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The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection
COVID-19 and dengue disease are challenging to tell apart because they have similarities in clinical and laboratory features during the acute phase of infection, leading to misdiagnosis and delayed treatment. The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 no...
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Published in: | Tropical medicine and infectious disease 2022-01, Vol.7 (2), p.20 |
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creator | Osuna-Ramos, Juan Fidel Reyes-Ruiz, José Manuel Ochoa-Ramírez, Luis Antonio De Jesús-González, Luis Adrián Ramos-Payán, Rosalío Farfan-Morales, Carlos Noe Romero-Utrilla, Alejandra Ríos-Burgueño, Efrén Rafael Rodríguez-Millán, José Del Ángel, Rosa María Velarde-Félix, Jesús Salvador |
description | COVID-19 and dengue disease are challenging to tell apart because they have similarities in clinical and laboratory features during the acute phase of infection, leading to misdiagnosis and delayed treatment. The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 non-critical patients from non-severe dengue cases between the second and eleventh day after symptom onset. A total of 288 patients infected with SARS-CoV-2 (n = 105) or dengue virus (n = 183) were included in this study. Neutrophil, platelet, and lymphocyte counts were used to calculate the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the neutrophil-lymphocyte*platelet ratio (NLPR). The logistic regression and ROC curves analysis revealed that neutrophil and platelet counts, NLR, LPR, and NLPR were higher in COVID-19 than dengue. The multivariate predictive model showed that the neutrophils, platelets, and NLPR were independently associated with COVID-19 with a good fit predictive value (
= 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84-0.91), platelet (AUC = 0.89, 95% CI = 0.85-0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84-0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94-0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions. |
doi_str_mv | 10.3390/tropicalmed7020020 |
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= 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84-0.91), platelet (AUC = 0.89, 95% CI = 0.85-0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84-0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94-0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions.</description><identifier>ISSN: 2414-6366</identifier><identifier>EISSN: 2414-6366</identifier><identifier>DOI: 10.3390/tropicalmed7020020</identifier><identifier>PMID: 35202215</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Age ; Blood ; Blood platelets ; Coronaviruses ; COVID-19 ; dengue ; Dengue fever ; Ethics ; Hematology ; Hospitals ; Infections ; Inflammatory diseases ; Laboratories ; Liver cirrhosis ; Lymphocytes ; Neutrophils ; neutrophil–lymphocyte ratio ; Pandemics ; peripheral blood cells count neutrophils ; Pneumonia ; predictors ; Public health ; Serology ; Severe acute respiratory syndrome coronavirus 2 ; Statistical analysis ; Thrombocytopenia</subject><ispartof>Tropical medicine and infectious disease, 2022-01, Vol.7 (2), p.20</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c496t-7c03a561d1295a2e85b59795feecab0f5e92633c08733a7f94db6c7b3041c8173</citedby><cites>FETCH-LOGICAL-c496t-7c03a561d1295a2e85b59795feecab0f5e92633c08733a7f94db6c7b3041c8173</cites><orcidid>0000-0001-7500-7571 ; 0000-0003-1415-6260 ; 0000-0002-6785-2035 ; 0000-0001-8280-9812 ; 0000-0002-2379-8591</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2633197029?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2633197029?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25752,27923,27924,37011,37012,38515,43894,44589,53790,53792,74183,74897</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35202215$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Osuna-Ramos, Juan Fidel</creatorcontrib><creatorcontrib>Reyes-Ruiz, José Manuel</creatorcontrib><creatorcontrib>Ochoa-Ramírez, Luis Antonio</creatorcontrib><creatorcontrib>De Jesús-González, Luis Adrián</creatorcontrib><creatorcontrib>Ramos-Payán, Rosalío</creatorcontrib><creatorcontrib>Farfan-Morales, Carlos Noe</creatorcontrib><creatorcontrib>Romero-Utrilla, Alejandra</creatorcontrib><creatorcontrib>Ríos-Burgueño, Efrén Rafael</creatorcontrib><creatorcontrib>Rodríguez-Millán, José</creatorcontrib><creatorcontrib>Del Ángel, Rosa María</creatorcontrib><creatorcontrib>Velarde-Félix, Jesús Salvador</creatorcontrib><title>The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection</title><title>Tropical medicine and infectious disease</title><addtitle>Trop Med Infect Dis</addtitle><description>COVID-19 and dengue disease are challenging to tell apart because they have similarities in clinical and laboratory features during the acute phase of infection, leading to misdiagnosis and delayed treatment. The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 non-critical patients from non-severe dengue cases between the second and eleventh day after symptom onset. A total of 288 patients infected with SARS-CoV-2 (n = 105) or dengue virus (n = 183) were included in this study. Neutrophil, platelet, and lymphocyte counts were used to calculate the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the neutrophil-lymphocyte*platelet ratio (NLPR). The logistic regression and ROC curves analysis revealed that neutrophil and platelet counts, NLR, LPR, and NLPR were higher in COVID-19 than dengue. The multivariate predictive model showed that the neutrophils, platelets, and NLPR were independently associated with COVID-19 with a good fit predictive value (
= 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84-0.91), platelet (AUC = 0.89, 95% CI = 0.85-0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84-0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94-0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions.</description><subject>Age</subject><subject>Blood</subject><subject>Blood platelets</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>dengue</subject><subject>Dengue fever</subject><subject>Ethics</subject><subject>Hematology</subject><subject>Hospitals</subject><subject>Infections</subject><subject>Inflammatory diseases</subject><subject>Laboratories</subject><subject>Liver cirrhosis</subject><subject>Lymphocytes</subject><subject>Neutrophils</subject><subject>neutrophil–lymphocyte ratio</subject><subject>Pandemics</subject><subject>peripheral blood cells count neutrophils</subject><subject>Pneumonia</subject><subject>predictors</subject><subject>Public health</subject><subject>Serology</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Statistical analysis</subject><subject>Thrombocytopenia</subject><issn>2414-6366</issn><issn>2414-6366</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNplkt9rFDEQxxdRbKn9B3yQgC--XM2v3SQvQt2zelCoD62vIZtM7nLsbc4kK_jfm-vV0ioEEma-82Hmm2matwRfMKbwx5LiPlgz7sAJTHE9L5pTyglfdKzrXj55nzTnOW8xxkS2uOP4dXPCWoopJe1pE243gO4y-HmcIGcUPfoOKew3kMyIPo8xOtTDOKI-zlPJqES0DLmEaT2HvEH9zY_VckEU8inu0BJqGJCbU82jSzsXQKvJgy0hTm-aV96MGc4f7rPm7urLbf9tcX3zddVfXi8sV11ZCIuZaTviCFWtoSDboVVCtR7AmgH7FhTtGLNYCsaM8Iq7obNiYJgTK4lgZ83qyHXRbPU-hZ1Jv3U0Qd8HYlprk0qwI2gMkipJmfOd4VQ5RYySwgkz8MFxRivr05G1n4dqtIWpVFueQZ9nprDR6_hLSymUoqoCPjwAUvw5Qy56F7KtfpoJ4pz1YRTJheraKn3_j3Qb5zRVq-5VRNVvPgDpUWVTzDmBf2yGYH1YDP3_YtSid0_HeCz5uwbsDxdstd4</recordid><startdate>20220130</startdate><enddate>20220130</enddate><creator>Osuna-Ramos, Juan Fidel</creator><creator>Reyes-Ruiz, José Manuel</creator><creator>Ochoa-Ramírez, Luis Antonio</creator><creator>De Jesús-González, Luis Adrián</creator><creator>Ramos-Payán, Rosalío</creator><creator>Farfan-Morales, Carlos Noe</creator><creator>Romero-Utrilla, Alejandra</creator><creator>Ríos-Burgueño, Efrén Rafael</creator><creator>Rodríguez-Millán, José</creator><creator>Del Ángel, Rosa María</creator><creator>Velarde-Félix, Jesús Salvador</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7500-7571</orcidid><orcidid>https://orcid.org/0000-0003-1415-6260</orcidid><orcidid>https://orcid.org/0000-0002-6785-2035</orcidid><orcidid>https://orcid.org/0000-0001-8280-9812</orcidid><orcidid>https://orcid.org/0000-0002-2379-8591</orcidid></search><sort><creationdate>20220130</creationdate><title>The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection</title><author>Osuna-Ramos, Juan Fidel ; 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The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 non-critical patients from non-severe dengue cases between the second and eleventh day after symptom onset. A total of 288 patients infected with SARS-CoV-2 (n = 105) or dengue virus (n = 183) were included in this study. Neutrophil, platelet, and lymphocyte counts were used to calculate the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the neutrophil-lymphocyte*platelet ratio (NLPR). The logistic regression and ROC curves analysis revealed that neutrophil and platelet counts, NLR, LPR, and NLPR were higher in COVID-19 than dengue. The multivariate predictive model showed that the neutrophils, platelets, and NLPR were independently associated with COVID-19 with a good fit predictive value (
= 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84-0.91), platelet (AUC = 0.89, 95% CI = 0.85-0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84-0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94-0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35202215</pmid><doi>10.3390/tropicalmed7020020</doi><orcidid>https://orcid.org/0000-0001-7500-7571</orcidid><orcidid>https://orcid.org/0000-0003-1415-6260</orcidid><orcidid>https://orcid.org/0000-0002-6785-2035</orcidid><orcidid>https://orcid.org/0000-0001-8280-9812</orcidid><orcidid>https://orcid.org/0000-0002-2379-8591</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Age Blood Blood platelets Coronaviruses COVID-19 dengue Dengue fever Ethics Hematology Hospitals Infections Inflammatory diseases Laboratories Liver cirrhosis Lymphocytes Neutrophils neutrophil–lymphocyte ratio Pandemics peripheral blood cells count neutrophils Pneumonia predictors Public health Serology Severe acute respiratory syndrome coronavirus 2 Statistical analysis Thrombocytopenia |
title | The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection |
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