Elsevier

Heart Rhythm

Volume 19, Issue 8, August 2022, Pages 1325-1333
Heart Rhythm

Clinical
Outcomes
The impact of heart rate circadian rhythm on in-hospital mortality in patients with stroke and critically ill: Insights from the eICU Collaborative Research Database

https://doi.org/10.1016/j.hrthm.2022.03.1230Get rights and content

Background

Data showing the impact of dysregulated heart rate circadian rhythm in patients with stroke and critically ill are scarce.

Objective

The purpose of this study was to investigate whether the circadian rhythm of heart rate was an independent risk factor for in-hospital mortality in patients with stroke and critically ill.

Methods

Study patients from the recorded eICU Collaborative Research Database were included in the present analyses. Three variables—mesor, amplitude, and peak time—were used to evaluate the heart rate circadian rhythm. The incremental value of circadian rhythm variables in addition to Acute Physiology and Chronic Health Evaluation (APACHE) IV score to predict in-hospital mortality was explored.

Results

A total of 6201 patients whose heart rate have cosinor rhythmicity. After adjustments, mesor per 10 beats/min increase was associated with a 1.18-fold (95% confidence interval [CI] 1.12- to 1.25-fold; P < .001) and amplitude per 5 beats/min was associated with a 1.17-fold (95% CI 1.07- to 1.27-fold; P < .001) increase in the risk of in-hospital mortality. The risk of in-hospital mortality was highest in patients who had peak time reached between 12:00 and 18:00 (odds ratio 1.35; 95% CI 1.06–1.72; P = .015). Compared with APACHE IV score only (c-index 0.757), a combination of APACHE IV score and circadian rhythm variables of heart rate (c-index 0.766) was associated with increased discriminative ability (P = .003).

Conclusion

Circadian rhythm of heart rate is an independent risk factor for in-hospital mortality in patients with stroke and critically ill. Including circadian rhythm variables of heart rate might increase the discriminative ability of the risk score to predict the prognosis of patients.

Introduction

Circadian rhythm is a representation of the solar day in the human body that allows the body to adapt to predictable changes in environmental time, and its coordination is essential for maintaining optimal physiological function and physical and mental health.1,2 Dysregulated circadian rhythm is associated with a variety of diseases, such as cardiovascular disease, depression, anxiety, and metabolic obesity.2,3

Generally, circadian rhythms cause the heart rate to rise during the day and decrease at night.4 The dysregulation of the heart rate circadian rhythm is an independent predictor of cardiovascular and nervous system diseases.5 It has been shown that the level of ischemic or hemorrhagic lesions in the cerebral hemisphere and the brainstem may result in impaired heart rate of circadian rhythm variability6; however, in patients with stroke and critically ill, the impact of the impaired circadian rhythm of heart rate in terms of all-cause mortality is still poorly understood.

The eICU Collaborative Research Database (https://eicu-crd.mit.edu) is one of the largest public databases in the world. It collects a large amount of high-quality clinical information of patients admitted to the intensive care unit (ICU) in 208 hospitals in the United States.7 In the present analyses, on the basis of data from the eICU Collaborative Research Database, we investigate the impact of circadian rhythm of heart rate on in-hospital mortality in patients with stroke and critically ill.

Section snippets

Methods

The present study collected data from the eICU Collaborative Research Database v2.0. The eICU Collaborative Research Database is a large public database created by Philips Healthcare in collaboration with the Laboratory for Computational Physiology at the Massachusetts Institute of Technology, covering routine data from 200,859 patients admitted to the ICU in 208 hospitals in the United States in 2014 and 2015, collecting a large amount of high-quality clinical information, including vital

Demographic and clinical characteristics

Of the total of 200,859 patients enrolled in the eICU database, 6354 patients were included in the present analyses, including 6201 (97.6%) patients whose heart rate have cosinor rhythmicity, 32 (0.5%) patients whose heart rate have 2 peaks/decreases during the day, and 121 (1.9%) patients whose heart rate showed circadian rhythm disruption (Figure 1). The baseline characteristics of patients with stroke and critically ill whose heart rate have cosinor rhythmicity are listed in Table 1.

Discussion

The main findings of the present analyses can be summarized as follows: (1) The circadian rhythm variables of heart rate (mesor, amplitude, and peak time) were the independent risk factors for in-hospital mortality in patients with stroke and critically ill. (2) Mesor per 10 beats/min increase and amplitude per 5 beats/min increase were associated with a 1.18-fold and a 1.17-fold increase in the risk of in-hospital mortality, respectively. In addition, the risk of in-hospital mortality was

Conclusion

We found that heart rate circadian rhythm changes can predict in-hospital mortality in patients with stroke and critically ill. Adding circadian rhythm variables such as mesor, amplitude, and peak time can increase the predictive effect of APACHE IV score on in-hospital mortality. In addition, for medications able to affect heart rate, differences in whether to use or when they were prescribed affected the circadian rhythm variables in the prediction of in-hospital mortality.

References (35)

  • T.J. Pollard et al.

    The eICU Collaborative Research Database, a freely available multi-center database for critical care research

    Sci Data

    (2018)
  • J.E. Zimmerman et al.

    Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients

    Crit Care Med

    (2006)
  • R. Parsons et al.

    CircaCompare: a method to estimate and statistically support differences in mesor, amplitude and phase, between circadian rhythms

    Bioinformatics

    (2020)
  • G. Cornelissen

    Cosinor-based rhythmometry

    Theor Biol Med Model

    (2014)
  • M.A. Kirkman et al.

    The intensive care management of acute ischemic stroke: an overview

    Intens Care Med

    (2014)
  • J.P. Broderick et al.

    Relationship of cardiac disease to stroke occurrence, recurrence, and mortality

    Stroke

    (1992)
  • J. Li et al.

    Stroke-related complications in large hemisphere infarction: incidence and influence on unfavorable outcome

    Ther Adv Neurol Disord

    (2019)

    • Cited by (7)

    View all citing articles on Scopus

    Funding Sources: This research was financially supported by the Special Support Scheme for Shaanxi Province, the Subject Innovation Team of Shaanxi University of Chinese Medicine (#2019-YS01), and Shaanxi Province Administration of Traditional Chinese Medicine Foundation of China (#2021-ZZ-JC018).

    Disclosures: The authors have no conflicts of interest to disclose.

    Availability of data and materials: Data analyzed during the present study are currently stored in the eICU Collaborative Research Database (https://eicu-crd.mit.edu). After completing the required training course (the Collaborative Institutional Training Initiative) and requesting access to the eICU Collaborative Research Database, researchers can seek to use the database. The author Z.Y. obtained the access of the database (certification number 40608375), and the relevant data were also available on Mendeley Data (https://doi.org/10.17632/jj3pgt3c36.1).

    1

    Co-first author.

    View full text
    © 2022 Heart Rhythm Society. All rights reserved.