A clinical study on the application of diabetic neuropathy index for the diagnosis and staging of diabetic peripheral neuropathy

O Kwang-Chun; Ran-Hui Kang

doi:10.4103/mjmsr.mjmsr_8_19

ORIGINAL ARTICLE

Year : 2019 | Volume : 10 | Issue : 2 | Page : 43-46

A clinical study on the application of diabetic neuropathy index for the diagnosis and staging of diabetic peripheral neuropathy

O Kwang-Chun, Ran-Hui Kang
Department of Endocrinology and Metabolism, Pyongyang Medical College, KIM IL SUNG University, Pyongyang, DPR, Korea

Date of Web Publication

24-Jan-2020

Correspondence Address:
Dr. O Kwang-Chun
Ryonhwa-Dong, Central District, Pyongyang
Korea

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/mjmsr.mjmsr_8_19

Abstract

Context: There are many methods for the diagnosis and staging of diabetic peripheral neuropathy (DPN), but they are usually complicated and comparatively expensive. Aims: The aim of the study is to establish the new methods based on diabetic neuropathy index (DNI) for the diagnosis and staging of DPN and to demonstrate its scientific validity in terms of DPN. Settings and Design: We used the neuropathy symptom score and the neuropathy examination score as standard criteria in our study. The sensitivity and specificity of the diagnostic methods using DNI were compared with standard criteria. Subjects and Methods: The DNI questionnaire asked about the medical history of diabetes, symptoms, peripheral neuropathy-related symptoms, characteristics of neuropathy, and findings associated with differential diseases. These parameters were assessed at positive or negative. We also evaluated some parameters associated with neurological examination, electromyography, and diabetic complications. Statistical Analysis Used: t-test was used to compare the characteristics between different treatments, and the receiver operating characteristic (ROC) curve was used to set the cutoff points. Results: The significant parameters for DPN diagnosis were DPN symptoms, tuning fork, Achilles reflex, tactile sensation, duration of diabetes, and reduced visual power. The area under the curve of DNI at ROC was 0.999, which means ROC was significant statistically. The best cutoff point to diagnose DPN was 4 in case of using DNI. Conclusions: Our study suggests that the DNI method is a relatively easier and cost-effective approach in terms of DPN diagnosis and staging because it has high sensitivity and specificity.

Keywords: Diabetic neuropathy index, diabetic peripheral neuropathy, diagnosis, staging

How to cite this article:
Kwang-Chun O, Kang RH. A clinical study on the application of diabetic neuropathy index for the diagnosis and staging of diabetic peripheral neuropathy. Muller J Med Sci Res 2019;10:43-6

How to cite this URL:
Kwang-Chun O, Kang RH. A clinical study on the application of diabetic neuropathy index for the diagnosis and staging of diabetic peripheral neuropathy. Muller J Med Sci Res [serial online] 2019 [cited 2023 May 30];10:43-6. Available from: https://www.mjmsr.net/text.asp?2019/10/2/43/276694

Introduction

Multiple criteria and recommendations have been made for the diagnosis and staging of diabetic peripheral neuropathy (DPN), but no consensus has emerged.^{[1],[2],[3],[4],[5],[6],[7],[8]}

Current various methods to screen and diagnose DPN are complicated and not cost-effective. Although the diagnosis and staging of DPN are very important, the easier and cost-effective diagnostic and staging tools on DPN have not been sufficiently investigated.^[9],[10]

Therefore, the purposes of our study are to establish the new methods based on the diabetic neuropathy index (DNI) for the diagnosis and staging of DPN and to demonstrate its scientific validity in terms of DPN.

Subjects and Methods

Individuals with diabetes mellitus (n = 150) and relatively healthy people (n = 40) were recruited at the Hospital of the Pyongyang Medical College KIM IL SUNG University. Those individuals were suffered from neuropathy. This study was approved by the local ethical committee of our hospital. Neuropathy was determined as previously. Among the patients with diabetes, 65 cases were male, and the mean age was 54.6 ± 4.4 years.

The questionnaire asked about the medical history of diabetes (duration and type of diabetes), symptoms (polydipsia, polyuria, polyphagia, weakness, weight loss, and complication-related symptoms including reduced visual power, facial edema, and elevated blood pressure), peripheral neuropathy-related symptoms (numbness, abnormal sensation, pain, and convulsion), characteristics of neuropathy (onset, durability pattern, and intensity), and findings associated with differential diseases. These parameters were assessed at positive or negative.

The neurological examination includes tactile sensitivity, vibration sense, and deep tendon reflex.

Moreover, we also evaluated motor nerve conduction velocity and H-wave interval in the tibial nerve by electromyography and assessed other diabetic complications including eye disorders, nephropathy, foot disease, and hypertension.

We used neuropathy symptom score (NSS) and neuropathy examination score (NES) as standard criteria in our study. The receiver operating characteristic (ROC) curve was used to set the cutoff points. The sensitivity and specificity of the diagnostic methods using DNI were compared with standard criteria.

P< 0.05 was considered statistically significant. All data processing and statistical analyses were performed with SPSS Statistics 11.0 (SPSS Inc., Chicago, IL, USA) software.

Results

Determination of significant parameters for the diagnosis of diabetic peripheral neuropathy

As shown in [Table 1], significant parameters according to DPN presence status were the duration of diabetes, reduced visual power, DPN symptoms (foot numbness, abnormal sensation, calf convulsion, and hand numbness), tuning fork, tactile sensation, and patellar reflex.

Table 1: Comparison of significances of parameters associated with symptoms and neurological examinations according to the diabetic peripheral neuropathy presence status (n=50)

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There were significant differences between the abnormal appearance rates of neurological examination parameters according to the DPN presence status [Table 2] and [Figure 1].

Table 2: Abnormal appearance rates of neurological examination parameters (percentage) (n=50)

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Figure 1: Abnormal appearance rates of neurological examination parameters according to the diabetic peripheral neuropathy status

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According to [Table 1] and [Table 2], the significant parameters for DPN diagnosis were DPN symptoms, tuning fork, Achilles reflex, tactile sensation, duration of diabetes, and reduced visual power.

Determination of cutoff points of diabetic neuropathy index for the diagnosis and staging and evaluation of the validity of the diabetic neuropathy index method

Determination of cutoff points of diabetic neuropathy index in terms of significant parameters

We assessed the DNI and set the cutoff points of DNI using ROC with SPSS 11.0 software.

According to [Table 3], the area under the curve of DNI at ROC was 0.999. It means ROC was significant statistically.

Table 3: Area under the curve of diabetic neuropathy index at receiver operating characteristic

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Sensitivity and specificity of diabetic neuropathy index cutoff points in the diabetic peripheral neuropathy diagnosis

As shown in [Table 4], the best cutoff point to diagnose DPN was 4 in case of using DNI. According to that, we made a DPN staging by using DNI. In this case, DNI of healthy people was 0–4, DNI of Stage 1 DPN was 5–8, DNI of Stage 2 DPN was 9–12, and DNI of Stage 3 DPN was 13–15.

Table 4: Comparison of diabetic peripheral neuropathy diagnostic tools according to the evaluation methods of neuropathy

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Association between the diabetic neuropathy index staging and neuropathy symptom score and neuropathy examination score severity methods

As shown in [Table 5] and [Table 6], the correspondence rate of DNI and NSS was 50.0% and the correspondence rate of DNI and NES was 56.0%.

Table 5: Association between the diabetic neuropathy index staging and neuropathy symptom score (n=100)

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Table 6: Association between the diabetic neuropathy index staging and neuropathy examination score (n=100)

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Evaluation of validity of diabetic neuropathy index method

As shown in [Table 7], there were significant differences of complication-related parameters between the different DPN stages when we classified the DPN stages using the DNI method.

Table 7: Comparison of some complication.related parameters according to the diabetic neuropathy index stages (n=100)

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Discussion

DPN is a frequent complication of diabetes, and multiple criteria and recommendations have been made about the screening and diagnosis, but no consensus has emerged.^[4],[5],[6]

According to the definition of DPN for a person with diabetes to be defined as having the DPN, they must have more than two traits among the neuropathic bilateral symptoms, loss or deficit of ankle reflex, and abnormal vibration sense. It may be a gold standard criterion in terms of DPN.^[7]

Current clinical modalities for screening include monofilament and vibratory and ankle reflex testing.^[1],[9],[11]

Both the indicator test and the vibration perception threshold are sensitive for neuropathy, but one study has found that the indicator test would be a good additional diagnostic tool for detecting neuropathy.^[12]

There are many methods to diagnose and classify the stages of DPN including the Leeds Assessment of Neuropathic Symptoms and Signs, Neuropathic Pain Questionnaire, NSS, NES, and Michigan Neuropathy Screening Instrument, but they are complicated and not cost-effective. Furthermore, there is no unified method to diagnose DPN means that DPN differs a lot from method to method.^{[13],[14],[15],[16]}

This is the first report that demonstrates the easier and cost-effective diagnostic and staging method for DPN that is using DNI in our country. According to our results, the significant parameters for DPN diagnosis were DPN symptoms, tuning fork, Achilles reflex, tactile sensation, duration of diabetes, and reduced visual power, and the best cutoff point to diagnose DPN was 4 in case of using DNI. When it comes to DPN staging using DNI, DNI of healthy people was 0–4, DNI of Stage 1 DPN was 5–8, DNI of Stage 2 DPN was 9–12, and DNI of Stage 3 DPN was 13–15. During the application of DNI method, there were significant differences of complication-related parameters between the different DPN stages.

Conclusion

The overall conclusion is that the DNI method is very useful to make a diagnosis and staging classification of DPN. In addition, the DNI method is very simple and cost-effective. Moreover, we think that our results analyzed in terms of sensitivity and specificity, highlight the relative advantages of DNI compared with other methods.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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