Evaluation of maternal serum lipid profiles and clinical chemistry parameters in the prediction of pre-eclampsia in pregnant women attending ANC and delivery services

Evaluation of maternal serum lipid profiles and clinical chemistry parameters in the prediction of pre-eclampsia in pregnant women attending ANC and delivery services | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluation of maternal serum lipid profiles and clinical chemistry parameters in the prediction of pre-eclampsia in pregnant women attending ANC and delivery services Endalamaw Tesfa, Abaineh Munshea, Endalkachew Nibret, Daniel Mekonnen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2404370/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Pre-eclampsia (PE) is a pregnancy related metabolic syndrome which adversely influence the mother and their newborn infants. Besides, lack of study in our population, some studies also reporting discrepancies in the association of lipid profiles and clinical chemistry parameters with the risk of PE. Hence, this study was designed to evaluate the diagnostic potential of serum lipid profiles and clinical chemistry parameters with PE. Institution-based case-control study was performed at Bahir Dar city governmental hospitals. The study participants were selected through simple random sampling and the socio-demographic data were collected by interview-administered questionnaire. Five ml of venous blood were collected to evaluate lipid profile and clinical chemistry parameters. Descriptive statistics, chi-squared test, multivariable logistic regression and Mann-Whitney U test were utilized for analysis of variables. ROC and combined ROC curve analysis were executed to check the diagnostic accuracy at 95% CI. A total of 336 study participants (168 cases and 168 controls) were included. The median concentrations of serum triglyceride (229 (180-293.75) vs 194 (158.5–255)), total cholesterol (196 (167.25–224) vs 185.5 (158.5-212.75)), ALT (23(20–32) vs 21 (20–25)) and AST (35 (23.25-45) vs 24 (20–35)) values were significantly increased in cases as compared with normal controls. However, the median concentrations of serum total protein (6.7(6.1–7.4) vs 7.1 (6.7–7.6)) and serum calcium (7.6 (7.1–7.9) vs 7.9(7.5–8.3)) were significantly decreased in cases than controls. Positive correlations were observed between blood pressure and serum levels of triglyceride, total cholesterol, ALT & AST values while negative correlations were shown between blood pressure and HDL-cholesterol, total protein and serum calcium values. The combined ROC curve analysis of serum lipid profiles and clinical chemistry parameters showed a moderate prediction potential of PE. Hence, serum lipid profiles and clinical chemistry parameters were utilized as the diagnostic biomarkers of PE. However, to generate tangible evidence on the roles of lipid profiles and clinical chemistry parameters in PE pathogenesis and to include them as routine diagnostic biomarker multi-center prospective studies will be warranted. Biological sciences/Biochemistry Health sciences/Medical research Pre-eclampsia Serum Lipid profiles Clinical chemistry Prediction. Figures Figure 1 Figure 2 1. Introduction Pre-eclampsia (PE) is a pregnancy related metabolic disorder which complicates about 2–8% of pregnancies globally 1, 2 . It is the most common cause of maternal and prenatal deaths in low and middle income countries as compared to developed nations 3 . The underlying cause of PE is not well understood, but the foetal and maternal interfaces play a significant role in the pathogenesis of PE, this is evidenced by fast resolution of signs and symptoms of PE after postpartum 4 . To date, PE evaluated as a two stage disease, the first stage presence of poor placental development and the second stage occurrence of maternal syndrome, accompanied as a result of immune maladaptation and ischemic placenta 5–8 . Failure in spiral artery remodeling during early pregnancy causes ischemic placenta, this in return leads to free radical generation, accumulation of lipid peroxides and activation of cytokines, all which trigger’s to endothelial dysfunction and maternal syndrome that are observed in PE 9–11 . Several physiological and metabolic adaptations occur during pregnancy including: changes in lipid metabolism; an increased in insulin resistance, hyperlipidemia and hypercholesterolemia 12 . Starting from the beginning of the second trimester of pregnancy, lipid profile parameters are gradually increased throughout the third trimester of pregnancy and returned to their normal ranges during the postpartum period 13 . Abnormal pre-pregnancy body weight is associated with higher risk of PE, through changing lipid metabolism pattern and immune dysregulation. This metabolic maladaptation is a typical manifestation of preeclampsia which occurred before the incidence of the clinical symptoms of the disease 9, 14 . Lipid induced alterations could play a significant role in endothelial dysfunction and disease progression 15, 16 . Dyslipidemia and excess lipid peroxides are associated with pregnancy complications like: PE, gestational diabetes, intrauterine growth restriction (IUGR) and abnormal birth weight 8, 17–19 . Different studies have been conducted on PE to develop simple diagnostic biomarkers and therapeutic agents but many of them are unable to develop cost effective biomarkers for PE that are utilized by low and middle income countries. Likewise, some studies have been done to validate the implication of abnormal maternal serum lipid profiles and PE risk 20–24 . Besides, there are no such types of studies performed in our study population, there have been controversies regarding the association of serum lipid profiles and clinical chemistry parameters with PE 25, 26 . This study was designed to provide information on these topics. Thus we hypothesized that changes in lipid profiles and clinical chemistry parameters have been observed during PE. Therefore, the main objective of the current study was to compare maternal serum lipid profiles and clinical chemistry parameters in cases and controls. Additionally, to evaluate the diagnostic accuracy of maternal serum lipid profiles and clinical chemistry parameters in pregnant women attending ANC and delivery services at Bahir Dar city public Hospitals. 2. Methods And Materials 2.1. Study design and stetting A hospital-based case-control study was conducted at Bahir Dar city governmental hospitals. Bahir Dar is the capital city of Amhara Regional State and is located at a distance of 565km northwest of Addis Ababa, Ethiopia. Based on the projection of finance and economic development bureau in 2020, Bahir Dar city including satellite Kebeles (Meshenti, Zenzelma, Zegie and Tiss Abay) had 389,177 population of which 13, 115 women were pregnant. In the city, three governmental hospitals are found that provide different health services. Felege Hiwot referral hospital and Addis Alem primary hospital were selected to conduct the study. 2.2. Study population All pregnant women attending ANC and delivery services in the two hospitals were our source populations. While those pregnant women attending ANC and delivery services during the study period and fulfilling the inclusion criteria were our study populations. 2.3. Study variables Dependent variable: pre-eclampsia. Independent variables including: socio-demographic variables, BMI, obstetric history, medical history, behavioral factors, lipid profiles and clinical chemistry parameters. 2.4. Sample size and sampling procedure The sample size was calculated using double population proportion formula by considering the mean ± standard deviation (SD) of the maternal serum high density lipoprotein-cholesterol (HDL-c) level. Based on the previous study the maternal serum HDL-c level was 51 ± 16 mg/dL in pre-eclamptic cases and 61.8 ± 25.6 mg/dL in normotensive control groups [ 20 ]. We took 95% confidence level at 90% power with 1:1 case to control ratio and the critical value, α = 5% (α = 0.05) and we utilized the following formula to calculate the sample size 27 . $$\text{n}=\frac{({\left({\sigma }1+{\sigma }2\right)}^{2}\left(\text{Z}{\alpha }+\text{Z}1-{\beta }{)}^{2}\right)}{{\left({\mu }1-{\mu }2\right)}^{2}}$$ n- Is the minimum sample size required for this study in the group, while µ1, σ1 and µ2, σ2 are the means and standard deviations of the cases and controls, respectively. Z α - is a constant obtained from the normal distribution table which is 1.96 if α is two sided whereas Z 1 - β is a constant conventionally set according to the power of the study which is 1.282. By putting the values on the above formula, the final estimated sample size including 8% non-response rate was 336 (168 cases and 168 controls). One hundred ninety six study participants were selected from Felege Hiwot referral hospital and one hundred forty study participants from Addis Alem primary hospital based on their patient load. Simple randomly sampling technique was applied to select the study participants after the diagnosis of cases and controls were confirmed by physicians. 2.5. Inclusion and exclusion criteria The cases were women with new-onset of hypertension plus proteinuria diagnosed after twenty weeks of gestation. In case of negative proteinuria, preeclampsia should be diagnosed as new-onset hypertension with other signs of multi-organ involvements such as: high blood pressure (≥ 160/110 mmHg), low platelet count ( 1.1 mg/dL or twice creatinine level without other renal pathology), elevated liver enzymes (increased twice the upper limit normal), signs of pulmonary edema confirmed by chest x-ray and other signs of neurological involvement 28, 29 . The controls were normotensive pregnant women who were attending antenatal care and delivery service in the two hospitals with the gestational age of ≥ 20 weeks. Those mothers having known chronic hypertension, gestational hypertension, renal disease and severely ill pregnant women who could not give consent were excluded. Diagnosis of cases and controls were confirmed by physicians though history taking, physical examination and laboratory investigations. 2.6. Anthropometric measurements Weight is measured using digital weight balance to the nearest 0.1KG in the absence of shoes and heavy cloths. Height is measured in meter to the nearest centimeters in the absence of shoes. BMI has been calculated by the formula weight in kilogram divided by height in meter square. If the BMI value ≥ 25Kg/m 2 considered as overweight while, BMI ≥ 30Kg/m 2 is taken as obese and BMI found between 18–25Kg/m 2 interpreted as normal. The gestational age of the women was determined based on their last menstrual period (LMP) or using obstetric ultrasound in unknown LMP. In this study, all the study participants were existed in the third trimesters of pregnancy (24 to 42 weeks). The expected fetal weight (EFW) was determined through obstetric ultrasound by radiologists and trained obstetricians. The blood pressure (BP) of the women is taken in sitting position twice at least 4 hours apart using mercury sphygmomanometer after taking at least 10 minutes rest. Systolic blood pressure was recorded at the first appearance of sounds, while diastolic blood pressure was recorded at disappearance of fifth-phase korotkoff sounds. 2.7 Operational definitions Hypertension is defined as blood pressure of ≥ 140/90 mmHg measured on two occasions at least 4 hours apart whereas severe hypertension is defined as measured blood pressure of ≥ 160/110 mmHg. Proteinuria is defined as urinary protein excretion of ≥ 300mg /24-h urine samples or ≥ 1 + on dipstick reading and protein/creatinine ratio of ≥ 0.3 or more [ 28 , 29 ]. Preeclampsia is defined as new-onset of hypertension plus proteinuria which diagnosed after 20 weeks of gestation 29, 30 . Hypertriglyceridemia is defined as an abnormal concentration of triglyceride in the blood. Hyperlipidemia defined as higher maternal serum lipid concentrations (cholesterol and triglycerides) as a result of different reasons 31 . 2.8. Data collection Socio-demographic and clinical data were collected using semi-structured questionnaire adopted from previously published literatures. The questionnaire was prepared in English and translated into local language Amharic then translated back into English to maintain the consistence of data. Random blood samples were collected by trained laboratory technologist from the antecubita vein of preeclamptic and normotensive pregnant women aseptically. About five milliliter of blood samples were drawn using 5ml syringe and transferred into serum separator test tubes that allowed forming a clot. The sample was separated by centrifugation with the speed of 4000 rpm for 5 minutes and the separated serum dispensed into appropriately labeled nunc-tube. Then, the serum was stored at - 80ºc till laboratory analysis was performed. 2.9. Data quality assurance Data collectors were trained about the objectives of the study, confidentiality issues, and the right of withdrawal, blood sample collection, sample transportation and storage. Additionally, the questionnaire was pre-tested in separate institution to check the validity and completeness of data collection instruments before the start of data collection. The data collectors were supervised by the principal investigator. Before performing the actual laboratory analysis the machine was calibrated and internal quality control was done with known standards. To maintain data quality we followed all the standard protocols in the pre-analytical, analytical and post-analytical phases. 2.10. Laboratory analysis Lipid profiles and clinical chemistry tests such as: triglycerides (TG), total cholesterol (TC), HDL-cholesterol, alanine transaminase (ALT), aspartate transaminase (AST), total protein (TP), total bilirubin (TB), direct bilirubin (DB), calcium, sodium and potassium ions were determined by closed system Dimension EXL 200 Integrated chemistry analyzer at Tibebe Ghion Specialized Hospital according to the manufacturer’s principles. We used the products of Siemens Healthineers reagents for the determination of lipid profiles and clinical chemistry parameters. The detail procedure of the test methods, reference ranges, analytical sensitivity and analytical measurement ranges were presented in the table. LDL-c was estimated based on Friedewald’s formula as described here: [LDL-c] = [Total cholesterol] - [(HDL-c) + (TG/5)], (TG/5) used to estimate VLDL-cholesterol. We took this formula if the TG level <400 mg/dL and the results were expressed in mg/dL ( Table 1 ) 32 . Table 1: Test methods, reference range (RR), analytical sensitivity (AS) and analytical measurement range (AMR) of lipid profiles and clinical chemistry parameters in Bahir Dar public Hospitals northwest, Ethiopia, 2022. S. No Analyte RR AS AMR Test methods 1 Triglycerides (mg/dL) 30—150 15 15 – 1000 Glycerol-3-phosphate-oxidase- peroxidase 2 Total cholesterol (mg/dL) 0—200 50 50 – 600 Cholesterol oxidase- horseradish peroxidase methods 3 HDL-cholesterol (mg/dL) 40—60 3 3 – 150 Modified cholesterol esterase & cholesterol oxidase methods 4 ALT (IU/L) 14—63 5 5 – 1000 Modified IFCC methods 5 AST (IU/L) 15—37 6 6 – 1000 Modified IFCC methods 6 Total bilirubin (mg/dL) 0.2—1 0.1 0.1 – 25.0 Doumas reference methods 7 Direct bilirubin (mg/dL) 0--0.2 0. 05 0. 05 –16.0 Doumas reference methods 8 Total protein (g/dL) 6.4-8.2 2.0 2.0 – 12.0 Modified biuret reaction 9 Sodium (mmol/L) 136-145 50 50 – 200 Indirect ion-selective method 10 Potassium (mmol/L) 3.5-5.1 1 1 – 10 Indirect ion-selective method 11 Calcium (mg/dL) 8.5--10.1 5 5 -- 15 Modification of o-cresolphthalein complexone reaction AS- analytical sensitivity, AMR- analytical measurement range, IFCC- International federation of clinical chemistry and RR- reference range. 2.11. Data analysis The data were entered into Microsoft excel and exported to SPSS version 20 statistical software for analysis. Descriptive statistics, chi-square tests and multivariable logistic regression models were performed to determine the frequency and association of variables with PE. Normality was assessed by Shapiro-Wilk tests. The association between PE with serum lipid profiles and clinical chemistry tests were evaluated through independent sample Mann-Whitney U tests and reported in median and interquartile ranges (IQR). Additionally, spearman correlation was executed to evaluate the correlation between blood pressure and predictors. To evaluate the robustness of lipid profiles and clinical chemistry parameters in the prediction of PE, single and combined receiver operating characteristics (ROC) curve analysis were performed. In all cases p-value <0.05 in two tailed was taken as the cut-point. 2.12. Ethical approval The study was approved by the ethical review committee of Bahir Dar University, Science College (Ref.no: PGRCSVD/143/2012). Further, support letter was got from Amhara Public Health Institute (APHI (Ref.no/3/851/2012)) to conduct the study. The aim and significance of the study were described for all study participants. Each study participants were informed about confidentiality, withdrawal and consent. Before the start of data collection written informed consent has been acquired from each study participants. We performed this study in accordance the principle of Helsinki declaration on medical researches involving human subjects. 3. Results 3.1. Socio-demographic characteristics of the study populations In the current study, a total of 336 study subjects (168 cases and 168 controls) were included. About 38.7% of the cases and 42.3% of the controls were found in the age groups of 26-30 years. Most of the study participants in the cases (97.6%) and controls (99.4%) were married and also 76.2% of the cases and 82.7% of the controls were urban dwellers. In this study, almost all cases (97.0%) and controls (94.6%) were followers of orthodox Christian religion. In the current study, 46.4% of preeclamptic and 58.3% normotensive pregnant women were completed secondary education and above. About 50.6% of the cases and 57.1% of the controls were housewife in their occupation (Table 2). Table 2: Socio-demographic characteristics of the study populations in Bahir Dar city public hospitals, northwest Ethiopia, 2022. Variables Frequency of cases, n (%) Frequency of controls, n (%) Age in years ≤ 20 12 (7.1) 10 (5.9) 21-25 45 (26.8) 54 (32.2) 26-30 65 (38.7) 71 (42.3) 31-35 29 (17.3) 22 (13.1) >35 17 (10.1) 11 (6.5) Residence Urban 128 (76.2) 139 (82.7) Rural 40 (23.8) 29 (17.3) Marital status Married 164 (97.6) 167 (99.4) Single 4 (2.4) 1 (0.6) Religion Orthodox Christian 163 (97) 159 (94.6) Muslim 5 (3) 9 (5.4) Education status Illiterate 48 (28.6) 27 (16.1) From grade 1-8 42 (25) 43 (25.6) From grade 9-12 44 (26.2) 40 (23.8) Certificate & above 34 (20.2) 58 (34.5) Occupation House wife 85 (50.6) 96 (57.1) Employed 29 (17.3) 37 (22) Merchant 17 (10.1) 22 (13.1) Farmer 18 (10.7) 1 (0.6) Student 6 (3.6) 5 (3) Other 13 7.7) 7 (4.2) 3.2. Obstetric and medical information of the study populations In the current study, 96 (57.1%) of the cases and 109 (64.9%) of the controls were multigravida. About 62.5% of the cases and 67.3% of the controls were had a habit of drinking alcohol and about 72.1% of the cases and 75% of the controls had a habit of drinking coffee. A statistical significant difference was observed in the mean values of gestational age (GA), body mass index (BMI), expected fetal weight (EFW), systolic blood pressure (SBP) and diastolic blood pressure (DBP) among the cases and normal controls (Table 3). Table 3: Obstetric and medical information of the study populations in Bahir Dar city public hospitals, northwest Ethiopia, 2022. Variables Cases, n (%) Controls, n (%) p-value Gravidity Primigravida 72 (42.9%) 59 (35.1%) 0.146 Multigravida 96 (57.1%) 109 (64.9%) Alcohol drinking Yes 105 (62.5%) 113 (67.3%) 0.361 No 63 (37.5%) 55 (32.7%) Coffee drinking Yes 121 (72.1%) 126 (75%) 0.537 No 47 (27.9%) 42 (25%) GA in weeks Mean ± SD 35.68 ± 4.57 38.7 ± 3.19 <0.001* BMI in kg/m 2 Mean ± SD 24.93 ± 3.91 23.58 ± 3.30 0.001* EFW in grams Mean ± SD 2436.29 ± 712.73 2966.43± 560.64 <0.001* SBP in mmHg Mean ± SD 154.85 ± 11.77 110.10 ± 8.09 <0.001* DBP in mmHg Mean ± SD 100.75 ±9.1 71.09 ± 7.4 <0.001* BMI-body mass index, DBP- diastolic blood pressure, EFW- expected fetal weight, GA-gestational age, n- sample size, SBP- systolic blood pressure, SD- standard deviation, * significant at p<0.05. 3.3. Lipid profiles and clinical chemistry parameters of PE Mann-Whitney U test was performed to check the association of continuous variables. In this analysis, the median of maternal serum lipid profiles and clinical chemistry results were compared between the cases and controls. The median serum values of triglyceride, total cholesterol, AST and ALT were significantly increased in preeclampsia as compared with normal controls. Instead, the median serum concentrations of HDL-c, total protein and calcium ion were significantly reduced in cases than controls. The median serum values of LDL-c, total bilirubin, direct bilirubin sodium and potassium ions showed non-significant association with preeclampsia ( Table 4 ). Table 4: Mann-Whitney U tests of lipid profiles and clinical chemistry parameters of preeclamptic women in Bahir Dar city public hospitals, northwest Ethiopia, 2022. S. No Parameters Cases (N=168) Median (IQR) Control (N=168) Median (IQR) p-value 1 Triglycerides (mg/dL) 229 (180-293.75) 194 (158.5-255) 0.001* 2 Total cholesterol (mg/dL) 196 (167.25-224) 185.5 (158.25-212.75) 0.014* 3 HDL-cholesterol (mg/dL) 51 (42-60.75) 53 (44-64.75) 0.041* 4 LDL-cholesterol (mg/dL) 92.3(70-121.7) 90.2(66.45-114.15) 0.194 5 ALT (IU/L) 23 (20-32) 21 (18-25.75) 0.001* 6 AST (IU/L) 35 (23.25-45) 24 (20-35) 0.001* 7 Total bilirubin (mg/dL) 0.40 (0.30-0.60) 0.40 (0.325-0.5) 0.925 8 Direct bilirubin (mg/dL) 0.10 (0.0- 0.10) 0.10 (0.10-0.10) 0.162 9 Total protein (g/dL) 6.8 (6.1-7.4) 7.1 (6.7-7.6) 0.001* 10 Sodium (mmol/L) 142 (141-144) 143 (141-145) 0.218 11 Potassium (mmol/L) 4 (3.7-4.3) 4 (3.7-4.2) 0.350 12 Calcium (mg/dL) 7.6 (7.1-7.9) 7.9 (7.5-8.3) 0.001* ALT- alanine transaminase, AST- aspartate transaminase, g/dL- gram per deciliter, HDL-cholesterol-high density lipoprotein cholesterol, IU/L- international unit per liter, LDL-cholesterol-low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, VLDL-cholesterol- very low density lipoprotein cholesterol, * significant at p<0.05. 3.4. ROC curves of lipid profiles and clinical chemistry parameters The mean serum levels of lipid profiles and clinical chemistry parameters were significantly higher in cases than controls. The areas under receiver operating curve (ROC) of triglyceride were 0.622 with the sensitivity (61.7%) and specificity (56%) at the cut-point of ≥ 205.5mg/dL. The areas under ROC of total cholesterol were 0.577 (sensitivity: 59.5%; specificity: 51.2%) with the cutoff values of ≥195 mg/dL and the areas under ROC of HDL-cholesterol were 0.559 (sensitivity: 59.5%; specificity: 48.8%) with the cut-point of ≥ 50.5 mg/dL. The areas under the ROC of AST and ALT were 0.656 and 0.620 (sensitivity: 65.5% and 61.3%; specificity: 60.7% and 54.8%) with the cut-point of ≥27.5 and 21.5 IU/L respectively. The areas under the ROC of total protein were 0.622 (sensitivity: 70.2%; specificity: 52.4%) with the cut-point of ≥6.85 g/dL. And also the area under ROC curves of serum calcium were 0.662 (sensitivity: 63.1%; specificity: 58.3%) with the cut-point of ≥7.75 mg/dL. Hence, ROC showed that lipid profiles and clinical chemistry parameters can be used as the biomarkers of PE ( Figure 1 ) . 3.5 Correlations of lipid profiles parameters with blood pressure In this study maternal serum level of triglyceride, total cholesterol, LDL-cholesterol, VLDL-cholesterol and aspartate transaminase showed positive significant correlations with systolic and diastolic blood pressure. On the other hand, maternal serum levels of HDL-cholesterol and total protein were showed negative significant correlations with systolic and diastolic blood pressure. A non-significant positive correlation was shown between maternal serum alanine transaminase with systolic and diastolic blood pressure ( Table 5 ). Table 5: Correlations of lipid profiles and clinical chemistry parameters with blood pressure in the women attending ANC and delivery services, northwest Ethiopia, 2022. S. No Variables Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Spearman correlation coefficient p-value Spearman correlation coefficient p-value 1 Triglycerides (mg/dL) 0.216 0.000* 0.215 0.000* 2 TC (mg/dL) 0.101 0.064 0.119 0.029* 3 LDL-c (mg/dL) 0.052 0.346 0.068 0.212 4 HDL-c (mg/dL) -0.123 0.024* -0.114 0.038* 5 ALT (IU/L) 0.186 0.001* 0.194 0.000* 6 AST (IU/L) 0.243 0.000* 0.246 0.000* 7 Total protein (g/dL) -0.192 0.000* -0.200 0.000* 8 Potassium (mmol/L) 0.012 0.824 0.045 0.410 9 Sodium (mmol/L) -0.098 0.072 -0.098 0.074 10 Calcium (mg/dL) -0.231 0.000* -0.264 0.000* 11 TB (mg/dL) -0.029 0.591 -0.016 0.769 12 DB (mg/dL) 0.036 0.516 -0.043 0.434 ALT- alanine transaminase, AST- aspartate transaminase, DB- direct bilirubin, g/dL- gram per deciliter, HDL-cholesterol-high density lipoprotein cholesterol, IU/L- international unit per liter, LDL-cholesterol-low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, TC- total cholesterol, TB- total bilirubin, TG- triglycerides, VLDL-cholesterol- very low density lipoprotein cholesterol. 3.6 Logistic regression analysis of the models of predictors Binary logistic regression analyses were performed to assess the diagnostic accuracy of lipid profiles and clinical chemistry parameters for PE. Hosmer and Lemeshow test was used to assess model fitness with the data. For every predictor we evaluated the odds ratio at 95% CI. Deviance was used to compare the logistic regression models (the higher the deviance, the model is less adequate). We assessed sensitivity, specificity, overall correct classification rate and AUC (95% CI). AUC was used to evaluate diagnostic accuracy of the combined lipid profiles and clinical chemistry parameters. The lipid profiles and clinical chemistry parameters were classified into five models to get the best diagnostic markers of PE ( Table 6 ). Table 6: Logistic regression analysis of the models of predictors in Bahir Dar public hospitals, northwest Ethiopia, 2022. Model Predictors Hosmer & Lemeshow Test (p-value) Deviance Sensitivity/ specificity/ overall correct classification AUC (95% at CI) p-value on predicted probability Model 1 GA, BMI, EFW, TG, TC, HDL-c, LDL-c, DB, TB, TP, ALT, AST, Na+ K+, Ca2+ 0.068 306.207 81%, 71.5% & 81% 0.877 (0.84, 0.9140 <0.001 Model 2 TG, TC, HDL-c, LDL-c, DB, TB, TP, ALT, AST, Na+ K+, Ca2+ 0.006 369.989 79.2, 70.8% & 75% 0.799 (0.751, 0.847) <0.001 Model 3 TG, TC, HDL-c, LDL-c, TP, ALT, AST, Ca2+ 0.177 376.211 78.6%, 70.8% & 74.5% 0.794 (0.746, 0.842) <0.001 Model 4 TG, TC, TP, ALT, AST, Ca2+ 0.405 383.414 79.8%, 68.5% & 74.1% 0.785 (0.736, 0.834) <0.001 Model 5 TG, TC, HDL-c, LDL-c, 0.351 441.577 61.9%, 61.3% & 61.9% 0.637 (0.578, 0.696) <0.001 Abbreviations: TG-triglycerides; TC: total cholesterol; HDL-c: High density lipoprotein-cholesterol; LDL-c: Low density lipoprotein-cholesterol; AST: aspartate transaminase; ALT: alanine transaminase; TP: total protein; TB: total bilirubin; DB: direct bilirubin; Na+: sodium; K+: potassium. The best model of predictors is shown in bold. 3.7 Combined ROC curves of lipid profiles and clinical chemistry parameters The serum lipid profiles and clinical chemistry parameters were entered into binary logistic regression model in combination to select the appropriate model that predicts the risk of PE. After we tried different combinations five models were selected based on their model fitness, deviance, sensitivity, specificity, overall classification rate and the area under receiver operating characteristic curves. The model fitness was checked by hosmer and lemeshow test.The first model includes fifteen parameters with 87.7% prediction potential of PE; in the second model twelve variables were included with 79.9% of prediction potential while in the third model six variables were entered with the 79.4% of prediction potential, whereas model 4 and 5 had the prediction potential of 78.5% and 63.7% respectively. Thus, model 1 had excellent prediction potential of PE while the other models had acceptable prediction potential of PE. Hence, lipid profiles and clinical chemistry parameters were used as diagnostic markers of PE ( Figure 2 ) . 3.8 Multivariable logistic regression analysis Those variables significant in univariate analysis were entered into multivariable logistic regression model to determine their association with PE. In the multivariable logistic regression model seven predictors were evaluated and six predictors were significantly associated with PE at 95% CI. Maternal serum triglycerides, total cholesterol, alanine transaminase and aspartate transaminase levels were significantly increased in pre-eclamptic women as compared to normotensive pregnant women. Instead, serum total protein and calcium concentration were significantly reduced in case than controls ( Table 7 ). Table 7: Multivariable logistic regression analysis of lipid profiles and clinical chemistry parameters in the women attending ANC and delivery services in Bahir Dar city public hospitals, northwest Ethiopia, 2022. Parameter B S.E Wald df Sig Exp(B) 95% C.I EXP (B) Lower Upper ALT (IU/L) -0.028 0.011 6.739 1 0.009* 0.972 0.952 0.993 AST (IU/L) -0.015 0.006 6.980 1 0.008* 0.985 0.973 0.996 TP (g/dL) 0.482 0.144 11.167 1 0.001* 1.620 1.221 2.149 TG (mg/dL) -0.005 0.002 8.106 1 0.004* 0.995 0.992 0.999 TC (mg/dL) -0.006 0.003 4.130 1 0.042* 0.994 0.987 1.000 HDL-c (mg/dL) 0.009 0.010 0.829 1 0.363 1.010 0.989 1.030 Calcium (mg/dL) 0.563 0.182 9.566 1 0.002* 1.755 1.229 2.507 ALT- alanine transaminase, AST- aspartate transaminase, g/dL- gram per deciliter, HDL-c- high density lipoprotein cholesterol, IU/L- international unit per liter, mg/dL- milligram per deciliter, TC- total cholesterol, TG- triglycerides, TP- total protein. 4. Discussion This hospital-based case-control study showed statistical significant inference among lipid profile concentrations and clinical chemistry parameters with PE. The mean age, serum values of total bilirubin, direct bilirubin, HDL-c, LDL-c, sodium and potassium ions were comparable between the two groups. The mean GA, BMI, EFW, systolic and diastolic blood pressure measurements were significantly varied between the cases and controls. It is known that PE causes intrauterine fetal restriction (IUGR) and resulted in adverse maternal and neonatal outcomes 33, 34 . The pathological mechanisms in PE and IUGR follows similar molecular pattern. Poor placenta in the early pregnancy leads placental ischemia; in turn this causes hypoxia and oxidative stress which is observed in PE and IUGR 35, 36 . In this study, statistical significant difference was observed in regards to EFW among the two groups but it is difficult to conclude that PE causes IUGR this may be confounded by differences in gestational age. Several lipid derived markers are identified which are used for the estimation of PE risk in pregnant women 37 . During the course of pregnancy lipid metabolism has been significantly changed due to hormonal imbalance and hyperglycemia this ended with hypertriglyceridemia and hypercholesterolemia 38, 39 . Abnormal lipid profile findings have been observed in preeclamptic women because of oxidative stress ended with endothelial malfunction this leads to deposition of lipids in the spiral artery which interfere trophoblast invasion by changing prostaglandin synthesis 21, 40 . The current study, showed significantly higher concentrations of serum triglyceride in cases than controls respectively. This is in line with the results reported in China and India 13, 41 . The population-based prospective cohort study performed in Netherlands further supports the result 42 . Moreover, our previous systematic review and the other two reviews further strengths our result 20, 24, 43 . During early gestation hypertriglyceridemia is occurred due to reduced triglyceride catabolism as a consequence of hormonal changes and reduced placental uptake of the fatty acids 24, 42, 44,45 . Besides, decreased in lipoprotein enzyme activity and insulin resistance are responsible for this low lipid catabolism at the cellular level which causes hypertriglyceridemia 24, 39, 44, 45 . Abnormal triglyceride is significantly associated with cardiovascular diseases, hypertension, diabetes mellitus and metabolic syndrome in obese and insulin resistant individuals 46-48 . In this study, the serum concentration of total cholesterol was significantly increased among cases than normal controls. This is in line with the studies reported in Ethiopia, India and Nigeria 20, 23, 49 . Although, the finding of this study was varied from the study conducted in Saudi Arabia 50 . This may be due to larger sample size we used and gestational age of the participants. In early pregnancy, the mother stayed in anabolic state due to hormonal imbalance and decreased in lipoprotein lipase enzyme activity, these causes hypercholesterolemia. This metabolic adaptation during the course of pregnancy had immense metabolic benefit to secure energy for mother and their fetus in later pregnancy 38, 39, 43 . Although, cholesterol predispose to atherosclerosis, it had diverse metabolic functions which served as the precursors of cell membrane, different steroid hormones and vitamins 51 . Our study proved that the mean serum HDL-cholesterol concentration was non-significantly reduced in preeclampsia than normal controls. Our previous review and other studies support the result 20, 43, 52 . However, the results of the current study vary from other studies 23, 53 . This minor difference may be due to the sample types (fasting and random blood samples) and the gestational age of the women. HDL-cholesterol involved in reverse cholesterol transport to the liver, which is changed into bile and utilized for the production of biologically active molecules 54 . Studies showed that higher concentration of HDL-cholesterol had protective potential against hypertension and cardiovascular diseases 55 . On the other hand lower blood concentration of HDL-cholesterol importantly increases the risks of hypertension and cardiovascular diseases 56, 57 . Our research article proved that the mean serum LDL-cholesterol concentration was non-significantly raised in cases than normal controls. Supporting result was reported in the study conducted in Saudi Arabia 50 . But inconsistent results were reported from other studies 20, 23, 49 . This difference may be because of the sample size and gestational ages. Besides, maternal serum VLDL-cholesterol concentration was significantly increased in cases than normal controls. This is line with the study conducted in India and our previous review further supports the result 20, 49 . LDL-cholesterol mainly synthesized from VLDL-cholesterol intravascularly as a result of lipoprotein lipase enzyme activity and transports cholesterol into smaller arteries and arterioles 58 . The contents of LDL-cholesterol deposited in the intima of the blood vessel which leads to oxidation of LDL-cholesterol. This oxidation affects the architecture of lipoproteins; this in turn activates macrophage to release inflammatory cytokine and later developed into fatty strakes and atherosclerosis 59, 60 . Liver cells synthesized VLDL-cholesterol to transport lipids reach in triacylglycerol into the vascular system 55 . Abnormally high plasma VLDL-cholesterol and LDL-cholesterol concentrations are positively related with an increased incidence of chronic diseases like; PE, high blood pressure, heart disease, diabetes, atherosclerosis 42, 51, 60 . The serum concentrations of AST and ALT values were significantly elevated in PE than normal pregnancy. Comparable results were reported in the studies conducted in Pakistan and India 61, 62 . Numerous evidences showed the association between PE and hepatic dysfunction 63, 64 . Organ dysfunctions are commonly utilized for the diagnosis of PE and severe form of PE, in case of negative proteinuria. HELLP syndrome, stands for hemolysis, elevated liver enzymes (increased twice the upper limit normal), low platelet counts (1.1 mg/dL or a doubling of the serum creatinine value in the absence of other renal disease), pulmonary edema and signs of neurological involvement 65 . Severe form of PE involves end organ damage which requires multidisciplinary treatment 66 . The serum total protein was significantly reduced in cases as compared to controls. Supporting evidence was reported in previous study 67 . Lower levels of serum total protein possibly due to reduction in hepatic synthesis of proteins as the consequence of reduced hepatic blood flow secondary to hypovolemia created by higher filtration pressure in the capillaries 68 . Moreover, it is also due to increased angiotensin secretion and increased vascular endothelial cell permeability and leakage of plasma protein 69 . Available data regarding on the association of electrolytes with PE is somewhat controversial 70-72 . The mechanism how potassium leads to hypertension is not fully addressed nonetheless it supposed that potassium suppresses renin-angiotensin system, activation of sodium potassium pump, decreased vascular resistance, increased excretion of sodium and water and also maintains the function of vascular smooth muscles in response to vasopressin leads to vasoconstriction and PE 73, 74 . We found that a significantly lower serum values of calcium in the cases than controls. Calcium is participated in various metabolic pathways including: muscle contraction, nerve impulse transmission, blood pressure regulation, bone and teeth formation, blood clotting, vasodilation, heart beat regulation, hormone and enzyme regulation, fertilization, and maintenance of fluid balance within the cells 75, 76 . The plasma calcium concentration is regulated via the feedback control system with the interaction of parathyroid hormone, active cholecalciferol and calcitonin 77 . Calcium is working as an intracellular signaling molecules with inositol triphosphate (IP3) and calmodulin kinases 78 . Calcium supplementation during pregnancy significantly reduced the risk of premature delivery and maternal deaths 79 . Other reports revealed that calcium supplementation also significantly decreased the risk of gestational hypertension, pre-eclampsia, neonatal mortality and pre-term births 80, 81 . The receiver operating characteristic (ROC) curves are useful for comparing the predictive ability of biomarkers 82 . The areas under the ROC curve (AUC) are used to assess the prediction accuracy of various models which ranges from 0.5 to 1.0. If AUC is ≥0.9 it is considered as outstanding and AUC between 0.80-0.89 is excellent and it is between 0.7-0.8 which is acceptable estimate 83 . The combined ROC was evaluated to check the diagnostic accuracy of serum lipid profiles and clinical chemistry parameters for PE risk. In the combined ROC curve analysis model 1 showed excellent (87.7%) diagnostic accuracy while model 2 (79.9%), model 3 (79.4%) and model 4 (78.5%) had moderate prediction potential of PE but model 5 (63.7%) had lower prediction potential of PE. The spearman correlation proved that significant positive correlations have been observed between blood pressure and serum triglyceride, total cholesterol, ALT and AST levels. However, significant negative correlations have been observed between blood pressure and serum total protein, calcium and HDL-cholesterol values. Thus, lipid profiles and clinical chemistry parameters could be utilized for the prediction of PE. 5. Limitations This laboratory based study served as the base line information for scientific community. The study conducted on cases and controls selected from the same source population. On the other hand, this study had some forms of limitation. Due to feasibility issues and together with Covid-19 pandemic we used random blood samples for the analysis of lipid profiles which may influence our result. In this study, all the study participants were found in the third trimester it will be better if the lipid profiles were checked across the different trimesters. The case-control study showed an association among the variables. Therefore, it is difficult to conclude the diagnostic accuracy of serum lipid profiles and clinical chemistry parameters to PE. Therefore, to affirm lipid profiles and clinical chemistry parameters as the diagnostic biomarker for PE multicenter prospective cohort study on fasting blood samples may give better insight. 6. Conclusion Our study showed that maternal serum lipid profiles and clinical chemistry parameters were significantly associated with preeclampsia. The spearman correlation showed significant positive correlation among blood pressure and serum triglyceride, total cholesterol, ALT and AST values whereas significant negative correlation have been seen between blood pressure and HDL-cholesterol, total protein and calcium values. The combined ROC curve analysis of lipid profiles and clinical chemistry parameters showed moderate prediction potential of PE risk than the single biomarkers. This result, suggested that lipid profiles and clinical chemistry parameters could be utilized in the prediction of PE. However, to generate tangible evidences how lipid profiles and clinical chemistry parameters give rise to PE and to include the tests as routine diagnostic marker for PE multi-center large prospective studies will be required. Abbreviations ALT- alanine transaminase, ANC- antenatal care, AST- aspartate transaminase, BMI- body mass index, CI- confidence interval, DBP- diastolic blood pressure, CVD- cardiovascular disease, EFW- expected fetal weight, GA- gestational age, g/dL- gram per deciliter, HDL-cholesterol- high density lipoprotein cholesterol, IQR- inter quartile range, IU/L- international unit per liter, IUGR- intrauterine fetal growth restriction, kg/m 2- kilogram per meter square, LDL-cholesterol- low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, PE- pre-eclampsia, SBP- systolic blood pressure, SD- standard deviation, TG- triglycerides, VLDL-cholesterol- very low density lipoprotein cholesterol. Declarations Acknowledgements We are extremely grateful to the Institute of Biotechnology (IOB) and College of Medicine and Health Science of Bahir Dar University. The authors would like to acknowledge the staff members of the IOB, especially Dr. Mengistie Taye for his unreserved support. We would like to acknowledge the staff members of Tibebe Ghion Specialized hospital laboratory department particularly Mr. Fekadu Ayelign for his endless assistance during laboratory work. Lastly, all authors would like to recognize the data collectors and study populations. Funding This research project is supported by the Institute of Biotechnology (IOB), Bahir Dar University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript . Availability of data and materials All data generated or analyzed during this study are included in this published article and its supplementary information files . Authors’ contributions ET: Conceptualization, reviewed the literature, methodology, laboratory analysis, writing original draft, writing and editing the manuscript. AM: Conceived the research topic, reviewed the literature, study design and validated the final manuscript. EN: Involved in securing budget, data analysis, editing the manuscript and validating the final manuscript. DM and MA: involved in laboratory analysis, data analysis, editing the manuscript and validating the final manuscript. ST: Involved in laboratory, data analysis, editing the manuscript and validating the final manuscript. All authors read and approved the final draft of the manuscript. Competing of interest The authors have declared that no competing interests exist. References Say L, Chou D, Gemmill A, Tunçalp Ö, Moller A-B, Daniels J, Gülmezoglu AM, Temmerman M, Alkema L: Global causes of maternal death: a WHO systematic analysis . The Lancet Global Health 2014, 2 (6):e323-e333. Yang Y, Le Ray I, Zhu J, Zhang J, Hua J, Reilly M: Preeclampsia Prevalence, Risk Factors, and Pregnancy Outcomes in Sweden and China . JAMA Netw Open 2021, 4 (5):e218401. 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Nahm FS: Receiver operating characteristic curve: overview and practical use for clinicians . Korean J Anesthesiol 2022, 75 (1):25-36. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2404370","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":164466706,"identity":"7c57bb46-22d6-4787-bddf-c741de8f002e","order_by":0,"name":"Endalamaw Tesfa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYHACA4YHIIq9seHAhwogg5m5gbCWBBDFc/jgwxlnQFoYidUikZZszNsGYhHQwi/dvPFDQs02eYMDOWbSvPNqo/nbgVp+VGzDqUVyzrFiiYRjtw03HDhjJjl32/HcGYcZGxh7ztzG7aobOQYSCWy3Gbcd7DGTeLvtWG4DUAszYxtuLfY3cox/JPy7bb/tMI+ZBO+cY7nzCWkxkMgxk0hsu5247RhbsiFvQ03uBkJaJG6klVkk9t1O3n+GGRjIxw7kbgRqOYjPL/wzkjff+PDttu3M+Q+BUVlTlzvv/OGDD35U4NaCDg6DyQNEqweCOlIUj4JRMApGwQgBAP9FZ9ipLOx9AAAAAElFTkSuQmCC","orcid":"","institution":"Bahir Dar University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Endalamaw","middleName":"","lastName":"Tesfa","suffix":""},{"id":164466707,"identity":"291f0f6a-2739-4691-9428-e44296ff242b","order_by":1,"name":"Abaineh Munshea","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abaineh","middleName":"","lastName":"Munshea","suffix":""},{"id":164466708,"identity":"84d2a0a6-5daa-46bf-8719-e07231d237e6","order_by":2,"name":"Endalkachew Nibret","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Endalkachew","middleName":"","lastName":"Nibret","suffix":""},{"id":164466709,"identity":"fb7d47a9-49ae-44ff-a367-94e8367f5607","order_by":3,"name":"Daniel Mekonnen","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Mekonnen","suffix":""},{"id":164466710,"identity":"1605c639-b041-4d52-8bdc-dab5c2f001d4","order_by":4,"name":"Mulusew Alemneh Sinishaw","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mulusew","middleName":"Alemneh","lastName":"Sinishaw","suffix":""},{"id":164466711,"identity":"e36e9a02-7772-47d4-961b-ae9713f57863","order_by":5,"name":"Solomon Tebeje Gizaw","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Solomon","middleName":"Tebeje","lastName":"Gizaw","suffix":""}],"badges":[],"createdAt":"2022-12-22 09:14:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2404370/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2404370/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":31177831,"identity":"392215d0-8106-4ad7-854f-832a1996cab0","added_by":"auto","created_at":"2023-01-05 18:03:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208045,"visible":true,"origin":"","legend":"\u003cp\u003eROC analysis of maternal serum lipid profiles and clinical chemistry parameters among pre-eclamptic and normotensive pregnant women.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2404370/v1/e669583a6c783aa8832f8e58.png"},{"id":31178147,"identity":"0e583bd3-9951-4990-a59b-8ead89247c8d","added_by":"auto","created_at":"2023-01-05 18:11:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80076,"visible":true,"origin":"","legend":"\u003cp\u003eCombined\u003cstrong\u003e \u003c/strong\u003eROC curve analysis of lipid profiles and clinical chemistry parameters among pre-eclamptic and normotensive pregnant women.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2404370/v1/d1b27407a9719faefaa81281.png"},{"id":37517320,"identity":"c08e336f-ee38-4999-b665-1742041ff892","added_by":"auto","created_at":"2023-05-26 03:44:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2408544,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2404370/v1/2e123d60-14a8-4db9-bcc0-6b33bb7fcda6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of maternal serum lipid profiles and clinical chemistry parameters in the prediction of pre-eclampsia in pregnant women attending ANC and delivery services","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePre-eclampsia (PE) is a pregnancy related metabolic disorder which complicates about 2\u0026ndash;8% of pregnancies globally \u003csup\u003e1, 2\u003c/sup\u003e. It is the most common cause of maternal and prenatal deaths in low and middle income countries as compared to developed nations \u003csup\u003e3\u003c/sup\u003e. The underlying cause of PE is not well understood, but the foetal and maternal interfaces play a significant role in the pathogenesis of PE, this is evidenced by fast resolution of signs and symptoms of PE after postpartum \u003csup\u003e4\u003c/sup\u003e. To date, PE evaluated as a two stage disease, the first stage presence of poor placental development and the second stage occurrence of maternal syndrome, accompanied as a result of immune maladaptation and ischemic placenta \u003csup\u003e5\u0026ndash;8\u003c/sup\u003e. Failure in spiral artery remodeling during early pregnancy causes ischemic placenta, this in return leads to free radical generation, accumulation of lipid peroxides and activation of cytokines, all which trigger\u0026rsquo;s to endothelial dysfunction and maternal syndrome that are observed in PE \u003csup\u003e9\u0026ndash;11\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral physiological and metabolic adaptations occur during pregnancy including: changes in lipid metabolism; an increased in insulin resistance, hyperlipidemia and hypercholesterolemia \u003csup\u003e12\u003c/sup\u003e. Starting from the beginning of the second trimester of pregnancy, lipid profile parameters are gradually increased throughout the third trimester of pregnancy and returned to their normal ranges during the postpartum period \u003csup\u003e13\u003c/sup\u003e. Abnormal pre-pregnancy body weight is associated with higher risk of PE, through changing lipid metabolism pattern and immune dysregulation. This metabolic maladaptation is a typical manifestation of preeclampsia which occurred before the incidence of the clinical symptoms of the disease \u003csup\u003e9, 14\u003c/sup\u003e. Lipid induced alterations could play a significant role in endothelial dysfunction and disease progression \u003csup\u003e15, 16\u003c/sup\u003e. Dyslipidemia and excess lipid peroxides are associated with pregnancy complications like: PE, gestational diabetes, intrauterine growth restriction (IUGR) and abnormal birth weight \u003csup\u003e8, 17\u0026ndash;19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDifferent studies have been conducted on PE to develop simple diagnostic biomarkers and therapeutic agents but many of them are unable to develop cost effective biomarkers for PE that are utilized by low and middle income countries. Likewise, some studies have been done to validate the implication of abnormal maternal serum lipid profiles and PE risk \u003csup\u003e20\u0026ndash;24\u003c/sup\u003e. Besides, there are no such types of studies performed in our study population, there have been controversies regarding the association of serum lipid profiles and clinical chemistry parameters with PE \u003csup\u003e25, 26\u003c/sup\u003e. This study was designed to provide information on these topics. Thus we hypothesized that changes in lipid profiles and clinical chemistry parameters have been observed during PE. Therefore, the main objective of the current study was to compare maternal serum lipid profiles and clinical chemistry parameters in cases and controls. Additionally, to evaluate the diagnostic accuracy of maternal serum lipid profiles and clinical chemistry parameters in pregnant women attending ANC and delivery services at Bahir Dar city public Hospitals.\u003c/p\u003e"},{"header":"2. Methods And Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and stetting\u003c/h2\u003e \u003cp\u003eA hospital-based case-control study was conducted at Bahir Dar city governmental hospitals. Bahir Dar is the capital city of Amhara Regional State and is located at a distance of 565km northwest of Addis Ababa, Ethiopia. Based on the projection of finance and economic development bureau in 2020, Bahir Dar city including satellite Kebeles (Meshenti, Zenzelma, Zegie and Tiss Abay) had 389,177 population of which 13, 115 women were pregnant. In the city, three governmental hospitals are found that provide different health services. Felege Hiwot referral hospital and Addis Alem primary hospital were selected to conduct the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study population\u003c/h2\u003e \u003cp\u003eAll pregnant women attending ANC and delivery services in the two hospitals were our source populations. While those pregnant women attending ANC and delivery services during the study period and fulfilling the inclusion criteria were our study populations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Study variables\u003c/h2\u003e \u003cp\u003eDependent variable: pre-eclampsia.\u003c/p\u003e \u003cp\u003eIndependent variables including: socio-demographic variables, BMI, obstetric history, medical history, behavioral factors, lipid profiles and clinical chemistry parameters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Sample size and sampling procedure\u003c/h2\u003e \u003cp\u003eThe sample size was calculated using double population proportion formula by considering the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) of the maternal serum high density lipoprotein-cholesterol (HDL-c) level. Based on the previous study the maternal serum HDL-c level was 51\u0026thinsp;\u0026plusmn;\u0026thinsp;16 mg/dL in pre-eclamptic cases and 61.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.6 mg/dL in normotensive control groups [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We took 95% confidence level at 90% power with 1:1 case to control ratio and the critical value, α\u0026thinsp;=\u0026thinsp;5% (α\u0026thinsp;=\u0026thinsp;0.05) and we utilized the following formula to calculate the sample size \u003csup\u003e27\u003c/sup\u003e.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{n}=\\frac{({\\left({\\sigma }1+{\\sigma }2\\right)}^{2}\\left(\\text{Z}{\\alpha }+\\text{Z}1-{\\beta }{)}^{2}\\right)}{{\\left({\\mu }1-{\\mu }2\\right)}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003en- Is the minimum sample size required for this study in the group, while \u0026micro;1, σ1 and \u0026micro;2, σ2 are the means and standard deviations of the cases and controls, respectively. Z\u003csub\u003eα\u003c/sub\u003e - is a constant obtained from the normal distribution table which is 1.96 if α is two sided whereas Z\u003csub\u003e1\u003c/sub\u003e-\u003csub\u003eβ\u003c/sub\u003e is a constant conventionally set according to the power of the study which is 1.282. By putting the values on the above formula, the final estimated sample size including 8% non-response rate was 336 (168 cases and 168 controls). One hundred ninety six study participants were selected from Felege Hiwot referral hospital and one hundred forty study participants from Addis Alem primary hospital based on their patient load. Simple randomly sampling technique was applied to select the study participants after the diagnosis of cases and controls were confirmed by physicians.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Inclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eThe cases were women with new-onset of hypertension plus proteinuria diagnosed after twenty weeks of gestation. In case of negative proteinuria, preeclampsia should be diagnosed as new-onset hypertension with other signs of multi-organ involvements such as: high blood pressure (\u0026ge;\u0026thinsp;160/110 mmHg), low platelet count (\u0026lt;\u0026thinsp;100\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L), signs of renal impairment (creatinine levels of \u0026gt;\u0026thinsp;1.1 mg/dL or twice creatinine level without other renal pathology), elevated liver enzymes (increased twice the upper limit normal), signs of pulmonary edema confirmed by chest x-ray and other signs of neurological involvement \u003csup\u003e28, 29\u003c/sup\u003e. The controls were normotensive pregnant women who were attending antenatal care and delivery service in the two hospitals with the gestational age of \u0026ge;\u0026thinsp;20 weeks. Those mothers having known chronic hypertension, gestational hypertension, renal disease and severely ill pregnant women who could not give consent were excluded. Diagnosis of cases and controls were confirmed by physicians though history taking, physical examination and laboratory investigations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Anthropometric measurements\u003c/h2\u003e \u003cp\u003eWeight is measured using digital weight balance to the nearest 0.1KG in the absence of shoes and heavy cloths. Height is measured in meter to the nearest centimeters in the absence of shoes. BMI has been calculated by the formula weight in kilogram divided by height in meter square. If the BMI value\u0026thinsp;\u0026ge;\u0026thinsp;25Kg/m\u003csup\u003e2\u003c/sup\u003e considered as overweight while, BMI\u0026thinsp;\u0026ge;\u0026thinsp;30Kg/m\u003csup\u003e2\u003c/sup\u003e is taken as obese and BMI found between 18\u0026ndash;25Kg/m\u003csup\u003e2\u003c/sup\u003e interpreted as normal. The gestational age of the women was determined based on their last menstrual period (LMP) or using obstetric ultrasound in unknown LMP. In this study, all the study participants were existed in the third trimesters of pregnancy (24 to 42 weeks). The expected fetal weight (EFW) was determined through obstetric ultrasound by radiologists and trained obstetricians. The blood pressure (BP) of the women is taken in sitting position twice at least 4 hours apart using mercury sphygmomanometer after taking at least 10 minutes rest. Systolic blood pressure was recorded at the first appearance of sounds, while diastolic blood pressure was recorded at disappearance of fifth-phase korotkoff sounds.\u003c/p\u003e\u003ch2\u003e 2.7 Operational definitions\u003c/h2\u003e\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eHypertension is defined as blood pressure of \u0026ge;\u0026thinsp;140/90 mmHg measured on two occasions at least 4 hours apart whereas severe hypertension is defined as measured blood pressure of \u0026ge;\u0026thinsp;160/110 mmHg.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProteinuria is defined as urinary protein excretion of \u0026ge;\u0026thinsp;300mg /24-h urine samples or \u0026ge;\u0026thinsp;1\u0026thinsp;+\u0026thinsp;on dipstick reading and protein/creatinine ratio of \u0026ge;\u0026thinsp;0.3 or more [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePreeclampsia is defined as new-onset of hypertension plus proteinuria which diagnosed after 20 weeks of gestation \u003csup\u003e29, 30\u003c/sup\u003e.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHypertriglyceridemia is defined as an abnormal concentration of triglyceride in the blood.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHyperlipidemia defined as higher maternal serum lipid concentrations (cholesterol and triglycerides) as a result of different reasons \u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Data collection\u003c/h2\u003e \u003cp\u003eSocio-demographic and clinical data were collected using semi-structured questionnaire adopted from previously published literatures. The questionnaire was prepared in English and translated into local language Amharic then translated back into English to maintain the consistence of data. Random blood samples were collected by trained laboratory technologist from the antecubita vein of preeclamptic and normotensive pregnant women aseptically. About five milliliter of blood samples were drawn using 5ml syringe and transferred into serum separator test tubes that allowed forming a clot. The sample was separated by centrifugation with the speed of 4000 rpm for 5 minutes and the separated serum dispensed into appropriately labeled nunc-tube. Then, the serum was stored at \u003csup\u003e-\u003c/sup\u003e80\u0026ordm;c till laboratory analysis was performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Data quality assurance\u003c/h2\u003e \u003cp\u003eData collectors were trained about the objectives of the study, confidentiality issues, and the right of withdrawal, blood sample collection, sample transportation and storage. Additionally, the questionnaire was pre-tested in separate institution to check the validity and completeness of data collection instruments before the start of data collection. The data collectors were supervised by the principal investigator. Before performing the actual laboratory analysis the machine was calibrated and internal quality control was done with known standards. To maintain data quality we followed all the standard protocols in the pre-analytical, analytical and post-analytical phases.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003e2.10.\u003c/strong\u003e \u003cstrong\u003eLaboratory analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLipid profiles and clinical chemistry tests such as: triglycerides (TG), total cholesterol (TC), HDL-cholesterol, alanine transaminase (ALT), aspartate transaminase (AST), total protein (TP), total bilirubin (TB), direct bilirubin (DB), calcium, sodium and potassium ions were determined by closed system Dimension EXL 200 Integrated chemistry analyzer at Tibebe Ghion Specialized Hospital\u0026nbsp;according to the manufacturer\u0026rsquo;s principles. We used the products of Siemens Healthineers reagents for the determination of lipid profiles and clinical chemistry parameters. The detail procedure of the test methods, reference ranges, analytical sensitivity and analytical measurement ranges were presented in the table. LDL-c was estimated based on Friedewald\u0026rsquo;s formula as described here: [LDL-c] = [Total cholesterol] - [(HDL-c) + (TG/5)], (TG/5) used to estimate VLDL-cholesterol. We\u0026nbsp;took this formula if the TG level \u0026lt;400 mg/dL and the results were expressed in mg/dL (\u003cstrong\u003eTable 1\u003c/strong\u003e) \u003csup\u003e32\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Test methods, reference range (RR), analytical sensitivity (AS) and analytical measurement range (AMR) of lipid profiles and clinical chemistry parameters in Bahir Dar public Hospitals northwest, Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"655\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003eS. No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalyte\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp\u003e\u003cstrong\u003eRR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e\u003cstrong\u003eAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e\u003cstrong\u003eAMR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest methods\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eTriglycerides (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp\u003e30\u0026mdash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e15 \u0026ndash; 1000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eGlycerol-3-phosphate-oxidase- peroxidase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eTotal cholesterol (mg/dL)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp\u003e0\u0026mdash;200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e50 \u0026ndash; 600\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eCholesterol oxidase- horseradish peroxidase methods\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eHDL-cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp\u003e40\u0026mdash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e3 \u0026ndash; 150\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eModified cholesterol esterase \u0026amp; cholesterol oxidase methods\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eALT (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e14\u0026mdash;63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e5 \u0026ndash; 1000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eModified IFCC methods\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eAST (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e15\u0026mdash;37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e6 \u0026ndash; 1000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eModified IFCC methods\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eTotal bilirubin (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.2\u0026mdash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e0.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e0.1 \u0026ndash; 25.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eDoumas reference\u0026nbsp;methods\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eDirect bilirubin (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0--0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e0. 05\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e0. 05 \u0026ndash;16.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eDoumas reference\u0026nbsp;methods\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e6.4-8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e2.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e2.0 \u0026ndash; 12.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eModified\u0026nbsp;biuret reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eSodium (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e136-145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e50 \u0026ndash; 200\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eIndirect ion-selective method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003ePotassium (mmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e3.5-5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e1 \u0026ndash; 10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eIndirect ion-selective method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"170\"\u003e\n \u003cp\u003eCalcium (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e8.5--10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"84\"\u003e\n \u003cp\u003e5 -- 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"216\"\u003e\n \u003cp\u003eModification of o-cresolphthalein complexone reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAS- analytical sensitivity, AMR- analytical measurement range, IFCC- International federation of clinical chemistry and RR- reference range.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11.\u003c/strong\u003e \u003cstrong\u003eData analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were entered into Microsoft excel and exported to SPSS version 20 statistical software for analysis. Descriptive statistics, chi-square tests and multivariable logistic regression models were performed to determine the frequency and association of variables with PE. Normality was assessed by Shapiro-Wilk tests. The association between PE with serum lipid profiles and clinical chemistry tests were evaluated through independent sample Mann-Whitney U tests and reported in median and interquartile ranges (IQR). Additionally, spearman correlation was executed to evaluate the correlation between blood pressure and predictors. To evaluate the robustness of lipid profiles and clinical chemistry parameters in the prediction of PE, single and combined receiver operating characteristics (ROC) curve analysis were performed. In all cases p-value \u0026lt;0.05 in two tailed was taken as the cut-point.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.12.\u003c/strong\u003e \u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethical review committee of Bahir Dar University, Science College (Ref.no: PGRCSVD/143/2012). Further, support letter was got from Amhara Public Health Institute (APHI (Ref.no/3/851/2012)) to conduct the study. The aim and significance of the study were described for all study participants. Each study participants were informed about confidentiality, withdrawal and consent. Before the start of data collection written informed consent has been acquired from each study participants. We performed this study in accordance the principle of Helsinki declaration on medical researches involving human subjects.\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003cp\u003e\u003cstrong\u003e3.1.\u003c/strong\u003e \u003cstrong\u003e\u0026nbsp;Socio-demographic characteristics of the study populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the current study, a total of 336 study subjects (168 cases and 168 controls) were included. About 38.7% of the cases and 42.3% of the controls were found in the age groups of 26-30 years. Most of the study participants in the cases (97.6%) and controls (99.4%) were married and also 76.2% of the cases and 82.7% of the controls were urban dwellers. In this study, almost all cases (97.0%) and controls (94.6%) were followers of orthodox Christian religion. In the current study, 46.4% of preeclamptic and 58.3% normotensive pregnant women were completed secondary education and above. About 50.6% of the cases and 57.1% of the controls were housewife in their occupation \u003cstrong\u003e(Table 2).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Socio-demographic characteristics of the study populations in Bahir Dar city public hospitals, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"289\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eFrequency of cases, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eFrequency of controls, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eAge in years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003e\u0026le; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e12 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e10 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003e21-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e45 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e54 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003e26-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e65 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e71 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003e31-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e29 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e22 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e17 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e11 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e128 (76.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e139 (82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e40 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e29 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e164 (97.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e167 (99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e4 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e1 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eOrthodox Christian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e163 (97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e159 (94.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e5 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e9 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eEducation status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e48 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e27 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eFrom grade 1-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e42 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e43 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eFrom grade 9-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e44 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e40 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eCertificate \u0026amp; above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e34 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e58 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" width=\"139\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eHouse wife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e85 (50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e96 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e29 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e37 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eMerchant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e17 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e22 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e18 (10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e1 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e6 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e5 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"150\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e13 7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp\u003e7 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.\u003c/strong\u003e \u003cstrong\u003e\u0026nbsp;Obstetric and medical information of\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;the study populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the current study, 96 (57.1%) of the cases and 109 (64.9%) of the controls were multigravida. About 62.5% of the cases and 67.3% of the controls were had a habit of drinking alcohol and about 72.1% of the cases and 75% of the controls had a habit of drinking coffee. A statistical significant difference was observed in the mean values of gestational age (GA), body mass index (BMI), expected fetal weight (EFW), systolic blood pressure (SBP) and diastolic blood pressure (DBP) among the cases and normal controls \u003cstrong\u003e(Table 3).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Obstetric and medical information of the study populations in Bahir Dar city public hospitals, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"301\"\u003e\n \u003cp align=\"center\"\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003eCases, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003eControls, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003ePrimigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e72 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e59 (35.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMultigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e96 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e109 (64.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eAlcohol drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e105 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e113 (67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e63 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e55 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eCoffee drinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e121 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e126 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e47 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e42 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eGA in weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e35.68 \u0026plusmn; 4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e38.7 \u0026plusmn; 3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eBMI in kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e24.93 \u0026plusmn; 3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e23.58 \u0026plusmn; 3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eEFW in grams\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e2436.29 \u0026plusmn; 712.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e2966.43\u0026plusmn; 560.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eSBP in mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e154.85 \u0026plusmn; 11.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e110.10 \u0026plusmn; 8.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"181\"\u003e\n \u003cp\u003eDBP in mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"120\"\u003e\n \u003cp align=\"center\"\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"132\"\u003e\n \u003cp align=\"center\"\u003e100.75 \u0026plusmn;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"126\"\u003e\n \u003cp align=\"center\"\u003e71.09 \u0026plusmn; 7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"72\"\u003e\n \u003cp align=\"center\"\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI-body mass index, DBP- diastolic blood pressure, EFW- expected fetal weight, GA-gestational age, n- sample size, SBP- systolic blood pressure, SD- standard deviation, \u003cstrong\u003e*\u003c/strong\u003esignificant at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.\u003c/strong\u003e \u003cstrong\u003eLipid profiles and clinical chemistry parameters of PE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMann-Whitney U test was performed to check the association of continuous variables. In this analysis, the median of maternal serum lipid profiles and clinical chemistry results were compared between the cases and controls. The median serum values of triglyceride, total cholesterol, AST and ALT were significantly increased in preeclampsia as compared with normal controls. Instead, the median serum concentrations of HDL-c, total protein and calcium ion were significantly reduced in cases than controls. The median serum values of LDL-c, total bilirubin, direct bilirubin sodium and potassium ions showed non-significant association with preeclampsia (\u003cstrong\u003eTable 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e Mann-Whitney U tests of lipid profiles and clinical chemistry parameters of preeclamptic women in Bahir Dar city public hospitals, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003eS. No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003eCases (N=168)\u003c/p\u003e\n \u003cp align=\"center\"\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003eControl (N=168)\u003c/p\u003e\n \u003cp align=\"center\"\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eTriglycerides (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e229 (180-293.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e194 (158.5-255)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eTotal cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e196 (167.25-224)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e185.5 (158.25-212.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.014*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eHDL-cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e51 (42-60.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e53 (44-64.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.041*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eLDL-cholesterol (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e92.3(70-121.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e90.2(66.45-114.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eALT (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e23 (20-32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e21 (18-25.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eAST (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e35 (23.25-45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e24 (20-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eTotal bilirubin (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e0.40 (0.30-0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e0.40 (0.325-0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eDirect bilirubin (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e0.10 (0.0- 0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e0.10 (0.10-0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e6.8 (6.1-7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e7.1 (6.7-7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eSodium (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e142 (141-144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e143 (141-145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e4 (3.7-4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e4 (3.7-4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"49\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp\u003eCalcium (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"138\"\u003e\n \u003cp align=\"center\"\u003e7.6 (7.1-7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"168\"\u003e\n \u003cp align=\"center\"\u003e7.9 (7.5-8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"78\"\u003e\n \u003cp align=\"center\"\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eALT- alanine transaminase, AST- aspartate transaminase, g/dL- gram per deciliter, HDL-cholesterol-high density lipoprotein cholesterol, IU/L- international unit per liter, LDL-cholesterol-low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, VLDL-cholesterol- very low density lipoprotein cholesterol, \u003cstrong\u003e*\u003c/strong\u003esignificant at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.\u003c/strong\u003e \u003cstrong\u003eROC curves of lipid profiles and clinical chemistry parameters\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean serum levels of lipid profiles and clinical chemistry parameters were significantly higher in cases than controls. The areas under receiver operating curve (ROC) of triglyceride were 0.622 with the sensitivity (61.7%) and specificity (56%) at the cut-point of \u0026ge; 205.5mg/dL. The areas under ROC of total cholesterol were 0.577 (sensitivity: 59.5%; specificity: 51.2%) with the cutoff values of \u0026ge;195 mg/dL and the areas under ROC of HDL-cholesterol were 0.559 (sensitivity: 59.5%; specificity: 48.8%) with the cut-point of \u0026ge; 50.5 mg/dL. The areas under the ROC of AST and ALT were 0.656 and 0.620 (sensitivity: 65.5% and 61.3%; specificity: 60.7% and 54.8%) with the cut-point of \u0026ge;27.5 and 21.5 IU/L respectively. The areas under the ROC of total protein were 0.622 (sensitivity: 70.2%; specificity: 52.4%) with the cut-point of \u0026ge;6.85 g/dL. And also the area under ROC curves of serum calcium were 0.662 (sensitivity: 63.1%; specificity: 58.3%) with the cut-point of \u0026ge;7.75 mg/dL. Hence, ROC showed that lipid profiles and clinical chemistry parameters can be used as the biomarkers of PE (\u003cstrong\u003eFigure 1\u003c/strong\u003e)\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5\u0026nbsp;\u003c/strong\u003e\u003cstrong style=\"text-align: inherit;\"\u003eCorrelations of lipid profiles parameters with blood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study maternal serum level of triglyceride, total cholesterol, LDL-cholesterol, VLDL-cholesterol and aspartate transaminase showed positive significant correlations with systolic and diastolic blood pressure. On the other hand, maternal serum levels of HDL-cholesterol and total protein were showed negative significant correlations with systolic and diastolic blood pressure. A non-significant positive correlation was shown between maternal serum alanine transaminase with systolic and diastolic blood pressure (\u003cstrong\u003eTable 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u003c/strong\u003e Correlations of lipid profiles and clinical chemistry parameters with blood pressure in the women attending ANC and delivery services, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003eS. No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"33.28050713153724%\"\u003e\n \u003cp\u003eSystolic blood pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"34.389857369255154%\"\u003e\n \u003cp\u003eDiastolic blood pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.723653395784545%\"\u003e\n \u003cp\u003eSpearman correlation coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.456674473067915%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.723653395784545%\"\u003e\n \u003cp\u003eSpearman correlation coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.096018735362996%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eTriglycerides (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eTC (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.029*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eLDL-c (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.038*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eALT (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eAST (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eSodium (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eCalcium (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eTB (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"8.55784469096672%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.771790808240887%\"\u003e\n \u003cp\u003eDB (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.45958795562599%\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.820919175911254%\"\u003e\n \u003cp\u003e-0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.568938193343898%\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eALT- alanine transaminase, AST- aspartate transaminase, DB- direct bilirubin, g/dL- gram per deciliter, HDL-cholesterol-high density lipoprotein cholesterol, IU/L- international unit per liter, LDL-cholesterol-low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, TC- total cholesterol, TB- total bilirubin, TG- triglycerides, VLDL-cholesterol- very low density lipoprotein cholesterol.\u003c/p\u003e\n\u003cp\u003e\u003cstrong style=\"text-align: inherit;\"\u003e3.6 Logistic regression analysis of the models of predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBinary logistic regression analyses were performed to assess the diagnostic accuracy of lipid profiles and clinical chemistry parameters for PE. Hosmer and Lemeshow test was used to assess model fitness with the data. For every predictor we evaluated the odds ratio at 95% CI. Deviance was used to compare the logistic regression models (the higher the deviance, the model is less adequate). We assessed sensitivity, specificity, overall correct classification rate and AUC (95% CI). AUC was used to evaluate diagnostic accuracy of the combined lipid profiles and clinical chemistry parameters. The lipid profiles and clinical chemistry parameters were classified into five models to get the best diagnostic markers of PE (\u003cstrong\u003eTable 6\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u003c/strong\u003e Logistic regression analysis of the models of predictors in Bahir Dar public hospitals, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003eHosmer \u0026amp; Lemeshow Test (p-value)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003eDeviance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eSensitivity/ specificity/ overall correct classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003eAUC (95% at CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003ep-value on\u003c/p\u003e\n \u003cp\u003epredicted probability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003eGA, BMI, EFW, TG, TC, HDL-c, LDL-c, DB, TB, TP, ALT, AST, Na+ K+, Ca2+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e306.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e81%, 71.5% \u0026amp; 81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0.877 (0.84, 0.9140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003eTG, TC, HDL-c, LDL-c, DB, TB, TP, ALT, AST, Na+ K+, Ca2+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e369.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e79.2, 70.8% \u0026amp; 75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0.799 (0.751, 0.847)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003eTG, TC, HDL-c, LDL-c, TP, ALT, AST, Ca2+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e376.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e78.6%, 70.8% \u0026amp; 74.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0.794 (0.746, 0.842)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003eTG, TC, TP, ALT, AST, Ca2+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e383.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e79.8%, 68.5% \u0026amp; 74.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0.785 (0.736, 0.834)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.802469135802468%\"\u003e\n \u003cp\u003eModel 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.90740740740741%\"\u003e\n \u003cp\u003eTG, TC, HDL-c, LDL-c,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.962962962962964%\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e441.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e61.9%, 61.3% \u0026amp; 61.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.814814814814815%\"\u003e\n \u003cp\u003e0.637 (0.578, 0.696)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.734567901234568%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e TG-triglycerides; TC: total cholesterol; HDL-c: High density lipoprotein-cholesterol; LDL-c: Low density lipoprotein-cholesterol; AST: aspartate transaminase; ALT: alanine transaminase; TP: total protein; TB: total bilirubin; DB: direct bilirubin; Na+: sodium; K+: potassium. The best model of predictors is shown in bold.\u003c/p\u003e\n\u003cp\u003e\u003cstrong style=\"text-align: inherit;\"\u003e3.7 Combined ROC curves of lipid profiles and clinical chemistry parameters\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serum lipid profiles and clinical chemistry parameters were entered into binary logistic regression model in combination to select the appropriate model that predicts the risk of PE. After we tried different combinations five models were selected based on their model fitness, deviance, sensitivity, specificity, overall classification rate and the area under receiver operating characteristic curves. The model fitness was checked by hosmer and lemeshow test.The first model includes fifteen parameters with 87.7% prediction potential of PE; in the second model twelve variables were included with 79.9% of prediction potential while in the third model six variables were entered with the 79.4% of prediction potential, whereas model 4 and 5 had the prediction potential of 78.5% and 63.7% respectively. Thus, model 1 had excellent prediction potential of PE while the other models had acceptable prediction potential of PE. Hence, lipid profiles and clinical chemistry parameters were used as diagnostic markers of PE (\u003cstrong\u003eFigure 2\u003c/strong\u003e)\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8\u0026nbsp;\u003c/strong\u003e\u003cstrong style=\"text-align: inherit;\"\u003eMultivariable logistic regression analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThose variables significant in univariate analysis were entered into multivariable logistic regression model to determine their association with PE. In the multivariable logistic regression model seven predictors were evaluated and six predictors were significantly associated with PE at 95% CI. Maternal serum triglycerides, total cholesterol, alanine transaminase and aspartate transaminase levels were significantly increased in pre-eclamptic women as compared to normotensive pregnant women. Instead, serum total protein and calcium concentration were significantly reduced in case than controls (\u003cstrong\u003eTable 7\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7:\u003c/strong\u003e Multivariable logistic regression analysis of lipid profiles and clinical chemistry parameters in the women attending ANC and delivery services in Bahir Dar city public hospitals, northwest Ethiopia, 2022.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"20%\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.476190476190476%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.523809523809524%\"\u003e\n \u003cp\u003eS.E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.428571428571429%\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.031746031746032%\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.158730158730158%\"\u003e\n \u003cp\u003eSig\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.476190476190476%\"\u003e\n \u003cp\u003eExp(B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"21.904761904761905%\"\u003e\n \u003cp\u003e95% C.I EXP (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"47.82608695652174%\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"52.17391304347826%\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eALT (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e-0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e6.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eAST (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e6.980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eTP (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e11.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e1.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e1.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e2.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eTG (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e8.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.004*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eTC (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e4.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.042*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e1.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e1.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eCalcium (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.523809523809524%\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e9.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.031746031746032%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.158730158730158%\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e1.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.476190476190476%\"\u003e\n \u003cp\u003e1.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003e2.507\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eALT- alanine transaminase, AST- aspartate transaminase, g/dL- gram per deciliter, HDL-c- high density lipoprotein cholesterol, IU/L- international unit per liter, mg/dL- milligram per deciliter, TC- total cholesterol, TG- triglycerides, TP- total protein.\u003c/p\u003e"},{"header":"4.\tDiscussion ","content":"\u003cp\u003eThis hospital-based case-control study showed statistical significant inference among lipid profile concentrations and clinical chemistry parameters with PE. The mean age, serum values of total bilirubin, direct bilirubin, HDL-c, LDL-c, sodium and potassium ions were comparable between the two groups. The mean GA, BMI, EFW, systolic and diastolic blood pressure measurements were significantly varied between the cases and controls. It is known that PE causes intrauterine fetal restriction (IUGR) and resulted in adverse maternal and neonatal outcomes \u003csup\u003e33, 34\u003c/sup\u003e. The pathological mechanisms in PE and IUGR follows similar molecular pattern. Poor placenta in the early pregnancy leads placental ischemia; in turn this causes hypoxia and oxidative stress which is observed in PE and IUGR \u003csup\u003e35, 36\u003c/sup\u003e. In this study, statistical significant difference was observed in regards to EFW among the two groups but it is difficult to conclude that PE causes IUGR this may be confounded by differences in gestational age.\u003c/p\u003e\n\u003cp\u003eSeveral lipid derived markers are identified which are used for the estimation of PE risk in pregnant women \u003csup\u003e37\u003c/sup\u003e. During the course of pregnancy lipid metabolism has been significantly changed due to hormonal imbalance and hyperglycemia this ended with hypertriglyceridemia and hypercholesterolemia \u003csup\u003e38, 39\u003c/sup\u003e. Abnormal lipid profile findings have been observed in preeclamptic women because of oxidative stress ended with endothelial malfunction this leads to deposition of lipids in the spiral artery which interfere trophoblast invasion by changing prostaglandin synthesis \u003csup\u003e21, 40\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe current study, showed significantly higher concentrations of serum triglyceride in cases than controls respectively. This is in line with the results reported in China and India \u003csup\u003e13, 41\u003c/sup\u003e. The population-based prospective cohort study performed in Netherlands further supports the result \u003csup\u003e42\u003c/sup\u003e. Moreover, our previous systematic review and the other two reviews further strengths our result \u003csup\u003e20, 24, 43\u003c/sup\u003e. During early gestation hypertriglyceridemia is occurred due to reduced triglyceride catabolism as a consequence of hormonal changes and reduced placental uptake of the fatty acids \u003csup\u003e24, 42, 44,45\u003c/sup\u003e. Besides, decreased in lipoprotein enzyme activity and insulin resistance are responsible for this low lipid catabolism at the cellular level which causes hypertriglyceridemia \u003csup\u003e24, 39, 44, 45\u003c/sup\u003e. Abnormal triglyceride is significantly associated with cardiovascular diseases, hypertension, diabetes mellitus and metabolic syndrome in obese and insulin resistant individuals \u003csup\u003e46-48\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, the serum concentration of total cholesterol was significantly increased among cases than normal controls. This is in line with the studies reported in Ethiopia, India and Nigeria \u003csup\u003e20, 23, 49\u003c/sup\u003e. Although, the finding of this study was varied from the study conducted in Saudi Arabia \u003csup\u003e50\u003c/sup\u003e. This may be due to larger sample size we used and gestational age of the participants. In early pregnancy, the mother stayed in anabolic state due to hormonal imbalance and decreased in lipoprotein lipase enzyme activity, these causes hypercholesterolemia. This metabolic adaptation during the course of pregnancy had immense metabolic benefit to secure energy for mother and their fetus in later pregnancy \u003csup\u003e38, 39, 43\u003c/sup\u003e. Although, cholesterol predispose to atherosclerosis, it had diverse metabolic functions which served as the precursors of cell membrane, different steroid hormones and vitamins \u003csup\u003e51\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur study proved that the mean serum HDL-cholesterol concentration was non-significantly reduced in preeclampsia than normal controls. Our previous review and other studies support the result \u003csup\u003e20, 43, 52\u003c/sup\u003e. However, the results of the current study vary from other studies \u003csup\u003e23, 53\u003c/sup\u003e. This minor difference may be due to the sample types (fasting and random blood samples) and the gestational age of the women. HDL-cholesterol involved in reverse cholesterol transport to the liver, which is changed into bile and utilized for the production of biologically active molecules \u003csup\u003e54\u003c/sup\u003e. Studies showed that higher concentration of HDL-cholesterol had protective potential against hypertension and cardiovascular diseases \u003csup\u003e55\u003c/sup\u003e. On the other hand lower blood concentration of HDL-cholesterol importantly increases the risks of hypertension and cardiovascular diseases\u003csup\u003e56, 57\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eOur research article proved that the mean serum LDL-cholesterol concentration was non-significantly raised in cases than normal controls. Supporting result was reported in the study conducted in Saudi Arabia \u003csup\u003e50\u003c/sup\u003e. But inconsistent results were reported from other studies \u003csup\u003e20, 23, 49\u003c/sup\u003e. This difference may be because of the sample size and gestational ages. Besides, maternal serum VLDL-cholesterol concentration was significantly increased in cases than normal controls. This is line with the study conducted in India and our previous review further supports the result \u003csup\u003e20, 49\u003c/sup\u003e. LDL-cholesterol mainly synthesized from VLDL-cholesterol intravascularly as a result of lipoprotein lipase enzyme activity and transports cholesterol into smaller arteries and arterioles \u003csup\u003e58\u003c/sup\u003e. The contents of LDL-cholesterol deposited in the intima of the blood vessel which leads to oxidation of LDL-cholesterol. This oxidation affects the architecture of lipoproteins; this in turn activates macrophage to release inflammatory cytokine and later developed into fatty strakes and atherosclerosis \u003csup\u003e59, 60\u003c/sup\u003e. Liver cells synthesized VLDL-cholesterol to transport lipids reach in triacylglycerol into the vascular system \u003csup\u003e55\u003c/sup\u003e. Abnormally high plasma VLDL-cholesterol and LDL-cholesterol concentrations are positively related with an increased incidence of chronic diseases like; PE, high blood pressure, heart disease, diabetes, atherosclerosis \u003csup\u003e42, 51, 60\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe serum concentrations of AST and ALT values were significantly elevated in PE than normal pregnancy. Comparable results were reported in the studies conducted in Pakistan and India \u003csup\u003e61, 62\u003c/sup\u003e. Numerous evidences showed the association between PE and hepatic dysfunction \u003csup\u003e63, 64\u003c/sup\u003e. Organ dysfunctions are commonly utilized for the diagnosis of PE and severe form of PE, in case of negative proteinuria. HELLP syndrome, stands for hemolysis, elevated liver enzymes (increased twice the upper limit normal), low platelet counts (\u0026lt;100×10\u003csup\u003e9\u003c/sup\u003e/L), renal insufficiency (serum creatinine concentrations \u0026gt;1.1 mg/dL or a doubling of the serum creatinine value in the absence of other renal disease), pulmonary edema and signs of neurological involvement \u003csup\u003e65\u003c/sup\u003e. Severe form of PE involves end organ damage which requires multidisciplinary treatment \u003csup\u003e66\u003c/sup\u003e. The serum total protein was significantly reduced in cases as compared to controls. Supporting evidence was reported in previous study \u003csup\u003e67\u003c/sup\u003e. Lower levels of serum total protein possibly due to reduction in hepatic synthesis of proteins as the consequence of reduced hepatic blood flow secondary to hypovolemia created by higher filtration pressure in the capillaries \u003csup\u003e68\u003c/sup\u003e. Moreover, it is also due to increased angiotensin secretion and increased vascular endothelial cell permeability and leakage of plasma protein \u003csup\u003e69\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAvailable data regarding on the association of electrolytes with PE is somewhat controversial \u003csup\u003e70-72\u003c/sup\u003e. The mechanism how potassium leads to hypertension is not fully addressed nonetheless it supposed that potassium suppresses renin-angiotensin system, activation of sodium potassium pump, decreased vascular resistance, increased excretion of sodium and water and also maintains the function of vascular smooth muscles in response to vasopressin leads to vasoconstriction and PE \u003csup\u003e73, 74\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003eWe found that a significantly lower serum values of calcium in the cases than controls. Calcium is participated in various metabolic pathways including: muscle contraction, nerve impulse transmission, blood pressure regulation, bone and teeth formation, blood clotting, vasodilation, heart beat regulation, hormone and enzyme regulation, fertilization, and maintenance of fluid balance within the cells \u003csup\u003e75, 76\u003c/sup\u003e. The plasma calcium concentration is regulated via the feedback control system with the interaction of parathyroid hormone, active cholecalciferol and calcitonin \u003csup\u003e77\u003c/sup\u003e. Calcium is working as an intracellular signaling molecules with inositol triphosphate (IP3) and calmodulin kinases \u003csup\u003e78\u003c/sup\u003e. Calcium supplementation during pregnancy significantly reduced the risk of premature delivery and maternal deaths \u003csup\u003e79\u003c/sup\u003e. Other reports revealed that calcium supplementation also significantly decreased the risk of gestational hypertension, pre-eclampsia, neonatal mortality and pre-term births \u003csup\u003e80, 81\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe receiver operating characteristic (ROC) curves are useful for comparing the predictive ability of biomarkers \u003csup\u003e82\u003c/sup\u003e. The areas under the ROC curve (AUC) are used to assess the prediction accuracy of various models which ranges from 0.5 to 1.0. If AUC is ≥0.9 it is considered as outstanding and AUC between 0.80-0.89 is excellent and it is between 0.7-0.8 which is acceptable estimate \u003csup\u003e83\u003c/sup\u003e. The combined ROC was evaluated to check the diagnostic accuracy of serum lipid profiles and clinical chemistry parameters for PE risk. In the combined ROC curve analysis model 1 showed excellent (87.7%) diagnostic accuracy while model 2 (79.9%), model 3 (79.4%) and model 4 (78.5%) had moderate prediction potential of PE but model 5 (63.7%) had lower prediction potential of PE. The spearman correlation proved that significant positive correlations have been observed between blood pressure and serum triglyceride, total cholesterol, ALT and AST levels. However, significant negative correlations have been observed between blood pressure and serum total protein, calcium and HDL-cholesterol values. Thus, lipid profiles and clinical chemistry parameters could be utilized for the prediction of PE. \u003c/p\u003e\n"},{"header":"5.\tLimitations ","content":"\u003cp\u003eThis laboratory based study served as the base line information for scientific community. The study conducted on cases and controls selected from the same source population. On the other hand, this study had some forms of limitation. Due to feasibility issues and together with Covid-19 pandemic we used random blood samples for the analysis of lipid profiles which may influence our result. In this study, all the study participants were found in the third trimester it will be better if the lipid profiles were checked across the different trimesters. The case-control study showed an association among the variables. Therefore, it is difficult to conclude the diagnostic accuracy of serum lipid profiles and clinical chemistry parameters to PE. Therefore, to affirm lipid profiles and clinical chemistry parameters as the diagnostic biomarker for PE multicenter prospective cohort study on fasting blood samples may give better insight.\u0026nbsp;\u003c/p\u003e"},{"header":"6.\tConclusion ","content":"\u003cp\u003eOur study showed that maternal serum lipid profiles and clinical chemistry parameters were significantly associated with preeclampsia. The spearman correlation showed significant positive correlation among blood pressure and serum triglyceride, total cholesterol, ALT and AST values whereas significant negative correlation have been seen between blood pressure and HDL-cholesterol, total protein and calcium values. The combined ROC curve analysis of lipid profiles and clinical chemistry parameters showed moderate prediction potential of PE risk than the single biomarkers. This result, suggested that lipid profiles and clinical chemistry parameters could be utilized in the prediction of PE. However, to generate tangible evidences how lipid profiles and clinical chemistry parameters give rise to PE and to include the tests as routine diagnostic marker for PE multi-center large prospective studies will be required.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eALT- alanine transaminase, ANC- antenatal care, AST- aspartate transaminase, BMI- body mass index, CI- confidence interval, DBP- diastolic blood pressure, CVD- cardiovascular disease, EFW- expected fetal weight, GA- gestational age, g/dL- gram per deciliter, HDL-cholesterol- high density lipoprotein cholesterol, IQR- inter quartile range, IU/L- international unit per liter, IUGR- intrauterine fetal growth restriction, kg/m\u003csup\u003e2-\u003c/sup\u003e kilogram per meter square, LDL-cholesterol- low density lipoprotein cholesterol, mg/dL- milligram per deciliter, mmol/L- millimole per liter, PE- pre-eclampsia, SBP- systolic blood pressure, SD- standard deviation, TG- triglycerides, VLDL-cholesterol- very low density lipoprotein cholesterol.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are extremely grateful to the Institute of Biotechnology (IOB) and College of Medicine and Health Science of Bahir Dar University. The authors would like to acknowledge the staff members of the IOB, especially Dr. Mengistie Taye for his unreserved support. We would like to acknowledge the staff members of Tibebe Ghion Specialized hospital laboratory department particularly Mr. Fekadu Ayelign for his endless assistance during laboratory work. Lastly, all authors would like to recognize the data collectors and study populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research project is supported by the Institute of Biotechnology (IOB), Bahir Dar University.\u0026nbsp;\u003cem\u003eThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll\u0026nbsp;\u003cstrong\u003edata generated or analyzed during this study are included in this published article and its supplementary information files\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eET: Conceptualization, reviewed the literature, methodology, laboratory analysis, writing original draft, writing and editing the manuscript. AM: Conceived the research topic, reviewed the literature, study design and validated the final manuscript. EN: \u0026nbsp;Involved in securing budget, data analysis, editing the manuscript and validating the final manuscript. DM and MA: involved in laboratory analysis, data analysis, editing the manuscript and validating the final manuscript. \u0026nbsp;ST: Involved in laboratory, data analysis, editing the manuscript and validating the final manuscript. All authors read and approved the final draft of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interests exist.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSay L, Chou D, Gemmill A, Tun\u0026ccedil;alp \u0026Ouml;, Moller A-B, Daniels J, G\u0026uuml;lmezoglu AM, Temmerman M, Alkema L: \u003cstrong\u003eGlobal causes of maternal death: a WHO systematic analysis\u003c/strong\u003e. \u003cem\u003eThe Lancet Global Health \u003c/em\u003e2014, \u003cstrong\u003e2\u003c/strong\u003e(6):e323-e333.\u003c/li\u003e\n\u003cli\u003eYang Y, Le Ray I, Zhu J, Zhang J, Hua J, Reilly M: \u003cstrong\u003ePreeclampsia Prevalence, Risk Factors, and Pregnancy Outcomes in Sweden and China\u003c/strong\u003e. \u003cem\u003eJAMA Netw Open \u003c/em\u003e2021, \u003cstrong\u003e4\u003c/strong\u003e(5):e218401.\u003c/li\u003e\n\u003cli\u003ePoon 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\u003cstrong\u003e75\u003c/strong\u003e(1):25-36.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pre-eclampsia, Serum, Lipid profiles, Clinical chemistry, Prediction.","lastPublishedDoi":"10.21203/rs.3.rs-2404370/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2404370/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePre-eclampsia (PE) is a pregnancy related metabolic syndrome which adversely influence the mother and their newborn infants. Besides, lack of study in our population, some studies also reporting discrepancies in the association of lipid profiles and clinical chemistry parameters with the risk of PE. Hence, this study was designed to evaluate the diagnostic potential of serum lipid profiles and clinical chemistry parameters with PE. Institution-based case-control study was performed at Bahir Dar city governmental hospitals. The study participants were selected through simple random sampling and the socio-demographic data were collected by interview-administered questionnaire. Five ml of venous blood were collected to evaluate lipid profile and clinical chemistry parameters. Descriptive statistics, chi-squared test, multivariable logistic regression and Mann-Whitney U test were utilized for analysis of variables. ROC and combined ROC curve analysis were executed to check the diagnostic accuracy at 95% CI. A total of 336 study participants (168 cases and 168 controls) were included. The median concentrations of serum triglyceride (229 (180-293.75) vs 194 (158.5\u0026ndash;255)), total cholesterol (196 (167.25\u0026ndash;224) vs 185.5 (158.5-212.75)), ALT (23(20\u0026ndash;32) vs 21 (20\u0026ndash;25)) and AST (35 (23.25-45) vs 24 (20\u0026ndash;35)) values were significantly increased in cases as compared with normal controls. However, the median concentrations of serum total protein (6.7(6.1\u0026ndash;7.4) vs 7.1 (6.7\u0026ndash;7.6)) and serum calcium (7.6 (7.1\u0026ndash;7.9) vs 7.9(7.5\u0026ndash;8.3)) were significantly decreased in cases than controls. Positive correlations were observed between blood pressure and serum levels of triglyceride, total cholesterol, ALT \u0026amp; AST values while negative correlations were shown between blood pressure and HDL-cholesterol, total protein and serum calcium values. The combined ROC curve analysis of serum lipid profiles and clinical chemistry parameters showed a moderate prediction potential of PE. Hence, serum lipid profiles and clinical chemistry parameters were utilized as the diagnostic biomarkers of PE. However, to generate tangible evidence on the roles of lipid profiles and clinical chemistry parameters in PE pathogenesis and to include them as routine diagnostic biomarker multi-center prospective studies will be warranted.\u003c/p\u003e","manuscriptTitle":"Evaluation of maternal serum lipid profiles and clinical chemistry parameters in the prediction of pre-eclampsia in pregnant women attending ANC and delivery services","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-05 18:03:13","doi":"10.21203/rs.3.rs-2404370/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f8b4a97-a48d-4f39-af1f-01de3c26c116","owner":[],"postedDate":"January 5th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":18091299,"name":"Biological sciences/Biochemistry"},{"id":18091300,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2023-05-26T03:44:18+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-05 18:03:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2404370","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2404370","identity":"rs-2404370","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}