{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T19:38:05Z","timestamp":1793821085697,"version":"4.6.1"},"reference-count":59,"publisher":"BMJ","issue":"1","license":[{"start":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T00:00:00Z","timestamp":1736121600000},"content-version":"unspecified","delay-in-days":5,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2024,12,9]]},"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>A combined cross-sectional and prospective observational study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>A tertiary care hospital.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>221 patients hospitalised for COVID-19 who have undergone comprehensive clinical, sonographic and survey-based evaluation predischarge and at 1\u2009month with subsequent 12-month follow-up. The final cohort included 166 patients who had completed the final visit at 12 months.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Main outcome measure<\/jats:title>\n                    <jats:p>A self-reported persistence of LCS at 12 months after discharge.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Self-reported LCS was detected in 76% of participants at 3 months and in 43% at 12 months after discharge. Patients who reported incomplete recovery at 1 year were characterised by a higher burden of comorbidities (Charlson index of 0.69\u00b10.96 vs 0.31\u00b10.51, p=0.001) and residual pulmonary consolidations (1.56\u00b11.78 vs 0.98\u00b11.56, p=0.034), worse blood pressure (BP) control (systolic BP of 138.1\u00b116.2 vs 132.2\u00b115.8\u2009mm Hg, p=0.041), renal (estimated glomerular filtration rate of 59.5\u00b114.7 vs 69.8\u00b120.7\u2009mL\/min\/1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      , p=0.007) and endothelial function (flow-mediated dilation of the brachial artery of 10.4\u00b15.4\u2009vs 12.4\u00b15.6%, p=0.048), higher in-hospital levels of liver enzymes (alanine aminotransferase (ALT) of 76.3\u00b160.8 vs 46.3\u00b125.3\u2009IU\/L, p=0.002) and erythrocyte sedimentation rate (ESR) (34.3\u00b112.1 vs 28.3\u00b112.6\u2009mm\/h, p=0.008), slightly higher indices of ventricular longitudinal function (left ventricular (LV) global longitudinal strain (GLS) of 18.0\u00b12.4\u2009vs 17.0\u00b12.3%, p=0011) and higher levels of Hospital Anxiety and Depression Scale anxiety (7.3\u00b14.2 vs 5.6\u00b13.8, p=0.011) and depression scores (6.4\u00b13.9 vs 4.9\u00b14.3, p=0.022) and EFTER-COVID study physical symptoms score (12.3\u00b13.8 vs 9.2\u00b14.2, p&lt;0.001). At 1 month postdischarge, the persisting differences included marginally higher LV GLS, mitral E\/e\u2019 ratio and significantly higher levels of both resting and exertional physical symptoms versus patients who reported complete recovery. Logistic regression and machine learning-based binary classification models have been developed to predict the persistence of LCS symptoms at 12 months after discharge.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Compared with post-COVID-19 patients who have completely recovered by 12 months after hospital discharge, those who have subsequently developed \u2018very long\u2019 COVID were characterised by a variety of more pronounced residual predischarge abnormalities that had mostly subsided by 1\u2009month, except for steady differences in the physical symptoms levels. A simple artificial neural networks-based binary classification model using peak ESR, creatinine, ALT and weight loss during the acute phase, predischarge 6-minute walk distance and complex survey-based symptoms assessment as inputs has shown a 92% accuracy with an area under receiver-operator characteristic curve 0.931 in prediction of LCS symptoms persistence at 12 months.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2024-084311","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T20:41:45Z","timestamp":1736196105000},"page":"e084311","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":13,"title":["Early prediction of long COVID-19 syndrome persistence at 12 months after hospitalisation: a prospective observational study from Ukraine"],"prefix":"10.1136","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6834-8845","authenticated-orcid":false,"given":"Oleksii","family":"Honchar","sequence":"first","affiliation":[{"name":"Department of Propedeutics of Internal Medicine, Nursing and Bioethics, Kharkiv National Medical University, Kharkiv, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetiana","family":"Ashcheulova","sequence":"additional","affiliation":[{"name":"Department of Propedeutics of Internal Medicine, Nursing and Bioethics, Kharkiv National Medical University, Kharkiv, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetyana","family":"Chumachenko","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Kharkiv National Medical University, Kharkiv, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmytro","family":"Chumachenko","sequence":"additional","affiliation":[{"name":"Department of Mathematical Modelling and Artificial Intelligence, National Aerospace University Kharkiv Aviation Institute, Kharkiv, Ukraine"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2025,1,6]]},"reference":[{"key":"2025121403411867000_15.1.e084311.1","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2023.1168628","article-title":"Exploring long COVID condition in Latin America: Its impact on patients\u2019 activities and associated healthcare use","volume":"10","author":"Angarita-Fonseca","year":"2023","journal-title":"Front Med (Lausanne)"},{"key":"2025121403411867000_15.1.e084311.2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.12603"},{"key":"2025121403411867000_15.1.e084311.3","unstructured":"NICE . 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