ABSTRACT
Background
Painful diabetic neuropathy affects ~20%–40% of individuals with diabetes, driven by peripheral small nerve fiber damage and modulated by spinal cord and brain mechanisms. Corneal nerve imaging using corneal confocal microscopy (CCM) and skin biopsy to quantify intraepidermal nerve fiber density (IENFD) are objective measures of small nerve fiber damage.
Objectives
CCM and IENFD were assessed for their ability to distinguish painful from painless diabetic neuropathy.
Methods
Following PROSPERO‐registered protocol and PRISMA guidelines, PubMed, Embase, and Web of Science were searched for studies on corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), corneal nerve fiber length (CNFL), and IENFD in patients with painful and painless diabetic neuropathy. Standardized mean difference (SMD) with 95% confidence intervals (CI) was pooled using random‐effects meta‐analyses.
Results
Seven studies (n = 683) showed lower CNFD (SMD −0.50, 95% CI −0.96 to −0.03, p = 0.03) and CNFL (SMD −0.32, 95% CI −0.59 to −0.05, p = 0.02) in painful compared to painless DPN, with no difference in CNBD. Ten studies (n = 664) demonstrated lower IENFD in painful compared to painless DPN (SMD −0.31, 95% CI −0.59 to −0.02, p = 0.03, I 2 69%). In three studies assessing both CCM and IENFD (n = 161), CNFD (p < 0.0001), CNBD (p = 0.01), CNFL (p = 0.0001), and IENFD (p = 0.008) were significantly lower in painful compared to painless DPN.
Conclusion
Both CCM and skin biopsy demonstrate small nerve fiber loss in painful compared to painless DPN, supporting their value in identifying alterations in small nerve fiber structure in painful DPN.
Keywords: CCM, diagnosis, IENFD, painful neuropathy, painless neuropathy
1. Introduction
Diabetic peripheral neuropathy (DPN) affects up to 50% of individuals with diabetes and can lead to debilitating painful neuropathy [1]. Questionnaires to assess the presence and severity of neuropathic pain [2] include the neuropathic pain symptom inventory (NPSI) [3], modified brief pain inventory [4], neuropathic pain questionnaire [5], Leeds assessment of neuropathic symptoms of sensory dysfunction (LANSS) [6], McGill pain questionnaire [7], and the Douleur Neuropathique 4 questionnaire (DN4) [8]. The diagnosis of painful neuropathy relies on eliciting symptoms, but they can be difficult to quantify due to the subjective and individual nature of pain [9].
Objective measures of neuropathy include nerve conduction studies (NCS) [10] but they only detect large‐fiber pathology, missing small fiber pathology, which underlies pain [11]. Intraepidermal nerve fiber density (IENFD) assessment is a reliable and objective measure of small nerve fiber loss in DPN [12]. However, the ability of IENFD to discriminate painful from painless neuropathy remains uncertain [13] and indeed peptidergic fibers are increased in painful neuropathy [14]. Corneal confocal microscopy (CCM) is a non‐invasive, ophthalmic imaging technique that detects small nerve fiber damage and has a comparable diagnostic performance to IENFD for diagnosing DPN [15]. Greater corneal nerve loss has been reported in some studies [16, 17], but in one study, there was increased corneal nerve branching [18] in patients with painful compared to painless diabetic neuropathy. As part of the AGORA initiative to evaluate surrogate markers of neuropathic pain, this systematic review with multiple meta‐analyses aims to evaluate and synthesize the current evidence on: 1 The utility of CCM in differentiating painful from painless DPN; 2 The utility of IENFD in differentiating painful from painless DPN; and finally, 3 A head‐to‐head comparison between CCM and IENFD in differentiating painful from painless DPN.
2. Materials and Methods
This systematic review and meta‐analyses were conducted following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses protocols (PRISAM‐P) [19]. The review protocol was pre‐registered with the International Prospective Register of Systematic Reviews (PROSPERO ID: CRD42024590897). This work forms part of the AGORA, an international multidisciplinary working group established to systematically evaluate surrogate markers of neuropathic pain. The role of genetic and epigenetic factors, clinical phenotyping, neuropsychological determinants, advanced neurophysiology, and neuroimaging signatures to differentiate painful from painless DPN are being addressed through separate systematic reviews and meta‐analyses, followed by a structured Delphi consensus process to update clinical guidelines. Our systematic review and multiple meta‐analyses fall under the clinical phenotyping and diagnostics domain.
Continuous outcomes such as corneal nerve fiber density (CNFD no/mm2), corneal nerve branch density (CNBD no/mm2), corneal nerve fiber length (CNFL mm/mm2), and intraepidermal fiber density (IENFD no/mm) were analyzed using the standard mean difference to account for any potential variability due to the use of different software for CCM image analysis (standardized mean difference [SMD]).
2.1. Search Strategy and Data Collection
For this systematic review and multiple meta‐analyses, three search strategies were applied to gather a comprehensive body of literature and to provide evidence in an area where data on this topic are limited. Three databases, PubMed, Embase (Ovid), and Web of Science, were searched. In Embase EmTREE, subject headings and keywords were used, whereas PubMed searches employed MeSH terms and keywords. Searches were restricted to English‐language publications, and gray literature, including dissertations and theses, was also systematically examined via Web of Science‐EXI.
The detailed search strategy for:
The utility of CCM in differentiating between painful and painless diabetic neuropathyis in Table S1.
The utility of IENFD in differentiating between painful and painless diabetic neuropathyis in Table S2.
The utility of CCM vs. IENFD in differentiating between painful and painless diabetic neuropathy is in Table S3.
2.2. Inclusion and Exclusion Criteria
We included studies with no restriction on the design that reported on at least one of the primary corneal nerve parameters: CNFD, CNBD, and CNFL for meta‐analysis 1, and studies that reported on IENFD for meta‐analysis 2, and studies that reported on both IENFD and at least one CCM parameter for meta‐analysis 3, in patients with:
Painful DPN (DPN + p)
Painless DPN (DPN‐p)
Studies that reported on one group only i.e., painful versus healthy control, or painless versus healthy control, case reports, narrative reviews, and systematic reviews were excluded. For uniformity, selected studies were restricted to those using Heidelberg Retina Tomograph III (HRT III) and CCMetrics or Morphometric software for CCM image analysis.
2.3. Study Selection
Following the removal of duplicates, titles and abstracts were initially screened by two independent reviewers (HG, RAM). Any disagreement in study selection at the full text stage was resolved through discussion and consensus. A PRISMA flow chart illustrating the search and selection process is presented in Figure 1 (meta‐analysis 1), Figure 3 (meta‐analysis 2), and Figure 5 (meta‐analysis 3).
FIGURE 1.
PRISMA Flow Chart for Meta‐analysis 1.
FIGURE 3.
PRISMA Flow Chart for Meta‐analysis 2.
FIGURE 5.
PRISMA Flow Chart for Meta‐analysis.
2.4. Data Extraction
Data were extracted by two authors (HG and RAM) using a pre‐piloted data extraction sheet, capturing the main outcomes (CNFD, CNBD, CNFL, and IENFD), study characteristics, and classification of painful or painless DPN.
2.5. Risk of Bias Assessment
The risk of bias for included studies was assessed using the Cochrane Risk of Bias tool, as outlined in chapter 8 of the Cochrane Handbook and embedded in RevMan Web [20]. This evaluates domains including performance, detection, attrition, reporting, and other potential biases. When items were not applicable, it was indicated as not applicable. Two reviewers (HG and RAM) independently conducted the assessment, with disagreements resolved through discussion.
2.6. Statistical Analysis
A random‐effect model was applied using RevMan web version 5, calculating the standard mean difference (SMD) with 95% confidence intervals (CI). Statistical significance was set at α < 0.05.
2.7. Heterogeneity
Clinical heterogeneity was examined using the Higgin's test via the I 2 statistic quantified between‐study variation, with 0%–40% considered low, 30%–60% moderate, 50%–90% substantial, and 75%–100% considerable heterogeneity (Cochrane handbook, chapter 10.10) [21].
3. Results
3.1. The Utility of CCM in Differentiating Painful From Painless DPN
The search strategy is detailed in Table S1 identified 59 records through database searches. Duplicates were removed by Covidence (n = 25), with 34 records remaining for title and abstract screening. After screening, 27 records were excluded based on relevance, leaving 7 full‐text articles that met the inclusion criteria and were included in the meta‐analysis. A flow chart of the study selection is detailed in Figure 1.
3.1.1. Corneal Nerve Fiber Density (CNFD)
Seven studies [16, 17, 18, 22, 23]. with 683 participants with DPN (344 DPN + p and 339 DPN‐p) were included in this meta‐analysis. CNFD was significantly lower in those with painful compared to painless DPN (SMD −0.50, 95% CI −0.96 to −0.03, p = 0.03, I 2 88%) (Figure 2a). To account for the substantial heterogeneity, the small study effect was assessed by the trim and fill technique, and the I 2 remained high (I 2 = 89%), thus all studies were included.
FIGURE 2.
(a) Forest plot showing the standardized mean difference in CNFD between patients with DPN + p and DPN‐p. (b) Forest plot showing the standard mean difference in CNBD between patients with DPN + p and DPN‐p. (c) Forest plot showing the standard mean difference in CNFL between patients with DPN + p and DPN‐p.
3.1.2. Corneal Nerve Branch Density (CNBD)
Seven studies [16, 17, 18, 22, 23, 24, 25] with 683 participants with DPN (344 DPN + p and 339 DPN‐p) were included in this meta‐analysis. There was no significant difference in CNBD between those with painful and painless DPN (SMD −0.20, 95% CI −0.45 to 0.05, p = 0.12, I 2 62%) (Figure 2b). To account for the substantial heterogeneity, small study effect was assessed by the trim and fill techniques, and I 2 remained high (I 2 = 62%), thus all studies were included.
3.1.3. Corneal Nerve Fiber Length (CNFL)
Seven studies [16, 17, 18, 22, 23, 24, 25] with 683 participants with DPN (344 DPN + p and 339 DPN‐p) were included in this meta‐analysis. CNFL was significantly lower in those with painful compared to painless DPN (SMD −0.32, 95% CI −0.59 to −0.05, p = 0.02, I 2 66%) (Figure 2c). To account for the substantial heterogeneity, the small study effect was assessed by the trim and fill technique, and the I 2 increased (I 2 = 70%), thus all studies were included.
3.2. The Utility of IENFD in Differentiating Painful From Painless DPN
The search strategy is detailed in Table S2 identified through database searching 168 records. Duplicates were removed by Covidence (n = 55), and 113 records remained for title and abstract screening. After screening, 103 records were excluded based on relevance, leaving 10 full‐text articles that met the inclusion criteria and were included in the meta‐analysis. A flow chart of the study selection is detailed in Figure 3.
3.2.1. Intraepidermal Nerve Fiber Density (IENFD)
Ten studies [14, 16, 26, 27, 28, 29, 30, 31, 32, 33] with 664 participants with DPN (365 DPN + p and 299 DPN‐p) were included in this meta‐analysis. IENFD showed an overall trend toward being significantly lower in those with painful compared to painless DPN (SMD −0.31, 95% CI −0.59 to −0.02, p = 0.03, I 2 69%) (Figure 4). To account for the substantial heterogeneity, small study effect was assessed by the trim and fill technique and while the I 2 remained the same (I 2 = 69%) the overall effect size of 8 studies (n = 623) [14, 16, 26, 27, 28, 29, 30, 31] remained significant (SMD −0.34, 95% CI −0.65 to −0.04, p = 0.03, I 2 69%).
FIGURE 4.
Forest plot showing the standardized mean difference in IENFD between patients with DPN + p and DPN ‐p.
3.2.2. Exploratory Description of Other Morphological Changes in Skin Biopsy
Bonhof 2017 reported that patients with both painful and painless diabetic sensorimotor polyneuropathy (DSPN) exhibited comparably reduced IENFD and fiber length. Additionally, the dermal nerve‐fiber‐regeneration (DNFL) marker GAP‐43/PGP9.5 ratio was significantly higher in painful compared to painless DSPN (1.18 ± 0.28 vs. 1.07 ± 0.10, p < 0.005) [31]. Shillo 2019 observed that lower serum 25‐hydroxyvitamin D levels were associated with reduced sub‐epidermal nerve‐fiber densities (SENFD) and specifically correlated with painful diabetic neuropathy [26]. Karlsson 2021 found no difference in IENFD between painful and painless DPN, however calcitonin gene‐related peptide (CGRP) (22.3 ± 14.3 vs. 15.2 ± 7.7 intercepts/mm2; p < 0.005), substance P (15.7 ± 12.8 vs. 9.5 ± 7.3, intercepts/mm2; p < 0.005) and total peptidergic fibers (37.9 ± 13.7 vs. 24.8 ± 11.0, intercepts/mm2; p < 0.005) were significantly higher in the painful compared to painless DPN group [14]. Karlsson 2021 also found no significant difference in axonal swelling between patients with painful and painless DPN (0.30 (0.0–0.57) vs. 0.12 (0.0–0.36)) [28].
3.3. The Utility of CCM vs. IENFD in Differentiating Painful From Painless DPN
The search strategy is detailed in Table S3 identified through database searching 283 records. Duplicates were removed by Covidence (n = 76), and 207 records remained for title and abstract screening. After screening, 197 records were excluded based on relevance, leaving 3 full‐text articles that met the inclusion criteria and were included in the meta‐analysis. A flow chart of the study selection is detailed in Figure 5.
3.3.1. Corneal Nerve Fiber Density (CNFD)
Three studies [16], [32], [34] with 161 participants with DPN (74 DPN + p and 87 DPN‐p) were included in this meta‐analysis. CNFD was significantly lower in painful compared to painless DPN (SMD −0.64, 95% CI −0.96 to −0.32, p < 0.0001, I 2 0%) (Figure 6a).
FIGURE 6.
(a) Forest plot showing the standard mean difference in CNFD between patients with DPN + p and DPN‐p. (b) Forest plot showing the standardized mean difference in CNBD between patients with DPN + p and DPN‐p. (c) Forest plot showing the standard mean difference in CNFL between patients with DPN + p and DPN‐p. (d) Forest plot showing the standard mean difference in IENFD between patients with DPN + p and DPN‐p.
3.3.2. Corneal Nerve Branch Density (CNBD)
Three studies [16], [32], [34] with 161 participants (77 DPN + p and 84 DPN‐p) were included in this meta‐analysis. CNBD was significantly lower in painful compared to painless DPN (SMD −0.39, 95% CI −0.71 to −0.08, p = 0.01, I 2 0%) (Figure 6b).
3.3.3. Corneal Nerve Fiber Length (CNFL)
Three studies [16, 32, 34] with 161 participants (77 DPN + p and 84 DPN‐p) were included in this meta‐analysis. CNFL was significantly lower in painful compared to painless DPN (SMD −0.63, 95% CI −0.95 to −0.31, p = 0.0001, I 2 0%) (Figure 6c).
3.3.4. Intraepidermal Nerve Fiber Density (IENFD)
Three studies [16, 32, 34] with 138 participants (63 DPN + p and 75 DPN‐p) were included in this meta‐analysis. IENFD was significantly lower in painful compared to painless DPN (SMD −0.46, 95% CI −0.80 to −0.12, p = 0.008, I 2 0%) (Figure 6d).
3.4. CCM Versus IENFD
In the three studies using both CCM and IENFD as a measure for small nerve fiber pathology, CNFD (SMD −0,64, 95% CI −0.96 to −0.32, p < 0.0001), CNBD (SMD −0.39, 95% CI −0.71 to −0.08, p = 0.01), CNFL (SMD −0.63, 95% CI −0.95 to −0.31, p = 0.0001), and IENFD (SMD −0.46, 95% CI −0.80, −0.12, p = 0.008) were significantly lower in patients with painful compared to painless DPN.
4. Discussion
Neuropathic pain is associated with small fiber neuropathy (SFN), primarily involving damage to the thinly myelinated (Aδ) and unmyelinated (C) nerve fibers [35]. SFN often presents with vague neuropathic symptoms and normal NCS, making diagnosis challenging [36]. Confirmation of SFN can be achieved using skin biopsy, quantitative sensory testing (QST), or CCM [35].
In this systematic review and multiple meta‐analyses, we demonstrate that both CCM and skin biopsy reveal greater small nerve fiber pathology with lower IENFD, CNFD, and CNFL but comparable CNBD in patients with painful compared to painless DPN. The lack of difference in CNBD may be attributed to the greater variability in this measure, as it increases with nerve regeneration. Indeed, we observed no differences in CNBD in the overall analysis (I 2 = 65%) but a significant difference in the head‐to‐head analysis (I 2 = 0%). This suggests that CNBD may be sensitive to methodological and population variability, and particularly concomitant nerve regeneration, with an increase in CNBD increasing heterogeneity, thereby limiting its ability to differentiate painful from painless DPN. Our findings contrast with a recent meta‐analysis by Vidyasagar [37], which reported no significant differences in CNFD, CNBD, or CNFL between painful and painless DPN. While many of the included studies overlap with our analyses, importantly, we restricted our inclusion criteria to studies employing manual CCM image analysis, whereas Vidyasagar combined both manual and automated methods to quantify corneal nerves. As previously reported by Wu et al. [38], automated analysis underestimates CNFL and CNBD due to the missed detection of thinner nerve branches caused by artifacts or lower image quality. Furthermore, because CNFL is calculated as the sum of fibers and branches, underestimation of branches automatically reduces CNFL, potentially masking true differences between painful and painless phenotypes, and likely contributed to the more robust separation of CNFD and CNFL observed in our study.
The reduction in IENFD among patients with painful DPN reinforces its role as the histological gold standard for assessing small nerve fiber integrity. Indeed, our findings align with a recent study showing that painful diabetic neuropathy is characterized by a reduction in IENFD [33]. However, several studies have demonstrated that loss of epidermal nerve fibers does not correlate with the presence or intensity of neuropathic pain. Truini [13] found no significant difference in epidermal nerve fiber density between patients with and without neuropathic pain, concluding that ongoing burning pain likely reflects mechanisms other than nociceptor loss [13]. The German Society of Neurology guidelines emphasize that a normal IENFD does not exclude neuropathic pain and that correlations between IENFD and pain intensity are inconsistent [39].
These findings underscore the need to move beyond simple quantification of epidermal nerve fiber loss and to examine other morphologic and molecular changes within the skin that may better reflect pain mechanisms. Thus, Bonhof 2017 reported that patients with both painful and painless diabetic sensorimotor polyneuropathy (DSPN) exhibited comparably reduced IENFD and fiber length, yet the dermal nerve‐fiber‐regeneration marker GAP‐43/PGP9.5 ratio was significantly higher in the painful DSPN group, suggesting enhanced dermal regenerative activity accompanying epidermal nerve fiber loss [31]. In another study, Shillo 2019 showed that lower serum 25‐hydroxyvitamin D levels were associated with reduced sub‐epidermal nerve‐fiber densities and correlated with painful diabetic neuropathy, hinting at an intersection between metabolic and structural determinants of pain [26].
Taken together, these findings highlight that while quantitative epidermal nerve loss is a common endpoint of small nerve fiber loss, the qualitative pattern of nerve and vascular remodeling, including features such as increased peptidergic fiber content, axonal swellings, regenerative sprouting, and microvascular proliferation, more accurately captures the complex morphological underpinnings of neuropathic pain. This supports the growing rationale for investigating complementary morphologic markers in skin biopsy beyond IENFD to elucidate the structural correlates with painful neuropathy.
In the subset of studies assessing both CCM and IENFD, we found significant reductions in all parameters: CNFD, CNBD, CNFL, and IENFD in painful compared to painless DPN, with CNFD and CNFL providing the strongest discriminatory power. Marshall reported a lower CNFD, but no difference in IENFD or cold or warm sensation thresholds [34], while Ferdousi reported a reduction in IENFD, CNFD, CNBD, and CNFL, but no difference in cold or warm sensation thresholds [16] in patients with painful compared to painless DPN. IENFD is considered the benchmark for small nerve fiber assessment; however, CCM demonstrated comparable performance in differentiating painful from painless DPN, and we have previously shown that CCM and IENFD have comparable diagnostic utility for DPN [15] Given its non‐invasive nature, rapid acquisition, and reproducibility, CCM emerges as a promising alternative to help differentiate painful from painless DPN in both clinical practice and clinical trials.
Despite the strengths of our combined meta‐analyses, including strict inclusion criteria, comprehensive literature searches, and pooled analyses, we acknowledge several limitations. Importantly, while the findings of our combined meta‐analyses are directionally consistent with prior systematic reviews, the work extends the literature by integrating multiple complementary meta‐analyses within a single framework. While IENFD has been evaluated for the diagnosis of DPN, there are limited systematic reviews and no prior meta‐analyses directly comparing the utility of IENFD with CCM in differentiating painful from painless DPN. Limiting studies to those using manual CCM analysis offers greater precision than automated analysis. Substantial heterogeneity was observed in both CCM and IENFD analyses, likely reflecting differences in study design, patient characteristics (e.g., diabetes type, duration, glycemic control), and image acquisition and analysis. We minimized variability by restricting CCM studies to those using the Heidelberg Retina Tomograph III with manual analysis; however, residual heterogeneity remains possible. The number of head‐to‐head studies directly comparing CCM and IENFD was limited, underscoring the need for larger comparative trials to confirm these findings.
We acknowledge that painful diabetic neuropathy is a complex, multidimensional condition, and pain severity and persistence cannot be fully explained by peripheral small fiber structural measures alone. Accordingly, this systematic review and multiple meta‐analyses did not address genetic, epigenetic, neuropsychological determinants, central sensitization, QST, neuroinflammation, autonomic dysfunction, advanced neurophysiology, or neuroimaging signatures. However, these domains are being evaluated in parallel systematic reviews within the AGORA program.
Overall, our findings support the use of both CCM and IENFD to identify structural differences in small nerve fibers between painful and painless DPN. It also highlights the promise of CCM as an objective, non‐invasive tool for pain‐related phenotyping/stratification rather than as a standalone diagnostic marker. Incorporating complementary morphologic and molecular markers of nerve regeneration, axonal swelling, or vascular remodeling, combined with clinical and functional pain assessments, may improve the contextual interpretation of our findings. Longitudinal and mechanistic studies are required to validate the utility of quantifying small nerve fiber structure to monitor therapeutic response in painful diabetic neuropathy.
Author Contributions
Rayaz A. Malik: supervision, resources, writing – review and editing. Grazia Devigili: supervision, writing – review and editing. Giuseppe Lauria: supervision, writing – review and editing.
Funding
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Table S1: Supporting Information.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Tesfaye S., Vileikyte L., Rayman G., et al., “Painful Diabetic Peripheral Neuropathy: Consensus Recommendations on Diagnosis, Assessment and Management,” Diabetes/Metabolism Research and Reviews 27, no. 7 (2011): 629–638. [DOI] [PubMed] [Google Scholar]
- 2. Cruccu G., Sommer C., Anand P., et al., “EFNS Guidelines on Neuropathic Pain Assessment: Revised 2009,” European Journal of Neurology 17, no. 8 (2010): 1010–1018. [DOI] [PubMed] [Google Scholar]
- 3. Bouhassira D., Attal N., Fermanian J., et al., “Development and Validation of the Neuropathic Pain Symptom Inventory,” Pain 108, no. 3 (2004): 248–257. [DOI] [PubMed] [Google Scholar]
- 4. Zelman D. C., Gore M., Dukes E., Tai K. S., and Brandenburg N., “Validation of a Modified Version of the Brief Pain Inventory for Painful Diabetic Peripheral Neuropathy,” Journal of Pain and Symptom Management 29, no. 4 (2005): 401–410. [DOI] [PubMed] [Google Scholar]
- 5. Backonja M. M. and Krause S. J., “Neuropathic Pain Questionnaire—Short Form,” Clinical Journal of Pain 19, no. 5 (2003): 315–316. [DOI] [PubMed] [Google Scholar]
- 6. Bennett M., “The LANSS Pain Scale: The Leeds Assessment of Neuropathic Symptoms and Signs,” Pain 92, no. 1–2 (2001): 147–157. [DOI] [PubMed] [Google Scholar]
- 7. Melzack R., “The Short‐Form McGill Pain Questionnaire,” Pain 30, no. 2 (1987): 191–197. [DOI] [PubMed] [Google Scholar]
- 8. Perez C., Galvez R., Huelbes S., et al., “Validity and Reliability of the Spanish Version of the DN4 (Douleur Neuropathique 4 Questions) Questionnaire for Differential Diagnosis of Pain Syndromes Associated to a Neuropathic or Somatic Component,” Health and Quality of Life Outcomes 5 (2007): 66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Boulton A. J., Vinik A. I., Arezzo J. C., et al., “Diabetic Neuropathies: A Statement by the American Diabetes Association,” Diabetes Care 28, no. 4 (2005): 956–962. [DOI] [PubMed] [Google Scholar]
- 10. Tesfaye S., Boulton A. J. M., Dyck P. J., et al., “Diabetic Neuropathies: Update on Definitions, Diagnostic Criteria, Estimation of Severity, and Treatments,” Diabetes Care 33, no. 10 (2010): 2285–2293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Boulton A. J., Boulton A. J. M., Malik R. A., Arezzo J. C., and Sosenko J. M., “Diabetic Somatic Neuropathies,” Diabetes Care 27, no. 6 (2004): 1458–1486. [DOI] [PubMed] [Google Scholar]
- 12. Lauria G., Faber C. G., and Cornblath D. R., “Skin Biopsy and Small Fibre Neuropathies: Facts and Thoughts 30 Years Later,” Journal of Neurology, Neurosurgery, and Psychiatry 93, no. 9 (2022): 915–918. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Truini A., Biasiotta A., di Stefano G., et al., “Does the Epidermal Nerve Fibre Density Measured by Skin Biopsy in Patients With Peripheral Neuropathies Correlate With Neuropathic Pain?,” Pain 155, no. 4 (2014): 828–832. [DOI] [PubMed] [Google Scholar]
- 14. Karlsson P., Provitera V., Caporaso G., et al., “Increased Peptidergic Fibers as a Potential Cutaneous Marker of Pain in Diabetic Small Fiber Neuropathy,” Pain 162, no. 3 (2021): 778–786. [DOI] [PubMed] [Google Scholar]
- 15. Chen X., Graham J., Dabbah M. A., et al., “Small Nerve Fiber Quantification in the Diagnosis of Diabetic Sensorimotor Polyneuropathy: Comparing Corneal Confocal Microscopy With Intraepidermal Nerve Fiber Density,” Diabetes Care 38, no. 6 (2015): 1138–1144. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Ferdousi M., Azmi S., Kalteniece A., et al., “Greater Small Nerve Fibre Damage in the Skin and Cornea of Type 1 Diabetic Patients With Painful Compared to Painless Diabetic Neuropathy,” European Journal of Neurology 28, no. 5 (2021): 1745–1751. [DOI] [PubMed] [Google Scholar]
- 17. Kalteniece A., Ferdousi M., Azmi S., et al., “Corneal Confocal Microscopy Detects Small Nerve Fibre Damage in Patients With Painful Diabetic Neuropathy,” Scientific Reports 10, no. 1 (2020): 3371. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Puttgen S., Bönhof G. J., Strom A., et al., “Augmented Corneal Nerve Fiber Branching in Painful Compared With Painless Diabetic Neuropathy,” Journal of Clinical Endocrinology and Metabolism 104, no. 12 (2019): 6220–6228. [DOI] [PubMed] [Google Scholar]
- 19. Moher D., Shamseer L., Clarke M., et al., “Preferred Reporting Items for Systematic Review and Meta‐Analysis Protocols (PRISMA‐P) 2015 Statement,” Systematic Reviews 4, no. 1 (2015): 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Higgins J. P. T., Page M. J., Elbers R. G., and Sterne J. A. C., “Chapter 8: Assessing Risk of Bias in a Randomized Trial [Last Updated October 2019],” in Cochrane Handbook for Systematic Reviews of Interventions Version 6.5, ed. Higgins J. P. T., Thomas J., Chandler J., et al. (Cochrane, 2024), cochrane.org/handbook. [Google Scholar]
- 21. Deeks J. J., Altman D. G., McKenzie J. E., and Veroniki A. A., “Chapter 10: Chapter 10: Analysing Data and Undertaking Meta‐Analyses [Last Updated November 2024],” in Cochrane Handbook for Systematic Reviews of Interventions Version 6.5, ed. Higgins J. P. T., Thomas J., Chandler J., et al. (Cochrane, 2024), cochrane.org/handbook. [Google Scholar]
- 22. Kalteniece A., Ferdousi M., Petropoulos I., et al., “Greater Corneal Nerve Loss at the Inferior Whorl Is Related to the Presence of Diabetic Neuropathy and Painful Diabetic Neuropathy,” Scientific Reports 8, no. 1 (2018): 3283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Worthington A., Kalteniece A., Ferdousi M., et al., “Spinal Inhibitory Dysfunction in Patients With Painful or Painless Diabetic Neuropathy,” Diabetes Care 44, no. 8 (2021): 1835–1841. [DOI] [PubMed] [Google Scholar]
- 24. Kalteniece A., Ferdousi M., Azmi S., et al., “Corneal Nerve Loss Is Related to the Severity of Painful Diabetic Neuropathy,” European Journal of Neurology 29, no. 1 (2022): 286–294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Quattrini C., Tavakoli M., Jeziorska M., et al., “Surrogate Markers of Small Fiber Damage in Human Diabetic Neuropathy,” Diabetes 56, no. 8 (2007): 2148–2154. [DOI] [PubMed] [Google Scholar]
- 26. Shillo P., Selvarajah D., Greig M., et al., “Reduced Vitamin D Levels in Painful Diabetic Peripheral Neuropathy,” Diabetic Medicine 36, no. 1 (2019): 44–51. [DOI] [PubMed] [Google Scholar]
- 27. Karlsson P., Sjogaard M. B., Schousboe K., et al., “Assessment of Neuropathy Subtypes in Type 1 Diabetes,” BMJ Open Diabetes Research & Care 12, no. 4 (2024): e004289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Karlsson P., Gylfadottir S. S., Kristensen A. G., et al., “Axonal Swellings Are Related to Type 2 Diabetes, but Not to Distal Diabetic Sensorimotor Polyneuropathy,” Diabetologia 64, no. 4 (2021): 923–931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Hu X., Buhl C. S., Sjogaard M. B., et al., “Structural Changes of Cutaneous Immune Cells in Patients With Type 1 Diabetes and Their Relationship With Diabetic Polyneuropathy,” Neurol Neuroimmunol Neuroinflamm 10, no. 5 (2023): e200144. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Chao C. C., Tseng M. T., Hsieh P. C., et al., “Brain Mechanisms of Pain and Dysautonomia in Diabetic Neuropathy: Connectivity Changes in Thalamus and Hypothalamus,” Journal of Clinical Endocrinology and Metabolism 107, no. 3 (2022): 1167–1180. [DOI] [PubMed] [Google Scholar]
- 31. Bonhof G. J., “Patterns of Cutaneous Nerve Fibre Loss and Regeneration in Type 2 Diabetes With Painful and Painless Polyneuropathy,” Diabetologia 60, no. 12 (2017): 2495–2503. [DOI] [PubMed] [Google Scholar]
- 32. Alam U., Petropoulos I. N., Ponirakis G., et al., “Vitamin D Deficiency Is Associated With Painful Diabetic Neuropathy,” Diabetes/Metabolism Research and Reviews 37, no. 1 (2021): e3361. [DOI] [PubMed] [Google Scholar]
- 33. Sloan G., Donatien P., Privitera R., et al., “Vascular and Nerve Biomarkers in Thigh Skin Biopsies Differentiate Painful From Painless Diabetic Peripheral Neuropathy,” Front Pain Res (Lausanne) 5 (2024): 1485420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Marshall A. G., Lee‐Kubli C., Azmi S., et al., “Spinal Disinhibition in Experimental and Clinical Painful Diabetic Neuropathy,” Diabetes 66, no. 5 (2017): 1380–1390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Geerts J. G. H., Gorissen‐Brouwers C. M., Faber C. G., and Merkies I. S., “Small Fiber Neuropathy: A Clinical and Practical Approach,” Journal for Nurse Practitioners 19, no. 4 (2023): 104547. [Google Scholar]
- 36. Themistocleous A. C., Ramirez J. D., Serra J., and Bennett D. L. H., “The Clinical Approach to Small Fibre Neuropathy and Painful Channelopathy,” Practical Neurology 14, no. 6 (2014): 368–379. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Vidyasagar P., Farrell S. F., Colorado L. H., Dando S., and Edwards K., “Corneal Nerve Morphology In Painful Diabetic Neuropathy: A Meta‐Analysis of in Vivo Confocal Microscopy Studies,” Biomedicine 13, no. 7 (2025): 1675. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Wu P. Y., Wu J. H., Hsieh Y. T., et al., “Comparing the Results of Manual and Automated Quantitative Corneal Neuroanalysing Modules for Beginners,” Scientific Reports 11, no. 1 (2021): 18208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Schlereth T., “Guideline “Diagnosis and Non Interventional Therapy of Neuropathic Pain” of the German Society of Neurology (Deutsche Gesellschaft Fur Neurologie),” Neurological Research and Practice 2 (2020): 16. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Supporting Information.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.