Background: Hyperkalemia is common among patients on maintenance hemodialysis (HD) and is associated with mortality. We hypothesized that clinical characteristics available at time of paramedic assessment before emergency department (ED) ambulance transport (ambulance-ED) would associate with severe hyperkalemia (K≥6 mmol/L). Rapid identification of patients who are at risk for hyperkalemia and thereby hyperkalemia-associated complications may allow paramedics to intervene in a timely fashion, including directing emergency transport to dialysis-capable facilities. Methods: Patients on maintenance HD from a single paramedic provider region, who had at least one ambulance-ED and subsequent ED potassium from 2014 to 2018, were examined using multivariable logistic regression to create risk prediction models inclusive of prehospital vital signs, days from last dialysis, and the presence of prehospital electrocardiogram (ECG) features of hyperkalemia. We used bootstrapping with replacement to validate each model internally, and performance was assessed by discrimination and calibration. Results: Among 704 ambulance-ED visits, severe hyperkalemia occurred in 75 (11%); 26 patients with ED hyperkalemia did not have a prehospital ECG. Younger age at transport, longer HD vintage, more days from last hemodialysis session (OR=49.84; 95% CI, 7.72 to 321.77 for ≥3 days versus HD the same day [before] ED transport), and prehospital ECG changes (OR=6.64; 95% CI, 2.31 to 19.12) were independently associated with severe ED hyperkalemia. A model incorporating these factors had good discrimination (c-statistic 0.82; 95% CI, 0.76 to 0.89) and, using a cutoff of 25% probability, correctly classified patients 89% of the time. Conclusions: Characteristics available at the time of ambulance-ED were associated with severe ED hyperkalemia. An awareness of these associations may allow health care providers to define novel care pathways to ensure timely diagnosis and management of hyperkalemia.
Background: Hyperkalemia is common among patients on maintenance hemodialysis (HD) and is associated with mortality. We hypothesized that clinical characteristics available at time of paramedic assessment before emergency department (ED) ambulance transport (ambulance-ED) would associate with severe hyperkalemia (K≥6 mmol/L). Rapid identification of patients who are at risk for hyperkalemia and thereby hyperkalemia-associated complications may allow paramedics to intervene in a timely fashion, including directing emergency transport to dialysis-capable facilities. Methods: Patients on maintenance HD from a single paramedic provider region, who had at least one ambulance-ED and subsequent ED potassium from 2014 to 2018, were examined using multivariable logistic regression to create risk prediction models inclusive of prehospital vital signs, days from last dialysis, and the presence of prehospital electrocardiogram (ECG) features of hyperkalemia. We used bootstrapping with replacement to validate each model internally, and performance was assessed by discrimination and calibration. Results: Among 704 ambulance-ED visits, severe hyperkalemia occurred in 75 (11%); 26 patients with ED hyperkalemia did not have a prehospital ECG. Younger age at transport, longer HD vintage, more days from last hemodialysis session (OR=49.84; 95% CI, 7.72 to 321.77 for ≥3 days versus HD the same day [before] ED transport), and prehospital ECG changes (OR=6.64; 95% CI, 2.31 to 19.12) were independently associated with severe ED hyperkalemia. A model incorporating these factors had good discrimination (c-statistic 0.82; 95% CI, 0.76 to 0.89) and, using a cutoff of 25% probability, correctly classified patients 89% of the time. Conclusions: Characteristics available at the time of ambulance-ED were associated with severe ED hyperkalemia. An awareness of these associations may allow health care providers to define novel care pathways to ensure timely diagnosis and management of hyperkalemia.
Keywords:
acid/base and electrolyte disorders; ambulance; emergency health services; end stage kidney disease; hyperkalemia; paramedic; risk prediction; transport
Authors: Henry H Ting; Harlan M Krumholz; Elizabeth H Bradley; David C Cone; Jeptha P Curtis; Barbara J Drew; John M Field; William J French; W Brian Gibler; David C Goff; Alice K Jacobs; Brahmajee K Nallamothu; Robert E O'Connor; Jeremiah D Schuur Journal: Circulation Date: 2008-08-13 Impact factor: 29.690
Authors: Amelie Bernier-Jean; Germaine Wong; Valeria Saglimbene; Marinella Ruospo; Suetonia C Palmer; Patrizia Natale; Vanessa Garcia-Larsen; David W Johnson; Marcello Tonelli; Jörgen Hegbrant; Jonathan C Craig; Armando Teixeira-Pinto; Giovanni F M Strippoli Journal: Clin J Am Soc Nephrol Date: 2021-12-01 Impact factor: 8.237
Authors: Hui Zhang; Douglas E Schaubel; John D Kalbfleisch; Jennifer L Bragg-Gresham; Bruce M Robinson; Ronald L Pisoni; Bernard Canaud; Michel Jadoul; Takashi Akiba; Akira Saito; Friedrich K Port; Rajiv Saran Journal: Kidney Int Date: 2012-02-01 Impact factor: 10.612