Evidence map›Paper›PMID 37052980›Full record

Observational studyJournal of medical Internet research2023

Fitbit Data to Assess Functional Capacity in Patients Before Elective Surgery: Pilot Prospective Observational Study.

Alessandra Angelucci, Massimiliano Greco, Stefano Canali, Giovanni Marelli, Gaia Avidano, Giulia Goretti, Maurizio Cecconi, Andrea Aliverti

Abstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2023. 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
–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

15 citing papers in PubMed.

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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

8 authors.

Alessandra AngelucciDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.ORCID 0000-0001-8266-9346
Massimiliano GrecoDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.ORCID 0000-0003-1003-4637
Stefano CanaliDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.ORCID 0000-0002-5948-3874
Giovanni MarelliDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.ORCID 0000-0002-4420-3534
Gaia AvidanoDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.ORCID 0000-0001-8198-212X
Giulia GorettiDepartment of Anesthesiology and Intensive Care, IRCCS Humanitas Research Hospital, Rozzano, Italy.ORCID 0000-0003-4241-2540
Maurizio CecconiDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.ORCID 0000-0002-4376-6538
Andrea AlivertiDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.ORCID 0000-0002-2950-0231

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative assessment is crucial to prevent the risk of complications of surgical operations and is usually focused on functional capacity. The increasing availability of wearable devices (smartwatches, trackers, rings, etc) can provide less intrusive assessment methods, reduce costs, and improve accuracy.

objectiveThe aim of this study was to present and evaluate the possibility of using commercial smartwatch data, such as those retrieved from the Fitbit Inspire 2 device, to assess functional capacity before elective surgery and correlate such data with the current gold standard measure, the 6-Minute Walk Test (6MWT) distance.

methodsDuring the hospital visit, patients were evaluated in terms of functional capacity using the 6MWT. Patients were asked to wear the Fitbit Inspire 2 for 7 days (with flexibility of -2 to +2 days) after the hospital visit, before their surgical operation. Resting heart rate and daily steps data were retrieved directly from the smartwatch. Feature engineering techniques allowed the extraction of heart rate over steps (HROS) and a modified version of Non-Exercise Testing Cardiorespiratory Fitness. All measures were correlated with 6MWT.

resultsIn total, 31 patients were enrolled in the study (n=22, 71% men; n=9, 29% women; mean age 76.06, SD 4.75 years). Data were collected between June 2021 and May 2022. The parameter that correlated best with the 6MWT was the Non-Exercise Testing Cardiorespiratory Fitness index (r=0.68; P<.001). The average resting heart rate over the whole acquisition period for each participant had r=-0.39 (P=.03), even if some patients did not wear the device at night. The correlation of the 6MWT distance with the HROS evaluated at 1% quantile was significant, with Pearson coefficient of -0.39 (P=.04). Fitbit step count had a fair correlation of 0.59 with 6MWT (P<.001).

conclusionsOur study is a promising starting point for the adoption of wearable technology in the evaluation of functional capacity of patients, which was strongly correlated with the gold standard. The study also identified limitations in the availability of metrics, variability of devices, accuracy and quality of data, and accessibility as crucial areas of focus for future studies.

Indexed as

Fitness TrackersWearable Electronic DevicesAgedFemaleHeart RateHumansMaleMonitoring, PhysiologicWalkingethics in wearablesmobile phonepreoperative risk assessmentsmartwatch datawearable devices

Identifiers

PMID37052980
PMCPMC10141298

What OpenQuestion holds

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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.