Danny Eytan1,2, Andrew J Goodwin1, Robert Greer1, Anne-Marie Guerguerian3, Mjaye Mazwi1, Peter C Laussen1,4. 1. Department of Critical Care Medicine, The Hospital for Sick Children, University of Toronto, Ontario, Canada. 2. Department of Pediatric Critical Care Medicine, Rambam Medical Center, Haifa, Israel. 3. Department of Critical Care Medicine, The Hospital for Sick Children, Research Institute, University of Toronto, Ontario, Canada. 4. Department of Anesthesia, University of Toronto, Ontario, Canada.
Abstract
OBJECTIVES: Define the distributions of heart rate and intraarterial blood pressure in children at admission to an ICU based on admission diagnosis and examine trends in these physiologic signs over 72 hours from admission (or to discharge if earlier). DESIGN: A retrospective analysis of continuously acquired signals. SETTING: A quaternary and primary referral children's hospital with a general PICU and cardiac critical care unit. PATIENTS: One thousand two hundred eighty-nine patients less than 18 years old were analyzed. Data from individual patient admissions were divided into 19 groups by primary admission diagnosis or surgical procedure. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Distributions at admission are dependent on patient age and admission diagnosis (p < 10(-6)). Heart rate decreases over time, whereas arterial blood pressure is relatively stable, with differences seen in the directions and magnitude of these trends when analyzed by diagnosis group (p < 10(-6)). Multiple linear regression analysis shows that patient age, diagnosis group, and physiologic vital sign value at admission explain 50-63% of the variation observed for that physiologic signal at 72 hours (or at discharge if earlier) with admission value having the greatest influence. Furthermore, the variance of either heart rate or arterial blood pressure for the individual patient is smaller than the variance measured at the level of the group of patients with the same diagnosis. CONCLUSIONS: This is the first study reporting distributions of continuously measured physiologic variables and trends in their behavior according to admission diagnosis in critically ill children. Differences detected between and within diagnostic groups may aid in earlier recognition of outliers as well as allowing refinement of patient monitoring strategies.
OBJECTIVES: Define the distributions of heart rate and intraarterial blood pressure in children at admission to an ICU based on admission diagnosis and examine trends in these physiologic signs over 72 hours from admission (or to discharge if earlier). DESIGN: A retrospective analysis of continuously acquired signals. SETTING: A quaternary and primary referral children's hospital with a general PICU and cardiac critical care unit. PATIENTS: One thousand two hundred eighty-nine patients less than 18 years old were analyzed. Data from individual patient admissions were divided into 19 groups by primary admission diagnosis or surgical procedure. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Distributions at admission are dependent on patient age and admission diagnosis (p < 10(-6)). Heart rate decreases over time, whereas arterial blood pressure is relatively stable, with differences seen in the directions and magnitude of these trends when analyzed by diagnosis group (p < 10(-6)). Multiple linear regression analysis shows that patient age, diagnosis group, and physiologic vital sign value at admission explain 50-63% of the variation observed for that physiologic signal at 72 hours (or at discharge if earlier) with admission value having the greatest influence. Furthermore, the variance of either heart rate or arterial blood pressure for the individual patient is smaller than the variance measured at the level of the group of patients with the same diagnosis. CONCLUSIONS: This is the first study reporting distributions of continuously measured physiologic variables and trends in their behavior according to admission diagnosis in critically ill children. Differences detected between and within diagnostic groups may aid in earlier recognition of outliers as well as allowing refinement of patient monitoring strategies.
Authors: Tellen D Bennett; Tiffany J Callahan; James A Feinstein; Debashis Ghosh; Saquib A Lakhani; Michael C Spaeder; Stanley J Szefler; Michael G Kahn Journal: J Pediatr Date: 2019-01-25 Impact factor: 4.406
Authors: Jessica Nicoll; Jonathan Somer; Danny Eytan; Vann Chau; Davide Marini; Jessie Mei Lim; Robert Greer; Safwat Aly; Mike Seed; Steven P Miller; Peter C Laussen; Mjaye L Mazwi; Steven M Schwartz Journal: Crit Care Explor Date: 2022-09-02
Authors: Yogen Singh; Javier Urbano Villaescusa; Eduardo M da Cruz; Shane M Tibby; Gabriella Bottari; Rohit Saxena; Marga Guillén; Jesus Lopez Herce; Matteo Di Nardo; Corrado Cecchetti; Joe Brierley; Willem de Boode; Joris Lemson Journal: Crit Care Date: 2020-10-22 Impact factor: 9.097