Heliyon 9 (2023) e15198 Contents lists available at ScienceDirect Heliyon journal homepage: www.cell.com/heliyon Research article Biochemical markers of nephrotic syndrome: An observational, cross-sectional study Emmanuel Kwaku Ofori a,*, Egyam Bill Clinton a,b, Obed Danso Acheampong a,c, Henry Asare- Anane a, Seth Kwabena Amponsah d, Jayasinghe SU e, Seth Dortey Amanquah a a Department of Chemical Pathology, University of Ghana Medical School, College of Health Sciences, University of Ghana, Accra, Ghana b MDS-Lancet Laboratories Ghana Limited, Accra, Ghana c School of Veterinary Medicine, College of Basic and Applied Sciences, University of Ghana, Accra, Ghana d Department of Medical Pharmacology, University of Ghana Medical School, College of Health Sciences, University of Ghana, Accra, Ghana e School of Health Sciences, College of Health and Medicine, University of Tasmania, Tasmania, Australia A R T I C L E I N F O A B S T R A C T Keywords: Background: Blood protein leakage, especially albumin, into the urine is the hallmark of nephrotic Nephrotic syndrome syndrome (NS), which poses a serious public health problem. The absence of albumin prompts the Albumin liver to produce more proteins to make up the difference. The therapeutic significance of these Proteins additional proteins in NS is not yet fully understood. Kidney Electrophoresis Methods: In total, 99 patients with NS and 47 persons without NS (control group) were included in this cross-sectional study. Socio-demographic and clinical information were obtained from re- cruits utilizing a standard questionnaire and a check of the lab order forms for individuals. Each participant had a 6-mL (6 mL) sample of venous blood taken and levels of calcium, C-reactive protein (CRP), albumin, and other proteins in the serum were assayed. The proteins in serum were separated using the electrophoresis technique, and the various fractions were then measured by a densitometer. Calculations were made for the oncotic pressure. Results: The NS group had significantly greater levels of serum CRP, urea, alpha-2-globulin, gamma globulins, and M component than the control group (p < 0.05 respectively). Trans- ferrin, total proteins, albumin, beta-1-globulins, calcium, and oncotic pressure were significantly higher in persons without NS compared to the NS group (p < 0.05 respectively). In addition, levels of CRP (odds ratio = 1.41, p = 0.005) and gamma globulin (odds ratio = 4.12, p = 0.005) in the blood were observed to be independent predictors in the occurrence of NS. These two factors increased the likelihood of developing NS by approximately 1.5 and 4 times, respectively. Conclusion: Among the proteins assayed, CRP and gamma globulin were found to be predictors of NS. Nonetheless, further studies are required to understand the mechanisms associated with these serum proteins in NS. * Corresponding author. E-mail address: ekofori1@ug.edu.gh (E.K. Ofori). https://doi.org/10.1016/j.heliyon.2023.e15198 Received 16 October 2022; Received in revised form 28 March 2023; Accepted 29 March 2023 Available online 5 April 2023 2405-8440/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). E.K. Ofori et al. H e l i y o n 9 (2023) e15198 1. Introduction Chronic Kidney Disease (CKD) is highly prevalent in sub-Saharan Africa and accounts for 14.6%–50% of renal disorders [1–4], and 0.35–1.34% of overall hospital admissions [5–8]. It is well known that Nephrotic syndrome (NS), characterized by chronic inflam- mation, and high levels of proteins in urine (i.e., 3.5 g/1.73 m2 of body surface area per day), is a major contributing factor to the development of CKD [5,9–13]. Importantly, exacerbation of NS can lead to end-stage renal disease, which usually necessitates transplantation of kidneys and/or weekly dialysis treatments [5,14] leading to outcomes that are associated with significant health, social, familial and financial burdens. Plasma proteins larger than 70 Kilo Dalton (kd) are known to be blocked from crossing the glomerular basement membrane in healthy kidneys by a charge- and size-selective barrier [15–18]. In contrast, damage to the glomerular basement membrane meshwork, typical in NS aetiology, may allow leakage of proteins from the blood [19–21]. For instance, it is not uncommon to see a marked increase in urine Albumin in NS. If left unabated, kidney membrane permeability can progressively increase, potentially resulting in a plethora of cardiovascular complications including coagulopathy [22,23]. Despite the different causes of NS, there is a substantial therapeutic challenge, especially in low-resource countries such as Ghana [24,25]. Accordingly, research reporting on proteinuria and oncotic pressure has a biased focus on Albumin. Because of the increased excretion of Albumin, the liver must produce more proteins vital to the upkeep of oncotic pressure. These proteins include alpha-2-macroglobulins and beta-lipoproteins [11,12]. The significance of these additional proteins in NS has not yet been fully elucidated, which could potentially have implications for the clinical management of NS. The aims of this research were twofold. 1. Determine variations in oncotic pressure, albumin, or non-albumin proteins in patients with NS and their healthier counterparts, 2. Investigate the predictors of NS development. 2. Methods 2.1. Research design, participants, and ethical consideration The study was conducted at MDS-Lancet Laboratories Ghana Limited. The Ethics and Protocol Review Committee of the University of Ghana’s College of Health Sciences (CHS) approved all procedures (ID: CHS–Et/M2-5.5/2019–2020). Before being admitted to the study, each participant gave their signed, informed consent. A total of 146 participants (99 individuals with NS and 47 healthy in- dividuals) were recruited for this research. MDS-Lancet Laboratories clientele who had a prior diagnosis of NS and/or who had been referred for additional diagnostic tests were eligible to be recruited into the NS group. The diagnostic criteria for NS have been described in a prior publication [26]. Participants in the control group all had negative clinical and laboratory indicators for NS and had been selected after having a routine medical examination at the facility. Medical staff and researchers decided not to include participants who had pre-existing conditions like diabetes mellitus, renal disorders, immunocompromised, or individuals who had serious diseases requiring emergency medical attention. 2.2. Outcome metrics 2.2.1. Anthropometric measurements and demographic traits Participants’ demographic and clinical details were collected via a standardized questionnaire and a review of their laboratory request form. All participants had their weight and height measured to the nearest 1.0 kg (kg) and 0.005 m (m), respectively, using a standard physician’s scale and a wall-mounted meter rule. To determine body mass index (BMI), we used the formula: weight/height squared (kg/m2). 2.2.2. Laboratory procedures A phlebotomist took 6 mL of venous blood from each of the subjects who were recruited while taking the necessary precautions to prevent hemolysis. Two milliliters of each blood sample were transferred to a tube containing ethylene diamine tetra acetic acid (EDTA), and the remaining 4 mL were transferred to a tube containing a gel separator for processing. After letting the samples in the gel separator tubes coagulate for ten to 15 min at room temperature, they were centrifuged at three thousand revolutions per minute for 10 min to obtain the sera. The collection of samples took place between the hours of 7:00 and 9:00 in the morning. Every day, a total of six samples were taken, then processed, and kept at − 20◦ Celsius for a period of up to six months. The concentrations of urea, creatinine, calcium, albumin, and non-albumin protein fractions (alpha-1-, alpha-2-, beta-1-, beta-2-, C reactive proteins, transferrin, M component, and gamma-globulins) were measured using sera. The various proteins were also determined using an electrophoretic method, with the various protein fractions identified using a densitometer. The oncotic pressure was calculated using a formula that was previously discussed [27]. 2.3. Statistical analysis The information that was gathered was initially entered into Microsoft Excel and then transferred to Statistical Products and Services Solutions version 25 for additional analysis. A preliminary analysis was carried out to see if the data violated normality or residual independence. This was checked using the Shapiro-Wilk test of normality and the assumption was not violated (p > 0.05). The obtained sociodemographic, clinical, and biochemical characteristics were summarized using descriptive statistics. An independent- 2 E.K. Ofori et al. H e l i y o n 9 (2023) e15198 sample t-test with an alpha level of 0.05 was used to evaluate whether there were differences in means for continuous data across the research groups. An Eta squared statistic was performed to measure the extent of the observed variations (effect size), and the results were interpreted as previously described (0.01 = minimal effect; 0.06 = moderate impact; and 0.14 = major effect) [28,29]. Lastly, to assess determinants of the occurrence of NS among the study subjects, a conditional logistic regression (to have a robust estimate of our results since the sample size was unbalanced) was carried out. We determined the p values, odds ratios, and confidence intervals for each predictor to establish its significance. Statistical significance was achieved when the probability value was less than 0.05. 3. Results 3.1. Demographic and clinical characteristics Table 1 provides an overview of the demographic information as well as the clinical features of the participants. There were 51.5% (n = 51) and 44.7% (n = 21) males in the NS and control groups, respectively. In the NS group, the distribution for females was 48.5% (n = 48), while the control group had a distribution of 55.3% (n = 26). Those in the NS group had a mean age of 46.95 ± 22.19 years old, while those in the control group were 45.72 ± 16.08 years old, with corresponding mean BMI values of 23.63 ± 3.06 kg/m2 and 25.14 ± 3.08 kg/m2, respectively for the NS and control groups. Furthermore, the majority did not have any NS family history [84.8% (n = 84) in the NS group and 91.5% (n = 43) in the control group]. 3.2. Albumin, oncotic pressure, and non-albumin protein levels in NS vs control When compared with the control group, an independent-sample t-test revealed that the serum levels of C-reactive protein, urea, alpha-2-globulin, gamma globulins and M component were significantly higher among the NS group (p < 0.05 for all). In contrast, the NS group had lower concentrations of transferrin, total proteins, albumin, beta-1-globulin, calcium and oncotic pressure (p < 0.05 for all). Levels of creatinine, alpha-1-globulin and beta-2-globulins were not different between the two groups (p > 0.05) (Table 2). 3.3. Predictors of the incidence of NS The findings of the binary logistic regression analysis are indicated in Table 3. Significant predictors of NS in this population Table 1 Participant demographics and clinical (categorical) characteristics. Variables NS Group Control Group Chi-square χ2 p-value Number (99) % Number (47) % Gender 0.85 0.74 Male 51 51.5 21 48.0 Female 48 48.5 26 52.0 Marital status 17.65 0.04 Single 28 28.3 6 12.8 Married 64 64.6 40 85.1 Not applicable 7 7.1 1 2.1 BMI 13.52 0.004 Underweight 9 9.09 1 2.13 Normal weight 60 60.6 20 42.5 Overweight 30 30.3 23 48.9 Obese 0 0.00 3 6.38 Occupation 6.12 0.33 Finance sector 12 12.1 4 8.5 Trader 23 23.2 16 34.0 Education sector 12 12.1 14 29.8 Retired 28 28.3 9 19.1 Student 10 10.1 3 6.4 Not applicable 8 8.1 1 2.1 Alcohol consumption Yes 45 45.5 23 48.9 0.19 0.58 No 54 54.5 24 51.1 Family history of nephrotic syndrome Yes 15 15.2 4 8.5 1.24 0.27 No 84 84.8 43 91.5 The sociodemographic and clinical characteristics of the research participants are summarized in Table 1. The frequency (No.) and percentages (%) of the data were calculated, and a p-value of 0.05 was judged significant. Age [Nephrotic Group (X ±SD) = 46.95 ± 22.19 years; Control Group (X ±SD) = 45.72 ± 16.08 years]; BMI [Nephrotic Group (X ±SD) = 23.63 ± 3.06 kg/m2; Control Group (X ±SD) = 25.14 ± 3.08 kg/m2]; NS is nephrotic syndrome, χ2 is chi-square. 3 E.K. Ofori et al. H e l i y o n 9 (2023) e15198 Table 2 A comparison of biochemical parameters of the study participants. Variables NS Group Control Group p-value 95% CI Mean ± S.E.M. Mean ± S.E.M. C-reactive protein (mg/L) 57.65 ± 8.34 1.88 ± 0.44 <0.001 39.20–72.33 Creatinine (μmol/L) 198.96 ± 33.95 125.76 ± 28.00 0.104 − 13.80 – 160.20 Urea (μmol/L) 9.34 ± 1.13 5.95 ± 0.78 0.020 0.67–6.12 Transferrin (μmol/L) 20.38 ± 0.98 33.98 ± 1.23 <0.001 − 16.72–− 10.47 Total proteins (g/L) 61.14 ± 1.76 68.89 ± 1.39 <0.001 − 13.18–− 4.32 Albumin (g/L) 26.51 ± 1.11 39.48 ± 1.18 <0.001 − 16.19–− 9.78 Alpha-1-globulin (g/L) 2.27 ± 0.09 1.89 ± 0.35 0.171 − 0.17 – 0.92 Alpha-2-globulin (g/L) 7.28 ± 0.30 6.56 ± 0.21 0.049 − 0.002 – 1.45 Beta-1-globulin (g/L) 4.83 ± 0.13 5.32 ± 0.12 0.013 − 0.85–− 0.14 Beta-2-globulin (g/L) 3.09 ± 0.14 3.06 ± 0.12 0.892 − 0.33–− 0.39 Gamma globulin (g/L) 13.14 ± 0.86 9.51 ± 0.18 <0.001 1.90–5.36 M component (g/L) 2.41 ± 1.24 0.25 ± 0.10 0.012 − 0.21 – 4.75 Calcium (mmol/L) 2.08 ± 0.03 2.41 ± 0.03 <0.001 − 0.42–− 0.24 Oncotic pressure (mmHg) 20.02 ± 0.74 27.73 ± 0.79 <0.001 − 9.86–− 5.57 The biochemical characteristics of the study participants are summarized in Table 2. The mean and standard error of the mean is used to describe the data. NS is nephrotic syndrome, SEM is the standard error of the mean. Statistical significance was set at the 0.05 alpha level. CI is the confidence interval. Table 3 Predictors for the development of NS. Predictors B S.E. Wald p-value OR 95% CI CRP 0.349 0.12 7.78 0.005 1.41* 1.107–1.792 Creatinine 0.015 0.002 0.014 0.90 1.00 0.996–0.004 Urea − 0.301 0.10 8.27 0.004 0.74* 0.606–0.910 Transferrin − 0.143 0.09 2.33 0.131 0.87 0.722–1.042 Total proteins − 0.367 0.44 0.69 0.412 0.69 0.292–1.642 Albumin 0.052 0.123 0.176 0.674 1.05 0.827–1.341 Alpha-1-globulin − 0.920 0.336 7.56 0.006 0.50* 0.206–0.767 Alpha-2-globulin 0.188 0.377 0.249 0.621 1.21 0.577–2.525 Beta-1-globulin 0.614 0.588 1.092 0.302 1.85 0.584–5.847 Beta-2-globulin − 0.752 0.579 1.682 0.203 0.47 0.151–1.469 Gamma globulin 1.415 0.506 7.833 0.005 4.12* 1.528–11.091 M component 0.343 0.359 0.914 0.339 1.41 0.698–2.846 Family history of nephrotic syndrome 1.537 1.030 2.229 0.135 4.65 0.618–35.00 Alcohol consumption 0.105 0.786 0.18 0.893 1.11 0.238–5.184 Gender 0.446 0.862 0.268 0.605 1.56 0.288–8.464 Oncotic pressure 0.290 0.730 0.158 0.691 1.34 0.320–5.594 BMI − 0.485 0.189 6.589 0.010 0.62* 0.425–0.892 Calcium − 3.127 1.856 2.838 0.092 0.14 0.001–1.667 The predictors of NS among study participants have been listed in Table 3. *Statistically significant at the alpha level of 0.05; SE is standard error; OR is odds ratio; CRP is C reactive protein; BMI is body mass index. included C-reactive protein (CRP), urea, alpha-1-globulin, gamma globulin and BMI. Raised levels of CRP (OR = 1.41, p = 0.005) and gamma globulin (OR = 4.12, p = 0.005) in the blood increased the odds of occurrence of NS by approximately one and a half and four- folds, respectively, whereas BMI (OR = 0.62, p = 0.010), serum levels of urea (OR = 0.74, p = 0.004), and alpha-1-globulin (OR = 0.50, p = 0.006) had less predictive power. 4. Discussion The primary purpose of this study was to evaluate the differences between NS and healthy volunteers concerning the concentra- tions of albumin and non-albumin proteins like C-reactive protein, urea, transferrin, alpha-1-globulin, alpha-2-globulin, beta-1- globulins, beta-2-globulins, gamma globulins, and M component. In comparison to the control group, those with NS had signifi- cantly increased concentrations of C-reactive protein, urea, gamma globulins and alpha-2-globulins in their blood. Furthermore, the levels of transferrin, total proteins, albumin, and beta-1-globulins were significantly lower in the case group compared to the control group. This observation of high C-reactive protein and low albumin levels among participants in the NS group is consistent with prior studies. In patients with NS undergoing dialysis, previous studies report high C-reactive protein levels and decreased blood albumin levels [30–32]. It is noteworthy, that, low blood albumin levels are a significant contributor to hypocalcemia in patients with NS [33, 34] and so a compelling argument may be made that this cohort of NS patients may be at risk of hypocalcemia. Although reduced levels of albumin among NS patients have been linked to hypovolemia, the albumin levels of the NS patients in the current study, although 4 E.K. Ofori et al. H e l i y o n 9 (2023) e15198 lower than the control group, did not appear to be associated with hypovolemia. A further significant objective of the present investigation was to determine whether or not individuals who had been diagnosed with NS had distinct colloid osmotic pressures from those who did not have NS. According to the findings of this study, the oncotic pressure in the group that had NS was significantly lower than that of the control group. Usually, patients with NS have much lower albumin than the general population [11,12]. Some studies have suggested that albumin is responsible for maintaining colloid oncotic pressure in the majority of instances. Reports suggest that albumin accounts for approximately eighty percent of the colloid osmotic pressure [35,36], which has been attributed to the fact that its concentration is over twice that of globulin, even though it has the lowest molecular weight among the major plasma proteins. Interestingly, colloid osmotic pressure has been proposed as a control of albumin production [37,38]. Most crucially, despite much larger levels of C-reactive protein, urea, alpha-2-globulins, and gamma globulins in the NS group, they were unable to maintain colloid oncotic pressure. This appears to be yet another piece of information from the current study that supports past claims that albumins are the main proteins contributing to colloid oncotic pressure. The third purpose of this research was to determine risk factors for NS. The chance of being diagnosed with NS rose by around 1.5 times for those with elevated C-reactive protein levels and by a factor of 4 for those with elevated gamma globulin levels. The risk of developing NS was however inversely associated with BMI and with blood levels of urea and alpha-1-globulin. Despite these afore- mentioned results, additional studies are required to fully elucidate predictors of the incidence of NS. A strength of the study was the quantification of non-albumin protein fractions in sera using a densitometer, after separation by electrophoresis. Some limitations of the current study included not determining several comorbidities such as hyperlipidemia, hy- pertension and diabetes mellitus in recruited subjects. These comorbidities are associated with serum osmotic pressure in NS. Thus, this study cannot account for the dynamics that these comorbidities bring to NS. The authors were also unable to incorporate infor- mation on how the detected biomarkers affected overall survival since we did not conduct a follow-up with the participants. Unfor- tunately, our case participants’ steroid therapy records were inaccessible for this investigation. This could have had an impact on the biochemical parameters measured. Additionally, urine samples were not collected and analyzed in this study, hence, may have pre- vented the understanding of a full picture of the epidemiology of NS. Furthermore, because this was a cross-sectional study, we were limited in our ability to determine the explanation or cause for the observed associations. 5. Conclusion In comparison to the control group, the NS group had higher levels of C-reactive protein, urea, and gamma globulins and lower levels of transferrin, total proteins, albumins, beta-1-globulins, calcium, and colloid osmotic pressure. Elevated C-reactive protein and gamma globulin levels in the blood enhanced the likelihood of developing NS by almost one-half and four-fold respectively. Although our findings add considerably to the gaps in the pathophysiology of NS, more research is needed to understand the mechanistic el- ements of NS. Ethical approval and consent to participate The College of Health Sciences (CHS), University of Ghana, through their Ethical and Protocol Review Committee (EPRC), gave ethical permission for this study (ID: CHS–Et/M2-5.5/2019–2020). In-depth descriptions of the study’s objective, risks, and benefits were given to participants. All participants signed a consent form after obtaining the necessary information. Author contribution statement Emmanuel Kwaku Ofori: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper. Egyam Bill Clinton: Performed the experiments; Contributed reagents, materials, analysis tools or data; Wrote the paper. Henry Asare-Anane: Conceived and designed the experiments; Wrote the paper. Seth Dortey Amanquah: Conceived and designed the experiments; Wrote the paper. Seth Kwabena Amponsah: Analyzed and interpreted the data; Wrote the paper. Jayasinghe SU: Analyzed and interpreted the data; Wrote the paper. Obed Danso Acheampong: Performed the experiments; Wrote the paper. Funding No funding was received for this project. Availability of data and material The corresponding author will make the datasets that were used throughout this study available to the interested party upon reasonable request. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to 5 E.K. Ofori et al. H e l i y o n 9 (2023) e15198 influence the work reported in this paper. Acknowledgements The authors would like to thank the Managers and Biomedical Scientists at MDS-Lancet Laboratories Ghana Limited. The authors also recognize the Department of Chemical Pathology, University of Ghana Medical School, for its institutional support. References [1] D.N. Adjei, et al., Chronic kidney disease burden among African migrants in three European countries and in urban and rural Ghana: the RODAM cross-sectional study, Nephrol. Dial. Transplant. 33 (2018) 1812–1822. [2] T.O. Olanrewaju, et al., Prevalence of chronic kidney disease and risk factors in North-Central Nigeria: a population-based survey, BMC Nephrol. 21 (2020) 1–10. [3] T.E. Matsha, R.T. Erasmus, Chronic kidney disease in sub-Saharan Africa, Lancet Global Health 7 (2019) e1587–e1588. [4] J.W. Stanifer, et al., The epidemiology of chronic kidney disease in sub-Saharan Africa: a systematic review and meta-analysis, Lancet Global Health 2 (2014) e174–e181. [5] S. Naicker, End-stage renal disease in sub-Saharan Africa, Kidney Int. Suppl. 3 (2013) 161–163. [6] F.A. Arogundade, R.S. Barsoum, CKD prevention in Sub-Saharan Africa: a call for governmental, nongovernmental, and community support, Am. J. Kidney Dis. 51 (2008) 515–523. [7] C. Osafo, et al., Genomic approaches to the burden of kidney disease in sub-Saharan Africa: the human heredity and health in Africa (H3Africa) kidney disease research network, Kidney Int. 90 (2016) 2–5. [8] W.A. Olowu, et al., Outcomes of acute kidney injury in children and adults in sub-Saharan Africa: a systematic review, Lancet Global Health 4 (2016) e242–e250. [9] J. Fabian, S. Naicker, HIV and kidney disease in sub-Saharan Africa, Nat. Rev. Nephrol. 5 (2009) 591–598. [10] S. Naicker, G. Ashuntantang, End stage renal disease in sub-Saharan Africa, in: Chronic Kidney Disease in Disadvantaged Populations, Elsevier, 2017, pp. 125–137. [11] C.-s. Wang, L.A. Greenbaum, Nephrotic syndrome, Pediatr. Clin. 66 (2019) 73–85. [12] R.P. Hull, D.J. Goldsmith, Nephrotic syndrome in adults, BMJ 336 (2008) 1185–1189. [13] I.G. Okpechi, et al., Nephrotic syndrome in adult black South Africans: HIV-associated nephropathy as the main culprit, J. Natl. Med. Assoc. 102 (2010) 1193–1197. [14] I.B. Salusky, W.G. Goodman, Cardiovascular calcification in end-stage renal disease, Nephrol. Dial. Transplant. 17 (2002) 336–339. [15] G. Jarad, J.H. Miner, Update on the glomerular filtration barrier, Curr. Opin. Nephrol. Hypertens. 18 (2009) 226. [16] S. Satchell, The role of the glomerular endothelium in albumin handling, Nat. Rev. Nephrol. 9 (2013) 717–725. [17] E. Arif, D. Nihalani, Glomerular filtration barrier assembly: an insight, Postdoc. J. 1 (2013) 33. [18] R.W. Naylor, et al., Complexities of the glomerular basement membrane, Nat. Rev. Nephrol. 17 (2021) 112–127. [19] J.L. Ruth, S.J. Wassner, Body composition: salt and water, Pediatr. Rev. 27 (2006) 181–188. [20] D. Ellison, F.C. Farrar, Kidney influence on fluid and electrolyte balance, Nurs. Clin. 53 (2018) 469–480. [21] T. Benzing, D. Salant, Insights into glomerular filtration and albuminuria, N. Engl. J. Med. 384 (2021) 1437–1446. [22] E. Siddall, et al., Capillary leak syndrome: etiologies, pathophysiology, and management, Kidney Int. 92 (2017) 37–46. [23] E. Ahmadian, et al., Covid-19 and kidney injury: pathophysiology and molecular mechanisms, Rev. Med. Virol. 31 (2021), e2176. [24] J.Y. Doe, et al., Nephrotic syndrome in African children: lack of evidence for ‘tropical nephrotic syndrome, Nephrol. Dial. Transplant. 21 (2006) 672–676. [25] R.A. Gbadegesin, et al., Genetic testing in nephrotic syndrome—challenges and opportunities, Nat. Rev. Nephrol. 9 (2013) 179–184. [26] C. Kodner, Diagnosis and management of nephrotic syndrome in adults, Am. Fam. Physician 93 (2016) 479–485. [27] J.A. Guardia, et al., Oncotic pressure and edema formation in hypoalbuminemic HIV-infected patients with proteinuria, Am. J. Kidney Dis. 30 (1997) 822–828. [28] T.R. Levine, C.R. Hullett, Eta squared, partial eta squared, and misreporting of effect size in communication research, Hum. Commun. Res. 28 (2002) 612–625. [29] I.S.H. AlWahaibi, et al., Cohen’s criteria for interpreting practical significance indicators: a critical study, Cypriot Journal of Educational Sciences 15 (2020) 246–258. [30] M. Kaplan, et al., Predictive value of C-reactive protein/albumin ratio in acute pancreatitis, Hepatobiliary Pancreat. Dis. Int. 16 (2017) 424–430. [31] F. Guerrero-Romero, M. Rodriguez-Moran, Relationship between serum magnesium levels and C-reactive protein concentration, in non-diabetic, non- hypertensive obese subjects, Int. J. Obes. 26 (2002) 469–474. [32] N.S. Akkececi, et al., The C-reactive protein/albumin ratio and complete blood count parameters as indicators of disease activity in patients with Takayasu arteritis, Med. Sci. Mon. Int. Med. J. Exp. Clin. Res.: Int. Med. J. Exp. Clin. Res. 25 (2019) 1401. [33] S.J. Park, J.I. Shin, Complications of nephrotic syndrome, Kor. J. Pediatr. 54 (2011) 322. [34] V.I. Winata, et al., Relationship between ionized calcium and serum albumin level in children with idiopathic nephrotic syndrome, Paediatr. Indones. 50 (2010) 361–364. [35] A. Darwish, F. Lui, Physiology, colloid osmotic pressure [Internet], in: StatPearls, StatPearls Publishing, 2021. [36] P. Caraceni, et al., Clinical indications for the albumin use: still a controversial issue, Eur. J. Intern. Med. 24 (2013) 721–728. [37] J.-L. Vincent, Relevance of albumin in modern critical care medicine, Best Pract. Res. Clin. Anaesthesiol. 23 (2009) 183–191. [38] C.M. Berkowitz, Does albumin regulate albumin? Hepatology 16 (1992) 1499–1501. 6