Introduction:
Left atrial volume are long term marker for an array of physiologic insults that lead to high end-diastolic pressures – likening it to the echocardiographic equivalent of the HbA1c [1]
Left atrial volume (LAV) is closely related to left ventricular (LV) diastolic dysfunction, and is affected by the factors associated with LV diastolic filling pressure. LAV is considered to be a biomarker of both the severity and the duration of LV diastolic filling pressure [2]. Enlargement of the left atrium (LA) is associated with poor endpoints, and may be useful for estimating cardiovascular events and death [3 – 4]. An increased LAV index (LAVI) has been identified as an important biomarker for chronically-increased LV diastolic pressure in CKD patients. Studies have suggested that LAVI could be a predictor of increased cardiovascular risk and mortality in patients with end-stage renal disease (ESRD) [5 – 6]
LAVI is left atrial volume indexed to body surface area and it is considered normal <28ml/m2; Increased mild<29-33ml/m2; Mod severe <33-39ml/m2 and Very severe >40ml/m2. [7]
In Resource constraint setting LAVI cannot be determined owing to expertise required to perform echocardiography. While electrocardiography is readily available tool and point of care physician can be easily trained. We explored utilising P wave parameters including newer parameters like P wave peak time in predicting severity of LAVI in our study.
Methods:
We included Chronic kidney disease patients (as per KIDGO definition) with age more than 18 years in our study from nephrology department (OPD/IPD) IMS BHU. We excluded patients with rhythm abnormalities, decreased ejection Fraction(<50%), valvular heart disease, coronary artery disease, Patient with poor echocardiographic assessment from our study. A total of 92 patients were enrolled in our study 20 were excluded 7 had atrial fibrillation, 5 had significant valvular lesion, 5 patients had reduced ejection fraction and 3 had poor echo window. So a total 72 patients met inclusion exclusion criteria.
Once patient enrolled in study, on same day demographic, disease history was taken. Each patient’s height, weight recorded and Body surface area was calculated by Du Bois method in m2. Patient’s blood investigation were done on interdialytic day and patient underwent electrocardiography and echocardiography.
Electrocardiography assessment
All patients underwent 12 lead electrocardiography which was recorded at 25mm/sec and voltage of 10mm/mV. Print out was taken and image was taken by android smart phone. ECG was assessed by cardiologist and image was magnified where ever required. From limb lead II (D2) P wave dispersion (PWDis), Maximum P wave duration (PWMax) and P wave peak time (PWPT) was calculated in milli seconds and terminal P force (PTFV1) was calculated from lead V1. PWDis was calculated by subtracting minimum P wave duration from maximum P wave duration in lead D2. P wave peak time is duration between beginning of P wave to peak of P wave in lead D2 and Terminal P force from lead V1 was calculated by multiplying depth of negative portion of P wave to width of the same expressed in mv x msec.
Echocardiography assessment
Transthoracic echocardiography was done by cardiologist on sosnosite Edge II echocardiography machine . Standard echocardiographic imaging was performed. Ejection Fraction was calculated by modified Simpson’s biplane method. Left atrial volume measurement was done at end of systole using biplane disc summation method and Left atrial volume was indexed body surface area to calculate left atrial volume index (LAVI) to calculate ml/m2.
Results:
We enrolled 92 patients of chronic kidney disease (as per KDIGO definition) out of which 72 met inclusion exclusion criteria. Study population mean age was 53+/-11 years. Of 72 individuals 22 (30.6%) were females. Stage wise depiction CKD seen table 1 with maximum number of patients stage 5 CKD- 43 patients (59.5%). 36 (50%) were on maintainance hemodialysis. Etiology of CKD depicted in table 2, DKD 39 (54.2%) was most common. We had 2 patients with CAKUT, In presumed CGN biopsy proven FSGS, IGAN and LN was there 1 each and in CTIN 1 had PCKD and 4 had history of NSAID abuse. In our study population 67(93.1%) patients were hypertensive, 69 (95.83%) patients were with anemia, 14 were severely anemic. 27 patients were with volume overload.
In our study DKD 39 (54.2%) was most common etiology. In presumed cases of CGN biopsy proven FSGS, IGAN and LN was there 1 each and in presumed CTIN cases 1 had PCKD and 4 had history of NSAID abuse. We had 2 patients with CAKUT
In our study population 67(93.1%) patients were hypertensive. In our study, 69 (95.83%) patients were with anemia, 14 were severely anemic.
In our study we divided patients according to left atrial volume index (LAVI) in which 52 patient were with increased LAVI group and 20 patients were with normal LAVI Group.
Mean P wave peak time with value 60.58+/-13.63 msec in increased LAVI group which was more than 27+/-7.32 msec in normal LAVI group, This difference was statically significant (p value 0.000), Similarly mean Max P wave duration in lead II (PW max) was more in increased LAVI group 108.27+/-21.84 msec compared to normal LAVI group 85.50+/-20.89 msec with statically significant difference (p value 0.001). Other parameters PFTV1 and P wave dispersion had no statically significant difference in two groups.
We analysed correlation of LAVI with P wave indices
Table 1 Depicts Pearson correlation coefficient with LAVI
There was significant positive correlation in LAVI with P wave peak time and Max P wave duration only. With other two parameters P wave dispersion and terminal P force there was no statistically significant correlation.
We also tried to predict severity of LAVI using different P wave parameters.
Table 2 Distribution of study population according to severity of increase in LAVI
When we compared means of different P wave indices is different severity of LAVI group using ANOVA we found that as severity of LAVI increases there is statistical significant increase in P wave peak time (across all categories) and Max P wave duration also increased as severity increases and change is more apparent in mod-severe to very severe category. While there is no statistical difference in P wave dispersion and terminal P force across categories.
To utilise P wave indices for predicting different severity LAVI, we tested different P wave parameters for LAVI cutt off >33ml/m2 (differentiating mild increase in LAVI from mod- severe increase in LAVI) and LAVI cut off >39 ml/m2 (differentiating mod-severe increase in LAVI from Very severe increase in LAVI)
When we tested electrocardiography parameters PWPT (D2), PW MAX (D2), PFTV1 and P wave dispersion against echocardiographic parameter LAVI . To predict increase LAVI >28ml/m2, We found P wave peak time had strong predictor capacity with maximum area under curve ) 0.983 (p value 0.00) 95% Confidence Interval (CI) 0.961-1.0 followed PW max 0.769 (P value 0.000) 95% CI 0.657-0.881 .
On testing P wave peak time against LAVI cutt off of 28 ml/m2 for increased LAVI on ROC we found value of P wave peak time of 45 msec has sensitivity of 84.6% and specificity reaching 100 % and if we take cutt off 35 msec sensitivity of 98.1% and specificity of 85% While for Pwave maximum duration in lead D2 95 mesc predicts increased LAVI with a sensitivity of 76.9% and specificity of 60%.
While testing P wave Parameters to predict increase LAVI >33ml/m2, We found P wave peak time had strong predictor capacity with maximum area under curve 0.955 (p value 0.00) 95% Confidence Interval (CI) 0.907-1.0 followed PW max 0.751 (P value 0.000) 95% CI 0.639-0.862.
On testing P wave peak time against LAVI cutt off of 33 ml/m2 for increased LAVI on ROC we found value of P wave peak time of 45 msec has sensitivity of 97.4% and specificity 82 % and if we take cutt off 55 msec sensitivity of 82.1% and specificity of 93.9% While for Pwave maximum duration in lead D2 105 mesc predicts increased LAVI with a sensitivity of 59% and specificity of 85%.
While testing P wave Parameters to predict increase LAVI >39ml/m2 (Very severe increase) We had similar findings, suggesting P wave peak time had strong predictor capacity with maximum area under curve 0.915 (p value 0.000) 95% Confidence Interval (CI) 0.851-0.978 followed PW max 0.831 (P value 0.000) 95% CI 0.733-0.929.
On testing P wave peak time against LAVI cutt off of 39 ml/m2 predicting very severly increased LAVI for increased LAVI on ROC we found value of P wave peak time of 55 msec has sensitivity of 92.0% and specificity 77.6 % and if we take cutt off 65 msec sensitivity of 72% and specificity of 92.5% While for Pwave maximum duration in lead D2 115 mesc predicts increased LAVI with a sensitivity of 68% and specificity of 85.1%.
Conclusions:
Discussion
Chronic kidney disease patients are at increased cardiovascular risk and left atrial volume index indirectly predicts long standing diastolic dysfunctinon.
Increased left atrial volume index is associated with increased morbidity and mortality. In a resource constraint setting where echocardiography is not readily available certain electrocardiographic parameters may act as surrogate markers and help to determine patient with increased cardiovascular risk. Facilitating early diagnosis and treatment of at risk patients. In our study of 72 patients we tried to include patients with different stages of CKD, different etiologies and patient with different clinical profile (eg with or without volume overload). We found that electrocardiography parameter P wave peak time correlates with LAVI and a cuttoff 45 msec can predict increased LAVI. Maximum P wave duration also to some extent correlates with increased LAVI, however P wave dispersion and terminal P force are not strong predictor of increased LAVI. We also tried ascertain severity of increase in LAVI using P wave indices and we found P wave peak time when tested for different cut off of LAVI, had maximum area under curve with statistically significant P value and to some extent Maximum P wave duration follow same but has less predictive value while P wave dispersion and terminal P force do not elicit any significant role in predicting LAVI severity. We also tried to determine cutt off to predict different severity of increase in LAVI using P wave parameters though clear cut of is difficult to determine in limited sample size but still Parameters like P wave peak time predicts trend to determine severity of LAVI like On testing P wave peak time against LAVI cutt off of 33 ml/m2 for increased LAVI on ROC we found value of P wave peak time of 45 msec has sensitivity of 97.4% and specificity 82 % and if we take cutt off 55 msec sensitivity of 82.1% and specificity of 93.9% and P wave peak time against LAVI cutt off of 39 ml/m2 predicting very severly increased LAVI for increased LAVI on ROC we found value of P wave peak time of 55 msec has sensitivity of 92.0% and specificity 77.6 % and if we take cutt off 65 msec sensitivity of 72% and specificity of 92.5% . These data illustrate that as P wave peak time increase LAVI increases though exact cutt off for different severity is difficult to determine with limited sample size but these points towards a trend.
In comparison to study done by Ibrahim yildiz et .al [8] in hemodialysis population we included entire CKD population in all stages re emphasizing Significance P wave peak time in predicting increased LAVI. On contrary to their findings we found that P wave maximum duration to some extent may influence LAVI.
Also in our studies we found that P wave parameters like p wave dispersion and Terminal P force in lead V1 do not adequately help to predict LAVI. The reason for P wave dispersion not linearly correlating with LAVI might be nature of this parameter, Increased PWD reflect prolongation of intraatrial and interatrial conduction time with lack of a well-coordinated conduction system within the atrial muscles discontinuous propagation of sinus impulses mainly between the left and right atria [9] so, beat to beat variation is not only function of LA mechanical factors but also affected by many other factors like Young athletes of high performance, Hypertension, Cardiac heart failure (CHF), Diabetes and Hemodialysis[10][11][12][13] and other factors not relevant to this study like valvular heart disease and channelopathies. These factors affect autonomic tone in patients, inflammatory pathway affecting conduction system.
Our study had certain limitations small sample size, temporal changes in parameters were not accessed. Also we had used 2D echocardiography in LV chamber assessment which itself have limitation that it is affected by image quality. Also, in rhythm disorders and valvular defects which independently affects P wave this study results cannot be implied.
Conclusion
Our study suggest newer Electrocardiographic parameters like P wave peak time independently can predict LAVI in CKD patients, Which is used to stratify cardiovascular risk especially left ventricular diastolic dysfunction. Electrocardiogram easily available tool and point of care physician can be easily trained to identify these new P wave parameters to identify at risk patients, Specifically in economic constraint setting and promptly adjusting management accordingly.
References
1. Marvin Louis Roy Lu, Michael Shane Lloyd, The HbA1C of the heart: Atrial volume index and outcomes of cardiac arrest, Resuscitation,Volume 170, 2022, Pages 314-315
2 Tsang TS, Barnes ME, Gersh BJ, Bailey KR,Seward JB. Left atrial volume as a morpho-physiologic expression of left ventricular dia-stolic dysfunction and relation to cardiovas-cular risk burden. Am J Cardiol. 2002 Dec;90(12):1284–9.
3 Lang RM, Bierig M, Devereux RB, Flachs-kampf FA, Foster E, Pellikka PA, et al.; Cham-ber Quantification Writing Group; American Society of Echocardiography’s Guidelines and Standards Committee; European Association of Echocardiography. Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr. 2005 Dec;18(12):1440–63.
4 Patel DA, Lavie CJ, Milani RV, Ventura HO.Left atrial volume index predictive of mortality independent of left ventricular geometry in a large clinical cohort with preserved ejection fraction. Mayo Clin Proc. 2011 Aug;86(8):730–7.
5. Barberato SH, Pecoits Filho R. Prognostic value of left atrial volume index in hemodialysis patients. Arq Bras Cardiol. 2007 Jun;88(6):643–50.
6 Choi MJ, Kim JK, Kim SG, Yoon JW, Koo JR, Kim HJ, et al. Left atrial volume index is a predictor of silent myocardial ischemia in high risk patients with end-stage renal disease. Int J Cardiovasc Imaging. 2013 Oct;29(7):1433–9.
7. Lang RM, Bierig M, Devereux RB, et al. Recommendations for chamber quantification: a report from the American Society of Echocardiography's Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. Am J Soc Echocardiogr. 2005;18(12):1440-1463
8. Yıldız İ, Özmen Yildiz P,Burak C, Rencüzoğulları İ, Karaveli Gursoy G, Kaya B, Karabağ Y,Çağdaş M. P Wave Peak Time for Predicting an Increased Left Atrial Volume Index in Hemodialysis Patients. Medical Principles and Practice J. 2019(2) 1011-7571
9. Geng HH, Li R, Su YM, Pan HY, Pan M, Ji XP. A functional single-nucleotide polymorphism in interleukin-6 promoter is associated with p wave dispersion in hypertensive subjects with atrial fibrillation. Int J Clin Exp Med 2014;7(11):4434e40.
10. Ertem AG, Erdo_gan M, Keles¸ T, Durmaz T, Bozkurt E. P-wave dispersion and left ventricular diastolic dysfunction in hypertension. Anatol J Cardiol 2015;15(1):78e9.
11. Kim DH, Kim GC, Kim SH, et al. The relationship between the left atrial volume and the maximum P-wave and P-wave dispersion in patients with congestive heart failure. Yonsei Med J 2007;48(5):810e7.
12. Demir K, Avci A, Kaya Z, et al. Assessment of atrial electromechanical delay and P-wave dispersion in patients with type 2 diabetes mellitus. J Cardiol 2016 Apr;67(4):378e83.
13. Chen SC, Su HM, Huang JC, et al. Association of P-Wave dispersion with overall and cardiovascular mortality in hemodialysis patients. Am J Nephrol 2015;42(3):198e205.
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.