Evidence map›Paper›PMID 36832119›Full record

ArticleDiagnostics (Basel, Switzerland)2023

Wearable Health Technology for Preoperative Risk Assessment in Elderly Patients: The WELCOME Study.

Massimiliano Greco, Alessandra Angelucci, Gaia Avidano, Giovanni Marelli, Stefano Canali, Romina Aceto, Marta Lubian, Paolo Oliva, Federico Piccioni, Andrea Aliverti and 1 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

17 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
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  9. Review
  10. [The potential of wearable technology in knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024
    Review
  11. Value-based preoperative assessment in a large academic hospital.Journal of anesthesia, analgesia and critical care · 2024
    Article
  12. Article
  13. Review
  14. Development of Machine Learning Model for VOHealthcare (Basel, Switzerland) · 2023
    Article
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  17. 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

11 authors at 3 institutions in 1 country.

Massimiliano GrecoDepartment of Biomedical Sciences, Humanitas University, 20072 Milan, Italy.ORCID 0000-0003-1003-4637
Alessandra AngelucciDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0001-8266-9346
Gaia AvidanoDepartment of Biomedical Sciences, Humanitas University, 20072 Milan, Italy.
Giovanni MarelliDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0002-4420-3534
Stefano CanaliDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0002-5948-3874
Romina AcetoDepartment of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089 Milan, Italy.
Marta LubianDepartment of Biomedical Sciences, Humanitas University, 20072 Milan, Italy.ORCID 0000-0002-1770-7710
Paolo OlivaClinical Engineering, IRCCS Humanitas Research Hospital, 20089 Milan, Italy.
Federico PiccioniDepartment of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089 Milan, Italy.ORCID 0000-0002-9589-1891
Andrea AlivertiDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0002-2950-0231
Maurizio CecconiDepartment of Biomedical Sciences, Humanitas University, 20072 Milan, Italy.
Humanitas University · ITPolitecnico di Milano · ITIRCCS Humanitas Research Hospital · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preoperative identification of high-risk groups has been extensively studied to improve patients' outcomes. Wearable devices, which can track heart rate and physical activity data, are starting to be evaluated for patients' management. We hypothesized that commercial wearable devices (WD) may provide data associated with preoperative evaluation scales and tests, to identify patients with poor functional capacity at increased risk for complications. We conducted a prospective observational study including seventy-year-old patients undergoing two-hour surgeries under general anesthesia. Patients were asked to wear a WD for 7 days before surgery. WD data were compared to preoperatory clinical evaluation scales and with a 6-min walking test (6MWT). We enrolled 31 patients, with a mean age of 76.1 (SD ± 4.9) years. There were 11 (35%) ASA 3-4 patients. 6MWT results averaged 328.9 (SD ± 99.5) m. Daily steps and 𝑉𝑂2𝑚𝑎𝑥 as recorded using WD and were associated with 6MWT performance (R = 0.56,

Indexed as

anesthesiaexercise testfitness trackersgeneral surgeryperioperative carerisk assessmentwearable electronic devices

Identifiers

PMID36832119
PMCPMC9955976
OpenAlexW4319786646

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.