Evidence map›Paper›PMID 36578991›Full record

ReviewNoro psikiyatri arsivi2022

Beyond Resection: Neuromodulation and Minimally Invasive Epilepsy Surgery.

Daniah Shamim, Obiefuna Nwabueze, Utku Uysal

Open access · greenAbstract readReview
In one paragraph

Review in Noro psikiyatri arsivi, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 27% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Review
  5. Review
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 at 1 institution in 1 country.

Daniah ShamimUniversity of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA.
Obiefuna NwabuezeUniversity of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA.
Utku UysalUniversity of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA.
University of Kansas Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epilepsy is a common neurological disease impacting both patients and healthcare systems. Approximately one third of patients have drug-resistant epilepsy (DRE) and are candidates for surgical options. However, only a small percentage undergo surgical treatment due to factors such as patient misconception/fear of surgery, healthcare disparities in epilepsy care, complex presurgical evaluation, primary care knowledge gap, and lack of systemic structures to allow effective coordination between referring physician and surgical epilepsy centers. Resective surgical treatments are superior to medication management for DRE patients in terms of seizure outcomes but may be less palatable to patients. There have been major advancements in minimally invasive surgeries (MIS) and neuromodulation techniques that may allay these concerns. Both epilepsy MIS and neuromodulation have shown promising seizure outcomes while minimizing complications. Minimally invasive methods include Laser Interstitial Thermal Therapy (LITT), RadioFrequency Ablation (RFA), Stereotactic RadioSurgery (SRS). Neuromodulation methods, which are more palliative, include Vagus Nerve Stimulation (VNS), Deep Brain Stimulation (DBS), and Responsive Neurostimulation System (RNS). This review will discuss the role of these techniques in varied epilepsy subtypes, their effectiveness in improving seizure control, and adverse outcomes.

Indexed as

Ablationepilepsy surgeryminimally invasive epilepsy surgeryneuromodulationseizure

Identifiers

PMID36578991
PMCPMC9767135
OpenAlexW4312532430

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.