ArticleBMC anesthesiology2026
Emerging technologies in interventional pain management: a scoping review on current innovations and future directions.
Article in BMC anesthesiology, 2026. 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.
- Review
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
backgroundEmerging digital and bioelectronic technologies are rapidly transforming interventional pain management, but their clinical roles and evidence base remain unclear. A scoping review of these innovations is needed to map the current landscape and identify gaps for future research.
objectiveTo conduct a scoping review of emerging technologies applied to interventional pain management, and to summarize their clinical applications, outcomes, and methodological limitations.
methodsThis scoping review followed the PRISMA-ScR guidelines and was structured according to the Population-Concept-Context (PCC) framework. A comprehensive search was performed in PubMed, Scopus, Web of Science, Embase, and CENTRAL from inception to January 1, 2026, using predefined search strategies targeting emerging technologies and interventional pain procedures. Titles, abstracts, and full texts were screened in a three-stage process, supplemented by backward citation searching. Data were charted on study and patient characteristics, technology type, interventional pain application, and reported outcomes. Methodological quality and risk of bias were appraised using Joanna Briggs Institute (JBI) tools appropriate to each study design.
resultsFour major themes emerged from the reviewed literature. (1) Precision patient selection and intelligent clinical decision support using multimodal artificial intelligence models, (2) physiologic closed‑loop neuromodulation and neural dosing guided by evoked compound action potentials, (3) AI‑assisted procedural guidance for ultrasound‑guided interventions, and (4) digital therapeutics, wearable technologies, and remote monitoring platforms supporting long‑term management. Across these domains, early evidence suggests that AI‑driven tools and data‑integrated neuromodulation systems may improve patient selection, procedural accuracy, therapy optimization, and longitudinal monitoring in interventional pain care. However, most studies remain limited by small sample sizes, heterogeneous outcome measures, and insufficient external validation.
conclusionsEmerging technologies demonstrate potential for precision, personalization, and effectiveness in interventional pain management. Nevertheless, additional multicenter, longitudinal research with standardized outcomes is essential before extensive clinical implementation.
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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.