Abstract Sat1208: Decoding Code Blue: An Analysis of Early Warning Scores, Diurnal Variation, and Potassium Prior to In-Hospital Cardiac Arrest

Background: Identifying patients at high risk for in-hospital cardiac arrest (IHCA) is critical for improving survival. While early warning scores (MEWS), metabolic derangements like dyskalemia, and diurnal patterns have been studied independently, a combined analysis of these pre-arrest characteristics is needed to create a more robust profile of patients at imminent risk. We aimed to identify predictors of IHCA by analysing physiological deterioration scores (MEWS), pre-arrest serum potassium(K), and timing of events in a multi-centre cohort. Methods: We conducted a retrospective chart review of 92 "Code Blue" events across three affiliated hospitals from November 1, 2024, to January 31, 2025. Subsequent codes within 20 minutes of ROSC were excluded. We collected data on: 1) MEWS scores within the 4 hours preceding the event; 2) the serum potassium level closest to the event, categorized as hypokalemia (<3.5 mEq/L), normokalemia (3.5-5.5), or hyperkalemia (>5.5); and 3) the time of day of the event. Analysis included descriptive statistics, binomial distribution analysis for MEWS, and Fisher’s Exact Test for K levels. Results/Data: Of 92 IHCA events (mean patient age 67.7 years), a distinct diurnal pattern was observed, with a primary peak in events between 08:00 and 11:00 and a secondary peak at 18:00. For patients with available data (n=63), a majority (57.1%) had a pre-arrest MEWS ≥ 4. Pre-arrest K was recorded in only 43 events (46.7%); of these, hypokalemia was present in 8 patients (18.6%) and hyperkalemia in 2 (4.7%), with no significant difference between these proportions (p=0.174). Conclusion: This multi-center analysis reveals potential opportunities for proactive intervention. A significant proportion of events cluster in the late morning, suggesting that resource allocation and heightened surveillance may be beneficial during these peak hours. Furthermore, the high prevalence of MEWS ≥ 4 pre-arrest, while not reaching statistical significance in this cohort, supports its use as a critical alert for potential clinical deterioration. Care escalation such as a rapid response in these patients with elevated MEWS score did not occur and cardiac arrest occurred. Given dyskalemia is present so frequently, further data is needed to explore whether intra-code measurement of K via point of care testing may change code outcomes. Combining temporal and physiological data may enhance risk stratification and help prevent in-hospital cardiac arrests.

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Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.sat1208
Primary Topic
Cardiac Arrest and Resuscitation
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article
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article

Abstract Sat1208: Decoding Code Blue: An Analysis of Early Warning Scores, Diurnal Variation, and Potassium Prior to In-Hospital Cardiac Arrest

Aradhya Abrol, Hareem Khalid, Sidrah Khan, Rafla Hassan et al.
Circulation
Cardiac Arrest and Resuscitation
article

Abstract Sat1208: Decoding Code Blue: An Analysis of Early Warning Scores, Diurnal Variation, and Potassium Prior to In-Hospital Cardiac Arrest

Aradhya Abrol, Hareem Khalid, Sidrah Khan, Rafla Hassan, Sreelatha Naik, Talha Liaqat, Ayla Karca, S Redding
article en

Abstract

Background: Identifying patients at high risk for in-hospital cardiac arrest (IHCA) is critical for improving survival. While early warning scores (MEWS), metabolic derangements like dyskalemia, and diurnal patterns have been studied independently, a combined analysis of these pre-arrest characteristics is needed to create a more robust profile of patients at imminent risk. We aimed to identify predictors of IHCA by analysing physiological deterioration scores (MEWS), pre-arrest serum potassium(K), and timing of events in a multi-centre cohort. Methods: We conducted a retrospective chart review of 92 "Code Blue" events across three affiliated hospitals from November 1, 2024, to January 31, 2025. Subsequent codes within 20 minutes of ROSC were excluded. We collected data on: 1) MEWS scores within the 4 hours preceding the event; 2) the serum potassium level closest to the event, categorized as hypokalemia (<3.5 mEq/L), normokalemia (3.5-5.5), or hyperkalemia (>5.5); and 3) the time of day of the event. Analysis included descriptive statistics, binomial distribution analysis for MEWS, and Fisher’s Exact Test for K levels. Results/Data: Of 92 IHCA events (mean patient age 67.7 years), a distinct diurnal pattern was observed, with a primary peak in events between 08:00 and 11:00 and a secondary peak at 18:00. For patients with available data (n=63), a majority (57.1%) had a pre-arrest MEWS ≥ 4. Pre-arrest K was recorded in only 43 events (46.7%); of these, hypokalemia was present in 8 patients (18.6%) and hyperkalemia in 2 (4.7%), with no significant difference between these proportions (p=0.174). Conclusion: This multi-center analysis reveals potential opportunities for proactive intervention. A significant proportion of events cluster in the late morning, suggesting that resource allocation and heightened surveillance may be beneficial during these peak hours. Furthermore, the high prevalence of MEWS ≥ 4 pre-arrest, while not reaching statistical significance in this cohort, supports its use as a critical alert for potential clinical deterioration. Care escalation such as a rapid response in these patients with elevated MEWS score did not occur and cardiac arrest occurred. Given dyskalemia is present so frequently, further data is needed to explore whether intra-code measurement of K via point of care testing may change code outcomes. Combining temporal and physiological data may enhance risk stratification and help prevent in-hospital cardiac arrests.

CirculationVol. 152(Suppl_3)
Geisinger Wyoming Valley Medical Center (US), Geisinger Health System (US), Geisinger Commonwealth School of Medicine (US)
Openalex Percentile: Top 53%
Cardiac Arrest and Resuscitation
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