{
    "abstract": "Post-acute sequelae of SARS-CoV-2 infection (PASC) represent a significant challenge in patient care, with symptoms persisting beyond three month's post-recovery. This study aimed to evaluate the incidence of PASC at one year post-COVID-19 and identify predictive biomarkers and comorbidities for effective risk stratification.\nA cohort of 120 adult patients, including 50 intensive care and 70 non-intensive care patients, was followed up at two weeks, six weeks, and one-year post-discharge using structured questionnaires. The study integrated comorbidities and laboratory biomarkers to forecast the risk for PASC.\nThe median age of participants was 56\u00a0years, with 40% having moderate to severe comorbidities. A year post-recovery, 32.8% exhibited post COVID-19 conditions. The most common symptoms were constitutional (16%), respiratory (8.4%), and neuropsychiatric (2.5%). Bayesian network analysis indicated significant correlations between constitutional symptoms, rehospitalisation, and biomarkers including C-reactive protein, lactate-dehydrogenase, ferritin, and albumin.\nThis study highlights the prolonged impact of PASC, one-year post infection. It highlights the role of specific biomarkers such as C-reactive protein, lactate-dehydrogenase, ferritin, and albumin in tailoring individual patient care by advancing understanding in post-COVID-19 symptoms prediction. Our findings support the need for further research to refine these insights, which are pivotal for the ongoing care of patients in the aftermath of COVID-19.",
    "authors": [
        {
            "affiliation": "Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, 682041, India.",
            "firstname": "Chithira V",
            "initials": "CV",
            "lastname": "Nair"
        },
        {
            "affiliation": "Department of Health Sciences Research, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India.",
            "firstname": "Malavika",
            "initials": "M",
            "lastname": "Krishnakumar"
        },
        {
            "affiliation": "Department of Health Sciences Research, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India.",
            "firstname": "Georg",
            "initials": "G",
            "lastname": "Gutjahr"
        },
        {
            "affiliation": "Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, 682041, India.",
            "firstname": "Kiran G",
            "initials": "KG",
            "lastname": "Kulirankal"
        },
        {
            "affiliation": "Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, 682041, India.",
            "firstname": "Merlin",
            "initials": "M",
            "lastname": "Moni"
        },
        {
            "affiliation": "Division of Infectious Diseases, Department of General Medicine, Amrita Institute of Medical Science and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, 682041, India. diputsmck@gmail.com.",
            "firstname": "Dipu T",
            "initials": "DT",
            "lastname": "Sathyapalan"
        }
    ],
    "conclusions": "This study highlights the prolonged impact of PASC, one-year post infection. It highlights the role of specific biomarkers such as C-reactive protein, lactate-dehydrogenase, ferritin, and albumin in tailoring individual patient care by advancing understanding in post-COVID-19 symptoms prediction. Our findings support the need for further research to refine these insights, which are pivotal for the ongoing care of patients in the aftermath of COVID-19.",
    "copyrights": "\u00a9 2025. The Author(s).",
    "doi": "10.1186/s12879-025-10619-w",
    "journal": "BMC infectious diseases",
    "keywords": [
        "Bayesian network",
        "Post-acute sequelae",
        "SARS-CoV-2"
    ],
    "methods": null,
    "publication_date": "2025-03-25",
    "pubmed_id": "40128677\n37278994\n37835106\n36215250\n35961348\n35991464\n35794549\n34586367\n37445634\n36311357\n35818362\n37366496\n36920842\n3558716\n34808527\n33614024\n36744129\n36319840\n37515140\n37814234\n35742722\n36538532",
    "results": "The median age of participants was 56\u00a0years, with 40% having moderate to severe comorbidities. A year post-recovery, 32.8% exhibited post COVID-19 conditions. The most common symptoms were constitutional (16%), respiratory (8.4%), and neuropsychiatric (2.5%). Bayesian network analysis indicated significant correlations between constitutional symptoms, rehospitalisation, and biomarkers including C-reactive protein, lactate-dehydrogenase, ferritin, and albumin.",
    "title": "Early biomarkers in hospitalized patients as predictors of post-acute sequelae of SARS-CoV-2 infection: a one-year cohort study.",
    "xml": "<Element 'PubmedArticle' at 0x7885062213f0>"
}