Prediction of Postpartum Diabetes Mellitus in Gestational Diabetes Mellitus Patients by Serum Ferritin

Research Article

Austin J Obstet Gynecol. 2017; 4(4): 1083.

Prediction of Postpartum Diabetes Mellitus in Gestational Diabetes Mellitus Patients by Serum Ferritin

Belal S¹*, Adaroas AS² and Nassar NEHA²

¹Department of Obstetrics and Gynecology, El Sahel Teaching Hospital, Egypt

²Department of Clinical and Chemical Pathology, El Sahel Teaching Hospital, Egypt

*Corresponding author: Shimaa Belal, Department of Obstetrics and Gynecology, El Sahel Teaching Hospital, Egypt

Received: November 05, 2017; Accepted: December 04, 2017; Published: December 11, 2017

Abstract

Objectives: The aim of this study is to determine the possible role of ferritin in predicting early development (eight week after delivery) of postpartum glucose intolerance and diabetes mellitus in patient with gestational diabetes mellitus.

Methodology: 50 pregnant women diagnosed as GDM, their gestational ages ranging from 24 to 37 weeks, were selected for this study. History was obtained, general examination was done, and Body Mass Index (BMI) was determined for all participants, as well as laboratory analysis of their serum for ferritin 8 weeks after delivery, and was evaluated for DM, based on the standard oral glucose tolerance test with 75g glucose.

Results: 10 cases developed postpartum DM, and 5 cases developed IGT/IFG. The mean interquartile serum ferritin was insignificantly higher in the diabetic group when compared to the normal group (P > 0.05). The serum ferritin level was a poor predictor for development of postpartum DM, (P > 0.05). The serum ferritin level was a poor predictor for development of postpartum IGT or DM (P < 0.05).

Conclusion: Serum ferritin was insignificantly higher in diabetic group when compared to normal group. Serum ferritin was a poor predictor of postpartum development of DM or IGT.

Keywords: Gestational diabetes mellitus; Ferritin

Introduction

Expert Committee on the Diagnosis and Classification of Diabetes Mellitus defined Gestational Diabetes Mellitus (GDM) as the new onset or new diagnosis of glucose intolerance during pregnancy, complicates 4% of pregnancies [1].

Women with a history of Gestational Diabetes Mellitus (GDM) are characterized by a high risk of Type 2 Diabetes Mellitus (T2DM) 7 fold, metabolic syndrome 2 to 5 fold and Cardiovascular Diseases (CVD) 1,7 fold. Women with lesser degrees of glucose intolerance share the same risks. Type 2 diabetes mellitus may occur from postpartum (5 to 14%) to several years later, up to 25 years [2].

Serum ferritin is sensitive to body stores of iron and is currently the most reliable non-invasive marker of iron status in pregnancy [3].

Because it is an acute phase protein, Serum Ferritin (SF) is increased independent of iron status by acute or chronic inflammation [2].

It was stated that in pregnant women, higher hemoglobin (Hb) (>13g/dl) was an independent risk for GDM and that women with iron deficiency anemia had a reduced risk of GDM [4].

A few studies found that high serum ferritin and C Reactive Protein (CRP) levels are independent risk factors for type 2 diabetes [5].

Iron stores, expressed as serum ferritin concentration, have been proposed to be a component of the insulin-resistance syndrome. Indeed, the concentration of circulating ferritin was significantly associated with centrally distributed body fatness as well as with several other measurements of obesity. In gestational diabetes, both Body Mass Index (BMI) and serum ferritin levels were found to be independent predictors of 2-h glucose during an oral glucose tolerance test [6].

In humans, elevated iron stores during pregnancy have been associated with maternal and neonatal morbidity. Women with raised ferritin levels in the third trimester of pregnancy have a greatly increased risk of preeclampsia, Intrauterine Growth Retardation (IUGR) and preterm delivery [7].

Subjects and Methods

This cohort study was conducted at Al Sahel Teaching hospital from Jan 2017 to July 2017. Patients were recruited from outpatients’ clinics and those who were admitted in hospitals. 50 pregnant women were diagnosed as gestational diabetes mellitus, their gestational ages ranged from 24 to 37 weeks were selected for this study.

Justification of the sample size

With the assumption that 12.5% will develop DM and 35% will develop either DM or impaired glucose tolerance (IGT), and AUC (Area under the curve) =80% with 15% margin of error and with alpha =0.05 and power of 80% the following sample size will be needed: 50 to differentiate between normal and any (DM or IGT), PASS power analysis and sample size, NCSS.www.ncss.com.

Inclusion criteria

Pregnant women diagnosed as gestational diabetes mellitus. Gestational age 24-37 weeks.

Exclusion criteri

Anaemia (hemoglobin =10.5gm/dl.

Acute or chronic inflammatory or infective diseases.

Pregestational diabetes mellitus.

Acute or chronic liver disease.

Acute or chronic renal disease and malignancy.

History of malignancy, seizure disorder, drug or alcohol abuse.

All patients enrolled in this study were subjected to the following:

• Informed written consent was obtained from the patients who were included in the study.

• To confirm exclusion and inclusion criteria complete history was taken; including: personal history, present history, past history, menstrual history, obstetric history, medical history and family history.

• General examination: vital signs, body mass index (BMI) [weight (kg)/height (m²)] below 25kg/m² was defined as normal, while 25-29.9 kg/m² was perceived as overweight and above 30 was considered as obese.

• For each patient a blood sample was collected for laboratory investigations (serum ferritin, C-reactive protein, insulin, glycosylated hemoglobin (HbA1c), and hemoglobin levels).

Method of blood samples collection

Venous blood sample of 5ml was collected from each subject using a disposable plastic syringe after sterilization of skin with iso propyl alcohol (70%) swabs.

Blood samples were collected in disposable plastic tubes and left for half an hour to allow clotting of the blood and separation of the serum.

The specimens were centrifuged immediately thereafter for 5 minutes at 4.000rpm, and the supernatant serum was transferred into another dry, clean, non contaminated tube and immediately frozen and stored at -20C. Serum ferritin level was measured using Enzyme- Linked Immunosorbent Assay (ELISA).

• Pregnancy outcomes were recorded in all subjects including weight of the baby.

• A diagnostic Oral Glucose Tolerance Test (OGTT) was performed eight weeks after delivery.

Measurements of OGTT

Diagnoses of type 2DM, Impaired Glucose Tolerance (IGT) and Impaired Fasting Glucose (IFG) were made with 75 gram OGTT based on the suggestions of the World Health Organization (WHO) 2006. The patients were divided into 3 groups according to their final diagnoses following 75 gram glucose loading test: Normal Glucose Tolerance (NGT) group (Patients with Fasting Plasma Glucose (FPG) of <110 mg/dl and the second hour the plasma glucose was = 140. IGT/IFG group (Patients with an FPG value of between 110-125 mg/ dl and following the loading, when at the second hour the plasma glucose was between 140-199 mg/dl. Type 2 DM group (Patients with FPG of =126mg/dl or following the loading, when at the second hour the plasma glucose was = 200mg/dl. Plasma glucose concentrations were measured using the standard glucose oxidize method from venous plasma samples.

Statistical methods

Statistical analysis was done on a personal computer using IBM© SPSS© Statistics version 21 (IBM© Corp., Armonk, NY) and MedCelc© version 11.4 (MedCalc© Software bvba, Ostend, Belgium).

Normality of numerical data distribution was tested using The Komogorov-Smirnov and the Shapiro-Wilk tests. Normally distributed numerical data were presented as mean and standard deviation and differences among the groups were compared parametrically using one-way analysis of variance (ANOVA) with application the Turkey Honstly Significant Difference (HSD) test for post hoc pair wise comparisons if ANOVA revealed a statistically significant difference among the group.

Skewed data are presented as quartiles and intergroup differences are compared non-parametrically using the Kruskal Wallis test. The Mann-Whitney U test was employed for post hoc pair wise comparisons if the Kruskal Wallis test revealed a statistically significant difference among the group.

Categorical data were presented as number and percentage and between-group differences are compared using the Pearson chi square test or the chi square test for trends for nominal or ordinal data, respectively. Fisher’s exact test is used in place of the chi square test if >20% of cells in any contingency table had an expected count of <5.

Receiver-Operating Characteristic (ROC) curve analysis was used to examine the value of continuous variables for prediction of binary outcomes. The DeLong method was used to compare the Areas Under the Curve (AUC) for any pair of ROC curves.

Multiple logistic regressions were used to determine independent predictors for binary outcomes.

All P values are two-sided. The Bonferroni method was used to correct for multiple pair wise comparisons with the U test. This indicated that to maintain a final type I error of 0.05, significance should be set at the P < 0.017 level for pair wise comparisons with the U test. Otherwise, P < 0.05 is considered statistically significant.

Results

Table 1 and 2 show characteristics of the included women.