• Users Online: 204
  • Print this page
  • Email this page


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2017  |  Volume : 8  |  Issue : 3  |  Page : 86-91

QT corrected for heart rate and qtc dispersion in Gujarati type 2 diabetics predominantly using preventive pharmacotherapy and with very low electrocardiogram left ventricular hypertrophy


1 Department of Physiology, GMC, Bhavnagar, Gujarat, India
2 Department of Medicine, GMC, Bhavnagar, Gujarat, India

Date of Web Publication29-Dec-2017

Correspondence Address:
Jayesh Dalpatbhai Solanki
Department of Physiology, Fourth Floor, Government Medical College, Bhavnagar, Bhavnagar - 364 001, Gujarat
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jod.jod_25_17

Rights and Permissions
  Abstract 


Background: There is a rising trend in the incidence of type 2 diabetes mellitus, and hyperglycaemia is known to cause cardiac dysautonomia, which may lead to life-threatening arrhythmias. It can be screened by simple electrocardiogram (ECG)-based QTc (QT corrected for heart rate) and QTd (QTc dispersion) indicating cardiac repolarisation abnormality. We studied QTc and QTd intervals in treated type 2 diabetics (T2D), testing the effect of age, gender, duration and control of disease. Materials and Methods: We conducted a cross-sectional study in a tertiary care teaching hospital of Gujarat, India, on 199 T2D (67 males and 132 females). Standard 12-lead ECG was recorded to derive QTc by Bazett's formula, QTd and ECG left ventricular hypertrophy (LVH). QTc >0.43 s in male and >0.45 s in female, QTd >80 msec were considered abnormal. Results: T2D (mean age 56 years, duration 6 years, coexisting hypertension 69%, glycaemic control 32% and use of β-blockers 56%) had QTc and QTd abnormality prevalence 15% and 20% respectively with ECG LVH prevailing in 3%. Male gender, poor glycaemic control and increased duration had negative impact on QT parameters with statistical significance only for first two and not for all results. Conclusion: Our study showed low-to-moderate prevalence of prolonged QTc and QTd, qualitatively more than quantitatively, in T2D with very low LVH and high prevalence of preventive pharmacotherapy, associated with male gender and glycaemic control. It underscores high risk of repolarisation abnormality, though moderate, that can be further primarily prevented by early screening and strict disease control.

Keywords: Diabetes, hyperglycaemia, hypertrophy, left ventricular, repolarisation


How to cite this article:
Solanki JD, Patel KJ, Lalwani N, Mehta HB, Shah CJ, Lakhtaria MN. QT corrected for heart rate and qtc dispersion in Gujarati type 2 diabetics predominantly using preventive pharmacotherapy and with very low electrocardiogram left ventricular hypertrophy. J Diabetol 2017;8:86-91

How to cite this URL:
Solanki JD, Patel KJ, Lalwani N, Mehta HB, Shah CJ, Lakhtaria MN. QT corrected for heart rate and qtc dispersion in Gujarati type 2 diabetics predominantly using preventive pharmacotherapy and with very low electrocardiogram left ventricular hypertrophy. J Diabetol [serial online] 2017 [cited 2018 Jan 22];8:86-91. Available from: http://www.journalofdiabetology.org/text.asp?2017/8/3/86/222086




  Introduction Top


There is alarming rise of type 2 diabetes mellitus (T2DM) in India, a disease having multiple unfavourable effects on the heart.[1] There is suboptimal disease control, lack of awareness and negligence towards early screening or primary prevention of various known cardiovascular aftermaths of type 2 diabetes.[2] Abnormal cardiac repolarisation is seen in uncontrolled diabetics that can progress to life-threatening arrhythmia.[3] However, same can be diagnosed by simple electrocardiogram (ECG)[4]-based QTc (QT corrected for heart rate) and QTd (QTc dispersion) and prevented by pharmacotherapy.[5] With increased duration of disease,[6] poor glycaemic control [6] and in the presence of various risk factors abnormality further worsens. Against this background, we quantified QT parameters in uncomplicated type 2 diabetics (T2D) and studied various correlates for it.


  Materials and Methods Top


Study design

This cross-sectional study was conducted in the Medicine department in association with Physiology department of Government Medical College, Bhavnagar, Gujarat, India.

Study subjects

After approval from the Institutional ethical Committee and written informed consent from each participant, volunteers were recruited for this study. Of a total number of participants who attended the outdoor clinic, all the adult participants were screened for the presence of type 2 diabetes. Participants coming to the clinic with record of treatment of diabetes were also included in this screening for confirmation. Of a total number of patients with type 2 diabetes, observed during the recruitment period (n = 400), 199 patients were consecutively selected for this study. Sample size was calculated by software Raosoft (Raosoft, Inc. free online software, Seattle, WA, USA). A sample of 199 participants for a population of 6 lakh with 7.33% prevalence of T2DM in our region gave us 95% confidence level, leaving 5% margin of error.

Inclusion and exclusion criteria

We enrolled T2D, with duration of at least 1 year and known current glycaemic control, aged 30–70 years, of either sex, with or without hypertension taking treatment (except insulin) regularly (through chart review), ready for written consent.

Exclusion criteria were those patients with duration <1 year of diabetes (n = 18), taking treatment of diabetes irregularly (n = 17), age >70 years (n = 140), chronic dysentery (n = 0), patients having cancer (n = 0), chronic kidney failure (n = 4), type 1 diabetes (n = 30), past history of cardiovascular intervention, on pacemaker (n = 0), drug therapy influencing autonomic function other than β-blocker (n = 70) and non-volunteers (n = 2) were excluded. None of the participants was using dipeptidyl peptidase 4 inhibitors.

Collection of data

After a 5-min rest, a blood pressure (BP) was recorded in a sitting position, on the right arm with a standard mercury manometer. Every participant had two readings, with the average of these reading recorded as the resting BP. To minimise measurement errors, one individual was assigned to measure BP for all the participants in both the groups. In accordance with the WHO guidelines, if a BP of more than ≥140/90 mmHg was recorded, a repeat measurement was obtained after a 5-min rest, with the subject in a supine position.

QT corrected for heart rate measurement[7]

We used 12-channel ECG machine to record strip ECG with standard norms. Participants were asked to lie in supine position, and 12-lead ECG was recorded on ECG machine. QT interval and RR interval were measured manually from the ECG strip for 10 successive readings. QT interval was measured using tangent method. RR interval was measured from one R-wave peak to another R-wave peak. QTc intervals were derived using Bazett's formula and average of 10 results was taken for each participant. Seven cases were discarded since lead II had artefact or shallow T -wave as well as difficult measurement of the QT.

Bazett's formula:

QTc = QT

√RR

No correction was used if heart rate was <60.

ECG left ventricular hypertrophy (LVH) criteria [8]:

We used the Cornell voltage criteria to define LVH which is as follows-

  1. S in V3 + R in aVL >28 mm (men)
  2. S in V3 + R in aVL >20 mm (women).


Defining norms:

We defined glycaemic control as per criteria laid by the American Diabetes Association 2014,[9] and good glycaemic control was defined as (1) FPG ≤126 mg% and (2) PP2BG ≤180 mg%.

QTc and QTd were analysed in two ways:

  1. Quantitative comparison-comparing absolute QT values
  2. Qualitative comparison-comparing frequency of normal or prolonged QT defined as per standard cutoffs.


QTc value >0.43 s in male and >0.45 s in female and QTd value >80 ms were considered abnormal.[10]

Systolic BP (SBP) <140 mmHg and diastolic BP <90 mmHg was defined as controlled BP.

Statistical analysis

The data were transferred on Excel Spreadsheet; descriptive analysis was expressed as mean ± standard deviation and categorical data as number (percentage). All calculations were done by GraphPad InStat 3 statistical software (demo version free software of GraphPad Software, Inc. California, USA). Observed difference in the mean distribution of QTc intervals was compared by student's t-test. We evaluated the strength of association between QTc and various parameters by calculating odds ratio, keeping confidence interval 95%, taking QTc >0.43 s in males and QTc >0.45 s in females as positive outcomes and QTc ≤0.43 s in males and QTc ≤0.45 s in females as negative outcome. Difference in distribution of categorical data between groups was tested by Fisher's exact test. Any observed difference was considered significant statistically with P < 0.05.


  Results Top


Our study group had mean age 56 years, preponderance of female gender (66%) and mean duration of diabetes 6 years with poor glycaemic control (32%) and moderate BP control (51%), whereas coexistence of hypertension was high (69%). Most of type 2 diabetes patients are taking biguanides except two patients.

Use of other drugs affecting cardiovascular outcome was statins (48%), aspirin (32%), β-blockers (56%), ACE inhibitors (29%).

Males were significantly elder (mean-59 vs. 54, P < 0.001) and with longer disease duration than females (mean-7 vs. 5, P= 0.01).

Otherwise, both gender-based subgroups were comparable with reference to glycaemic control, BP control and prevalence of use of pharmacotherapy [Table 1].
Table 1: Baseline and clinical data of study participants-whole group and gender wised

Click here to view


ECG-based parameters showed average QTc 0.42 s and QTd 47.8 msec in whole group with the prevalence of abnormal QTc, QTd and ECG LVH (15%, 20% and 3%, respectively). As compared to females, males had insignificantly higher quantitative QTc and QTd. The prevalence of abnormal QTc was significantly higher in males compared to females (QTc-22% vs. 11%, P= 0.034). The prevalence of prolonged QTd and ECG LVH were not much different between these subgroups [Table 2].
Table 2: Electrocardiogram parameters of the study group-gender wise and in total

Click here to view


We divided study participants into two subgroups with disease duration more than or less than 5 years, keeping them comparable for gender distribution, disease control and use of preventive pharmacotherapy. Participants with longer duration had higher prevalence of qualitative QTc prolongation as compared to those with <5-year duration (17% vs. 12%, P= 0.418). Other QT parameters were better with less duration but differences were insignificant statistically [Table 3].
Table 3: Comparison of study parameters between participants with diabetes duration ≥5 years (n=113) and <5 years (n=86)

Click here to view


Based on the American Diabetes Association 2014 guidelines, participants were divided into the group with good glycaemic control or poor glycaemic control. These two subgroups were not different in baseline data, disease control or drugs used. Group with poor glycaemic control had high mean QTc (P 0.003) and higher prevalence of prolonged QTd (24% vs. 11%, P= 0.036) as compared to the group with good glycaemic control. Later group had small, insignificantly better qualitative QTc and quantitative QTd than former group [Table 4].
Table 4: Comparison of study parameters between good glycaemics (n=64) and poor glycaemics (n=135)

Click here to view



  Discussion Top


Cardiovascular complications are well documented in type 2 diabetes, but cardiac autonomic neuropathy is neglected.[11] Cardiac dysautonomia is known in T2DM [6],[12],[13] and can be screened by various tests to judge cardiac autonomic balance. We compared effect of type 2 diabetes on cardiac autonomic balance judged by simple ECG-based QT intervals.

We found low-to-moderate prevalence of abnormally prolonged QTc (15%) and QTd (20%) in ambulatory-treated T2D. This is more than the prevalence of QT abnormality found in normal healthy participants in our region.[13] Although, our diabetic group revealed a prevalence, lesser than other similar studies.[14],[15] This can be attributed to two of the main factors, low prevalence of LVH in ECG and use of preventive pharmacotherapy. QT prolongation marks the heterogenicity of left ventricular mass that correlates with LVH [16] seen in patients with diabetes [17] and more so in hypertensive diabetics (which comprised of more than two-third of our cases). Very low LVH prevalence (3%) explains the lower incidence of QTc or QTd abnormalities. There are studies showing QT prolongation in the absence of LVH, but still 'low LVH leads to low-QT abnotmality' holds true in our cases. This becomes even significant with the fact that only one-third diabetics had optimum glycaemic control, whose the absence is risk factor for QT interval prolongation. The second possible factor for lower than expected QT abnormality is the presence of co-existing hypertension which brings the additive risk [18] but also offers the benefit of use antihypertensive drugs. Normotensive diabetics not receiving this preventive pharmacotherapy such as beta-blockers,[19] first-line antihypertensives and aspirin are not offered this benefit. Beta-blockers have beneficial effect on QT interval as previously documented [19] and we found the same, evident as low-QT abnormality in patients with diabetes with use of beta-blocker in majority (56%). A recent study [18] has shown that beta-blockers in T2DM prevent hypoglycaemia-related complications such as hypertension, hypokalemia, QT prolongation, cardiac arrhythmia and sudden cardiac death. As compared to with beta-blocker, intensive glycaemic control without beta-blocker, has found to have increased all-cause and cardiovascular mortality,[19] and this study gives a re-affirmative clue to that. In our previous study, we found that use of antihypertensive drug mainly ACE inhibitor gives better profile of diabetic vasculopathy in hypertensive diabetics as compared to normotensive diabetics not receiving the same.[20] Hence, the preventive effect of these drugs in our study group can be understood that was applicable to hypertensives, consisting of 2 out of three participants.

We had males with worse QT profile than females, having mean age in mid-fifties, in contrast to few studies done in younger age group.[17],[21] The mean age beyond menopausal age explains the absence of female advantage due to hormones.[22] and our result is supported by another study with broad age group of normal healthy Indians.[23] Another reason for the male disadvantage may be higher mean age (59 vs. 54) and disease duration (7 vs. 5 years) in males than females. Duration did not affect results of QT parameters significantly in contrast with the previous studies.[13],[14] It can be due to delay in diagnosis, delay in onset of treatment, poor glycaemic control and low self-care despite increasing duration. Poor glycaemic control and its effect on cardiovascular study parameters known in our type 2 diabetics,[11],[24] same being true in the current study. Hyperglycaemia imposes direct damage to cardiac myocyte.[14] Good diabetic control may reduce the prevalence of QT abnormality from 15% to 20% to the normal level of 5%–10%.

Our recent study showed a high prevalence of prolonged QTc, both qualitatively and quantitatively, in hypertensives of our region on monotherapy (n = 142, mean age 40 years, 58% males) with poor pressure control, associated with female gender and age but not duration or BP.[25] The same study also showed [26] prolonged QTc more so in newly diagnosed hypertensives, unaffected by duration of hypertension or use of ACEI or CCB but associated with modifiable risk factors. These two results are just alike current study done focusing diabetes instead of hypertension. Both conditions have common risk factors, associates and aftermaths, increasing trend and silent progressing nature. It suggests that early screening, better disease control, ECG monitoring and lifestyle interventions, all can serve as good preventive measures. Prolonged QTc and QTd indicates heterogenicity of ventricular depolarisation.[16] This is due to an underlying change in ion channels responsible for the synchronised electrical activity.[27] Prolonged repolarisation leaves a scope for circus movement of electrical impulse. This can lead to ventricular arrhythmia that begins as premature ventricular contraction. T2D have more likelihood of cardiovascular diseases,[28] more so when the diagnosis is delayed, HbA1c reports are unavailable, lifestyle modifications are neglected, awareness is less and screening tools such as ECG and HRV are sparely used. ECG is a simple diagnostic tool that can be practised even at primary health care level.[29] A simple rule of 50 can be used to detect arrhythmia risk early which states that QT interval should be normally <50% of RR interval. However, it is undertreated and underused in asymptomatic, at-risk patients such as patients with diabetes or hypertensives. QTc and QTd are validated diagnostic tools available since long. QTc >440 msec and QTd >80 msec are known individual predictor of CVD events.[16] It becomes more useful in T2DM than myocardial infarction or congestive heart failure as ECG baseline is stable and other arrhythmia are absent.[30] T2DM is incurable lifelong companion where quality of life and longevity are endangered by cardiovascular risk. Healthy heart is a key to apparently healthy life in diabetics, but it needs assurance by timely screening and benefit of glycaemic control.

This study was limited by manual method of measurement, moderate sample size, unavailability of HbA1c, the absence of biochemical parameters, the presence of confounding factors. We did not have other tests to detect cardiac dysautonomia and various macrovascular and microvascular complications were not studied. It also needs follow-up study to ascertain exact cause-effect relationship.


  Conclusion Top


We found low-to-moderate QTc abnormality, qualitative more than quantitative, in T2D having poor glycaemic control and very low ECG LVH, which were not significantly affected by disease duration but with male gender and poor glycaemic control. It suggests possible beneficial effect of use of co-existing preventive pharmacotherapy other than hypoglycaemics and a possibility of preventing cardiac repolarisation abnormality with early diagnoses and prompt glycaemic control.

Acknowledgement

We are thankful to medicine department of our teaching government hospital for allowing us to conduct this study. We kindly acknowledge the support of Indian Council of Medical Research for selecting, approving and funding this project under short-term studentship programme for the year 2015.

Financial support and sponsorship

This study was financially supported by ICMR (Indian Council Of Medical Research) under STS 2015.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Mohan V, Venkatraman JV, Pradeepa R. Epidemiology of cardiovascular disease in type 2 diabetes: The Indian scenario. J Diabetes Sci Technol 2010;4:158-70.  Back to cited text no. 1
    
2.
Ramachandran A, Shetty AS, Nandhitha A, Snehalatha C. Type 2 Diabetes in India: Challenges and Possible Solutions. Available from: http://www.apiindia.org/medicine_update_2013/chap40.pdf. [Last accessed on 2016 Oct 08].  Back to cited text no. 2
    
3.
Dekker JM, Crow RS, Hannan PJ, Schouten EG, Folsom AR, ARIC Study, et al. Heart rate-corrected QT interval prolongation predicts risk of coronary heart disease in black and white middle-aged men and women: The ARIC study. J Am Coll Cardiol 2004;43:565-71.  Back to cited text no. 3
    
4.
Giunti S, Gruden G, Fornengo P, Barutta F, Amione C, Ghezzo G, et al. Increased QT interval dispersion predicts 15-year cardiovascular mortality in type 2 diabetic subjects: The population-based Casale Monferrato study. Diabetes Care 2012;35:581-3.  Back to cited text no. 4
    
5.
Francis J. Prevention of sudden cardiac death. Indian Pacing Electrophysiol J 2011;11:91-2.  Back to cited text no. 5
    
6.
Tarvainen MP, Laitinen TP, Lipponen JA, Cornforth DJ, Jelinek HF. Cardiac autonomic dysfunction in type 2 diabetes-Effect of hyperglycemia and disease duration. Front Endocrinol (Lausanne) 2014;5:130.  Back to cited text no. 6
    
7.
Casale PN, Devereux RB, Alonso DR, Campo E, Kligfield P. Improved sex-specific criteria of left ventricular hypertrophy for clinical and computer interpretation of electrocardiograms: Validation with autopsy findings. Circulation 1987;75:565-72.  Back to cited text no. 7
    
8.
Lanjewar P, Pathak V, Lokhandwala Y. Issues in QT interval measurement. Indian Pacing Electrophysiol J 2004;4:156-61.  Back to cited text no. 8
    
9.
American Diabetes Association. Standards of medical care in diabetes--2014. Diabetes care. 2014;37:S14.  Back to cited text no. 9
    
10.
Moss AJ. The QT interval and torsade de pointes. Drug Saf 1999;21 Suppl 1:5-10.  Back to cited text no. 10
    
11.
Verrotti A, Prezioso G, Scattoni R, Chiarelli F. Autonomic neuropathy in diabetes mellitus. Front Endocrinol (Lausanne) 2014;5:205.  Back to cited text no. 11
    
12.
Solanki JD, Basida SD, Mehta HB, Panjwani SJ, Gadhavi BP. Comparative study of cardiac autonomic status by heart rate variability between under-treatment normotensive and hypertensive known type 2 diabetics. Indian Heart J 2017;69:52-6.  Back to cited text no. 12
    
13.
Solanki JD, Thesia AM, Mehta HH, Shah CJ, Mehta HB. Evaluation of cardiac autonomic status using QTc interval in patients with leprosy. Asia Pac Clin Transl Nerv Syst Dis 2016;1:144-8.  Back to cited text no. 13
    
14.
Cox AJ, Azeem A, Yeboah J, Soliman EZ, Aggarwal SR, Bertoni AG, et al. Heart rate-corrected QT interval is an independent predictor of all-cause and cardiovascular mortality in individuals with type 2 diabetes: The diabetes heart study. Diabetes Care 2014;37:1454-61.  Back to cited text no. 14
    
15.
Ziegler D, Zentai CP, Perz S, Rathmann W, Haastert B, Döring A, et al. Prediction of mortality using measures of cardiac autonomic dysfunction in the diabetic and nondiabetic population: The MONICA/KORA Augsburg cohort study. Diabetes Care 2008;31:556-61.  Back to cited text no. 15
    
16.
Molnar J, Rosenthal JE, Weiss JS, Somberg JC. QT interval dispersion in healthy subjects and survivors of sudden cardiac death: Circadian variation in a twenty-four-hour assessment. Am J Cardiol 1997;79:1190-3.  Back to cited text no. 16
    
17.
Jobe M, Kane A, Jones JC, Pessinaba S, Nkum BC, Abdou Ba S, et al. Electrocardiographic left ventricular hypertrophy among Gambian diabetes mellitus patients. Ghana Med J 2015;49:19-24.  Back to cited text no. 17
    
18.
Lehtonen AO, Puukka P, Varis J, Porthan K, Tikkanen JT, Nieminen MS, et al. Prevalence and prognosis of ECG abnormalities in normotensive and hypertensive individuals. J Hypertens 2016;34:959-66.  Back to cited text no. 18
    
19.
Tsujimoto T, Sugiyama T, Noda M, Kajio H. Intensive glycemic therapy in patients with type 2 diabetes on β-blockers. Diabetes Care 2016;39:1818-26.  Back to cited text no. 19
    
20.
Solanki JD, Makwana AH, Mehta HB, Gokhale PA, Shah CJ. Hypertension in type 2 diabetes mellitus: Effect of the disease and treatment on development of peripheral artery disease. Int J Diabetes Dev Ctries 2015;35 Suppl 3:S380-4.  Back to cited text no. 20
    
21.
Nielsen JB, Graff C, Rasmussen PV, Pietersen A, Lind B, Olesen MS, et al. Risk prediction of cardiovascular death based on the QTc interval: Evaluating age and gender differences in a large primary care population. Eur Heart J 2014;35:1335-44.  Back to cited text no. 21
    
22.
Villareal RP, Woodroof AL, Massumi A. Gender and cardiac arrhythmias. Tex Heart Inst J 2001;28:265-75.  Back to cited text no. 22
    
23.
Hingorani P, Natekar M, Deshmukh S, Karnad DR, Kothari S, Narula D, et al. Morphological abnormalities in baseline ECGs in healthy normal volunteers participating in phase I studies. Indian J Med Res 2012;135:322-30.  Back to cited text no. 23
  [Full text]  
24.
Solanki JD, Makwana AH, Mehta HB, Gokhale PA, Shah CJ. Evaluating glycemic control and its correlation with peripheral artery disease in ambulatory type 2 diabetic patients of an Urban area of Gujarat, India. Int J Clin Exp Physiol 2014;1:221-5.  Back to cited text no. 24
  [Full text]  
25.
Solanki JD, Gadhavi BP, Makwana AH, Mehta HB, Shah CJ, Gokhale PA. Early screening of hypertension and cardiac dysautonomia in each hypertensive is needed inference from a study of qtc interval in Gujarati hypertensives. Int J Prev Med 2017. [Ahead of print].  Back to cited text no. 25
    
26.
Solanki JD, Gadhavi BP, Makwana AH, Mehta HB, Shah CJ, Gokhale PA, et al. QTc interval in young Gujarati hypertensives: Effect of disease, antihypertensive monotherapy, and coexisting risk factors. J Pharmacol Pharmacother 2016;7:165-70.  Back to cited text no. 26
[PUBMED]  [Full text]  
27.
Kuo CS, Munakata K, Reddy CP, Surawicz B. Characteristics and possible mechanism of ventricular arrhythmia dependent on the dispersion of action potential durations. Circulation 1983;67:1356-67.  Back to cited text no. 27
    
28.
Hemmingsen B, Lund SS, Gluud C, Vaag A, Almdal TP, Hemmingsen C, et al. Targeting intensive glycaemic control versus targeting conventional glycaemic control for type 2 diabetes mellitus. Cochrane Database Syst Rev 2013;11:CD008143.  Back to cited text no. 28
    
29.
Shanit D, Cheng A, Greenbaum RA. Telecardiology: Supporting the decision-making process in general practice. J Telemed Telecare 1996;2:7-13.  Back to cited text no. 29
    
30.
de Santiago A, García-Lledó A, Ramos E, Santiago C. Prognostic value of ECGs in patients with type-2 diabetes mellitus without known cardiovascular disease. Rev Esp Cardiol 2007;60:1035-41.  Back to cited text no. 30
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed98    
    Printed5    
    Emailed0    
    PDF Downloaded18    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]