key: cord-0270144-1nsye97n authors: MENEKSE, E.; DUZ, M. E.; BALCI, A. title: A biological variation-based approach to the day-to-day changes of D-dimer, Fibrinogen, and Ferritin levels that are crucial in the clinical course of COVID-19 in healthy smokers and non-smokers date: 2021-10-26 journal: nan DOI: 10.1101/2021.10.24.21265444 sha: 1387d00b38fe3ffba2d901d466fe85aa785d7435 doc_id: 270144 cord_uid: 1nsye97n Objective D-dimer, ferritin, and fibrinogen parameters in COVID-19 patients are essential, particularly in inpatients and intensive care unit patients. It is vital to know the changes that occur due to the biological structure of the person than the disease effect in these tests to manage the fatal disease better. Method Blood samples were taken on the first, third, and fifth days from 30 healthy volunteers, 15 of whom were smokers, 15 were non-smokers, and D-dimer, ferritin, and fibrinogen tests were studied with repeated measurements. After the data was processed for normality and homogeneity and removing extreme values, CVA, CVI, CVG, CVT, RCV, II, I%, B%, TE% values were calculated via a complete nested ANOVA design, according to Callum G, Fraser, and EFLM. Results CVI and CVG values of D-dimer were calculated as 49.07% and 40.69% for all individuals, 49.26% and 27.71% for smokers, 48.80% and 51.67% for non-smokers, respectively. In terms of fibrinogen, the same analyzes for all individuals were calculated as 11.18% and 10.62%, 3.25% and 20.17% for smokers, 9.11% and 6.79% for non-smokers, respectively. The same ferritin analyses were calculated as 23.74% and 63.31% for all individuals, 34.98% and 35.24% for smokers, 30.53% and 74.87% for non-smokers, respectively. Conclusion Changes in D-dimer measurements every other day in healthy individuals can be observed depending on the biological characteristics of the individuals, and the population-based reference interval may be insufficient for clinical evaluation. Therefore, each individual should be evaluated within themselves. When assessing the results of ferritin and fibrinogen in non-smoking individuals, it should be taken into account that significant differences may occur between individuals. Besides, it should be kept in mind that there may be considerable changes due to biological variation in the repeated measurements of ferritin every other day. The COVID-19 pandemic has opened deep wounds for human history, and its impact continues. Vaccination studies have not reached the desired levels, except for a few countries, and there is no cure for the disease [1] . The number of admissions to hospitals, the rate of inpatients, and the number of admissions to the intensive care unit have not yet fallen to the desired level [2] . For this reason, healthcare providers have to provide rapid diagnosis and treatment and make quick decisions. It is also vital to determine in advance which patient the COVID-19 infection will be mild and which will be severe to protect human life against the deadly virus. In terms of patients, biochemical parameters that can be of great benefit were determined when outpatient treatment, hospitalization, discharge, and admission to the intensive care unit were considered clinically [3] [4] [5] . Especially in the follow-up of inpatients and intensive care unit patients, D-dimer, fibrinogen, and ferritin have come to the fore, and they are influential on clinical decisions [6, 7] . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint variations may be related to natural variation [expressed as coefficient of variation (CV)] consisting of variations in preanalytical (CV P ), analytical (CV A ), and within-subject biological variation (CV I ) [8] . Between-subject biological variation (CV G ), described as the changes between the setpoints of different individuals, is another component of biological variation (BV) like CV I [8] . The index of individuality (II) calculated in the form of CV I /CV G is helpful at the point of whether the use of population-based reference intervals can be beneficial or not [9] . The reference change value (RCV) obtained from the BV data provides information on whether the differences in repeated measurements of the same analyte are clinically significant [10] . Previously the biological variation data compiled and collected by Dr. Carmen Ricos and colleagues on the Westgard website started to be published systematically by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) as of May 2019 [11, 12] . Besides, at the EFLM 1st Strategic Conference, BV studies were updated and re-standardized by addressing the analysis of BV data, the characteristics of the individuals who will form the sample, the differences in the working groups, and the uncertainties in the calculations [13] . Above all, EFLM has continued to work to accomplish the challenges on these problems and has strived to broaden the reliable BV data by courtesy of the Working Group in BV (WG-BV) [14] . Also, analytical performance specifications (APS) for imprecision (I%), bias (B%), and total error (TE%) of several analytes derived from BV data were published on the EFLM website [12] . It has been reported that for biological variation analysis, samples should be taken from healthy individuals within a period of at least ten weeks, weekly [15] . However, it is essential that we must use all the resources we have in combating the deadly and incurable COVID-19 pandemic. Between-individual and intra-individual changes in follow-up parameters directly affect clinical decisions about patients. If CVI, CVG, and RCV can affect these decisions on a . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint daily basis, it may be important to evaluate the results from this perspective in terms of benefit to patients. This is our primary motivation that drives our work to realize. Thirty healthy individuals as fifteen smokers and fifteen non-smokers, volunteered for the study. Volunteers were selected from the laboratory work team. A detailed explanation about the study was made to the volunteers. Informed consent was obtained from individuals. Amasya University ethics committee approval was taken for the study. The reason to form the groups according to smoking is because of the prothrombotic, inflammatory, and endothelial damage effects of smoking. Since these effects can impact our research parameters and smoking is an essential factor in COVID-19 patients, we carried out our group planning in this direction. Unlike the known biological variation studies, samples were taken from the volunteers for a total of three days, on the first, third, and fifth days, as the parameters that affect the clinical decisions taken in terms of daily changes in COVID-19 were evaluated. Those with a history of deep vein thrombosis and pulmonary embolism, and those who received antiaggregant or anticoagulant therapy were excluded from the study, as their Ddimer and fibrinogen results would be affected, and those with chronic inflammatory conditions, anemic patients, and those receiving iron therapy excluded because their ferritin levels could be affected. Those who had COVID-19, pregnant women, and regular medication were also excluded from the study. . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint Fasting blood was collected from the volunteers every other day, on the first, third, and fifth days, in a yellow-capped tube with no gel additive and a blue-capped citrate tube. Blood samples were drawn between 8 a.m -10 a.m with an 8-hour night fasting by the same trained phlebotomist. Twenty minutes after blood was taken, plasma and serum samples were obtained by centrifugation at 1500 G for 15 minutes. Plasma and serum samples were accumulated at -80 ° C until the day of the study. After waiting for the samples to dissolve at room temperature on the analyzing day, centrifugation was performed again at 1500 G for 15 minutes. All tests were duplicated to assess analytical variation. Serum ferritin analyzes were Başakşehir, Istanbul, TURKEY). The 99th percentile limit is specified as ≥ 0.5 µg FEU/mL, within run % CV 1.3-3.7, between run % CV 3.3-4.5. All analyzes were performed on a single day with the same lot number of calibrators, controls, and reagents. On the days of the studies, two levels of quality control samples, one normal and one pathological were run for each analyte to verify suitability for analysis. In order to reduce analytical variation, the assays of all volunteers were run under the same calibrator curve. . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The following calculation was used to calculate the RCV for the parameters: RCV = 2 1/2 *Z*(CV A 2 +CV I 2 ) 1/2 . II values were obtained using the following calculation: Finally, analytical performance specifications (APS) for the targeted uncertainty (% I), bias (% B), and total error (% TE) are specified using the formulas shown below: I%=0.5CV I B%=0.25(CVI2+CVG2)1/2 TE%=I%×1.65+B% . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint The data of the 30 patients were statistically analyzed. According to normality tests, D-dimer, fibrinogen, and ferritin parameters were found to comply with the normal distribution (p=0.074, p=0.063, p=0.086, respectively). After performing the extreme value analyzes, individuals 8 and 12 from the non-smoking group and individual 15 (number 30 in total) from the smoker group were excluded from the study together with the repeated analysis data for ferritin. According to the repeated normality tests, ferritin was again found to be normally distributed (p=0.067). After testing the homogeneity of variances (p=0.867 for D-dimer, 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 F e r r i t i n m e a n a n d S D l e v e l s . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The subject is limited in terms of literature regarding BV and APS data of D-dimer. In a study of 19 healthy non-pregnant women, the CV I for D-dimer was 23.3, CV G 26.5, and CV A 31.8 [16] . On the Westgard website, D-dimer BV data is shown as; CV I 23.5, CV G 26.5, I% 11.65, B% 8.82, and TE% 28.04, data probably taken from the same study [11] . Considering our study data, CV G values in terms of D-dimer are compatible in smokers with previous studies. Besides, the CV A was found to be lower than the stated study before [16] . Our study quality was found to be low in terms of APS. It may be because we sampled every other day, as we aim to see short-term changes rather than long-term weekly sampling. However, our CV A values express the quality of our measurements. D-dimer's high RCV and II values indicate that the test will show high changes in short-range measurements. Also, test individuality is high, and it would not be appropriate to evaluate patients according to population-based reference ranges. The researchers determined BV values for fibrinogen as CV I 11.9, CV G 17.0, and CV A 2.7 [17] . In one review, CV I values for fibrinogen were reported in the range of 13-67 and CV G values in the range 33-87 [18] . According to Westgard data, CV I was 10.7, CV G 15.8, I% 5.4, B% 4.8, TE% 13.6 for fibrinogen [11] . Our study findings are suitable with previous studies in BV and APS, except for CV G values that we found higher in smokers than literature. When . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint all patients and the non-smoking group were considered, II values were found to be high, while it was found to be low in smokers. We do not understand the low individuality of fibrinogen in smokers. Perhaps, the difference in the amount and type of cigarettes people use may cause different results between individuals, reducing the individuality index. While the median CV I value of ferritin was given as 12.8 in the EFLM database, in the studies reported on the same page, CV I was stated in the ranges of 9.7-25. 8 higher. Similar to our D-dimer results, CVG values were calculated lower in the smoking group, but the II value was also high. In addition, our RCV calculations included high results. According to our calculations, the population-based reference interval may not be sufficient for the clinical evaluation of ferritin values repeated every other day. Also, ferritin measurements in smokers can show individual characteristics. Although our CVA data were at acceptable levels except for the smoking group, our APS calculations could not exhibit an adequate level of quality. Changes in D-dimer measurements every other day in healthy individuals can be observed depending on the biological characteristics of the individuals, and the population-based reference interval may be insufficient for clinical evaluation. Each individual should be evaluated within himself/herself. When evaluating the results of ferritin and fibrinogen in non-smoking individuals, it should be taken into account that significant differences may . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint occur between individuals. Besides, it should be kept in mind that there may be significant changes due to biological variation in the repeated measurements of ferritin every other day. Our inability to reach sufficient APS values in D-dimer and ferritin parameters maybe because we do not apply a typical biological variation procedure because we are planning every other day for COVID-19, which requires rapid clinical decision-making and can change treatment plans according to daily parameter changes. First of all, this study was conducted with healthy volunteers and does not reflect the clinical and biological conditions of COVID-19 patients. Besides, the study is not a typical biological variation analysis planned according to the procedures specified in the EFLM guidelines but is designed to observe the day-to-day change. data. Statistics and research. Coronavirus (COVID-19) vaccinations Accessed online at 20.03.2021. 2. Ncov 2019 Live. World COVID-19 stats Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease the author/funder, who has granted medRxiv a license to display the preprint in perpetuity Prognostic value of liver biochemical parameters for COVID-19 Koagulopatie asociovaná s onemocněním COVID-19 C-reactive protein, procalcitonin, D-dimer, and ferritin in severe coronavirus disease-2019: a meta-analysis Fibrinogen and D-dimer variances and anticoagulation recommendations in Covid-19: current literature review Biological variation: from principles to practice Influence of index of individuality on false positives in repeated sampling from healthy individuals Reference change values Accessed online at 20.03.2021. 12. EFLM Biological Variation Database International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity Sample collections from healthy volunteers for biological variation estimates' update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine Reliability of biological variation data available in an online database: need for improvement Biological variation database: structure and criteria used for generation and update A model for calculating the within-subject biological variation and likelihood ratios for analytes with a time-dependent change in concentrations exemplified with the use of D-dimer in suspected venous thromboembolism in healthy pregnant women Biological Variation of Hemostasis Variables in . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted October 26, 2021. ; https://doi.org/10.1101/2021.10.24.21265444 doi: medRxiv preprint