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Observational Study
. 2017 May;45(5):790-797.
doi: 10.1097/CCM.0000000000002325.

New-Onset Atrial Fibrillation in the Critically Ill

Affiliations
Observational Study

New-Onset Atrial Fibrillation in the Critically Ill

Travis J Moss et al. Crit Care Med. 2017 May.

Abstract

Objective: To determine the association of new-onset atrial fibrillation with outcomes, including ICU length of stay and survival.

Design: Retrospective cohort of ICU admissions. We found atrial fibrillation using automated detection (≥ 90 s in 30 min) and classed as new-onset if there was no prior diagnosis of atrial fibrillation. We identified determinants of new-onset atrial fibrillation and, using propensity matching, characterized its impact on outcomes.

Setting: Tertiary care academic center.

Patients: A total of 8,356 consecutive adult admissions to either the medical or surgical/trauma/burn ICU with available continuous electrocardiogram data.

Interventions: None.

Measurements and main results: From 74 patient-years of every 15-minute observations, we detected atrial fibrillation in 1,610 admissions (19%), with median burden less than 2%. Most atrial fibrillation was paroxysmal; less than 2% of admissions were always in atrial fibrillation. New-onset atrial fibrillation was subclinical or went undocumented in 626, or 8% of all ICU admissions. Advanced age, acute respiratory failure, and sepsis were the strongest predictors of new-onset atrial fibrillation. In propensity-adjusted regression analyses, clinical new-onset atrial fibrillation was associated with increased hospital mortality (odds ratio, 1.63; 95% CI, 1.01-2.63) and longer length of stay (2.25 d; CI, 0.58-3.92). New-onset atrial fibrillation was not associated with survival after hospital discharge (hazard ratio, 0.99; 95% CI, 0.76-1.28 and hazard ratio, 1.11; 95% CI, 0.67-1.83, respectively, for subclinical and clinical new-onset atrial fibrillation).

Conclusions: Automated analysis of continuous electrocardiogram heart rate dynamics detects new-onset atrial fibrillation in many ICU patients. Though often transient and frequently unrecognized, new-onset atrial fibrillation is associated with poor hospital outcomes.

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Conflict of interest statement

Dr. Moorman received funding from Advanced Medical Predictive Devices, Diagnostics, and Displays. He owns equity and is Chief Medical Officer of Advanced Medical Predictive Devices, Diagnostics, and Displays in Charlottesville, VA, which has licensed related technologies from the University of Virginia Licensing and Ventures Group. For several months in 2015, he received consulting fees. His wife Liza is Clinical Implementation Officer of Advanced Medical Predictive Devices, Diagnostics, and Displays. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Figures

Figure 1.
Figure 1.
Flowchart of criteria for categorization of atrial fibrillation (AF) status. Flowchart of patient admissions analyzed and definitions of categorization according to AF status. ECG = electrocardiogram, MICU = medical ICU, SICU = surgical/trauma/burn ICU.
Figure 2.
Figure 2.
Cumulative incidence of atrial fibrillation (AF). Cumulative incidence of AF as a function of time monitored. There was no significant difference in the cumulative incidence of AF as a function of time monitored between the groups with AF (p = 0.613).
Figure 3.
Figure 3.
Determinants of atrial fibrillation, length of stay, and hospital mortality. Effect of each (A) categorical predictor or (B) continuous predictor across its range on the log odds of developing atrial fibrillation. ses represented by line height or ribbon width, respectively. Grayscale is the relative proportion of variance accounted for by each term measured by Wald chi-square statistics (χ2) minus the degrees of freedom (df). OASIS = Oxford Acute Severity of Illness Score.
Figure 4.
Figure 4.
Determinants of ICU length of stay and hospital mortality. A, Estimated marginal effects on ICU length of stay of most significant predictors and atrial fibrillation (AF) status. For continuous predictors, we estimated the marginal effect between the interquartile range (75th percentile value vs 25th percentile value). B, Estimated odds ratio on hospital mortality of most significant predictors and AF status. For continuous predictors, we estimated the odds ratio between the interquartile range (75th percentile value vs 25th percentile value). OASIS = Oxford Acute Severity of Illness Score.
Figure 5.
Figure 5.
Impact of new-onset atrial fibrillation (AF) on outcomes. A, Probability of survival after hospital discharge according to AF status. Survival estimates at time zero reflect the differences in hospital mortality where admissions with new-onset clinical AF had by the poorest hospital mortality. B, Fold change in hospital outcomes—ICU length of stay (ICU LOS) and hospital mortality for new-onset subclinical and clinical AF as a function of the median AF burden, quantified as the percentage of all ICU monitoring, compared to propensity-matched controls without any AF.

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