Pediatric Echo Z-Scores: A Practical Guide

Summary

• A z-score expresses how far a cardiac measurement lies from the expected mean for a child's body size: Z = (observed value − predicted mean) / SD [2].
• By convention, −2 to +2 is the normal range for most cardiac structures. +2 to +3 is mild dilation, and >+3 is moderate to severe dilation requiring follow-up [2].
• For coronary arteries, a z-score ≥10 defines a giant aneurysm (Kawasaki disease) and mandates intervention [3,6].
• The 2024 AHA aortopathy statement grades aortic dilation as mild (z 2-3), moderate (z 3-4), severe (z 4-5), and very severe (z >5) [4].
• Body surface area (BSA) is the preferred indexing variable for cardiac chamber size in children, and the Haycock formula is recommended by ASE guidelines [1].
• Existing BSA-based z-score models systematically underestimate abnormality in overweight and obese children, by more than 0.8 z-score units in some series [10,11].

Scoring

General cardiac structures

Source: standard pediatric echocardiographic quantification convention [2].

Aortic dilation (2024 AHA aortopathy statement) [4]

Coronary artery involvement, Kawasaki disease (AHA classification) [3,6]

Clinical pearl. High-risk features that warrant consideration of intensified initial therapy for Kawasaki disease include a baseline coronary artery z-score ≥2.5 and age <6 months [6]. Patients with small coronary aneurysms (z <5) show near-universal normalization and near-zero risk of adverse cardiac events; those with z-score ≥10 remain at substantial risk [6].

Body Surface Area

Cardiac structure growth correlates with cardiac output, and cardiac output correlates with total body size. This is why BSA, rather than age or weight alone, is the most widely accepted indexing variable for cardiovascular z-scores [1].

Calculate BSA in the BSA Calculator →

Caution. The same BSA formula must be used consistently for serial measurements in an individual patient. Errors in height or weight measurement cascade through the z-score calculation and can cause misclassification.

Reference Systems

General cardiac structures

A 2021 comparison found PHN curves similar to Boston and Italian curves for most measurements but divergent from Detroit curves at high BSA. Despite excellent overall correlation between models, significant z-score differences were seen for many individual measurements, which matters when comparing publications that use different models and when z-score thresholds drive clinical decisions [7].

Compare PHN and Detroit datasets in the Echo Z-Score Calculator →

Coronary artery z-scores

Both systems perform comparably across populations, though the Canadian (Dallaire) system defines a higher proportion of abnormalities. AHA risk stratification for Kawasaki disease is based on formulas from the NHLBI Pediatric Heart Network [8].

Run coronary-specific assessment in the Coronary Z-Score Calculator →

Browse all pediatric z-score calculators →

Neonates and young infants

A 2023 study of more than 13,000 healthy newborns found LV parameters measured in the first week of life differed substantially from those measured in subsequent weeks, requiring separate reference intervals for the two periods [5]. Standard z-score systems may be less reliable at the extremes of BSA; use age-specific reference intervals when available for neonatal echocardiography [5].

Emerging systems

A 2025 Canadian study of more than 20,000 children developed z-score equations adjusted for body size, BMI, and age using generalized additive models (GAMLSS). These showed less bias than BSA-only models in overweight, young, and early school-aged children [9].

Limitations

Obesity. BSA-based z-scores carry systematic bias in overweight and obese children. A multicenter study found existing BSA-based z-scores incompletely adjust for weight and BMI, underestimating true abnormality by more than 0.8 z-score units in higher-BMI subjects compared with lean subjects, because BSA-based models overestimate predicted dimensions as weight or BMI increases [10].

Height-based normalization produces higher cardiovascular z-scores in heavier children, while BSA-based normalization produces higher z-scores in lighter children; increasing BMI has opposite effects on the two approaches. Models using height and weight as independent predictors, rather than combined into BSA, may reduce residual associations with abnormal body habitus [11].

Measurement variability. A small measurement error can shift z-score classification substantially, particularly in young patients. Interobserver variability for echocardiographic measurements is reported at ≥5% [2].

Extremes of body size. Z-scores from different models diverge at both extremes of BSA. Detroit z-scores diverge from PHN z-scores at high BSA [7]. In neonates at the extremes of BSA, existing reference intervals can yield differing z-scores for the same measurement [5].

Clinical Applications

Kawasaki disease. Coronary artery z-scores are central to risk stratification and management under the AHA classification (see Scoring, above) [3,6].

Clinical pearl. A coronary artery z-score climbing from 2.5 toward 5 over serial studies, in an infant under 6 months of age, is a high-risk trajectory that warrants consideration of intensified initial therapy [6].

Cardiomyopathy. Serial z-scores track disease progression. An LV z-score climbing from 2 to 4 over months signals the need to discuss transplant listing or mechanical support.

Aortopathy. The 2024 AHA statement recommends z-score-based severity classification for aortic dilation, with intervention thresholds that vary by underlying diagnosis (for example, Marfan syndrome versus bicuspid aortic valve) [4].

Post-surgical surveillance. Trends matter more than single values. Remodeling back toward normal z-scores is reassuring; progressive increases push toward re-intervention.

Management

Practical steps for applying z-scores in clinical practice:

1. Use the same z-score system consistently within an institution and for serial measurements in an individual patient.
2. Verify the echo system's reference set. Spot-check automated calculations against the Echo Z-Score Calculator occasionally, since software errors occur.
3. Ensure accurate anthropometrics. Inaccurate height or weight is a common source of z-score error.
4. Report z-scores prominently, alongside the raw measurement, not buried at the end of the report.
5. Optimize measurement technique. If a measurement looks borderline, obtain it in two planes.
6. Account for obesity effects. In obese children, BSA-based z-scores may underestimate true abnormality; correlate clinically [10,11].
7. Use age-appropriate reference intervals for neonates, particularly in the first week of life [5].
8. Interpret z-scores in clinical context. A z-score of 2.1 does not mandate intervention on its own; weigh symptoms, chamber function, rate of change, and underlying diagnosis. A stable or normalizing z-score on serial echoes is reassuring; progressive increases push toward earlier intervention.

Caution. The z-score is a tool, not a decision. Clinical judgment remains essential.

References

1. Lopez L, Saurers DL, Barker PCA, et al. Guidelines for Performing a Comprehensive Pediatric Transthoracic Echocardiogram: Recommendations From the American Society of Echocardiography. J Am Soc Echocardiogr. 2024;37(2):119-170.
2. Lopez L, Colan SD, Frommelt PC, et al. Recommendations for Quantification Methods During the Performance of a Pediatric Echocardiogram. J Am Soc Echocardiogr. 2010;23(5):465-495.
3. McCrindle BW, Rowley AH, Newburger JW, et al. Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement From the American Heart Association. Circulation. 2017;135(17):e927-e999.
4. Morris SA, Flyer JN, Yetman AT, et al. Cardiovascular Management of Aortopathy in Children: A Scientific Statement From the American Heart Association. Circulation. 2024;150(11):e228-e254.
5. Vøgg ROB, Sillesen AS, Wohlfahrt J, et al. Normative Echocardiographic Left Ventricular Parameters and Reference Intervals in Infants. J Am Coll Cardiol. 2023;81(22):2175-2185.
6. Jone PN, Tremoulet A, Choueiter N, et al. Update on Diagnosis and Management of Kawasaki Disease: A Scientific Statement From the American Heart Association. Circulation. 2024;150(23):e481-e500.
7. Lopez L, Frommelt PC, Colan SD, et al. Pediatric Heart Network Echocardiographic Z Scores: Comparison With Other Published Models. J Am Soc Echocardiogr. 2021;34(2):185-192.
8. Lopez L, Colan S, Stylianou M, et al. Relationship of Echocardiographic Z Scores Adjusted for Body Surface Area to Age, Sex, Race, and Ethnicity: The Pediatric Heart Network Normal Echocardiogram Database. Circ Cardiovasc Imaging. 2017;10(11):e006979.
9. Lauzon-Schnittka J, Plante V, Dahdah N, et al. Z Scores for Pediatric Echocardiography Dimensions Adjusted for Body Size, BMI, and Age. Circ Cardiovasc Imaging. 2025;:e017944.
10. Plante V, Gobeil L, Xiong WT, et al. Alternative to Body Surface Area as a Solution to Correct Systematic Bias in Pediatric Echocardiography Z Scores. Can J Cardiol. 2021;37(11):1790-1797.
11. Mahgerefteh J, Lai W, Colan S, et al. Height Versus Body Surface Area to Normalize Cardiovascular Measurements in Children Using the Pediatric Heart Network Echocardiographic Z-Score Database. Pediatr Cardiol. 2021;42(6):1284-1292.