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FINDRISC questionnaire as a potential screening strategy for gestational diabetes mellitus

ElifMESECI

Obstetrics and Gynecology Department, Acıbadem Kozyatagı Hospital, Istanbul, Turkey

E-mail : elfmsc@yahoo.com

Yasar Ozlem MERICLILER

Internal Medicine, Endocrinology and Metabolism Clinic, Acıbadem University Medical School , Acıbadem Kozyatagı Hospital, Istanbul, Turkey

AyseGulcin DEMIRDOVEN

Obstetrics and Gynecology Department, Fatih University Medical School, Istanbul, Turkey

Erdogan ASLAN

Obstetrics and Gynecology Department, Yeni Karaman Mah, Bursa, Turkey

Semra KAYATAS ESER

Obstetrics and Gynecology Department, Zeynep Kamil Education and Training Hospital, Istanbul, Turkey

Yasemin KANEK

Acıbadem Kozyatagı Hospital, Istanbul, Turkey

Mustafa SERTESER

Department of Medical Biochemistry, Acıbadem Univesity, School of Medicine, Acibadem Labmed Clinical Laboratories, Istanbul, Turkey

Ali Murat YAYLA

Department of Perinatology, Acıbadem Kozyatagı Hospital, Istanbul, Turkey

DOI: 10.15761/FWH.1000101

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Abstract

Objective

We aimed to determine the predictive value of FINDRISC score as a screening method for gestational diabetes mellitus (GDM).

Methods

 A prospective, cross - sectional study was carried out with a total 111 pregnant women. At the first antenatal visit, FINDRISC questionnaire was filled out by one doctor.A 50 g oral glucose challenge test (GCT) was performed between the 24 - 28thweek of gestation. If the test exceeded thethreshold value, a 3 h 100g oral glucose tolerance test (OGTT) was performed toconfirm the diagnosis of GDM.

Results

44 (39.6%) of 111 patientsGCT were positive. 17 patients (16.2%) werenewly diagnosed with GDM. The FINDRISC scores of the GDM (+) patients were found to be significantly higher than that of GDM (-) group with a cutoff value of>9. At this cutoff point the sensitivity, specifity, positive predictive value, negative predictive value, and + likelihood ratiowere 52.94, 79.79, 32.1, 90.4, and 2.62, respectively.The area under the ROC curvein the detection of GDM was 0.708 ± 0.07.

Conclusion

 FINDRISC score may serve as an easy, non - invasive and cost - saving initial assessment tool for screening of GDM.

Key words

findrisc score, gestational diabetes mellitus, screening

Introduction

Gestational diabetes mellitus (GDM) defined as glucose intolerance with onset or first recognition during pregnancy, occurs in 2 - 5% of all pregnancies [1].It is associated with increased rates of adverse pregnancy outcomes, such as macrosomia, neonatal jaundice, neonatal hypoglycemia, and birth - related trauma. In addition, women with GDM are at higher risk for the development of type 2 diabetes mellitus (T2D) later in life [2]. Trials show that treatment of GDM by dietary restrictions and insulin therapy, if required, reduces the rate of perinatal complications [2]. Hence, identification and treatment of women with GDM is universally regarded as oneoftheprimary goals of obstetric healthcare givers, as prompted by manyprofessional authorities including World Health Organization (WHO), American Congress of Obstetricians and Gynecologists (ACOG), Royal College of Obstetricians and Gynaecologists (RCOG), American Diabetes Association (ADA) and similars [3-6].

GDM and T2D has many common pathophysiologicabnormalities like insulin resistance, hyperinsulinemia, and beta-cell hypofunction [1].The distinctive features of T2D such as older age, higher body mass index (BMI), and family history of diabetesare also proved to beindependent risk factors for the development of GDM [7,8]. Genetically it has been shown that T2D risk alleles are more frequent among women with a history of GDM [9]. These data raises the argument that GDM may be a phase of the syndrome of insulin resistance [1].

Many studies proved that if high risk individuals could be detected in the prediabetic state, preventive attempts like life style modification and the use of insulin sensitizing drugs such as metformine could prevent or delay the development of T2D [6]. This urge for the early detection of the high risk individuals resulted in a search for the development of a simple, practical and informative scoring system forscreening the population. FINDRISC score is a questionnaire designed to screen the population for increased T2D risk and several studies showed a correlation of a high FINDRISC score and the diagnosis of any degree of glucose metabolism disorder [10]. However, there have been no publications found on the use of the Findrisc forscreening of GDM during pregnancy in particular.             

Our aim in this study was to investigate whether FINDRISC questionnaire could be used as a screening method to detect women with increased risk of having GDM.

Materials and method

In thisprospective, cross-sectional study 111 women followed during their pregnancy at the outpatient obstetric department of Kozyatagı Acıbadem Hospital, Istanbul, Turkey, between 2011 - 2013 were invited to participate.Individuals were eligible if they had no prior chronic medical illness, not taking glucocorticoids.Women with a history of preexisting diabetes, who delivered before 28 weeks of gestation and multifetal gestations were excluded from the study.All participants were informed aboutthe aim ofthe study andgave written informed consent to attend. This study was approved by the ethics committee of Acıbadem University of Medical School.

Patients that came to the first antenatal follow up before the 4th gestational week , whose β - human chorionic gonadotrophin (β -hcg)tests were positivebut gestational sac were not observed by ultrasound, were included to our study. Heights, waist circumferences, weights of the patients were measured by trained personnel. BMI was calculated as weight (kg)/[(height (m)]². Obstetric history, history of previous pregnancies, family history of diabetes, age, smoking habits were noted. 111 women who accepted to participate had replied the questions of the FINDRISC questionnaire at the same visit by one doctor.

The FINDRISC is calculated based on a simple questionnaire with 8 questions, including age (years), BMI (kg/m²), waist circumference (WC: cm), history ofantihypertensive drug treatment, history of high blood glucose, family history of diabetes, daily consumption of fruits, berries, or vegetables (consume every day vs. not), and daily physical activity (having at least 30 minutes of physical activity during work or at leisure time vs. not). It isshown in Table 1.1 and 1.2 [10].The answer of every question is assigned with different weighted scores according to the risk increase associated with the respective values in the regression model in the original cohort. The final score is the sum of thescores from 8 questions and ranges from 0 to 26.

Finnish Diabetes Risk Score

point (s)

Age

< 35

35 - 44

45 - 54

55 - 64

> 64

0

1

2

3

4

Family History of T2D

none

Parents, siblings, children

grandparents, aunt, uncle, cousin

0

5

3

(highest score is 5)

Waist circumference (cm)

Female   /     Male

< 80       /     < 94

80 - 88     /     94 - 102

>88        /      > 102

0

3

4

Exercise

( at least 30 min / day)

Yes

no

0

2

Diet: daily vegetables, fruit and fiber consumption

Yes

no

0

1

Hypertension

no

Yes

0

2

History of high blood glucose

no

Yes

0

5

Body mass index (kg / m2)

< 25

25 - 30

> 30

0

1

3

Table 1.1:Type  2 diabetes risk test (FINDRISC questionnaire) [10].

Total scores (points)

Risk rating

10-year risk

< 7

Low

1%  (1/100)

7 - 11

Mild

4%  (1/25)

12 - 14

Moderate

16% (1/6)

15 - 20

High

33%  (1/3)

> 20

Very high

50%  (1/2)

Table 1.2 : Evaluation of FINDRISC (diabetes risk score) [10].

During monthly follow - up, weight gain at each trimester, laboratory tests including 50 g glucose challenge test (GCT)and if performed 100 g 3 h oral glucose tolerance test (OGTT), the follow - up method of any newly diagnosed GDM (diet and / or insulin), diabetes regulation parameters such as HbA1c and fructosamine, duration of pregnancy in days, birth weight of the neonate in grams, and Apgar score of the neonatewere recorded.

Fordiagnosis of GDM, we used two-step approch according to ADA 2010 definitions [12]. A 50 g oral glucose challenge test was performed between the 24 - 28th week of gestation. The test was performed irrespective of time of the day and of the last meal. Plasma glucose was measured 1 h after administration of a solution containing 50 g glucose. The predefined cutoff value for an abnormal test result was a 1h plasma glucose value of > 140 mg / dl [12]. If 50g oral glucose challenge test exceeded the predefined threshold value, a 3 h 100 g OGTT was performed within one week to rule out or confirm the diagnosis of GDM. The OGTT was performed in the morning after 8 to 12h overnight fast and 3days of normal carbohydrate diet (150 - 200 g/day). A positive OGTT was defined according toCarpenter and Coustan thresholds as two or more values that were abnormal: fasting ≥ 96 mg/dl, 1h ≥ 180 mg / dl, 2h ≥ 155 mg / dl, 3h≥ 140 mg / dl [12,13].

HbA1c and fructosamine were measured in patients with confirmed GDM and fructosamine was repeatedmonthly as a marker for blood sugar regulation.

Glucose, fructosamine and HbA1c levels were analyzed in Cobas Integra 400 by using reagents from Roche Diagnostics.

Statistical calculations were performed with NCSS (Number Cruncher Statistical System) 2007 Statistical Software (Utah, USA)program for Windows. Besides standard descriptive statistical calculations (mean, standard deviation) unpaired t test was used in the comparison of two groups, andChi square test and odds ratio was performed during the evaluation of qualitative data. The results were evaluated within a 95% confidence interval. Statistical significance level was established at p<0.05.

To calculate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratio(LR) (+) for the FINDRISC score measurements at varying cut - off values, a conventional receiver operating characteristic curve was generated and the area under the curve (AUC) was calculated for FINDRISC scores.

Results

111 women were included to the study. 44 (39.6%) of 111 patients oral glucose challenge test were positive. Based on oral glucose tolerance test, 17 patient (16.2%) werenewly diagnosed with gestational diabetes mellitus, 26 patients (23.4%) had impaired glucose tolerance .The descriptive propertiesof the participantswere shown in Table 2.

GDM (-)

GDM (+)

p

n

94

17

Age

32.24±4.22

33.41±3.55

0.286

BMI  (kg/m2)

22.62±3.71

24.41±3.73

0.069

Smoking

                No

                Yes

                Quit

n=67   71.28 %

n=7      7.45 %

n=20   21.28 %

n=8    47.06 %

n=4    23.53 %

n=5   29.41 %

0.03

0.308

Educational attainment

                Primary school

                High school

                College

n= 1      1.06 %

n=9       9.57 %

n= 84   89.36 %

n= 1     5.88 %

n= 3      17.65 %

n=13    76.65 %

0.091

Parity

                1

                2

                3

Duration of pregnancy (weeks)

 

n= 75    79.79 %

n= 16    17.02%

n= 3        1.19 %

38.72 ± 1.26

n= 16   94.12 %

n= 1       5.88 %

n= 0       0.00 %

38.41 ± 1.06

0.035

0.346

Birth weight of the infant (gr)

3434.19 ±

3282.71 ± 293.49

0.156

Rate of weight gain (kg)

              1st trimester

              2nd trimester

              3rd trimester

              Total weight gain

 

1.06 ± 1.46

5.81 ± 1.68

6.72 ± 2.31

13.60 ± 3,32

 

 

2.82 ± 0.93

7.03 ± 2.07

7.04 ± 2.03

17.87 ± 3.21

 

 

0.0001

0.001

0.586

0.0001

 

Table 2:  Characteristics of the study population.

Age, number of pregnancies, BMI, own birth weight of mothers, and the level of education were statistically similar both in GDM (+) and (–) groups.

Smoking history was statistically higher in the GDM (+) group (n = 4, 23%, p= 0.03). Cessation of smoking was comparable betweengroups.

Family history of DM in any relative showed 2.5 fold increased risk in GDM (+) group whereas T2D history of the mother, father, siblings, and second degree relative showed a 2.37, 2.7, 3, and 2.5 fold increase for the risk of GDM, respectively. The odds ratios (OR) wereshown in Table 3.

Family history of T2D

GDM ( - )

GDM ( + )

p

OR (95% CI)

none

n = 41  43.62%

n = 4   23.53%

Mother

n = 13  13.83%

n = 3   17.65%

0.365

2.37(0.47 - 11.98)

Father

n = 15  15.96%

n = 4   23.53%

0.223

2.7  (0.61 - 12.4)

Sibling

n = 1     1.06%

n = 0     0.00%

0.999

3    (0.11 - 87.27)

Second degree relative

n = 24  25.53%

n = 6  35.29%

0.185

2.5   (0.66 - 10)

Any family history of T2D

                 None

                 (+)

n = 41  43.62%

n = 53  56.38%

n = 4     23.53%

n = 13   76.47%

0.021

2.5 (0.76 - 8.29)

Table 3: Odds ratios and 95% confidence intervals for GDM associated with family history of T2D.OR: odds ratio; CI: confidence interval; Data are n (%) or odds ratio (95% CI).

Total weight gain in the GDM (+) group during 1sttrimester, and 2nd trimester and entire pregnancywere statistically higher than that of GDM (-) group (p = 0.0001, p = 0.001, p = 0.0001, respectively). There was no significant difference for the weight gain during the 3rd trimester among the groups (p = 0.586). Weight characteristics of the participants wereshown in Table 2.Pregnancy duration was similar in both groups as well as the birth weight of the neonates (p = 0.346 and p = 0.156, respectively; Table 2).

FINDRISC score of the GDM ( + ) (9 ± 3.64) group was significantly higher than the GDM (-) (6.13 ± 3.6) group (p = 0.003). The area under the ROC curve with less than 2 risk factors in the detection of GDM was 0.708 ± 0.07 , as shown in Table 4.

GDM ( - )

n  = 94

GDM ( + )

n  = 17

FINDRISC

6.13 ± 3.6

9± 3.64

p = 0.003

 

FINDRISC ≤ 2 Risk

Area under the ROC curve (AUC)

0.708 ± 0.07

Table 4:FINDRISC  score of the groups  and area under the ROC curve for the score.

The cutoff value for the FINDRISC score was > 9 and at this cutoff point the sensitivity, specifity, positive predictive value, negative predictive value, and + LR were 52.94, 79.79, 32.1, 90.4, and 2.62, respectively , as shown in Table5. Criterion values and coordinates of the ROC curve were shown in Figure 1.          

Figure 1: Area under receive-operating characteristic curve (AUC) of FINDRISC score values to predict GDM.

Criterion

Sensitivity

Specificity

PPV

NPV

+ LR

- LR

> 0

100.00

6.38

16.2

100.0

1.07

0.00

> 1

100.00

7.45

16.3

100.0

1.08

0.00

> 2

100.00

22.34

18.9

100.0

1.29

0.00

> 3

94.12

27.66

19.0

96.3

1.30

0.21

> 4

88.24

29.79

18.5

93.3

1.26

0.39

> 5

82.35

45.74

21.5

93.5

1.52

0.39

> 6

70.59

56.38

22.6

91.4

1.62

0.52

> 7

52.94

63.83

20.9

88.2

1.46

0.74

> 8

52.94

75.53

28.1

89.9

2.16

0.62

> 9*

52.94

79.79

32.1

90.4

2.62

0.59

> 10

41.18

85.11

33.3

88.9

2.76

0.69

>11

29.41

92.55

41.7

87.9

3.95

0.76

> 12

17.65

97.87

60.0

86.8

8.29

0.84

> 13

11.76

98.94

66.7

86.1

11.06

0.89

> 14

5.88

98.94

50.0

85.3

5.53

0.95

> 15

0.00

98.94

0.0

84.5

0.00

1.01

> 16

0.00

100.00

 

84.7

 

1.00

Table5:Treshold values for FINDRISC  score showing sensitivity, specificity, PPV, NPV along with LR + / LR - tests. PPV / NPV: positive / negative predictive value, LR +/ LR - : likelihood ratio of positive / negative tests.

Discussion

The first important observation resulting from our study is the significant difference of the FINDRISC score among the GDM (+) and (-) groups. The FINDRISC scores of the GDM (+) patients were found to be significantly higher than that of GDM (-) group with a cutoff value of> 9. FINDRISC score >9 had asensitivity, specifity, positive predictive value, negative predictive value, and + LR were 52.94, 79.79, 32.1, 90.4, and 2.62, respectively. So a pregnant with > 9 FINDRISChas 2.62 times more risk to be GDM than a pregnant with< 9. Although there was sufficient data about the predictive value of the FINDRISC questionnaire as a potential screening strategy for T2D in healthy population [11], so far we did not meet any published data about FINDRISC questionnaire used for the evaluation of GDM during pregnancy. Crowe et al. compared FINDRISC score with 75 g OGTT in a population with a history of GDM to predict prediabetes / diabetes and concluded it to be a convenient screening method helping to determine which patients may need more frequent screening post GDM [12].

Our findings about the risk factors for GDM were largely in concordance with the literature with some exceptions. Although our GDM (+) patients were slightly older, there was no significant difference among the groups.Age is classically used in risk scores for GDM and it is one of the questions in FINDRISC questionnaire. Cosson et al. reported that women > 35 years old compared with those < 25 had a twofold increased risk of GDM [13]. SimilarlyBMI was insignificantly higher in the GDM (+) group compared to the GDM (-) group. Weight is also a widely accepted risk factor for GDM and a part of FINDRISC questionnaire. A recent meta-analysis showed that for each increasing kilogram per meter squared of BMI, the prevalence of GDM rose by 0.92% [14]. The disconcordance of our results to the current literature on age and BMI might be because of our small sample size. However, ethnic differences among the study populations, different BMI cut - off values used to define obesity in different studies, and the strict diet of our overweight/obese patients to control weight gain during pregnancy may be other factors. But our finding that total gestational weight gain as well as the 1st and 2nd trimester weight gain were significantly higher in the GDM (+) group was consistentlysupported by the literature [8,15].

Family history of diabetes has been reported to increase the risk for the development of GDM by 1.6 - 3.0 fold in different series [16,17]. In our patient group family history of T2D in any relative showed 2.5 fold increased risk. Although some studies emphesized different risk ratios for paternal or maternal T2D history [18], in our study group T2D history of the mother, father, siblings, and second degree relatives showed a comparable increase at the risk of GDM (2.37, 2.7, 3, and 2.5 fold increase, consecutively).

Historically, HbA1c measurements and fructosamine levels did not adequately discriminate women with normal pregnancy from those with GDM, even though HbA1c levels wereproved to decline in normal pregnancy [19]. In this aspect , our findings were alsoconsistent with literature and monthly repeated fructosamine measurements in GDM patients were comparable with the baseline values at the time of the GDM diagnosis.

Our study has some limitations. First, our sample numberwas low. Another limitation is the possibility of misclassification on diagnosis of GDM because not all participants had OGTTfor definitive diagnosis. AlthoughGCT was used to define GDM (+) and (-) cases, its usemay impactour sensitivity, specificity and other satistical results. We do not haveevidence that FINDRISC score>9 is associated withpoorer pregnancy outcome, or thattreatment from early pregnancy prevent complications, because we had small sample size andhad not any perinatal comlications. Thus, it isan important area offurther research. The strengthof our study is that selection and information bias were unlikely because of the prospective design.

As for the neonatal outcomes, we did not find any difference betweengroups for macrosomia, prematurity, or any other neonatal complications. This may be due to the fact that the blood glucose levels of all of our diabetic patientsremained below the target values.

The traditional diabetes screening methods, including the fasting plasma glucose (FPG), OGTT or HbA1c test, are invasive and expensive. A simple, non -invasive, cost effective and sensitive screening tool is needed in the primary care setting, especially in low-income countries. We suggest thatusing FINDRISCscore at the first antenatal visitas a preliminary screening method followed with more invasive and accurate diagnosis in primary carecan be a cost - effective and practical method.

Overall, we assume that risk factors proposed in FINDRISC questionnaire successfullypredicted GDM. However, prospective studies conducted over larger populations should clarify the clinical relevance of this result. In two large series of Cosson and Jensen, despitea detailed screening of the risk factors the diagnosed number of GDM patients were very low and Cosson emphasized that 34.7% of women with GDM would have been missed without universal screening [13,17]. But both of the studies showed that the prevalence of GDM was particularly high when the number of risk factors was greater than three. Since FINDRISC questionnaire analyses eight different risk factors, the cutoff>9 was assumed to be equivalent to three or more positive scores.

In conclusion, women with a history of GDM are considered as high-risk individuals for the development of T2D in later life, andGDM is proved to share many common features and risk factors with T2D such as insulin resistance, obesity, and family history of T2D. The earlydetection and treatment is warranted not only asignificant burden for the patients themselvesbut alsofor the health care system and thenationaleconomy.FINDRISC score may serve as an easy, non - invasive and cost saving initial assessment toolto diagnose women with these features at the beginning of pregnancy leading to take early precautions such as diet and exercise and may lead to lower perinatal complications.

Acknowledgements

We thank all the participants for attending in this study.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

References

  1. Clark MC, Qui C, Amerman B, Porter B, Fineberg N,et al.(1997) Gestational Diabetes: Should it be added to the syndrome of insulin resistance? Diab Care20: 867 - 871. [Crossref]
  2. Van Leeuwen M, Zweers EJK, Opmeer B, Van Ballegooie E, Ter Brugge HG,et al.(2007)  Comparison of accuracy measures of two screening tests for gestational diabetes mellitus. Diab Care30: 2779-2784.[Crossref]
  3. World Health Organization (WHO)2013. Diagnostic Criteria and Classification Of Hyperglycaemia Firs Detected in Pregnancy. WHO 2013.WHO / NMH / MND13.2
  4. American College of Obstetricians and Gynecologist (ACOG). Gestational Diabetes Mellitus.Washington (DC) : American College of Obstetricians and Gynecologist (ACOG); 213 Aug.11.p. (ACOG practice bulletin; no137)
  5. Royal College of Obstetricians and Gynaecologists (RCOG). Diagnosis and Treatment of Gestational Diabetes.Scientific Impact Paper No.23, Jan.2011.
  6. American Diabetes Association (ADA).Standards of Medical Care in Diabetes - 2014. Diabetes Care Volume37, January2014.
  7. Cypryk K, Szymczak W, Czupryniak L, Sobczak M, Lewiski A (2008) Gestational diabetes mellitus-an analysis of risk factors. Endocrynol Pol59: 393 -397.[Crossref]
  8. Heude B, Thiebaugeorges O, Goua V, Forhan A, Kaminski M,et al.(2012)Pre-pregnancy body mass index and weight gain during pregnancy: relations with gestational diabetes and hypertension, and birth outcomes. Matern Child Health J16: 355 - 363.[Crossref]
  9. Lauenborg J, Grarup N, Damm P, Borch-Johnsen K, Jorgensen T,et al.(2009) Common type 2 diabetes risk gene variants associate with gestational diabetes. J Clin Endocrinol Metab94: 145-150.[Crossref]
  10. Lindstrom J, Toumilehto J (2003) The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diab Care26: 725-731.[Crossref]
  11. Lindström J, Peltonen M, Eriksson JG, Aunola S, Hamalainen H,et al.(2008) Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study. Diab Care31: 857-862.[Crossref]
  12. American Diabetes Association (ADA). Standards of Medical Care in Diabetes – 2010 (2010) Diabetes Care. 33: S62–S69.[Crossref]
  13. Carpenter MW, Coustan DR (1982) Criteria for screening tests for gestational diabetes. Am J Obstet Gynecol 144: 768–773.[Crossref]
  14. Makrilakis K, Liatis S, Grammatikou S, Zacharopoulou O, Tigas S,et al.(2007) Screening for diabetes and pre-diabetes using the FINDRISK questionnaire in a random Greek population: The Deplan type 2 diabetes prevention study. Diabetes56: pA629.
  15. Crowe C, Noctor E, Carmody LA, Wickham B, Avalos G,et al. (2012) Validation of a diabetes risk score in identifying patients at risk of progression to abnormal glucose tolerance post partum. BMC Proceedings6: O36.
  16. Cosson E, Benbara A, Pharisien I, Nguyen MT, Revaux A, et al.(2013) Diagnostic and prognostic performances over 9 years of a selective screening strategy for gestational diabetes mellitus in a cohort of 18,775 subjects. Diab Care 36: 598-603.[Crossref]
  17. Torloni MR, Betran AP, Horta BL, Nakamura MU, Atallah AN,et al.(2010) Prepregnancy BMI and the risk of gestational diabetes:a systematic review of the literature with meta-analysis. Obes Rev10: 194-203.[Crossref]
  18. Cheng YW, Chang JH, Kurbisch-Block I, Inturrisi M, Shafer S, et al.(2008) Gestational weight gain and gestational diabetes mellitus. Obstet Gynecol112: 1015-1022. [Crossref]
  19. Galtier F (2006) Definition, epidemiology, risk factors. Diabetes Metab32: 140-146.
  20. Jensen DM, Molsted-Pederson L, Beck-Nielsen H, Westergaard JG, Ovesen P, et al.(2003) Screening for gestational diabetes mellitus by a model based on risk predictors: a prospective study. Am J Obstet Gynecol34: 719-728.[Crossref]
  21. Tabak AG, Tamas G, Peterfalvi A, Bornyak Z, Madarasz E,et al.(2009) The effect of paternal and maternal history of diabetes mellitus on the development of gestational diabetes mellitus. J Endocrinol Invest32: 606-610.[Crossref]
  22. Nielsen LR, Ekbom P, Damm P, Glümer C, Frandsen MM,et al.(2004) HbA1c levels are significantly lower in early and late pregnancy. Diab Care27:1200-1201.[Crossref]

Article Type

Research Article

Publication history

Received date: January 19, 2016
Accepted date: February 16, 2016
Published date: February 19, 2016

Copyright

©2016Meseci E. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation

Meseci E, Mericliler YO, Demirdoven AG, Aslan E, Eser SK, et al.(2016) FINDRISC questionnaire as a potential screening strategy for gestational diabetes mellitus. Front Womens Health 1: DOI: 10.15761/FWH.1000101

Corresponding author

Elif MESECİ

Obstetrics and Gynecology, Department, AcıbademKozyatagı Hospital, Inonu Cd. Okur S. No:20Kozyatagı34742 Istanbul, Turkey, Tel: +90 216 571 43 30; Fax: + 90 216 571 40 00

E-mail : elfmsc@yahoo.com

Finnish Diabetes Risk Score

point (s)

Age

< 35

35 - 44

45 - 54

55 - 64

> 64

0

1

2

3

4

Family History of T2D

none

Parents, siblings, children

grandparents, aunt, uncle, cousin

0

5

3

(highest score is 5)

Waist circumference (cm)

Female   /     Male

< 80       /     < 94

80 - 88     /     94 - 102

>88        /      > 102

0

3

4

Exercise

( at least 30 min / day)

Yes

no

0

2

Diet: daily vegetables, fruit and fiber consumption

Yes

no

0

1

Hypertension

no

Yes

0

2

History of high blood glucose

no

Yes

0

5

Body mass index (kg / m2)

< 25

25 - 30

> 30

0

1

3

Table 1.1:Type  2 diabetes risk test (FINDRISC questionnaire) [10].

Total scores (points)

Risk rating

10-year risk

< 7

Low

1%  (1/100)

7 - 11

Mild

4%  (1/25)

12 - 14

Moderate

16% (1/6)

15 - 20

High

33%  (1/3)

> 20

Very high

50%  (1/2)

Table 1.2 : Evaluation of FINDRISC (diabetes risk score) [10].

GDM (-)

GDM (+)

p

n

94

17

Age

32.24±4.22

33.41±3.55

0.286

BMI  (kg/m2)

22.62±3.71

24.41±3.73

0.069

Smoking

                No

                Yes

                Quit

n=67   71.28 %

n=7      7.45 %

n=20   21.28 %

n=8    47.06 %

n=4    23.53 %

n=5   29.41 %

0.03

0.308

Educational attainment

                Primary school

                High school

                College

n= 1      1.06 %

n=9       9.57 %

n= 84   89.36 %

n= 1     5.88 %

n= 3      17.65 %

n=13    76.65 %

0.091

Parity

                1

                2

                3

Duration of pregnancy (weeks)

 

n= 75    79.79 %

n= 16    17.02%

n= 3        1.19 %

38.72 ± 1.26

n= 16   94.12 %

n= 1       5.88 %

n= 0       0.00 %

38.41 ± 1.06

0.035

0.346

Birth weight of the infant (gr)

3434.19 ±

3282.71 ± 293.49

0.156

Rate of weight gain (kg)

              1st trimester

              2nd trimester

              3rd trimester

              Total weight gain

 

1.06 ± 1.46

5.81 ± 1.68

6.72 ± 2.31

13.60 ± 3,32

 

 

2.82 ± 0.93

7.03 ± 2.07

7.04 ± 2.03

17.87 ± 3.21

 

 

0.0001

0.001

0.586

0.0001

 

Table 2:  Characteristics of the study population.

Family history of T2D

GDM ( - )

GDM ( + )

p

OR (95% CI)

none

n = 41  43.62%

n = 4   23.53%

Mother

n = 13  13.83%

n = 3   17.65%

0.365

2.37(0.47 - 11.98)

Father

n = 15  15.96%

n = 4   23.53%

0.223

2.7  (0.61 - 12.4)

Sibling

n = 1     1.06%

n = 0     0.00%

0.999

3    (0.11 - 87.27)

Second degree relative

n = 24  25.53%

n = 6  35.29%

0.185

2.5   (0.66 - 10)

Any family history of T2D

                 None

                 (+)

n = 41  43.62%

n = 53  56.38%

n = 4     23.53%

n = 13   76.47%

0.021

2.5 (0.76 - 8.29)

Table 3: Odds ratios and 95% confidence intervals for GDM associated with family history of T2D.OR: odds ratio; CI: confidence interval; Data are n (%) or odds ratio (95% CI).

GDM ( - )

n  = 94

GDM ( + )

n  = 17

FINDRISC

6.13 ± 3.6

9± 3.64

p = 0.003

 

FINDRISC ≤ 2 Risk

Area under the ROC curve (AUC)

0.708 ± 0.07

Table 4:FINDRISC  score of the groups  and area under the ROC curve for the score.

Criterion

Sensitivity

Specificity

PPV

NPV

+ LR

- LR

> 0

100.00

6.38

16.2

100.0

1.07

0.00

> 1

100.00

7.45

16.3

100.0

1.08

0.00

> 2

100.00

22.34

18.9

100.0

1.29

0.00

> 3

94.12

27.66

19.0

96.3

1.30

0.21

> 4

88.24

29.79

18.5

93.3

1.26

0.39

> 5

82.35

45.74

21.5

93.5

1.52

0.39

> 6

70.59

56.38

22.6

91.4

1.62

0.52

> 7

52.94

63.83

20.9

88.2

1.46

0.74

> 8

52.94

75.53

28.1

89.9

2.16

0.62

> 9*

52.94

79.79

32.1

90.4

2.62

0.59

> 10

41.18

85.11

33.3

88.9

2.76

0.69

>11

29.41

92.55

41.7

87.9

3.95

0.76

> 12

17.65

97.87

60.0

86.8

8.29

0.84

> 13

11.76

98.94

66.7

86.1

11.06

0.89

> 14

5.88

98.94

50.0

85.3

5.53

0.95

> 15

0.00

98.94

0.0

84.5

0.00

1.01

> 16

0.00

100.00

 

84.7

 

1.00

Table5:Treshold values for FINDRISC  score showing sensitivity, specificity, PPV, NPV along with LR + / LR - tests. PPV / NPV: positive / negative predictive value, LR +/ LR - : likelihood ratio of positive / negative tests.

Figure 1: Area under receive-operating characteristic curve (AUC) of FINDRISC score values to predict GDM.