Pediatric RV Function (TAPSE) Z-Score Calculator

Z-Scores for RV systolic function.

Using data published in the June 2009 JASE, this calculator determines the age-adjusted Tricuspid Annular Plane Systolic Excursion (TAPSE) z-scores:

Notes:

For the purpose of calculating the z-score, I used the published mean and "-3SD" lower limit to calculate each SD ([mean – lower limit] / 3)- which is a little bit off-label. That is, the standard deviation by itself is not published— only the ±2 and ±3 ranges are published— and there is some variation in how those back-calculate to "1 SD". Even though the title of the article suggest using the data for calculating z-scores, it is not perfectly clear how we are supposed to do this.

For the purpose of drawing the plot, I used the published ±2 SD values (the 2.5 – 97.5 percentiles).

While the authors note the independent influence of BSA on TAPSE (they also provide a separate graph for BSA vs. TAPSE), it is not clear to me how we are supposed to apply this information. For each age group, a TAPSE/BSA index value is determined by dividing the mean TAPSE by the mean BSA for each age group. The indexed values are noted to decrease with increasing age/BSA. However, no range of normal indexed values is given. The manner in which BSA was estimated for the study is not presented. The BSA vs. TAPSE data used to construct their graph are not published.

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References:

Right ventricular function in infants, children and adolescents: reference values of the tricuspid annular plane systolic excursion (TAPSE) in 640 healthy patients and calculation of z score values.
Koestenberger M, Ravekes W, Everett AD, Stueger HP, Heinzl B, Gamillscheg A, Cvirn G, Boysen A, Fandl A, Nagel B.
J Am Soc Echocardiogr. 2009 Jun;22(6):715-9. Epub 2009 May 7.

Fetal Echo Z-Score Calculator: Updated

Cardiac valve, chamber, and arch z-scores based on femur length; predicted LMP/EDD/EGA; LV/RV size discrepancy ratios.

This update provides the following functionality:

Fetal cardiac z-scores calculated from femur length

According to the source article, each of the independent variables (EGA, FL, BPD) had similar performance, with the regressions based on femur length being slightly superior. I have not yet compared the z scores across the two calculations- it is likely that minor differences exist between z-scores based on femur length, and those based on the derived EGA.

Femur length estimates of EGA, EDD, and LMP

Since the ICAEL guidelines require reporting of the EGA (and manner of determination), this is estimated according to this common citation: New charts for ultrasound dating of pregnancy. Without getting wrapped up in the subtleties of another field entirely, this reference seemed suitable . From the looks of it though, EGA predictions by femur length alone are open to some criticism.

Size discrepancy ratios

A common referral for fetal echocardiography is the discovery on routine ultrasound of a "size discrepancy" between the left and right ventricles. The authors of this new article Left Ventricle to Right Ventricle Size Discrepancy in the Fetus: The Presence of Critical Congenital Heart Disease Can Be Reliably Predicted suggest the use of easily calculated ratios as a simple manner for stratifying the various underlying lesions. Ratios of 0.6 for each of the sites (MV/TV, LV/RV, AoV/PV) appear to have good predictive value- particularly when used in combination with the transverse arch measurement and descriptions of the flow across the atrial septum.

The topic of z-scores is touched upon briefly with reference to the transverse arch. Although the data presented suggests that the arch z-scores were significantly different between groups (intervention vs. not), no cutoff values for the z-score are suggested. It is interesting (to me) that the stated z-scores in the intervention vs. non groups is –4.7 vs. –3.2 (or, the difference between the 0.0001 percentile and the 0.0687 percentile !!). If one uses the normal boundaries of the 5th and 95th cumulative percentiles (z-scores of ±1.65), or the more liberal 2.3-97.3 percentiles (z scores of ±2), even the non-intervention group seems way out there.

It is also interesting to me that the chamber size and valve z-scores weren't discussed- at all. Many of the referrals for 'size discrepancy' seem more imagined than real, and z-scores of the left heart structures ought to provide evidence of normality, even if things appear discrepant. Along those lines, I am looking forward to the manuscript to follow this abstract: Fetal Cardiac Growth: New Z-Score Ranges From 3,000 Normal Pregnancies.

You can find the updated z-score calculator here:

ParameterZ.com Fetal Echo Z-Score Calculator

LV Mass Reference Values: Smackdown

I am starting to think I should change the tagline for this blog to:

more questions than answers

I am in the midst of building another smackdown calculator:



I hope that it use is self-explanatory and that it requires no introduction- because I am now out of time (heading out to the ASE meeting!).
This is still a 'work in progress' (I seem to have lots of these). Upon my return from the nation's capitol, I plan to add additional functionality:

• tips on measurement technique
• input validation
• automatically detecting discrepancies between references
• allowing users the opportunity to provide feedback in the cases where there are discrepancies

I think this is going to be very interesting ...

Smackdown Revisited

After tackling the z-score:percentile issue, I thought it might be interesting to graph how different z-score equations look in this light. Here is what I derived as the cumulative density function for the aortic valve z-score (1.0 m²; male) using data published from Boston, Wessex, Cincinnati, and Detroit:

I think that because I have explained z-scores to our students and fellows so many times, and made use of my own roughly drawn bell-shaped curve, this next depiction of the probability density function highlights the differences most strikingly for me:

The mean (50th percentile) of the Wessex data is clearly and importantly different than the others... and only the Cincinnati data demonstrates an appreciable degree of skewness, with a long right tail. Of course, none of the investigators mention how they tested for skewness (mean/median/mode?).

(This post is an elaboration of an earlier comparison of different published z-score equations that graphically depicted the predicted mean values of the aortic valve annulus.)

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Validation and re-evaluation of a discriminant model predicting anatomic suitability for biventricular repair in neonates with aortic stenosis.

Colan SD, McElhinney DB, Crawford EC, Keane JF, Lock JE.

J Am Coll Cardiol. 2006 May 2;47(9):1858-65. Epub 2006 Apr 17.

Relationship of the dimension of cardiac structures to body size: an echocardiographic study in normal infants and children.

Daubeney PE, Blackstone EH, Weintraub RG, Slavik Z, Scanlon J, Webber SA.

Cardiol Young. 1999 Jul;9(4):402-10.

Two-dimensional echocardiographic valve measurements in healthy children: gender-specific differences.

Zilberman MV, Khoury PR, Kimball RT.

Pediatr Cardiol. 2005 Jul-Aug;26(4):356-60. Erratum in: Pediatr Cardiol. 2008 Mar;29(2):475.

Regression equations for calculation of z scores of cardiac structures in a large cohort of healthy infants, children, and adolescents: an echocardiographic study.

Pettersen MD, Du W, Skeens ME, Humes RA.

J Am Soc Echocardiogr. 2008 Aug;21(8):922-34. Epub 2008 Apr 11.

Echo Z-Scores and Percentiles

I recently revisited the idea of calculating percentiles in addition to z-scores for the pediatric echo z-score calculators.

The cumulative percent is shown along with the z-score in the following image:

 

Since the relationship between z-score and percentile is constant, it seemed to me of no great benefit to add the percentile information. However, I now feel that percentiles convey information that some find more meaningful. For instance, the commonly accepted limits of normal for z-scores is -2 to +2 (the middle 95% of values). This range corresponds to percentiles of 2.3 and 97.7. But maybe a more realistic range of normal is

• 5th - 95th percentiles: z-scores of ± 1.65
• 10th - 90th percentiles: z-scores of ± 1.3

Using percentiles might encourage us to draw a more conservative boundary for the range of normal, which, in my opinion, will help us interpret otherwise "borderline" z-scores. Accepting the normal range of ±2, a z-score of -2.3 doesn't seem that far off. However, -2.3 is the 1st percentile- clearly nowhere near "normal".

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Initially, I had thought that maybe I'd find a z-score/percentile table,  and simply incorporate a lookup routine,

but I like the idea of calculating the percentile better. However, the calculation (or rather, estimation) is hardly straightforward.

After some searching and trial and error, I finally found something that I could adapt. I admit I don't really understand how the polynomial approximation works, but hey, it does work, and it's in the public domain.

The first z-score calculator to receive the percentiles "upgrade" is the Aortic Root Z-Score Calculator. I hope to add the functionality to the others as well, as time permits.