Association of nutritional related biochemical markers with COVID-19 infection: a case-control study

Association of nutritional related biochemical markers with COVID-19 infection: a case-control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of nutritional related biochemical markers with COVID-19 infection: a case-control study Yaser Khajebishak, Ali Soleimani, Sadra Madani, Asghar Tanomand, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7745377/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 15 You are reading this latest preprint version Abstract Introduction: Since its detection, COVID19 has led to a worldwide health crisis with multi-systemic complications, involving the respiratory, cardiovascular, etc., health issues. Identifying of possible risk factors is important in finding the disease at an early stage and may improve the survival of patients. This study was carried out to evaluate inflammatory, hematological and nutritional indicators in order to determine the risk of COVID19 infection. Material and methods From 2021 to 2023 in Maragheh, northwest of Iran, 234 COVID19 cases and 160 nonCOVID19 controls were studied in this case-control study. Recruits were selected from referrals to local hospitals and health care centers of Maragheh University of Medical Scinces. Laboratory methods were used to determine the levels of serum vitamin D, potassium, CRP, and the hematological indices. Standard statistical analysis were performed in SPSS version 21and p-value less than 0.05 was considered statistically significant. Results The gender distribution was almost the same in both groups (54% female and 52% p = 0.858). The median serum level of CRP was higher in COVID19 patients 60.5 (40.0–85.0) mg/L compared to the non-COVID19 group 37.5 (20.0–65.0) mg/L (p < 0.001). The creatinine level was lower in the COVID19 group than in the non-COVID19 group (p = 0.033). Additionally, the median of vitamin D was significantly lower in COVID19 group 33.0 (IQR: 22.045.0) ng/mL (p < 0.001). The significant protective effect of vitamin D, potassium, creatinine, and lymphocyte to CRP (Lym. CRP) ratio with COVID19 was observed, while positive association was detected among age, CRP, and neutrophil to lymphocyte (Neu. Lym) ratio and increased risk of COVID19. Conclusion In conclusion, a simple approach to possibly lower the risk of COVID19 could be assessment inflammatory (CRP and lymphocyte to neutrophil ratio) and nutritional biomarkers (serum vitamin D and potassium). COVID19 CRP lymphocyte to neutrophil ratio vitamin D potassium Figures Figure 1 Introduction COVID19, the disease caused by SARS-CoV-2 was first detected in December 2019 from Wuhan China. It spread rapidly to become a respiratory disease and emerged as a critical global issue. Throughout the pandemic, it became clear that COVID-19 does more than affect the lungs. The virus provokes various health implications, including immune, cardiovascular, neurological, and gastrointestinal disruptions. Many patients with a diagnosis of COVID-19 represent the range of symptoms including fever, anorexia, cough, fatigue, and lymphopenia ( 1 – 3 ). Given the evidence, the role of optimized nutrition in accelerating the recovery of respiratory diseases and the immune system has been confirmed ( 4 , 5 ). While optimal nutritional status and strong immune system have a critical role in determining survival from COVID-19 death ( 6 , 7 ), nutrition deficiency worsens the status of patients and raises the mortality rate by increasing the length of hospitalization, delaying the recovery time, and increasing the rates of complications ( 8 – 10 ). This has caused an interest towards vitamins/minerals, and how some diseases like COVID-19 may be made worse by them ( 11 , 12 ). Vitamin D, a fat-soluble immunomodulating vitamin, plays a major role in inflammation ( 13 , 14 ). It was shown that vitamin D reduces the inflammatory cytokine storm via various mechanisms ( 20 ). In COVID-19 patients, often notice imbalances in electrolytes and vitamin levels, which makes their situation even more challenging ( 15 , 16 ). Hypokalemia as a main complication of disease, exacerbates respiratory distress and heart injury via various mechanisms ( 17 , 18 ). Magnesium play exerts multiple important roles in the human body such as transportation and activation of vitamins ( 19 ). To correct function, both vitamin D receptor (VDR) and vitamin D binding protein (VDBP) need magnesium as a cofactor ( 20 – 22 ). Along with nutrition deficiency, the main causes of mortality in these patients are inflammatory cytokine storm and the weakness of the immune system ( 23 , 24 ). Cytokine storm can result in lymphopenia ( 25 – 27 ) and myocardial injury, which aggravates mortality in COVID-19 patients ( 28 – 30 ). Two other biomarkers of systemic inflammation, the neutrophil-to-lymphocyte ratio (NLR) and the CRP-to-albumin ratio, further complicate their condition ( 31 , 32 ). Since the emerging importance of biochemical and nutrient indices in survival as well as recovery after COVID-19 patients, this study was conducted to investigate serum levels of vitamin D, potassium, CRP, and Lymphocyte-to-neutrophil ratio at Maragheh University of Medical Sciences, Iran. Materials and Methods We conducted an observational case-control study, recruiting 394 participants (234 COVID-19 patients and 160 non-COVID-19 controls) between 2021 and 2023 at healthcare centers of Maragheh University of Medical Sciences in northwest Iran. Maragheh is the second-largest city in the southern East Azerbaijan Province and serves as a major healthcare hub for at least five neighboring cities. During the COVID-19 pandemic, its hospitals were chosen as the main referral points for the area during the COVID-19 epidemic. Two different groups of study volunteers were chosen. A control group of asymptomatic patients attending outpatient COVID-19 screening centers and a case group of people presenting with suspected COVID-19 symptoms. As assessed by infectious disease experts, for the case group, the diagnosis was confirmed by findings from both CT scans and PCR analysis. People with serious chronic illnesses, including kidney and liver diseases, high blood pressure, diabetes, heart diseases, and mental or degenerative neurological diseases, were excluded. Participants were given a written informed consent form and a demographic questionnaire completed at baseline. The regional ethics committee accepted the study protocol (Approval number: 5/4/2787). For biochemical testing, we collected 5 mL of venous blood from each participant. For serum separation, samples were immediately centrifuged (3000 rpm, 10 minutes), then aliquoted and preserved at -80°C until assay. A Sysmex XP300 analyzer (Sysmex Corporation, Kobe, Japan) was used to measure complete blood counts, from which the lymphocyte-to-neutrophil ratio was determined. By the full blood count test, the absolute lymphocyte and neutrophil counts were obtained. Serum albumin was measured using the Parsazmon kit and Vitamin D levels were determined through an automated assay (Vidas PC analyzer, BioMerieux, France). Additional measurements included CRP (commercial ELISA kit), potassium and magnesium (AutoAnalyzer system), and creatinine (enzymatic method). The sample size was calculated based on the CRP variable from a previous study. By the power of 90%, a confidence interval of 95%, and a two-tailed test, the minimum sample size was obtained as 100 individuals in each group ( 33 ). Statistical Analysis Statistical analysis was carried out with SPSS software (version 21.0, Chicago, IL, USA). After assessing data normality using the Kolmogorov-Smirnov test, we showed normally distributed data as mean (SD) and nonnormal data as median (IQR). Frequencies and percentages represented categorical variables. Group comparisons utilized independent samples t-tests or Mann-Whitney U tests for numerical data and chi-square tests for categorical factors. Multiple logistic regression was used to control the confounding factors and calculate odds ratios for COVID-19 predictive variables. Statistical significance was set at p < 0.05. Results Out of the 394 participants enrolled, 234 were categorized as COVID19. Patients in the COVID19 group had a median age of 52.1 (44.0–60.0).There was a significant difference between groups in terms of the age variable. About 54% of COVID19 patients were females, and in nonCOVID19, about 52%. No significant difference was detected in gender variables between groups. In the COVID19 group, the serum CRP level was 60.5 (40.085.0); in the nonCOVID19 group, it was 37.5 (20.0 65.0) (p < 0.001). The COVID19 group had considerably reduced serum creatinine level than the non-COVID19 group (p = 0.033). Table 1 presents the nutritional-related variables and biochemical marker results for the subjects. Table 1 Nutritional-related factors and biochemical biomarkers in the participants (n = 394) variables COVID-19 (n = 234) Non-COVID-19 (n = 160) p Age (y) ** 53.0 (44.0–60.0) 48.0 (42.0-55.7) 0.001 Gender [(n (%)]* - Male - Female 109 (46.6) 125 (53.4) 76 (47.5) 84 (52.5) 0.858 Albumin (g/dL)** 3.70 (3.20–4.02) 3.60 (3.20-4.00) 0.679 Creatinine (mg/dL) ** 1.00 (0.82–1.20) 1.10 (0.87–1.48) 0.033 CRP (mg/L)** 60.50 (40.00–85.00) 37.50 (20.00–65.00) < 0.001 CRP/ Albumin 17.12 (10.82–25.58) 10.11 (5.11–17.46) < 0.001 Potassium (mg/dL) ** 3.78 (0.47) 4.02 (0.58) < 0.001 Magnesium (mg/dL) ** 1.91 (1.80–2.20) 1.90 (1.70–2.13) 0.096 Hemoglobin (g/dL) 12.86 (1.82) 12.56 (2.35) 0.154 Hematocrit (%) 39.09 (5.07) 38.10 (6.52) 0.090 MCH (pg) 29.00 (27.00–30.00) 29.00 (27.00–30.00) 0.397 MCHC (g/dL) 33.00 (32.00–34.00) 33.00 (32.00–34.00) 0.766 MCV (fl) 87.00 (83.00–89.00) 87.00 (84.00–91.00) 0.228 Platelets 190500.00 (154000.00-243000.00) 211500.0 (162250.0-282250.0) 0.024 RBC 10*6/µL 4.00 (4.00–5.00) 4.50 (3.90-5.00) 0.218 WBC 10*3/µL 6800.00 (4900.00-9600.00) 7800.00 (5450.00-10500.00) 0.026 Lymphocyte (%) 17.00 (10.00–25.00) 20.00 (11.00–28.00) 0.027 Neutrophil (%) 77.00 (69.00–85.00) 75.00 (62.25-83.00) 0.011 Eosinophil (%) 2.00 (1.00–3.00) 2.00 (2.00–4.00) 0.012 Monocyte (%) 3.00 (2.00–5.00) 4.00 (3.00–5.00) 0.012 Neu.Lym 4.48 (2.72–8.57) 3.8 (2.24–7.24) 0.020 Lym.CRP 0.27 (0.12–0.50) 0.45 (0.21–1.08) < 0.001 Pla/Lym 12289.5 (7107.1-22143.8) 11461.5 (6972.2-20424.2) 0.517 Lym. Mono 5.0 (3.05-7.00) 5.0 (3.0-7.2) 0.929 * Data presented as frequency (%), Chi-square test ** Data presented as median (25–75 percentile), Mann- Whitney U-test p < 0.05 was defined as significant The median (IQR) of vitamin D in COVID19 patients was 33.0 (22.0–45.0) ng/mL, and a significant difference was observed in serum concentration of participants (p < 0.001). Figure 1 shows the serum level of vitamin D in both groups. The significant protective role of vitamin D, potassium, creatinine, and the lymphocyte to CRP ratio was confirmed by multivariate logistic regression in COVID19 risk. Indeed, the COVID19 risk decreased by 3% and 56% for each unit increase in vitamin D and potassium, respectively. In contrast, a positive direct relationship was detected in terms of age, CRP, and neutrophil-to-lymphocyte ratio. In such a way, the COVID19 risk increased by 4% with each unit (year) increase in age. COVID19 risk was also enhanced by 3% and 6% with each unit increase in CRP and Neu. Lym ratio, respectively. Table 2 represents the logistic regression results of nutritional and biochemical-related factors in COVID19 patients. Table 2 Results of logistic regression for nutritional-related factors and biochemical biomarkers in COVID-19 patients Variables Adjusted* OR p 95% CI (lower to upper) Age (y) 1.04 0.001 (1.02 to 1.07) Vitamin D (ng/mL) 0.97 < 0.001 (0.96 to 0.98) CRP (mg/L) 1.03 0.031 (1.02 to 1.15) Potassium (mg/dL) 0.44 0.002 (0.26 to 1.73) Creatinine (mg/dL) 0.60 < 0.001 (0.45 to 0.80) Neu.Lym 1.06 0.036 (1.00 to 1.11) Lym.CRP 0.42 0.002 (0.25 to 0.72) OR: odds ratio p < 0.05 is defined as significant Discussion COVID19 is a respiratory infection with a broad clinical spectrum from asymptomatic, to severe complications leading to multiple organ failure and eventually death ( 34 , 35 ). In this study, levels of vitamin D in COVID19 cases were significantly lower than the values of controls. Recent studies have demonstrated that levels of vitamin D are markedly lower in patients with COVID-19, especially those with severe illness, and are associated with longer hospitalization and mortality rates ( 36 – 44 ). Merzon et al. showed an independent relationship between low plasma 25-hydroxy vitamin D levels and the risk of both developing COVID19 and hospitalization for it( 37 ). A similar association was found in other cohorts: increased mortality in patients with vitamin D deficiency was also noted ( 45 , 46 ). Contrary to our results, cereda et al. discovered that although vitamin D deficiency was quite common among hospitalized COVID19 patients, low vitamin D levels were not related to worse clinical outcomes; unexpectedly, higher vitamin D levels were correlated with increased inhospital mortality after accounting for confounders ( 47 ). Nasiri et al. discovered that lower vitamin D was linked to longer hospital stays but not to significantly altered death or time to oxygen recovery ( 48 ). Furthermore complicating the relationship between vitamin D status and disease outcomes, povaliaeva et al.(2022) have demonstrated that COVID19 could disturb vitamin D metabolism ( 49 ). Although most data supports a relationship between low vitamin D and worse COVID19 outcomes, some research emphasizes the need for more investigation and cautions against assuming a simple causal link ( 47 , 49 ). Vitamin D prevents the progression of COVID19 through cooperative processes that improve immune control and reduce aberrant inflammatory responses. It makes the body's first defense better by helping make substances like cathelicidin and defensins. These can directly stop the virus from copying itself and help clear it out ( 50 – 52 ). Vitamin D also controls the balance between proinflammatory and antiinflammatory signals, therefore altering adaptive immune responses. By means of this immunomodulatory effect, the probability of a cytokine storm—a possibly fatal hyperinflammatory reaction associated with serious COVID19 effects—is reduced ( 50 , 53 , 54 ). Moreover, by increasing the expression of angiotensinconverting enzyme receptor (ACE2), the principal cellular receptor for SARSCoV2 viral entrance, this mechanism could offer pulmonary protection by lowering the pathogenic consequences of the virus on the reninangiotensin-aldosterone system (RAAS) ( 52 , 55 ). Furthermore, vitamin D lessens oxidative stress and maintains respiratory epithelial integrity, hence minimizing pulmonary tissue damage ( 53 , 56 ). While causation must be proven by big randomized trials ( 52 , 57 ), present observational and meta-analytic data continually links adequate vitamin D levels to lower infection rates, less severe disease progression, and fewer ICU admissions. The many effects of vitamin D on immune regulation, inflammation management, and tissue protection may prevent COVID19 from advancing to more advanced stages ( 50 – 53 , 55 ). The regression analysis confirmed it as possible sensitivity factors for COVID19, since the potassium level was noticeably lower in COVID19 versus controls. Our findings indicate that potassium levels in COVID19 patients are significantly lower than in control groups, consistent with evidence from multiple studies ( 58 – 62 ). Hypokalemia may be linked to a higher severity of disease and adverse outcomes. ( 18 , 61 , 63 , 64 ). Indeed, several meta-analyses and cohort/observational studies have shown that hypokalemia and hyperkalemia are among the most often seen electrolyte abnormalities in COVID19 patients. Higher probability of requiring invasive mechanical ventilation and increased illness severity are related to both hyperkalemia and hypokalemia ( 58 , 59 , 61 , 65 ). Hypokalemia was found to be a frequent disorder in hospitalized COVID19 patients and an independent predictor of the need for invasive mechanical ventilation in a large case series, therefore indicating its use as a marker of disease severity rather than death ( 43 ). Among women patients and those using diuretics, another study indicated a high prevalence of hypokalemia but discovered no statistically significant relationship with ICU admission or inhospital fatality ( 64 , 66 ). Nevertheless, there are inconsistencies in the researches; one prospective study, for instance, found no significant difference in serum potassium levels between COVID19 patients and controls ( 67 ). Although hypokalemia is related to illness severity, certain research have shown that both low and high potassium levels during hospitalization are connected with increased mortality, therefore pointing to a J shaped relationship and highlighting the need of keeping potassium within a normal range ( 68 ). Some research has shown that higher serum potassium levels are more intimately related to higher death in COVID19 patients ( 69 ) than hypokalemia is ( 68 , 70 ). Further pooled analyses confirm that lower potassium levels are correlated with more severe COVID19 ( 58 , 71 ). The relationship between potassium homeostasis and clinical results seems complicated, though; while some studies show opposing results on the prognostic relevance of both hypo and hyperkalemia ( 61 , 64 , 66 , 68 – 70 ). Hypokalaemia is frequently seen in patients with severe COVID19; it is related to more need for invasive mechanical ventilation and longer hospital stays ( 59 , 61 , 72 ). The binding of SARS-CoV2 to ACE2 receptors upsets the renin angiotensin in aldosterone system (RAAS), hence increasing angiotensin II activity. This raises sodium reabsorption and potassium excretion in the kidneys, therefore leading to continuous urinary potassium loss ( 59 , 73 , 74 ). Because the degree of hypokalaemia corresponds with indicators of systemic inflammation and disease severity, it is a sensitive biomarker for progression in COVID19 ( 61 , 72 , 74 ). Hypokalaemia also raises the risk of cardiac arrhythmias, particularly when used in conjunction with specific medications or direct viral impacts on the heart ( 59 , 72 , 73 ). Therefore, in extreme COVID19 instances, monitoring and controlling potassium levels is vital both to inform prognosis and to avoid problems ( 59 , 61 , 72 ). Highlighting its potential as an inflammatory indicator for assessing disease risk and severity, the current research showed a significantly higher CRP to albumin ratio (CAR) in COVID19 patients as opposed to noninfected controls. This result are consistent with a evidence suggesting that an elevated CAR is a strong prognostic marker in COVID19, intimately linked with greater disease severity, higher intensive care unit (ICU) admission, and increased death risk ( 75 – 82 ). Significantly, no studies thus far have indicated opposing results, thereby, validating the consistency and reliability of our findings even further. Higher CAR values have been independently associated with worse clinical outcomes—including longer hospital stays, ICU admission, and requirement for mechanical ventilation—with suggested cutoff values for risk stratification ranging from roughly 1.6 to 25 depending on the population and outcome measured ( 75 – 78 , 80 , 81 ). The biological basis of CAR's prognostic significance is its combination of two critical markers: CRP, an acute phase reactant reflecting systemic inflammation and immune activation, and albumin, a negative acutephase protein whose levels decline with inflammation and inadequate nutritional state ( 75 , 76 , 80 , 81 , 83 ). High CAR therefore reflects both increased inflammatory response and impaired nutritional or hepatic reserves—both of which are related to COVID19 progression and organ dysfunction ( 75 , 76 , 80 , 81 ). Mechanistically, elevated CRP levels imply cytokinedriven inflammation, whereas hypoalbuminemia may reflect capillary leakage, liver damage, or malnutrition—all contributing to immune dysregulation and adverse clinical outcomes ( 75 , 76 , 80 , 81 ). While other studies show comparable predictive power among these indicators ( 75 , 77 , 78 , 80 – 82 ), some have found CAR to predict death and severe disease better than CRP or albumin alone. Variations in ideal CAR cutoffs and predictive accuracy ( 78 , 84 , 85 ). could be explained by methodological differences including patient populations (general, pregnant, or postacute COVID19), timing of measurement, and result definitions. Overall, the evidence argues for CAR as a strong, readily available biomarker for early risk stratification in COVID19, however more prospective studies and standardization of cutoff values are required to perfect its clinical use ( 75 – 82 ). This study found notable changes in hematological indicators between noninfected controls and COVID19 patients. Observed in the COVID19 group was a rise in the neutrophiltolymphocyte ratio (NLR) and a corresponding drop in the lymphocytetoCRP ratio (LCR). These findings suggest a move toward greater systemic inflammation and compromised immunological regulation, therefore both NLR and LCR may be helpful indicators in the setting of COVID19. Independent of age or comorbidities, several recent metaanalyses and large cohort studies have shown that a high NLR is a strong predictor of both severe COVID19 illness and death, with admissions having higher NLR values correlating with worse outcomes ( 86 – 90 ). Similarly, diminished LCR has been shown to be strongly related with higher risk of ICU admission and death; certain studies even indicate that in predicting 28-day mortality ( 91 – 93 ) LCR can even beat NLR. Furthermore, it has been noted that while NLR and LCR levels usually stabilize during recovery, patients with bad prognosis exhibit continuously abnormal values ( 92 , 94 ). To our knowledge, no studies have published results contradicting our findings. These results highlight the clinical use of NLR and LCR as affordable, readily available indicators for early risk stratification and management of COVID19 patients, as well as the key role of immune and inflammatory dysregulation in disease progression ( 86 , 89 , 91 , 93 , 94 ). Conclusion In this study, we investigated the indirect indicators of COVID-19 risk in 394 subjects. Of all examined parameters, age, vitamin D, CRP, creatinine, potassium, Neu.Lym, and Lym.CRP was recognized to be a prognostic value in detecting COVID-19 risk. Given the importance of vitamins and electrolytes, periodic assessments and timely diagnosis can be helpful in early interventions through designing a complete food plan containing enough energy and high-potassium and vitamin content. Future studies are needed to assess dietary intake and other biochemical laboratory influences on COVID-19 risk. Abbreviations ACE2: Angiotensin Converting Enzyme Receptor CAR: CRP to Albumin Ratio COVID19: Coronavirus disease 2019 CRP: C Reactive Protein ICU: Intensive Care Unit RAAS: Renin Angiotensin in Aldosterone System NLR: Neutrophil-to-lymphocyte ratio NLR: Neutrophil to Lymphocyte Ratio VDR: Vitamin D receptor VDBP: Vitamin D binding protein Declarations Authors' contributions: Y.KH: Contributed to the design, data interpretation, and approval of the final version of the manuscript. A.S: Contributed to data analysis and interpretation of results. S.M: Contributed to the data collection. A.T: Contributed to the manuscript revising M.A, Y.B, A.N.Y: Contributed to the confirmation and referring patients. L.P: Contributed to the conception, supervised the study, and approved of the final version of the manuscript. Conflict of interest: Authors declare that there is no conflict of interest. Acknowledgements: The authors would like to acknowledge the financial support of Maragheh University of Medical Sciences for this research. The authors also thank all participants who contributed to this research. Clinical trial number: Not applicable. Funding Declaration: Not applicable Ethics approval and consent to participate: According to Helsinki's Declaration, t he protocol of the study was approved by the ethics committee of Maragheh University of Medical Sciences and a written informed consent form was completed by participants. 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Int J Med Sci. 2021;18:736–43. Wang L, Canela V. Hyperkalemia Is Associated With Increased Mortality Rates in COVID-19 Patients. J Am Soc Nephrol. 2022;33:884. Miri M, Badriahmadi S, Shamshirian A, Ghalibaf AM, Mozdourian M. Electrolyte Imbalance and COVID-19 Severity in Hospitalized Patients. Nephro-Urology Monthly; 2022. Kusuma AANJ, Manuaba I, Widiyanti E, Hartanto F. The Profile of Serum Potassium Level and Cardiomegaly in Pregnancy with COVID-19 in Prof. Dr. I.G.N.G. Ngoerah General Hospital. J South Asian Federation Obstet Gynecol. 2024. Bhatnagar M. Hypokalemia as a Surrogate Marker of Severity in COVID 19 Infection. J Endocr Soc. 2021;5. Mandal A, Wenban C, Heer R, Kho J, Missouris C. Covid-19, hypokalaemia and the renin-angiotensin-aldosterone system. Annals Med Surg. 2021;65. Chen D, Li X, Song Q, Hu C, Su F, Dai J. Hypokalemia and Clinical Implications in Patients with Coronavirus Disease 2019 (COVID-19). medRxiv. 2020. Giner-Galvañ V, Pomares-Gómez F, Quesada J, Rubio-Rivas M, Tejada-Montes J, Baltasar-Corral J et al. C-Reactive Protein and Serum Albumin Ratio: A Feasible Prognostic Marker in Hospitalized Patients with COVID-19. Biomedicines. 2022;10. Uzum Y, Turkkan E. Predictivity of CRP, Albumin, and CRP to Albumin Ratio on the Development of Intensive Care Requirement, Mortality, and Disease Severity in COVID-19. Cureus. 2023;15. Grigoli ECA, Sejópoles M, Gomes L, Fontes CF. Diagnostic Value of C-Reactive Protein, Albumin, and the CRP-to-Albumin Ratio for Predicting Mortality in Hospitalized Patients with COVID-19 in Brazilian hospitals. J Adv Med Med Res. 2023. Nazri NAM, Azman WW, Musa N, Ismail TST, Harun A, Yaacob NMB et al. C-reactive Protein, Albumin, Urea, CRP/Albumin Ratio, and Urea/Albumin Ratio: A Retrospective Evaluation in COVID-19 Patients. NOVEMBER. 2023. 2023. Ergenç Z, Ergenç H, Araç S, Usanmaz M, Alkılınç E, Kaya G et al. Novel biochemical prognostic indicators in COVID-19: Can CRP/albumin, urea/albumin, and LDH/albumin ratios be used to predict mortality and length of hospitalization? Med Sci Discovery. 2022. Lucijanić M, Stojic J, Atić A, Čikara T, Osmani B, Barisic-Jaman M, et al. Clinical and prognostic significance of C-reactive protein to albumin ratio in hospitalized coronavirus disease 2019 (COVID-19) patients. Wiener klinische Wochenschrift. 2022;134:377–84. Li Y, Li H, Song C, Lu R, Zhao Y, Lin F et al. Early Prediction of Disease Progression in Patients with Severe COVID-19 Using C-Reactive Protein to Albumin Ratio. Disease Markers. 2021;2021. Ayranci M, Küçükceran K, Koçak S, Girişgin A, Dündar Z. The Role of Procalcitonin/Albumin Ratio and CRP/Albumin Ratio in Predicting In-hospital Mortality in COVID-19 Patients. J acute Med. 2023;13 4:150–8. Faghfouri AH, Zarrin R, Maleki V, Payahoo L, Khajebishak Y. A comprehensive mechanistic review insight into the effects of micronutrients on toll-like receptors functions. Pharmacol Res. 2020;152:104619. Yilmaz N, Tosun F, Comert E, Durán M, Tuna V. The Relationship of CRP/Albumin ratio level and prognosis in pregnant COVID-19 patients. Niger J Clin Pract. 2022;25:1745–50. Afşin D, Kerget B. Evaluation of the Relationship between CRP/Albumin Ratio and Pulmonary Function Parameters in Patients with Post-Acute COVID-19. Clin Lab. 2022;68:8. Parthasarathi A, Padukudru S, Arunachal S, Basavaraj C, Krishna M, Ganguly K et al. The Role of Neutrophil-to-Lymphocyte Ratio in Risk Stratification and Prognostication of COVID-19: A Systematic Review and Meta-Analysis. Vaccines. 2022;10. Simadibrata D, Calvin J, Wijaya A, Ibrahim N. Neutrophil-to-lymphocyte ratio on admission to predict the severity and mortality of COVID-19 patients: A meta-analysis. Am J Emerg Med. 2020;42:60–9. Zinellu A, Mangoni A. A systematic review and meta-analysis of the association between the neutrophil, lymphocyte, and platelet count, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio and COVID-19 progression and mortality. Expert Rev Clin Immunol. 2022;18:1187–202. Feng X, Li S, Sun Q, Zhu J, Chen B, Xiong M et al. Immune-Inflammatory Parameters in COVID-19 Cases: A Systematic Review and Meta-Analysis. Front Med. 2020;7. Yang A, Liu J-P, Tao W-Q, Li H-M. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol. 2020;84:106504. Wu Z, Cao Y, Liu Z, Geng N, Pan W, Zhu Y et al. Study on the predictive value of laboratory inflammatory markers and blood count-derived inflammatory markers for disease severity and prognosis in COVID-19 patients: a study conducted at a university-affiliated infectious disease hospital. Ann Med. 2024;56. Ardestani MT, Najafi-Asl M, Zade PB, Norouzian M. Hematological Indicators as Prognostic Factors for COVID-19 Mortality: Exploring Anemia and Systemic Inflammation. Hormozgan Med J. 2024. Lagunas-Rangel F. Neutrophil-to‐lymphocyte ratio and lymphocyte‐to‐C‐reactive protein ratio in patients with severe coronavirus disease 2019 (COVID‐19): A meta‐analysis. J Med Virol. 2020;92:1733–4. Jemaa AB, Salhi N, Othmen MB, Ali B, Guissouma J, Ghadhoune H, et al. Evaluation of individual and combined NLR, LMR and CLR ratio for prognosis disease severity and outcomes in patients with COVID-19. Int Immunopharmacol. 2022;109:108781. Additional Declarations No competing interests reported. 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16:04:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":724073,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7745377/v1/88b44f61-4ee1-4a24-bf26-603d862b57cd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of nutritional related biochemical markers with COVID-19 infection: a case-control study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCOVID19, the disease caused by SARS-CoV-2 was first detected in December 2019 from Wuhan China. It spread rapidly to become a respiratory disease and emerged as a critical global issue. Throughout the pandemic, it became clear that COVID-19 does more than affect the lungs. The virus provokes various health implications, including immune, cardiovascular, neurological, and gastrointestinal disruptions. Many patients with a diagnosis of COVID-19 represent the range of symptoms including fever, anorexia, cough, fatigue, and lymphopenia (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGiven the evidence, the role of optimized nutrition in accelerating the recovery of respiratory diseases and the immune system has been confirmed (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). While optimal nutritional status and strong immune system have a critical role in determining survival from COVID-19 death (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), nutrition deficiency worsens the status of patients and raises the mortality rate by increasing the length of hospitalization, delaying the recovery time, and increasing the rates of complications (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). This has caused an interest towards vitamins/minerals, and how some diseases like COVID-19 may be made worse by them (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Vitamin D, a fat-soluble immunomodulating vitamin, plays a major role in inflammation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). It was shown that vitamin D reduces the inflammatory cytokine storm via various mechanisms (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn COVID-19 patients, often notice imbalances in electrolytes and vitamin levels, which makes their situation even more challenging (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Hypokalemia as a main complication of disease, exacerbates respiratory distress and heart injury via various mechanisms (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Magnesium play exerts multiple important roles in the human body such as transportation and activation of vitamins (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). To correct function, both vitamin D receptor (VDR) and vitamin D binding protein (VDBP) need magnesium as a cofactor (\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlong with nutrition deficiency, the main causes of mortality in these patients are inflammatory cytokine storm and the weakness of the immune system (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Cytokine storm can result in lymphopenia (\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) and myocardial injury, which aggravates mortality in COVID-19 patients (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Two other biomarkers of systemic inflammation, the neutrophil-to-lymphocyte ratio (NLR) and the CRP-to-albumin ratio, further complicate their condition (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSince the emerging importance of biochemical and nutrient indices in survival as well as recovery after COVID-19 patients, this study was conducted to investigate serum levels of vitamin D, potassium, CRP, and Lymphocyte-to-neutrophil ratio at Maragheh University of Medical Sciences, Iran.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e We conducted an observational case-control study, recruiting 394 participants (234 COVID-19 patients and 160 non-COVID-19 controls) between 2021 and 2023 at healthcare centers of Maragheh University of Medical Sciences in northwest Iran. Maragheh is the second-largest city in the southern East Azerbaijan Province and serves as a major healthcare hub for at least five neighboring cities. During the COVID-19 pandemic, its hospitals were chosen as the main referral points for the area during the COVID-19 epidemic. Two different groups of study volunteers were chosen. A control group of asymptomatic patients attending outpatient COVID-19 screening centers and a case group of people presenting with suspected COVID-19 symptoms. As assessed by infectious disease experts, for the case group, the diagnosis was confirmed by findings from both CT scans and PCR analysis. People with serious chronic illnesses, including kidney and liver diseases, high blood pressure, diabetes, heart diseases, and mental or degenerative neurological diseases, were excluded. Participants were given a written informed consent form and a demographic questionnaire completed at baseline. The regional ethics committee accepted the study protocol (Approval number: 5/4/2787).\u003c/p\u003e\u003cp\u003eFor biochemical testing, we collected 5 mL of venous blood from each participant. For serum separation, samples were immediately centrifuged (3000 rpm, 10 minutes), then aliquoted and preserved at -80\u0026deg;C until assay. A Sysmex XP300 analyzer (Sysmex Corporation, Kobe, Japan) was used to measure complete blood counts, from which the lymphocyte-to-neutrophil ratio was determined. By the full blood count test, the absolute lymphocyte and neutrophil counts were obtained. Serum albumin was measured using the Parsazmon kit and Vitamin D levels were determined through an automated assay (Vidas PC analyzer, BioMerieux, France). Additional measurements included CRP (commercial ELISA kit), potassium and magnesium (AutoAnalyzer system), and creatinine (enzymatic method). The sample size was calculated based on the CRP variable from a previous study. By the power of 90%, a confidence interval of 95%, and a two-tailed test, the minimum sample size was obtained as 100 individuals in each group (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis was carried out with SPSS software (version 21.0, Chicago, IL, USA). After assessing data normality using the Kolmogorov-Smirnov test, we showed normally distributed data as mean (SD) and nonnormal data as median (IQR). Frequencies and percentages represented categorical variables. Group comparisons utilized independent samples t-tests or Mann-Whitney U tests for numerical data and chi-square tests for categorical factors. Multiple logistic regression was used to control the confounding factors and calculate odds ratios for COVID-19 predictive variables. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOut of the 394 participants enrolled, 234 were categorized as COVID19. Patients in the COVID19 group had a median age of 52.1 (44.0\u0026ndash;60.0).There was a significant difference between groups in terms of the age variable. About 54% of COVID19 patients were females, and in nonCOVID19, about 52%. No significant difference was detected in gender variables between groups.\u003c/p\u003e\n\u003cp\u003eIn the COVID19 group, the serum CRP level was 60.5 (40.085.0); in the nonCOVID19 group, it was 37.5 (20.0 65.0) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The COVID19 group had considerably reduced serum creatinine level than the non-COVID19 group (p\u0026thinsp;=\u0026thinsp;0.033). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the nutritional-related variables and biochemical marker results for the subjects.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNutritional-related factors and biochemical biomarkers in the participants (n\u0026thinsp;=\u0026thinsp;394)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003evariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCOVID-19 (n\u0026thinsp;=\u0026thinsp;234)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-COVID-19 (n\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (y) **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.0 (44.0\u0026ndash;60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.0 (42.0-55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender [(n (%)]*\u003c/p\u003e\n \u003cp\u003e- Male\u003c/p\u003e\n \u003cp\u003e- Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (46.6)\u003c/p\u003e\n \u003cp\u003e125 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (47.5)\u003c/p\u003e\n \u003cp\u003e84 (52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlbumin (g/dL)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.70 (3.20\u0026ndash;4.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.60 (3.20-4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.679\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCreatinine (mg/dL) **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (0.82\u0026ndash;1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10 (0.87\u0026ndash;1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP (mg/L)**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.50 (40.00\u0026ndash;85.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.50 (20.00\u0026ndash;65.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP/ Albumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.12 (10.82\u0026ndash;25.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.11 (5.11\u0026ndash;17.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotassium (mg/dL) **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.78 (0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.02 (0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMagnesium (mg/dL) **\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.91 (1.80\u0026ndash;2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.90 (1.70\u0026ndash;2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.86 (1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.56 (2.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHematocrit (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.09 (5.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.10 (6.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMCH (pg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.00 (27.00\u0026ndash;30.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.00 (27.00\u0026ndash;30.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.397\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMCHC (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.00 (32.00\u0026ndash;34.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.00 (32.00\u0026ndash;34.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMCV (fl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.00 (83.00\u0026ndash;89.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.00 (84.00\u0026ndash;91.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e190500.00 (154000.00-243000.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e211500.0 (162250.0-282250.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRBC 10*6/\u0026micro;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.00 (4.00\u0026ndash;5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.50 (3.90-5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWBC 10*3/\u0026micro;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6800.00 (4900.00-9600.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7800.00 (5450.00-10500.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphocyte (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.00 (10.00\u0026ndash;25.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.00 (11.00\u0026ndash;28.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutrophil (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.00 (69.00\u0026ndash;85.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.00 (62.25-83.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEosinophil (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00 (1.00\u0026ndash;3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00 (2.00\u0026ndash;4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonocyte (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00 (2.00\u0026ndash;5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.00 (3.00\u0026ndash;5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeu.Lym\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.48 (2.72\u0026ndash;8.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8 (2.24\u0026ndash;7.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLym.CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27 (0.12\u0026ndash;0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45 (0.21\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePla/Lym\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12289.5 (7107.1-22143.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11461.5 (6972.2-20424.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLym. Mono\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 (3.05-7.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 (3.0-7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e* Data presented as frequency (%), Chi-square test\u003c/p\u003e\n \u003cp\u003e** Data presented as median (25\u0026ndash;75 percentile), Mann- Whitney U-test\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was defined as significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe median (IQR) of vitamin D in COVID19 patients was 33.0 (22.0\u0026ndash;45.0) ng/mL, and a significant difference was observed in serum concentration of participants (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the serum level of vitamin D in both groups. The significant protective role of vitamin D, potassium, creatinine, and the lymphocyte to CRP ratio was confirmed by multivariate logistic regression in COVID19 risk. Indeed, the COVID19 risk decreased by 3% and 56% for each unit increase in vitamin D and potassium, respectively. In contrast, a positive direct relationship was detected in terms of age, CRP, and neutrophil-to-lymphocyte ratio. In such a way, the COVID19 risk increased by 4% with each unit (year) increase in age. COVID19 risk was also enhanced by 3% and 6% with each unit increase in CRP and Neu. Lym ratio, respectively. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e represents the logistic regression results of nutritional and biochemical-related factors in COVID19 patients.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of logistic regression for nutritional-related factors and biochemical biomarkers in COVID-19 patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eAdjusted*\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI (lower to upper)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.02 to 1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVitamin D (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.96 to 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.02 to 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotassium (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.26 to 1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.45 to 0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeu.Lym\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.00 to 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLym.CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.25 to 0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eOR: odds ratio\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is defined as significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCOVID19 is a respiratory infection with a broad clinical spectrum\u0026ensp;from asymptomatic, to severe complications leading to multiple organ failure and eventually death (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In this study, levels of vitamin D in COVID19 cases were significantly lower than the values\u0026ensp;of controls. Recent studies have demonstrated that\u0026ensp;levels of vitamin D are markedly lower in patients with COVID-19, especially those with severe illness, and are associated with longer hospitalization and mortality rates (\u003cspan additionalcitationids=\"CR37 CR38 CR39 CR40 CR41 CR42 CR43\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Merzon et al. showed an independent relationship between low plasma 25-hydroxy vitamin D levels and the risk of both developing COVID19 and hospitalization for it(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). A similar association was found in other cohorts: increased mortality in patients with vitamin D deficiency was also noted (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eContrary to our results, cereda et al. discovered that although vitamin D deficiency was quite common among hospitalized COVID19 patients, low vitamin D levels were not related to worse clinical outcomes; unexpectedly, higher vitamin D levels were correlated with increased inhospital mortality after accounting for confounders (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Nasiri et al. discovered that lower vitamin D was linked to longer hospital stays but not to significantly altered death or time to oxygen recovery (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Furthermore complicating the relationship between vitamin D status and disease outcomes, povaliaeva et al.(2022) have demonstrated that COVID19 could disturb vitamin D metabolism (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Although most data supports a relationship between low vitamin D and worse COVID19 outcomes, some research emphasizes the need for more investigation and cautions against assuming a simple causal link (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Vitamin D prevents the progression of COVID19 through cooperative processes that improve immune control and reduce aberrant inflammatory responses. It makes the body's first defense better by helping make substances like cathelicidin and defensins. These can directly stop the virus from copying itself and help clear it out (\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Vitamin D also controls the balance between proinflammatory and antiinflammatory signals, therefore altering adaptive immune responses. By means of this immunomodulatory effect, the probability of a cytokine storm\u0026mdash;a possibly fatal hyperinflammatory reaction associated with serious COVID19 effects\u0026mdash;is reduced (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, by increasing the expression of angiotensinconverting enzyme receptor (ACE2), the principal cellular receptor for SARSCoV2 viral entrance, this mechanism could offer pulmonary protection by lowering the pathogenic consequences of the virus on the reninangiotensin-aldosterone system (RAAS) (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Furthermore, vitamin D lessens oxidative stress and maintains respiratory epithelial integrity, hence minimizing pulmonary tissue damage (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). While causation must be proven by big randomized trials (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), present observational and meta-analytic data continually links adequate vitamin D levels to lower infection rates, less severe disease progression, and fewer ICU admissions. The many effects of vitamin D on immune regulation, inflammation management, and tissue protection may prevent COVID19 from advancing to more advanced stages (\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe regression analysis confirmed it as possible sensitivity factors for COVID19, since the potassium level was noticeably lower in COVID19 versus controls. Our findings indicate that potassium levels in COVID19 patients are significantly lower than in control groups, consistent with evidence from multiple studies (\u003cspan additionalcitationids=\"CR59 CR60 CR61\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Hypokalemia may be linked to a higher severity of disease and adverse outcomes. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Indeed, several meta-analyses and cohort/observational studies have shown that hypokalemia and hyperkalemia are among the most often seen electrolyte abnormalities in COVID19 patients. Higher probability of requiring invasive mechanical ventilation and increased illness severity are related to both hyperkalemia and hypokalemia (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Hypokalemia was found to be a frequent disorder in hospitalized COVID19 patients and an independent predictor of the need for invasive mechanical ventilation in a large case series, therefore indicating its use as a marker of disease severity rather than death (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Among women patients and those using diuretics, another study indicated a high prevalence of hypokalemia but discovered no statistically significant relationship with ICU admission or inhospital fatality (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNevertheless, there are inconsistencies in the researches; one prospective study, for instance, found no significant difference in serum potassium levels between COVID19 patients and controls (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Although hypokalemia is related to illness severity, certain research have shown that both low and high potassium levels during hospitalization are connected with increased mortality, therefore pointing to a J shaped relationship and highlighting the need of keeping potassium within a normal range (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSome research has shown that higher serum potassium levels are more intimately related to higher death in COVID19 patients (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e) than hypokalemia is (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). Further pooled analyses confirm that lower potassium levels are correlated with more severe COVID19 (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). The relationship between potassium homeostasis and clinical results seems complicated, though; while some studies show opposing results on the prognostic relevance of both hypo and hyperkalemia (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan additionalcitationids=\"CR69\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHypokalaemia is frequently seen in patients with severe COVID19; it is related to more need for invasive mechanical ventilation and longer hospital stays (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). The binding of SARS-CoV2 to ACE2 receptors upsets the renin angiotensin in aldosterone system (RAAS), hence increasing angiotensin II activity. This raises sodium reabsorption and potassium excretion in the kidneys, therefore leading to continuous urinary potassium loss (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBecause the degree of hypokalaemia corresponds with indicators of systemic inflammation and disease severity, it is a sensitive biomarker for progression in COVID19 (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e). Hypokalaemia also raises the risk of cardiac arrhythmias, particularly when used in conjunction with specific medications or direct viral impacts on the heart (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). Therefore, in extreme COVID19 instances, monitoring and controlling potassium levels is vital both to inform prognosis and to avoid problems (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHighlighting its potential as an inflammatory indicator for assessing disease risk and severity, the current research showed a significantly higher CRP to albumin ratio (CAR) in COVID19 patients as opposed to noninfected controls. This result are consistent with a evidence suggesting that an elevated CAR is a strong prognostic marker in COVID19, intimately linked with greater disease severity, higher intensive care unit (ICU) admission, and increased death risk (\u003cspan additionalcitationids=\"CR76 CR77 CR78 CR79 CR80 CR81\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). Significantly, no studies thus far have indicated opposing results, thereby, validating the consistency and reliability of our findings even further.\u003c/p\u003e\u003cp\u003eHigher CAR values have been independently associated with worse clinical outcomes\u0026mdash;including longer hospital stays, ICU admission, and requirement for mechanical ventilation\u0026mdash;with suggested cutoff values for risk stratification ranging from roughly 1.6 to 25 depending on the population and outcome measured (\u003cspan additionalcitationids=\"CR76 CR77\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). The biological basis of CAR's prognostic significance is its combination of two critical markers: CRP, an acute phase reactant reflecting systemic inflammation and immune activation, and albumin, a negative acutephase protein whose levels decline with inflammation and inadequate nutritional state (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). High CAR therefore reflects both increased inflammatory response and impaired nutritional or hepatic reserves\u0026mdash;both of which are related to COVID19 progression and organ dysfunction (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMechanistically, elevated CRP levels imply cytokinedriven inflammation, whereas hypoalbuminemia may reflect capillary leakage, liver damage, or malnutrition\u0026mdash;all contributing to immune dysregulation and adverse clinical outcomes (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). While other studies show comparable predictive power among these indicators (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan additionalcitationids=\"CR81\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e), some have found CAR to predict death and severe disease better than CRP or albumin alone. Variations in ideal CAR cutoffs and predictive accuracy (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e). could be explained by methodological differences including patient populations (general, pregnant, or postacute COVID19), timing of measurement, and result definitions. Overall, the evidence argues for CAR as a strong, readily available biomarker for early risk stratification in COVID19, however more prospective studies and standardization of cutoff values are required to perfect its clinical use (\u003cspan additionalcitationids=\"CR76 CR77 CR78 CR79 CR80 CR81\" citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study found notable changes in hematological indicators between noninfected controls and COVID19 patients. Observed in the COVID19 group was a rise in the neutrophiltolymphocyte ratio (NLR) and a corresponding drop in the lymphocytetoCRP ratio (LCR). These findings suggest a move toward greater systemic inflammation and compromised immunological regulation, therefore both NLR and LCR may be helpful indicators in the setting of COVID19.\u003c/p\u003e\u003cp\u003eIndependent of age or comorbidities, several recent metaanalyses and large cohort studies have shown that a high NLR is a strong predictor of both severe COVID19 illness and death, with admissions having higher NLR values correlating with worse outcomes (\u003cspan additionalcitationids=\"CR87 CR88 CR89\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e). Similarly, diminished LCR has been shown to be strongly related with higher risk of ICU admission and death; certain studies even indicate that in predicting 28-day mortality (\u003cspan additionalcitationids=\"CR92\" citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e) LCR can even beat NLR. Furthermore, it has been noted that while NLR and LCR levels usually stabilize during recovery, patients with bad prognosis exhibit continuously abnormal values (\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e). To our knowledge, no studies have published results contradicting our findings. These results highlight the clinical use of NLR and LCR as affordable, readily available indicators for early risk stratification and management of COVID19 patients, as well as the key role of immune and inflammatory dysregulation in disease progression (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we investigated the indirect indicators of COVID-19 risk in 394 subjects. Of all examined parameters, age, vitamin D, CRP, creatinine, potassium, Neu.Lym, and Lym.CRP was recognized to be a prognostic value in detecting COVID-19 risk. Given the importance of vitamins and electrolytes, periodic assessments and timely diagnosis can be helpful in early interventions through designing a complete food plan containing enough energy and high-potassium and vitamin content. Future studies are needed to assess dietary intake and other biochemical laboratory influences on COVID-19 risk.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACE2: Angiotensin Converting Enzyme Receptor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR: CRP to Albumin Ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCOVID19: Coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003eCRP: C Reactive Protein\u003c/p\u003e\n\u003cp\u003eICU: Intensive Care Unit\u003c/p\u003e\n\u003cp\u003eRAAS: Renin Angiotensin in Aldosterone System\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNLR: Neutrophil-to-lymphocyte ratio\u003c/p\u003e\n\u003cp\u003eNLR: Neutrophil to Lymphocyte Ratio\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVDR: Vitamin D receptor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVDBP: Vitamin D binding protein\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.KH: Contributed to the design, data interpretation, and approval of the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA.S: Contributed to data analysis and interpretation of results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eS.M: Contributed to the data collection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA.T: Contributed to the manuscript revising\u003c/p\u003e\n\u003cp\u003eM.A, Y.B, A.N.Y: Contributed to the confirmation and referring patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eL.P: Contributed to the conception, supervised the study, and approved of the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e Authors declare that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e The authors would like to acknowledge the financial support of Maragheh University of Medical Sciences for this research. The authors also thank all participants who contributed to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e According to Helsinki's Declaration,\u003cstrong\u003e\u0026nbsp;t\u003c/strong\u003ehe protocol of the study was approved by the ethics committee of Maragheh University of Medical Sciences and a written informed consent form was completed by participants. The regional ethics committee of the Maragheh University of Medical Science approved the protocol of the study and allocated the number IR.MARAGHEHPHC.REC.1399.021.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvalibilty of data and materials:\u0026nbsp;\u003c/strong\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSanamandra P, Gada JV, Misra S, Barasara SA, Varthakavi PK, Bhagwat NM. Correlation between Serum Vitamin D3 Levels and Severity of COVID-19, Experience from a COVID-19-Dedicated Tertiary Care Hospital from Western India. Indian J Endocrinol Metab. 2023;27(2):170\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePimentel GD, Dela Vega MCM, Pichard C. 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Int Immunopharmacol. 2022;109:108781.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID19, CRP, lymphocyte to neutrophil ratio, vitamin D, potassium","lastPublishedDoi":"10.21203/rs.3.rs-7745377/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7745377/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003eSince its detection, COVID19 has led to a worldwide health crisis with multi-systemic complications, involving the respiratory, cardiovascular, etc., health issues. Identifying of possible risk factors is important in finding the disease at an early stage and may improve the survival of patients. This study was carried out to evaluate inflammatory, hematological and nutritional indicators in order to determine the risk of COVID19 infection.\u003c/p\u003e\u003ch2\u003eMaterial and methods\u003c/h2\u003e\u003cp\u003eFrom 2021 to 2023 in Maragheh, northwest of Iran, 234 COVID19 cases and 160 nonCOVID19 controls were studied in this case-control study. Recruits were selected from referrals to local hospitals and health care centers of Maragheh University of Medical Scinces. Laboratory methods were used to determine the levels of serum vitamin D, potassium, CRP, and the hematological indices. Standard statistical analysis were performed in SPSS version 21and p-value less than 0.05 was considered statistically significant.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe gender distribution was almost the same in both groups (54% female and 52% p\u0026thinsp;=\u0026thinsp;0.858). The median serum level of CRP was higher in COVID19 patients 60.5 (40.0\u0026ndash;85.0) mg/L compared to the non-COVID19 group 37.5 (20.0\u0026ndash;65.0) mg/L (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The creatinine level was lower in the COVID19 group than in the non-COVID19 group (p\u0026thinsp;=\u0026thinsp;0.033). Additionally, the median of vitamin D was significantly lower in COVID19 group 33.0 (IQR: 22.045.0) ng/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The significant protective effect of vitamin D, potassium, creatinine, and lymphocyte to CRP (Lym. CRP) ratio with COVID19 was observed, while positive association was detected among age, CRP, and neutrophil to lymphocyte (Neu. Lym) ratio and increased risk of COVID19.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eIn conclusion, a simple approach to possibly lower the risk of COVID19 could be assessment inflammatory (CRP and lymphocyte to neutrophil ratio) and nutritional biomarkers (serum vitamin D and potassium).\u003c/p\u003e","manuscriptTitle":"Association of nutritional related biochemical markers with COVID-19 infection: a case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-07 01:28:52","doi":"10.21203/rs.3.rs-7745377/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-07T19:32:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T08:48:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T03:30:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-02T05:46:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93778633407753313720683612517821039585","date":"2025-10-31T04:16:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324647807699502293221274915729270312466","date":"2025-10-30T15:40:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264271427993788038592564085516510650914","date":"2025-10-30T07:04:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202566751716065843026810282710742693948","date":"2025-10-29T20:42:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228926419789273846459749153943212635421","date":"2025-10-28T22:34:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99940234401120709131296490353860176057","date":"2025-10-28T15:45:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-27T19:53:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T10:19:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-08T07:56:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-08T06:45:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-10-08T06:41:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"74de5e30-9ee6-46ae-9e65-48bfca38d15a","owner":[],"postedDate":"November 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T15:59:25+00:00","versionOfRecord":{"articleIdentity":"rs-7745377","link":"https://doi.org/10.1186/s12879-025-12297-0","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-12-23 15:57:10","publishedOnDateReadable":"December 23rd, 2025"},"versionCreatedAt":"2025-11-07 01:28:52","video":"","vorDoi":"10.1186/s12879-025-12297-0","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12297-0","workflowStages":[]},"version":"v1","identity":"rs-7745377","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7745377","identity":"rs-7745377","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}