Competing-risk analysis of coronavirus disease 2019 in-hospital mortality in a Northern Italian centre from SMAtteo COvid19 REgistry (SMACORE)
An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hos...
Saved in:
| Published in | Scientific reports Vol. 11; no. 1; pp. 1137 - 10 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
13.01.2021
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2045-2322 2045-2322 |
| DOI | 10.1038/s41598-020-80679-2 |
Cover
| Abstract | An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19. |
|---|---|
| AbstractList | An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19. An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19.An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19. An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19. Abstract An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of the study is to identify predictors of in-hospital mortality and discharge in a cohort of Lombardy patients with COVID-19. All consecutive hospitalised patients from February 21st to March 30th, 2020, with confirmed COVID-19 from the IRCCS Policlinico San Matteo, Pavia, Lombardy, Italy, were included. In-hospital mortality and discharge were evaluated by competing risk analysis. The Fine and Gray model was fitted in order to estimate the effect of covariates on the cumulative incidence functions (CIFs) for in-hospital mortality and discharge. 426 adult patients [median age 68 (IQR 56 to 77 years)] were admitted with confirmed COVID-19 over a 5-week period; 292 (69%) were male. By 21 April 2020, 141 (33%) of these patients had died, 239 (56%) patients had been discharged and 46 (11%) were still hospitalised. Among these 46 patients, updated as of 30 May, 2020, 5 (10.9%) had died, 8 (17.4%) were still in ICU, 12 (26.1%) were transferred to lower intensity care units and 21 (45.7%) were discharged. Regression on the CIFs for in-hospital mortality showed that older age, male sex, number of comorbidities and hospital admission after March 4th were independent risk factors associated with in-hospital mortality. Older age, male sex and number of comorbidities definitively predicted in-hospital mortality in hospitalised patients with COVID-19. |
| ArticleNumber | 1137 |
| Author | Celsa, Ciro Biscarini, Simona Roda, Silvia Seminari, Elena Attanasio, Massimo Cammà, Calogero Pieri, Teresa Chiara Di Matteo, Angela Sambo, Margherita Sachs, Michele Battaglia, Salvatore Enea, Marco Asperges, Erika Di Filippo, Alessandro Colaneri, Marta Novati, Stefano Sacchi, Paolo Valsecchi, Pietro Lupi, Matteo Maiocchi, Laura Gallazzi, Ilaria Zuccaro, Valentina Bruno, Raffaele |
| Author_xml | – sequence: 1 givenname: Valentina surname: Zuccaro fullname: Zuccaro, Valentina organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 2 givenname: Ciro surname: Celsa fullname: Celsa, Ciro organization: Section of Gastroenterology and Hepatology, Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Doctoral Programme in Oncology and Experimental Surgery, Department of Surgical, Oncological and Stomatological Disciplines, University of Palermo – sequence: 3 givenname: Margherita surname: Sambo fullname: Sambo, Margherita organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 4 givenname: Salvatore surname: Battaglia fullname: Battaglia, Salvatore organization: Department of Economics, Business and Statistics, University of Palermo – sequence: 5 givenname: Paolo surname: Sacchi fullname: Sacchi, Paolo organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 6 givenname: Simona surname: Biscarini fullname: Biscarini, Simona organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 7 givenname: Pietro surname: Valsecchi fullname: Valsecchi, Pietro organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 8 givenname: Teresa Chiara surname: Pieri fullname: Pieri, Teresa Chiara organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 9 givenname: Ilaria surname: Gallazzi fullname: Gallazzi, Ilaria organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 10 givenname: Marta surname: Colaneri fullname: Colaneri, Marta organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 11 givenname: Michele surname: Sachs fullname: Sachs, Michele organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 12 givenname: Silvia surname: Roda fullname: Roda, Silvia organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 13 givenname: Erika surname: Asperges fullname: Asperges, Erika organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 14 givenname: Matteo surname: Lupi fullname: Lupi, Matteo organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 15 givenname: Alessandro surname: Di Filippo fullname: Di Filippo, Alessandro organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 16 givenname: Elena surname: Seminari fullname: Seminari, Elena organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 17 givenname: Angela surname: Di Matteo fullname: Di Matteo, Angela organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 18 givenname: Stefano surname: Novati fullname: Novati, Stefano organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 19 givenname: Laura surname: Maiocchi fullname: Maiocchi, Laura organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia – sequence: 20 givenname: Marco surname: Enea fullname: Enea, Marco organization: Department of Economics, Business and Statistics, University of Palermo – sequence: 21 givenname: Massimo surname: Attanasio fullname: Attanasio, Massimo organization: Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo – sequence: 22 givenname: Calogero surname: Cammà fullname: Cammà, Calogero organization: Section of Gastroenterology and Hepatology, Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo – sequence: 23 givenname: Raffaele surname: Bruno fullname: Bruno, Raffaele email: raffaele.bruno@unipv.it organization: U.O.C. Malattie Infettive I Fondazione IRCCS Policlinico San Matteo, Università di Pavia, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33441892$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9UsFuEzEUXKEiWkp_gAOyxKUcFry2N2tfkKpVgEiFSAXOltf7nDjs2sF2IuUn-GacpIW2h_pi-72Z8VjzXhYnzjsoitcVfl9hyj9EVtWCl5jgkuNJI0ryrDgjmNUloYSc3DufFhcxrnBeNRGsEi-KU0oZq7ggZ8Wf1o9rSNYtymDjL6ScGnbRRuQN0j54p7Y2bCLqbQQVARFcCWRdufRxbZMa0OhD3mza5SpS6Fu-LiE4NNtXlUMaXAqATPAj-v71KiXwqJ1vbZ91bqYLG1PYocvcaec303eviudGDREubvfz4uen6Y_2S3k9_zxrr65LXXOeyr5nndKEAJiuFzWZaMyqjlAALibE5AalxnSgGyEoA6L7HlMDDe5ETaEz9LyYHXV7r1ZyHeyowk56ZeWh4MNCqpCsHkAKhQ1hDWWqqVnNOAclsiTXVe7U9V7r41FrvelG6A8fVsMD0YcdZ5dy4beyycFlf1ng8lYg-N8biEmONmoYBuXAb6LMr_McuaCTDH37CLrym5AzO6AayklNqox6c9_RPyt3sWcAPwJ08DEGMFLnMJP1e4N2kBWW-yGTxyGTecjkYcjknkoeUe_UnyTRIylmsFtA-G_7CdZfPqzkbA |
| CitedBy_id | crossref_primary_10_4103_jehp_jehp_246_23 crossref_primary_10_1093_rheumatology_kead637 crossref_primary_10_1177_23337214221079956 crossref_primary_10_1016_j_jamda_2021_07_005 crossref_primary_10_3390_s21248503 crossref_primary_10_3390_medicina59010032 crossref_primary_10_61486_SGRL8486 crossref_primary_10_1016_j_cmpb_2023_107545 crossref_primary_10_1016_S2352_4642_21_00134_6 crossref_primary_10_1097_MPH_0000000000002532 crossref_primary_10_1177_09622802221106300 crossref_primary_10_3390_electronics12183878 crossref_primary_10_23876_j_krcp_23_137 crossref_primary_10_1186_s12877_021_02673_1 crossref_primary_10_3390_math11173772 crossref_primary_10_1371_journal_pone_0257613 crossref_primary_10_1038_s41598_022_19264_8 crossref_primary_10_3390_jcm11195787 crossref_primary_10_1016_j_cct_2022_106758 crossref_primary_10_3390_jpm13040620 crossref_primary_10_3390_idr14030052 |
| Cites_doi | 10.2807/1560-7917.ES.2020.25.3.2000045 10.1016/S0140-6736(20)30627-9 10.1016/j.ijid.2020.03.017 10.1038/s41421-020-0147-1 10.3389/fmed.2020.00185 10.1002/bimj.201800274 10.2307/2531595 10.1016/j.ejim.2017.02.002 10.1016/j.jhin.2020.03.020 10.1016/j.jinf.2020.04.021 10.1016/S1473-3099(20)30086-4 10.1001/jama.2020.1585 10.1097/CCM.0000000000004207 10.18632/aging.103579 10.1080/01621459.1999.10474144 10.1016/0021-9681(87)90171-8 10.1001/jama.2020.6775 10.1093/eurheartj/ehu131 10.1007/s12016-017-8648-x 10.1016/j.tmaid.2020.101623 10.1016/S2213-2600(20)30117-X 10.7326/0003-4819-124-11-199606010-00008 10.2337/dc12-0788 10.1001/jama.2016.0287 10.1016/S0140-6736(20)30566-3 10.1002/sim.2712 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2021 The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s) 2021 – notice: The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | C6C AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AEUYN AFKRA AZQEC BBNVY BENPR BHPHI CCPQU COVID DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2P M7P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS Q9U 7X8 5PM DOA |
| DOI | 10.1038/s41598-020-80679-2 |
| DatabaseName | Springer Nature Open Access Journals CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Coronavirus Research Database ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences ProQuest Health & Medical Collection Medical Database Science Database Biological Science Database (ProQuest) Proquest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition Coronavirus Research Database ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE MEDLINE - Academic Publicly Available Content Database CrossRef |
| Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: DOAJ: Directory of Open Access Journal (DOAJ) url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 4 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 5 dbid: BENPR name: ProQuest Central Database Suite (ProQuest) url: http://www.proquest.com/pqcentral?accountid=15518 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 2045-2322 |
| EndPage | 10 |
| ExternalDocumentID | oai_doaj_org_article_9a0f24734a7545488ea94e28c19a055f PMC7806993 33441892 10_1038_s41598_020_80679_2 |
| Genre | Journal Article |
| GeographicLocations | Italy |
| GeographicLocations_xml | – name: Italy |
| GroupedDBID | 0R~ 3V. 4.4 53G 5VS 7X7 88A 88E 88I 8FE 8FH 8FI 8FJ AAFWJ AAJSJ AAKDD ABDBF ABUWG ACGFS ACSMW ACUHS ADBBV ADRAZ AENEX AEUYN AFKRA AJTQC ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS AZQEC BAWUL BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C6C CCPQU DIK DWQXO EBD EBLON EBS ESX FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE KQ8 LK8 M0L M1P M2P M48 M7P M~E NAO OK1 PIMPY PQQKQ PROAC PSQYO RNT RNTTT RPM SNYQT UKHRP AASML AAYXX AFPKN CITATION PHGZM PHGZT CGR CUY CVF ECM EIF NPM 7XB 8FK AARCD COVID K9. PJZUB PKEHL PPXIY PQEST PQGLB PQUKI PRINS Q9U 7X8 PUEGO 5PM |
| ID | FETCH-LOGICAL-c588t-dd4bac22eefbd9526c041b23ee8962f22e33ffbec79934e2cdd03fe70b953ebf3 |
| IEDL.DBID | 7X7 |
| ISSN | 2045-2322 |
| IngestDate | Wed Aug 27 01:30:36 EDT 2025 Thu Aug 21 17:43:23 EDT 2025 Thu Sep 04 23:51:27 EDT 2025 Wed Aug 13 05:10:51 EDT 2025 Thu Jan 02 22:32:30 EST 2025 Thu Apr 24 23:00:36 EDT 2025 Tue Jul 01 01:07:12 EDT 2025 Fri Feb 21 02:38:58 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| License | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c588t-dd4bac22eefbd9526c041b23ee8962f22e33ffbec79934e2cdd03fe70b953ebf3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://www.proquest.com/docview/2477382521?pq-origsite=%requestingapplication% |
| PMID | 33441892 |
| PQID | 2477382521 |
| PQPubID | 2041939 |
| PageCount | 10 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_9a0f24734a7545488ea94e28c19a055f pubmedcentral_primary_oai_pubmedcentral_nih_gov_7806993 proquest_miscellaneous_2478038936 proquest_journals_2477382521 pubmed_primary_33441892 crossref_citationtrail_10_1038_s41598_020_80679_2 crossref_primary_10_1038_s41598_020_80679_2 springer_journals_10_1038_s41598_020_80679_2 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2021-01-13 |
| PublicationDateYYYYMMDD | 2021-01-13 |
| PublicationDate_xml | – month: 01 year: 2021 text: 2021-01-13 day: 13 |
| PublicationDecade | 2020 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London – name: England |
| PublicationTitle | Scientific reports |
| PublicationTitleAbbrev | Sci Rep |
| PublicationTitleAlternate | Sci Rep |
| PublicationYear | 2021 |
| Publisher | Nature Publishing Group UK Nature Publishing Group Nature Portfolio |
| Publisher_xml | – name: Nature Publishing Group UK – name: Nature Publishing Group – name: Nature Portfolio |
| References | CharlsonMEPompeiPAlesKLMacKenzieCRA new method of classifying prognostic comorbidity in longitudinal studies: Development and validationJ. Chronic Dis.19874053733831:STN:280:DyaL2s7ms1GnsQ%3D%3D10.1016/0021-9681(87)90171-8 FabbianFA modified Elixhauser score for predicting in-hospital mortality in internal medicine admissionsEur. J. Intern. Med.201740374210.1016/j.ejim.2017.02.002 Richardson, S., et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area (published online ahead of print, 2020 Apr 22). JAMA. e206775, https://doi.org/10.1001/jama.2020.6775 (2020) SingerMThe third international consensus definitions for sepsis and septic shock (Sepsis-3)JAMA20163158018101:CAS:528:DC%2BC28XhtlGrt7fE10.1001/jama.2016.0287 PutterHFioccoMGeskusRBTutorial in biostatistics: Competing risks and multi-state modelsStat. Med.200726112389243023684221:STN:280:DC%2BD2s3hs1agsA%3D%3D10.1002/sim.2712 JaillonSBerthenetKGarlandaCSexual dimorphism in innate immunityClin. Rev. Allergy Immunol.20195633083211:CAS:528:DC%2BC2sXhs1SktL%2FF10.1007/s12016-017-8648-x SuissaSAzoulayLMetformin and the risk of cancer: Time-related biases in observational studiesDiab. Care201235266526731:CAS:528:DC%2BC38XhvFShsrnN10.2337/dc12-0788 ZhengZRisk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysisJ Infect.2020812e16e251:CAS:528:DC%2BB3cXhsVKkt7%2FO10.1016/j.jinf.2020.04.021 GlesbyMJHooverDRSurvivor treatment selection bias in observational studies: Examples from the AIDS literatureAnn. Intern. Med.199612499910051:STN:280:DyaK283ht1egtA%3D%3D10.7326/0003-4819-124-11-199606010-00008 Asperges, E., et al. Rapid response to COVID-19 outbreak in Northern Italy: How to convert a classic infectious disease ward into a COVID-19 response centre. J. Hosp. Infect.105(3), 477–479, https://doi.org/10.1016/j.jhin.2020.03.020 (2020) https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 Rodriguez-Morales, A.J., et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis (published online ahead of print, 2020 Mar 13). Travel Med. Infect. Dis. 34, 101623 (2020) DeLongERDeLongDMClarke-PearsonDLComparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approachBiometrics19884438378451:STN:280:DyaL1M%2Fns12ksQ%3D%3D10.2307/2531595 Wolbers, M., et al. Competing risks analyses: objectives and approaches. Eur. Heart J. 35(42), 2936–2941, https://doi.org/10.1093/eurheartj/ehu131 (2014) RemuzziARemuzziGCOVID-19 and Italy: What next?Lancet202039510231122512281:CAS:528:DC%2BB3cXltFeqsLw%3D10.1016/S0140-6736(20)30627-9 OpalSMGirardTDElyEWThe immunopathogenesis of sepsis in elderly patientsClin. Infect. Dis.202541suppl 7S504S512 YangJPrevalence of comorbidities and its effects in patients infected with SARS-CoV-2: A systematic review and meta-analysisInt. J. Infect. Dis.20209491951:CAS:528:DC%2BB3cXnslOgsrY%3D10.1016/j.ijid.2020.03.017 Levin, A., et al. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney InjuryWork Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int. Suppl.2, 1 (2012) Istituto Superiore di Sanità. Characteristics of COVID-19 Patients Dying in Italy. Report Based on Available Data on May 7th, 2020. https://www.epicentro.iss.it/en/coronavirus/sars-cov-2-analysis-of-deaths. Coronavirus Disease (COVID-19) Technical Guidance: Laboratory Testing for 2019-nCoV in Humans. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/laboratory-guidance. Cai, H. Sex difference and smoking predisposition in patients with COVID-19 (published correction appears in Lancet Respir. Med.8(4)) (2020) Iosa, M., Paolucci, S., & Morone, G. Covid-19: A dynamic analysis of fatality risk in Italy. Front. Med. (Lausanne). 7, 185, https://doi.org/10.3389/fmed.2020.00185 (2020) FineJPA proportional hazards model for the sub-distribution of a competing riskJ. Am. Stat. Assoc.19999449650910.1080/01621459.1999.10474144 ZhouFClinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort studyLancet202039510229105410621:CAS:528:DC%2BB3cXkvVGktL8%3D10.1016/S0140-6736(20)30566-3 Wang, D., et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China (published online ahead of print, 2020 Feb 7). JAMA. 323(11), 1061–1069, https://doi.org/10.1001/jama.2020.1585 (2020) CormanVMDetection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCREuro Surveill.2020253200004510.2807/1560-7917.ES.2020.25.3.2000045 Cao, Y., et al. Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations. Cell Discov. 6, 11, https://doi.org/10.1038/s41421-020-0147-1 (2020) De Giorgi, A., et al. OUTcome and COMorbidity Evaluation of INTernal MEDicine COVID19 (OUTCOME-INTMED-COV19) Study Collaborators. Prediction of in-hospital mortality of patients with SARS-CoV-2 infection by comorbidity indexes: an Italian internal medicine single center study. Eur. Rev. Med. Pharmacol. Sci.24(19), 10258–10266 (2020) Putter, H., Schumacher, M., & van Houwelingen, H.C. On the relation between the cause-specific hazard and the subdistribution rate for competing risks data: The Fine-Gray model revisited. Biom. J. 62(3), 790–807, https://doi.org/10.1002/bimj.201800274 (2020) FangXEpidemiological, comorbidity factors with severity and prognosis of COVID-19: A systematic review and meta-analysisAging (Albany NY).2020121312493125031:CAS:528:DC%2BB3cXisFCmurrJ10.18632/aging.103579 ShiHRadiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: A descriptive studyLancet Infect. Dis.20202044254341:CAS:528:DC%2BB3cXjvFWhtbs%3D10.1016/S1473-3099(20)30086-4 GaoCAssociation between cardiac injury and mortality in hospitalized patients infected with Avian Influenza A (H7N9) virusCrit. Care Med.20204844514581:CAS:528:DC%2BB3cXltlKntL4%3D10.1097/CCM.0000000000004207 S Jaillon (80679_CR17) 2019; 56 JP Fine (80679_CR31) 1999; 94 ME Charlson (80679_CR6) 1987; 40 80679_CR26 80679_CR24 80679_CR29 F Fabbian (80679_CR7) 2017; 40 C Gao (80679_CR30) 2020; 48 MJ Glesby (80679_CR21) 1996; 124 80679_CR22 80679_CR23 H Putter (80679_CR5) 2007; 26 Z Zheng (80679_CR13) 2020; 81 H Shi (80679_CR25) 2020; 20 80679_CR9 80679_CR1 80679_CR16 ER DeLong (80679_CR32) 1988; 44 80679_CR19 80679_CR4 80679_CR3 J Yang (80679_CR14) 2020; 94 VM Corman (80679_CR27) 2020; 25 80679_CR18 X Fang (80679_CR15) 2020; 12 S Suissa (80679_CR20) 2012; 35 80679_CR12 A Remuzzi (80679_CR2) 2020; 395 80679_CR10 M Singer (80679_CR28) 2016; 315 SM Opal (80679_CR11) 2025; 41 F Zhou (80679_CR8) 2020; 395 |
| References_xml | – reference: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020 – reference: Rodriguez-Morales, A.J., et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis (published online ahead of print, 2020 Mar 13). Travel Med. Infect. Dis. 34, 101623 (2020) – reference: GlesbyMJHooverDRSurvivor treatment selection bias in observational studies: Examples from the AIDS literatureAnn. Intern. Med.199612499910051:STN:280:DyaK283ht1egtA%3D%3D10.7326/0003-4819-124-11-199606010-00008 – reference: Wolbers, M., et al. Competing risks analyses: objectives and approaches. Eur. Heart J. 35(42), 2936–2941, https://doi.org/10.1093/eurheartj/ehu131 (2014) – reference: FineJPA proportional hazards model for the sub-distribution of a competing riskJ. Am. Stat. Assoc.19999449650910.1080/01621459.1999.10474144 – reference: DeLongERDeLongDMClarke-PearsonDLComparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approachBiometrics19884438378451:STN:280:DyaL1M%2Fns12ksQ%3D%3D10.2307/2531595 – reference: Asperges, E., et al. Rapid response to COVID-19 outbreak in Northern Italy: How to convert a classic infectious disease ward into a COVID-19 response centre. J. Hosp. Infect.105(3), 477–479, https://doi.org/10.1016/j.jhin.2020.03.020 (2020) – reference: OpalSMGirardTDElyEWThe immunopathogenesis of sepsis in elderly patientsClin. Infect. Dis.202541suppl 7S504S512 – reference: JaillonSBerthenetKGarlandaCSexual dimorphism in innate immunityClin. Rev. Allergy Immunol.20195633083211:CAS:528:DC%2BC2sXhs1SktL%2FF10.1007/s12016-017-8648-x – reference: Cai, H. Sex difference and smoking predisposition in patients with COVID-19 (published correction appears in Lancet Respir. Med.8(4)) (2020) – reference: YangJPrevalence of comorbidities and its effects in patients infected with SARS-CoV-2: A systematic review and meta-analysisInt. J. Infect. Dis.20209491951:CAS:528:DC%2BB3cXnslOgsrY%3D10.1016/j.ijid.2020.03.017 – reference: ZhouFClinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort studyLancet202039510229105410621:CAS:528:DC%2BB3cXkvVGktL8%3D10.1016/S0140-6736(20)30566-3 – reference: SingerMThe third international consensus definitions for sepsis and septic shock (Sepsis-3)JAMA20163158018101:CAS:528:DC%2BC28XhtlGrt7fE10.1001/jama.2016.0287 – reference: RemuzziARemuzziGCOVID-19 and Italy: What next?Lancet202039510231122512281:CAS:528:DC%2BB3cXltFeqsLw%3D10.1016/S0140-6736(20)30627-9 – reference: Cao, Y., et al. Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations. Cell Discov. 6, 11, https://doi.org/10.1038/s41421-020-0147-1 (2020) – reference: Levin, A., et al. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney InjuryWork Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int. Suppl.2, 1 (2012) – reference: Iosa, M., Paolucci, S., & Morone, G. Covid-19: A dynamic analysis of fatality risk in Italy. Front. Med. (Lausanne). 7, 185, https://doi.org/10.3389/fmed.2020.00185 (2020) – reference: SuissaSAzoulayLMetformin and the risk of cancer: Time-related biases in observational studiesDiab. Care201235266526731:CAS:528:DC%2BC38XhvFShsrnN10.2337/dc12-0788 – reference: De Giorgi, A., et al. OUTcome and COMorbidity Evaluation of INTernal MEDicine COVID19 (OUTCOME-INTMED-COV19) Study Collaborators. Prediction of in-hospital mortality of patients with SARS-CoV-2 infection by comorbidity indexes: an Italian internal medicine single center study. Eur. Rev. Med. Pharmacol. Sci.24(19), 10258–10266 (2020) – reference: Putter, H., Schumacher, M., & van Houwelingen, H.C. On the relation between the cause-specific hazard and the subdistribution rate for competing risks data: The Fine-Gray model revisited. Biom. J. 62(3), 790–807, https://doi.org/10.1002/bimj.201800274 (2020) – reference: PutterHFioccoMGeskusRBTutorial in biostatistics: Competing risks and multi-state modelsStat. Med.200726112389243023684221:STN:280:DC%2BD2s3hs1agsA%3D%3D10.1002/sim.2712 – reference: Wang, D., et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China (published online ahead of print, 2020 Feb 7). JAMA. 323(11), 1061–1069, https://doi.org/10.1001/jama.2020.1585 (2020) – reference: Istituto Superiore di Sanità. Characteristics of COVID-19 Patients Dying in Italy. Report Based on Available Data on May 7th, 2020. https://www.epicentro.iss.it/en/coronavirus/sars-cov-2-analysis-of-deaths. – reference: Richardson, S., et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area (published online ahead of print, 2020 Apr 22). JAMA. e206775, https://doi.org/10.1001/jama.2020.6775 (2020) – reference: Coronavirus Disease (COVID-19) Technical Guidance: Laboratory Testing for 2019-nCoV in Humans. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/laboratory-guidance. – reference: CharlsonMEPompeiPAlesKLMacKenzieCRA new method of classifying prognostic comorbidity in longitudinal studies: Development and validationJ. Chronic Dis.19874053733831:STN:280:DyaL2s7ms1GnsQ%3D%3D10.1016/0021-9681(87)90171-8 – reference: ZhengZRisk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysisJ Infect.2020812e16e251:CAS:528:DC%2BB3cXhsVKkt7%2FO10.1016/j.jinf.2020.04.021 – reference: FangXEpidemiological, comorbidity factors with severity and prognosis of COVID-19: A systematic review and meta-analysisAging (Albany NY).2020121312493125031:CAS:528:DC%2BB3cXisFCmurrJ10.18632/aging.103579 – reference: GaoCAssociation between cardiac injury and mortality in hospitalized patients infected with Avian Influenza A (H7N9) virusCrit. Care Med.20204844514581:CAS:528:DC%2BB3cXltlKntL4%3D10.1097/CCM.0000000000004207 – reference: FabbianFA modified Elixhauser score for predicting in-hospital mortality in internal medicine admissionsEur. J. Intern. Med.201740374210.1016/j.ejim.2017.02.002 – reference: ShiHRadiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: A descriptive studyLancet Infect. Dis.20202044254341:CAS:528:DC%2BB3cXjvFWhtbs%3D10.1016/S1473-3099(20)30086-4 – reference: CormanVMDetection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCREuro Surveill.2020253200004510.2807/1560-7917.ES.2020.25.3.2000045 – volume: 25 start-page: 2000045 issue: 3 year: 2020 ident: 80679_CR27 publication-title: Euro Surveill. doi: 10.2807/1560-7917.ES.2020.25.3.2000045 – volume: 395 start-page: 1225 issue: 10231 year: 2020 ident: 80679_CR2 publication-title: Lancet doi: 10.1016/S0140-6736(20)30627-9 – volume: 94 start-page: 91 year: 2020 ident: 80679_CR14 publication-title: Int. J. Infect. Dis. doi: 10.1016/j.ijid.2020.03.017 – ident: 80679_CR18 doi: 10.1038/s41421-020-0147-1 – ident: 80679_CR24 doi: 10.3389/fmed.2020.00185 – ident: 80679_CR26 – ident: 80679_CR23 doi: 10.1002/bimj.201800274 – volume: 41 start-page: S504 issue: suppl 7 year: 2025 ident: 80679_CR11 publication-title: Clin. Infect. Dis. – volume: 44 start-page: 837 issue: 3 year: 1988 ident: 80679_CR32 publication-title: Biometrics doi: 10.2307/2531595 – volume: 40 start-page: 37 year: 2017 ident: 80679_CR7 publication-title: Eur. J. Intern. Med. doi: 10.1016/j.ejim.2017.02.002 – ident: 80679_CR3 doi: 10.1016/j.jhin.2020.03.020 – ident: 80679_CR16 – volume: 81 start-page: e16 issue: 2 year: 2020 ident: 80679_CR13 publication-title: J Infect. doi: 10.1016/j.jinf.2020.04.021 – volume: 20 start-page: 425 issue: 4 year: 2020 ident: 80679_CR25 publication-title: Lancet Infect. Dis. doi: 10.1016/S1473-3099(20)30086-4 – ident: 80679_CR9 doi: 10.1001/jama.2020.1585 – ident: 80679_CR12 – volume: 48 start-page: 451 issue: 4 year: 2020 ident: 80679_CR30 publication-title: Crit. Care Med. doi: 10.1097/CCM.0000000000004207 – volume: 12 start-page: 12493 issue: 13 year: 2020 ident: 80679_CR15 publication-title: Aging (Albany NY). doi: 10.18632/aging.103579 – volume: 94 start-page: 496 year: 1999 ident: 80679_CR31 publication-title: J. Am. Stat. Assoc. doi: 10.1080/01621459.1999.10474144 – ident: 80679_CR1 – ident: 80679_CR29 – volume: 40 start-page: 373 issue: 5 year: 1987 ident: 80679_CR6 publication-title: J. Chronic Dis. doi: 10.1016/0021-9681(87)90171-8 – ident: 80679_CR10 doi: 10.1001/jama.2020.6775 – ident: 80679_CR22 doi: 10.1093/eurheartj/ehu131 – volume: 56 start-page: 308 issue: 3 year: 2019 ident: 80679_CR17 publication-title: Clin. Rev. Allergy Immunol. doi: 10.1007/s12016-017-8648-x – ident: 80679_CR4 doi: 10.1016/j.tmaid.2020.101623 – ident: 80679_CR19 doi: 10.1016/S2213-2600(20)30117-X – volume: 124 start-page: 999 year: 1996 ident: 80679_CR21 publication-title: Ann. Intern. Med. doi: 10.7326/0003-4819-124-11-199606010-00008 – volume: 35 start-page: 2665 year: 2012 ident: 80679_CR20 publication-title: Diab. Care doi: 10.2337/dc12-0788 – volume: 315 start-page: 801 year: 2016 ident: 80679_CR28 publication-title: JAMA doi: 10.1001/jama.2016.0287 – volume: 395 start-page: 1054 issue: 10229 year: 2020 ident: 80679_CR8 publication-title: Lancet doi: 10.1016/S0140-6736(20)30566-3 – volume: 26 start-page: 2389 issue: 11 year: 2007 ident: 80679_CR5 publication-title: Stat. Med. doi: 10.1002/sim.2712 |
| SSID | ssj0000529419 |
| Score | 2.4222643 |
| Snippet | An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The aim of... Abstract An accurate prediction of the clinical outcomes of European patients requiring hospitalisation for Coronavirus Disease 2019 (COVID-19) is lacking. The... |
| SourceID | doaj pubmedcentral proquest pubmed crossref springer |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 1137 |
| SubjectTerms | 692/699 692/699/255 692/699/255/2514 Aged Aged, 80 and over Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - mortality Female Hospital Mortality Humanities and Social Sciences Humans Italy - epidemiology Male Middle Aged Mortality multidisciplinary Patients Registries - statistics & numerical data Risk analysis Risk Assessment Risk factors Science Science (multidisciplinary) |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3daxQxEA9SEHwRv12tEsEHRUPztZvNYz2uVKEWqoW-hSSb2IO6J3d7Bf8J_2Yn2dzZ8_PF10wSZjOTnZlM8huEnjsfmYrCEgi7OJG-Y8R5r4iijZMebISI6aHw0fvm8FS-O6vPrpT6SnfCRnjgceH2tKWRSyWkVWDsQd2C1TLw1jOg1HVMf1-q6ZVgakT15loyXV7JUNHuLcFSpddkEC216fCE8C1LlAH7f-dl_npZ8qeMaTZEB7fQzeJB4v2R89voWujvoOtjTcmvd9G3SfaEYShJ18axLagjeB6xT3AF9nK2WC1xycxgMM0az3pyXgqI4M_ZIQfnHFqxxTmxExY9fjvkIxGcOQw4vUvBH472hyHM8eT4ctbBPCfTT7l6HH4BlMnxyfTlPXR6MP04OSSl6ALxddsOpOuks57zEKLrdM0bTyVzXITQ6oZHIAgRI0hegWcDgvBdR0Geijpdi-CiuI92-nkfHiLsPETqDAYEAXMEqVn0ilkrG2mTp1EhthaA8QWRPBXGuDA5My5aMwrNgNBMFprhFXq1GfNlxOP4a-83Sa6bnglLOzeAhpmiYeZfGlah3bVWmLLBlwYGKAHRNYeveLYhw9ZM-Rbbh_kq92kTfqFoKvRgVKINJ0KAH9pq4FBtqdcWq9uUfnae4b9h0gbWvkKv14r4g60_L8Wj_7EUj9ENnu70UEaY2EU7w2IVnoBTNrinef99B60YMYU priority: 102 providerName: Directory of Open Access Journals – databaseName: Scholars Portal Journals: Open Access dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfR1db9QwLJqGkHhBfFM2UJB4AEGg-WjTPiA0TjcNpDFpcNLeojRNtpNGy3q9if0JfjNOmh46OPZax5ETO7UdxzZCLyrjqHRcE3C7GBGmpqQyRhKZ5pUwoCO484nCh1_yg5n4fJKdbKGx3VHcwMVG1873k5p1529_Xlx9gAP_fkgZL94tQAn5RDFwhAp_L0Lgl3wjxIv8U75o7g-1vlkpaBlzZzajrumnUMZ_k-357xPKv-KoQT3t30G3o12J9wZBuIu2bHMP3Rw6TV7dR78mwT4GVOIfk2Mda5Hg1mHjixjoy3m3XOAYr8GgsEs8b8hZbCuCv4cdApMdvmKNQ7jHdg3-1IeLEhwotNhnq-Cvh3t9b1s8Obqc1zDP8fQ09JTDLwEyOTqevnqAZvvTb5MDElsxEJMVRU_qWlTaMGatq-oyY7lJBa0Yt7Yoc-YAwLlzIA8S7B1hmanrFLgs06rMuK0cf4i2m7axjxGuDPjvFBAshzmsKKkzkmotcqG9_ZEgOjJAmVin3LfLOFchXs4LNTBNAdNUYJpiCXq9wvkxVOm4dvRHz9fVSF9hO3xou1MVD6wqdeqYkFxoCUYm_OasLmFhhaEAyTKXoN1RKtQotQoQJAefm8Eqnq_AcGB9FEY3tl2GMYWvasjzBD0ahGhFCedgnRYlUCjXxGuN1HVIMz8LRcFh0hz2PkFvRkH8Q9b_t-LJ9avYQbeYf8OTUkL5Ltruu6V9CkZYXz0LJ-s3FL0tJg priority: 102 providerName: Scholars Portal – databaseName: HAS SpringerNature Open Access 2022 dbid: AAJSJ link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlR1daxQxMJQrgi_it6dVIvigaHDzsZvs43lcqQe10FroW8hmk_ZAd-Vur-Cf8Dc7yWZXTqvg604mzGYmmUnmC6FXlfVUem4IXLsYEbampLJWEpkVlbCgI7gPicLHn4qjc7G8yC_2EBtyYWLQfixpGY_pITrs_QYUTUgGg8uOCm8fBI7dfSXh-J2g_dlsebYcX1aC70rQMmXIZFzdgLyjhWKx_psszD8DJX_zlkYldHgX3UnWI5719N5De665j271_SS_P0A_5tEKBlQSQsaxSRVHcOuxDaUKzPVqvd3g5JXBoJZLvGrIVWoegr9GYxwMc_iKDY5OHbdu8McuPofgSKHDIScFnx3Pus61eH5yvaphntPFZewch18DZH5yunjzEJ0fLj7Pj0hquEBsrlRH6lpUxjLmnK_qMmeFzQStGHdOlQXzAODce-C6BKtGOGbrOgNeyqwqc-4qzx-hSdM27gnClYVbOgUEx2EOJ0rqraTGiEKYYGVMER0YoG2qRh6aYnzR0SvOle6ZpoFpOjJNsyl6O-J862tx_HP0h8DXcWSoox0_tOtLneRKlybzTEgujARTEg4zZ0r4MWUpQPLcT9HBIBU6be6NBgTJ4WbN4C9ejmDYlsHXYhrXbuMYFWoX8mKKHvdCNFLCOdigqgQK5Y547ZC6C2lWV7H0N0xawNpP0btBEH-R9felePp_w5-h2yxE7mSUUH6AJt16656D6dVVL9Je-wmixCku priority: 102 providerName: Springer Nature |
| Title | Competing-risk analysis of coronavirus disease 2019 in-hospital mortality in a Northern Italian centre from SMAtteo COvid19 REgistry (SMACORE) |
| URI | https://link.springer.com/article/10.1038/s41598-020-80679-2 https://www.ncbi.nlm.nih.gov/pubmed/33441892 https://www.proquest.com/docview/2477382521 https://www.proquest.com/docview/2478038936 https://pubmed.ncbi.nlm.nih.gov/PMC7806993 https://doaj.org/article/9a0f24734a7545488ea94e28c19a055f |
| Volume | 11 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3da9swEBdby2AvY99z1wUN9rCxiVoftuynkZqULpB2pCvkzciy1AY2u02cwv6J_c07yUpK9tEXG3SSOPtO0k930h1C7yptqbRcEdh2MSJ0TUmltSQyTiuhYY3g1l0Unpykx-diPEtmweC2DMcq13Oin6jrVjsb-QETUnLYzjD6-eqauKxRzrsaUmjcR7sUkIhL3SBncmNjcV4sQfNwVybm2cES1it3pwz2TJkzoRC2tR75sP3_wpp_H5n8w2_ql6Ojx-hRwJF42Av-CbpnmqfoQZ9Z8ucz9KvweBiaEnd4HKsQewS3FmsXtEDdzBerJQ7-GQwLdI7nDbkMaUTwDw_LAaJDKVbYu3fMosFfOm8YwZ5Dg93tFHw2GXadaXFxejOvoZ_p6MLnkMPvgVKcTkcfnqPzo9G34piE1AtEJ1nWkboWldKMGWOrOk9YqmNBK8aNyfKUWSBwbi3IXwK-EYbpuo5BqjKu8oSbyvIXaKdpG_MK4UrDfp1CA8OhDyNyarWkSolUKIc3IkTXAih1iEvu0mN8L71_nGdlL7QShFZ6oZUsQh83ba76qBx31j50ct3UdBG1fUG7uCjDAC1zFVvQMS6UBFAJ05pROXxYpilQksRGaH-tFWUY5svyVikj9HZDhgHqvC6qMe3K18lcFEOeRuhlr0QbTjgHNJrlwKHcUq8tVrcpzfzSBwGHTlP49xH6tFbEW7b-_yv27v6K1-ghc2d2Ykoo30c73WJl3gDo6qqBH1kDtDscjs_G8D4cnXydQmmRFgNvyIDnRGS_AWU2L78 |
| linkProvider | ProQuest |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtR3ZbhMx0CqpELwgbhYKGAkkEFhdH3s9VKgNqVLapCi0Ut8Wr9duI8FuSTZF_Qk-iW9j7HhThaNvfd2xLXtnPKdnBqGXhTI0MVwSMLsYEaqkpFAqIUkYF0KBjODGJgoPhnH_UHw8io5W0K82F8Y-q2x5omPUZa2sj3ydiSThYM4w-v70O7Fdo2x0tW2hIX1rhXLDlRjziR27-vwHmHDTjZ0PgO9XjG33Drp94rsMEBWlaUPKUhRSMaa1KcosYrEKBS0Y1zrNYmYAwLkxcNQERLnQTJVlCAdIwiKLuC4Mh3WvoVVhHSgdtLrVG34aLbw8No4maOazdUKerk9BYtqsNrDaUuvEIWxJIrrGAf_Sdv9-tPlH5NYJxO3b6JbXZPHmnPTuoBVd3UXX570tz--hn12nkcNUYp-vY-mrn-DaYGXLJsiz8WQ2xT5ChEFFyPC4Iie-kQn-5gwDMBLgK5bYBZj0pMI7jXPNYLdDjW1-DP482GwaXePu_tm4hHVGvWPXxQ6_Bkh3f9R7cx8dXglaHqBOVVf6EcKF0gWnMEFzWEOLjBqVUClFLKTVeAJEWwTkyldGtw06vuYuQs_TfI60HJCWO6TlLEBvF3NO53VBLh29ZfG6GGlrersP9eQ49ywiz2RogMq5kAmotcBYtczgYKmiAIkiE6C1lipyz2im-cW1CNCLBRhYhI37yErXMzcmtXUUeRygh3MiWuyEc9CH0wx2mCyR19JWlyHV-MSVIYdFY_j3AXrXEuLFtv7_Kx5fforn6Eb_YLCX7-0Md5-gm8y-IAopoXwNdZrJTD8FFbApnvl7htGXq77avwH58m_j |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtR3LbtQw0CpFIC6IN4ECRgIJBNbGj8TJAaGy3VWX0hYVKu0tOI7drtQmZTdb1J_gg_g6xk6y1fLordeMbY0z4_GM54XQi1xbKi1XBMwuRoQuKMm1lkSGcS403BHcukTh7Z14c198HEfjFfSry4VxYZWdTPSCuqi0eyPvMSElB3OG0Z5twyI-bwzfn3wnroOU87R27TQaFtkyZz_AfJu9G20ArV8yNhx87W-StsMA0VGS1KQoRK40Y8bYvEgjFutQ0JxxY5I0ZhYAnFsL25RwjQvDdFGEgLwM8zTiJrcc1r2CrkouhGsbIcdy8b7jPGiCpm2eTsiT3gzuSpfPBvZa4p5vCFu6C33LgH_puX-Ha_7hs_VX4fAWutnqsHi9YbrbaMWUd9C1pqvl2V30s-91cZhKXOA6Vm3dE1xZrF3BBHU6mc5nuPUNYVAOUjwpyWHbwgQfe5MAzAP4ihX2riUzLfGo9o8y2GNosMuMwV-21-vaVLi_ezopYJ29wYHvX4dfAaS_uzd4fQ_tXwpR7qPVsirNQ4RzbXJOYYLhsIYRKbVaUqVELJTTdQJEOwJkuq2J7lpzHGXeN8-TrCFaBkTLPNEyFqA3izknTUWQC0d_cHRdjHTVvP2HanqQtcIhS1Vogb-5UBIUWhCpRqWwsURTgESRDdBaxxVZK2Jm2fmBCNDzBRiEg_P4qNJUcz8mcRUUeRygBw0TLTDhwLQ0SQFDucReS6guQ8rJoS9ADovG8O8D9LZjxHO0_v8rHl28i2foOhzo7NNoZ-sxusFc6FBICeVraLWezs0T0P3q_Kk_ZBh9u-xT_Rv0WW1_ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Competing-risk+analysis+of+coronavirus+disease+2019+in-hospital+mortality+in+a+Northern+Italian+centre+from+SMAtteo+COvid19+REgistry+%28SMACORE%29&rft.jtitle=Scientific+reports&rft.au=Zuccaro+Valentina&rft.au=Ciro%2C+Celsa&rft.au=Sambo+Margherita&rft.au=Battaglia+Salvatore&rft.date=2021-01-13&rft.pub=Nature+Publishing+Group&rft.eissn=2045-2322&rft.volume=11&rft.issue=1&rft_id=info:doi/10.1038%2Fs41598-020-80679-2&rft.externalDBID=HAS_PDF_LINK |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2045-2322&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2045-2322&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2045-2322&client=summon |