{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T20:10:43Z","timestamp":1793304643631,"version":"4.5.0"},"reference-count":21,"publisher":"BMJ","issue":"4","license":[{"start":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T00:00:00Z","timestamp":1681689600000},"content-version":"unspecified","delay-in-days":16,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2023,3,28]]},"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>COVID-19 is currently diagnosed in hospital settings. An easy and practical diagnosis of COVID-19 is needed in primary care. For this purpose, the usability of complete blood count in the diagnosis of COVID-19 was investigated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Retrospective, cross-sectional study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>Single-centre study in a tertiary university hospital in Erzurum, Turkey.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>Between March 2020 and February 2021, patients aged 18\u201370 years who applied to the hospital and underwent both complete blood count and reverse-transcription-PCR tests for COVID-19 were included and compared. Conditions affecting the test parameters (oncological\u2013haematological conditions, chronic diseases, drug usage) were excluded.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Outcome Measure<\/jats:title>\n                    <jats:p>The complete blood count and COVID-19 results of eligible patients identified using diagnostic codes [U07.3 (COVID\u201319) or Z03.8 (observation for other suspected diseases and conditions)] were investigated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Of the 978 patients included, 39.4% (n=385) were positive for COVID-19 and 60.6% (n=593) were negative. The mean age was 41.5\u00b114.5 years, and 53.9% (n=527) were male. COVID-19-positive patients were found to have significantly lower leucocyte, neutrophil, lymphocyte, monocyte, basophil, platelet and immature granulocyte (IG) values (p&lt;0.001). Neutrophil\/lymphocyte, neutrophil\/monocyte and IG\/lymphocyte ratios were also found to be significantly decreased (p&lt;0.001). With logistic regression analysis, low lymphocyte count (OR 0.695; 95%\u2009CI 0.597 to 0.809) and low red cell distribution width-coefficient of variation (RDW-CV) (OR 0.887; 95%\u2009CI 0.818 to 0.962) were significantly associated with COVID-19 positivity. In receiver operating characteristic analysis, the cut-off values of lymphocyte and RDW-CV were 0.745 and 12.35, respectively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Although our study was designed retrospectively and reflects regional data, it is important to determine that low lymphocyte count and RDW-CV can be used in the diagnosis of COVID-19 in primary care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2022-069493","type":"journal-article","created":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T10:46:17Z","timestamp":1681728377000},"page":"e069493","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":6,"title":["How to diagnose COVID-19 in family practice? Usability of complete blood count as a COVID-19 diagnostic tool: a cross-sectional study in Turkey"],"prefix":"10.1136","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8486-9915","authenticated-orcid":false,"given":"Mustafa","family":"Bayraktar","sequence":"first","affiliation":[{"name":"Family Medicine, Ataturk University, Erzurum, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erdal","family":"Tekin","sequence":"additional","affiliation":[{"name":"Emergency Medicine, Ataturk University, Erzurum, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehmet Nuri","family":"Kocak","sequence":"additional","affiliation":[{"name":"Neurology, Ataturk University, Erzurum, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2023,4,17]]},"reference":[{"key":"2025121514202839000_13.4.e069493.1","unstructured":"WHO timeline: WHO\u2019s COVID\u201319 response: world health organization [15.11.2022]. n.d. Available: https:\/\/www.who.int\/emergencies\/diseases\/novel-coronavirus-2019\/interactive-timeline#event-69"},{"key":"2025121514202839000_13.4.e069493.2","unstructured":"WHO coronavirus disease (COVID\u201319) dashboard: world health organization [15.11.2022]. n.d. Available: https:\/\/covid19.who.int\/"},{"key":"2025121514202839000_13.4.e069493.3","unstructured":"Diagnostic testing for SARS-cov-2: world health organization [15.11.2022]. n.d. Available: https:\/\/www.who.int\/publications\/i\/item\/diagnostic-testing-for-sars-cov-2"},{"key":"2025121514202839000_13.4.e069493.4","doi-asserted-by":"crossref","DOI":"10.3390\/healthcare10091780","article-title":"The cost-effectiveness of requesting a complete blood count (CBC) in the management of COVID-19 in saudi arabia","volume":"10","author":"Sayed","year":"2022","journal-title":"Healthcare (Basel)"},{"key":"2025121514202839000_13.4.e069493.5","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1002\/jmv.25819","article-title":"Neutrophil-to-lymphocyte ratio and lymphocyte-to-C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID-19): A meta-analysis","volume":"92","author":"Lagunas-Rangel","year":"2020","journal-title":"J Med Virol"},{"key":"2025121514202839000_13.4.e069493.6","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1080\/20009666.2020.1816276","article-title":"Hematological parameters predicting severity and mortality in COVID-19 patients of Pakistan: a retrospective comparative analysis","volume":"10","author":"Asghar","year":"2020","journal-title":"J Community Hosp Intern Med Perspect"},{"key":"2025121514202839000_13.4.e069493.7","doi-asserted-by":"crossref","DOI":"10.7717\/peerj.9482","article-title":"Hemogram data as a tool for decision-making in COVID-19 management: applications to resource scarcity scenarios","volume":"8","author":"Avila","year":"2020","journal-title":"PeerJ"},{"key":"2025121514202839000_13.4.e069493.8","doi-asserted-by":"publisher","DOI":"10.15537\/smj.2021.42.4.20200818"},{"key":"2025121514202839000_13.4.e069493.9","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1515\/cclm-2022-0182","article-title":"How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory data","volume":"60","author":"Carobene","year":"2022","journal-title":"Clin Chem Lab Med"},{"key":"2025121514202839000_13.4.e069493.10","doi-asserted-by":"crossref","DOI":"10.1007\/s13755-021-00167-3","article-title":"External validation of machine learning models for COVID-19 detection based on complete blood count","volume":"9","author":"Campagner","year":"2021","journal-title":"Health Inf Sci Syst"},{"key":"2025121514202839000_13.4.e069493.11","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1515\/cclm-2020-1294","article-title":"Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests","volume":"59","author":"Cabitza","year":"2020","journal-title":"Clin Chem Lab Med"},{"key":"2025121514202839000_13.4.e069493.12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcv.2020.104502"},{"key":"2025121514202839000_13.4.e069493.13","doi-asserted-by":"crossref","first-page":"e114","DOI":"10.7861\/clinmed.2020-0373","article-title":"Complete blood count might help to identify subjects with high probability of testing positive to SARS-cov-2","volume":"20","author":"Formica","year":"2020","journal-title":"Clin Med (Lond)"},{"key":"2025121514202839000_13.4.e069493.14","doi-asserted-by":"crossref","first-page":"106705","DOI":"10.1016\/j.intimp.2020.106705","article-title":"Use of machine learning and artificial intelligence to predict SARS-cov-2 infection from full blood counts in a population","volume":"86","author":"Banerjee","year":"2020","journal-title":"Int Immunopharmacol"},{"key":"2025121514202839000_13.4.e069493.15","doi-asserted-by":"crossref","first-page":"3295","DOI":"10.1007\/s00500-021-05810-5","article-title":"Simple hemogram to support the decision-making of COVID-19 diagnosis using clusters analysis with self-organizing maps neural network","volume":"27","author":"Souza","year":"2023","journal-title":"Soft Comput"},{"key":"2025121514202839000_13.4.e069493.16","doi-asserted-by":"crossref","unstructured":"Velazquez S , Madurga R , Castellano JM , et al . Hemogram-derived ratios as prognostic markers of ICU admission in COVID-19. 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