ReviewIndian journal of orthopaedics2025
Data-Driven Strategies in Orthopaedics: Optimizing Surgical Precision and Patient Outcomes.
Review in Indian journal of orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Leveraging data to transform surgical outcomes and precision in orthopaedics.Journal of clinical orthopaedics and trauma · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Incorporating data-driven technologies in orthopaedic surgery transforms clinical outcomes and enhances surgical precision. These advancements include predictive modelling, machine learning, Internet of Things (IoT)-enabled devices, and data visualization tools. This review aims to examine the current state of data-driven methods in orthopaedic surgery, highlight their clinical impact, and address existing challenges and future directions. Materials and Methods: A comprehensive literature search was conducted across databases such as PubMed, Scopus, and Web of Science to identify relevant studies exploring data-driven technologies' applications in orthopaedic settings. The analysis focused on preoperative planning, intraoperative guidance, and postoperative monitoring while considering ethical concerns and implementation challenges in low and middle-income countries. Results: The findings indicate that 3D imaging and patient-specific surgical guides enhance preoperative planning, improving accuracy and reducing surgical errors. Robot-assisted systems provide real-time intraoperative support, leading to better precision and reduced recovery times. Postoperative monitoring through wearable devices enables continuous patient tracking, allowing for early detection of complications and improved patient engagement. However, challenges related to data privacy, interoperability, and ethical considerations persist, potentially hindering broader adoption. Conclusions: Integrating data-driven technologies is promising for advancing orthopaedic surgery by improving patient outcomes and surgical success rates. Addressing the identified challenges through ongoing research and interdisciplinary collaboration is essential for facilitating the effective implementation of these innovations in clinical practice. Future studies should focus on using data-driven technologies and ethical guidelines to improve orthopaedic outcomes and overcome challenges, particularly in low- and middle-income countries. Supplementary Information: The online version contains supplementary material available at 10.1007/s43465-025-01461-y.
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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 OpenQuestion graph.