Development and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score
Introduction. Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods....
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creator | Zdravkovic, Marija Popadic, Viseslav Klasnja, Slobodan Pavlovic, Vedrana Aleksic, Aleksandra Milenkovic, Marija Crnokrak, Bogdan Balint, Bela Todorovic-Balint, Milena Mrda, Davor Zdravkovic, Darko Toskovic, Borislav Brankovic, Marija Markovic, Olivera Bjekic-Macut, Jelica Djuran, Predrag Memon, Lidija Stojanovic, Ana Brajkovic, Milica Todorovic, Zoran Hadzi-Djokic, Jovan Jovanovic, Igor Nikolic, Dejan Cvijanovic, Dane Milic, Natasa |
description | Introduction. Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID-19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID-19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL-6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID-19. Results. The study population included 160 COVID-19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety-six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at-risk (score>1). In addition, patients were considered at high risk with a risk score>2. By applying the risk model to the validation cohort (n=304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805-0.921) and 0.665 (95% CI 0.598-0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID-19 disease at admission to ICU. Further external validation on a larger group of patients is needed to |
doi_str_mv | 10.1155/2021/6654388 |
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Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID-19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID-19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL-6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID-19. Results. The study population included 160 COVID-19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety-six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at-risk (score>1). In addition, patients were considered at high risk with a risk score>2. By applying the risk model to the validation cohort (n=304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805-0.921) and 0.665 (95% CI 0.598-0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID-19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.</description><identifier>ISSN: 1942-0900</identifier><identifier>EISSN: 1942-0994</identifier><identifier>DOI: 10.1155/2021/6654388</identifier><identifier>PMID: 34257816</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Adult ; Age ; Aged ; Aged, 80 and over ; Cardiovascular disease ; Coronaviruses ; COVID-19 ; COVID-19 - blood ; COVID-19 - mortality ; COVID-19 - therapy ; Diabetes ; Female ; Hospitalization ; Humans ; Hypertension ; Intensive Care Units ; Laboratories ; Male ; Middle Aged ; Models, Biological ; Mortality ; Multivariate analysis ; Oxygen - administration & dosage ; Oxygen - blood ; Patients ; Pneumonia ; Regression analysis ; Respiration, Artificial ; Risk Assessment ; SARS-CoV-2 - metabolism ; Ventilators</subject><ispartof>Oxidative medicine and cellular longevity, 2021, Vol.2021 (1), p.6654388-6654388</ispartof><rights>Copyright © 2021 Marija Zdravkovic et al.</rights><rights>Copyright © 2021 Marija Zdravkovic et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Marija Zdravkovic et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c448t-cec73690df089015e364b1bb84ee9230b04edffdb99399589328bc2f6bfcfe4a3</citedby><cites>FETCH-LOGICAL-c448t-cec73690df089015e364b1bb84ee9230b04edffdb99399589328bc2f6bfcfe4a3</cites><orcidid>0000-0003-4768-676X ; 0000-0002-3390-1599 ; 0000-0002-2334-7862 ; 0000-0002-2431-9388 ; 0000-0001-8869-9976 ; 0000-0002-0992-7481 ; 0000-0002-5154-8434 ; 0000-0001-7074-1187 ; 0000-0003-0675-6004 ; 0000-0002-9676-7198 ; 0000-0002-6708-3301 ; 0000-0002-5298-8722 ; 0000-0002-0958-8811 ; 0000-0003-2823-6245 ; 0000-0002-7737-0857 ; 0000-0002-7054-3778 ; 0000-0002-7367-8723 ; 0000-0002-6040-0183 ; 0000-0002-9349-6249 ; 0000-0003-4059-0263 ; 0000-0002-5957-0716 ; 0000-0003-3551-1428 ; 0000-0002-0571-5772 ; 0000-0001-8367-9511 ; 0000-0001-8987-2849</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245230/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245230/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4024,27923,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34257816$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kocic, Gordana</contributor><contributor>Gordana Kocic</contributor><creatorcontrib>Zdravkovic, Marija</creatorcontrib><creatorcontrib>Popadic, Viseslav</creatorcontrib><creatorcontrib>Klasnja, Slobodan</creatorcontrib><creatorcontrib>Pavlovic, Vedrana</creatorcontrib><creatorcontrib>Aleksic, Aleksandra</creatorcontrib><creatorcontrib>Milenkovic, Marija</creatorcontrib><creatorcontrib>Crnokrak, Bogdan</creatorcontrib><creatorcontrib>Balint, Bela</creatorcontrib><creatorcontrib>Todorovic-Balint, Milena</creatorcontrib><creatorcontrib>Mrda, Davor</creatorcontrib><creatorcontrib>Zdravkovic, Darko</creatorcontrib><creatorcontrib>Toskovic, Borislav</creatorcontrib><creatorcontrib>Brankovic, Marija</creatorcontrib><creatorcontrib>Markovic, Olivera</creatorcontrib><creatorcontrib>Bjekic-Macut, Jelica</creatorcontrib><creatorcontrib>Djuran, Predrag</creatorcontrib><creatorcontrib>Memon, Lidija</creatorcontrib><creatorcontrib>Stojanovic, Ana</creatorcontrib><creatorcontrib>Brajkovic, Milica</creatorcontrib><creatorcontrib>Todorovic, Zoran</creatorcontrib><creatorcontrib>Hadzi-Djokic, Jovan</creatorcontrib><creatorcontrib>Jovanovic, Igor</creatorcontrib><creatorcontrib>Nikolic, Dejan</creatorcontrib><creatorcontrib>Cvijanovic, Dane</creatorcontrib><creatorcontrib>Milic, Natasa</creatorcontrib><title>Development and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score</title><title>Oxidative medicine and cellular longevity</title><addtitle>Oxid Med Cell Longev</addtitle><description>Introduction. Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID-19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID-19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL-6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID-19. Results. The study population included 160 COVID-19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety-six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at-risk (score>1). In addition, patients were considered at high risk with a risk score>2. By applying the risk model to the validation cohort (n=304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805-0.921) and 0.665 (95% CI 0.598-0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID-19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.</description><subject>Adult</subject><subject>Age</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Cardiovascular disease</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - blood</subject><subject>COVID-19 - mortality</subject><subject>COVID-19 - therapy</subject><subject>Diabetes</subject><subject>Female</subject><subject>Hospitalization</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Intensive Care Units</subject><subject>Laboratories</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>Mortality</subject><subject>Multivariate analysis</subject><subject>Oxygen - administration & dosage</subject><subject>Oxygen - blood</subject><subject>Patients</subject><subject>Pneumonia</subject><subject>Regression analysis</subject><subject>Respiration, Artificial</subject><subject>Risk Assessment</subject><subject>SARS-CoV-2 - metabolism</subject><subject>Ventilators</subject><issn>1942-0900</issn><issn>1942-0994</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kU1vEzEQhlcIREvhxhlZ4oIES_25WfeAFCWURmqVStBeLa89TlztroN3NyX_hR-LVwkRcODkkeedZz7eLHtN8EdChDinmJLzohCcleWT7JRITnMsJX96jDE-yV503QPGBaOcPM9OGKdiUpLiNPs5hy3UYdNA2yPdWnSva29170OLgkMa3Qx177c6el3VgG4jWG_SB6CbYKFGLsQUxT5V9buxYra8X8xzItFtgiRoh-bQJLBvV-jKr9Zo-WO3ghZd1uER6R5NbeO7bmzXB7SY3V2g6WI-RV9NiPAye-Z03cGrw3uW3V1-_ja7yq-XXxaz6XVuOC_73ICZsEJi63ApMRHACl6Rqio5gKQMV5iDdc5WUjIpRSkZLStDXVE544BrdpZ92nM3Q9WANWnsqGu1ib7RcaeC9urvTOvXahW2qqRcpAYJ8O4AiOH7AF2v0lIG6lq3EIZOUSFIOjhjNEnf_iN9CENs03qKTlJeTAgfgR_2KhND10Vwx2EIVqPtarRdHWxP8jd_LnAU__Y5Cd7vBWvfWv3o_4_7BctNtWw</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Zdravkovic, 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and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score</title><author>Zdravkovic, Marija ; Popadic, Viseslav ; Klasnja, Slobodan ; Pavlovic, Vedrana ; Aleksic, Aleksandra ; Milenkovic, Marija ; Crnokrak, Bogdan ; Balint, Bela ; Todorovic-Balint, Milena ; Mrda, Davor ; Zdravkovic, Darko ; Toskovic, Borislav ; Brankovic, Marija ; Markovic, Olivera ; Bjekic-Macut, Jelica ; Djuran, Predrag ; Memon, Lidija ; Stojanovic, Ana ; Brajkovic, Milica ; Todorovic, Zoran ; Hadzi-Djokic, Jovan ; Jovanovic, Igor ; Nikolic, Dejan ; Cvijanovic, Dane ; Milic, Natasa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c448t-cec73690df089015e364b1bb84ee9230b04edffdb99399589328bc2f6bfcfe4a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>Age</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Cardiovascular disease</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 - blood</topic><topic>COVID-19 - mortality</topic><topic>COVID-19 - therapy</topic><topic>Diabetes</topic><topic>Female</topic><topic>Hospitalization</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Intensive Care Units</topic><topic>Laboratories</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Biological</topic><topic>Mortality</topic><topic>Multivariate analysis</topic><topic>Oxygen - administration & dosage</topic><topic>Oxygen - blood</topic><topic>Patients</topic><topic>Pneumonia</topic><topic>Regression analysis</topic><topic>Respiration, Artificial</topic><topic>Risk Assessment</topic><topic>SARS-CoV-2 - metabolism</topic><topic>Ventilators</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zdravkovic, Marija</creatorcontrib><creatorcontrib>Popadic, Viseslav</creatorcontrib><creatorcontrib>Klasnja, Slobodan</creatorcontrib><creatorcontrib>Pavlovic, Vedrana</creatorcontrib><creatorcontrib>Aleksic, Aleksandra</creatorcontrib><creatorcontrib>Milenkovic, Marija</creatorcontrib><creatorcontrib>Crnokrak, Bogdan</creatorcontrib><creatorcontrib>Balint, Bela</creatorcontrib><creatorcontrib>Todorovic-Balint, Milena</creatorcontrib><creatorcontrib>Mrda, Davor</creatorcontrib><creatorcontrib>Zdravkovic, Darko</creatorcontrib><creatorcontrib>Toskovic, Borislav</creatorcontrib><creatorcontrib>Brankovic, Marija</creatorcontrib><creatorcontrib>Markovic, Olivera</creatorcontrib><creatorcontrib>Bjekic-Macut, Jelica</creatorcontrib><creatorcontrib>Djuran, Predrag</creatorcontrib><creatorcontrib>Memon, Lidija</creatorcontrib><creatorcontrib>Stojanovic, Ana</creatorcontrib><creatorcontrib>Brajkovic, Milica</creatorcontrib><creatorcontrib>Todorovic, Zoran</creatorcontrib><creatorcontrib>Hadzi-Djokic, Jovan</creatorcontrib><creatorcontrib>Jovanovic, Igor</creatorcontrib><creatorcontrib>Nikolic, Dejan</creatorcontrib><creatorcontrib>Cvijanovic, Dane</creatorcontrib><creatorcontrib>Milic, Natasa</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Oxidative medicine and cellular longevity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zdravkovic, Marija</au><au>Popadic, Viseslav</au><au>Klasnja, Slobodan</au><au>Pavlovic, Vedrana</au><au>Aleksic, Aleksandra</au><au>Milenkovic, Marija</au><au>Crnokrak, Bogdan</au><au>Balint, Bela</au><au>Todorovic-Balint, Milena</au><au>Mrda, Davor</au><au>Zdravkovic, Darko</au><au>Toskovic, Borislav</au><au>Brankovic, Marija</au><au>Markovic, Olivera</au><au>Bjekic-Macut, Jelica</au><au>Djuran, Predrag</au><au>Memon, Lidija</au><au>Stojanovic, Ana</au><au>Brajkovic, Milica</au><au>Todorovic, Zoran</au><au>Hadzi-Djokic, Jovan</au><au>Jovanovic, Igor</au><au>Nikolic, Dejan</au><au>Cvijanovic, Dane</au><au>Milic, Natasa</au><au>Kocic, Gordana</au><au>Gordana Kocic</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score</atitle><jtitle>Oxidative medicine and cellular longevity</jtitle><addtitle>Oxid Med Cell Longev</addtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><issue>1</issue><spage>6654388</spage><epage>6654388</epage><pages>6654388-6654388</pages><issn>1942-0900</issn><eissn>1942-0994</eissn><abstract>Introduction. Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID-19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID-19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL-6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID-19. Results. The study population included 160 COVID-19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety-six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at-risk (score>1). In addition, patients were considered at high risk with a risk score>2. By applying the risk model to the validation cohort (n=304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805-0.921) and 0.665 (95% CI 0.598-0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID-19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>34257816</pmid><doi>10.1155/2021/6654388</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-4768-676X</orcidid><orcidid>https://orcid.org/0000-0002-3390-1599</orcidid><orcidid>https://orcid.org/0000-0002-2334-7862</orcidid><orcidid>https://orcid.org/0000-0002-2431-9388</orcidid><orcidid>https://orcid.org/0000-0001-8869-9976</orcidid><orcidid>https://orcid.org/0000-0002-0992-7481</orcidid><orcidid>https://orcid.org/0000-0002-5154-8434</orcidid><orcidid>https://orcid.org/0000-0001-7074-1187</orcidid><orcidid>https://orcid.org/0000-0003-0675-6004</orcidid><orcidid>https://orcid.org/0000-0002-9676-7198</orcidid><orcidid>https://orcid.org/0000-0002-6708-3301</orcidid><orcidid>https://orcid.org/0000-0002-5298-8722</orcidid><orcidid>https://orcid.org/0000-0002-0958-8811</orcidid><orcidid>https://orcid.org/0000-0003-2823-6245</orcidid><orcidid>https://orcid.org/0000-0002-7737-0857</orcidid><orcidid>https://orcid.org/0000-0002-7054-3778</orcidid><orcidid>https://orcid.org/0000-0002-7367-8723</orcidid><orcidid>https://orcid.org/0000-0002-6040-0183</orcidid><orcidid>https://orcid.org/0000-0002-9349-6249</orcidid><orcidid>https://orcid.org/0000-0003-4059-0263</orcidid><orcidid>https://orcid.org/0000-0002-5957-0716</orcidid><orcidid>https://orcid.org/0000-0003-3551-1428</orcidid><orcidid>https://orcid.org/0000-0002-0571-5772</orcidid><orcidid>https://orcid.org/0000-0001-8367-9511</orcidid><orcidid>https://orcid.org/0000-0001-8987-2849</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Age Aged Aged, 80 and over Cardiovascular disease Coronaviruses COVID-19 COVID-19 - blood COVID-19 - mortality COVID-19 - therapy Diabetes Female Hospitalization Humans Hypertension Intensive Care Units Laboratories Male Middle Aged Models, Biological Mortality Multivariate analysis Oxygen - administration & dosage Oxygen - blood Patients Pneumonia Regression analysis Respiration, Artificial Risk Assessment SARS-CoV-2 - metabolism Ventilators |
title | Development and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score |
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