ReviewOrthopedic research and reviews2026
Digital Health and Smart Technologies in Shoulder Arthroplasty: Emerging Tools and Clinical Implications.
Review in Orthopedic research and reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Shoulder arthroplasty has evolved substantially in surgical technique, implant design, and indications. Careful coordination across the patient care pathway remains central to optimizing outcomes. Concurrently, rapid advances in digital health, wearable technologies, smart implants, and intraoperative innovations are being explored across orthopedics, with emerging applications in shoulder arthroplasty. Objective: This narrative review synthesizes current evidence on digital technologies relevant to shoulder arthroplasty, with particular attention to the strength and origin of the available data. Patients and Methods: A structured review of recent literature was performed, including primary studies in shoulder arthroplasty as well as relevant evidence extrapolated from hip and knee arthroplasty. Areas examined included CT-based 3D planning, navigation, patient-specific instrumentation, robotics, augmented/mixed reality, mobile health (mHealth) platforms, wearable devices, tele-rehabilitation, sensor-enabled implants, and artificial intelligence (AI). Results: In shoulder arthroplasty, digital planning tools, navigation systems, and patient-specific instrumentation have demonstrated improvements in implant positioning accuracy in selected studies; however, evidence linking these technologies to superior long-term clinical outcomes remains limited. Robotic systems and augmented reality applications are in early investigational phases. Postoperative digital health tools, including tele-rehabilitation and wearable monitoring, have shown non-inferior functional outcomes compared with conventional care in hip and knee arthroplasty, with only preliminary and pilot data currently available in shoulder populations. Sensor-enabled implants and AI-based predictive models represent emerging areas of research, but external validation, workflow integration, and cost-effectiveness analyses remain insufficient. Conclusion: Digital and smart health technologies in shoulder arthroplasty are evolving and largely investigational. While early findings and extrapolated evidence from other arthroplasty domains suggest potential benefits in planning accuracy, patient engagement, and outcome monitoring, robust shoulder-specific clinical validation is limited. Further prospective studies are required before widespread clinical adoption can be recommended. This narrative review synthesizes emerging evidence in this field, which is currently dominated by feasibility studies, technical reports, and early-phase clinical investigations, with limited high-level outcome data specific to shoulder arthroplasty.
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Registered trials
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 Socratic graph.