{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T05:08:45Z","timestamp":1772168925679,"version":"3.50.1"},"update-to":[{"DOI":"10.12688\/f1000research.151333.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000}}],"reference-count":72,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns3:p>\n                    Background COVID-19 disease has spread rapidly worldwide, causing high mortality. Accessible biomarkers capable of early identification of patients at risk of severe form are needed in clinical practice. The aim of the study was to determine the biological markers that predict a critical condition. Methods Retrospective study including patients with confirmed COVID-19 hospitalized between September 2020 and June 2021. The primary endpoint was progression to critical status within 7 days from admission. We defined two groups: Critical group: Patients who developed a critical condition or died or transferred to the ICU before or at 7\n                    <ns3:sup>th<\/ns3:sup>\n                    day. Non-critical group: Patients who remained in non-critical respiratory status until 7\n                    <ns3:sup>th<\/ns3:sup>\n                    day or discharged before or at 7\n                    <ns3:sup>th<\/ns3:sup>\n                    day. Results Our study included 456 patients, with a sex ratio of 1.32 and an average age of 62 years. At the 7\n                    <ns3:sup>th<\/ns3:sup>\n                    day of hospitalization, 115 (25.2%) patients were in the critical group and 341 (74.8%) patients were in the non-critical group. The univariate logistic regression indicated that laboratory findings between non-critical and critical groups showed that C-reactive protein (CRP) (p=0.047), D-Dimer (p=0.011), creatinine (0.026), creatine kinase (p=0.039), lactate dehydrogenase (p=0.04), and troponin (p=0.001) were all higher among patients in critical group. However, lymphocyte (p&lt;0.001) and platelet (p&lt;0.001) counts were significantly lower among the critical group. Multivariate logistic regression model, identified four independent risk factors: lymphopenia (OR=2.771, 95%CI=1.482-5.181, p=0.001), Neutrophil to Lymphocyte Ratio (NLR) (OR=2.286, 95%CI=1.461-3.578, p&lt;0.001), thrombocytopenia (OR=1.944, 95%CI=1.092-3.459, p=0.024), and CRP&gt;71.5 (OR=1.598, 95% CI=1.042-2.45, p=0.032) were associated to critical group. Conclusions Our results show the predictive value of lymphopenia, thrombocytopenia, high NLR and CRP levels to evaluate the prognosis of COVID-19 pneumonia. A prognostic score could be proposed for guiding clinical care and improving patient outcomes.\n                  <\/ns3:p>","DOI":"10.12688\/f1000research.151333.2","type":"journal-article","created":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T11:30:07Z","timestamp":1731929407000},"page":"918","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Laboratory findings predictive of critical illness in hospitalized COVID-19 patients in Tunisia"],"prefix":"10.12688","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-5868-0293","authenticated-orcid":false,"given":"Donia","family":"Belkhir","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4979-8853","authenticated-orcid":false,"given":"Hana","family":"Blibech","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Line","family":"Kaabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3596-8025","authenticated-orcid":false,"given":"Saoussen","family":"Miladi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed Aymen","family":"Jebali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jalloul","family":"Daghfous","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadia","family":"Mehiri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed","family":"Laatar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nozha","family":"Ben Salah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Houda","family":"Snene","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bechir","family":"Louzir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2560","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"624","DOI":"10.3390\/v14030624","article-title":"Molecular Epidemiology of SARS-CoV-2 in Tunisia (North Africa) through Several Successive Waves of COVID-19.","volume":"14","author":"A Chouikha","year":"2022 Mar 17","journal-title":"Viruses."},{"key":"ref2","doi-asserted-by":"publisher","first-page":"497-506","DOI":"10.1016\/S0140-6736(20)30183-5","article-title":"Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.","volume":"395","author":"C Huang","year":"2020 cited 2022 Dec 17","journal-title":"Lancet."},{"key":"ref3","article-title":"Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia - PMC.","year":"cited 2023 Nov 1"},{"key":"ref4","doi-asserted-by":"publisher","article-title":"Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis.","year":"cited 2023 Mar 7","DOI":"10.1515\/cclm-2020-0369\/html"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s40364-020-00217-0","article-title":"A meta-analysis of potential biomarkers associated with severity of coronavirus disease 2019 (COVID-19).","volume":"8","author":"C Danwang","year":"2020 Aug 31 cited 2023 Mar 24","journal-title":"Biomark. 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We have addressed each of your suggestions and comments in detail, as outlined below:  \n<b>Overall comments:<\/b>  1- Given the emergence of several variants of SARS-CoV-2, do the authors believe their findings could be applicable for evaluating the prognosis of COVID-19 patients infected with different variants?  Response: Yes, We have added in the limitations section that we took into consideration the fact that our study included several variants of the virus, which impacts the clinical presentation and the outcome of the infection. However, we believe that although the period of our study is lagged compared to the studies cited in the discussion, our results remain relevant for assessing the prognosis of patients with COVID-19, regardless of the variant.  \n<b>Introduction:&nbsp;<\/b>  1)&nbsp;The introduction does not clarify the relationship between study markers and SARS-CoV-2 infection:&nbsp; Response:We added a paragraph in the introduction section, clarifying the relationship between SARS-COV2 infection and the study of biomarkers.  \n<b>Methodology:<\/b>  * Why was the 7th day of hospitalization chosen as an outcome measure? Response: Several studies have shown the variation over time of the various markers, accompanying the \u201ccytokine storm\u201d that precedes the onset of ARDS, which usually occurs after 8 to 12 days from the onset of symptoms. Hence, we chose the 7th day after hospitalization, approximately corresponding to the 14th day after symptom onset, as the threshold for classifying patients into critical or non-critical groups. We added a paragraph explaining the phenomenon of cytokine storm and our choice of the 7\n<sup>th<\/sup> day of hospitalization.  *Are patients transferred to the intensive care unit before or on Day 7 classified as critical or non-critical? This classification is repeated for both outcome measure, which is bit confusing. Response: Patients transferred to the intensive care unit before or on day 7 were classified as critical. (It was incorrect to mention this phrase in the &quot;non-critical&quot; paragraph, we corrected it).  *If a patient from the non-critical group progresses to a critical state is that patients included in the critical group: Response: Patients who developed critical state after day 7 were not considered among the critical group.  *&nbsp;The definition of ARDS could be removed for brevity&nbsp; &nbsp;Response: This&nbsp;section was removed.  *Please condense the study section into 2-3 paragraphs Response: This section was condensed in 3 paragraphs.  *More details about D-dimer, CRP, Troponin and NT-Pro-BNP measurement should be further explained as a separate section each Response:&nbsp; We added a short description to detail each marker  \n<b>Results:<\/b>  *&nbsp;What clinical symptom is used to calculate the time of onset of symptoms to admission in the COVID-19 unit?&nbsp; Response: Any of the 6 symptoms listed in Table 1&nbsp;  * In Table 1, the authors indicate that 11 patients from the non-critical group were transferred to the ICU. Based on the study\u2019s critical group outcome measure, were these 11 patients included in the critical group?&nbsp; Response: Patients transferred to ICU after day 7 were not considered as critical.  * In Table 3, please remove the word \u201celevated\u201d from the side headings.&nbsp; Response: The word \u201cElevated\u201d was replaced by \u201cIncreased\u201d (Please note that the items in this table correspond to marker abnormalities, and the number of patients with abnormalities, and not to their levels). &nbsp; * Does \u201cN\u201d in the side heading of Table 3 refers to mean or count? Response:&nbsp;N refers to the count.  &nbsp;\n<b>Discussion and limitation<\/b>  &nbsp;1. The discussion and limitation section is lengthy and may lose the reader\u2019s interest. Consider streamlining this section to enhance engagement. Response: We have removed some parts that do not affect the scope of the discussion.  &nbsp;\n<b>Conclusion<\/b>  1. The authors provided a generalized statement in the conclusion\/ Please specify the major findings concisely. Please modify the same in abstract section  Response:Some specifications related to the majors findings were added in this section as well as in the abstract","URL":"https:\/\/f1000research.com\/articles\/13-918\/v2#referee-comment-12824","order":2,"name":"referee-comment-12824","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.174176.r344478, Santiago J Ballaz, Universidad Esp\u00edritu Santo, Samborond\u00f3n, 09 Dec 2024, version 2, indexed","URL":"https:\/\/f1000research.com\/articles\/13-918\/v2#referee-response-344478","order":3,"name":"referee-response-344478","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"The author(s) declared that no grants were involved in supporting this work","order":4,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}