Saudi Journal of Kidney Diseases and Transplantation

: 2016  |  Volume : 27  |  Issue : 5  |  Page : 893--901

Renal transplantation: Assessment of "at risk" diabetic foot and recommendations for mitigation

OP Prajapati1, AK Verma1, RK Sharma2, M Sabaretnam1,  
1 Department of Endocrine Surgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
2 Department of Nephrology and Renal Transplantation, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

Correspondence Address:
O P Prajapati
Department of Endocrine Surgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh


We conducted a prospective study (between November 2013 and January 2015) to identify DQfoot at riskDQ in the diabetic renal transplant patients at a Tertiary Care Hospital in India. Patients (151) were divided into three groups: diabetic transplant recipients (n = 42), new onset diabetes after transplantation (NODAT) (n = 59), and controls (nondiabetic renal transplant recipients) (n = 50). Foot neuropathy and vasculopathy were assessed by standard methods. Patients with DQat riskDQ feet were given foot care advice. Of the 151 patients, 144 patients were male and seven were female with a male:female ratio of 20:1. Peripheral neuropathy was present among 42.9% of diabetic transplant patients, 35.6% of NODAT patients, and 12% of control patients. Vasculopathy was present in 28.6% of diabetic transplant patients, 23.7% of NODAT patients, and 2% of control patients. On multivariate analysis, patientSQs age, mean time interval since transplantation, and HbA1c levels were significantly associated with neuropathy, whereas the duration of diabetes and vibration perception threshold was associated with vasculopathy. After undergoing renal transplantation, a significant number of diabetic and NODAT patients has their DQfeet at riskDQ who in future may develop full-blown lesions of the diabetic foot. Proper advice to patients and information to the treating doctor helps to mitigate the risk.

How to cite this article:
Prajapati O P, Verma A K, Sharma R K, Sabaretnam M. Renal transplantation: Assessment of "at risk" diabetic foot and recommendations for mitigation.Saudi J Kidney Dis Transpl 2016;27:893-901

How to cite this URL:
Prajapati O P, Verma A K, Sharma R K, Sabaretnam M. Renal transplantation: Assessment of "at risk" diabetic foot and recommendations for mitigation. Saudi J Kidney Dis Transpl [serial online] 2016 [cited 2021 Oct 22 ];27:893-901
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Full Text


Diabetes mellitus is increasing by epidemic proportions in various countries of the world, particularly in India. Type 2 diabetes accounts for 90% of diabetics in India. [1] About 12-25% of diabetic patients develop foot lesions sometime in their lifetime [2] and around 2% of these undergo minor or major amputation. [3] Peripheral neuropathy, peripheral arterial disease (PAD), foot ulceration, and lower extremity amputations are twice as common in diabetics as compared to nondiabetics, and the incidence may still be higher in diabetics undergoing renal transplantation [4] for the end-stage renal disease (ESRD). Uncontrolled diabetic neuropathy and vasculopathy may lead to many foot complications in the lifetime of these patients. [5],[6] Even in the face of non-obstructed vessels, impaired microcirculation diminishes blood supply to the foot. [7]

To date, there is no study available in the literature, assessing "foot at risk" among totally asymptomatic diabetic renal transplant recipients.

This study aims at identifying "foot at risk" in these asymptomatic renal transplant patients by detecting subtle neurovascular insufficiency at an early stage and to suggest corrective and/or preventive measures in these patients.


This prospective study was conducted between November 2013 and January 2015 (15 months) at the transplant clinic of Department of Nephrology and Renal Transplantation and Department of Endocrine Surgery at the Sanjay Gandhi Postgraduate Institute of Medical Science, India, a tertiary care center. All consecutive patients from one transplant unit were enrolled.

Neuropathy was assessed by three methods: diabetic neuropathy symptom (DNS) scoring [8] [Table 1], Semmes-Weinstein monofilament (SWMF), [9] and vibration perception threshold (VPT). [10] Coarse touch was estimated by SWMF-10 (DSL Dhansai Laboratory, India) which gives pressure equivalent to 10 g. [9] The vibration perception component of neuropathy (VPT) was measured as Volts using a Standard Biothesiometer (Sensitometer VPT. digi. DSL Dhansai Laboratory, India). [10],[11] For the assessment of vasculopathy, ankle brachial index (ABI) was calculated using hand-held Doppler (Minidop ES 100VX Pocket Doppler, Hadeco, Japan). The minimum ABI from either foot was taken as reference value for a given patient. [12] An ABI of 0.9 or above indicated a normal flow, whereas values below 0.9 were indicative of impaired blood flow and taken as abnormal. [13]{Table 1}

Ethical clearance was obtained from the Institute's Ethical Committee. A standardized per forma, as well as patient instruction sheet, was designed and printed. Patient's demographics, clinical and investigative details, and medical therapy received were recorded. Other parameters recorded included serum creatinine, HbA[1]c, type of diabetic control, neurovascular insufficiency, episodes of graft rejection and therapy, immunosuppression (tacrolimus-based or cyclosporine-based), etc. Diabetic foot advice has been handed over to the patient and explained also.

All transplant patients were reviewed at three monthly intervals regarding renal graft function and simultaneously also underwent their foot assessment. Study patients comprised three groups: diabetics have undergone renal transplantation (diabetic transplant group), new onset diabetes after transplantation (NODAT) group, and nondiabetic renal failure patients having undergone renal transplantation (control group).

Patients having preexisting lesions of diabetic foot in the form of ulcers, callus and deformity, gangrene, etc., were excluded from the study and were referred to the Department of Endocrine Surgery for appropriate foot care. Patients with incomplete follow records were also excluded from the analysis.

Patient's demographics, clinical and investigative details, and medical therapy received were recorded. Other parameters recorded included serum creatinine, HbA [1] c, type of diabetic control, neurovascular insufficiency, episodes of graft rejection and therapy, immunosuppression (tacrolimus-based or cyclosporine-based), etc. Information about patients having "foot at risk" was communicated to the concerned renal transplant physician.

 Statistical Analysis

Statistical analysis was done using the Statistical Package for the Social Sciences for Windows (SPSS) software version 17 for Windows in consultation with the Department of Biostatistics. The continuous variables among the two groups were compared using ttest/Mann-Whitney U-test (based on normality). Chi-square test was used to compute association between categorical variables among two groups. Where appropriate, univariate, and multivariate analyses were done using linear regression. ANOVA was also used to compare the values over the visits. P <0.05 has been considered significant.


One hundred and fifty-one patients were eligible for the study, 42 in the diabetic transplant group, 59 in the NODAT patients group, and 50 in the control group (nondiabetic transplants patients). One hundred and forty-four patients were male and seven were female with a male:female ratio of 20:1. The mean age in diabetic transplant group was 45.7 ± 11.9 years (range: 23-68 years), in NODAT group was 42.5 ± 10.8 years (range: 18-68 years), and 37.0 ± 10.0 years (range 16-67 years) in the control group. The mean age of diabetic transplant and NODAT groups was significantly higher than the control group (P <0.001 and P = 0.01, respectively). Although the mean age of the NODAT group was lower than the diabetic transplant group, this was no statistically significant.

The mean duration of diabetes before undergoing renal transplant was 85 ± 62.8 (range: 10-234 months) in the diabetic group. The median duration of diabetes in this group until the first assessment was 105.5 months (range: 37-348 months) which was much higher than in NODAT patients (34.0 months, range: 2- 244 months) as expected. Mean interval between transplantation and the start of the study was 41.5 ± 37.3 months (range: 3-147 months) in diabetic group, 65.5 ± 62.3 months (range: 3-244 months) in NODAT group (P = 0.035), and 67.5 ± 60.3 (range: 2-230 months) in the control group (P = 0.028). However, on comparing the control group with NODAT group, no statistically significant difference was observed (P = 0.853).

Of the diabetic patients, 61.4% (n = 62) patients had good diabetic control (HbA1c <7) (good diabetic control group) and 39 patients (38.6%) had poor diabetic control (HbA1c >7) (poor diabetic control group).

Diabetes was controlled on oral hypoglycemic agents (OHAs) (16.7% in the diabetic group, 27.1% in NODAT group), insulin (78.6% in the diabetic group, 62.7% in NODAT group), and diet alone (4.7%% in the diabetic group, 10.2% in NODAT group). On comparing overall diabetic control, higher number of patients on insulin had good diabetic control (n = 51, 67%) than those on OHA (n = 8, 42%), the difference being statistically significant (P <0.05).

Peripheral neuropathy as assessed by VPT was present in 42.9% of the diabetic transplant patients, 35.6% of NODAT patients, and in only 12% of control patients. Neuropathy assessed by SWMF was present in 35.7% of the diabetic transplant patients, in 30.5% of NODAT patients, and in only 10% of control patients [Table 2].{Table 2}

Mean VPT was 22.7 ± 12.9 volt (range: 5.3-51) in diabetic transplant group, 21.1 ± 11.9 volt (range: 5.4-49.1) in NODAT group, and 11.8 ± 7.2 volt (range: 3.8-30.9) in the control group. The difference in mean VPT between diabetic transplant and control and between NODAT and control patients was statistically significant (P <0.001), whereas no statistically significant difference was found between diabetic and NODAT patients (P = 0.35).

When we analyzed the entire group on the basis of whether they have normal or abnormal VPT, we find a significant difference in DNS score (P <0.05) and the overall and in SMWF score (P <0.05).

A total of 15 patients were found to have neuropathy in the good diabetic control group, of whom, 11 were found to have neuropathy by all the three tests (DNS, SWMF, and VPT). Twelve patients showed the evidence of neuropathy by two modalities (SWMF and VPT) and 13 by only one modality (DNS and SWMF) or VPT singly neuropathy detection modalities showed good to excellent correlation between DNS and monofilament (correlation coefficient 0.884, P <0.001), between DNS and VPT (0.684, P <0.001) as well, and between monofilament and VPT (correlation coefficient 0.693, P <0.001).

Despite comprehensive diabetic management, 38.6% of the patients (n = 39) had bad diabetic control (HbA1c ≥7). In the overall bad diabetic control group (diabetic transplant + NODAT, n = 39), significantly higher number of patients were managed on insulin (64.1%, n = 25) versus 11 patients (28.2%) were managed on OHAs (P <0.05). Total 24 patients were found to have neuropathy in this group. Of which 18 patients were found to have neuropathy by all the three tests (DNS, SWMF, and VPT), 20 patients showed evidence of neuropathy by two modalities (SWMF and VPT), while only VPT showed the presence of neuropathy in 24 patients. DNS showed neuropathy in 19 and SWMF in 20 patients when applied singly. Correlation coefficient between VPT and SWMF for bad control group was 0.811 (strong positive correlation, P <0.001) and between VPT and DNS was 0.693 (good positive correlation, P <0.001), whereas between SWMF and DNS was 0.778 (good positive correlation, P <0.001).

On further perusal of DNS scoring system, only four patients (6.5%) had moderate to severe neuropathy (Grade 2-4) in the good diabetic control group, whereas seven patients (17.9%) showed moderate to severe neurpathy in the bad diabetic control group, the difference being statistically significant (P <0.05). This observation indicates that when diabetic control is good, only 6% patients do exhibit severe neuropathy. However, when diabetic control becomes bad, the incidence rises 3-fold to around 18%. When the diabetic control is good, the incidence of neuropathy is less (24.1%), but when the control is bad, the incidence of neuropathy is more (61.5%).

On univariate analysis, neuropathy was significantly associated with patient's age, duration of diabetes mellitus, mean time interval between transplant and assessment, and HbA1c level, whereas on multivariate analysis, only patient's age, mean time interval between transplant and assessment, and HbA1c level were significantly associated [Table 3].{Table 3}

Vasculopathy, as assessed by ABI, was present in 28.6% (n = 12) patients of diabetic transplant group, 23.7% (n = 14) in NODAT patients group, and only one patient (2%) belonging to control group. ABI in this control patient was 0.79 [Table 4].{Table 4}

Mean ABI among diabetic transplant group (0.94 ± 0.13) (range: 0.67-1.45) was significantly higher than controls (1.00 ± 0.06) (range: 0.79-1.18). There were no significant differences between the diabetic and NODAT groups or between the NODAT and control groups.

The overall incidence of vasculopathy in bad diabetic control group was 35.9% (n = 14) compared to 19.4% (n = 12) in good diabetic control group. The mean ABI in good diabetic control group and bad diabetic control group was 0.97 ± 0.09 and 0.94 ± 0.16, respectively, and was not statistically different (P >0.05). On univariate analysis, significant risk factors associated with vasculopathy were patient's age, duration of diabetes mellitus, HbA1c level, and VPT, whereas on multivariate analysis, only duration of diabetes mellitus and VPT could be identified as significant risk factors [Table 5].{Table 5}

Type of immunosuppression versus neuropathy and vasculopathy

Neuropathy was present in 32.5 % (11/34) of patients treated with cyclosporine-based immunosuppression, whereas it was present in 28.6% (33/115) of patients treated with tacrolimus-based immunosuppression, the difference was not statistically significant (P = 0.681). Vasculopathy was present in 20.5% (7/34) of patients treated with cyclosporine-based immunosuppression, whereas it was present in 16.5% (19/115) of patients treated with tacrolimusbased immunosuppression, again the difference was not statistically significant (P = 0.583).

Effect of foot care education and glycemic control education on neuropathy and vasculopathy

On testing, all patients exhibiting evidence of neuropathy and/or vasculopathy received oral, as well as printed instructions about foot care. This information was also entered in the patients'outpatient department (OPD) records for the benefit of incharge transplant physician.

On repeated testing using ANOVA, VPT value was found decreasing, and ABI was found increasing over the time suggestive of improvement in neuropathy, as well as vasculopathy. The difference between the first and second visit was statistically significant (P <0.05), but the difference between the second and third visit was statistically insignificant, which indicates a significant improvement in neuropathy and vasculopathy at three months during follow-up. The improvement continued over the next six months, but the rate of improvement decreased and also lost the statistical significance. This improvement was observed across the board in all the three groups and also groups categorized as good and bad diabetic control groups. This observation suggests the impact of education was maximum initially but later withered away, implying the need of aggressive foot care education at each OPD visit. Incidentally, glycemic control also improved with time as indicated by decreasing levels of HbA1c over the visits by repeated testing using ANOVA.

Effect of antirejection therapy on neuropathy and vasculopathy

During this study period, 11 patients experienced episodes of graft rejection which was managed by antirejection therapy involving methylprednisolone, antithymocyte globulin, and IgG. All these patients had VPT values >25 volts indicating the presence of neuropathy. These patients also had bad diabetic control in 80% of patients and vasculopathy in 45% (5/11) of the patients.

Relationship between neuropathy and vasculopathy

When a scatter plot was made keeping ABI on X-axis and VPT on Y-axis and a trend line was drawn, it showed an inverse relationship between ABI and VPT [Figure 1]. A line drawn vertically from ABI value 0.9 (below which ABI starts becoming abnormal) intersects the trend line at a point which corresponds to a VPT value of 22.5 volts.{Figure 1}


It is quite sad and depressing to find a lack of studies about the condition of feet in renal transplant patients with diabetes. By observing neuropathic ulcers in the feet of few diabetic patients with ESRD, who had undergone renal transplantation at our center, the idea of assessing neurovascular insufficiency in these patients came in the mind so as to identify patients having "foot at risk." It is very disheartening for a transplant physician to see his patient getting maimed or die due to a preventable disease with an excellently functioning renal allograft.

The mean age of diabetic transplant and NODAT patients was significantly higher than control patients. Due to small sample size of females in each group, no statistical test could be applied. The results showed that neuropathy was present in approximately 40% of patients belonging to diabetic transplant and NODAT group, whereas in the control group, it was 12%. Peripheral neuropathy in nondiabetic transplant patients has been well-described by many workers due to causes including uremic neuropathy, dialysis neuropathy, and drug induced (tacrolimus and cyclosporine) in the literature. [14],[15],[16],[17],[18],[19],[20],[21] Although these factors are common to all the groups, the addition of diabetes causes a quantum jump in the incidence of neuropathy. When neuropathy was further analyzed on the basis of good or bad diabetic control, it was astonishing to find that a majority of patients having bad diabetic control suffered from neuropathy and the neuropathy tended to be more severe in nature.

It was reassuring to find a high degree of statistically significant correlation between testing modalities used to evaluate neuropathy. Although DNS scoring and monofilament testing were qualitative in nature yet had an excellent correlation with VPT, which also provided quantification of neuropathy. The first two being simple in nature but are quite effective in detecting neuropathy as a screening tool in an OPD.

Although the duration of diabetes is less in NODAT group as compared to diabetic transplant group, but the incidence of neuropathy is almost similar in both the groups. This may be due to the fact that NODAT group had been exposed to a prolonged period of metabolic insult because of prolonged immunosuppression. Drugs including tacrolimus and cyclosporine which are used to prevent graft rejection after transplantation are associated with neuropathy of varied incidence reported in the literature. [17],[18],[19],[20],[21] With cyclosporine, the incidence varies from 10% to 40%. [17],[18],[19] However, in the case of tacrolimus, it is controversial; some studies report that it improves neuropathy, whereas certain other studies report that it causes neuropathy with the incidence to the tune of 5-30%. [20],[21] In our study, the incidence of neuropathy was similar in both cyclosporine and tacrolimus-based immunosuppression. This might be due to difficulty in achieving euglycemia with tacrolimus and corticosteroid which might further result in progression of neuropathy. Although PAD is very common in diabetic patients, it remains grossly under-recognized. [22] Diagnosis of PAD is often difficult when it is associated with peripheral neuropathy because neuropathy could mask the pain and thus recognition of PAD. [23] The prevalence of PAD in our study was 28.6% in diabetic transplant, 23.7% in NODAT, and only 2% in control patients. In a review study, the reported prevalence of PAD ranges between 9.5% and 13.6% in diabetic patients versus 4% in the general population [13] and in other studies, it is reported between 10% and 30% [24],[25],[26] in diabetic patients. Although, in our study, we have used ABI, the sensitivity of which remains less in diabetic patients than PAD due to other causes, implying that the actual prevalence may be somewhat more than what has been indicated. Potential pathophysiologic mechanisms by which decreased creatinine clearance in chronic renal disease might predispose to PAD include altered calcium, phosphorus, lipoprotein, and homocysteine metabolism, as well as altered inflammatory and coagulation pathways. [27] Because of corticosteroids, glycemic control becomes difficult and most of the time remains bad. This further contributes in the propagation of preexisting vasculopathy.

As per the standard teaching in medicine, neuropathy once set-in does not improve with time. Surprisingly, our study shows an objective improvement in neuropathy, as well as vasculopathy. Simultaneously, within this period falling HbA1c values also indicated a better glycemic control. In our view, better metabolic control contributed toward an improvement in neuropathy and vasculopathy. Hence, it can be surmised that if neuropathy and vasculopathy can be detected at an early stage in renal transplant patients, it may be reversed by achieving a tighter glycemic control. Simultaneously, by giving foot care education to these patients, we can prevent "foot at risk" to progress into a frank diabetic foot.

From the scatter plot in [Figure 1], it is obvious that neuropathy and vasculopathy are inversely related to each other. It was interesting observation to find out the corresponding VPT at a point when ABI starts becoming abnormal, indicating the value of VPT at which vasculopathy has also started setting in. Thus, it can be deduced that if a patient shows a VPT of 22 or above in a transplant OPD, the physician should be careful to look for vasculopathy and start appropriate corrective measure.

During graft rejection, high dose of steroid is used, and it is evident from our study that institution of anti-rejection therapy causes worsening of glycemic control, as well as worsening of neuropathy and vasculopathy.

 Limitation of the study

Only some of the components of somatic neuropathy could be detected did not investigate temperature, fine touch, and autonomic neuropathy because of various constraints of space, availability of equipment, etc.


Majority of the diabetic transplant and NODAT patients have early and detectable yet reversible neuropathy. DNS and SWMF testing are simple yet highly reliable tools to detect neuropathy in the OPD. When VPT reaches 22 volts, vasculopathy also starts to set-in. Tighter glycemic control is imperative for improving and reversing early onset neuropathy and vasculopathy, while foot care education is necessary for preventing "foot at risk" to develop diabetic foot lesions. Patients who experienced rejection episodes and were given antirejection therapy have more chance of developing neuropathy and vasculopathy It is strongly recommended that renal transplant clinics should compulsorily employ a chiropodist/podiatrist to detect "foot at risk" so as to prevent long-term diabetic foot complications which in future may escalate to cause severe foot lesions, loss of limb or life. The old adage "an ounce of prevention is better than a pound of cure" still holds true.


1Mohan V, Sandeep S, Deepa R, Shah B, Varghese C. Epidemiology of type 2 diabetes: Indian scenario. Indian J Med Res 2007; 125:217-30.
2Singh N, Armstrong DG, Lipsky BA. Preventing foot ulcers in patients with diabetes. JAMA 2005;293:217-28.
3Margolis D, Malay DS, Hoffstad OJ, et al. Prevalence of Diabetes, Diabetic Foot Ulcer, and Lower Extremity Amputation among Medicare Beneficiaries, 2006 to 2008. Diabetic Foot Ulcers. Data Points #1 (Prepared by the University of Pennsylvania DEcIDE Center, under Contract No. HHSA29020050041I). AHRQ Publication No. 10(11)-EHC009-EF. Rockville, MD: Agency for Healthcare Research and Quality; February, 2011.
4Ritz E, Orth SR. Nephropathy in patients with type 2 diabetes mellitus. N Engl J Med 1999;3 41:1127-33.
5Pecoraro RE, Reiber GE, Burgess EM. Pathways to diabetic limb amputation. Basis for prevention. Diabetes Care 1990;13:513-21.
6Lavery LA, Armstrong DG, Vela SA, Quebedeaux TL, Fleischli JG. Practical criteria for screening patients at high risk for diabetic foot ulceration. Arch Intern Med 1998;158: 157-62.
7Pham HT, Economides PA, Veves A. The role of endothelial function on the foot. Microcirculation and wound healing in patients with diabetes. Clin Podiatr Med Surg 1998;15:85-93.
8Meijer JW, Smit AJ, Sonderen EV, Groothoff JW, Eisma WH, Links TP. Symptom scoring systems to diagnose distal polyneuropathy in diabetes: The Diabetic Neuropathy Symptom score. Diabet Med 2002;19:962-5.
9Feng Y, Schlösser FJ, Sumpio BE. The Semmes Weinstein monofilament examination as a screening tool for diabetic peripheral neuropathy. J Vasc Surg 2009;50:675-82.
10Garrow AP, Boulton AJ. Vibration perception threshold - A valuable assessment of neural dysfunction in people with diabetes. Diabetes Metab Res Rev 2006;22:411-9.
11Young MJ, Breddy JL, Veves A, Boulton AJ. The prediction of diabetic neuropathic foot ulceration using vibration perception thresholds. A prospective study. Diabetes Care 1994;17:557-60.
12Kim ES, Wattanakit K, Gornik HL. Using the ankle-brachial index to diagnose peripheral artery disease and assess cardiovascular risk. Cleve Clin J Med 2012;79:651-61.
13Potier L, Abi Khalil C, Mohammedi K, Roussel R. Use and utility of ankle brachial index in patients with diabetes. Eur J Vasc Endovasc Surg 2011;41:110-6.
14Krishnan AV, Kiernan MC. Uremic neuropathy: Clinical features and new pathophysiological insights. Muscle Nerve 2007;35:27390.
15O'Regan J, Walsh R, Kelly D, Plant L, Eustace J, McNamara B. Neuropathy in the hemodialysis population: A review of neurophysiology referrals in a tertiary center. Ren Fail 2012;34:538-41.
16Mambelli E, Barrella M, Facchini MG, et al. The prevalence of peripheral neuropathy in hemodialysis patients. Clin Nephrol 2012;77: 468-75.
17Ponticelli C, Campise MR. Neurological complications in kidney transplant recipients. J Nephrol 2005;18:521-8.
18Basic-Jukic N, Basic-Kes V, Kes P, FuricCunko V, Bacic-Baronica K. Neurological complications in renal transplant recipients. Acta Med Croatica 2008;62 Suppl 1:76-81.
19Bechstein WO. Neurotoxicity of calcineurin inhibitors: Impact and clinical management. Transpl Int 2000;13:313-26.
20Wu G, Weng FL, Balaraman V. Tacrolimusinduced encephalopathy and polyneuropathy in a renal transplant recipient. BMJ Case Rep 2013;2013. pii: Bcr2013201099.
21Sayin R, Soyoral YU, Erkoc R. Polyneuropathy due to cyclosporine A in patients with renal transplantation: A case report. Ren Fail 2011;33:528-30.
22Hirsch AT, Criqui MH, Treat-Jacobson D, et al. Peripheral arterial disease detection, awareness, and treatment in primary care. JAMA 2001;286:1317-24.
23Gregg EW, Sorlie P, Paulose-Ram R, et al. Prevalence of lower-extremity disease in the US adult population >=40 years of age with and without diabetes: 1999-2000 national health and nutrition examination survey. Diabetes Care 2004;27:1591-7.
24Maser RE, Steenkiste AR, Dorman JS, et al. Epidemiological correlates of diabetic neuropathy. Report from Pittsburgh Epidemiology of Diabetes Complications Study. Diabetes 1989;38:1456-61.
25Pradeepa R, Rema M, Vignesh J, Deepa M, Deepa R, Mohan V. Prevalence and risk factors for diabetic neuropathy in an urban South Indian population: The Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med 2008;25:407-12.
26Rani PK, Raman R, Rachapalli SR, Pal SS, Kulothungan V, Sharma T. Prevalence and risk factors for severity of diabetic neuropathy in type 2 diabetes mellitus. Indian J Med Sci 2010;64:51-7.
27O'Hare A, Johansen K. Lower-extremity peripheral arterial disease among patients with end-stage renal disease. J Am Soc Nephrol 2001;12:2838-47.