https://m2.mtmt.hu/ hun 2026-09-21 22:46 JournalArticle 34877190 VALIDATED true Export Date: 2 June 2024 0 false 2026-08-10T20:25:31.216+0000 2024-05-27T10:03:10.582+0000 2024-05-26T18:03:52.879+0000 true 10026589 Tichy Rita /api/admin/10026589 Admin Tichy Rita (SE_KK_Admin5_TR, admin) true 10026589 2026-03-27T10:20:51.697+0000 2026-03-27T10:20:51.697+0000 2024-05-27T10:03:10.594+0000 true 10080205 Szalóky-Siki Ágnes /api/admin/10080205 Admin Szalóky-Siki Ágnes (SE_KK_Admin5_SZSA, admin) true Admin 10025544 /api/admin/10025544 Lévayné Deseő Katalin (MTMT Központi admin) Lévayné Deseő Katalin true 10025544 true 2025-06-04T23:11:59.349+0000 true false true 24 24 /api/publicationtype/24 PublicationType Folyóiratcikk 1 true 24 JournalArticle true 10000359 Study Group true 24 24 /api/publicationtype/24 PublicationType Folyóiratcikk 1 true 24 JournalArticle /api/subtype/10000359 Sokszerzős vagy csoportos szerzőségű szakcikk SubType Sokszerzős vagy csoportos szerzőségű szakcikk (Folyóiratcikk) 104 true 10000359 true 1 /api/category/1 Category Tudományos true 1 Devaux, Yvan true true /api/journal/10015678 REVIEWED NATURE COMMUNICATIONS 2041-1723 true false 10015678 false 10015678 true 2041-1723 Journal FOREIGN 15 1 4259 4259 12 2024 Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82–0.84) and a balanced accuracy of 0.78 (95% CI 0.77–0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40–0.74). Quantitative PCR validated LEF1-AS1’s adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management. 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false true PersonAuthorship 116780680 /api/authorship/116780680 Jordan, Marko 19 0.0 false false false Jordan Marko true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 116780681 /api/authorship/116780681 Brandenburger, Timo 20 0.0 false false false Brandenburger Timo true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 116780682 /api/authorship/116780682 Benczik, Bettina [Benczik, Bettina (Bioinformatika), szerző] Farmakológiai és Farmakoterápiás Intézet (SE / AOK / I); HUN-REN-SE Rendszerfarmakológiai Kutatócsoport (SE / AOK / I / FFI) 21 0.0 false false false Author 10069234 /api/author/10069234 Benczik Bettina (Bioinformatika) Benczik Bettina true true Benczik Bettina true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 116780683 /api/authorship/116780683 Agg, Bence [Ágg, Bence (Farmakológia), szerző] Farmakológiai és Farmakoterápiás Intézet (SE / AOK / I); HUN-REN-SE Rendszerfarmakológiai Kutatócsoport (SE / AOK / I / FFI) 22 0.0 false false false Author 10057401 /api/author/10057401 Ágg Bence (Farmakológia) Ágg Bence true 10057401 true Agg Bence true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 116780684 /api/authorship/116780684 Ferdinandy, Peter [Ferdinandy, Péter (Farmakológia, mol...), szerző] Farmakológiai és Farmakoterápiás Intézet (SE / AOK / I); HUN-REN-SE Rendszerfarmakológiai Kutatócsoport (SE / AOK / I / FFI) 23 0.0 false false false Author 10010125 /api/author/10010125 Ferdinandy Péter (Farmakológia, molekuláris medicina) Ferdinandy Péter true 10010125 true Ferdinandy Peter true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 116780685 /api/authorship/116780685 Vehreschild, Jörg Janne 24 0.0 false false false Vehreschild Jörg Janne true false false AuthorshipType 1 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(2024) NATURE COMMUNICATIONS 2041-1723 15 1<div class="JournalArticle Publication long-list"> <div class="authors"> <img title="Forrásközlemény" style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" >Devaux Yvan ✉ </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10069234"><a href="/gui2/?type=authors&mode=browse&sel=10069234" target="_blank">Benczik Bettina (<span class="authorship-author-name">Benczik Bettina</span> <span class="authorAux-mtmt"> Bioinformatika</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Farmakológiai és Farmakoterápiás Intézet; <span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/<span title="Farmakológiai és Farmakoterápiás Intézet">FFI</span>/HUN-REN-SE Rendszerfarmakológiai Kutatócsoport</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10057401"><a href="/gui2/?type=authors&mode=browse&sel=10057401" target="_blank">Agg Bence (<span class="authorship-author-name">Ágg Bence</span> <span class="authorAux-mtmt"> Farmakológia</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Farmakológiai és Farmakoterápiás Intézet; <span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/<span title="Farmakológiai és Farmakoterápiás Intézet">FFI</span>/HUN-REN-SE Rendszerfarmakológiai Kutatócsoport</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10010125"><a href="/gui2/?type=authors&mode=browse&sel=10010125" target="_blank">Ferdinandy Peter (<span class="authorship-author-name">Ferdinandy Péter</span> <span class="authorAux-mtmt"> Farmakológia, molekuláris medicina</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/Farmakológiai és Farmakoterápiás Intézet; <span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Intézet">I</span>/<span title="Farmakológiai és Farmakoterápiás Intézet">FFI</span>/HUN-REN-SE Rendszerfarmakológiai Kutatócsoport</span> ;&nbsp;&nbsp;&nbsp; et al. (35) </div> <div><a target="_blank" href="/api/publication/34877190?labelLang=hun">Összes szerző</a></div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;34877190" target="_blank">Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality</a></div> <div> <span class="journal-title">NATURE COMMUNICATIONS</span> <span class="journal-issn">( <a target="_blank" href="https://portal.issn.org/resource/ISSN/2041-1723">2041-1723</a>)</span>: <span class="journal-volume">15</span> <span class="journal-issue">1</span> <span class="page"> Paper 4259. 12 p. </span> <span class="year">(2024)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.1038/s41467-024-47557-1" target="_blank" href="https://doi.org/10.1038/s41467-024-47557-1"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="001228176400030" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/001228176400030"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85193708350" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85193708350"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="38769334" target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=38769334&dopt=Abstract"> PubMed </a> </span> </span> <OnlyViewableByAuthor><div class="ratings"> <div class="journal-subject">Folyóirat szakterülete: Scopus - Biochemistry, Genetics and Molecular Biology (miscellaneous)&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;D1</div> <div class="journal-subject">Folyóirat szakterülete: Scopus - Chemistry (miscellaneous)&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;D1</div> <div class="journal-subject">Folyóirat szakterülete: Scopus - Physics and Astronomy (miscellaneous)&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;D1</div> <div class="journal-subject">Regionális Tudományok Bizottsága IXGJO RTB [1901-]&nbsp;&nbsp;&nbsp;A nemzetközi</div> </div></OnlyViewableByAuthor> <div class="publication-citation" style="margin-left: 0.5cm;"> <span title="Nyilvános idézőközlemények összesen, említések nélkül" class="citingPub-count">Nyilvános idéző összesen: 17</span> | Független: 8 | Függő: 9 | Nem jelölt: 0 | WoS jelölt: 15 | Scopus jelölt:&nbsp;16 | WoS/Scopus jelölt:&nbsp;17 | DOI jelölt:&nbsp;17 </div> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;34877190&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 2 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 34877190</span> | <span class="status-data status-VALIDATED"> Egyeztetett </span> Forrás Idéző | <span class="type-subtype">Folyóiratcikk ( Sokszerzős vagy csoportos szerzőségű szakcikk ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">kézi felvitel</span> </div> <div class="funder"> (RRF-2.3.1-21-2022-00003), (2020-1.1.5-GYORSÍTÓSÁV-2021-00011), (2020-1.1.6-JOVO-2021-00013) </div> <div class="lastModified">Utolsó módosítás: 2024.05.27. 12:03 Szalóky-Siki Ágnes (SE_KK_Admin5_SZSA, admin) </div> <div class="lockedBy">Központi kezelésű 2025.06.05. 01:11 Lévayné Deseő Katalin (MTMT Központi admin) </div> <pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: Export Date: 2 June 2024</pre> </div></div>