Evidence map›Paper›PMID 39869170›Full record

ReviewCurrent pain and headache reports2025

An Algorithmic Overview of Advanced Pain Therapies: A Narrative Review.

Peter D Vu, Ryan S D'Souza, Saba Javed

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pain and headache reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Peter D VuDepartment of Physical Medicine and Rehabilitation, McGovern Medical School, The University of Texas Health Science Center at Houston, 1333 B Moursund St., Ste. 114, Houston, TX, 77030, USA. peter.d.vu@uth.tmc.edu.ORCID http://orcid.org/0000-0001-6056-7250
Ryan S D'SouzaDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
Saba JavedDepartment of Pain Medicine, Division of Anesthesiology, Critical Care & Pain Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewQuickly referenceable, streamlined, algorithmic approaches for advanced pain management are lacking for patients, trainees, non-pain specialists, and interventional specialists. This manuscript aims to address this gap by proposing a comprehensive, evidence-based algorithm for managing neuropathic, nociceptive, and cancer-associated pain. Such an algorithm is crucial for pain medicine education, offering a structured approach for patient care refractory to conservative management. RECENT

findingsA comprehensive literary review with PubMed and regulatory documents from the United States Food and Drug Administration were searched for a variety of interventions. Pain syndromes were categorized into nociceptive and neuropathic pain, and an algorithm was constructed. Serving as an educational tool for patients, trainees, and non-pain specialists, and as an accessible reference for pain specialists, this algorithm bridges knowledge gaps, promotes interdisciplinary collaboration, and streamlines the learning curve for new practitioners. The strength of this algorithm lies in integrating extensive clinical data, emphasizing the latest clinical evidence, and providing a structured decision-making pathway.

Indexed as

AlgorithmsNeuralgiaPain ManagementHumansAdvanced pain proceduresAdvanced pain therapiesAlgorithmNarrative review

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.