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Study compares different epidural injections to treat lumbosacral radicular pain

lumbosacral radicular pain lumbosacral radicular pain
lumbosacral radicular pain lumbosacral radicular pain

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In people having lumbosacral radicular pain, the parasagittal interlaminar technique has the greatest probability of functional improvement and pain alleviation.

The findings of a systematic review and network meta-analysis showed that in short-term and intermediate-term follow-up, the parasagittal interlaminar (PIL) approach exhibits the highest likelihood for pain mitigation and functional improvement. Zhihe Yun et al. aimed to determine which epidural injection technique was most successful for treating adult patients with lumbosacral radicular pain.

Databases like Web of Science, Cochrane Library, Pubmed, and Embase were explored. The data extraction and quality evaluation were conducted separately by two authors. To include the estimates of indirect and direct treatment comparisons and rank the treatments in order, a Bayesian random effects model was used. Effect estimates were provided as mean difference (MD) along with 95% credible ranges (CrI).

Epidural injection techniques for lumbosacral radicular pain, including caudal (C), interlaminar (IL), transforaminal (TF), and PIL, were evaluated from 7 studies. Midline interlaminar (MIL) versus PIL (MD, 1.16), MIL vs TF (MD, 1.12), C vs TF (MD, 1.07) in the short-term follow-up and MIL vs TF (MD, 1.8) in the intermediate-term follow-up all showed a clinically meaningful treatment difference for pain alleviation.

In the short-term follow-up for functional improvement, a clinically meaningful difference was seen with MIL versus PIL (MD, 9.9) and MIL vs TF (MD, 1.08). Additionally, both in the short and intermediate-term follow-up, the PIL technique and TF technique were ranked in the top 2 for functional improvement and pain alleviation.

Source:

Pain Physician

Article:

Comparative Effects of Different Epidural Injection Approaches on Lumbosacral Radicular Pain: A Systematic Review and Network Meta-analysis

Authors:

Zhihe Yun et al.

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