Finding Z: Expanding on the Growth of Neonates

Jae Kim, MD, PhD / November 2017

Finding Z: Expanding on the Growth of Neonates

As a Canadian American, I found it surprising when I first came to the U.S. that what I was saying in my speech was so distinctively Canadian. People asked if I was Canadian even after a few minutes of conversation. With all the American television I grew up watching, I thought I talked “American,” but quickly realized that was not the case.

Sometimes it was the swooping “out” or “about” that was the glaring sign. Other times it was the choice of words that tipped others off: pop versus soda, air con versus AC, washroom versus bathroom, or pronouncing the letter z as “zed” versus “zee”. Strangely, without any intent on making any changes, I found myself adapting immediately to the last choice, using “zee” for the letter “z” in my dialogue, instead of “zed” which I grew up on.

I am not sure if I had always felt subconsciously that this was a smoother and gentler way of saying this letter or, more likely, that it was all the Sesame Street I watched in my childhood that unearthed the alphabet rhyming song, “…w, x, y, and z, now I know my ABC’s…” (which just does not work with zed), making this conversion a cinch.

All this thought about the letter “z” brings to mind our z-score, and a smoother, gentler way of calculating growth.

 

Z-score and neonatal growth

The z-score is a statistical term that refers to the measure of the distance a data point is away from the group mean. With newer growth charts, we are now becoming more familiar with the z-score as growth data.

The great thing about z-score compared to percentiles (which all of us are more familiar with) is that there are no limits to the outer margins, unlike percentiles that stop above 100% or below 0%. As an example, our NICU once had to follow a preterm infant with primordial dwarfism. The only way to track their growth potential was through the z-score, as their data were so far off the normal curves.

I recently came back from the fall Minnesota Neonatal Nutrition conference, where we had an intense and lively discussion about growth, overgrowth, and undergrowth. One of the topics that came up circled around how we monitor growth using growth charts, and the best way we can determine if our nutrition plan is working.

It has been a longstanding concern of mine that we are severely behind in our methods. It is true we have come a long way from the paper growth charts (these were so hard to find and so easy to lose) where we plotted with pencil scribble points to approximate growth. Eyeballing is what most of us did (and still do), and this is simply hard to be accurate with curvilinear slopes and small scale.

We all welcomed the move to electronic medical records (EMR) and growth charts with automated graphing with percentiles and z-score calculations provided at any given point, but tracking growth can still be difficult with these data. Digital zooming can help, but raw numbers, either percentiles or z scores, are what we require.

Some have advocated (shout out to Ian Griffin) for standardizing the growth data into a simple linear x-y chart with z-score on the y axis, and the starting z-score at the linear horizontal midpoint of the graph, and tracking any changes up or down from there. I really like the simplicity of this, but we need to convince our EMR companies to incorporate it, and then we all need to get familiar with tracking an infant in this alternate manner. Our adaptation to electronic data remains sluggish. We should really start speaking in both percentiles and z-scores to determine if a child is on the right track.

One would think that determining the appropriate growth velocity would be simple and consistent. The recent article by Dr. Tanis Fenton and colleagues reviewing the various methods of assessing growth velocity was fascinating in that there were many different methods practiced, each reflecting a different philosophy of assessment.1

Deciding the ideal starting percentile/z-score is contentious. Most target the original birth percentiles/z-scores which leads to many of our infants falling away quickly from these targets in the first week of life. This is partly due to loss of water and lean body mass. The shedding of extracellular water and contraction of the extracellular compartment is an adaptive response to extrauterine life, so I wonder if an infant needs to be docked at the start.

The current debate is to decide whether to consider the birth percentiles/z-scores or recovery percentiles/z-scores, which often start tracking after a week, as the true target. Dr. Fenton has suggested for tracking and comparison purposes that we look at day of life 7 as a reference point for the recovery percentiles/z-scores. This makes sense to me to standardize this metric as the nadir generally occurs before 7 days, and positive growth starts happening thereafter, generally on the “new” recovery z-score line. We can then all compare which of these two targets represent the ideal growth objectives for our own preterm infants.

We also had some lengthy (pardon the pun) discussions on length and how we all want accurate length measurements, given its tighter link with neurodevelopment, but don’t have a good solution to ensuring consistently accurate length recording. This remains a two-person procedure for preterm infants, and we are stuck on resolving this seemingly simple metric. Any novel suggestions for a simple length tool would be great aid. I once got excited about the knemometer (accurately measured lower limb) but it was a fail. Shark Tank addicts and closet inventors: can you share any thoughts?

 

Energy expenditure

The other part of the equation that we need help with is in the energy expenditure side. It is simply not good enough to determine nutrient and energy intake without knowing how much energy expenditure is spent at rest, and with increased demand such as activity, feeding, increased work of breathing, sepsis, etc. To some extent we are relying on the ability of the infant to regulate their own energy expenditure based on the intake we provide. No one has found a suitable calorimetry measure for our infants, and we need a solution here to finish our equations.

We have relied too long on a universal number for growth such as weight gain of 15 g/kg/day or 18g/day of absolute weight gain. These numbers are fine for some parts of the growth curve, but certainly not for other parts, and once you add in the catchup demands, these numbers need major modification. Recommended numbers don’t work well throughout the late preterm period where the most critical growth is occurring in the convalescent period, making this error-prone.

 

Tracking neonatal growth today

How are we tracking growth? Most of us now base preterm growth on whatever our EMR has put in, and thankfully most now standardize to the Fenton or Olsen curves. The Fenton growth chart is my favorite, not only because it was created by a fellow Canadian, but also because it represents a curve that can be responsive and iterative with new data (including Olsen) as they get generated in the future. Consider it the rolling growth chart for preterm infants. The latest development will be how to incorporate the cross-sectional data from the recent INTERGROWTH standards that have solid date for the moderate to late preterm infant. Stay tuned on this one.

 

Catching up on growth

Also, what do we do about catchup growth? It seems the Barker’s hypothesis and origins of adult onset diseases, including the fears of rapid postnatal growth pushing more of our infants into higher risk for metabolic syndrome down the road, has dominated the concerns of many providers – who then try to slow down our nutrient delivery when growth becomes excessive. The balancing act is ensuring optimal neurodevelopment, which is strongly correlated with growth, against the metabolic programming that can occur with fetal growth restriction and postnatal catchup growth.

Compensating for catchup growth is a big mess. We don’t want to impose the metabolic effects of catchup growth, but once a preterm infant loses enough weight, multiple z lines are crossed and catchup is inevitable. We don’t have enough data to know what pattern of catchup growth is safe, and the answer perhaps may be none. Being consistent in both calculating the ideal weight gain velocity and incorporating catchup growth is a common goal. Determining how to do this is very inconsistent. Our nutrition community needs to talk more together and get a standard approach in place.

At the Minnesota meeting, Dr. Susan Carlson told of a soon to be published article on properly defining malnutrition for our infants that will likely begin the conversation for us in finding the best way to standardize our approach. We need to better define the undernutrition that persists in our NICUs, and find common ground on how to address it.

 

Recommendations

With each baby, we need to have an individualized plan. Pick a target and see if you can reach that goal. Remember that “Goldilocks” rules apply: not too much and not too little growth. Define the catchup recovery period and add it into the plan. Trust the empiric data of that child. There is no such thing as 24 kcal/oz and hold. Increase volume first then calories. Follow your baby’s growth daily and react to at most a 3-4 day trend.

Dance with the growth, sing to the growth, be the growth. Be the power of “zee!”

 

References:

Fenton TR, Chan HT, Madhu A, Griffin IJ, Hoyos A, Ziegler EE, Groh-Wargo S,
Carlson SJ, Senterre T, Anderson D, Ehrenkranz RA. Preterm Infant Growth Velocity
Calculations: A Systematic Review. Pediatrics. 2017 Mar;139(3). pii: e20162045.
doi: 10.1542/peds.2016-2045. Review. PubMed PMID: 28246339.

About the Author

Jae Kim is an academic neonatologist and pediatric gastroenterologist and nutritionist at UC San Diego Medical Center and Rady Children’s Hospital of San Diego. He has been practicing medicine for over 23 years both in Canada and the USA. He has published numerous journal articles, book chapters, and speaks nationally on a variety of neonatal topics. He is the Director for the Neonatal-Perinatal Medicine Fellowship Program at UC San Diego and the Nutrition Director of an innovative multidisciplinary program to advance premature infant nutrition called SPIN (Supporting Premature Infant Nutrition, spinprogram.ucsd.edu). He is the co-author of the book, Best Medicine: Human Milk in the NICU. Dr. Kim is a clinical consultant with Medela LLC.

One thought on “Finding Z: Expanding on the Growth of Neonates

  1. “Some have advocated (shout out to Ian Griffin) for standardizing the growth data into a simple linear x-y chart with z-score on the y axis… but we need to convince our EMR companies to incorporate it….”

    Crib Notes, a NICU-specific EMR module that integrates with enterprise system, (cribnotes.com) does exactly that, and the display of Z-scores in this way changes the way we see growth data. Looking at the conventional growth charts, it’s often difficult to appreciate subtle reductions in the weight percentile, particularly for the severely growth restricted population. Our initial experience is that prior assessments of adequacy of weight gain have not been correct, and we are beginning to more aggressively increase calories in pursuit of a least a flat Z-score line.

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