Evidence map›Paper›PMID 40036212›Full record

ArticlePloS one2025

A new trauma severity scoring system adapted to wearable monitoring: A pilot study.

Alice Lemarquand, Pierre Jannot, Léo Kammerlocher, Gaëlle Lissorgues, Michel Behr, Pierre-Jean Arnoux, Salah Boussen

Abstract readValidation Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

7 authors.

Alice LemarquandLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.ORCID https://orcid.org/0000-0003-4224-6685
Pierre JannotLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.
Léo KammerlocherLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.
Gaëlle LissorguesLaboratoire ESYCOM, Université Gustave Eiffel, Noisy-le-Grand, France.
Michel BehrLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.
Pierre-Jean ArnouxLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.
Salah BoussenLaboratoire de Biomécanique Appliquée, Université Gustave Eiffel, Aix-Marseille Université, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable technologies represent a strong development axis for various medical applications and these devices are increasingly used in daily life as illustrated by smart watches' popularisation. Combined with new data processing methods, it constitutes a promising opportunity for telemonitoring, triage in mass casualty situations, or early diagnosis after a traffic or sport accident. An approach to processing the physiological data is to develop severity scoring systems to quantify the critical level of an individual's health status. However, the existing severity scores require a human evaluation. A first version of a severity scoring system adapted to continuous and real-time wearable monitoring is proposed in this article. The focus is made on three physiological parameters straightforwardly measurable with wrist-wearables: heart rate, respiratory rate, and SpO2, which may be enough to characterise continuously hemodynamic and respiratory status. Intermediate score functions corresponding to each physiological parameter have been established using a sigmoid model. The boundary conditions have been defined based on a survey conducted among 54 health professionals. An adapted function has also been developed to merge the three intermediate scores into a global score. The scores are associated with a triage tricolour code: green for a low-priority casualty, orange for a delayable one, red for an urgent one. Preliminary confrontation of the new severity scoring system with real data has been carried out using a database of 84 subjects admitted to the intensive care unit. Colour classification by the new scoring system was compared with independent physicians' direct evaluation as a reference. The prediction success rate values 74% over the entire database. Two examples of continuous monitoring over time are also given. The new score has turned out to be consistent, and may be easily upgraded with the integration of additional vital signs monitoring or medical information.

Indexed as

Remote Patient MonitoringTrauma Severity IndicesWearable Electronic DevicesWounds and InjuriesDatasets as TopicHeart RateHumansIntensive Care UnitsOxygen SaturationPilot ProjectsRespiratory RateVital Signs

Identifiers

PMID40036212
PMCPMC11878944

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Registered trials

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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.