8f6832ad.png"},{"id":81987756,"identity":"e3ce263e-c8c9-4d4d-a6a9-33d995333c41","added_by":"auto","created_at":"2025-05-05 16:05:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3276915,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4419711/v1/bbaefa30-0746-4436-9e6e-63cafe19a5ed.pdf"},{"id":57937755,"identity":"814fb261-a831-49bc-b077-331c75db68c0","added_by":"auto","created_at":"2024-06-07 17:43:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20876,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4419711/v1/47601e7cb3344766506c6a52.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Short and Long-Term Trajectories of the Post COVID-19 Condition: Results from the EuCARE POSTCOVID study","fulltext":[{"header":"Background","content":"\u003cp\u003eLong COVID, also referred to as Post-COVID-19 Condition (PCC), is defined by the Center for Disease Control and Prevention (CDC) as the presence of persisting symptoms four weeks after the acute SARS-CoV-2 infection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is estimated that PCC affects a substantial proportion of patients, ranging from 10\u0026ndash;40%, placing a heavy burden on already stressed health systems [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Symptoms can last for months, with many studies following patients for up to one year since the acute phase, and a few others suggesting symptoms may last even longer [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor the sake of simplicity, symptoms can be grouped in clusters in order to identify different PCC phenotypes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. One study found shortness of breath and chronic fatigue as the most frequent long COVID manifestations, while female sex and severe COVID-19 infection during the acute phase were the main risk factors for developing PCC [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Evidence indicates a decline in PCC incidence following the surge of the Omicron variant compared to the wild-type virus, while incidence was higher with the Alpha and Delta variants [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A follow-up study on long-term outcomes in 242,712 COVID-19 patients showed patients infected with the Omicron variant were 88% less likely to experience lingering symptoms compared to the original viral strain [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Preliminary data suggest a reduction in the risk of developing long-term cardiorespiratory sequelae after Omicron infection compared to the wild-type virus, while neurological symptoms, such as depression and anxiety, continue to be prevalent [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. It is currently unclear how long this condition persists, and whether clinical phenotypes change over time.\u003c/p\u003e \u003cp\u003eMany factors have been associated with PCC development, most notably older age, female sex, the severity of acute infection, and prior comorbidities, while vaccination and antiviral treatment seem to play a protective role [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Several authors have suggested a possible role of psychological factors in the development of PCC, especially during the initial waves of the pandemic (2020\u0026ndash;2021) due to isolation during lockdowns and fear of a new, previously unknown disease [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. One study measured depression and anxiety levels during lockdowns, which resulted to be at quasi-clinical levels [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Evidence for a possible reduction in psychological symptoms with later variants is currently limited.\u003c/p\u003e \u003cp\u003eSince the onset of the ongoing COVID-19 pandemic, healthcare professionals have encountered unprecedented challenges in the management and follow-up of patients. The implementation of lockdown measures, coupled with the surge in patient numbers and the resulting strain on health systems, necessitated novel approaches to follow-up care and the optimization of hospital resources. Additionally, the prevalence of old age and comorbidities, common characteristics in COVID-19 patients, heightened the risk of loss to follow-up. In response to these challenges, new methods of patient re-evaluation, such as telemedicine, have been introduced, benefiting both patients and healthcare providers [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Telemedicine employs audio and/or visual devices to facilitate communication between patients and healthcare professionals.\u003c/p\u003e \u003cp\u003eThis study presents the outcomes of a follow-up program designed for COVID-19 patients from the EuCARE POSTCOVID cohort [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], conducted from January 2020 to June 2023, employing in person evaluations and telemedicine. Our aim was to examine the trajectories of PCC and clinical outcomes over time, as well as to identify potential factors associated with PCC persistence in a cohort of both hospitalized and non-hospitalized patients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThe EuCARE POSTCOVID study is a retrospective and prospective cohort study including patients with at least one follow-up examination at 2\u0026ndash;3, 6\u0026ndash;10 and \u0026ge;\u0026thinsp;12 months after an acute SARS CoV-2 infection. It includes 6 centers in over 3 continents and aims to investigate the long-term outcome of SARS CoV-2 infection; the study protocol has already been described elsewhere [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Patients included in this study have been evaluated at the post COVID service of the Clinic of Infectious Diseases, San Paolo Hospital, ASST Santi Paolo e Carlo, Milan, Italy or by telemedicine from February 2020 to June 2023. We included both hospitalized COVID-19 patients and outpatients with milder disease who were not hospitalized during the acute phase. The study flow chart is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy procedures\u003c/h2\u003e \u003cp\u003eAt each visit, patients underwent blood exams and completed a condensed version of the post-COVID-19 WHO Case Report Form (CRF) to document symptoms. Following the acute phase and/or hospital discharge, we gathered data on persistent symptoms not previously experienced before COVID-19 infection. If any symptoms were reported, we investigated whether they persisted, their frequency, or if they had already resolved. Additionally, patients completed the Hospital Anxiety and Depression Scale (HADS-A/D) to assess symptoms of anxiety and depression and a screening tool for Post-Traumatic Stress Disorder (PTSD).\u003c/p\u003e \u003cp\u003eThe HADS-A/D includes 7 questions each for anxiety and depression. A total HADS score between 8 and 10 indicates \"possible\" cases, while scores of 11 or more denote \"probable\" cases for both anxiety and depression. Scores higher than 10 were utilized to identify symptoms of anxiety and depression. The Post-traumatic Stress Disorder Checklist-5 (PCL-5) is a 20-item self-report measure assessing the 20 DSM-5 symptoms of PTSD, with a 5-point scale for each symptom. A total symptom severity score ranging from 0 to 80 can be obtained, and a cut-off of 31\u0026ndash;33 was considered indicative of PTSD[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary outcome was the proportion of participants who were diagnosed with PCC, as defined by the CDC definition: the presence of \u0026ge;\u0026thinsp;1 symptom 4 or more weeks after the acute infection, either at entry in the cohort (2\u0026ndash;3 months after the acute infection) or at any of the follow-up visits. We also focused on the main symptoms clusters of PCC as previously identified [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]: fatigue, respiratory symptoms, brain fog/central nervous symptoms, chronic pain and anosmia/dysgeusia. A list of symptoms included in each PCC phenotype is provided in Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e This study has been approved by the Ethics Committee Milano Area 1 (n 1869, 01/08/2022) and all patients have signed an informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eCategorical variables are presented as absolute numbers and percentages, quantitative variables as median and interquartile range (IQR). The proportion of patients diagnosed with PCC and the main PCC phenotypes at each time point have been compared by Chi-square test. Among patients with at least two follow up examinations, we compared those who had never experienced PCC, those who resolved PCC, and those with persistent PCC at the last available follow-up using Chi-square test and non-parametric Kruskal-Wallis test. For patients diagnosed with PCC at the first follow-up (2\u0026ndash;3 months post-acute phase), we examined factors associated with the persistence of PCC \u003cem\u003eversus\u003c/em\u003e its resolution using Chi-square test and non-parametric Mann-Whitney test. Finally, by fitting a multivariable logistic regression analysis adjusted for possible confounders, we explored factors associated with ongoing PCC at the last available follow-up in comparison to those who had never experienced PCC or had recovered from it. Statistical analyses were performed by SPSS (version 29) and STATA software (version 14).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eStudy population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThree medical evaluations were conducted in total (Figure 1). Patients were evaluated at 2-3 months after the acute phase and then followed up at 6-10 months and more than 12 months. Initially, 853 patients underwent a first follow-up assessment at 3 months post-acute phase (IQR 2-3), and thus were included in our study. The median age was 62 years (IQR 52-73), with the majority being men (59% males, 41% females). Most patients were evaluated in 2020 and 2021 (66.7% and 19.3% respectively); accordingly, only 12.5% of the cohort had been vaccinated before SARS CoV-2 infection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe cohort includes 766 hospitalized COVID-19 patients (89.8%) and a smaller subset of individuals (87, 10.2%) who experienced a mild acute illness and were not hospitalized. Regarding disease severity during the acute phase, approximately one third of patients received treatment with a reservoir mask (RM), high-flow nasal cannula (HFNC), or continuous positive airway pressure (CPAP), while 8% of patients required admission to the intensive care unit (ICU) (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf 853 patients, 418 individuals (49%) also completed follow-up evaluations at 7 months (IQR 6-10); 69 patients (17%) were followed up at a median of 26 months (IQR 20-33). 26/853 (3%), 218/418 (52%) and 58/59 (84%) evaluations were performed by telemedicine. The missing patients included those who were lost to follow-up (18 at the second follow-up visit, 157 at the third), those with ongoing scheduled appointments, or those yet to be contacted to schedule a visit. Additionally, 3 patients (0.35%) died after the first evaluation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePCC and main phenotypes over time\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInterestingly, we observed a reduction in the proportion of symptomatic patients over time: PCC was present in 551 out of 853 patients (64.6%) at the first medical evaluation; at the second visit, 152 out of 418 patients (36.4%) still had PCC symptoms, and finally, PCC persisted in 21 out of 69 patients (30.4%) at the third medical evaluation (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eIn our cohort of patients, we identified five main clinical phenotypes of PCC: fatigue, respiratory sequelae, brain fog, chronic pain and anosmia/dysgeusia (table 2). The clinical presentation of PCC varied through time: while anosmia/dysgeusia was the most prominent symptom at the first follow-up (211/551 patients, 38.3%), it became less common at the second evaluation and was present in only 1/21 PCC patients (4.8%) at the third follow up, making it the less represented symptom cluster in the long term.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFatigue and respiratory symptoms were present in approximately 1 in 4 patients (123/551, 22.3% and 143/551, 25.9% of patients, respectively) at the first follow up visit. The frequency of these symptoms increased with each subsequent evaluation. For fatigue, it was present in 62 out of 152 cases (40.7%) at the second visit and in 13 out of 21 cases (61.9%) at the third visit. Similarly, respiratory sequelae were found in 75 out of 152 cases (49.3%) at the second visit and in 11 out of 21 cases (52.4%) at the third visit, making them the most common manifestations of PCC after long-term follow-up. The percentage of PCC patients suffering from chronic pain and brain fog, which were fairly uncommon manifestations 3 months after the acute phase (49/551, 8.9% and 29/551, 5.3% respectively), increased significantly at the last evaluation (10/21, 47.6% and 5/21, 23.8%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison among patients who had never had PCC, patients who had recovered from PCC and patients with ongoing PCC\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 418 patients, representing 49% of the initial 853-patient cohort, underwent a second medical evaluation. Subsequently, we proceeded to compare patients who had never developed PCC, patients who had recovered from PCC symptoms, and patients with persistent PCC at the last available follow-up (Table 3).\u003c/p\u003e\n\u003cp\u003eFemale sex, having had the acute infection in 2020, a longer hospital stay, and lack of COVID-19 vaccination were positively associated with PCC (either persistent or resolved) when compared to patients who never developed PCC. Additionally, psychological symptoms such as anxiety, depression, and PTSD were more common among patients with PCC, with PTSD reaching statistical significance.\u003c/p\u003e\n\u003cp\u003eNotably, no statistically significant association was found between PCC and other commonly cited risk factors in current literature, such as obesity, the number of preexisting comorbidities and the maximum grade of oxygen therapy during the acute phase.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparison between patients with resolved PCC and ongoing PCC\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe also analyzed a total of 308 patients who were diagnosed with PCC at the entry in the cohort and had at least two follow-up visits. Among these, 198/308 (64.3%) no longer had PCC symptoms at subsequent evaluations, while 110/308 (35.7%) had persistent PCC at a median follow up of 8 months (IQR 6-15) (table 4). We compared these two groups to identify factors associated with PCC persistence over time. We observed that female sex and lack of COVID-19 vaccination were positively associated with PCC persistence. Additionally, while not reaching statistical significance, psychological symptoms such as anxiety, depression, and PTSD were also observed more frequently in patients with persistent PCC.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFactors associated with PCC persistence over time\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFinally, we examined factors associated with ongoing PCC (compared to those who never had PCC or had resolved symptoms at the last available follow-up) using logistic regression analysis. Having had acute SARS CoV-2 infection in 2020 remained independently associated with persistent PCC, even after adjusting for age, sex, preexisting comorbidities, and the severity of acute disease (AOR 0.479 for 2021 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.253-0.908, p=0.024; AOR 0.771 for 2022 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.259-2.297, p=0.641; AOR 0.086 for 2023 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.086-3.830, p=0.565).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our cohort, primarily consisting of unvaccinated, hospitalized patients and a smaller sample of outpatients during the early stages of the pandemic, we observed a reduction in the percentage of PCC over the follow-up period. According to the CDC definition [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], over two-thirds of patients exhibited PCC symptoms at the initial 2\u0026ndash;3-month follow-up, a proportion that decreased progressively with subsequent visits, with one-third of patients still experiencing PCC at a long follow- up of 2 years or more.\u003c/p\u003e \u003cp\u003eWhile anosmia/dysgeusia is prevalent in the first post-acute period, fatigue, respiratory sequelae, and to a lesser extent, brain fog emerged as the predominant long-term PCC phenotypes, in accordance with what described in other cohorts [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Similar data have already been published showing a reduction of ear, nose and throat (ENT) symptoms over time but a possible long-term persistence of chronic fatigue [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Fatigue, observed in half of our patients, shares several similarities with myalgic encephalomyelitis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], a condition that follows several infections, defined by chronic fatigue that lasts at least six months and is associated with brain fog, sleep disorders, post-exertional malaise and orthostatic intolerance [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilar to PCC, the diagnosis of myalgic encephalomyelitis is primarily clinical and requires the exclusion of differential diagnoses. Thus far, the pathogenetic mechanisms of myalgic encephalomyelitis remain poorly understood, and there is no specific treatment available apart from cognitive and motor rehabilitation therapies, which have been extensively studied [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Due to the overlap in symptoms and therapeutic approaches, myalgic encephalomyelitis is now acknowledged as one of the potential manifestations of PCC. Accurate identification and management of these patients could significantly improve their quality of life [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile these findings underscore the ongoing significance of PCC, with potentially millions of people still suffering from it, delineating whether these symptoms are exclusively attributable to long COVID remains complex [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. While certain manifestations may have a clear correlation with acute SARS-CoV-2 infection in the early post-acute phase, numerous confounding factors may emerge over time. For example, factors such as fatigue, cognitive difficulties, and anxiety tend to increase with age, as do comorbidities. This complicates the attribution of PCC outcomes solely to the viral infection rather than to other ensuing concomitant factors. Moreover, many PCC symptoms closely resemble those of other post-viral syndromes and poorly defined conditions like chronic fatigue syndrome, underscoring the imperative for a more precise and concise definition of long-term PCC [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with existing literature, female sex, prolonged hospitalization, and lack of COVID-19 vaccination were positively associated with PCC among patients with at least two follow-up visits [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In our unadjusted analysis and in almost all previous studies investigating long COVID, females were characterized by a higher risk of PCC, possibly due to a higher prevalence of psychological issues and/or hormonal factors yet to be understood [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. A recent study investigated the impact of sex and gender on PCC and found that socio-economic factors, as well as stress levels, income, being females and living alone and lower education, were predictors of PCC and may partially explain the higher incidence of PCC in women [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEven though few of the patients in our cohort had been vaccinated before infection, unvaccinated patients were found to be at higher risk of PCC, as well documented by various observational studies and meta-analyses [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also observed that PCC persists over time, particularly among patients infected in the first waves of the pandemic. This association may partly stem from the psychological toll of lockdown measures, social distancing, and the fear surrounding a novel disease and might also explain the association with psychological issues as well as anxiety, depression and PTSD in the long-term follow up. The reduction in PCC persistence was displayed only for the comparison between the two first calendar period (2021 vs 2020), while we didn\u0026rsquo;t observe any reduction in most recent years (2022 and 2023) compared to 2020; this could be due to different reasons, including the small sample size mainly in the last years, the possible protective effect of COVID-19 vaccination in reducing the burden of PCC symptoms [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], but also the reduction in PCC incidence following the infection with most recent variants. In fact, a reduction of PCC after Omicron infection compared to the Wuhan strain has also been reported by other authors and by other analyses in the EuCARE POSTCOVID study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has some limitations. Our study design may introduce a possible selection bias that precludes definitive conclusions regarding PCC incidence rates, as patients returning for follow-up visits inherently have a higher risk of exhibiting PCC symptoms, while many others, who were lost to follow-up, were likely asymptomatic or followed up in other long COVID centers. Similarly, our study fails to definitively ascertain the potential protective effects of vaccines and antiviral therapies, which were introduced after the majority of our patients had already been enrolled. Given that most of our patients were unvaccinated, hospitalized during the acute phase and with mild to moderate symptoms, the generalizability of our findings might be limited. Finally, we haven\u0026rsquo;t a control group of patients without COVID-19 to be followed up over time to ascertain the incidence of symptoms associated with PCC; this will be the focus of our future\u003c/p\u003e \u003cp\u003eDespite these limitations, our data suggest a potential decrease in the burden of PCC over time along with an evolving clinical phenotype, with fatigue and respiratory sequelae emerging prominently, alongside, albeit to a lesser extent, anxiety and depression-related symptoms. This underscores the potential role of psychological support in managing these patients and highlights the necessity for further long-term investigations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are thankful to all the patients who participated in the study and their families. We would like to thank all the staff of the Clinic of Infectious Diseases and Tropical Medicine, San Paolo Hospital, ASST Santi Paolo e Carlo, Department of Health Sciences, University of Milan who cared for the patients and all the colleagues involved in the EuCARE project. The preliminary results have been submitted as abstract at the 16\u003csup\u003eth\u003c/sup\u003e Italian Conference on AIDS and Antiviral Research (ICAR).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received the contribution of the EuCARE Project funded by the European Union\u0026acute;s Horizon Europe Research and Innovation Programme under Grant Agreement No 101046016.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGM and FB developed the question research and the study protocol. AS, FB and MS helped with patients\u0026rsquo; recruitment. JFM, CCM, ASL, MMS, FCS, MI, DJ, ES, AA, CT, JARQ, CM, IF and FI participated in EuCARE POSTCOVID study. LB, KP, EV helped in psychological tests and interpretation. AS, FB, MG, RR and GM helped in analyzing and interpreting the data. AS, FB, and GM contributed to the final data interpretation and the writing of the manuscript. All authors contributed to the editing of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study will be conducted in accordance with the Declaration of Helsinki, ICH-GCP, and relevant national legal and regulatory requirements. The Ethics Committee Area A Milan and the Ethics Committee at each clinical research site have approved the study protocol, informed consent forms, and participant information materials before the beginning of the study commences (version 1.1; 08/02/2022). Each enrolled subjects sign an informed consent for study participation and personal data handling before enrollment. The confidentiality of all study participants will be protected, and all data will be kept confidential and stored in accordance with regulatory laws. Data dissemination will only occur in anonymous form, and personal information will not be released without the patient\u0026apos;s written consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCDC: \u003cstrong\u003eLong-Term Effects of COVID-19. 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Vincenzo JD, Gill H, Subramaniapillai M, Lui LMW, Cao B, Mansur RB, Ho RC\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eCOVID-19 vaccination for the prevention and treatment of long COVID: A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eBrain Behav Immun \u003c/em\u003e2023, \u003cstrong\u003e111\u003c/strong\u003e:211-229.\u003c/li\u003e\n\u003cli\u003eAzzolini E, Levi R, Sarti R, Pozzi C, Mollura M, Mantovani A, Rescigno M: \u003cstrong\u003eAssociation Between BNT162b2 Vaccination and Long COVID After Infections Not Requiring Hospitalization in Health Care Workers\u003c/strong\u003e. \u003cem\u003eJAMA \u003c/em\u003e2022, \u003cstrong\u003e328\u003c/strong\u003e(7):676-678.\u003c/li\u003e\n\u003cli\u003eHedberg P, Naucl\u0026eacute;r P: \u003cstrong\u003ePost-COVID-19 Condition After SARS-CoV-2 Infections During the Omicron Surge vs the Delta, Alpha, and Wild Type Periods in Stockholm, Sweden\u003c/strong\u003e. \u003cem\u003eJ Infect Dis \u003c/em\u003e2024, \u003cstrong\u003e229\u003c/strong\u003e(1):133-136.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Study population characteristics\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 853\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e62 (52-73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eFemales, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e346 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e323 (37.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eObesity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e151/545 (17.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 vaccination before infection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e107 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eCalendar period, n (%):\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e569 (66.7%)\u003c/p\u003e\n \u003cp\u003e165 (19.3%)\u003c/p\u003e\n \u003cp\u003e97 (11.4%)\u003c/p\u003e\n \u003cp\u003e22 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eSetting, n (%):\u003c/p\u003e\n \u003cp\u003eOutpatients\u003c/p\u003e\n \u003cp\u003eHospital admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e87 (10.2%)\u003c/p\u003e\n \u003cp\u003e766 (89.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eAntiviral treatment, n (%):\u003c/p\u003e\n \u003cp\u003eNMV/r\u003c/p\u003e\n \u003cp\u003eRDV\u003cbr\u003e\u0026nbsp;mAb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003eN 166\u003c/p\u003e\n \u003cp\u003e20 (12%)\u003c/p\u003e\n \u003cp\u003e112 (67.5%)\u003c/p\u003e\n \u003cp\u003e34 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eSteroid therapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e284/375 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eInterstitial pneumonia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e565/643 (87.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.63636363636363%\" valign=\"top\"\u003e\n \u003cp\u003eOxygen therapy, n (%):\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eNC/VM\u003c/p\u003e\n \u003cp\u003eRM/HFNC/cPAP\u003c/p\u003e\n \u003cp\u003eNIV/OTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.36363636363637%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e215 (25.2%)\u003c/p\u003e\n \u003cp\u003e285 (33.4%)\u003c/p\u003e\n \u003cp\u003e285 (33.4%)\u003c/p\u003e\n \u003cp\u003e68 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLegend\u003c/strong\u003e: Quantitative variables are presented as median and Interquartile Range, categorical variables as absolute numbers and percentages.\u003c/p\u003e\n\u003cp\u003eComorbidities, at least one comorbidity; obesity, Body Mass Index \u0026gt;30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: PCC phenotypes over time\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC 1\u003csup\u003est\u003c/sup\u003e follow up\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 551\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC 2\u003csup\u003end\u003c/sup\u003e follow up N 152\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC 3\u003csup\u003erd\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;follow up N 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC phenotypes:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e123 (22.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e62 (40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e13 (61.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory sequelae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e143 (25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e75 (49.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e11(52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003eBrain fog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e29 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e48 (31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003eChronic pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e49 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e49 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e10 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.24922118380062%\" valign=\"top\"\u003e\n \u003cp\u003eAnosmia/Dysgeusia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e211 (38.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e24 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e1 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937694704049843%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLegend\u003c/strong\u003e: Phenotypes of Post COVID-19 condition: fatigue (fatigue, post exertional malaise; respiratory sequelae: dyspnea, cough, shortness of breath, chest pain; brain fog: headache, cognitive deficits; chronic pain: joint, muscle and bone pain; anosmia/dysgeusia).\u003c/p\u003e\n\u003cp\u003ePCC, Post COVID-19 condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Comparison among patients who had never had PCC, patients with resolved and patients with persistent PCC\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 418\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever PCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 82 (19.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResolved\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 133 (31.8%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersistent PCC\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 203 (48.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e59 (52-71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e64 (51-73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e59 (50-68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e60 (53-72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eFemales, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e164 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e36 (43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e62 (46.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e66 (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e146 (34.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e27 (32.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e48 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e71 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eObesity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e92/314 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e10/44 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e27/86 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e55/184 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 vaccination before infection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e37/366 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e12 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e15 (14.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e10 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eCalendar period, n (%):\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e287 (69%)\u003c/p\u003e\n \u003cp\u003e98 (23.6%)\u003c/p\u003e\n \u003cp\u003e24 (5.8%)\u003c/p\u003e\n \u003cp\u003e7 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (39.5%)\u003c/p\u003e\n \u003cp\u003e39 (48.1%)\u003c/p\u003e\n \u003cp\u003e8 (9.9%)\u003c/p\u003e\n \u003cp\u003e2 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73 (55.3%)\u003c/p\u003e\n \u003cp\u003e44 (33.3%)\u003c/p\u003e\n \u003cp\u003e12 (9.1%)\u003c/p\u003e\n \u003cp\u003e3 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e182 (89.7%)\u003c/p\u003e\n \u003cp\u003e15 (7.4%)\u003c/p\u003e\n \u003cp\u003e4 (2%)\u003c/p\u003e\n \u003cp\u003e2 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eSetting, n (%):\u003c/p\u003e\n \u003cp\u003eOutpatients\u003c/p\u003e\n \u003cp\u003eHospital admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (6.5%)\u003c/p\u003e\n \u003cp\u003e391 (93.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (12.2%)\u003c/p\u003e\n \u003cp\u003e72 (87.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5 (2.5%)\u003c/p\u003e\n \u003cp\u003e198 (97.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e12 (9%)\u003c/p\u003e\n \u003cp\u003e121 (91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eLenght of hospital stay, days, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e27 (22-36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.7-24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e29 (23-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e28 (21-39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eInterstitial pneumonia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e286/324 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e44/53 (83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e91/101 (90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e151/170 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eOxygen therapy, n (%):\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eNC/VM\u003c/p\u003e\n \u003cp\u003eRM/HFNC/cPAP\u003c/p\u003e\n \u003cp\u003eNIV/OTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e96 (23%)\u003c/p\u003e\n \u003cp\u003e143 (34.2%)\u003c/p\u003e\n \u003cp\u003e151 (36.1%)\u003c/p\u003e\n \u003cp\u003e28 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24 (29.3%)\u003c/p\u003e\n \u003cp\u003e25 (30.5%)\u003c/p\u003e\n \u003cp\u003e31 (37.8%)\u003c/p\u003e\n \u003cp\u003e2 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30 (22.6%)\u003c/p\u003e\n \u003cp\u003e43 (32.3%)\u003c/p\u003e\n \u003cp\u003e49 (36.8%)\u003c/p\u003e\n \u003cp\u003e11 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42 (20.7%)\u003c/p\u003e\n \u003cp\u003e75 (36.9%)\u003c/p\u003e\n \u003cp\u003e71 (35%)\u003c/p\u003e\n \u003cp\u003e15 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eMonths from the acute phase, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e8 (6-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e8 (6-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e10 (6-21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e7 (6-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eHADS/A, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e41/295 (13.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e1/28 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e20/88 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e20/179 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003eHADS/D, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e25/293 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e1/28 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e13/86 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e11/179 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.92511700468019%\" valign=\"top\"\u003e\n \u003cp\u003ePSTD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e68/216 (31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.664586583463338%\" valign=\"top\"\u003e\n \u003cp\u003e0/18 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e30/66 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.224648985959437%\" valign=\"top\"\u003e\n \u003cp\u003e38/132 (28.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.736349453978159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLegend\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eComparison among patients who had never had PCC, patients with resolved and patients with persistent PCC\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eat the last available follow up.\u003c/p\u003e\n\u003cp\u003eQuantitative data are expressed as median, interquartile range, categorical data as absolute numbers, percentages (p values by Chi-square and Kruskal-Wallis test).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCC, Post COVID-19 condition.\u003c/p\u003e\n\u003cp\u003eComorbidities, at least one comorbidity; obesity, Body Mass Index \u0026gt;30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation.\u0026nbsp;HADS/A-D, Hospital Anxiety and Depression scale; a score above 11 was considered pathological. PSTD, screening tool for post-traumatic stress disorders (PCL-5, a score above 33 was considered pathological).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Factors associated with PCC persistence\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 308\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon PCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 198 (64.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN 110 (35.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e60 (51-72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e58 (50-68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e61 (53-72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eFemales, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e117 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e62 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e55 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e112 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e70 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e42 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.621\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eObesity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e76/255 (29.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e53 (29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e23 (31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 vaccination before infection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e23/287 (8%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e9/195 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e14/92 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eCalendar period, n (%):\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e251 (81.8%)\u003c/p\u003e\n \u003cp\u003e39 (12.7%)\u003c/p\u003e\n \u003cp\u003e13 (4.2%)\u003c/p\u003e\n \u003cp\u003e5 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e181 (91.4%)\u003c/p\u003e\n \u003cp\u003e12 (6.1%)\u003c/p\u003e\n \u003cp\u003e3 (1.5%)\u003c/p\u003e\n \u003cp\u003e3 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e70 (64.2%)\u003c/p\u003e\n \u003cp\u003e27 (24.8%)\u003c/p\u003e\n \u003cp\u003e10 (9.2%)\u003c/p\u003e\n \u003cp\u003e2 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eSetting, n (%):\u003c/p\u003e\n \u003cp\u003eOutpatients\u003c/p\u003e\n \u003cp\u003eHospital admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (3.9%)\u003c/p\u003e\n \u003cp\u003e296 (96.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (1.5%)\u003c/p\u003e\n \u003cp\u003e195 (98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9 (8.2%)\u003c/p\u003e\n \u003cp\u003e101 (91.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eInterstitial pneumonia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e226/254 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e148/167 (88.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e78/87 (89.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eOxygen therapy, n (%):\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003cp\u003eNC/VM\u003c/p\u003e\n \u003cp\u003eRM/HFNC/cPAP\u003c/p\u003e\n \u003cp\u003eNIV/OTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64 (20.8%)\u003c/p\u003e\n \u003cp\u003e111 (36%)\u003c/p\u003e\n \u003cp\u003e107 (34.7%)\u003c/p\u003e\n \u003cp\u003e26 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40 (20.2%)\u003c/p\u003e\n \u003cp\u003e74 (37.4%)\u003c/p\u003e\n \u003cp\u003e69 (34.8%)\u003c/p\u003e\n \u003cp\u003e15 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24 (21.8%)\u003c/p\u003e\n \u003cp\u003e37 (33.6%)\u003c/p\u003e\n \u003cp\u003e38 (34.5%)\u003c/p\u003e\n \u003cp\u003e11 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eMonths from the acute phase, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e8 (6-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e10 (6-19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e7 (6-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eHADS/A, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e39/263 (14.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e20/178 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e19/85 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003eHADS/D, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e23/261 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e11 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e12 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.439252336448597%\" valign=\"top\"\u003e\n \u003cp\u003ePSTD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.978193146417446%\" valign=\"top\"\u003e\n \u003cp\u003e67/195 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e38/131 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.757009345794394%\" valign=\"top\"\u003e\n \u003cp\u003e29/64 (45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.068535825545172%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLegend:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong patients diagnosed with PCC at entry in the cohort (at the first follow up examination after the acute phase), comparison between patients who resolved PCC and patients with persistent PCC.\u003c/p\u003e\n\u003cp\u003eQuantitative data are expressed as median, interquartile range, categorical data as absolute numbers, percentages (p values by Chi-square and Kruskal-Wallis test).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCC, Post COVID-19 condition.\u003c/p\u003e\n\u003cp\u003eComorbidities, at least one comorbidity; obesity, Body Mass Index \u0026gt;30; NMV/r: Nirmatrelvir/ritonavir; RDV: Remdesivir; mAB: anti SARS CoV-2 monoclonal antibodies; NC: nasal cannula; MV: Venturi mask; RM: reservoir mask; HFNC: high flows nasal cannula; cPAP: continuous positive airway pressure; NIV: Non invasive ventilation; OTI: orotracheal intubation. HADS/A-D, Hospital Anxiety and Depression scale; a score above 11 was considered pathological. PSTD, screening tool for post-traumatic stress disorders (PCL-5, a score above 33 was considered pathological).\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS CoV-2, long COVID, Post Acute Sequelae of SARS CoV-2, Post COVID-19 condition","lastPublishedDoi":"10.21203/rs.3.rs-4419711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4419711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePost COVID-19 condition (PCC) affects 10\u0026ndash;40% of patients and is characterized by persisting symptoms at \u0026ge;\u0026thinsp;4 weeks after SARS CoV-2 infection. Symptoms can last 7 or even more months. How long PCC persists and any changes in its clinical phenotypes over time require further investigation. We investigated PCC trajectories and factors associated with PCC persistence.\u003c/p\u003e\u003ch2\u003eMaterial and methods\u003c/h2\u003e \u003cp\u003eWe included both hospitalized COVID-19 patients and outpatients from February 2020 to June 2023, who underwent at least one follow-up visit after acute infection at San Paolo Hospital, University of Milan. Follow-up visits were conducted at the post COVID-19 clinic or via telemedicine. During each follow-up examination, patients completed a short version of the WHO CRF for ongoing symptoms, the Hospital Anxiety and Depression Scale (HADS), and a screening tool for Post-Traumatic Stress Disorder (PTSD). Statistical analyses involved Chi-square, Mann-Whitney, Kruskal-Wallis tests, and logistic regression analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe enrolled 853 patients (median age 62, IQR 52\u0026ndash;73; 41% females). 551/853 (64.6%), 152/418 (36.4%) and 21/69 (30.4%) presented PCC at median follow up of 3 (IQR 2\u0026ndash;3), 7 (IQR 6\u0026ndash;10) and 26 (IQR 20\u0026ndash;33) months, respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The main clinical phenotypes were fatigue, respiratory sequelae, brain fog and chronic pain; anosmia/dysgeusia was observed mostly in the first post-acute period. Female sex, acute disease in 2020, a longer hospital stay and no COVID-19 vaccination were associated with persistence or resolution of PCC compared to never having had PCC. Anxiety, depression and PTSD were more common in PCC patients. By fitting a logistic regression analysis, acute infection in 2020 remained independently associated with persistent PCC, adjusting for age, sex, preexisting comorbidities and disease severity (AOR 0.479 for 2021 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.253\u0026ndash;0.908, p\u0026thinsp;=\u0026thinsp;0.024; AOR 0.771 for 2022 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.259\u0026ndash;2.297, p\u0026thinsp;=\u0026thinsp;0.641; AOR 0.086 for 2023 \u003cem\u003evs\u003c/em\u003e 2020, 95%CI 0.086\u0026ndash;3.830, p\u0026thinsp;=\u0026thinsp;0.565).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThere was a reduction in the PCC burden 7 months following the acute phase; still, one third of patients experienced long-lasting symptoms. The main clinical presentations of PCC remain fatigue, respiratory symptoms, brain fog, and chronic pain. Having had SARS CoV-2 infection during the first pandemic phases appears to be associated with persistent PCC.\u003c/p\u003e","manuscriptTitle":"Short and Long-Term Trajectories of the Post COVID-19 Condition: Results from the EuCARE POSTCOVID study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 17:43:05","doi":"10.21203/rs.3.rs-4419711/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-27T07:56:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-27T07:10:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-21T11:28:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-05-14T13:52:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10a27a3a-6e31-4c2a-858a-97303374aec8","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T16:01:18+00:00","versionOfRecord":{"articleIdentity":"rs-4419711","link":"https://doi.org/10.1186/s12879-025-10805-w","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-04-29 15:57:35","publishedOnDateReadable":"April 29th, 2025"},"versionCreatedAt":"2024-06-07 17:43:05","video":"","vorDoi":"10.1186/s12879-025-10805-w","vorDoiUrl":"https://doi.org/10.1186/s12879-025-10805-w","workflowStages":[]},"version":"v1","identity":"rs-4419711","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4419711","identity":"rs-4419711","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}