<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-14T02:28:03Z</responseDate><request verb="GetRecord" identifier="oai:repisalud.isciii.es:20.500.12105/13398" metadataPrefix="marc">https://repisalud.isciii.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:repisalud.isciii.es:20.500.12105/13398</identifier><datestamp>2024-09-27T08:25:51Z</datestamp><setSpec>com_20.500.12105_19604</setSpec><setSpec>com_20.500.12105_2051</setSpec><setSpec>col_20.500.12105_19605</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Lopez-Escobar, Alejandro</subfield>
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      <subfield code="a">Madurga, Rodrigo</subfield>
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      <subfield code="a">Castellano, Jose Maria</subfield>
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      <subfield code="a">Velazquez, Sara</subfield>
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      <subfield code="a">Suárez Del Villar, Rafael</subfield>
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      <subfield code="a">Menendez, Justo</subfield>
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      <subfield code="a">Peixoto, Alejandro</subfield>
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      <subfield code="a">Jimeno, Sara</subfield>
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      <subfield code="a">Ventura, Paula Sol</subfield>
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      <subfield code="a">Ruiz de Aguiar, Santiago</subfield>
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      <subfield code="c">2021-03-26</subfield>
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      <subfield code="a">Infection by SARS-CoV2 has devastating consequences on health care systems. It is a global health priority to identify patients at risk of fatal outcomes. 1955 patients admitted to HM-Hospitales from 1 March to 10 June 2020 due to COVID-19, were were divided into two groups, 1310 belonged to the training cohort and 645 to validation cohort. Four different models were generated to predict in-hospital mortality. Following variables were included: age, sex, oxygen saturation, level of C-reactive-protein, neutrophil-to-platelet-ratio (NPR), neutrophil-to-lymphocyte-ratio (NLR) and the rate of changes of both hemogram ratios (VNLR and VNPR) during the first week after admission. The accuracy of the models in predicting in-hospital mortality were evaluated using the area under the receiver-operator-characteristic curve (AUC). AUC for models including NLR and NPR performed similarly in both cohorts: NLR 0.873 (95% CI: 0.849-0.898), NPR 0.875 (95% CI: 0.851-0.899) in training cohort and NLR 0.856 (95% CI: 0.818-0.895), NPR 0.863 (95% CI: 0.826-0.901) in validation cohort. AUC was 0.885 (95% CI: 0.885-0.919) for VNLR and 0.891 (95% CI: 0.861-0.922) for VNPR in the validation cohort. According to our results, models are useful in predicting in-hospital mortality risk due to COVID-19. The RIM Score proposed is a simple, widely available tool that can help identify patients at risk of fatal outcomes.</subfield>
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      <subfield code="a">Diagnostics (Basel). 2021; 11(4):596</subfield>
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      <subfield code="a">http://hdl.handle.net/20.500.12105/13398</subfield>
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      <subfield code="a">Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score).</subfield>
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