Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 396

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

Deep brain stimulation for pain relief: A meta-analysis

Open access
Bittar, Richard G., Kar-Purkayastha, Ishani, Owen, Sarah L., Bear, Renee E., Green, Alex, Wang, ShouYan, Aziz, Tipu Z.·2005·Journal of Clinical Neuroscience

Abstract

Deep brain stimulation (DBS) has been used to treat intractable pain for over 50 years. Variations in targets and surgical technique complicate the interpretation of many studies. To better understand its efficacy, we performed a meta-analysis of DBS for pain relief. MEDLINE (1966 to February 2003) and EMBASE (1980 to January 2003) databases were searched using key words deep brain stimulation, sensory thalamus, periventricular gray and pain. Inclusion criteria were based on patient characteristics and protocol clarity. Six studies (between 1977-1997) fitting the criteria were identified. Stimulation sites included the periventricular/periaqueductal grey matter (PVG/PAG), internal capsule (IC), and sensory thalamus (ST). The long-term pain alleviation rate was highest with DBS of the PVG/PAG (79%), or the PVG/PAG plus sensory thalamus/internal capsule (87%). Stimulation of the sensory thalamus alone was less effective (58% long-term success) (p < 0.05). DBS was more effective for nociceptive than deafferentation pain (63% vs 47% long-term success; p < 0.01). Long-term success was attained in over 80% of patients with intractable low back pain (failed back surgery) following successful trial stimulation. Trial stimulation was successful in approximately 50% of those with post-stroke pain, and 58% of patients permanently implanted achieved ongoing pain relief. Higher rates of success were seen with phantom limb pain and neuropathies. We conclude that DBS is frequently effective when used in well-selected patients. Neuroimaging and neuromodulation technology advances complicate the application of these results to modern practice. Ongoing investigations should shed further light on this complex clinical conundrum.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jocn.2004.10.005

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 29 references

Cited by

See all 396

Metadata

Authors
Bittar, R. G., Kar-Purkayastha, I., Owen, S. L., Bear, R. E., Green, A., Wang, S., & Aziz, T. Z.
Venue
Journal of Clinical Neuroscience
Publisher
Elsevier BV
Published
2005-06
Volume
12
Issue
5
Pages
515-519
ISSN
0967-5868 (ISSN-L)
OpenAlex
W2165706145
Cited by
396
References
29
FWCI
1.45
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Deep brain stimulation for pain relief: A meta-analysis. https://app.cochat.ai/papers/10.1016/j.jocn.2004.10.005
The paper
Bittar, R. G., Kar-Purkayastha, I., Owen, S. L., Bear, R. E., Green, A., Wang, S., & Aziz, T. Z. (2005). Deep brain stimulation for pain relief: A meta-analysis. Journal of Clinical Neuroscience. https://doi.org/10.1016/j.jocn.2004.10.005

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.