Evidence map›Paper›PMID 40016479›Full record

ReviewIntensive care medicine experimental2025

Wearable devices for patient monitoring in the intensive care unit.

Alessandra Angelucci, Massimiliano Greco, Maurizio Cecconi, Andrea Aliverti

Abstract readReview
In one paragraph

Review in Intensive care medicine experimental, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

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  10. Predicting and Early Detection of Delirium through Motion Patterns: A Narrative Review.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2026
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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

4 authors.

Alessandra AngelucciDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.
Massimiliano GrecoDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy. massimiliano.greco@hunimed.eu.ORCID http://orcid.org/0000-0003-1003-4637
Maurizio CecconiDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
Andrea AlivertiDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.

Funding

National Plan for NRRP Complementary Investments PNC0000003
6 · The paper itself

Abstract

Wearable devices (WDs), originally launched for fitness, are now increasingly recognized as valuable technologies in several clinical applications, including the intensive care unit (ICU). These devices allow for continuous, non-invasive monitoring of physiological parameters such as heart rate, respiratory rate, blood pressure, glucose levels, and posture and movement. WDs offer significant advantages in making monitoring less invasive and could help bridge gaps between ICUs and standard hospital wards, ensuring more effective transitioning to lower-level monitoring after discharge from the ICU. WDs are also promising tools in applications like delirium detection, vital signs monitoring in limited resource settings, and prevention of hospital-acquired pressure injuries. Despite the potential of WDs, challenges such as measurement accuracy, explainability of data processing algorithms, and actual integration into the clinical decision-making process persist. Further research is necessary to validate the effectiveness of WDs and to integrate them into clinical practice in critical care environments.Take home messages Wearable devices are revolutionizing patient monitoring in ICUs and step down units by providing continuous, non-invasive, and cost-effective solutions. Validation of their accuracy and integration in the clinical decision-making process remain crucial for widespread clinical adoption.

Indexed as

Continuous monitoringCritical careIntensive care unitNon-invasive technologyWearable devices

Identifiers

PMID40016479
PMCPMC11868008

What OpenQuestion holds

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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.