Type 2 diabetes mellitus (T2DM) has emerged as a global health epidemic, with the International Diabetes Federation estimating that approximately 537 million adults were living with diabetes in 2021, a number projected to rise to 783 million by 2045. Among the myriad complications associated with T2DM, diabetic peripheral neuropathy (DPN) stands as one of the most common and disabling, affecting an estimated 30–50% of patients with long-standing disease. DPN is defined as a symmetrical, length-dependent sensorimotor polyneuropathy attributable to metabolic and microvascular alterations resulting from chronic hyperglycemia. It is a leading cause of foot ulceration, lower extremity amputation, and significantly diminished quality of life.

The clinical manifestations of DPN are protean, encompassing a wide spectrum of sensory, motor, and autonomic symptoms. Sensory neuropathy typically presents with a characteristic "glove-and-stocking" distribution of numbness, tingling, burning pain, and loss of protective sensation. Motor involvement may manifest as muscle weakness, atrophy, and gait disturbances, while autonomic dysfunction can affect cardiovascular, gastrointestinal, and genitourinary systems. The heterogeneity of clinical presentations poses significant challenges for early diagnosis and timely intervention.

Chronic hyperglycemia is widely recognized as the primary pathogenic driver of DPN. The mechanisms through which sustained elevation of blood glucose damages peripheral nerves are multifaceted and include activation of the polyol pathway, enhanced formation of advanced glycation end products (AGEs), increased oxidative stress, protein kinase C activation, and microvascular ischemia. Hyperglycemia-induced polyol pathway activation leads to accumulation of sorbitol and fructose in nerve tissue, with concomitant depletion of myo-inositol and reduced Na⁺-K⁺-ATPase activity, impairing nerve conduction. Simultaneously, AGEs accumulate in peripheral nerves, cross-linking structural proteins and activating pro-inflammatory pathways through receptor for AGE (RAGE) signaling. These metabolic derangements converge to produce oxidative stress, mitochondrial dysfunction, and ultimately, neuronal apoptosis.

Glycated hemoglobin (HbA1c) reflects average blood glucose levels over the preceding 2–3 months and is the gold standard for assessing long-term glycemic control. Multiple large-scale clinical trials have established the relationship between glycemic control and microvascular complications. The Diabetes Control and Complications Trial (DCCT) demonstrated that intensive glycemic control (mean HbA1c 7.3%) resulted in a 60% reduction in neuropathy compared to conventional therapy (mean HbA1c 9.1%). Similarly, the United Kingdom Prospective Diabetes Study (UKPDS) showed that intensive glucose control led to a 40% relative reduction in sensory nerve function deterioration as measured by biothesiometry. These landmark trials unequivocally established that lowering HbA1c reduces the risk of DPN.

Despite this well-established association, the precise correlation between specific glycemic parameters—including fasting blood glucose, postprandial blood glucose, and HbA1c—and the clinical manifestations and severity of DPN in T2DM patients requires further elucidation. Recent studies have demonstrated that higher HbA1c levels significantly correlate with increased neuropathy severity, and that elevated HbA1c is an independent risk factor for DPN. Furthermore, glycemic variability, assessed through coefficient of variation of fasting plasma glucose, has been associated with an increased risk of painful DPN. Nerve conduction studies have shown significant negative correlations between HbA1c and nerve conduction parameters, indicating that poor glycemic control directly impairs both motor and sensory nerve function.

Given the substantial clinical and public health burden of DPN, understanding the relationship between glycemic parameters and neuropathy manifestations is of paramount importance for risk stratification, early detection, and implementation of preventive strategies. This study was therefore undertaken to correlate the values of plasma glucose levels (fasting and postprandial) and HbA1c with the clinical manifestations of peripheral neuropathy in patients with type 2 diabetes mellitus.

This hospital-based cross-sectional observational study was conducted at the Department of Biochemistry of a tertiary care teaching hospital over a period of 18 months. The study protocol was reviewed and approved by the Institutional Ethics Committee.

Written informed consent was obtained from all participants after explaining the nature, purpose, and potential risks of the study in their native language. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.

Study Population

A total of 120 patients with type 2 diabetes mellitus attending the outpatient and inpatient departments of the hospital were enrolled in the study. Patients were recruited through consecutive sampling. The sample size was calculated based on expected correlation coefficient of 0.30 between HbA1c and neuropathy score, with 80% power and 5% level of significance, yielding a minimum sample size of 85 participants; 120 patients were enrolled to account for potential dropouts and incomplete data.

Inclusion and Exclusion Criteria

Inclusion criteria: Patients aged 30–70 years with a documented diagnosis of type 2 diabetes mellitus (as per American Diabetes Association criteria) for at least 2 years, who were willing to provide informed consent and undergo the required clinical and laboratory evaluations.

Exclusion criteria: Patients with type 1 diabetes mellitus; those with other causes of neuropathy (including alcoholic neuropathy, vitamin B12 deficiency, uremic neuropathy, hypothyroidism, HIV-associated neuropathy, or hereditary neuropathies); patients with acute diabetic complications (diabetic ketoacidosis, hyperosmolar hyperglycemic state); individuals with severe hepatic or renal impairment (serum creatinine > 2.0 mg/dL); pregnant or lactating women; patients on medications known to affect nerve function (e.g., chemotherapeutic agents, isoniazid); and those with any acute infection or inflammatory condition at the time of assessment.

Clinical Assessment

A detailed medical history was obtained from each participant using a structured proforma. Demographic data including age, gender, and occupation were recorded. Diabetes-related history included duration of diabetes, current treatment regimen (oral hypoglycemic agents, insulin, or combination), and presence of other microvascular complications (retinopathy, nephropathy). Anthropometric measurements including height, weight, and body mass index (BMI) were recorded.

Assessment of peripheral neuropathy: All participants underwent a comprehensive clinical neurological examination. The presence and severity of DPN were evaluated using two validated screening tools:

1. Toronto Clinical Neuropathy Score (TCNS): This instrument assesses neuropathic symptoms (pain, paresthesia, numbness), sensory testing (pinprick, temperature, light touch, vibration, and position sense), and reflex testing (ankle and knee reflexes). The maximum score is 19, with scores of 0–5 indicating no neuropathy, 6–8 mild neuropathy, 9–11 moderate neuropathy, and ≥12 severe neuropathy.
2. Michigan Neuropathy Screening Instrument (MNSI): The MNSI comprises a 15-item self-administered questionnaire and a brief physical examination (foot inspection, vibration perception, ankle reflexes, and monofilament testing). A total score of ≥ 2.5 on the physical examination component is considered indicative of DPN.

Clinical manifestations were classified as predominantly sensory, motor, sensorimotor, or autonomic based on history and examination findings.

Laboratory Investigations

After an overnight fast of 10–12 hours, 10 mL of venous blood was collected from each participant under strict aseptic conditions. Blood samples were collected in plain vacutainer tubes for serum separation. The following investigations were performed:

1. Fasting blood sugar (FBS): Estimated using the glucose oxidase-peroxidase (GOD-POD) method on an automated biochemistry analyzer (Beckman Coulter AU5800).
2. Postprandial blood sugar (PPBS): Blood samples were collected 2 hours after ingestion of a standardized meal, and glucose was estimated using the same method.
3. Glycated hemoglobin (HbA1c): Measured using high-performance liquid chromatography (HPLC) using the Bio-Rad D-100 system. The method is certified by the National Glycohemoglobin Standardization Program (NGSP). HbA1c was expressed as a percentage of total hemoglobin.
4. Other biochemical parameters: Serum creatinine, blood urea, and lipid profile were also estimated to characterize the study population and identify potential confounders.

Nerve Conduction Studies

Nerve conduction studies (NCS) were performed in a subset of 80 patients (40 with DPN and 40 without DPN) using a four-channel electromyography machine (Nicolet Viking Select). Standard techniques were employed for motor nerve conduction studies of the median, ulnar, tibial, and common peroneal nerves, and sensory nerve conduction studies of the median, ulnar, and sural nerves.

The following parameters were recorded: distal motor latency, motor nerve conduction velocity (MNCV), compound muscle action potential (CMAP) amplitude, sensory nerve conduction velocity (SNCV), and sensory nerve action potential (SNAP) amplitude. NCS were performed by a trained neurophysiologist who was blinded to the clinical and biochemical data of the participants.

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using SPSS software version 26.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (SD) or median with interquartile range, depending on the distribution. Categorical variables were expressed as frequencies and percentages. The normality of data distribution was assessed using the Kolmogorov-Smirnov test.

Comparisons between groups (DPN vs. no DPN) were performed using independent sample t-tests for normally distributed continuous variables and Mann-Whitney U tests for non-normally distributed variables. Categorical variables were compared using the chi-square test or Fisher's exact test, as appropriate. Pearson's correlation coefficient was used to assess the relationship between glycemic parameters (FBS, PPBS, HbA1c) and neuropathy severity scores (TCNS, MNSI) and nerve conduction parameters. Multivariate logistic regression analysis was performed to identify independent predictors of DPN. A p-value < 0.05 was considered statistically significant.

Baseline Characteristics of the Study Population

A total of 120 patients with type 2 diabetes mellitus were enrolled in the study, comprising 68 males (56.7%) and 52 females (43.3%). The mean age of the study population was 54.6 ± 10.8 years (range: 32–70 years). The mean duration of diabetes was 9.4 ± 6.2 years (range: 2–28 years). The majority of patients (71.7%) were on oral hypoglycemic agents, 15.8% were on insulin therapy, and 12.5% were on combination therapy. The overall prevalence of DPN in the study population, based on TCNS criteria, was 45.8% (55/120 patients). Among the DPN group, the severity distribution was as follows: mild neuropathy (TCNS 6–8) in 30.9% (17/55), moderate neuropathy (TCNS 9–11) in 41.8% (23/55), and severe neuropathy (TCNS ≥12) in 27.3% (15/55).

Table 1: Baseline Demographic and Clinical Characteristics

*Data expressed as mean ± SD or n (%). BMI: Body Mass Index. Statistically significant (p < 0.05).

Patients with DPN were significantly older (57.3 ± 10.2 vs. 52.4 ± 10.9 years, p = 0.012) and had a longer duration of diabetes (12.6 ± 6.8 vs. 6.8 ± 4.5 years, p < 0.001) compared to those without DPN. The prevalence of retinopathy and nephropathy was significantly higher in the DPN group, reflecting the concurrent microvascular complications associated with poor glycemic control.

Comparison of Glycemic Parameters

Table 2: Comparison of Glycemic Parameters between DPN and No DPN Groups

*Data expressed as mean ± SD. FBS: Fasting Blood Sugar; PPBS: Postprandial Blood Sugar; HbA1c: Glycated Hemoglobin. Statistically significant (p < 0.05).

Patients with DPN demonstrated significantly higher levels of all glycemic parameters compared to those without DPN. The mean FBS in the DPN group was 168.4 ± 42.6 mg/dL versus 142.3 ± 38.5 mg/dL in the non-DPN group (p < 0.001). PPBS was also significantly elevated in the DPN group (256.2 ± 58.4 vs. 218.7 ± 52.3 mg/dL, p < 0.001). Most notably, HbA1c levels were substantially higher in patients with DPN (9.6 ± 1.8% vs. 7.4 ± 1.5%, p < 0.001), representing a mean difference of 2.2%.

Correlation between Glycemic Parameters and Neuropathy Severity

Table 3: Correlation between Glycemic Parameters and Neuropathy Severity Scores

*TCNS: Toronto Clinical Neuropathy Score; MNSI: Michigan Neuropathy Screening Instrument; FBS: Fasting Blood Sugar; PPBS: Postprandial Blood Sugar; HbA1c: Glycated Hemoglobin. p < 0.001 for all correlations.

HbA1c showed the strongest positive correlation with both TCNS (r = 0.582, p < 0.001) and MNSI scores (r = 0.541, p < 0.001), indicating that higher HbA1c levels are associated with greater neuropathy severity. PPBS demonstrated moderate positive correlations with both scores (TCNS: r = 0.438, p < 0.001; MNSI: r = 0.402, p < 0.001), while FBS showed slightly weaker but still significant correlations (TCNS: r = 0.412, p < 0.001; MNSI: r = 0.385, p < 0.001).

HbA1c Distribution by Neuropathy Severity

Table 4: HbA1c Levels Stratified by Neuropathy Severity

Data expressed as mean ± SD. TCNS: Toronto Clinical Neuropathy Score.

A clear gradient was observed between HbA1c levels and neuropathy severity. Patients with severe neuropathy had a mean HbA1c of 11.2 ± 1.7%, compared to 9.8 ± 1.4% in moderate neuropathy, 8.2 ± 1.6% in mild neuropathy, and 7.4 ± 1.5% in those without neuropathy. The difference in HbA1c between severity groups was statistically significant (ANOVA p < 0.001).

Clinical Manifestations of DPN

Among the 55 patients with DPN, the predominant clinical type was sensory neuropathy, observed in 52.7% (29/55) of patients. Sensorimotor neuropathy was present in 30.9% (17/55), while pure motor neuropathy was observed in 16.4% (9/55). Autonomic symptoms were documented in 23.6% (13/55) of patients with DPN, often in combination with other types.

Table 5: Clinical Manifestations in Patients with DPN

Numbness (76.4%) and tingling (69.1%) were the most frequently reported sensory symptoms, followed by burning pain (49.1%) and loss of vibration sense (63.6%). Motor symptoms such as muscle weakness (32.7%) and gait disturbance (21.8%) were less common but contributed significantly to functional impairment.

Nerve Conduction Study Findings

Nerve conduction studies were performed in 80 patients (40 with DPN and 40 without DPN). Patients with DPN demonstrated significantly prolonged distal motor latencies, reduced motor nerve conduction velocities, and decreased CMAP and SNAP amplitudes across all tested nerves compared to those without DPN.

Table 6: Nerve Conduction Parameters in DPN vs. No DPN Groups

*MNCV: Motor Nerve Conduction Velocity; SNCV: Sensory Nerve Conduction Velocity; SNAP: Sensory Nerve Action Potential. Statistically significant (p < 0.001).

Correlation between HbA1c and Nerve Conduction Parameters

Table 7: Correlation between HbA1c and Nerve Conduction Parameters

*MNCV: Motor Nerve Conduction Velocity; SNCV: Sensory Nerve Conduction Velocity; SNAP: Sensory Nerve Action Potential. Statistically significant.

HbA1c showed significant negative correlations with all nerve conduction parameters, indicating that poorer glycemic control is associated with worse nerve function. The strongest correlation was observed between HbA1c and sural SNAP amplitude (r = -0.512, p < 0.001), followed by sural SNCV (r = -0.498, p < 0.001), suggesting that sensory nerves are particularly vulnerable to hyperglycemic damage.

Multivariate Logistic Regression Analysis

Multivariate logistic regression analysis was performed to identify independent predictors of DPN. After adjusting for age, gender, BMI, diabetes duration, hypertension, dyslipidemia, and treatment modality, the following factors emerged as significant independent predictors: HbA1c (OR: 2.84, 95% CI: 1.82–4.43, p < 0.001), diabetes duration (OR: 1.18, 95% CI: 1.08–1.29, p < 0.001), and age (OR: 1.06, 95% CI: 1.01–1.12, p = 0.018). For each 1% increase in HbA1c, the odds of having DPN increased by nearly 2.84-fold, underscoring the dominant role of glycemic control in neuropathy pathogenesis.

The present study demonstrates a strong and significant correlation between glycemic parameters—particularly HbA1c—and the presence, severity, and clinical manifestations of peripheral neuropathy in patients with type 2 diabetes mellitus. Our findings reveal that patients with DPN have significantly higher levels of FBS, PPBS, and HbA1c compared to those without neuropathy, with HbA1c showing the strongest association with neuropathy severity. These observations are consistent with the established paradigm that chronic hyperglycemia is the primary metabolic driver of diabetic neuropathy.

The prevalence of DPN in our study population was 45.8%, which aligns closely with global estimates indicating that up to 50% of patients with T2DM develop DPN during their disease course. This high prevalence underscores the substantial clinical and public health burden of this complication. The finding that patients with DPN had a significantly longer duration of diabetes (12.6 ± 6.8 vs. 6.8 ± 4.5 years) is consistent with the understanding that cumulative glycemic exposure over time is a critical determinant of neuropathy risk. The presence of other microvascular complications (retinopathy and nephropathy) in the DPN group further supports the concept of concurrent microvascular damage driven by shared pathogenic mechanisms.

The most compelling finding of this study is the strong positive correlation between HbA1c and neuropathy severity, as measured by both the TCNS (r = 0.582) and MNSI (r = 0.541). This correlation was dose-dependent, with a clear gradient observed across neuropathy severity categories: patients with severe neuropathy had a mean HbA1c of 11.2 ± 1.7% compared to 7.4 ± 1.5% in those without neuropathy. This observation is in agreement with the study by Nisintha et al., who reported that higher HbA1c levels significantly correlated with increased neuropathy severity (severe: 12.1 ± 1.3% vs. mild: 8.4 ± 2.0%; p = 0.002). Similarly, Zhang et al. identified HbA1c as a known risk factor for DPN, with elevated HbA1c levels independently associated with reduced nerve conduction velocities.

The correlation between HbA1c and nerve conduction parameters in our study provides objective electrophysiological evidence linking poor glycemic control to nerve dysfunction. The significant negative correlations between HbA1c and both motor and sensory nerve conduction parameters—particularly the sural SNAP amplitude (r = -0.512) and sural SNCV (r = -0.498)—indicate that sensory nerve fibers are especially susceptible to hyperglycemic injury. These findings are corroborated by recent studies demonstrating that HbA1c levels correlate with conduction velocities of tibial nerve motor fibers and sensory fibers of the ulnar, median, and sural nerves. Zhang et al. further demonstrated that the effect of increased HbA1c upon DPN, especially on conduction velocities of sensory fibers in the ulnar and sural nerves, may be partially mediated by decreased activated partial thrombin time (APTT), suggesting a complex interplay between glycemic control, coagulation, and nerve function.

The clinical manifestations of DPN observed in our study—predominantly sensory symptoms such as numbness (76.4%), tingling (69.1%), and loss of vibration sense (63.6%)—are consistent with the typical "length-dependent" pattern of diabetic neuropathy, where distal sensory nerve fibers are affected earliest and most severely. The predominance of sensory neuropathy (52.7%) over sensorimotor (30.9%) and pure motor (16.4%) types reflects the known pathophysiology, wherein sensory neurons, with their long axonal projections, are particularly vulnerable to metabolic and ischemic insults. Motor involvement, when present, typically occurs at later stages of the disease and contributes to muscle weakness and functional impairment.

The pathogenic mechanisms linking hyperglycemia to peripheral nerve damage are multifaceted. Chronic elevation of blood glucose activates the polyol pathway, leading to accumulation of sorbitol and fructose in Schwann cells and neurons, with concomitant depletion of myo-inositol and reduced Na⁺-K⁺-ATPase activity. Simultaneously, enhanced formation of advanced glycation end products (AGEs) leads to cross-linking of structural proteins and activation of pro-inflammatory pathways through RAGE signaling. These metabolic derangements, together with increased oxidative stress, mitochondrial dysfunction, and microvascular ischemia, converge to produce axonal degeneration, demyelination, and ultimately, neuronal apoptosis. Our finding that HbA1c correlates more strongly with neuropathy severity than FBS or PPBS may reflect the fact that HbA1c provides a more comprehensive measure of cumulative glycemic exposure, capturing both fasting and postprandial glucose excursions over an extended period.

The clinical implications of our findings are substantial. The strong association between HbA1c and DPN severity underscores the critical importance of stringent glycemic control in preventing and delaying the progression of neuropathy. The DCCT demonstrated that intensive glycemic control (mean HbA1c 7.3%) resulted in a 60% reduction in neuropathy compared to conventional therapy (mean HbA1c 9.1%). Similarly, the UKPDS showed that intensive glucose control led to a 40% relative reduction in sensory nerve function deterioration. These landmark trials, together with our findings, provide compelling evidence that maintaining HbA1c levels close to target (< 7%) is essential for neuropathy prevention. The dose-response relationship observed in our study suggests that even modest improvements in glycemic control may translate into meaningful reductions in neuropathy risk.

The identification of HbA1c as a strong independent predictor of DPN (OR: 2.84 per 1% increase) in multivariate analysis further emphasizes its utility as a risk stratification tool. Routine monitoring of HbA1c, combined with regular screening for DPN using validated instruments such as the TCNS or MNSI, may facilitate early identification of patients at risk, enabling timely interventions to prevent progression. Given that DPN is often asymptomatic in its early stages, such screening is of paramount importance for preventing the devastating consequences of advanced disease, including foot ulceration and amputation.

Several limitations of this study should be acknowledged. First, the cross-sectional design precludes the establishment of causal relationships, although the well-established biological plausibility and evidence from longitudinal trials support the observed associations. Second, the study was conducted at a single tertiary care center, which may limit the generalizability of findings to community-based or primary care populations. Third, the relatively small sample size, particularly for subgroup analyses based on neuropathy severity, may have limited statistical power to detect smaller differences. Fourth, we did not assess glycemic variability, which emerging evidence suggests may independently contribute to DPN risk beyond mean HbA1c. Fifth, we did not evaluate other potential confounders such as physical activity, dietary patterns, or genetic factors that may influence neuropathy risk. Finally, the use of clinical scoring systems, while validated, may be subject to inter-observer variability.

Future research should focus on longitudinal studies to establish the temporal relationship between glycemic parameters and DPN progression, and to evaluate whether interventions targeting glycemic variability, in addition to mean HbA1c, confer additional neuroprotective benefits. Studies incorporating advanced neurophysiological techniques and biomarkers of nerve injury may provide further insights into the pathogenic mechanisms linking hyperglycemia to peripheral nerve damage.

This study demonstrates that poor glycemic control, as reflected by elevated HbA1c and blood glucose levels, is strongly correlated with the presence and severity of peripheral neuropathy in patients with type 2 diabetes mellitus. HbA1c shows the strongest correlation with neuropathy severity and serves as a reliable biomarker for predicting neuropathy risk. Sensory neuropathy, characterized by numbness, tingling, and loss of vibration sense, is the predominant clinical manifestation.

Nerve conduction studies confirm that poor glycemic control is associated with significant impairment of both motor and sensory nerve function. These findings underscore the critical importance of stringent glycemic control—targeting HbA1c levels < 7%—in preventing and delaying the progression of diabetic peripheral neuropathy. Routine screening for DPN using validated instruments, combined with regular monitoring of HbA1c, should be an integral component of diabetes care to facilitate early detection and intervention, thereby reducing the substantial morbidity associated with this debilitating complication.

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