Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative

Association between acquiring SARS-CoV-2 during pregnancy and post-acute sequelae of SARS-CoV-2 infection: RECOVER electronic health record cohort analysis

Background

Little is known about post-acute sequelae of SARS-CoV-2 infection (PASC) after acquiring SARS-CoV-2 infection during pregnancy. We aimed to evaluate the association between acquiring SARS-CoV-2 during pregnancy compared with acquiring SARS-CoV-2 outside of pregnancy and the development of PASC.

Methods

This retrospective cohort study from the Researching COVID to Enhance Recovery (RECOVER) Initiative Patient-Centred Clinical Research Network (PCORnet) used electronic health record (EHR) data from 19 U.S. health systems. Females aged 18-49 years with lab-confirmed SARS-CoV-2 infection from March 2020 through June 2022 were included. Validated algorithms were used to identify pregnancies with a delivery at >20 weeks' gestation. The primary outcome was PASC, as previously defined by computable phenotype in the adult non-pregnant PCORnet EHR dataset, identified 30-180 days post-SARS-CoV-2 infection. Secondary outcomes were the 24 component diagnoses contributing to the PASC phenotype definition. Univariable comparisons were made for baseline characteristics between individuals with SARS-CoV-2 infection acquired during pregnancy compared with outside of pregnancy. Using inverse probability of treatment weighting to adjust for baseline differences, the association between SARS-CoV-2 infection acquired during pregnancy and the selected outcomes was modelled. The incident risk is reported as the adjusted hazard ratio (aHR) with 95% confidence intervals.

Findings

In total, 83,915 females with SARS-CoV-2 infection acquired outside of pregnancy and 5397 females with SARS-CoV-2 infection acquired during pregnancy were included in analysis. Non-pregnant females with SARS-CoV-2 infection were more likely to be older and have comorbid health conditions. SARS-CoV-2 infection acquired in pregnancy as compared with acquired outside of pregnancy was associated with a lower incidence of PASC (25.5% vs 33.9%; aHR 0.85, 95% CI 0.80-0.91). SARS-CoV-2 infection acquired in pregnant females was associated with increased risk for some PASC component diagnoses including abnormal heartbeat (aHR 1.67, 95% CI 1.43-1.94), abdominal pain (aHR 1.34, 95% CI 1.16-1.55), and thromboembolism (aHR 1.88, 95% CI 1.17-3.04), but decreased risk for other diagnoses including malaise (aHR 0.35, 95% CI 0.27-0.47), pharyngitis (aHR 0.36, 95% CI 0.26-0.48) and cognitive problems (aHR 0.39, 95% CI 0.27-0.56).

Interpretation

SARS-CoV-2 infection acquired during pregnancy was associated with lower risk of development of PASC at 30-180 days after incident SARS-CoV-2 infection in this nationally representative sample. These findings may be used to counsel pregnant and pregnant capable individuals, and direct future prospective study.

Funding

National Institutes of Health (NIH) Other Transaction Agreement (OTA) OT2HL16184.

Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients - A Large-Scale Observational Cohort Study from the RECOVER Initiative

Paxlovid has been approved for use in patients who are at high risk for severe acute COVID-19 illness. Evidence regarding whether Paxlovid protects against Post-Acute Sequelae of SARS-CoV-2 infection (PASC), or Long COVID, is mixed in high-risk patients and lacking in low-risk patients. With a target trial emulation framework, we evaluated the association of Paxlovid treatment within 5 days of SARS-CoV-2 infection with incident Long COVID and hospitalization or death from any cause in the post-acute period (30-180 days after infection) using electronic health records from the Patient-Centered Clinical Research Networks (PCORnet) RECOVER repository. The study population included 497,499 SARS-CoV-2 positive patients between March 1, 2022, to February 1, 2023, and among which 165,256 were treated with Paxlovid within 5 days since infection and 307,922 were not treated with Paxlovid or other COVID-19 treatments. Compared with the non-treated group, Paxlovid treatment was associated with reduced risk of Long COVID with a Hazard Ratio (HR) of 0.88 (95% CI, 0.87 to 0.89) and absolute risk reduction of 2.99 events per 100 persons (95% CI, 2.65 to 3.32). Paxlovid treatment was associated with reduced risk of all-cause death (HR, 0.53, 95% CI 0.46 to 0.60; risk reduction 0.23 events per 100 persons, 95% CI 0.19 to 0.28) and hospitalization (HR, 0.70, 95% CI 0.68 to 0.73; risk reduction 2.37 events per 100 persons, 95% CI 2.19 to 2.56) in the post-acute phase. For those without documented risk factors, the associations (HR, 1.03, 95% CI 0.95 to 1.11; risk increase 0.80 events per 100 persons, 95% CI -0.84 to 2.45) were inconclusive. Overall, high-risk, nonhospitalized adult patients with COVID-19 who were treated with Paxlovid within 5 days of SARS-CoV-2 infection had a lower risk of Long COVID and all-cause hospitalization or death in the post-acute period. However, Long COVID risk reduction with Paxlovid was not observed in low-risk patients.

Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER program

IMPORTANCE

The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant.

OBJECTIVE

To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021.

DESIGN

Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021.

SETTING

Healthcare facilities in New York and Florida.

PARTICIPANTS

Patients who were at least 20 years old and had diagnosis codes that included at least one SARS-CoV-2 viral test during the study period.

EXPOSURE

Laboratory-confirmed COVID-19 infection, classified by the most common variant prevalent in those regions at the time.

MAIN OUTCOME(S) AND MEASURE(S)

Relative risk (estimated by adjusted hazard ratio [aHR]) and absolute risk difference (estimated by adjusted excess burden) of new conditions, defined as new documentation of symptoms or diagnoses, in persons between 31-180 days after a positive COVID-19 test compared to persons without a COVID-19 test or diagnosis during the 31-180 days after the last negative test.

RESULTS

We analyzed data from 560,752 patients. The median age was 57 years; 60.3% were female, 20.0% non-Hispanic Black, and 19.6% Hispanic. During the study period, 57,616 patients had a positive SARS-CoV-2 test; 503,136 did not. For infections during the ancestral strain period, pulmonary fibrosis, edema (excess fluid), and inflammation had the largest aHR, comparing those with a positive test to those without a COVID-19 test or diagnosis (aHR 2.32 [95% CI 2.09 2.57]), and dyspnea (shortness of breath) carried the largest excess burden (47.6 more cases per 1,000 persons). For infections during the Delta period, pulmonary embolism had the largest aHR comparing those with a positive test to a negative test (aHR 2.18 [95% CI 1.57, 3.01]), and abdominal pain carried the largest excess burden (85.3 more cases per 1,000 persons).

CONCLUSIONS AND RELEVANCE

We documented a substantial relative risk of pulmonary embolism and a large absolute risk difference of abdomen-related symptoms after SARS-CoV-2 infection during the Delta variant period. As new SARS-CoV-2 variants emerge, researchers and clinicians should monitor patients for changing symptoms and conditions that develop after infection.

Health-Related Quality of Life for Patients with Post-Acute COVID-19 Syndrome: Identification of Symptom Clusters and Predictors of Long-Term Outcomes

BACKGROUND

Following COVID-19 infection, as many as a third of patients have long-term symptoms, known as post-acute sequelae (PASC). The mechanisms contributing to PASC remain largely unknown and, due to the heterogeneity of symptoms, treating PASC provides unique challenges.

OBJECTIVE

Our study sought to (1) identify clinical symptom profiles based on PROMIS Global Health (GH) items, (2) evaluate demographic and clinical differences across profiles, and (3) identify predictors of change in health-related quality of life (HRQL) over time.

DESIGN

This was an observational cohort study of patients with PASC who completed PROMIS-GH between 2/11/21 and 12/3/21 as part of routine care, with data extracted from the electronic health record.

PARTICIPANTS

There were 1407 adult patients (mean age 49.6 ± 13.7, 73% female, 81% White race) with PASC seen in the recovery clinic between 2/11/21 and 12/3/21, with 1129 (80.2%) completing PROMIS-GH as routine care.

MAIN MEASURES

HRQL was measured with PROMIS-GH at initial visit and after 12 months.

KEY RESULTS

Latent profile analysis identified symptom classes based on five PROMIS-GH items (mental health, ability to carry out physical activities, pain, fatigue, and emotional problems). Four latent profiles were identified: (1) "Poor HRQL" (n = 346), (2) "Mixed HRQL: good mental/poor physical" (n = 232), (3) "Mixed HRQL: poor mental/good physical" (n = 324), and (4) "Good HRQL" (n = 227). Demographics and comorbidities varied significantly across profile with patients with more severe COVID-19 infection more likely to be in profiles 1 and 2. Overall, patients improved 2 T-score points on PROMIS-GH after 12 months, with differences by profile. Predictors of improved HRQL included profile, lower body mass index, and fewer COVID symptoms.

CONCLUSIONS

Patients with PASC have distinct HRQL symptom profiles which were able to differentiate across COVID-19 severity and symptoms. Improvement over 12 months differed by profile. These profiles may be used to better understand the mechanisms behind PASC. Future research should evaluate their ability to guide treatment decisions to improve HRQL.

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis

Background

Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England.

Methods

With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models.

Findings

We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 in men (99.5-102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record.

Interpretation

In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID.

Funding

This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Association between COVID-19 and the Risk of Vascular Dementia: A Mendelian Randomisation Study of the Potential Cognitive Sequela of COVID-19

A growing body of observational studies and Mendelian Randomisation analyses suggest an increased risk of Alzheimer's disease and dementia following COVID-19 infection. However, evidence on the potential association between COVID-19 and vascular dementia, which is plausible given the vascular complications of COVID-19 infection, is still limited. In this study, we conducted a two-sample Mendelian Randomisation analysis to examine the potential causal relationship between COVID-19 phenotypes and the risk of vascular dementia, using summary data from large-scale GWASs. The two-sample Mendelian Randomisation analysis did not detect any significant associations of COVID-19 infection, COVID-19 hospitalisation, or critical COVID-19 with the risk of vascular dementia, with weighted average β values of -0.29 (95% CI: -0.84, 0.26; p = 0.301), -0.12 (95% CI: -0.36, 0.13; p = 0.345), and -0.07 (95% CI: -0.23, 0.09; p = 0.374), respectively. Our findings do not support the hypothesis that vascular dementia is one of the long-term sequelae of COVID-19.

Vaccination and the risk of post-acute sequelae after COVID-19 in the Omicron-predominant period

OBJECTIVES

To assess the association of primary and third doses of vaccination with the risk of post-acute sequelae of COVID-19.

METHODS

This retrospective cohort study utilized a combined database of nationwide health care claims data, COVID-19 patient registry, and vaccination records from South Korea. Individuals diagnosed with COVID-19 in the Omicron variant-dominant period of January-March 2022 were tracked for 30-120 days post-infection. The exposure of interest was the receipt of primary and third doses of the SARS-CoV-2 vaccine. The occurrence of 26 specific conditions in eight domains was compared using Cox regression with inverse probability of treatment weighting.

RESULTS

This study included 394 773 unvaccinated individuals and 7 604 081 individuals receiving ≥2 doses of vaccine. Compared with unvaccinated individuals, vaccination with at least two doses was associated with a reduced risk (adjusted hazard ratio; 95% CI) of several conditions, including ischaemic heart disease (0.73; 0.57-0.94), heart failure (0.55; 0.48-0.63), cardiac dysrhythmia (0.72; 0.61-0.85), cardiac arrest (0.41; 0.33-0.51), pulmonary embolism (0.66; 0.52-0.84), venous thromboembolism (0.54; 0.44-0.66), acute renal failure (0.56; 0.46-0.67), new dialysis (0.45; 0.34-0.59), chronic obstructive pulmonary disease (0.74; 0.65-0.84), acute pancreatitis (0.64; 0.51-0.80), and diabetes (0.82; 0.71-0.95). The risks of heart failure, cardiac dysrhythmias, cardiac arrest, pulmonary embolism, and new dialysis were lower in those who were vaccinated with three doses compared with those who were vaccinated with two doses.

DISCUSSION

Vaccination was associated with a decreased risk of post-acute sequelae of COVID-19, suggesting its potential role in mitigating the indirect impacts of COVID-19.

Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative

Estimates of post-acute sequelae of SARS-CoV-2 infection (PASC) incidence, also known as Long COVID, have varied across studies and changed over time. We estimated PASC incidence among adult and pediatric populations in three nationwide research networks of electronic health records (EHR) participating in the RECOVER Initiative using different classification algorithms (computable phenotypes). Overall, 7% of children and 8.5%-26.4% of adults developed PASC, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 4% in children and ranged from 4-7% among adults, representing a lower-bound incidence estimation based on two control groups - contemporary COVID-19 negative and historical patients (2019). Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Our findings indicate that preventing and mitigating Long COVID remains a public health priority. Examining temporal patterns and risk factors of PASC incidence informs our understanding of etiology and can improve prevention and management.

Social Networks as a Key Health Determinant in Acute Illness Recovery: A Lesson from the COVID-19 Pandemic

BACKGROUND

The COVID-19 pandemic highlighted the importance of considering social determinants of health in health outcomes. Within this spectrum of determinants, social networks garnered attention as the pandemic highlighted the negative effects of social isolation in the context of social distancing measures. Postpandemic, examining the role social networks play in COVID-19 recovery can help guide patient care and shape future health policies. This study aimed to investigate the relationship between social networks and self-rated health change, as well as physical function, in patients recovering from COVID-19 pneumonia.

METHODS

This was a retrospective cohort study utilizing clinical data from 2 New York City hospitals and a 9-month follow-up survey of COVID-19 pneumonia survivors. We evaluated a composite Social Network Score from the 6-item Lubben Social Network Scale and its association with 2 outcomes: 1) self-rated health change and 2) physical function.

RESULTS

A total of 208 patients were included in this study. A 1-point increase in the Social Network Score was associated with greater odds of both same or improved self-rated health change (odds ratio [OR] 1.07, 95% CI 1.02-1.12, P = .01), as well as unimpaired physical function (OR 1.08, 95% CI 1.03-1.14, P < .01).

CONCLUSION

This study emphasized the importance of social networks as a social determinant of health among patients recovering from COVID-19 hospitalization. Targeted interventions to enhance social networks may benefit not only COVID-19 patients but also individuals recovering from other acute illnesses.

EFFECT OF PAXLOVID TREATMENT DURING ACUTE COVID-19 ON LONG COVID ONSET: AN EHR-BASED TARGET TRIAL EMULATION FROM THE N3C AND RECOVER CONSORTIA

Preventing and treating post-acute sequelae of SARS-CoV-2 infection (PASC), commonly known as Long COVID, has become a public health priority. In this study, we examined whether treatment with Paxlovid in the acute phase of COVID-19 helps prevent the onset of PASC. We used electronic health records from the National Covid Cohort Collaborative (N3C) to define a cohort of 426,352 patients who had COVID-19 since April 1, 2022, and were eligible for Paxlovid treatment due to risk for progression to severe COVID-19. We used the target trial emulation (TTE) framework to estimate the effect of Paxlovid treatment on PASC incidence. We estimated overall PASC incidence using a computable phenotype. We also measured the onset of novel cognitive, fatigue, and respiratory symptoms in the post-acute period. Paxlovid treatment did not have a significant effect on overall PASC incidence (relative risk [RR] = 0.98, 95% confidence interval [CI] 0.95-1.01). However, it had a protective effect on cognitive (RR = 0.90, 95% CI 0.84-0.96) and fatigue (RR = 0.95, 95% CI 0.91-0.98) symptom clusters, which suggests that the etiology of these symptoms may be more closely related to viral load than that of respiratory symptoms.

Distinct Type 1 Immune Networks Underlie the Severity of Restrictive Lung Disease after COVID-19

The variable etiology of persistent breathlessness after COVID-19 have confounded efforts to decipher the immunopathology of lung sequelae. Here, we analyzed hundreds of cellular and molecular features in the context of discrete pulmonary phenotypes to define the systemic immune landscape of post-COVID lung disease. Cluster analysis of lung physiology measures highlighted two phenotypes of restrictive lung disease that differed by their impaired diffusion and severity of fibrosis. Machine learning revealed marked CCR5+CD95+ CD8+ T-cell perturbations in mild-to-moderate lung disease, but attenuated T-cell responses hallmarked by elevated CXCL13 in more severe disease. Distinct sets of cells, mediators, and autoantibodies distinguished each restrictive phenotype, and differed from those of patients without significant lung involvement. These differences were reflected in divergent T-cell-based type 1 networks according to severity of lung disease. Our findings, which provide an immunological basis for active lung injury versus advanced disease after COVID-19, might offer new targets for treatment.

Long-term neuropsychiatric sequelae of Delta versus Omicron SARS-CoV-2 infection

OBJECTIVES

Studies have reported increased rates of long-term neuropsychiatric sequelae after SARS-CoV-2 infection using electronic health-record (EHR) data; however, the majority were conducted before Omicron and booster rollout. We estimated the long-term risks and excess burdens of pre-specified new-incident neuropsychiatric diagnoses after Delta versus Omicron BA.1/2 infection in a highly-vaccinated and boosted cohort of adult Singaporeans.

METHODS

The national SARS-CoV-2 testing registry was used to construct cohorts of Singaporean adults infected during periods of Delta and Omicron BA.1/2 predominance and a contemporaneous test-negative control group. New-incident neuropsychiatric diagnoses recorded in the national health care claims database were identified up to 300 days postinfection. Risks and excess burden were estimated using a doubly robust competing-risks survival analysis.

RESULTS

104 179 and 375 903 infected cases were assigned to Delta and Omicron cohorts and compared against test-negative controls (Delta: N = 666 575 and Omicron: N = 619 379). Elevated risk of cognition or memory disorders was consistently reported across Omicron (Adjusted hazards ratio [aHR], 1.24; 95% CI, 1.12-1.38) and Delta cohorts (aHR, 1.63; 95% CI, 1.39-1.92). Delta-variant infection was associated with an increased risk of anosmia or dysgeusia (aHR, 4.53; 95% CI, 2.78-7.41) and psychosis (aHR, 1.65; 95% CI, 1.22-2.22). By contrast, Omicron-variant infection was associated with a risk of abnormal involuntary movements (aHR, 1.93; 95% CI, 1.32-2.83). Risks of neuropsychiatric sequelae predominantly accrued in hospitalized individuals.

DISCUSSIONS

A modestly increased risk of cognition and memory disorders at 300 days after SARS-CoV-2 infection was observed among adult Singaporeans infected during the Delta/Omicron BA.1/2 transmission. There was no overall increased risk of neuropsychiatric sequelae observed across other domains. Variant-specific differences were also observed in individual neuropsychiatric sequelae, including an elevated risk of anosmia or dysgeusia after Delta-variant infection.

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation

In healthcare, machine learning (ML) shows significant potential to augment patient care, improve population health, and streamline healthcare workflows. Realizing its full potential is, however, often hampered by concerns about data privacy, diversity in data sources, and suboptimal utilization of different data modalities. This review studies the utility of cross-cohort cross-category (C4) integration in such contexts: the process of combining information from diverse datasets distributed across distinct, secure sites. We argue that C4 approaches could pave the way for ML models that are both holistic and widely applicable. This paper provides a comprehensive overview of C4 in health care, including its present stage, potential opportunities, and associated challenges.

Reaching out to Patients with Long COVID to Better Understand Their Life Experiences and How to Support Their Recovery: A Patient-Oriented Knowledge Sharing Session

This article reports on participants' experiences with long COVID-19 (LC) (symptoms, impact, healthcare use, and perceived needs) and satisfaction with a patient-oriented knowledge-sharing session organized by a multidisciplinary team of healthcare professionals, researchers, and a patient partner. Twenty-six participants completed a pre-session survey. On average, they were 21 months post-COVID-19 infection (SD 10.9); 81% of them were female, and 84% were 40+ years old. The main symptoms reported included fatigue (96%), cognitive problems (92%), and general pain or discomfort (40%). More than half of the participants reported that LC has had a significant impact on their health-related quality of life. Eighty-one percent of the participants reported seeking medical help for their LC symptoms and found the services provided by physical therapists, primary care providers, and acupuncturists to be helpful in managing their condition. Participants would like to have access to healthcare providers and clinics specializing in LC. They liked the session and found the information presented useful. This information helps to better understand the experiences of people living with LC and how to support their recovery.

Longitudinal NMR-Based Metabolomics Study Reveals How Hospitalized COVID-19 Patients Recover: Evidence of Dyslipidemia and Energy Metabolism Dysregulation

Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), can manifest as long-term symptoms in multiple organ systems, including respiratory, cardiovascular, neurological, and metabolic systems. In patients with severe COVID-19, immune dysregulation is significant, and the relationship between metabolic regulation and immune response is of great interest in determining the pathophysiological mechanisms. We aimed to characterize the metabolomic footprint of recovering severe COVID-19 patients at three consecutive timepoints and compare metabolite levels to controls. Our findings add proof of dysregulated amino acid metabolism in the acute phase and dyslipidemia, glycoprotein level alterations, and energy metabolism disturbances in severe COVID-19 patients 3-4 months post-hospitalization.

Gut Microbiome Composition and Dynamics in Hospitalized COVID-19 Patients and Patients with Post-Acute COVID-19 Syndrome

The gut microbiome plays a pivotal role in the modulation of host responses during viral infections, and recent studies have underscored its significance in the context of coronavirus disease 2019 (COVID-19). We aimed to investigate the dynamics and compositional changes in the gut microbiome of COVID-19 patients, addressing both the acute phase and the recovery process, with a particular focus on the emergence of post-COVID-19 conditions. Involving 146 COVID-19 patients and 110 healthy controls, this study employed a shotgun metagenomics approach for cross-sectional and longitudinal analyses with one- and three-month follow-ups. We observed a decline in taxonomic diversity among hospitalized COVID-19 patients compared to healthy controls, while a subsequent increase in alpha diversity was shown during the recovery process. A notable contribution of Enterococcus faecium was identified in the acute phase of the infection, accompanied by an increasing abundance of butyrate-producing bacteria (e.g., Roseburia, Lachnospiraceae_unclassified) during the recovery period. We highlighted a protective role of the Prevotella genus in the long-term recovery process and suggested a potential significance of population-specificity in the early gut microbiome markers of post-acute COVID-19 syndrome. Our study represents distinctive gut microbiome signatures in COVID-19, with potential diagnostic and prognostic implications, pinpointing potential modulators of the disease progression.