Blood Pressure Classification Status in Children With CKD Following Adoption of the 2017 American Academy of Pediatrics Guideline

Abstract

Rationale and objective:

Accurate detection of hypertension is crucial for clinical management of pediatric chronic kidney disease (CKD). The 2017 American Academy of Pediatrics childhood hypertension guidelines included new normative blood pressure (BP) values and revised definitions of BP categories. In this study, we examined the effect of applying these changes to the Chronic Kidney Disease in Children (CKiD) cohort compared to use of the 2004 Fourth Report normative data and definitions.

Study Design:

Observational cohort study.

Setting and participants:

Children and adolescents in the CKiD cohort.

Exposures:

Clinic blood pressure measurements.

Outcome:

Blood pressure percentiles and hypertension stages calculated using the 2017 and 2004 guidelines.

Analytical approach:

Agreement analysis compared the estimated percentile and prevalence of high blood pressure based on the 2017 and 2004 guidelines to clinic and combined ambulatory blood pressure readings.

Results:

The proportion of children classified as having normal clinic blood pressure was similar using the 2017 and 2004 guidelines, but the use of the 2017 normative data classified more participants as having hypertensive-range blood pressure (22% vs. 11%) with marginal reproducibility (kappa= 0.569, 95%CI: 0.538, 0.599). Those identified as hypertensive by the 2017 guidelines had higher levels of proteinuria compared to those identified using the 2004 guidelines. There were substantially more participants with white coat and ambulatory hypertension when using the 2017 guidelines (3.5% vs. 1.5%; and 15.5% vs. 7.9%, respectively). The proportion with masked hypertension was lower using the 2017 guidelines (40.2% vs. 47.8%, respectively) with good reproducibility (kappa= 0.799, 95%CI: 0.778, 0.819), and the percentage of participants with normal ambulatory blood pressure was similar (40.9% vs. 42.9%, respectively),

Limitations:

Relationship with long-term progression and target organ damage was not assessed.

Conclusion:

A greater percentage of children with CKD were identified as hypertensive based on both clinic and ambulatory blood pressure when using the 2017 vs. the 2004 guidelines, and the 2017 guidelines better discriminated those with higher levels of proteinuria. The substantial differences in the classification of hypertension when using the 2004 vs. 2017 guidelines should inform clinical care.

INTRODUCTION

In 2017, the American Academy of Pediatrics (AAP) released an updated clinical practice guideline (CPG) for evaluation and management of hypertension in children and adolescents¹. The AAP CPG includes new normative blood pressure (BP) values based upon blood pressure measurements restricted to those obtained in children of normal body weight², and revised the classification system for childhood hypertension, including adoption of adult hypertension thresholds for adolescents aged ≥13 years of age³. The revision was considered a transformative improvement that incorporated the latest understanding of hypertension detection and pathology for pediatric populations. Several studies have since demonstrated that these changes lead to an overall increase in the percentage of children diagnosed with hypertension, with differential effects by age^4–8. Additionally, categorization of BP patterns using ambulatory blood pressure monitoring and clinically measured BP has also been shown to be affected by the changes in the AAP CPG, leading to higher percentages of children with white coat hypertension and fewer with masked hypertension⁹.

We previously demonstrated that hypertension is highly prevalent among children with chronic kidney disease (CKD), and that it plays an important role in mediating progression of childhood CKD^10–15. The new blood pressure values and thresholds in the AAP CPG, while similar, do not directly map from the earlier guideline based on age, sex and height alone because of the changes in the definition of the normative population. Thus, they are expected to modify estimates of the prevalence of both office and ambulatory hypertension in a representative population of children with kidney diseases, but these potential changes have not been comprehensively characterized. In this study, we sought to characterize and describe the consequences of application of the 2017 AAP CPG to define hypertension in children with CKD compared to the previous guideline. This descriptive comparison aims to provide updated prevalence estimates of hypertension and BP control in a unique population of children with chronic kidney diseases using standardized BP measurements, including both clinic and ambulatory blood pressure.

METHODS

Study Population

The Chronic Kidney Disease in Children (CKiD) study is an observational cohort study of children with CKD in the United States and Canada. Children age 1–16 with a diagnosis of CKD and estimated glomerular filtration rate between 30–90 ml/min per 1.73 m² were eligible for inclusion. Briefly, participants contributed data at annual study visits, including objective measures of kidney function, cardiovascular health and growth; self- or parental-reported general health, medical history and medication use. The full study protocol has been described previously¹⁶. All participants provided informed consent/assent and all protocols were approved by local Institutional Review Boards. For this analysis, we described blood pressure percentiles in pediatric participants (age < 18) using the normative blood pressure values and classification schemes from the 2004 Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents¹⁷ and from the 2017 AAP CPG¹. A secondary analysis describes ambulatory blood pressure in a subset of those contributing 24-hour ambulatory blood pressure monitoring (ABPM) studies.

Blood pressure measurement

Clinic blood pressure (BP) was measured by auscultation using a centrally calibrated aneroid sphygmomanometer and was summarized as the average of at least two or up to three auscultatory measurements obtained at least 30 seconds apart. Details of the CKiD clinic BP measurement protocol have been published previously [10]. Height (cm) was measured using a stadiometer and calculated as the average of two measurements taken at each visit. Age- and sex- specific height z-scores were calculated using growth charts from the Centers for Disease Control (CDC)¹⁸.

Ambulatory blood pressure (ABP) data were collected over twenty-four-hours at the second annual study visit and every two years thereafter using an oscillometric device (Spacelabs 90217, Spacelabs, Inc., Issaquah, WA, USA). Research-quality ABPM studies were restricted to those with >21 hours of data collected, no more than 3 total missed hours, wake success rate ≥ 75%, and sleep success rate ≥ 75%. Additional details of the ABPM study protocol have been published previously¹⁹.

Blood Pressure Guidelines

The primary aim of this analysis was to assess the impact of changing from the 2004 Fourth Report to the 2017 AAP Clinical Practice Guideline on classification of blood pressure status of CKiD study participants. We briefly describe each classification system in turn.

Fourth Report (2004)

Normative blood pressure values were calculated in the Fourth Report using all data from ~70,000 children aged 8 to 17 in the NHANES database. Systolic and diastolic percentiles were calculated using mixed-effects linear regression models based on age, sex, and height¹⁷.

American Academy of Pediatrics (2017)

The 2017 AAP CPG¹ implemented two major changes to the calculation of blood pressure percentiles. First, given the known effects of obesity on BP in childhood²⁰, approximately 20,000 children with overweight and obesity were excluded from the calculation of normal population BP percentiles. Inclusion of these children in the Fourth Report normative data likely led to biased percentile estimates. Therefore, the normative values in the CPG were based on a population of roughly 50,000 normal-weight children. Second, percentiles were calculated using quantile regression models based on age, sex, and height. These models were more flexible and provided the best fit compared to other models tested². Another important feature was that these models were restricted to children less than 18 years with height z-score > −3.09 or < 3.09 which correspond to extreme values: shorter than 0.1% of the normal population and taller than 99.9% of the normal population, respectively.

Blood Pressure Classification

Clinic Blood Pressure

Blood pressure categories are described in Table 1a (Fourth Report) and 1b (AAP CPG). Major changes in the 2017 AAP CPG classification system compared to that in the Fourth Report included adoption of the term ‘elevated BP’ for BP values between the 90^th and 95^th percentiles, and simplification of the stage 2 hypertension threshold. Additionally, static cut-points were adopted for children 13 years of age and older; the resultant categories are congruent with those in the latest adult guidelines³.

Table 1.

Descriptive characteristics of study population across all person-visits with available blood pressure staging data (n= 6031 person-visits from 1041 participants), stratified by BP stage based on the 2004 Fourth Report and 2017 AAP Clinical Practice Guidelines. Median [25^th percentile, 75^th percentile] or % (n).^*

	2004 Fourth Report				2017 AAP CPG
	Normotensive	Pre-HTN	Stage 1 HTN	Stage 2 HTN	Normotensive	Elevated BP	Stage 1 HTN	Stage 2 HTN
N % of total	4110 68%	1248 21%	605 10%	68 1%	3938 65%	731 12%	1093 18%	269 4%
Age, years	12.9 [9.2, 16.1]	15.2 [10.2, 17.7]	11.3 [7.0, 15.7]	16.4 [9.2, 24.3]	13.4 [9.8, 16.4]	13.7 [8.7, 17.0]	11.4 [7.2, 16.1]	14.7 [9.2, 17.9]
Male sex	60.4% (2481)	74.1% (925)	57.7% (349)	35.3% (24)	58.5% (2303)	72.1% (527)	70.3% (768)	67.3% (181)
Height z-score	−0.48 [−1.18, 0.26]	−0.42 [−1.10, 0.41]	−0.72 [−1.52, −0.01]	−0.29 [−1.06, 0.07]	−0.50 [−1.19, 0.24]	−0.35 [−1.10, 0.48]	−0.51 [−1.23, 0.22]	−0.46 [−1.31, 0.18]
Kidney disease characteristics
Glomerular CKD	23.7% (974)	26.8% (334)	23.1% (140)	38.2% (26)	24.4% (962)	26.1% (191)	21.0% (230)	33.8% (91)
eGFR, mL/min/1.73m2	48.3 [35.3, 62.7]	47.8 [31.9, 63.6]	43.5 [29.8, 59.4]	36.8 [23.8, 52.9]	47.8 [35.0, 62.6]	48.9 [34.7, 62.2]	46.8 [31.5, 63.2]	35.5 [23.4, 57.4]
Urine protein:creatinine (UPC)	0.29 [0.12, 0.81]	0.52 [0.17, 1.50]	0.58 [0.17, 1.95]	1.07 [0.23, 2.53]	0.29 [0.12, 0.83]	0.42 [0.16, 1.16]	0.47 [0.16, 1.50]	1.28 [0.25, 3.17]
0.5 ≤ UPC < 2 mg/mgCr	28.3% (944)	32.4% (317)	28.5% (135)	34.6% (19)	28.7% (925)	32.5% (186)	29.4% (248)	26.4% (56)
UPC ≥ 2 mg/mgCr	8.2% (273)	18.4% (180)	24.7% (117)	30.9% (17)	8.2% (265)	12.9% (74)	19.8% (167)	38.2% (81)
Blood pressure parameters within each system
SBP z-score	−0.22 [−0.81, 0.32]	−1.05 [0.52, 1.44]	1.81 [1.11, 2.25]	3.23 [2.95, 3.84]	−0.33 [−1.00, 0.30]	0.88 [0.25, 1.34]	1.34 [0.44, 1.88]	2.05 [0.55, 2.33]
SBP percentile	41.3 [20.8, 62.5]	85.4 [69.9, 92.5]	96.5 [86.8, 98.8]	99.9 [99.8, 99.9]	45.0 [23.0, 66.0]	85.0 [73.0, 92.0]	94.5 [82.0, 98.0]	99.0 [97.5, 99.0]
DBP z-score	0.10 [−0.42, 0.58]	1.31 [0.61, 1.50]	1.76 [0.94, 2.14]	3.04 [2.80, 3.55]	−0.10 [−0.84, 0.52]	0.64 [−0.52, 1.34]	1.65 [0.50, 1.858]	2.33 [0.00, 2.33]
DBP percentile	54.1 [33.7, 72.0]	90.5 [73.0, 93.3]	96.1 [82.6, 98.4]	99.9 [99.7, 99.9]	53.0 [32.0, 73.0]	82.0 [56.0, 91.0]	96.0 [87.5, 98.0]	99 [98.0, 99.0]

^*Abbreviations used in table: CKD, chronic kidney disease; DBP, diastolic blood pressure, HTN, hypertension; eGFR, estimated glomerular filtration rate; SBP, systolic blood pressure, UPC, urine protein-to-creatinine ratio

Ambulatory Blood Pressure

ABPM studies were classified as normal or abnormal based on data measured during the 24-hour collection. As in previous reports from the CKiD study¹⁹, we defined abnormal ABP as meeting at least one of two conditions: (1) wake or sleep mean ABP ≥ 95th percentile of ambulatory BP or (2) wake or sleep load ≥ 25th percentile. Of note, this interpretation differs from that recommended at the time by the American Heart Association²¹, but has been consistently applied in our prior analyses of ABPM data in the CKiD cohort.

Combination Clinic and Ambulatory Blood Pressure

Clinic and ambulatory BP measurements were combined and classified into one of four blood pressure phenotypes: normal BP (normal clinic BP and normal ABP); white coat hypertension (hypertensive clinic but normal ambulatory BP); masked hypertension (normal clinic BP and hypertensive ABP); and ambulatory hypertension (hypertensive clinic and ambulatory BP).

Statistical Analysis

For assessment of the BP status of CKiD participants based on office BP, the unit of analysis was person-visit with available BP stage data in the pediatric age range (age < 18 years). We compared distributions of blood pressure percentiles by BP guidelines using agreement plots, and described differences using modified Bland-Altman methods to quantify differences based on the 2017 and 2004 normative data. Specifically, for SBP and DBP, we plotted the difference between the 2017 and 2004 percentiles (i.e., 2017 percentile – 2004 percentile) on the 2004 percentiles to characterize how participant classification changed based on use of the normative data from the earlier and current guidelines. To describe how children transitioned between BP stage categories before and after the guidelines were updated, we generated cross-tabulations and quantified differences using the kappa statistic.

To obtain a valid estimate of kappa that does not violate the assumption of independence with repeated measures, we used a resampling approach to randomly select one BP measurement per individual which was categorized according to the 2004 and the 2017 guidelines. Each random sample comprised a single observation from each participant to create cross-sectional subsets of longitudinal data in which observations were independent. From the sampling distribution of 2000 resamplings, the median provided an estimate of the kappa that would have been obtained in a cross-sectional analysis, and the 2.5th and 97.5th percentiles estimated the 95% confidence interval.

To address ABPM data, we also described changes in blood pressure classification based on a combination of office and ambulatory blood pressure (i.e., white coat, masked, confirmed hypertension) in a subset of CKiD participants who underwent ABPM. Similar to the first analysis, we compared distributions of BP classification and how the characterization of ABPM data changed when the guidelines were revised.

All analyses were completed using R version 4.0.2. Statistical significance was defined as p<0.05.

RESULTS

This study had complete blood pressure staging data at 6031 regular study visits from 1041 participants (64% male), as described in Table 1. Across all person-visits, the median age was 13.3 years, median eGFR was 50.4 mL/min/1.73m² and 273 (26%) had a glomerular diagnosis. Mean follow-up time was 4.5 years, during which participants contributed an average of 6.1 person-visits. BP percentile data were available at 5139 person-visits from 1034 participants who were 18 years of age or younger, with a median age across all person-visits of 12.1 years and follow-up contribution of 5.2 person-visits.

According to the 2004 guidelines, 4110 (68%) person-visits were normotensive, 1248 (21%) were pre-hypertensive, and 605 (10%) and 68 (1%) had stage 1 and 2 hypertension, respectively. The 2017 AAP CPG classified 3938 (66%) person-visits as normotensive, 731 (12%) with elevated BP, and 1093 (18%) and 269 (4%) with stage 1 and 2 hypertension, respectively. Based on the 2004 Fourth Report, there were differences in age, sex, diagnosis, based on BP stage, though a clear pattern was not present. However, as participant 2004 Fourth Report BP stage increased, eGFR decreased (median eGFR 48.3 to 36.8 mL/min/1.73m² for the normotensive and stage 2 hypertension person-visits, respectively). This relationship was also observed when classifying participants based on the 2017 AAP CPG: median eGFR for normotensive person-visits was 47.8ml/min|1.73m² and was substantially lower for those in Stage 2 hypertension (median eGFR= 38.7 mL/min/1.73m²). Proteinuria was also substantially higher among those with higher BP classifications, although the discrimination between Stage 1 and Stage 2 hypertension was greater using the 2017 CPG classifications (median uPrCr= 0.47 vs. 1.28 mg/mgCr) compared to the 2004 Fourth report (median uPrCr= 0.58 vs. 1.07 mg/mgCr).

Supplemental Figure 1 shows the distribution of systolic (panels A & C) and diastolic (panels B & D) blood pressure percentiles separately according to each guideline. Based on the 2004 Fourth Report, the distribution of both SBP and DBP percentiles were skewed right and demonstrated an excess burden of high BP at the upper end of the distribution. This is consistent with the high prevalence of hypertension in this population¹⁰. Importantly, for percentiles based on the 2017 AAP CPG normative data, there was even greater skew toward the higher percentiles. Characterization of the proportion of participants with SBP greater than the 95th percentile increased from 9% to 11% from the 2004 to 2017 normative data, while the proportion with DBP greater than the 95th percentile increased from 9% to 13%.

Figure 1 presents a visualization of the differences between the 2004 and 2017 guidelines, with the 2004 guidelines as the reference. Specifically, the x-axis presents the 2004 percentile levels and the y-axis displays the difference between the 2017 and 2004 percentile levels to demonstrate how data changed from 2004- to 2017-derived percentiles. This figure is stratified by SBP (Figure 2a) and DBP (Figure 2b) percentiles. The horizontal reference line indicates no difference in percentiles, and a nonparametric spline describes the average behavior of the data, with 95% confidence bands; however, the density of the data result in very tight confidence bands that are difficult to observe. SBP percentiles based on the 2017 CPG normative data were, on average, increased compared to the 2004 Fourth Report, particularly between the 20^th and 90^th percentiles. For DBP percentiles, substantially higher percentile levels were observed based on the 2017 CPG at percentiles higher than the 50^th percentiles. For both SBP and DBP comparisons, there was substantial variability and not every 2004-calculated BP percentile corresponded to a higher 2017-calcuated percentile.

Figure 1.

Differences between 2017 AAP CBG blood pressure percentiles and 2004 Fourth Report percentiles plotted on the 2004 Fourth Report percentiles, stratified by systolic blood pressure (SBP) and diastolic blood pressure (DBP), with nonparametric lowess splines with 95% confidence bands. The horizontal reference line at 0 indicates no difference between 2017- and 2004-calculated percentiles.

Figure 2.

Description of agreement between BP stages based on 2004 Fourth Report and 2017 AAP CPG (n= 6031 person-visits from 1041 participants). Resampling cross-sectional estimate of Kappa statistic= 0.569 (95% CI: 0.538, 0.599).

Figure 2 describes how classification of participants BP data were distributed between BP stages according to the different guidelines. The largest differences were seen from the Fourth Report prehypertension and stage 1 hypertension groups. Of the 1248 person-visits with prehypertension, a majority increased in severity to stage 1 (52%) or stage 2 (6%) hypertension when applying the 2017 AAP CPG, while only 37% remained in the 2017 elevated hypertension group. Of the 605 person-visits with Fourth Report stage 1 hypertension, 24% transitioned to 2017 AAP CPG Stage 2 hypertension. The kappa statistic for concordance between the two classification systems was 0.569 (95% CI: 0.538, 0.599), indicating marginal reproducibility.

Agreement in blood pressure classification based on a subset of participants with available ambulatory blood pressure data are described in Table 2. From the entire study population, 706 participants contributed successful ABPM data at 1578 visits. Children participating in the ABPM protocol comprised 200 (28%) with a glomerular diagnosis and 430 (61%) boys; participants had a mean age of 12.4 years at their first ABPM visit. Among those who were considered normotensive (Fourth Report), 5% (n = 36) became white coat hypertensive (2017 AAP CPG); in contrast, 17% (n = 4) of those classified with white coat hypertension (Fourth Report) were classified as normotensive in the 2017 CPG. Among those who had stage 1 hypertension (Fourth Report), 17% (n = 130) transitioned to stage 2 hypertension (2017 AAP CPG), while 8% (n = 10) of those with stage 2 hypertension (Fourth Report) were redefined as stage 1 hypertensive (2017 AAP CPG). The kappa statistic for this table was 0.799 (95% CI: 0.778, 0.819) indicating good reproducibility of classification between the two guidelines.

Table 2.

Description of agreement between ambulatory BP categories based on 2004 Fourth Report and 2017 AAP CPG (N=1578 person-visits)^* Resampling cross-sectional estimate of Kappa statistic= 0.799 (95% CI: 0.778, 0.819).

	2004 Fourth Report
2017 AAP CPG	Normotensive n= 677 (42.9%)	White coat HTN n= 23 (1.5%)	Masked HTN n= 754 (47.8%)	Ambulatory HTN n= 124 (7.9%)
Normotensive n= 645 (40.9%)	641 (94.7%)	4 (17.4%)	0 (0%)	0 (0%)
White coat HTN n= 55 (3.5%)	36 (5.3%)	19 (82.6%)	0 (0%)	0 (0%)
Masked HTN n= 634 (40.2%)	0 (0%)	0 (0%)	624 (82.8%)	10 (8.1%)
Ambulatory HTN n= 244 (15.5%)	0 (0%)	0 (0%)	130 (17.2%)	114 (91.9%)

^*Abbreviations used in table: AAP, American Academy of Pediatrics; CPG, clinical practice guideline; HTN, hypertension

DISCUSSION

This comparison of the 2004 Fourth Report and the 2017 AAP CPG normative BP values and classification systems demonstrates important differences that will affect the diagnosis and treatment of hypertension in pediatric CKD. Most importantly, as Figure 2 demonstrates, there was substantial variability of 2017 BP percentiles around the same 2004 BP percentiles. The calculation of percentiles between the two guidelines do not directly map to each other which means that clinicians cannot confidently estimate a patient’s 2017 BP percentile from their 2004 BP percentile alone. While on average, the 2017 CPG normative BP values placed participants into higher percentiles than the 2004 data, substantial heterogeneity was present: determining 2017-based percentiles from 2004-calculated percentiles is challenging without completely re-calculating, with the exception of very low and very high blood pressure levels.

The 2017 guidelines also have implications for ABPM-determined normotension, masked hypertension, white coat hypertension and ambulatory hypertension. Interestingly, the normative data used to interpret pediatric ABPM studies has not changed²¹, but the implementation of the 2017 AAP CPG normative data results in new classifications between normotension and white coat hypertension, and between masked hypertension and confirmed hypertension. We noted that the prevalence of white coat hypertension increased, but remained relatively rare in this population, and the proportion of masked hypertension decreased, with these individuals re-classified as having ambulatory hypertension. This transition demonstrates a major strength of the 2017 guidelines since the proportion with ambulatory hypertension nearly doubled: properly identifying ambulatory and masked hypertension in clinic is essential for the optimal management of CKD-related hypertension in children²².

Changes in trends of pediatric blood pressure have been previously described in NHANES as a representation of the general population⁵. However, the present analysis presents new data specific to a pediatric CKD population in which blood pressure management is critical to delay disease progression. Most importantly, this population is particularly high risk, with a much higher prevalence of elevated blood pressure than in the general population. Furthermore, our results demonstrate that the proportion of CKiD participants with significantly elevated BP is even higher than previously thought.¹⁰

These results underscore the importance of correct identification and classification of BP status in pediatric CKD. Clearly, use of the 2017 CBP normative BP values yields higher percentiles and higher prevalence of hypertension stages compared to the application of the 2004 BP values. Given this, all CKiD analyses now incorporate the 2017 AAP CPG to characterize relative BP percentiles. This change aside, it is important to recognize that even the older CKiD analyses that used the 2004 normative values and consistently demonstrated the importance of BP in the clinical management of CKD^{10–13,23–25}. More recent CKiD publications have used the 2017 guidelines and have already yielded insight into a potential role for clinical measures to help manage BP in pediatric CKD¹⁵, such as demonstrating the effects of calcium channel blocker therapy on BP and proteinuria²⁶.

The new 2017 AAP CPG resolves the previous challenge of differing BP categories between pediatric and adult populations, which was a previous methodologic problem in CKiD due to the 2004 pediatric guidelines. Harmonizing BP staging from pediatric to adult populations is crucial for a longitudinal pediatric and young adult cohort like CkiD in which children are followed into young adulthood, when the cardiovascular complications of CKD may become more clinically apparent. Consistent staging offers valid clinical management and epidemiologic inference through the transition from pediatric to adulthood.

We now discuss implications and considerations for those conducting research, especially in the construction of statistical models for epidemiologic inference, using the new guidelines. Researchers working with pediatric data with transitions to adult should note that BP percentiles and z-scores based on the 2017 AAP guidelines are only applicable to children ≤18 years. Normative z-scores in particular are useful to evaluate differences on the continuous scale and identify linear or nonlinear relationships with an outcome and overcomes the loss of power associated with categorizing by BP stage (i.e., categorization of an independent variable²⁷). This approach is particularly useful for etiologic or risk factor analyses. However, the main limitation is that percentiles (and corresponding z-scores) cannot be calculated for those >19 years old so analyses with BP as a continuous variable are limited to pediatric populations. BP may also be categorized into four stages: normal BP, pre-hypertensive, Stage 1 hypertension, and Stage 2 hypertension. While there may be a potential loss of information in the process of categorizing, there are two main benefits to this approach. First, it reflects the real world in how clinicians diagnose, treat and generally manage BP. Second, it allows for the inclusion of children and young adults in a harmonized and consistent system because the 2017 guidelines offer consistency in BP stage between pediatric and adult populations¹.

These principles also apply when deciding how to handle BP as an outcome in statistical models. The researcher will have to decide if BP on the continuous scale is most appropriate for the study question and restrict to an analytic population of only children and use BP z-scores (which are normally distributed and behave better in regression analyses than percentiles). Alternatively, if the researcher wishes to use hypertension stage as an outcome, then the analytic sample can include both children and young adults. Depending on the question, a four-level categorical outcome could be used in a multinomial logistic regression model, or for a simpler model, one may consider using logistic regression with normal vs. not normal as the outcome.

The differences in BP classification presented in this analysis should be carefully considered as clinicians track and understand longitudinal BP control for individual patients. We recommend re-calculating previous BP percentiles using the 2017 CPG and basing treatment decisions on the reclassified BP stages. Clinicians should be aware that whereas re-calculating percentiles will yield more hypertension and higher BP percentiles in their patient population overall, this may not be true for individual patients given some subtle differences seen in the general pediatric population based on sex and age.²⁸ Similarly, if staging and percentiles of historic data are not re-calculated, there will likely be abruptly higher levels observed for those who were previously within the normal range based on the 2004 Fourth Report and are now being characterized using the 2017 CPG. Clinicians should also be aware that the dynamics are different between SBP and DBP percentiles. For SBP, in general, most percentiles will be higher using the 2017 CPG system (except for those that are very low or very high). For DBP, only BP levels higher than the 50^th percentile by the 2004 system will yield higher percentiles by the 2017 CPG.

Most patients with CKD, adults and children alike, experience inexorable deterioration of kidney function over time. Of the various factors that contribute to this progression, hypertension is perhaps the most amenable to modification, and numerous studies have demonstrated that control of hypertension can indeed delay the need for kidney replacement therapy. The changes in normative data and classification found in the 2017 AAP Clinical Practice Guideline constitute a significant advance in our ability to identify pediatric CKD patients with abnormal BP and implement life-prolonging therapy.