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  1. Braun BJ, Grimm B, Hanflik AM, Marmor MT, Richter PH, Sands AK, et al.
    EFORT Open Rev, 2020 Jul;5(7):408-420.
    PMID: 32818068 DOI: 10.1302/2058-5241.5.200021
    There are many digital solutions which assist the orthopaedic trauma surgeon. This already broad field is rapidly expanding, making a complete overview of the existing solutions difficult.The AO Foundation has established a task force to address the need for an overview of digital solutions in the field of orthopaedic trauma surgery.Areas of new technology which will help the surgeon gain a greater understanding of these possible solutions are reviewed.We propose a categorization of the current needs in orthopaedic trauma surgery matched with available or potential digital solutions, and provide a narrative overview of this broad topic, including the needs, solutions and basic rules to ensure adequate use in orthopaedic trauma surgery. We seek to make this field more accessible, allowing for technological solutions to be clearly matched to trauma surgeons' needs. Cite this article: EFORT Open Rev 2020;5:408-420. DOI: 10.1302/2058-5241.5.200021.
  2. Marmor MT, Grimm B, Hanflik AM, Richter PH, Sivananthan S, Yarboro SR, et al.
    Indian J Orthop, 2022 Jul;56(7):1112-1122.
    PMID: 35813536 DOI: 10.1007/s43465-022-00629-0
    BACKGROUND: Patient-Reported Outcome Measures (PROMs) are widely used for measurement of functional outcomes after orthopaedic trauma. However, PROMs rely on patient collaboration and suffer from various types of bias. Wearable Activity Monitors (WAMs) are increasingly used to objectify functional assessment. The objectives of this systematic review were to identify and characterise the WAMs technology and metrics currently used for orthopaedic trauma research.

    METHODS: PubMed and Embase biomedical literature search engines were queried. Eligibility criteria included: Human clinical studies published in the English language between 2010 and 2019 involving fracture management and WAMs. Variables collected from each article included: Technology used, vendor/product, WAM body location, metrics measured, measurement time period, year of publication, study geographic location, phase of treatment studied, fractures studied, number of patients studied, sex and age of the study subjects, and study level of evidence. Six investigators reviewed the resulting papers. Descriptive statistics of variables of interest were used to analyse the data.

    RESULTS: One hundred and thirty-six papers were available for analysis, showing an increasing trend of publications per year. Accelerometry followed by plantar pressure insoles were the most commonly employed technologies. The most common location for WAM placement was insoles, followed by the waist. The most commonly studied fracture type was hip fractures followed by fragility fractures in general, ankle, "lower extremity", and tibial fractures. The rehabilitation phase following surgery was the most commonly studied period. Sleep duration, activity time or step counts were the most commonly reported WAM metrics. A preferred, clinically validated WAM metric was not identified.

    CONCLUSIONS: WAMs have an increasing presence in the orthopaedic trauma literature. The optimal implementation of this technology and its use to understand patients' pre-injury and post-injury functions is currently insufficiently explored and represents an area that will benefit from future study.

    SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO ID:210344.

    SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43465-022-00629-0.

  3. Braun BJ, Histing T, Menger MM, Platte J, Grimm B, Hanflik AM, et al.
    Medicina (Kaunas), 2023 Feb 19;59(2).
    PMID: 36837604 DOI: 10.3390/medicina59020403
    Background and Objectives: Outcome data from wearable devices are increasingly used in both research and clinics. Traditionally, a dedicated device is chosen for a given study or clinical application to collect outcome data as soon as the patient is included in a study or undergoes a procedure. The current study introduces a new measurement strategy, whereby patients' own devices are utilized, allowing for both a pre-injury baseline measure and ability to show achievable results. Materials and Methods: Patients with a pre-existing musculoskeletal injury of the upper and lower extremity were included in this exploratory, proof-of-concept study. They were followed up for a minimum of 6 weeks after injury, and their wearable outcome data (from a smartphone and/or a body-worn sensor) were continuously acquired during this period. A descriptive analysis of the screening characteristics and the observed and achievable outcome patterns was performed. Results: A total of 432 patients was continuously screened for the study, and their screening was analyzed. The highest success rate for successful inclusion was in younger patients. Forty-eight patients were included in the analysis. The most prevalent outcome was step count. Three distinctive activity data patterns were observed: patients recovering, patients with slow or no recovery, and patients needing additional measures to determine treatment outcomes. Conclusions: Measuring outcomes in trauma patients with the Bring Your Own Device (BYOD) strategy is feasible. With this approach, patients were able to provide continuous activity data without any dedicated equipment given to them. The measurement technique is especially suited to particular patient groups. Our study's screening log and inclusion characteristics can help inform future studies wishing to employ the BYOD design.
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