Evidence map›Paper›PMID 28458554›Full record

ArticleTherapeutics and clinical risk management2017

Patient characteristics associated with false arrhythmia alarms in intensive care.

Patricia R Harris, Jessica K Zègre-Hemsey, Daniel Schindler, Yong Bai, Michele M Pelter, Xiao Hu

Open access · goldAbstract read
In one paragraph

Article in Therapeutics and clinical risk management, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Reducing False Alarm Rates and Workload in ICUs by Improving Arrhythmia Detection Algorithms of Patient Monitoring Systems.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. An annotated ventricular tachycardia (VT) alarm database: Toward a uniform standard for optimizing automated VT identification in hospitalized patients.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2023
    Article
  11. Article
  12. Observational
  13. Contribution of Electrocardiographic Accelerated Ventricular Rhythm Alarms to Alarm Fatigue.American journal of critical care : an official publication, American Association of Critical-Care Nurses · 2019
    Article
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Patricia R HarrisDepartment of Nursing, School of Health and Natural Sciences, Dominican University of California, San Rafael.
Jessica K Zègre-HemseySchool of Nursing.
Daniel SchindlerIntensive Care Unit, The Neuroscience Center, Sutter Eden Medical Center, Castro Valley.
Yong BaiHu Research Laboratory, Department of Physiological Nursing, School of Nursing, University of California, San Francisco.
Michele M PelterDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA.
Xiao HuDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA.
Dominican University of California · USUniversity of California, San Francisco · USEden Medical Center · USUniversity of North Carolina at Chapel Hill · US

Funding

North Carolina Translational & Clinical Sciences Institute (NC TraCS)KL2TR001109 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$5.7M
Develop&validate SuperAlarm to detect patient deterioration with few false alarmsR01HL128679 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HU, XIAO · 2015 to 2018
$2.4M
NCATS NIH HHS KL2 TR001109NHLBI NIH HHS R01 HL128679
6 · The paper itself

Abstract

introductionA high rate of false arrhythmia alarms in the intensive care unit (ICU) leads to alarm fatigue, the condition of desensitization and potentially inappropriate silencing of alarms due to frequent invalid and nonactionable alarms, often referred to as false alarms.

objectiveThe aim of this study was to identify patient characteristics, such as gender, age, body mass index, and diagnosis associated with frequent false arrhythmia alarms in the ICU.

methodsThis descriptive, observational study prospectively enrolled patients who were consecutively admitted to one of five adult ICUs (77 beds) at an urban medical center over a period of 31 days in 2013. All monitor alarms and continuous waveforms were stored on a secure server. Nurse scientists with expertise in cardiac monitoring used a standardized protocol to annotate six clinically important types of arrhythmia alarms (asystole, pause, ventricular fibrillation, ventricular tachycardia, accelerated ventricular rhythm, and ventricular bradycardia) as true or false. Total monitoring time for each patient was measured, and the number of false alarms per hour was calculated for these six alarm types. Medical records were examined to acquire data on patient characteristics.

resultsA total of 461 unique patients (mean age =60±17 years) were enrolled, generating a total of 2,558,760 alarms, including all levels of arrhythmia, parameter, and technical alarms. There were 48,404 hours of patient monitoring time, and an average overall alarm rate of 52 alarms/hour. Investigators annotated 12,671 arrhythmia alarms; 11,345 (89.5%) were determined to be false. Two hundred and fifty patients (54%) generated at least one of the six annotated alarm types. Two patients generated 6,940 arrhythmia alarms (55%). The number of false alarms per monitored hour for patients' annotated arrhythmia alarms ranged from 0.0 to 7.7, and the duration of these false alarms per hour ranged from 0.0 to 158.8 seconds. Patient characteristics were compared in relation to 1) the number and 2) the duration of false arrhythmia alarms per 24-hour period, using nonparametric statistics to minimize the influence of outliers. Among the significant associations were the following: age ≥60 years (

conclusionPatients likely to trigger a higher number of false arrhythmia alarms may be those with older age, confusion, cardiovascular diagnoses, and ECG features that indicate BBB or ventricular pacing, respiratory diagnoses, and mechanical ventilatory support. Algorithm improvements could focus on better noise reduction (eg, motion artifact with confused state) and distinguishing BBB and paced rhythms from ventricular arrhythmias. Increasing awareness of patient conditions that apparently trigger a higher rate of false arrhythmia alarms may be useful for reducing unnecessary noise and improving alarm management.

Indexed as

alarm fatigueelectrocardiographypatient safety

Identifiers

PMID28458554
PMCPMC5403122
OpenAlexW2268146483

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.