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ORIGINAL ARTICLE
Year : 2017  |  Volume : 10  |  Issue : 3  |  Page : 263-267  

The accuracy of polyuria, polydipsia, polyphagia, and Indian Diabetes Risk Score in adults screened for diabetes mellitus type-II


1 District TB Centre, Nanded, Maharashtra, India
2 Department of Paediatrics, Government Medical College, Nagpur, Maharashtra, India
3 Department of Community Medicine, Government Medical College, Miraj, Maharashtra, India
4 District TB Centre, Sindhudurg, Maharashtra, India
5 Department of Community Medicine, Government Medical College, Dhule, Maharashtra, India

Date of Web Publication19-May-2017

Correspondence Address:
Shivshakti D Pawar
District TB Centre, Old Civil Hospital Campus, Vazirabad, Nanded - 431 601, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0975-2870.206569

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  Abstract 

Context: The World Health Organization report suggests that over 19% of the world's diabetic population currently resides in India. Unfortunately, >50% of the diabetics in India are unaware about their diabetic status. In the poor income country like India, it is essential to use cost-effective methods for screening for diabetes, and traditionally using three classical symptoms and Indian Diabetes Risk Score (IDRS) tool is helpful but, data regarding their diagnostic accuracy is very less. Objective: (1) To assess the diagnostic accuracy of polyuria, polydipsia, polyphagia, and IDRS for detecting diabetes. Settings and Design: Six hundred and seventy-seven adult individuals >20 years of age were screened for diabetes and assessed polyuria, polydipsia, polyphagia, and IDRS score. All were subjected for postprandial blood glucose level. Subjects and Methods: For diagnostic accuracy sensitivity, specificity, positive and negative predictive values, likelihood ratios (LRs, for positive and negative tests), and accuracy was calculated for each symptom. Similarly, by receiver operative curve (ROC) curve analysis, we carried out sensitivity and specificity of IDRS. Results: There was statistically significant association between these three classical symptoms and diabetes status of individuals. When present, all these three symptoms carried 7.34% sensitivity and 98.42% specificity with positive predictive value 47.06% and NPV 84.70%, LR+4.36, LR−0.94 with accuracy of 85%. The optimum cutoff value of IDRS score was >50, which carried sensitivity 73%, specificity 58.7%, and area under curve for ROC was 68% (P < 0.001). Conclusions: This study has shown highest specificity for these three classical symptoms in diagnosing diabetes, but these symptoms were insensitive to detect all diabetic subjects.

Keywords: Diabetes mellitus type II, Indian Diabetes Risk Score, polyphagia, polyuria, polydipsia


How to cite this article:
Pawar SD, Thakur P, Radhe B K, Jadhav H, Behere V, Pagar V. The accuracy of polyuria, polydipsia, polyphagia, and Indian Diabetes Risk Score in adults screened for diabetes mellitus type-II. Med J DY Patil Univ 2017;10:263-7

How to cite this URL:
Pawar SD, Thakur P, Radhe B K, Jadhav H, Behere V, Pagar V. The accuracy of polyuria, polydipsia, polyphagia, and Indian Diabetes Risk Score in adults screened for diabetes mellitus type-II. Med J DY Patil Univ [serial online] 2017 [cited 2019 Jun 16];10:263-7. Available from: http://www.mjdrdypu.org/text.asp?2017/10/3/263/206569


  Introduction Top


The worldwide prevalence of diabetes mellitus has risen dramatically over the past two decades, from estimated 30 million cases in 1985 to 177 million in 2000. Based on current trends, >366 million individuals will have diabetes by the year 2030.[1],[2] The prevalence of type 2 diabetes mellitus is rising much more rapidly because increasing obesity and reduced body activity levels as countries become more industrialized. This is true in most countries, and 6 of the top 10 countries with highest prevalence of diabetes are in Asia and India is the topmost in it.[2] Worldwide estimates project that in 2030 the greatest number of individuals with diabetes will be 45–64 years age group.[1]

In India, its population has increased susceptibility of diabetes mellitus. The prevalence of disease in adults was found to be 2.4% in rural and 4%–11.6% in urban dwellers. High frequencies of impaired glucose tolerance shown by some studies ranging from 3.6% to 9.1%, indicate the potential for further rise in the prevalence of diabetes in coming decade.[3],[4] Hence, in Indian set up where the majority of population is below poverty line, it is very essential for practicing physicians to suspect the adults for diabetes based on traditional peculiar classical symptoms rather than directly doing costly investigations for detecting diabetes. This study will try to elucidate the importance of polyuria, polydipsia, polyphagia (3 P's of diabetes), and Indian Diabetes Risk Score (IDRS) in the accuracy of diabetes detection.


  Subjects and Methods Top


It was a cross-sectional study. 677 number of adults (here age >25 years) who attended diabetes detection camp in 5 days conducted in Mumbai in November 2013 agreed to participate in the study were included in the study. All participant attendees were clinically examined in the morning session, and blood samples were taken in the afternoon session, i.e., 2 h following the afternoon meal. All enrolled adults in the present study were consented to participate. Ethical clearance from the Regional Medical College is sought.

Inclusion criteria

Inclusion criteria were all adults above 20 years of age.

Exclusion criteria

Exclusion criteria were already known diabetics and pregnant women.

With all aseptic precautions, participants were subjected for capillary blood examination for postprandial blood sugar testing; a blood sugar >200 mg/dl is considered diabetic using the American Diabetes Association Criteria, (ADA) 2011.[5] The Standardized Digital Glucometer (Accu-Check, Roche Diagnostics, Germany) was used on all 5 days and blood sugar estimated.

Risk assessment regarding diabetes was carried out before clinical examination by physicians using IDRS and asking common symptoms pertaining to diabetes and recorded. Components of IDRS are shown in [Table 1].[6]
Table 1: Indian Diabetes Risk Score

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Statistical analysis

Bivariate analysis was performed using Chi-square test. P< 0.05 was considered to be statistically significant. Standard epidemiological definitions of sensitivity, specificity, positive predictive value (PPV), negative predictive value, positive likelihood ratio (LR+), negative likelihood ratio (LR−) are used. The ratio of total diabetics detected by this study and nondiabetics was calculated for estimating the overall accuracy of the test. Statistical analysis was performed using SPSS version 20 (IBM Crop., Armonk, New York) and MedCalc version 15.8 software (MedCalc Soft. Comp., Ostend, Belgium).


  Results Top


A total 677 adults underwent postprandial blood glucose examination revealed that 109 had blood glucose level >200 mg/dl and were considered diabetic. Baseline characteristics and clinical symptoms of patients with hyperglycemia (>200 mg/dl) and without hyperglycemia (<200 mg/dl) are shown in [Table 2]. There is a statistically significant difference between different age groups and sex of patients regarding their hyperglycemic status. A standardized glucometer was used for blood sugar estimation, which though does not accurately estimate venous blood glucose; but many studies show well correlation (correlation coefficients >0.95) between venous blood glucose and capillary blood glucose, depicting glucometer findings can be used as a surrogate for venous blood glucose. Screened population was homogenous regarding diet, exercise, obesity pattern, type of work (sedentary and nonsedentary) with regards of their hyperglycemic status (P > 0.05). Out of total hypertensives, 34% were hyperglycemic, and only 15% of nonhypertensives were hyperglycemic, this difference was statistically significant (P < 0.001).
Table 2: Baseline characteristics of screened individuals

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[Table 3] shows that there is a statistically significant difference between individuals reporting classical symptoms of diabetes (polyuria, polydipsia, and polyphagia), and there hyperglycemic status (P < 0.0001), suggesting these three classical symptoms associated with diabetic/hyperglycemic status of the study subjects.
Table 3: Association between polyuria, polydipsia, polyphagia, and diabetes status

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[Table 4] shows the diagnostic evaluation of the polyuria, polydipsia, and polyphagia. Here, sensitivity of these symptoms in diagnosing diabetes was going on decreasing, i.e., 31.19% for polyuria, 21.10% for polydipsia, and 11.01% for polyphagia, but specificity of these symptoms was going on increasing, respectively. These 3 symptoms, when present in a patient then its specificity for diagnosing diabetes is 98.42%, and sensitivity is 7.34%, indicating the highest value of specificity when these symptoms present in an individual; in diagnosing diabetes. In other words, if an individual was truly suffering from diabetes, his/her chance of having all these three symptoms was 7.34%, and regarding specificity, those individuals who did not have all these three symptoms, 98.42% surety that they were not suffering from diabetes. Similarly, LR+ and LR− were going on increasing, respectively and was highest in the persons who have all these classical symptoms, indicating when all these three symptoms present in an individual, he/she was 4.63 times more likely of having diabetes (here postprandial glucose >200 mg/dl) than not having it. We got the prevalence of diabetes 16% (109/677), which is also called pretest probability. Pretest odds is same in each symptom (it is calculated by formula: number of diabetic patients/number of nondiabetic patients [109/568]). PPV was going on increasing in each symptom, respectively, and was maximum in patients whom have all three symptoms; indicating when all three symptoms are present in an individual, probability of suffering from diabetes is 47.06%. Same can be interpreted for negative predictive values. Accuracy was also going on increasing, and highest when the patient has three classical symptoms.
Table 4: Diagnostic accuracies of polyuria, polydipsia, polyphagia

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[Figure 1] depicts the receiver operative curve (ROC) curve of IDRS score which ranges from 0 to 100 and hyperglycemic status/diabetes status optimum cutoff point of IDRS was >50 (sensitivity is 73%, specificity is 58.4%); for screening purpose cutoff point was >40 (sensitivity is 86%, specificity is 38.4%). For this ROC, area under the curve (AUC) was 68.4% and was statistically significant (P < 0.001).
Figure 1: Receiver operative curve for Indian Diabetes Risk Score, dotted blue lines represent the upper and lower limits of 95% confidence limits of receiver operative curve line in the graph

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  Discussion Top


Current data on diagnostic accuracy of polyuria, polydipsia, and polyphagia in diabetes are limited.

In our study, there was male preponderance and age-wise increase in prevalence noted, which have been reported in previously in numerous studies.[7]

In this cross-sectional study, three classical symptoms of diabetes, i.e., polyuria, polydipsia, and polyphagia had a limited clinical diagnostic utility. None of these symptoms were able to accurately discriminate patients of having diabetes and not having it; even when patients having all these three symptoms did not show predictive values and sensitivity values 100%.

Among all these 677 patients, sensitivity of these signs was decreasing in order polyuria >polydipsia >polyphagia and much less in patients having all these signs, means only 7.34% of diabetic individuals shown three classical symptoms. False negative rate of these symptoms was high. However, specificity of these symptoms was increasing in order polyuria <polydipsia <polyphagia and highest in individuals who having all three classical symptoms. Hence, these symptoms carry highest true negatives rate.

All symptoms carry LR+ and LR− in increasing order from polyuria <polydipsia <polyphagia <all three symptoms. PPV or posttest probability was increasing and was higher when all three symptoms present. Negative predictive value was much higher than PPV of all three symptoms. Individuals who did not have any of three symptoms, there is 84.7% probability of not having diabetes to them; and in all individuals who had all three symptoms, 47.06% surety of having diabetes to them. However, in each symptom, posttest probability of diabetes was much more than pretest probability because LR+ is more than 1 in each symptom and was in increasing order.

In a study conducted by Mohan et al. in 2005 had shown sensitivity 72.5% and specificity 60.1% of IDRS for determining undiagnosed diabetes in a population for optimum score value >60.[4] Here, in our study, IDRS had sensitivity 73.00% and specificity 58.40% for optimum score value >50. The difference in getting less value of optimum point of score was mostly due to less sample size in our study. However, AUC in our study for the ROC curve for IDRS is 68% which was approximately similar to the study conducted by Mohan et al. which had 69% AUC.

Limitation

We used capillary blood glucose here for the study purpose. The World Health Organization and ADA Criteria for diabetes diagnosis are based on venous blood. Glucometer used here in our study measures whole blood glucose, so it gives somewhat higher blood glucose level.


  Conclusions Top


Although the results of this present study substantiate the general conclusions of three diagnostic clinical symptoms of diabetes that these symptoms can rule out diabetes when these symptoms not present in a patient, these symptoms also demonstrate that these diagnostic symptoms are too insensitive to identify the majority of patients with diabetes in contemporary practice. IDRS score >50 have optimum sensitivity and specificity in detecting diabetes.

In a country of scarce resources and unaffordability of tools for diabetes detection like India, with having high burden of diabetes; these simple diagnostic symptoms and IDRS tool is useful for screening of population for diabetes.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: Estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53.  Back to cited text no. 1
[PUBMED]    
2.
Bhalwar R. Textbook of Community Medicine. 1st ed. New Delhi: UIP Publications; 2013. p. 598-9.  Back to cited text no. 2
    
3.
World Health Organization. Prevention and Control of Diabetes Mellitus. Report of an Intercurrent Workshop, SEA/NCD/40. Dhaka, Bangladesh; 27-30 April, 1998.  Back to cited text no. 3
    
4.
Mohan V, Deepa M, Deepa R, Shanthirani CS, Farooq S, Ganesan A, et al. Secular trends in the prevalence of diabetes and impaired glucose tolerance in urban South India – The Chennai Urban Rural Epidemiology Study (CURES-17). Diabetologia 2006;49:1175-8.  Back to cited text no. 4
[PUBMED]    
5.
American Diabetes Association. Standards of medical care in diabetes-2011. Diabetes Care 2011;34 Suppl 1:S11-61.  Back to cited text no. 5
    
6.
Mohan V, Deepa R, Deepa M, Somannavar S, Datta M. A simplified Indian Diabetes Risk Score for screening for undiagnosed diabetic subjects. J Assoc Physicians India 2005;53:759-63.  Back to cited text no. 6
    
7.
Ramachandran A. Epidemiology of diabetes in India: Three decades of research. J Assoc Physicians India 2003;51:771-7.  Back to cited text no. 7
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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Introduction
Subjects and Methods
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