Thursday, May 22, 2014

Dr Ravi Ramamurthy has done it again!

This time, he is talking about the statistics part of the erstwhile article we discussed in the previous post: "Risk stratification at diagnosis for children with hypertrophic cardiomyopathy: an analysis of data from the Pediatric Cardiomyopathy Registry". He explains some of the jargon related to medical statistics for the understanding of those who can just spell the word!

Here we go: 
“There are lies, damned lies and statistics” …..

Mark Twain certainly did not have medical biostatistics when he popularized this phrase.
The contribution of statistics to medical science cannot be said in the same light. The weight of a study is determined by its statistics. So let us just take a breather from just satisfying our intellectual taste buds by tasting only the abstract of an article and proceed to actually looking at the entire cooking process.
I was exposed to statistics when I accompanied my mother to the vegetable market.  The potatoes were “sampled”; by size, freshness, color etc. Then they were screened for “predictive markers” indicating their likely shelf life before they reach their “end point” either cooked or rot. And the inevitable remark that out of the last purchase, what percent of the potatoes went bad (“failed to survive”) within a fortnight (“period of observation”). These observations helped us predict and pick the best potatoes.
 In the article under discussion, “Risk stratification at diagnosis for children with hypertrophic cardiomyopathy: an analysis of data from the Pediatric Cardiomyopathy Registry” the clinical implications and its applicability is quite obvious. So the million dollar question would be “Why do we need statistics to prove it?” The answer is simple. Any data needs to be authenticated before it can be applied in practice or replicated. This authentication process is done by statistics.
In this study, two important statistical analytical methods were employed. Let’s discuss them in brief.

Cox proportional-hazards regression:
How important is it?
 It appears in one in ten papers.
How easy is it to understand?
Aim to understand the end result – the “hazard ratio” (HR).
When is it used?
The Cox regression model is used to investigate the relationship between an event (usually death) and possible explanatory variables, for instance observe table 3 & 4 in the article in detail: “Idiopathic, diagnosed at age less than 1 year; Idiopathic, diagnosed at age more than or equal to 1 year; Malformation syndromes; Inborn errors of metabolism; With restrictive cardiomyopathy; With dilated cardiomyopathy.”
What does it mean?
The Cox regression model provides us with estimates of the effect that different factors have on the time until the end event. As well as considering the significance of the effect of different factors the model can give us an estimate of life expectancy for an individual.
Regression and correlation are easily confused.Correlation measures the strength of the association between variables.Regression quantifies the association. It should only be used if one of the variables is thought to precede or cause the other. Interpreting the Cox model involves examining the coefficients for each explanatory variable. A positive regression coefficient for an explanatory variable means that the hazard is higher and thus the prognosis is worse. Conversely, a negative regression coefficient implies a better prognosis for patients with higher values of that variable
The “HR” is the ratio of the hazard (chance of something harmful happening) of an event in one group of observations divided by the hazard of an event in another group. A HR of 1 means the risk is1 × that of the second group, i.e. the same. A HR of2 implies twice the risk.
Kaplan–Meier estimate of the survivor function
To determine the Kaplan–Meier estimate of the survivor function for the above example, a series of time intervals is formed. Each of these intervals is constructed to be such that one observed death is contained in the interval, and the time of this death is taken to occur at the start of the interval. A plot of the Kaplan–Meier estimate of the survivor function (Figure 1) is a step function, in which the estimated survival probabilities are constant between adjacent death times and only decrease at each death. Figure 1 of the said article depicts a step wise graph of the surviving subjects in the study upto five years where the number of surviving subjects can be seen on the Y axis of the graph.

I have tried to simplify these statistical tests, probably a bit too simplified. The intricacies regarding a test lie in deciding where and when to use a certain test. This narration cannot dwell in these details. Secondly the calculations are quite enormous and confusing. But thankfully suitable software are available to carry out these tests. It is imperative for a researcher to be conversant with the various statistical software packages available before embarking on a study. A few examples are Epi 6, SSPS, SAS etc. A researcher should have his statistical test decided before embarking on a study, therefore it is prudent to discuss with a biostatistician beforehand.

So much for now. 

That is Dr Ravi Ramamurthy for you! If you have any doubts or applause, please email  them to or write a comment in the comments box below. It will be honored!                                               

Sunday, May 4, 2014

Hello to the readers!

Our new fellowship student Lt Col Dr Ravi Ramamurthy has agreed to contribute his video presentation on “Natural history of ASD, VSD and PDA” for the readers of blog. Please find the same attached. It can be downloaded from here, but any use of material in the video should be with consent of author. You can write to my email ( for the same.

Please comment on the contents of this video.



Saturday, May 3, 2014

Dr Kiran welcomes the readers to the blog of Pediatric cardiology department, Narayana Hrudayalaya Hospital, Bangalore.

“Working as a team is like work of sled dogs; all the dogs have to put in their best to achieve the maximum result. However, only the lead dog can enjoy the scenic beauty of the journey. If you are not the lead dog, the scenery never changes!” is one of the most satirical quotes on team work by Lewis Grizzard. If one can imagine the picture of dog-sled team, the plight of dogs behind the lead-dog can be easily appreciated.

Every place wherein teamwork is involved would be infested with above situation. I have realized that the most important component of a team is its LEADER. A good and efficient leader (both are mandatory!) can get the best out of even a mediocre team. However, a bad and inefficient leader (either of one!) can break even the best team to tatters. Just imagine a set of brightest minds being led by an unentreprising, negative-toned, escapist, selfish, time-lacking, nepotistic person with sole objective of his own good! Unfortunately, most of the teams in sub-continent face this problem.

A learned friend of mine always laments the lack of leadership in India in general. He attributes it to the prolonged slavery of our masses for centuries. He claims that we are good in taking orders and executing it, but very bad in giving orders and monitoring them. He adds that the cause of moral chaos in most working places of the country is lack of leadership. I have not found a counterargument till now! Leadership, however, has never found any priority in our country. Most of the people were accidental leaders with variable success. May be, we will have a generation in future who understands the need for leadership and would provide the right impetus.

This post, I wish to discuss another interesting article. It is titled “Risk stratifi cation at diagnosis for children with hypertrophic cardiomyopathy: an analysis of data from the Pediatric Cardiomyopathy Registry” by Prof Steven Lipshultz and colleagues for the Pediatric Cardiomyopathy Registry Study Group. The article was published in Lancet in 2013 – pages 1889 -1897. Prof Lipshultz was very kind in permitting me to use his article for discussion in the blog.

The authors start with a premise that treatment of children with hypertrophic cardiomyopathy might be improved if the risk of death or heart transplantation could be predicted by risk factors present at the time of diagnosis. They have statistically analysed data of 1085 children with hypertrophic cardiomyopathy from 1990 to 2009 collected from the Pediatric Cardiomyopathy Registry. Their objective was to understand how patient factors measured at diagnosis predicted the subsequent risk of the primary outcome of death or heart transplantation.

Their analyses revealed that poorest outcomes were recorded for the 69 children with pure hypertrophic cardiomyopathy with inborn errors of metabolism (death or heart transplantation: 57% at 2 years). For children with mixed functional phenotypes, it was lesser. (mixed hypertrophic and dilated cardiomyopathy: 45%, mixed hypertrophic and restrictive cardiomyopathy: 38%). When the child was diagnosed with hypertrophic cardiomyopathy at younger than 1 year, it was 21%. When there was an associated malformation syndrome with hypertrophy cardiomyopathy, it was 23%. The best outcome was for those children with idiopathic hypertrophic cardiomyopathy diagnosed at or after age of 1 year. This group had rate of death or heart transplantation of 3% at 2 years.

The authors have opined that the risk factor for poor outcome included
• Young age
• Low weight or body mass index Z-score
• Presence of congestive heart failure
• Lower left ventricular fractional shortening, or higher left ventricular end-diastolic posterior wall thickness or end-diastolic ventricular septal thickness at the time of diagnosing cardiomyopathy.
For all hypertrophic cardiomyopathy subgroups, the risk of death or heart transplantation was significantly increased when two or more risk factors were present and also as the number of risk factors increased. The authors emphasize the importance of detailed clinical analyses and counseling with improved risk stratification using the data to improve patient outcomes.

The article (Lancet 2013; 382: 1889–97) is important for many reasons. First: the design and analyses of data. Second: clear demonstration of the predictive value of multiple risk factors. Third: benefit to the selected patient groups for early listing for heart transplantation. Fourth: practical utility of the same criteria on global basis. The last one was the basis for my discussion the article here. Reading the entire article is worth the time one invests in it. It would be useful to pediatric cardiologists, genetists, pediatricians, critical care physicians and transplant policy makers of respective countries.

With that let us dwell into the interesting learning scenarios. Just out of interest, I counted the number of such scenarios I have discussed in the past. I have done 93 without using any caption and 210 using captions so far! Did not believe we had so many learnings!! From now on, I would be numbering them accordingly, for the ease of future reference. I will start with no 301 from this post onwards. Whenever we discuss a scenario in future, we shall quote the number.


RV infundibulum is a curious place. Obstruction in this place needs tack and precision to tackle. Anything more would cause undue dilatation and any less would leave residual obstruction which may proceed further with time. We do come across roomy RVOTs after surgical corrections. How many of them would proceed further to formation of aneurysms and diverticulums? Despite doing huge number of congenital heart surgeries, we have seldom come across such instances. Is the better learning curve of surgeons makes any difference? What is the overall incidence of such happenings? Is there a definition or consensus to categorize these lesions? Please let us know your takes on this.


Formation of RVOT muscle bundle with VSD is a known phenomenon. We owe our knowledge on this to the phenomenal work by Benjamin Gasul and colleagues. I have seen many pediatric cardiologists calling this “Gasulization”! The understanding for the formation of these muscle bundles is the impetus provided by high blood flow across RVOT provided by VSD. By corollary, once the VSD is closed, the growth of these muscles should stop. However, in rare instances, we do come across development of muscle bundles in RVOT even after VSD is closed. The progress is also well documented, with increasing gradients. The obstruction is not an entirely dynamic phenomenon either. Is there any other impetus for development of DCRV other than VSD? How far are these similar to isolated DCRV (without VSD)? What is the natural history of isolated DCRV, which is by and large seen in adults? Please let us know your experience.


Problem with newer modalities of investigations is its perceptive utility; it is either over-used or under-used. In a developing country like ours, Cardiac MRI is a premium. Those who can accurately interpret it are even more premium! Owing to the problem, such investigations take huge time to get their utility established. It may the responsibility of professional bodies like PCSI to give a comprehensive set of indications for the utility of using newer modalities like MRI that are appropriate for our country. This will not only improve the utility, it will also avoid the overuse for wrong indications. It is time to custom-make our needs than extrapolating the data from a developed nation blindly. I would love to hear the opinion of readers on this.


We had a small tussle on nomenclature of coronary artery fistulae recently. One of our senior surgeons suggested that the Coronary artery fistulae terminating in left sided chambers are called Coronary-Cameral and those terminating on right heart chambers are called Coronary Arteriovenous fistula. His argument was so emphatic that many agreed with him. It is true that the Coronary artery fistulae are anomalies of termination, but my understanding of nomenclature was different. Also, it is very difficult to argue with senior surgeons even if you have adequate proof! Anyway, this gave an opportunity to revise the nomenclature. Tiryakioglu and colleagues have defined both these terminologies in their article in Texas heart journal in 2010. As per their definition, Fistulae that arise from a coronary artery and then terminate into a chamber of the heart are known as coronary-cameral, while those terminating into a vein are coronary arteriovenous fistulae. Another very impressive article on this I found was Kim et al titled “Coronary artery anomalies: Classification and ECG-gated multi-detector row CT findings with angiographic correlation in Radiographics in 2006. Worth revising!


How important is it to diagnose juxtaposition of atrial appendages correctly in the pre-operative period? Not many would know how to diagnose this entity on echocardiography correctly. Most often, such omissions are harmless. However, in certain diagnoses, this entity becomes important. In cases of TGA with juxtaposition, balloon atrial septostomy is a difficult job due to orientation of interatrial septum. Problems associated with Senning and Mustard procedures are well known in Juxtapositions. We have also seen tricuspid valve anomalies associated with these conditions. Our surgeons could recall utility of juxtapositions in Fontan completion. Is there anything other than these? Please enumerate your experiences.

That brings us to the conclusion of this post. Please write your comments in the comments section. If you find any problem in posting comments, please feel free to mail it to my email id I shall post them on your behalf.