Sleep Disruption is Associated with Increased Ventricular Ectopy and Cardiac Arrest in Hospitalized Adults
Bibliographic record
Abstract
To determine whether sleep disruption increases ventricular ectopy and the risk of cardiac arrest in hospitalized patients. Hospital emergency codes (HEC) trigger multiple hospital-wide overhead announcements. In 2014 an electronic “code white” program was instituted to protect staff from violent patients. This resulted in an increase in nocturnal HEC. Telemetry data was examined between September 14 and October 2, 2014. The frequency of nocturnal announcements was correlated with changes in frequency of premature ventricular complexes per hour (PVC/h). Cardiac arrest data were examined over a 3-y period. All HEC were assumed to have triggered announcements. The relationship between nocturnal HEC and the incidence of subsequent cardiac arrest was examined. 2,603 hours of telemetry were analyzed in 87 patients. During nights with two or fewer announcements, PVC/h decreased 33% and remained 30% lower the next day. On nights with four or more announcements, PVC/h increased 23% (P < 0.001) and further increased 85% the next day (P = 0.001). In 2014, following the introduction of the code white program, the frequency of all HEC increased from 1.1/day to 6.2/day (P < 0.05). The frequency of cardiac arrest/24 h rose from 0.46/day in 2012–2013 to 0.62/day in 2014 (P = 0.001). During daytime hours (06:00–22:00), from 2012 through 2014, the frequency of cardiac arrest following zero, one or at least two nocturnal HEC were 0.331 ± 0.03, 0.396 ± 0.04 and 0.471 ± 0.09 respectively (R2 = 0.99, P = 0.03). Sleep disruption is associated with increased ventricular ectopy and increased frequency of cardiac arrest. In healthy subjects, acute sleep disturbance is associated with adverse metabolic and electrophysiologic effects. It is unclear whether this translates into clinically relevant events in hospitalized patients. At our hospital overhead announcements such as fire alarms and cardiac arrest are broadcast directly into patient rooms. At night, these announcements acutely disrupt sleep. We studied the effect of these announcements on ventricular ectopy as captured on telemetry and the hospital-wide frequency of cardiac arrest. We found a striking correlation between nocturnal announcements and both increased ventricular ectopy and the frequency of cardiac arrest. These data reveal the clinical relevant effects of acute sleep disruption and represent a call to action to improve the sleep environment for hospitalized patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".