ReviewDiagnostics (Basel, Switzerland)2025
Review Article: Diagnostic Paradigm Shift in Spine Surgery.
Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Review
- Artificial intelligence and machine learning in spine care: Advancing precision diagnosis, treatment, and rehabilitation.World journal of orthopedics · 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
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Meticulous clinical examination is essential for spinal disorders to utilize the diagnostic methods and technologies that strongly support physicians and enhance clinical practice. A significant change in the approach to diagnosing spinal disorders has occurred in the last three decades, which has enhanced a more nuanced understanding of spine pathology. Traditional radiographic methods such as conventional and functional X-rays and CT scans are still the first line in the diagnosis of spinal disorders due to their low cost and accessibility. As more advanced imaging technologies become increasingly available worldwide, there is a constantly increasing trend in MRI scans for detecting spinal pathologies and making treatment decisions. Not only do MRI scans have superior diagnostic capabilities, but they also assist surgeons in performing meticulous preoperative planning, making them currently the most widely used diagnostic tool for spinal disorders. Positron Emission Tomography (PET) can help detect inflammatory lesions, infections, and tumors. Other advanced diagnostic tools such as CT/MRI fusion image, Functional Magnetic Resonance Imaging (fMRI), Upright and Kinetic MRI, magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), and diffusion tensor imaging (DTI) could play an important role when it comes to detecting more special pathologies. However, some technical difficulties in the daily praxis and their high costs act as obstacles to their further spread. Integrating artificial intelligence and advancements in data analytics and virtual reality promises to enhance spinal procedures' precision, safety, and efficacy. As these technologies continue to develop, they will play a critical role in transforming spinal surgery. This paradigm shift emphasizes the importance of continuous innovation and adaptability in improving the diagnosis and treatment of spinal disorders.
Indexed as
Identifiers
What OpenQuestion holds
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.