Prevalence of peripheral neuropathy in patients with diabetes: A systematic review and meta-analysis

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PCD-854; No. of Pages 10

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Primary Care Diabetes journal homepage: http://www.elsevier.com/locate/pcd

Original research

Prevalence of peripheral neuropathy in patients with diabetes: A systematic review and meta-analysis Juan Sun a , Ya Wang b , Xiaoyi Zhang c , Shengze Zhu a , Hong He d,∗ a

School of Medicine, Nantong University, No.19 Qixiu Road, Chongchuan District, Nantong, Jiangsu Province, China Affiliated Hospital of Nantong University, No. 20, Xisi Road, Chongchuan District, Nantong, Jiangsu Province, China Department of Endocrinology, Affiliated Hospital of Nantong University, No. 20, Xisi Road, Chongchuan District, Nantong, Jiangsu Province, China d Department of Nursing, Affiliated Hospital of Nantong University, No. 20, Xisi Road, Chongchuan District, Nantong, Jiangsu Province, 226001, China b c

a r t i c l e

i n f o

Article history: Received 28 June 2019 Received in revised form 10 December 2019 Accepted 25 December 2019 Available online xxx Keywords: Diabetes mellitus Diabetic peripheral neuropathy Prevalence Meta-analysis

a b s t r a c t Aims: We aimed to determine pooled prevalence of diabetic peripheral neuropathy (DPN) in patients with diabetes and to explore the impacts of research variables on prevalence estimates. Methods: A systematic search was performed in PubMed, EMBASE, The Cochrane Library and Scopus from onset up to July 2018 to identify articles investigating the prevalence of DPN. Random-effects models were used to calculate the pooled prevalence of DPN. The heterogeneity of the study was estimated with the I2 statistic. The publication bias was described by Egger’s test and funnel plot. Results: A total of 29 studies with a total of 50,112 participants were included in this meta-analysis. The results showed that the pooled prevalence of DPN was 30% (95% confidence interval, CI 25–34%). The pooled prevalence of DPN among patients with type 2 diabetes mellitus was higher than patients with type 1 diabetes mellitus (31.5%, 95% CI 24.4–38.6% vs 17.5%, 95% CI 4.8–30.2%). The pooled prevalence of DPN of studies involving a mixed type of diabetes mellitus was 24.8% (95% CI 13.1–36.5%, I2 = 99.1%). Conclusions: Medical staff should strengthen the evaluation and diagnosis of DPN. Moreover, they need to teach diabetic patients how to prevent this complication. © 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

1. Introduction Diabetes mellitus (DM) is an important public health issues worldwide. As the incidence of diabetes increases, the incidence of complications is expected to increase accordingly [1]. DPN is one of the most common complications of DM and it is caused by persistent high glucose levels. This problem is an important cause of disability and poor quality of life in diabetic patients [2]. It is also associated with an increased incidence of foot ulcers [3]. It has been reported that amputation in people with DPN is 10–20 times more common than the group without diabetes. Every 30 s, somewhere in the world, the lower limbs or part of the lower limbs are amputated due to this problem [4]. Furthermore, DPN patients will consume more medical resources and spend more medical expenses. Present epidemiological data show that the prevalence of DPN in patients with diabetes ranges widely from 16% to as high as 66%

Abbreviations: DPN, diabetic peripheral neuropathy; CI, confidence interval. ∗ Corresponding author. E-mail address: [email protected] (H. He).

in different studies [4]. Many factors contribute to this huge difference, including study quality, study design, ethnic differences, and different diagnosis methods. In order to enhance awareness of prevention and management of DPN in patients with diabetes, a reliable estimates of DPN prevalence is required. To our knowledge, in 2014, related researchers had conducted a systematic review and meta-analysis of the prevalence of DPN. This study showed that the overall prevalence of DPN was as high as 53% in Iran [5]. In addition, few systematic review or meta-analysis has been found that quantified the prevalence of DPN in diabetic patients in the last five years of research. The present study, therefore, set out to establish pooled prevalence levels of DPN in patients with diabetes, and to explore the impacts of research variables on prevalence estimates.

2. Methods We registered the protocol of this review in PROSPERO (International prospective register of systematic reviews; http://www. crd.york.ac.uk/prospero/) under the following registration number: CRD42018108002.

https://doi.org/10.1016/j.pcd.2019.12.005 1751-9918/© 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

Please cite this article in press as: J. Sun, et al., Prevalence of peripheral neuropathy in patients with diabetes: A systematic review and meta-analysis, Prim. Care Diab. (2019), https://doi.org/10.1016/j.pcd.2019.12.005

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Fig. 1. Flowchart of literature research DPN, diabetic peripheral neuropathy.

2.1. Search strategy

2.4. Quality assessment

We searched electronic databases (PubMed, EMBASE, The Cochrane Library and Scopus) for studies published up to July 31, 2018, using terms “diabetes,” “diabetes mellitus,” “Peripheral Nervous System Disease*,” “Peripheral Neuropath*,” “Peripheral Nerve Disease*,” and “Peripheral Nervous System Disorders”(Appendix A). To avoiding missing any relevant studies, we also screened the reference lists of eligible studies.

We evaluated the quality of included studies using the modified version of the Newcastle–Ottawa Scale [6] which comprises of the following domains: sample representativeness and size, comparability between respondents and non - respondents, assessment of DPN and statistical quality. The total score ranges from 0 to 5, ≥3 points indicates low risk of bias, and <3 points indicates high risk of bias. 2.5. Statistical analysis

2.2. Eligibility criteria The inclusion criteria were as follows: (a) cross-sectional design, baseline cross-section data from longitudinal studies or trials before random allocation; (b) detected DPN by careful neurological examination or electrophysiology; (c) participants were type 1 diabetes mellitus or type 2 diabetes mellitus. Studies not meeting these criteria, review articles, case reports, commentaries, letters to the editor, articles not published in English, and studies of participants without diabetes or were pregnant were excluded.

2.3. Data extraction Two independent investigators (W Y and Z XY) screened and extracted data from all included studies. Any discrepancies between them were resolved by consensus. The extracted data included the name of first author, year of publication, region, study design, study type, sample size, DPN events, number of males, mean age, DM duration years, number of participants with type 1 diabetes or type 2 diabetes, reported prevalence of DPN and diagnosis methods. When this data was not available, we contacted the corresponding author to obtain information missing in the published research report.

To evaluate the pooled effect, a 95% confidence interval (CI) was considered, and statistical significance was set at a P < 0.05. Random-effects models were used to pool studies reporting the prevalence of DPN in patients with diabetes. Heterogeneity was estimated by the I2 statistic. We carried out subgroup analysis of types of diabetes, age groups, diabetes duration, diagnostic tools, and region to detect potential sources of heterogeneity among the studies. Meta-regression was used to determine the effect of types of diabetes, age groups, diabetes duration, diagnostic tools, and region on the prevalence estimates. The Funnel plots and Egger’s test were combined to explore the potential publication bias. Sensitivity analysis was performed to assess the robustness of the results by consecutively excluding each study. All statistical analysis were executed using the meta-analysis software Stata version 12.0 (StataCorp, College Station, TX, USA). 3. Results We retrieved 1153 studies using our search strategy after removing duplicates papers. After reading the title and abstract, 1048 studies were removed and 105 articles were retained for full text eligibility assessment. Finally, 29 studies met the search criteria and were included in the systematic review. The details are presented in Fig. 1 according to the PRISMA guidelines [7]. Among

Please cite this article in press as: J. Sun, et al., Prevalence of peripheral neuropathy in patients with diabetes: A systematic review and meta-analysis, Prim. Care Diab. (2019), https://doi.org/10.1016/j.pcd.2019.12.005

Region

Study type

Study design

Sample size

DPN

Male (%)

Age (mean ± SD)

No. T1DM/T2DM

DM duration Prevalence of KDM/NDDM years(mean ± SD/interquartile DPN (%) range

Methods for detecting DPN

MNOS

Pai YW 2018 [8]

Taiwan

Hospital based

Cross sectional

2837

604

1641 (57.8)

63.9 ± 13.0

0/2837

10.1 ± 8.4

KDM and NDDM

21.3

3

A Tahrani AA 2017 [9] B Tahrani AA 2017 Kisozi T 2017 [10] A Jaiswal M 2017 [11] B Jaiswal M 2017 A Gogia S 2017 [12] B Gogia S 2017 LiL 2015 [13]

UK

Hospital based Hospital based Hospital based Population based Population based Hospital based Hospital based Hospital based Facility based

126

48

76 (60.3)

54.9 ± 12.5

0/126

12.05 ± 8.25

KDM

38.1

140

76

79 (56.4)

59.2 ± 10.8

0/140

10.5 ± 8.24

KDM

54.3

MNSI assessment

3

248

73

154 (62)

48.5 ± 13.4

NS

NS

NDDM

29.4

NSS, NDS

3

1734

114

872 (50)

18 ± 4

1734/0

7.2 ± 1.2

KDM

7

MNSI assessment

4

258

56

83 (32)

22 ± 3.5

0/258

7.9 ± 2

KDM

22

MNSI assessment

4

273

113

202 (75)

57.8 ± 11.5

0/273

8.3 ± 6.7

KDM

41.4

DNS instrument

3

273

67

202 (75)

57.8 ± 11.5

0/273

8.3 ± 6.7

KDM

24.5

DNE instrument

3

3359

1113

1607 (47.8)

58.8 ± 13

0/3359

NS

KDM

33.1

4

208

67

99 (47.6)

57.6 ± 12.2

0/208

9.8 ± 2.8

KDM

32.2

Medical history and careful examination MNSI assessment

3

Hospital based Hospital based

Cross sectional Cross sectional Cross sectional Longitudinal studies Longitudinal studies Cross sectional Cross sectional Cross sectional Cross sectional Cross sectional Cross sectional

MNSI, neurological examination, vibration perception by a trained health professional MNSI assessment

264

69

87 (33)

59 ± 6.8

0/264

7.3 ± 2.7

KDM

24.1

MNSI assessment

4

552

110

346 (62.7)

53.4 ± 10.5

28/524

NS

KDM

19.9

4

Registry based Registry based

Cross sectional Cross sectional

377

130

181 (44.8)

NS

0/404

8.3

KDM

34.5

Vibration perception, neurological symptoms MNSI assessment

13043

1296

6761 (51.8)

63.8 ± 12.8

0/13043

NS

KDM

9.9

UK Mulago USA

India India China

3

D’Souza M 2015 [14] Adeniyi AF 2015 [15] Wang DD 2014 [16]

India

Lee CM 2014 [17] Brownrigg JRW 2014 [18]

Taiwan

Bansal D 2014 [19]

India

Hospital based

Cross sectional

2006

586

989 (49.3)

NS

0/1637

NS

KDM and NDDM

29.2

Lu B 2013 [20] A Jaiswal M 2013 [21] B Jaiswal M 2013

Shanghai

Community based Population based Population based

Cross sectional Longitudinal studies Longitudinal studies

534

45

230 (43.1)

64.0 ± 9.9

0/534

NS

8.4

329

27

161 (49)

15.7 ± 4.3

329/0

6.2 ± 0.9

KDM and NDDM KDM

10 g monofilament peripheral sensation assessment by primary care physicians, practice nurses and podiatrists Combination of more than one abnormal result of 10-g monofilament, pinprick sensations and ankle reflexes, and categorized according to the severity level using VPT NSS, NDS

8.2

MNSI assessment

4

70

18

28 (40)

21.6 ± 4.1

0/70

7.6 ± 1.8

KDM

25.7

MNSI assessment

4

Ibadan Arabia

England

USA USA

3 4

3

3

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USA

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Study ID

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Table 1 Baseline characteristics of included studies.

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Region

Study type

Study design

Sample size

DPN

Male (%)

Age (mean ± SD)

No. T1DM/T2DM

DM duration Prevalence of KDM/NDDM years(mean ± SD/interquartile DPN (%) range

Methods for detecting DPN

MNOS

Won JC 2012 [22]

Korea

Hospital based

Cross sectional

3999

1338

1939 (48.5)

59 ± 10

0/3999

9.6 ± 7.6

KDM

33.5

4

AKatulanda P 2012 [23] BKatulanda P 2012 Azura MS 2012 [24]

Sri Lanka

National based National based Hospital based

Cross sectional Cross sectional Cross sectional

337

199

125 (37.1)

56.8 ± 11.2

NS

NS

KDM

59.1

Review of medical records, MNSI score and monofilament test DNS assessment

191

55

72 (37.7)

51.4 ± 13.5

NS

NS

NDDM

28.8

DNS assessment

5

254

22

NS

53.3 ± 9.06

0/254

NS

NDDM

8.7

3

Sri Lanka

5

Kärvestedt L 2011 [25]

Sweden

Population based

Cross sectional

156

106

95 (61)

61.7 ± 7.2

0/156

7.0 ± 5.7

NS

67

Erbas T 2011 [26] Mørkrid K 2010 [27] Liu F 2010 [28]

Turkey

Hospital based Hospital based Hospital based

Cross sectional Cross sectional Cross sectional

1113

450

599 (53.8)

52.1 ± 9.6

91/1022

8.28 ± 6.6.

NS

40.4

The monofilament 5.07(10 g) to one or more sites tested At least one of the types of neuropathy recorded (PAN, PMN, PSN). Clinical examination

294

58

139 (47.3)

50.8 ± 10.6

0/294

7.0 ± 1.8

KDM

19.7

NSS,NDS

3

1193

203

594 (49.8)

59.17 ± 11.82

0/1193

6.45 ± 6.3

KDM and NDDM

17.02

4

PopBusui R 2009 [29] Wu EQ 2007 [30] Janghorbani M 2006 [31]

USA

Hospital based Community based Hospital based

Longitudinal studies Cross sectional Cross sectional

2314

1173

1632 (71)

62.4 ± 8.9

0/2314

10.4 ± 8.7

NS

51

10 g Semmes Weinstein monofilament and 128-Hz tuning fork MNSI assessment

4

1023

105

450 (44)

68 ± 15

256/726

15 ± 12

NS

11

MNSI assessment

5

810

608

289 (35.7)

52.7 ± 9.9

0/810

8.2 ± 6.8

NS

75.1

Assessment of neurological function including neuropathic symptoms and physical signs and nerve conduction velocity

4

Malaysia

Bangladesh China

France Iran

4

4

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Table 1 (Continued)

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Region

Study type

Study design

Sample size

DPN

Male (%)

Age (mean ± SD)

No. T1DM/T2DM

DM duration Prevalence of KDM/NDDM years(mean ± SD/interquartile DPN (%) range

Methods for detecting DPN

MNOS

A Eppens MC 2006 [32]

Sydney

Hospital based

Longitudinal studies

1376

375

574 (47.1)

15.52 ± 2.30

1433/0

7.05 ± 3.64

NS

27

4

B Eppens MC 2006

Sydney

Hospital based

Longitudinal studies

24

5

34 (50)

15.09 ± 2.21

0/68

1.69 ± 1.97

NS

21

Delcourt C 1998 [33]

France

Hospital based

Longitudinal studies

427

135

227 (53.2)

56.9 ± 9.2

0/427

10.6 ± 7.4

KDM

31.6

Tesfaye S 1996 [34]

Europe

Hospital based

Cross sectional

3250

910

1668 (51.3)

32.7 ± 10.2

3250/0

14.7 ± 9.3

NS

28

Flynn MD 1995 [35]

Bristol

Hospital based

Longitudinal studies

506

119

294 (58.1)

43 ± 18

NS

15 ± 10

NS

23.5

Young MJ 1993 [36]

UK

Hospital based

Cross sectional

6487

1849

3498 (53.9)

59

2414/3949

8

NS

28.5

Thermal threshold test and vibration threshold Thermal threshold test and vibration threshold VPT was greater than the 95th percentile of its distribution in normal subjects either at the mall toe or at the great toe. Neuropathic symptoms,Neurological examination, VPT assessment, Autonomic function assessment A vibration threshold >95th centile for age combined with absent/impaired ankle reflexes NSS,NDS

4

4

5

3

4

T1DM, Type 1 diabetes mellitus T2DM, Type 2diabetes mellitus MNSO, Modified version of the Newcastle–Ottawa Scale SD, Standard deviation; DM, Diabetes mellitus; DPN, Diabetic peripheral neuropathy; KDM, Known diabetes mellitus; NDDM, Newly detected diabetes mellitus; MNOS, Modified version of the Newcastle–Ottawa Scale; MNSI, Michigan Neuropathy Screening Instrument; NDS, Neuropathy disability score; NSS, Neuropathy Symptom Score; DNS, Diabetic Neuropathy Symptom; DNE, Diabetic Neuropathy Examination; SWF, Semmes-Weinstein monofilament test; TCSS, Toronto Clinical Scoring System; NS, Not state; PAN, Peripheral autonomic neuropathy; PMN, Peripheral motor neuropathy; PSN, Peripheral sensory neuropathy.

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Table 1 (Continued)

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Fig. 2. The forest plot of the included studies.

the included studies, 3 [11,21,32] studies measured the prevalence of DPN in different types of diabetes, one [12] study estimated the prevalence using different diagnostic methods, one [9] study estimated the prevalence in different ethnic groups, and one [23] study estimated the prevalence of DPN in the newly detected diabetes mellitus (NDDM) and known diabetes mellitus(KDM). Finally, we considered each of the above mentioned studies as two, which meant that 35 studies were included in the final data analysis.

3.2. Pooled prevalence of DPN in people with diabetes

3.1. Study characteristics

Table 2 shows results of subgroup analysis. Studies were stratifies based on types of diabetes, publication years, country, age groups, DM duration, and methods for detecting DPN. The results showed that patients with type 2 diabetes (31.5%, 95% CI 24.4–38.6%) tended to produce higher estimates of DPN prevalence than type 1 diabetes (17.5%, 95% CI 4.8–30.2%) and a mixed type diabetes (24.8%, 95% CI 13.1–36.5%). The subgroup analysis for country of origin also showed that Europeans tended to yield higher DPN prevalence than Asians (31.8%, 95%CI 23.5–40.2% vs 30.9%, 95%CI 24.0–37.9%). Meanwhile, the longer the duration of diabetes, the higher the prevalence of DPN. The prevalence varied from 20.8% (95% CI 4.6–37.1%) to 32.0% (95%CI 22.0–41.9%). The studies applied MNSI reported higher prevalence of DPN (27.8%, 95% CI 18.9–36.6), while the studies with NSS, NDS tended to have the lower DPN estimates (21.5%, 95%CI 9.6–33.3). The age of patients also had

Table 1 presents the characteristics of the included studies. Studies were published between 1993–2018. The total sample size of these studies was 50,112 cases. The maximum sample size was 13,043 cases and the minimum sample size was 24 cases. 17 [8,12–14,16,17,19,20,22–24,26–28] studies took place in Asia, 9 [9,18,25,30,33–36] in Europe, 2 [10,15] in Africa, 2 [32] in Oceania and 5 [11,21,29] in North America. Appendix B shows the risk of bias assessment of studies included in this review. When evaluated by the modified Newcastle–Ottawa quality assessment criteria, out of 5 possible points, 4 [23,30,34] studies received 5 points, 18 [11,13,15,18,21,22,25,26,28,29,31–33,36] studies received 4 points, and 13 [8–10,12,14,17,19,20,24,27,35] studies received 3 points.

Results combined using random effects model showed the pooled prevalence of DPN in people with diabetes was 30% (95% [CI] 25–34%). Significant heterogeneity was identified among studies (p = 0.000, I2 = 99%). The results are presented in Fig. 2. 3.3. Subgroup analysis and meta-regression

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Table 2 The impact of study characteristics on the prevalence of peripheral neuropathy in diabetic patients: Subgroup analysis. Heterogeneity Subgroup analysis DM types T1DM T2DM Mixed Not clear Region Europe Asia Africa Oceania North America Diagnosis method MNSI NSS,NDS VPT 10 g monofilament peripheral sensation assessment Not clear DM duration years Mean ≤ 5 5 < Mean ≤ 10 Mean > 10 Not clear Age years Mean ≤ 30 31 ≤ Mean ≤ 45 46 ≤ Mean ≤ 60 Mean > 60 Not clear

n

Prevalence (95% CI), %

Q

I2

p-Value

4 23 4 4

17.5 (4.8–30.2) 31.5 (24.4–38.6) 24.8 (13.1–36.5) 35.2 (18.8–51.6)

595.90 4805.38 399.19 123.00

99.5 99.5 99.2 97.6

0.000 0.000 0.000 0.000

9 17 2 2 5

31.8 (23.5–40.2) 30.9 (24.0–37.9) 27.7 (23.8–31.5) 27.1 (24.8–29.4) 22.6 (0.9–44.2)

1642.57 1883.42 0.69 0.59 1397.38

99.5 99.2 0.0 0.0 99.7

0.016 0.021 0.000 0.000 0.060

13 4 6 4

27.8 (18.9–36.6) 21.5 (9.6–33.3) 25.9 (22.8–29.0) 46.3 (33.0–59.5)

2006.92 236.50 26.92 368.06

99.4 98.7 81.4 99.2

0.000 0.000 0.000 0.000

8

29.5 (24.6–34.4)

743.15

99.1

0.000

1 17 8 9

20.8 (4.6–37.1) 31.1 (23.2–39.1) 32.0 (22.0–41.9) 25.0 (15.9–34.2)

0.00 2689.35 942.55 1389.97

– 99.4 99.3 99.4

– 0.000 0.000 0.000

6 2 19 6 2

18.0 (8.4–27.5) 26.1 (21.7–30.4) 33.7 (27.7–39.6) 27.7 (15.4–40.1) 31.4 (24.6–36.5)

268.78 4.81 1474.65 1807.20 3.95

98.1 79.2 98.8 99.7 74.7

0.000 0.028 0.000 0.000 0.047

DM, Diabetes mellitus; T1DM, Type 1 diabetes mellitus; T2DM, Type 2 diabetes mellitus; DPN, Diabetic peripheral neuropathy; MNSI, Michigan Neuropathy Screening Instrument; NDS, Neuropathy disability score; NSS, Neuropathy Symptom Score; VPT, Vibration perception threshold.

impact on the prevalence. Before the age of 60, the prevalence of DPN increased from 18.0% (95% CI 8.4–27.5%) to 33.7% (95% CI 27.7–39.6%). After the age of 60, the prevalence dropped to 27.7% (95% CI 15.4–40.1%). According to the univariable meta-regression (Table 3), different diagnosis methods were statistically significant determinants of prevalence, while other factors in the table were not. After adjusting for the impact of other covariates on prevalence, DPN estimates derived from unclear methods were significantly higher than estimates from other tools in the table (odds ratio[OR] 1.28, 95% CI 1.08–1.52). 3.4. Publication bias and sensitivity analysis The funnel plot and Egger’s tests show a potential publication bias in this meta-analysis. The results are presented in Fig. 4 and Appendix C. Sensitivity analysis were carried out by excluding each study one by one and recalculating the combined prevalence on the remaining studies. The result showed the pooled prevalence of any DPN in people with diabetes varied from 28.1% (95% CI 23.7–32.5) to 30.2% (95% CI 25.2–35.2). It showed no abnormalities (Fig. 3). 4. Discussion Diabetes is one of the most common chronic diseases. As one of the complications, DPN seriously affects the quality of life of diabetics patients. The present systematic review and meta-analysis provides a comprehensive estimation of the prevalence of DPN. A total of 29 studies with a total of 50,112 participants meets the inclusion criteria. The overall prevalence of DPN is 30% (95% CI 25–34%). Different studies vary in methods to diagnose DPN. It is well known that MNSI is the most commonly used tool for assessing

DPN in diabetic patients. Related studies have shown that the tool has a sensitivity of 80% and a specificity of 95% [37]. Two parts make up the MNSI: the first part is a historical questionnaire to assess the presence of neuropathic symptoms; the second is the physical examination conducted by the medical staff. However, the main disadvantage of this method is that it is time consuming and requires special equipment. NDS and NSS are also common methods for diagnosing DPN. Previous studies reported that the NDS had a sensitivity of 65% and a specificity of 91% and the NSS had a sensitivity of 87% and a specificity of 60% [10]. Nevertheless, some studies have pointed out that both methods lack of a rigorous assessment of small nerve fiber damage [20]. The nerve conduction studies (NCS) is considered as an objective, sensitive, quantitative, non-invasive means of inspection. Nerve conduction velocity (NCV) is the most important test item in NCS. Studies have shown that in diabetic patients with symptoms and/or signs of neuropathy, DPN can be diagnosed if NCS is abnormal at the same time [38]. Related researchers have pointed out that NCS can identify the distribution of damaged nerves and identify whether the lesion is single or multiple, symmetrical, distal or proximal, motor or sensory nerve damage [39]. NCS can be used as an early and reliable indicator of DPN. However, it has some limitations. First, NSC is expensive and time consuming. It requires specialist testing. Second, it primarily assesses the function of large, myelinated nerve fibers that are insensitive to damage to small nerves and demyelinated nerve fibers. Clinically, it will cause missed diagnosis. Subgroup analysis revealed some interesting findings. We found that the prevalence of DPN among patients with type 2 diabetes tended to be higher than patients with type 1 diabetes. In studies of mixed type of diabetes, some of them [11,21] also showed that participants with type 2 diabetes were more likely to develop DPN. This phenomenon might have something to do with the older age and

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Table 3 Odds ratios for diabetic peripheral neuropathy in terms of type of diabetes, country, diagnosis method, diabetes duration, and age years from univariable meta-regression models. Variable Type of diabetes Mixed T1DM T2DM Not stated Region Oceania Europe Asia Africa North America Diagnosis method NSS,NDS MNSI VPT 10 g monofilament peripheral sensation assessment Not clear DM duration years Mean ≤ 5 5 < Mean ≤ 10 Mean > 10 Not clear Age years 31 ≤ Mean ≤ 45 Mean ≤ 30 46 ≤ Mean ≤ 60 Mean > 60 Not clear

Number of studies

OR (95% CI)

Z value

p-Value

4 4 23 4

Reference 0.93 (0.74–1.17) 1.07 (0.89–1.28) 1.11 (0.88–1.40)

Reference −0.63 0.77 0.90

Reference 0.531 0.449 0.373

2 9 17 2 5

Reference 1.08 (0.81–1.43) 1.07 (0.81–1.40) 1.03 (0.72–1.48) 0.98 (0.73–1.33)

Reference 0.56 0.50 0.19 −0.13

Reference 0.580 0.624 0.847 0.901

4 13 6 4

Reference 0.95 (0.78–1.16) 1.06 (0.91–1.25) 1.04 (0.87–1.25)

Reference −0.54 0.79 0.43

Reference 0.594 0.438 0.667

8

1.28 (1.08–1.52)

2.92

<0.05*

1 17 8 9

Reference 1.11 (0.75–1.64) 1.12 (0.75–1.67) 1.04 (0.70–1.55)

Reference 0.54 0.57 0.22

Reference 0.593 0.571 0.828

2 6 19 6 2

Reference 0.93 (0.71–1.22) 1.08 (0.85–1.39) 1.02 (0.78–1.34) 1.06 (0.76–1.48)

Reference −0.57 0.66 0.15 0.37

Reference 0.573 0.517 0.881 0.713

DM, Diabetes mellitus; T1DM, Type 1 diabetes mellitus; T2DM, Type 2 diabetes mellitus; DPN, Diabetic peripheral neuropathy; MNSI, Michigan Neuropathy Screening Instrument; NDS, Neuropathy disability score; NSS, Neuropathy Symptom Score; VPT, Vibration perception threshold. * p < 0.05.

Fig. 3. Sensitivity analyses through consecutively excluding each study.

metabolic syndrome in patients with type 2 diabetes. Meanwhile, the difference in cardiovascular risk profiles [11] was also one of the reasons. However, some studies failed to reach such a conclusion. The difference might be attributed to a significant imbalance in the number of participants with different types of diabetes. Typ-

ically, the total sample of one study was 1400 patients, but only 24 patients had type 2 diabetes, and the rest of the sample were all patients with type 1 diabetes [32]. In addition, the result of subgroup analysis by country showed that Europeans tended to have a higher prevalence of DPN than Asians. This inconsistency might

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DPN is one of the three major risk factors for the occurrence of falls in patients with diabetes, along with vestibular dysfunction and diabetic retinopathy [40]. Currently, because of the diverse clinical manifestations of DPN, there is currently no unified diagnostic method in clinical practice. Each method has its own advantages and limitations. In the clinic, doctors are required to conduct detailed consultation and physical examination first, and follow the principle of individualization to select the most suitable examination method for each patient. If possible, comprehensive judgment should be made in combination with different diagnostic methods. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Conflict of interest The authors state that they have no conflict of interest. Acknowledgements Thanks to Nan Deng for her help in literature searching help provided in this study. Thanks to Dr Baoguo Zhang for modifying the syntax of the meta-analysis. Appendix A. Supplementary data Fig. 4. Funnel plot of the meta-analysis SE, standard error.

be due to the social and cultural factors. This study also showed that as the duration of diabetes increased, the number of patients gradually increased. At the same time, the prevalence of DPN was also found to peak between 46 and 60 years of age. After the age of 60, the prevalence decreased. This phenomenon might be related to increased mortality in elderly patients with diabetes. Compared to NSS, NDS, studies using MNSI tended to report higher prevalence of DPN possibly due to the higher sensitivity and specificity of this method. Our study had several strengths. We explored the impact of research variables on prevalence estimates. The results showed different region, types of diabetes, disease duration, patients age, and diagnosis method had an important impact on the prevalence estimates. Furthermore, all studies included in the meta-analysis were studies of medium quality or higher. We excluded the studies with a quality assessment of less than 3 points, so the conclusion of the study had some reliability. The present study also had several limitations. First, the search was limited to articles published in English. There might be omissions in document retrieval and inclusion because of the limits of language and retrieval. Second, the heterogeneity between studies was still high after subgroup analysis. This was also the main difficulty encountered in our research. Due to large differences in diagnostic methods, we could not accurately classify it in subgroup analysis. Additionally, unexamined factors, such as gender, medication might also be source of heterogeneity, but due to incomplete data, we were unable to analyze these factors. Third, the Egger test showed there was a potential publication bias. Many factors mi contribute to this bias. First, the heterogeneity and language restrictions mentioned above were one of the important reasons. Second, the asymmetry of the funnel plot did not mean that there must be publication bias. Some other reasons, such as the illusion, opportunity etc might also cause asymmetry of the funnel plot.

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.pcd.2019.12. 005. References [1] G. Danaei, M.M. Finucane, L. Yuan, et al., National, regional, and global trends in fasting plasma and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 countryyears and 2·7 million participant, Lancet 378 (2011) 31–40, http://dx.doi.org/ 10.1016/s0140-6736(11)60679-x. [2] A. Vinik, Neuropathies in children and adolescents with diabetes: the tip of the iceberg, Pediatr. Diabetes 7 (2010) 301–304, http://dx.doi.org/10.1111/j.13995448.2006.00213.x. [3] C.C. Lee, B.A. Perkins, S. Kayaniyil, et al., Peripheral neuropathy and nerve dysfunction in individuals at high risk for type 2 diabetes: the PROMISE cohort, Diabetes Care 38 (2015) 793–800, http://dx.doi.org/10.2337/dc14-2585. [4] International Diabetes Federation, IDF Diabetes Atlas, 8th ed., 2018 [Accessed 21 December 2018]. http://www.diabetesatlas.org/. [5] S. Sobhani, H. Asayesh, F. Sharifi, et al., Prevalence of diabetic peripheral neuropathy in Iran: a systematic review and meta-analysis, J Diabetes Metab. Disord. Control 13 (2014) 97, http://dx.doi.org/10.1186/s40200-014-0097-y. [6] N. Deng, X. Zhang, F. Zhao, et al., Prevalence of lipohypertrophy in insulintreated diabetes patients: a systematic review and meta-analysis, J. Diabetes Investig. 9 (3) (2017), http://dx.doi.org/10.1111/jdi.12742. [7] N. Panic, E. Leoncini, G.D. Belvis, et al., Evaluation of the endorsement of the preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement on the quality of published systematic review and meta-analyses, PLoS One 8 (2013), e83138, http://dx.doi.org/10.1371/journal.pone.0083138. [8] Y.W. Pai, C.H. Lin, I.T. Lee, M.H. Chang, Prevalence and biochemical risk factors of diabetic peripheral neuropathy with or without neuropathic pain in Taiwanese adults with type 2 diabetes mellitus, Diabetes Metab. Syndr. Clin. Res. Rev. 12 (2018) 111–116, http://dx.doi.org/10.1016/j.dsx.2017.09.013. [9] A.A. Tahrani, Q.A. Altaf, M.K. Piya, et al., Peripheral and autonomic neuropathy in South Asians and White Caucasians with type 2 diabetes mellitus: possible explanations for epidemiological differences, J. Diabetes Res. 2017 (2017) 1–10, http://dx.doi.org/10.1155/2017/1273789. [10] T. Kisozi, E. Mutebi, M. Kisekka, et al., Prevalence, severity and factors associated with peripheral neuropathy among newly diagnosed patients with diabetes attending mulago hospital: a cross-sectional study, Afr. Health Sci. 17 (2017) 463–473, http://dx.doi.org/10.4314/ahs.v17i2.21. [11] M. Jaiswal, J. Divers, D. Dabelea, et al., Prevalence of and risk factors for diabetic peripheralneuropathy in youth with type 1 and type 2 diabetes: search for diabetes in youth study, Diabetes Care 40 (2017) 1226–1232, http://dx.doi.org/ 10.2337/dc17-0179.

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G Model PCD-854; No. of Pages 10 10

ARTICLE IN PRESS J. Sun et al. / Primary Care Diabetes xxx (2019) xxx–xxx

[12] S. Gogia, C. Rao, Prevalence and risk factors for peripheral neuropathy among type 2 diabetes mellitus patients at a tertiary care hospital in coastal Karnataka, Indian J. Endocrinol. Metab. 21 (2017) 665–669, http://dx.doi.org/10. 4103/ijem.IJEM 43 17. [13] L. Li, J. Chen, J. Wang, D. Cai, Prevalence and risk factors of diabetic peripheral neuropathy in Type 2 diabetes mellitus patients with overweight/obese in Guangdong province, China, Prim. Care Diabetes 9 (2015) 191–195, http://dx. doi.org/10.1016/j.pcd.2014.07.006. [14] M. D’Souza, V. Kulkarni, U. Bhaskaran, et al., Diabetic peripheral neuropathy and its determinants among patients attending a tertiary health care centre in Mangalore, India, J. Public Health Res. 4 (2015) 120–124, http://dx.doi.org/10. 4081/jphr.2015.450. [15] A.F. Adeniyi, O.S. Aiyegbusi, O.O. Ogwumike, et al., Habitual physical activity, peripheral neuropathy, foot deformities and lower limb function: characterising prevalence and interlinks in patients with type 2 diabetes mellitus, J. Endocrinol. Metab. Diabetes South Afr. 20 (2015) 48–54, http://dx.doi.org/10. 1080/16089677.2015.1056482. [16] D.D. Wang, B.A. Bakhotmah, F.B. Hu, et al., Prevalence and correlates of diabetic peripheral neuropathy in a Saudi Arabic population: a cross-sectional study, PLoS One 9 (2014), e106935, http://dx.doi.org/10.1371/journal.pone.0106935. [17] C.M. Lee, C.C. Chang, M.Y. Pan, et al., Insufficient early detection of peripheral neurovasculopathy and associated factors in rural diabetes residents of Taiwan: a cross-sectional study, BMC Endocr. Disord. 14 (2014) 89, http://dx.doi.org/10. 1186/1472-6823-14-89. [18] J.R. Brownrigg, S. de Lusignan, A. McGovern, et al., Peripheral neuropathy and the risk of cardiovascular events in type 2 diabetes mellitus, Heart 100 (2014) 1837–1843, http://dx.doi.org/10.1136/heartjnl-2014-305657. [19] D. Bansal, K. Gudala, H. Muthyala, et al., Prevalence and risk factors of development of peripheral diabetic neuropathy in type 2 diabetes mellitus in a tertiary care setting, J. Diabetes Investig. 5 (2014) 714–721, http://dx.doi.org/10.1111/ jdi.12223. [20] B. Lu, J. Hu, J. Wen, et al., Determination of peripheral neuropathy prevalence and associated factors in Chinese subjects with diabetes and pre-diabetes — ShangHai diabetic neuropathy epidemiology and molecular genetics study (SHDREAMS), PLoS One 8 (2013), e61053-, http://dx.doi.org/10.1371/journal.pone. 0061053. [21] M. Jaiswal, A. Lauer, C.L. Martin, et al., Peripheral neuropathy in adolescents and young adults with type 1 and type 2 diabetes from the SEARCH for Diabetes in Youth follow-up cohort: a pilot study, Diabetes Care 36 (2013) 3903–3908, http://dx.doi.org/10.2337/dc13-1213. [22] J.C. Won, H.S. Kwon, C.H. Kim, et al., Prevalence and clinical characteristics of diabetic peripheral neuropathy in hospital patients with type 2 diabetes in Korea, Diabet. Med. 29 (9) (2012), http://dx.doi.org/10.1111/j.1464-5491.2012. 03697. [23] P. Katulanda, P. Ranasinghe, R. Jayawardena, et al., The prevalence, patterns and predictors of diabetic peripheral neuropathy in a developing country, Diabetol. Metab. Syndr. 4 (2012) 21, http://dx.doi.org/10.1186/1758-5996-4-21. [24] M.S. Azura, H.I. Adibah, S. Juwita, Risk factor of peripheral neuropathy among newly diagnosed type 2 patients with diabetes in primary care clinic, Int. J. Collab. Res. Intern. Med. Public Health 4 (2012) 1858–1867. [25] L. Kärvestedt, E. Mårtensson, V. Grill, et al., The prevalence of peripheral neuropathy in a population-based study of patients with type 2 diabetes in Sweden, J. Diabetes Complicat. 25 (2011) 97–106, http://dx.doi.org/10.1016/j.jdiacomp. 2010.04.001. [26] T. Erbas, M. Ertas, A. Yucel, M. Senocak, et al., Prevalence of peripheral neuropathy and painful peripheral neuropathy in Turkish patients with

[27]

[28]

[29]

[30]

[31]

[32]

[33]

[34]

[35]

[36]

[37]

[38]

[39]

[40]

diabetes, J. Clin. Neurophysiol. 28 (2011) 51–55, http://dx.doi.org/10.1097/ wnp.0b013e3182051334. K. Mørkrid, L. Ali, A. Hussain, Risk factors and prevalence of diabetic peripheral neuropathy: a study of type 2 diabetic outpatients in Bangladesh, Int. J. Diabetes Dev. 30 (2010) 11–17, http://dx.doi.org/10.4103/0973-3930.60004. F. Liu, Y. Bao, R. Hu, et al., Screening and prevalence of peripheral neuropathy in type 2 diabetic outpatients: a randomized multicentre survey in 12 city hospitals of China, Diabetes Metab. Res. Rev. 26 (2010) 481–489, http://dx.doi.org/ 10.1002/dmrr.1107. R. Pop-Busui, J. Lu, N. Lopes, et al., Prevalence of diabetic peripheral neuropathy and relation to glycemic control therapies at baseline in the BARI 2D cohort, J. Peripher. Nerv. Syst. 14 (2009) 1–13, http://dx.doi.org/10.1111/j.1529-8027. 2009.00200.x. E.Q. Wu, J. Borton, G. Said, et al., Estimated prevalence of peripheral neuropathy and associated pain in adults with diabetes in France, Curr. Med. Res. Opin. 23 (2007) 2035–2042, http://dx.doi.org/10.1185/030079907X210516. M. Janghorbani, H. Rezvanian, A. Kachooei, et al., Peripheral neuropathy in type 2 diabetes mellitus in Isfahan, Iran: prevalence and risk factors, Acta Neurol. Scand. 114 (2006) 384–391, http://dx.doi.org/10.1111/j.1600-0404.2006. 00716.x. M.C. Eppens, M.E. Craig, J. Cusumano, et al., Prevalence of diabetes complications in adolescents with type 2 compared with type 1 diabetes, Diabetes Care 29 (2006) 1300–1306, http://dx.doi.org/10.2337/dc05-2470. C. Delcourt, F. Vauzelle-Kervroedan, G. Cathelineau, et al., Low prevalence of long-term complications in non-insulin-dependent diabetes mellitus in France: a multicenter study. CODIAB-INSERM-ZENECA Pharma Study Group, J Diabetes Complicat. 12 (1998) 88–95, http://dx.doi.org/10.1016/s10568727(97)98005-3. S. Tesfaye, L.K. Stevens, J.M. Stephenson, et al., Prevalence of diabetic peripheral neuropathy and its relation to glycaemic control and potential risk factors: the EURODIAB IDDM Complications Study, Diabetologia 39 (1996) 1377–1384, http://dx.doi.org/10.1007/s001250050586. M.D. Flynn, I.A. O’Brien, R.J.M. Corrall, The prevalence of autonomic and peripheral neuropathy in insulin-treated diabetic subjects, Diabet. Med. 12 (1995) 310–313, http://dx.doi.org/10.1111/j.1464-5491.1995.tb00483.x. M.J. Young, A.J. Boulton, A.F. MacLeod, et al., A multicentre study of the prevalence of diabetic peripheral neuropathy in the United Kingdom hospital clinic population, Diabetologia 36 (1993) 150–154, http://dx.doi.org/10.1007/ BF00400697. W.H. Herman, R. Pop-Busui, B.H. Braffett, et al., Use of the Michigan Neuropathy Screening Instrument as a measure of distal symmetrical peripheral neuropathy in Type 1 diabetes: results from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications, Diabet. Med. 29 (2012) 937–944, http://dx.doi.org/10.1111/j.1464-5491.2012.03644.x. S. Tesfaye, A.J. Boulton, P.J. Dyck, et al., Diabetic neuropathies: update on definitions, diagnostic criteria, estimation of severity, and treatments, Diabetes Care 33 (2010) 2285–2293, http://dx.doi.org/10.2337/dc10-1303. K. Wooten, Clinical features and electrodiagnosis of diabetic peripheral neuropathy in the dysvascular patient, Phys. Med. Rehabil. Clin. N. Am. 20 (2009) 657–676, http://dx.doi.org/10.1016/j.pmr.2009.06.011. Y. Agrawal, J.P. Carey, C.C. Della Santina, et al., Diabetes, vestibular dysfunction, and falls: analyses from the National Health and Nutrition Examination Survey, Otol. Neurotol. 31 (2010) 1445–1450, http://dx.doi.org/10.1097/MAO. 0b013e3181f2f035.

Please cite this article in press as: J. Sun, et al., Prevalence of peripheral neuropathy in patients with diabetes: A systematic review and meta-analysis, Prim. Care Diab. (2019), https://doi.org/10.1016/j.pcd.2019.12.005