Outcomes after laser interstitial thermal ablation for temporal lobe epilepsy: a systematic review and meta-analysis.
Soha A AlomarRana H MoshrefLeena H MoshrefAbdulrahman J SabbaghPublished in: Neurosurgical review (2023)
Epilepsy is a common condition that affects approximately 1% of the world's population, with about one-third being refractory epilepsy. Temporal lobe epilepsy is the most common type of drug-resistant epilepsy, and laser interstitial thermal therapy (LITT) is an innovative treatment. In this systematic review and meta-analysis, we aimed to summarize the current evidence on outcomes after LITT, including seizure freedom rate, complication rate, and neurocognitive outcome. PubMed and OVID Medline search engines were systematically searched for all indexed publications in the English language up to July15, 2023. The search was limited to human studies. Proportions and 95% confidence interval (CI) values were calculated for seizure, neurocognitive outcome, and complication rate. A total of 836 patients were included. Overall seizure outcomes, regardless of the pathology, included Engel I outcome in 56% (95% CI, 52.4-59.5%), Engel II outcome in 19.2% (95% CI, 15.4-23.6%), Engel III outcome in 17.3% (95% CI, 13.5-21.8%), and Engel IV outcome in 10.5% (95% CI 6.3-17%) of the patients. The overall decline in verbal and visual memory regardless of laterality was 24.2 (95% CI 8.6-52%) and 25.2% (8.3-55.8%). For naming, the decline was 13.4% (6.6-25.4%). The results of the pooled analysis in comparison with available data in the literature showed that seizure outcomes after LITT were slightly inferior to published data after temporal lobectomy. Data on cognitive outcomes after LITT are scarce and heterogeneous.
Keyphrases
- temporal lobe epilepsy
- drug resistant
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- systematic review
- working memory
- prognostic factors
- endothelial cells
- multidrug resistant
- bipolar disorder
- big data
- type diabetes
- machine learning
- mesenchymal stem cells
- adipose tissue
- autism spectrum disorder
- high resolution
- acinetobacter baumannii
- artificial intelligence
- deep learning
- mass spectrometry
- high speed