|META-ANALYSIS AND SYSTEMATIC REVIEW
|Year : 2018 | Volume
| Issue : 3 | Page : 85-94
Point prevalence of painful diabetic neuropathy in the Middle East and North Africa region: A systematic review with meta-analysis
Sabri Garoushi1, Mark I Johnson2, Osama A Tashani3
1 Centre for Pain Research; MENA Research Group, School of Clinical and Applied Sciences, Leeds Beckett University, Leeds, UK; Faculty of Medicine, University of Benghazi, Benghazi, Libya, United Kingdom
2 Centre for Pain Research; MENA Research Group, School of Clinical and Applied Sciences, Leeds Beckett University, Leeds, UK
3 Centre for Pain Research; MENA Research Group, School of Clinical and Applied Sciences, Leeds Beckett University, Leeds, UK; Faculty of Medicine, University of Benghazi, Benghazi, Libya
|Date of Web Publication||4-Oct-2018|
Dr. Sabri Garoushi
School of Clinical and Applied Sciences, Portland Way, Leeds Beckett University, Leeds
Source of Support: None, Conflict of Interest: None
Background/Aim: Painful diabetic neuropathy (PDN) is a common complication of diabetes. Over recent decades, there has been a rise in the prevalence of diabetes in the Middle East and North Africa (MENA) region. It is suspected that this will be accompanied by an increase in PDN. Epidemiological research on PDN is needed to inform health policy in the MENA region. The aim of this systematic review was to estimate the point prevalence of PDN in countries from the MENA region. Methods: Cross-sectional or longitudinal studies that reported the prevalence of adults with PDN in the MENA region were sought by searching three computerized databases (Medline via web of science, PubMed, and Science Direct). Titles and abstracts were reviewed and screened independently by two researchers (SG and OT). Data extracted were as follows: age, sex, body mass index, sample size, type and duration of diabetes, and point prevalence of PDN. PDN point prevalence was calculated as event rate (i.e., proportion out of 1) and used to produce the overall prevalence in the region using comprehensive meta-analysis software. Results: The searches identified 1657 records. The full texts of 16 records were retrieved following removal of 600 duplicates and exclusions of 1045 abstracts. Five studies were eligible for review following screening of full-text reports. Four of the five reports described surveys of PDN conducted in one country: Saudi Arabia (1 report), Turkey (2 reports), and Algeria (1 report). One report described surveys conducted in Egypt, Lebanon, Jordan, and the Gulf States. The Douleur Neuropathique 4 (DN4) questionnaire was used in seven of the surveys and the Leeds Assessment of Neuropathic Symptoms and Signs pain scale in one survey. The prevalence of PDN was 65.3% for Saudi Arabia, 14% and 23% for Turkey, and 45% for Algeria. The prevalence of PDN was 53.7% in a study that combined estimates from Egypt, Lebanon, Jordan, and Gulf States. Overall, the prevalence of PDN in people with diabetes was 43.2% (95% confidence interval = 30.1%–57.2%, 8 surveys, 7898 participants, 3761 women). Conclusions: The prevalence of PDN in people with diabetes from the MENA region was 43.2% (7898 participants) and higher than estimates from other regions of the world such as the United Kingdom (22%–35%) and the United States of America (11%–25%).
Keywords: Diabetes, douleur neuropathique 4, Middle East and North Africa, Middle East, Neuropathic pain, North Africa, painful diabetic neuropathy, prevalence, S-Leeds Assessment of Neuropathic Symptoms and Signs
|How to cite this article:|
Garoushi S, Johnson MI, Tashani OA. Point prevalence of painful diabetic neuropathy in the Middle East and North Africa region: A systematic review with meta-analysis. Libyan J Med Sci 2018;2:85-94
|How to cite this URL:|
Garoushi S, Johnson MI, Tashani OA. Point prevalence of painful diabetic neuropathy in the Middle East and North Africa region: A systematic review with meta-analysis. Libyan J Med Sci [serial online] 2018 [cited 2022 Jan 23];2:85-94. Available from: https://www.ljmsonline.com/text.asp?2018/2/3/85/242732
| Introduction|| |
Neuropathic pain is defined by the International Association for the Study of Pain as “pain that arises as a direct consequence of a lesion or diseases affecting the somatosensory system.” Neuropathic pain is one of the major complications of many diseases such as diabetes, AIDS, and cancer. However, the pathophysiology and the exact mechanism of neuropathic pain are still not very clear. In people with diabetes, the most common pain with neuropathic characteristics is known as painful diabetic neuropathy (PDN). This is a very common complication of diabetes and can affect up to a third of patients. Epidemiological studies suggested that PDN is the most prevalent pain condition with neuropathic characteristics. The typical presentation of PDN is symmetrical “stocking and gloves” distribution and is often associated with nocturnal exacerbation. There can be cutaneous hypersensitivity leading to acute distress on contact with an external stimulus (allodynia) which is defined as pain that is caused by a stimulus that does not normally cause pain. The pain can be worse at night and disturbs sleep, causing tiredness during the day, distressing allodynia, and severe pain in the legs has also been reported. This may be so painful that it prevents patients from performing their daily activities, thereby impacting their employment and social life. The constant, unremitting pain, and withdrawal from social life often result in depression. In extreme cases, patients lose their appetite and experience significant weight loss leading to a distinctive condition called “diabetic neuropathic cachexia” and was first recognized by and reported as a case study recently by.
PDN treatment is challenging and like other neuropathic pain entities, is not responsive to the treatment regimens routinely used to treat the pain of nociceptive or inflammatory nature. Indeed, one of the characteristics of PDN is that it does not respond to common pain management protocols. For example, nonsteroidal anti-inflammatory drugs (NSAIDs) are seldom effective in the relief of PDN. Unsurprisingly, there is a continuous revision of the guidelines of PDN treatment.,,
With the epidemic of diabetes in the Middle East and North Africa (MENA), it is suggested that neuropathic pain will be on the increase and urgent intervention is warranted. Indeed, epidemiological and basic research about neuropathic pain is needed at this stage in the developing countries to inform health policy and health education to improve the quality of life of diabetic patients. Over 38 million people (about 11% of the population) have diabetes in the MENA region, and these figures are expected to be more than doubled by 2040. This leads to the fact that MENA region countries have got the highest rates of diabetes prevalence in the world. Above 40.6% are underdiagnosed and are at higher risk of developing harmful and costly complications. In 2017, about £15.45 billion GBP ($20.5 billion USD) was spent in treating diabetes, this is around 15% of the total health budget in the region.
The diagnosis and treatment of PDN in the MENA region are inadequate. There has been a single effort to estimate the prevalence of PDN in the Middle East and not in the MENA region, and still only four countries in the Middle East were involved in the study (Jambart et al., 2011), which estimated the point prevalence of PDN in a large cross-sectional study in Egypt, Jordan, Lebanon, and Gulf states. The study used the Douleur Neuropathique-4 (DN4) neuropathic assessment tool on 3989 type 1 and type 2 diabetic patients and found that 2144 patients (53.7%, 95% confidence interval [CI] 52.2–55.3) had a score of equal to or more than 4 on the DN4 tool; a criteria suggestive of a strong probability of the existence of PDN. The highest percentage was in Egypt (61.3%, 95% CI 58–65). Furthermore, some studies tried to assess the prevalence of PDN in individual countries in the MENA region such as Saudi Arabia (65.3% 95% CI 62.4–68.2) and Turkey (23% 95% CI 20.8–25.2).
The aim of this systematic review is to review the relevant cross-sectional studies that attempted to estimate the prevalence of PDN in countries from the MENA region. The main specific question that this systematic review should answer is: What is the point prevalence of PDN in the MENA region? This will be the primary outcome of this systematic review. The secondary outcomes will be the risk factors of PDN in the MENA region.
| Methods|| |
Criteria to consider studies
The studies eligible to be included in this systematic review have to be; cross-sectional studies, surveys and government reports of the prevalence of PDN in diabetic patients in the MENA region countries. Longitudinal studies of diabetic patients which contain data on PDN are also included if it is possible to estimate the point prevalence reported. Reviews, case studies, and discussion articles were excluded from the study. Duplicates and irrelevant titles are removed before screening against the following eligibility criteria: (1) Published materials including; peer-reviewed journals articles, conference proceedings, and theses with a focus on PDN in a region or country from the MENA region. (2) Government reports are considered if they are published, and (3) The aim of studies should be to evaluate the prevalence, risk factors, complications, medications, and treatment.
The following computerized databases were searched on November 17, 2017 and updated on April 4, 2018 for studies published between 1950 and 2017: (1) Web of science, (2) PubMed, (3) Science Direct, and (4) Google was used to search for publications written in the Arabic language. Keywords used were as follows: combinations of keywords, and MeSH terms when appropriate, were used to locate the studies: (neuropathic pain, pain, diabetic neuropathy, PDN, peripheral PDN, and PDN) and (Diabet*, MENA, Middle East, North Africa, MENA, Algeria, Bahrain, Djibouti, Egypt, Iran, Israel, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, West Bank and Gaza and Yemen). MENA countries were selected following the World Bank classification. Titles and abstracts were reviewed and screened by two researchers independently (SG and OT). This was done following the AMSTAR (A Measurement Tool to Assess Systematic Reviews) recommendation to have more than one reviewer to screen hits to reduce bias and improve the quality of the research. Disagreement between the two reviewers was sorted through a discussion about the potential articles, and a final consensus was reached. When there is still a disagreement a third reviewer (MJ) acted as an arbiter. Full articles or reports were retrieved when the abstract suggests that the study fits the decided inclusion criteria. The guidelines followed to choose and check observational studies were: meta-analysis of observational studies in epidemiology and preferred reporting items for systematic reviews and meta-analysis.
Assessment of the quality of the studies
For a study to be included, it should be appraised through applying criteria developed for epidemiological research by The Joanna Briggs Institute (JBI) and reported in the JBI Reviewer Manual. These criteria are also used to qualitatively comment on the quality of the study and to check if they meet the robust methodological approach recommended for cross-sectional surveys. The checklist questions used in the assessment are: how representative is the sample for the target population, method of recruitment, adequacy of the sample size, description of the participants, appropriate and robust data analysis, appropriateness and reliability of the condition's measurement tool, accounting for confounding factors, and identification of subpopulation within the sample. Attached to this checklist is a prevalence critical appraisal tool to follow to help answer each question. The studies were assessed by SG and approved by OT.
Quantitative synthesis of data
The following data were extracted from the studies and surveys on PDN in different countries in the MENA region and summarized in tabular form by SG and cross-checked by OT: (1) Age, sex, and body mass index (BMI) of participants in the surveys, (2) Type of screening tool used, 3) Sample size, (4) Type and duration of diabetes, and (5) Point prevalence of PDN as reported (usually as a percentage of the whole sample).
Calculating the summary effect size
PDN point prevalence from each study or survey included was then calculated in this systematic review as an event rate (i.e., proportion out of 1). Then, data were pooled to produce the overall point prevalence in the region using comprehensive meta-analysis software. This overall prevalence will be calculated as the summary effect size. There are two models to calculate the summary effect: fixed-effect analysis or random-effect analysis.
In the fixed-effect analysis, the assumption is that all studies have the same true effect size, and the summary effect is the estimate of this common effect size. Whereas, in the random-effect analysis, we assume that the true effect size is different between the studies and that the studies in the analysis represent a random sample of effect sizes. The summary effect in the random effect model is the estimate of the mean of a distribution of effects. To pool data from the relevant studies, the assumption was that because of the differences between the populations, the random effect model is more appropriate.
Identifying the heterogeneity is important to identify to what extent the study results are consistent with the meta-analysis even if the random effect model was used. The degree of heterogeneity was categorized by the I2 statistic. I2 of <40% represents a low level of heterogeneity, above 40% and to 70% is of moderate heterogeneity, above 70% is of the high level of heterogeneity.
Publication bias was assessed using a funnel plot. A funnel plot (Begg's funnel plot) is a scatterplot of treatment effect against a measure of the study precision. It is used as a model to visually detect publication bias or systematic heterogeneity. A symmetric inverted funnel figure arises from a data set, in which publication bias is unlikely. Whereas, if there is asymmetry in either side, then publication bias may be present.
| Results|| |
The initial search identified 1651 reports, and an additional six reports were identified manually [Figure 1]. After removing duplicates and scrutinizing the titles of articles, 18 articles were deemed potentially relevant for full-text retrieval. After retrieval of all 18 articles, all were published in English apart from two articles, one was published in French and another one in Spanish. Screening of full-text reports resulted in 13 exclusions. Only five articles were suitable for inclusion in this systematic review.
|Figure 1: PRISMA flow chart for the process of identifying eligible studies|
Click here to view
Excluded studies [Table 1]
Thirteen full-text articles were excluded with reasons. One study was a short bibliographic review written in Spanish with an English Abstract. This report and another article which was also excluded because it was a systematic review of the epidemiology of PDN worldwide contained no data on cross-sectional surveys on the MENA regions., Two different nationwide telephone surveys were led in Morocco and Kuwait to identify the prevalence of chronic pain with neuropathic characteristics in the general population. Harifi et al. (2013) used the Arabic version of the DN4-interview questionnaire and surveyed 5328 participants from the Moroccan general population. They concluded that PDN prevalence is nearly 47% in diabetic patients. Zaghoul et al. (2017) also used the DN4-interview questionnaire in Kuwait and surveyed 759 participants from the general population. The figure of PDN in the sample was found as 32.2%. Both studies were not considered for the systematic review as they did not fit the inclusion criteria for the review, as the primary reason for the studies was to measure chronic pain with neuropathic elements and not the prevalence of PDN. In these two studies, the categorization of PDN was not appropriate as it included any chronic pain that has neuropathic characteristics in diabetic participants in the sample study.
Kiani et al. (2010) conducted a study about the prevalence and associated risk factors of peripheral diabetic neuropathy in Hamedan, Iran. They conducted a cross-sectional study on 600 diabetic patients. This study's focus was on the associated risk factors of peripheral diabetic neuropathy, and surprisingly, there were no data collected about the pain. Another study in Iran was on the prevalence of diabetic neuropathy and related factors. This cross-sectional study on 124 diabetic patients in Tehran did not contain data on pain in this small sample size, and therefore, it was excluded.
Akbar et al. conducted a study titled “subclinical diabetic neuropathy, a common complication in Saudi diabetics,” There was no mention of PDN in this study, although there was one mention in the discussion section that neuropathic damage contributes significantly to morbid foot problems and unhappiness in diabetes, without further elaboration on this.
Shehab et al.'s study was conducted in Kuwait, questioning the role of Vitamin D deficiency in developing peripheral neuropathy in type 2 diabetes. They concluded that Vitamin D is an independent risk factor for peripheral diabetic neuropathy, but no data about PDN were published.
Liberman et al. performed a cross-sectional study in a primary care setting to identify the prevalence of chronic pain in type 2 diabetic patients in Israel. They used the S-Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale in their study to identify if the participant may or may not have neuropathic pain, and deducted that almost 50% of type 2 diabetic patients may have pain that is neuropathic in origin. This study was not included as there has been no further exclusion to other conditions which may mimic the PDN. In fact, more than two-thirds of PDN patients have at least one or two comorbid pain conditions causing pain symptoms such as osteoarthritis (34%), nociceptive lower back pain (27%), and lower back pain with neuropathic involvement (13%). All of the previous indicates that contamination of the results in this study is likely.
Algeffari carried out the latest study in the region in Saudi Arabia. He conducted a multicenter cross-sectional study in a primary healthcare center and evaluated 242 type 2 diabetes patients for the presence or absence of PDN, and predicted prevalence of 35%. However, he carried that out by using the Michigan Neuropathy Screening Instrument (MNSI), which is not used to screen for PDN but rather used to screen for peripheral neuropathy. There was no clear explanation in Algeffari's article about the justification for the use of the MNSI to diagnose PDN. The last update regarding the use of screening tools to diagnose neuropathic pain and the PDN did not mention the MNSI as one of the recommended tools to use. On inspection of this tool, it was clear that it is a measure to assess and evaluate the distal symmetrical peripheral neuropathy in diabetes rather than the pain. For this reason, this article was not considered for the systematic review.
Three other studies were conducted in the MENA region about the PDN, but each of these studies was excluded due to a different reason. Hoffman et al.'s study was a cross-national burden of painful diabetic peripheral neuropathy in Asia, Latin America, and the Middle East. They researched the human burden of the PDN by quantifying functional and health status impairments, including, mental health, sleep, mobility, self-care, and usual activities. The data from three different regions were collected and compared to data from the United States of America (USA) and United Kingdom (UK). They concluded that the PDN has a substantial burden on diabetic patients and the data are similar from the ones collected in the USA and UK. However, there is no epidemiological data about the prevalence of PDN in the regions. Another discussion paper published by Petropoulos et al. (2016) focused on the need to allow more efforts and resources to tackle the PDN in the MENA region. They recognized the key articles for a study conducted about peripheral neuropathy in the MENA region and identified the studies conducted about the PDN. They identified the lack of awareness among both health practitioners and patients regarding the PDN and prompted the researchers to perform more research in the region to capture a better understanding of the condition and to educate both health practitioners and patients about the condition and how common it is. They have also suggested to follow the recommendations of Bohlega et al., to treat PDN in the MENA region that was adopted from the IASP guidelines. This study by Petropoulos et al. (2016) is not valid in the systematic review as it is a discussion paper. Finally, Aizarani et al. attempted to provide primary guidelines for PDN for the MENA. They have outlined the fact that the condition is still understudied in the region and also the knowledge of the health professionals is not yet mature about it. They also recommended to implement an annual screening to identify PDN using screening tools such as the DN4. The study was not included in the systematic review because it was a discussion paper.
Characteristics of included studies
Four of the five included studies were reports of surveys in the MENA countries which are published in peer review journals (one in Saudi Arabia, one in Algeria, and two in Turkey). The other study contained presentations and analysis of a survey that was conducted in three countries and an area within the MENA region (Egypt, Lebanon, Jordan, and the Gulf States). The survey in the Gulf States was a report on data from a sample from both Kuwait and the United Arab Emirates without any reporting to disentangle data from these two countries, and for this purpose, the Gulf States was considered as a single country for simplification.
Halawa et al (2010). conducted the earliest study in the region in Saudi Arabia. They conducted an epidemiological survey involved 100 outpatient diabetes mellitus clinics across Saudi Arabia, and a total of 1039 participants signed up. The enrolment period was between October 2006 and March 2007, and the inclusion criteria were, age ≥18, diabetic ≥5 years. They mentioned that they excluded patients with mental health disorders or any other disorder that might affect the reliability of their response to the study questionnaire. They used the DN4 in their study to screen for the PDN. The aim of their study was to determine the prevalence of PDN and to determine the demographic profile and pharmaceutical management of these patients. They concluded that 65.3% (n = 678, 95% CI: 62.4–68.2) of the participants have PDN and identified the increase in age, male gender, and increased the duration of diabetes as significant factors to develop PDN. Smoking history, obesity and racial difference found not to be significant risk factors to develop PDN. About two-thirds of the studied participants who likely have PDN were found to be taking medication to control the pain. Pregabalin was the most frequently prescribed medication (62.3%), followed by Vitamin B complex (22.9%), Gabapentin (8%), and Diclofenac (2%). Some patients received a mixture of the previous medications.
Jambart et al. (2011) carried out a single-visit epidemiological investigation in 400 private-practice clinics in four different countries across the Middle East (Egypt, Lebanon, Jordan, and the Gulf States). They recruited a total of 4097 participants (Egypt (830), Lebanon (1394), Jordan (1223), and Gulf States (650), between January and December 2009. They included the participants if these criteria were met; aged ≥18 years, duration of diabetes (Type 1 ≥5 years) (Type 2, any duration), no current psychiatric illness and no other type of neuropathic pain of nondiabetic origin (radiculopathy, postherpetic neuralgia, cancer-related pain, spinal cord injury pain, multiple sclerosis pain, carpal tunnel syndrome pain, trigeminal neuralgia, and fibromyalgia or phantom limb). The screening tool that was used was the Arabic DN4. The study aimed to identify the prevalence of the PDN in the Middle East and to describe the demographic characteristics of the participants. They admitted that the DN4 information from 108 participants was missing. The overall prevalence of PDN was (53.7%, 95% CI 52.2–55.3), with the highest proportion from Egypt (61.3%, 95% CI 55.9–64.7) and the lowest proportion from the Gulf States (37.1%, 95% CI 33.4–40.8). Jordan and Lebanon had a prevalence of (57.5%, 95% CI 54.7–60.2) and (53.9%, 95% CI 51.3–56.5) consecutively. They calculated the multivariate regression analysis (odds ratio [OR]) in the whole sample to identify the significant demographic and clinical variables associated with developing PDN. They recognized the duration of diabetes ≥10 years to be the most significant predictor of PDN (OR 2.43). Other important predictors are age ≥65 years (OR 2.13), age 50–64 years (OR 1.75), type 1 diabetes (OR 1.59), BMI≥30 kg/m2 (OR 1.35), and female gender (OR 1.27). They identified race and smoking status to be insignificant. Overall, 68.8% of patients with PDN were found to be taking medications for pain control. The most frequently used medication was NSAIDs (31.6%), followed by Pregabalin (19.2%) and Gabapentin (7.7%).
Erbas et al. (2011) performed a multicenter cross-sectional study in diabetic patients attending university outpatient clinics in Turkey. They recruited a total of 1113 patients (diabetes type 1 and 2) from 14 centers. The aim of their study was to determine the prevalence of diabetic peripheral neuropathy and to identify the prevalence of PDN from this sample. There was no mention of the details of the recruitment process including the inclusion/exclusion criteria. To measure the diabetic peripheral neuropathy, they used the clinical diabetic neuropathy score that was supported by electromyography and nerve conduction studies, and to diagnose the PDN the LANSS pain scale was the tool of choice. They identified the prevalence of the diabetic peripheral neuropathy as 40.4% by clinical examination alone, and this increased to 62.2% when combining nerve conduction studies with clinical examination whereas, the prevalence of the PDN was 14% (95% CI 12–16). When applying the logistic regression model, the increase in age (OR = 1.03) and the duration of diabetes (OR = 1.07) identified the significant independent factors to develop PDN. There were no figures mentioned in the study regarding pain treatments.
Aouiche et al. (2014) carried out in their study in Algeria on 400 people with diabetes to identify the prevalence of the PDN. They used the original French DN4, and they also published their study in French. The study was conducted in a primary health center in Kouba, Algeria. There were no details about the recruitment and inclusion/exclusion criteria in the selection of the participants. The prevalence of PDN in the sample was 45% (95% CI 40.1–49.9). Their results showed that female gender, increase of age, increase in diabetes duration, and poor glycemic control are strongly related to developing PDN. The most common pain control medications found to be used were anticonvulsant (74%), mainly pregabalin. Other medications used less frequently are Vitamin therapy (14.8%), NSAIDs (7.5%), and antidepressants (3.8%).
Celik et al. (2016) performed a cross-sectional study on 1357 diabetic patients, who have been regularly followed up in the University of Istanbul medical faculty diabetes outpatient clinic between November 2013 and April 2013, with the aim to define the PDN frequency and severity in the selected sample. The screening tool used was the Turkish DN4. The prevalence of PDN was found as 23% (20.8–25.2). When the logistic regression model was applied to identify the significant relation of specific factors to develop PDN, increase in diabetes duration (OR = 1.02), elevated HBA1c levels (OR = 1.11), presence of retinopathy (OR = 1.41), and management with at least one oral hypoglycemic agent (OR = 1.47) or any insulin regimen (OR = 1.62) (compared with diet only-management) were considerably associated with PDN occurrence.
Tools used to estimate the painful diabetic neuropathy prevalence
As mentioned before, all studies used neuropathic pain screening tools. The screening tools used to identify the PDN in these studies were DN4 questionnaire (four studies) and LANSS pain scale (1 study). Halawa et al. (2010) used the DN4 (clinician-administered) in Saudi Arabia where the Arabic language is the official used language in the country and was the earliest study conducted in the region, but they have not mentioned if they have translated and culturally adapted the questionnaire into Arabic or not. In fact, the DN4 was originally validated into the French language (2005) and then was widely adopted into many other languages including Arabic. Surprisingly, Harifi et al. (2011) claimed that they are the first to translate and adapt an Arabic version of the DN4 and this was a year after the publication of Halawa et al. (2010). Jambart et al. (2011) also used the DN4 (clinician-administered) in their study where all countries included using the Arabic language, but they clearly cited in their study that they have used the validated Arabic version of the DN4 that was introduced by Harifi et al. (2011). However, as Harifi's DN4 was translated to Arabic, but specifically adapted into the Moroccan Arabic dialect, it was unclear how it was used in the Eastern Arabic countries in which this version of Arabic is not comprehended or understood.
Erbas et al. (2011) were the only ones who used the LANSS pain scale provided by Bennett (2001). They have used the Turkish version of the LANSS that was validated into the Turkish language by Yucel et al. Although the official language in Algeria is Arabic, the DN4 (clinician-administered) was used in this study with the original French version. This is likely because the French language is widely used in Algerian culture and there was no need to use the Arabic version of the DN4. Unal-Cevik et al. (2010) conducted their study in Turkey and used the Turkish adapted DN4 (clinician-administered) that was previously validated in 2010.
In all the selected five studies (8 surveys), there were estimations of the prevalence of PDN. Overall, the studies recruited 7898 participants, 3761 women, with type 2 or type 1 diabetes.
Other reported variables
Only three studies reported the blood sugar figures, Erbas et al. (2013) reported the fasting plasma glucose mg/dl Mean ± standard deviation (SD) (169.6 ± 72.9). The other two studies reported the HbA1c levels, Aouiche et al., (2014) found that 34.5% have HbA1c of 8% or more (normal should be <5.7) whereas, Celick et al. (2016) reported the HbA1c (%) in two groups, Group 1 with DN 4 <4 Mean ± SD (7.8 ± 1.6) and Group 2 of DN 4 ≥4 Mean ± SD (8.1 ± 1.6). All studies reported BMI apart from Celick et al. (2016), the BMI reported showed that most participants were overweight or obese [Table 2]. In all studies, the percentage of Type 1 diabetes was only around 10% of the total participants. The duration of the diabetes was reported as at least 10 years in all studies.
Quality assessment of the included studies [Table 3]
The sample size in the five selected studies was representative of the target population, this consensus was reached as the target population were diabetic patients, and all studies included demographic data. Details of the recruitment process in all studies were not clearly reported. The recruitment should have followed a random sampling method, and this should have been clearly mentioned in the methods section of the study and how the randomization was carried out. Only Erbas et al. (2011) mentioned that they randomized the sample with no further details. This led to the fact that all studies scored “unclear” for this question.
There is no clear documentation in all the studies regarding the sample size calculation. In fact, their authors should have clearly documented on which basis they chose the number of participants and what kind of calculation method they carried out. Adequate sample size is an important factor in ensuring good precision of the final estimate. This meant all the studies also scored “unclear” for this question. In all five studies, the participants' characteristics and setting were described in detail as mentioned before. The data analysis was conducted with sufficient coverage of the sample, as there was no refusal to participate dropouts from the all studies. Objectively, standard criteria were used for the measurement of the condition, and there was an appropriate statistical analysis in all of the studies, as validated screening tools were used to measure the PDN and statistical analysis was carried out to appreciate the prevalence from the data.
Measurement of the reliability of the condition was clearly recognized in Jambart et al. (2011), Erbas et al. (2011), and Celick et al. (2016), but there was no clear record or declaration of this in the other two studies. Jambart et al. (2011) stated that the DN4 (clinician-administered) was supervised by an experienced health practitioner, and the examination section was performed by the same health practitioner. Erbas et al. (2011) used the LANSS which contains an examination section that was performed by an experienced health professional. Finally, Celick et al. (2016) specified that DN4 (clinician-administered) was applied by an experienced nurse. As mentioned in the characteristics of the included studies, an appropriate statistical analysis was performed in all of the studies. Important confounding factors, subgroups, and differences were identified and accounted for in all studies as can be appreciated in the included studies characteristics. Subpopulation was identified using objective criteria in all studies, and this can be appreciated while looking at the characteristics of the included studies.
The overall estimate of PDN is 43.2% (95% CI 30.1%–57.2%, effect size = −0.949, P = 0.343) [Forest plot, [Figure 2]. The highest prevalence of PDN was that of Halawa et al. (2010) in Saudi Arabia at 65.3%, and the lowest was that of 14% in Turkey. The LANSS which was used in Turkey produced the lowest prevalence while DN4 estimates ranged from 23% to 65.3%. As mentioned above, the random effect model was applied because of the assumption that these studies concern different populations in different countries using different assessment tools. Heterogeneity was low in this random effect model as I2 was 10.1%. It is suggested from the forest plot and associated calculation that all the effect sizes were significant apart from the overall effect.
|Figure 2: Forest plot of the prevalence estimates of Painful diabetic neuropathy as extracted from 8 surveys in the Middle East and North Africa region. Event rate (proportion with individuals with the condition out of 1 was used instead of %)|
Click here to view
| Discussion|| |
To the best of our knowledge, this study is the first attempt to systematically review the point prevalence of PDN in the MENA region. Although there are 21 countries in the region, only five studies were conducted on the condition in a total of 7 countries. The Prevalence of PDN in the MENA region was found to be 43.2% (7898 participants, 5 studies, 7 countries, and 8 surveys). This is higher than estimates from other regions of the world such as the UK (22%–35%),,, Belgium (14%), France (20%), South Africa (30.3%), and the USA (11%–25%)., Petropoulos et al. (2016) and Aizarani et al. clearly concluded that PDN is understudied in the MENA region and that there is a need for an increasing number of high-quality studies to appreciate a more precise impact of the condition in the region. All studies conducted in the region used simple screening questionnaires. There is a clear lack of awareness in the region of the disease amongst all, from doctors to the affected groups. There is a clear consensus that patients with any pain conditions are left unclear where to be referred to, because pain medicine is under-considered in the region. Jambart et al. (2011) suggested that there is a higher incidence of the PDN compared to the Western population, most likely because of the key clinical features such as the poor glycemic control in the MENA region compared to the Western population. They emphasized that good glycemic control and the control of other common diabetes risk factors such as high blood pressure, dyslipidemia and chronic kidney diseases can help bring the numbers of PDN down. This can also lead to a better quality of life to the patients.
Only three of the five studies provided some findings regarding the pain treatments used. Halawa et al. (2010) and Aouiche et al. (2014) indicated that the Pregabalin was the most commonly used pain control medication, 62.3%, and 74%, respectively whereas, Jambart et al. (2011) reported the pregabalin as the second most used medication (19.2%) after the NSAIDS (31.6%). Other pain medications were reported in less incidence for pain management such as Vitamin B complex, Diclofenac, Gabapentin, and antidepressants. Bohlega et al. published recommendations from an expert panel for the Middle East region's guidelines for the pharmacological treatment of peripheral neuropathic pain. They suggested using Pregabalin or Gabapentin or Tricyclic antidepressants as first-line treatment options and SNRI (such as duloxetine of venlafaxine) or opioids analgesics (such as tramadol or oxycodone) as the second-line treatment options. However, from the previous medication findings, the guidelines are not well-followed. Some of the medications mentioned in the studies in the region are not recommended to use for neuropathic pain and rather used for other nociceptive and/or inflammatory type of pain such as NSAIDs.
The age of participants in these surveys was ≥18 years old except Jambart et al.'s (2011) study. Although they clearly mentioned in the inclusion criteria that the minimum recruitment age is ≥18 years old, they then state in their results that the age of the participants ranged from 11 to 107 years old. The fact that Halawa et al. (2010) used the DN4 (clinician-administered) questionnaire in the Saudi population without mentioning if it was translated by them or not provides a disadvantage to this study. All of the five studies reported a strong relationship between the increased duration of diabetes and the increase in age to the development of the PDN. Jambart et al. (2011) and Aouiche et al. (2014) reported the female gender as another risk factor to develop PDN, but Halawa et al. (2010) reported that males are more likely to develop PDN than females. Other reported predictors are, increase in weight (BMI ≥30 kg/m2), poor glycemic control. All of the previous agreements with other epidemiological studies conducted in the MENA region and outside the region as well.,
Strengths and weaknesses of the study
One of the main strengths of this study is that it provides a cornerstone to researchers to further study the condition in the region. This study also uncovers the absolute truth that serious steps need to be taken to tackle the widespread nature of PDN in the region. The results of this study should be dealt with caution as it is not entirely representative of the region, as a prevalence study was conducted in only 7 out of the 21 countries in the region, with Turkey being the most fortunate of having two studies conducted and the other countries only one study. Another limitation is that there was no high-quality study conducted in the region and all studies were conducted using only screening questionnaires and no other more confirmatory methods were used to support the findings, for example, thorough neurological examinations or QST testing or nerve conduction studies.
Future research opportunities
The selected studies showed weaknesses in study design, selection of an assessment tool which was not entirely suitable for the target population, clinician-led delivery of the questionnaire, no sample calculations, and errors in random selection of the sample. There is a need for robust studies using strict random selection criteria and larger sample sizes. This study provides a platform to study the PDN in the region in more detail; it also highlights the essentiality of managing diabetes complications.
| Conclusions|| |
The prevalence of PDN in people with diabetes from the MENA region was 43.2% (7898 participants, 5 studies, 7 countries, and 8 surveys) and higher than estimates from other regions of the world such as the UK (22%–35%),,, Belgium (14%), France (20%), South Africa (30.3%), and the USA (11%–25%)., Only seven countries were studied in the region from a total of 21 countries. Given the high figures of the PDN, there is a need for more studies to be conducted in different countries in the region.
Financial support and sponsorship
The first author is funded by the State of Libya. The funders had no role in the preparation of the manuscript.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Finnerup NB, Haroutounian S, Kamerman P, Baron R, Bennett DL, Bouhassira D, et al.
Neuropathic pain: An updated grading system for research and clinical practice. Pain 2016;157:1599-606.
Aslam A, Singh J, Rajbhandari S. Pathogenesis of painful diabetic neuropathy. Pain Res Treat 2014;2014:412041.
Chong MS, Hester J. Diabetic painful neuropathy: Current and future treatment options. Drugs 2007;67:569-85.
Quattrini C, Tesfaye S. Understanding the impact of painful diabetic neuropathy. Diabetes Metab Res Rev 2003;19 Suppl 1:S2-8.
Ellenberg M. Diabetic neuropathic cachexia. Diabetes 1974;23:418-23.
Naccache DD, Nseir WB, Herskovitz MZ, Khamaisi MH. Diabetic neuropathic cachexia: A case report. J Med Case Rep 2014;8:20.
Dworkin RH, O'Connor AB, Backonja M, Farrar JT, Finnerup NB, Jensen TS, et al.
Pharmacologic management of neuropathic pain: Evidence-based recommendations. Pain 2007;132:237-51.
Haanpää M, Hietaharju A. Halting the March of painful diabetic neuropathy. Pain 2013;1.
Finnerup NB, Attal N, Haroutounian S, McNicol E, Baron R, Dworkin RH, et al.
Pharmacotherapy for neuropathic pain in adults: A systematic review and meta-analysis. Lancet Neurol 2015;14:162-73.
Majeed A, El-Sayed AA, Khoja T, Alshamsan R, Millett C, Rawaf S, et al.
Diabetes in the Middle-East and North Africa: An update. Diabetes Res Clin Pract 2014;103:218-22.
Petropoulos IN, Javed S, Azmi S, Khan A, Ponirakis G, Malik RA. Diabetic neuropathy and painful diabetic neuropathy in the Middle East and North Africa (MENA) region: Much work needs to be done. J Taibah Univ Med Sci 2016;11:284-94.
Halawa MR, Karawagh A, Zeidan A, Mahmoud AE, Sakr M, Hegazy A, et al.
Prevalence of painful diabetic peripheral neuropathy among patients suffering from diabetes mellitus in Saudi Arabia. Curr Med Res Opin 2010;26:337-43.
Celik S, Yenidunya G, Temel E, Purisa S, Uzum AK, Gul N, et al.
Utility of DN4 questionnaire in assessment of neuropathic pain and its clinical correlations in Turkish patients with diabetes mellitus. Prim Care Diabetes 2016;10:259-64.
Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, et al.
Development of AMSTAR: A measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol 2007;7:10.
Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al.
Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA 2000;283:2008-12.
Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009;6:e1000097.
Duffy ME. The joanna briggs institute: Its contribution to evidence-based practice. Clin Nurse Spec 2005;19:184-6.
Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods 2010;1:97-111.
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60.
Harbord RM, Higgins J. Meta-regression in Stata. Meta 2008;8:493-519.
Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol 2008;61:991-6.
Aouiche S, Ouerdane K, Frioui M, Boudaoud AA, Ragguem A, Boudiba A. Neuropathie diabétique douloureuse: Fréquence, facteurs de risque et gravité dans une cohorte de 400 sujets diabétiques en Algérie.Méd Mal Métab 2014;8:211-5.
Souza LA, Pessoa AP, Franco Lc, Pereira Ll. Epidemiology and quality of life on people with painful diabetic neuropathy: A bibliographic review. Rev Eletron Enferm 2010;12:746-52.
Veves A, Backonja M, Malik RA. Painful diabetic neuropathy: Epidemiology, natural history, early diagnosis, and treatment options. Pain Med 2008;9:660-74.
Harifi G, Amine M, Ait Ouazar M, Boujemaoui A, Ouilki I, Rekkab I, et al.
Prevalence of chronic pain with neuropathic characteristics in the moroccan general population: A national survey. Pain Med 2013;14:287-92.
Zghoul N, Ross EL, Edwards RR, Ahmed A, Jamison RN. Prevalence of chronic pain with neuropathic characteristics: A randomized telephone survey among medical center patients in Kuwait. J Pain Res 2017;10:679-87.
Tabatabaei-Malazy O, Mohajeri-Tehrani M, Madani S, Heshmat R, Larijani B. The prevalence of diabetic peripheral neuropathy and related factors. Iran J Public Health 2011;40:55-62.
Akbar DH, Mira SA, Zawawi TH, Malibary HM. Subclinical diabetic neuropathy: A common complication in Saudi diabetics. Saudi Med J 2000;21:433-7.
Shehab D, Al-Jarallah K, Mojiminiyi OA, Al Mohamedy H, Abdella NA. Does Vitamin D deficiency play a role in peripheral neuropathy in type 2 diabetes? Diabet Med 2012;29:43-9.
Liberman O, Peleg R, Shvartzman P. Chronic pain in type 2 diabetic patients: A cross-sectional study in primary care setting. Eur J Gen Pract 2014;20:260-7.
Gore M, Brandenburg NA, Dukes E, Hoffman DL, Tai KS, Stacey B, et al.
Pain severity in diabetic peripheral neuropathy is associated with patient functioning, symptom levels of anxiety and depression, and sleep. J Pain Symptom Manage 2005;30:374-85.
Algeffari MA. Painful diabetic peripheral neuropathy among saudi diabetic patients is common but under-recognized: Multicenter cross-sectional study at primary health care setting. J Family Community Med 2018;25:43-7.
Attal N, Bouhassira D, Baron R. Diagnosis and assessment of neuropathic pain through questionnaires. Lancet Neurol 2018;17:456-66.
Hoffman DL, Sadosky A, Alvir J. Cross-national burden of painful diabetic peripheral neuropathy in Asia, Latin America, and the Middle East. Pain Pract 2009;9:35-42.
Bohlega S, Alsaadi T, Amir A, Hosny H, Karawagh AM, Moulin D, et al.
Guidelines for the pharmacological treatment of peripheral neuropathic pain: Expert panel recommendations for the middle east region. J Int Med Res 2010;38:295-317.
Aizarani C, Amir AA, Benchouk Z, Al-Samen MA, Farghaly M, Kandil A, et al
. The dos and don'ts of painful diabetic peripheral neuropathy: Primary care guidelines for the Middle East and North Africa. Middle East J Fam Med 2017;15:4-18.
Jambart S, Ammache Z, Haddad F, Younes A, Hassoun A, Abdalla K, et al.
Prevalence of painful diabetic peripheral neuropathy among patients with diabetes mellitus in the middle east region. J Int Med Res 2011;39:366-77.
Erbas T, Ertas M, Yucel A, Keskinaslan A, Senocak M, Group TS. Prevalence of peripheral neuropathy and painful peripheral neuropathy in Turkish diabetic patients. Journal of Clinical Neurophysiology. 2011;28:51-5.
Harifi G, Ouilki I, El Bouchti I, Ouazar MA, Belkhou A, Younsi R, et al.
Validity and reliability of the Arabic adapted version of the DN4 questionnaire (Douleur neuropathique 4 questions) for differential diagnosis of pain syndromes with a neuropathic or somatic component. Pain Pract 2011;11:139-47.
Bennett M. The LANSS Pain Scale: the Leeds assessment of neuropathic symptoms and signs. Pain, 2001;92:147-57.
Yucel A, Senocak M, Kocasoy Orhan E, Cimen A, Ertas M. Results of the leeds assessment of neuropathic symptoms and signs pain scale in Turkey: A validation study. J Pain 2004;5:427-32.
Le Roux CS. Language in education in Algeria: A historical vignette of a 'most severe'sociolinguistic problem. Lang Hist 2017;60:112-28.
Unal-Cevik I, Sarioglu-Ay S, Evcik D. A comparison of the DN4 and LANSS questionnaires in the assessment of neuropathic pain: Validity and reliability of the Turkish version of DN4. J Pain 2010;11:1129-35.
Abbott CA, Malik RA, van Ross ER, Kulkarni J, Boulton AJ. Prevalence and characteristics of painful diabetic neuropathy in a large community-based diabetic population in the U.K. Diabetes Care 2011;34:2220-4.
Lawson E, editor. Painful Diabetic Polyneuropathy: A Comprehensive Guide for Clinicians: Springer Science & Business Media; 2013.
Van Acker K, Bouhassira D, De Bacquer D, Weiss S, Matthys K, Raemen H, et al.
Prevalence and impact on quality of life of peripheral neuropathy with or without neuropathic pain in type 1 and type 2 diabetic patients attending hospital outpatients clinics. Diabetes Metab 2009;35:206-13.
Bouhassira D, Letanoux M, Hartemann A. Chronic pain with neuropathic characteristics in diabetic patients: A French cross-sectional study. PLoS One 2013;8:e74195.
Jacovides A, Bogoshi M, Distiller LA, Mahgoub EY, Omar MK, Tarek IA, et al.
An epidemiological study to assess the prevalence of diabetic peripheral neuropathic pain among adults with diabetes attending private and institutional outpatient clinics in South Africa. J Int Med Res 2014;42:1018-28.
Dyck PJ, Kratz KM, Karnes JL, Litchy WJ, Klein R, Pach JM, et al.
The prevalence by staged severity of various types of diabetic neuropathy, retinopathy, and nephropathy in a population-based cohort: The Rochester diabetic neuropathy study. Neurology 1993;43:817-24.
Hébert HL, Veluchamy A, Torrance N, Smith BH. Risk factors for neuropathic pain in diabetes mellitus. Pain 2017;158:560-8.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]