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Derivation of paediatric blood pressure percentiles from electronic health records.

EBioMedicine(2023)

Cited 0|Views22
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Abstract
BACKGROUND:Identification of abnormal blood pressure (BP) in children requires normative data. We sought to examine the feasibility of using "real-world" office BP data obtained from electronic health records (EHR) to generate age-, sex- and height-specific BP percentiles for children. METHODS:Using data collected 01/01/2009-8/31/2021 from eight large children's healthcare organisations in PEDSnet, we applied a mixed-effects polynomial regression model with random slopes to generate Z-scores and BP percentiles and compared them with currently used normative BP distributions published in the 2017 American Academy of Paediatrics (AAP) Clinical Practise Guidelines (CPG). FINDINGS:We identified a study sample of 292,412 children (1,085,083 BP measurements), ages 3-17 years (53% female), with no chronic medical conditions, who were not overweight/obese and who were primarily seen for general paediatric care in outpatient settings. Approximately 45,000-75,000 children contributed data to each age category. The PEDSnet systolic BP percentile values were 1-4 mmHg higher than AAP CPG BP values across age-sex-height groups, with larger differences observed in younger children. Diastolic BP values were also higher in younger children; starting with age 7 years, diastolic BP percentile values were 1-3 mmHg lower than AAP CPG values. Cohen's Kappa was 0.90 for systolic BP, 0.66 for diastolic BP, and 0.80 overall indicating excellent agreement between PEDSnet and 2017 AAP CPG data for systolic BP and substantial agreement for diastolic BP. INTERPRETATION:Our analysis indicates that real-word EHR data can be used to generate BP percentiles consistent with current clinical practise on BP management in children. FUNDING:Funding for this work was provided by the Preserving Kidney Function in Children with Chronic Kidney Disease (PRESERVE) study; Patient-Centred Outcomes Research Institute (PCORI) RD-2020C2020338 (Principal Investigator: Dr. Forrest; Co-Principal Investigator: Dr. Denburg).
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