Evidence map›Paper›PMID 42667580›Full record

ArticleJournal of clinical monitoring and computing2026

Patient characteristics and monitor alarms in a cardiac ICU: A retrospective cross-sectional study.

Juho O Jämsä, Kimmo H Uutela, Mitja Lääperi, Anna-Maija Tapper, Lasse Lehtonen

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Article in Journal of clinical monitoring and computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Juho O JämsäUniversity of Helsinki, Helsinki, Finland. juho.jamsa@helsinki.fi.ORCID https://orcid.org/0000-0002-6704-1515
Kimmo H UutelaGE Healthcare, Helsinki, Finland.
Mitja LääperiLääperi Statistical Consulting, Helsinki, Finland.
Anna-Maija TapperUniversity of Helsinki, Helsinki, Finland.
Lasse LehtonenUniversity of Helsinki, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose was to describe patient monitor alarm burden in a cardiac surgical intensive care unit and explore whether routinely available patient characteristics are associated with alarm frequency, type, and duration. Secondary objectives were to assess indirect signs of alarm fatigue and compare alarm rates with two previous studies using identical monitors in different clinical units. We retrospectively collected patient-monitor alarm data and patient characteristics over four consecutive weeks in the cardiac surgical intensive care unit of Helsinki University Hospital. The study population comprised 81 patients. Alarm data were analysed descriptively and modelled using negative-binomial regression. Patients produced 45,044 alarms, with a median alarm rate of 6.8 [4.8 to 10.8] alarms per patient per hour. Older age was associated with fewer alarms (IRR = 0.90, 95% CI 0.83 to 0.98, P < 0.05). ASA 5 classification was associated with more low- ETCO2 alarms (IRR = 9.05, 95% CI 3.37 to 27.88, P < 0.05). Smoking was associated with more low invasive blood pressure alarms (IRR = 1.94, 95% CI 1.05 to 3.90, P < 0.05). Alarm load was high, clinician interaction with alarms was limited, and many alarms were momentary. Alarm rates were similar across three clinically different units using identical monitors. Routinely available patient characteristics were associated with selected alarm patterns, but the findings are hypothesis-generating. Similar alarm rates across different units suggest that default settings may not reflect unit- or patient-specific monitoring needs. The results suggest low positive predictive value and possible alarm fatigue, supporting unit-level alarm review that incorporates patient-level alarm patterns and signal-quality improvement, with prospective validation before patient-specific alarm-management changes.

Indexed as

Alarm fatigueClinical alarmsIntensive carePatient characteristicsPatient monitoringPatient safety

Identifiers

PMID42667580

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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.