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Abstract: SA-PO682

Derivation and Validation of a Novel Automated Algorithm for Staging Infant Blood Pressures

Session Information

  • Pediatric Nephrology - 2
    October 26, 2024 | Location: Exhibit Hall, Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Pediatric Nephrology

  • 1900 Pediatric Nephrology

Authors

  • Williams, Chloe N., The Hospital for Sick Children, Toronto, Ontario, Canada
  • Jawa, Tasha A., Queen's University, Kingston, Ontario, Canada
  • Cockovski, Vedran, The Hospital for Sick Children, Toronto, Ontario, Canada
  • Nunes, Sophia, The Hospital for Sick Children, Toronto, Ontario, Canada
  • Khondker, Adree, University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada
  • Teoh, Chia Wei, The Hospital for Sick Children, Toronto, Ontario, Canada
  • Radhakrishnan, Seetha, The Hospital for Sick Children, Toronto, Ontario, Canada
  • Zappitelli, Michael, The Hospital for Sick Children, Toronto, Ontario, Canada
Background

Infant blood pressure (BP) is assessed by visual evaluation of sex and age specific BP curves (i.e., “manual staging”). Manual staging is time consuming and error prone, but is the standard method to assess infant BP. We developed and evaluated accuracy of a novel computerized algorithm to stage BP category in infants.

Methods

We retrospectively acquired BP data in electronic health records (EHRs) from infants hospitalized at a quaternary healthcare center between June 2018-August 2019. Infants <1 year old with paired systolic/diastolic BP were included. First or last admission BP was randomly selected for evaluation. An algorithm to estimate published BP curves was created by digitizing age and sex-based infant BP cutoff curves into a series of points, then deriving each curve's equation of best fit via regression. All BP’s were staged manually by two raters (normal, elevated or hypertensive [stage 1 or 2]). The algorithm was evaluated for agreement (using Cohen’s kappa and % agreement) with manual staging.

Results

Of 2407 BP measurements, 1304 patients were staged as normal, 298 elevated BP, and 805 hypertensive by manual staging (inter-rater agreement for manual staging was kappa 0.82 [0.58-1.00]). By the algorithm, 1368 had normal BP, 323 elevated BP and 716 hypertensive. Agreement between manual and algorithm classification was 89.4% (kappa 0.83 [0.82-0.85]). Discrepancy between manual vs. algorithm BP staging was noted for 255 BPs. Five BPs (2% of errors) were incorrectly staged by the algorithm and correctly staged by manual staging; 63 BP’s (24.7% of errors) were incorrectly staged by manual staging and correctly staged by the algorithm. The remaining discrepancies (73.3% of errors) were BPs on/near the curve at the border of normal vs. abnormal BP. The algorithm has been made into a ShinyApp (developed by A. Khondker), available at https://sickkidsnephrology.shinyapps.io/InfantHypertension/ (Figure 1).

Conclusion

The new infant BP staging algorithm has strong agreement with manual staging and may be used to stage BP in infants in the clinical setting and within EHRs.