Daily Anesthesiology Research Analysis
A double-blind RCT (n=200) shows that pre-emptive ketamine reduces the incidence of chronic post-thoracotomy pain—especially neuropathic features—without lowering in-hospital opioid use. A network meta-analysis finds no meaningful differences between TIVA, volatile anesthesia, and conscious sedation for endovascular stroke therapy outcomes. A meta-research study shows that large language models, including a specialized model, currently underperform expert-crafted search strings for anesthesiolog
Summary
A double-blind RCT (n=200) shows that pre-emptive ketamine reduces the incidence of chronic post-thoracotomy pain—especially neuropathic features—without lowering in-hospital opioid use. A network meta-analysis finds no meaningful differences between TIVA, volatile anesthesia, and conscious sedation for endovascular stroke therapy outcomes. A meta-research study shows that large language models, including a specialized model, currently underperform expert-crafted search strings for anesthesiology systematic reviews.
Research Themes
- Perioperative pain prevention and chronic postsurgical pain
- Anesthetic strategy for neurointerventional stroke care
- AI/LLMs in evidence synthesis for anesthesiology
Selected Articles
1. Perioperative ketamine to reduce and prevent acute and chronic post-thoracotomy pain: a randomized, double-blind, placebo-controlled clinical trial.
In a double-blind RCT of 200 thoracotomy patients, pre-emptive ketamine reduced the incidence of chronic post-thoracotomy pain—particularly neuropathic features—without reducing in-hospital opioid consumption or NRS scores beyond the immediate 6-hour period. The study supports ketamine’s role in preventing chronic postsurgical neuropathic pain after thoracotomy.
Impact: This trial addresses a major unmet need: prevention of chronic post-thoracotomy pain, a frequent and debilitating complication. The findings may change perioperative analgesic protocols for thoracic surgery.
Clinical Implications: Consider incorporating pre-emptive ketamine into thoracotomy analgesic pathways to reduce chronic neuropathic pain risk, with the understanding that acute opioid requirements may not decrease.
Key Findings
- Pre-emptive ketamine reduced coughing-related pain in the first 6 postoperative hours versus placebo.
- No difference in NRS pain scores at rest or with coughing on PODs 1–8 and no reduction in opioid consumption.
- Significantly lower incidence of chronic postoperative pain with neuropathic features (S-LANSS ≥12 at 30 days) in the ketamine group.
Methodological Strengths
- Randomized, double-blind, placebo-controlled design with trial registration (NCT03105765).
- Standardized neuropathic pain assessment using LANSS/S-LANSS at defined timepoints up to 90 days.
Limitations
- Single trial with limited detail on dosing regimen in the abstract; external generalizability needs confirmation.
- Telephone survey for S-LANSS at follow-up may introduce reporting bias; acute pain endpoints showed no sustained benefit.
Future Directions: Define optimal ketamine dosing/timing, explore patient subgroups most likely to benefit, and assess longer-term outcomes beyond 90 days and multimodal combinations.
2. Evaluating the utility of large language models in generating search strings for systematic reviews in anesthesiology: a comparative analysis of top-ranked journals.
Across 85 anesthesiology SRs, expert-crafted search strings recovered substantially more target studies than LLM-generated strings. A structured, PICO-aligned LLM (Meta-Analysis Librarian) outperformed a general-purpose LLM (ChatGPT 4o) but still lagged behind human-authored strategies.
Impact: This meta-research directly informs how anesthesiology teams should (and should not) leverage LLMs in evidence synthesis, a rapidly evolving and high-stakes methodological domain.
Clinical Implications: For systematic reviews and guidelines, retain information specialists and validated search methodologies; LLM outputs may be useful adjuncts but require expert oversight and validation.
Key Findings
- Original (human-authored) search strings achieved a median 65% retrieval rate, significantly outperforming LLMs.
- The specialized PICO-based Meta-Analysis Librarian (median 24%) outperformed ChatGPT 4o (median 6%) but remained inferior to expert strategies.
- Results highlight the current limitations of LLMs for PubMed retrieval in anesthesiology SRs.
Methodological Strengths
- Large comparative sample of 85 SRs from top anesthesiology journals.
- Objective benchmark using original SR search results and standardized, PICO-aligned prompts.
Limitations
- Evaluation limited to PubMed; performance across other databases remains unknown.
- Retrieval rate metric depends on original SR search results as the reference, which may themselves be imperfect.
Future Directions: Test hybrid human-LLM workflows, expand to multi-database environments, and refine domain-specific models trained on high-quality search strategies.
3. Comparing General Anesthesia-Based Regimens for Endovascular Treatment of Acute Ischemic Stroke: A Systematic Review and Network Meta-Analysis.
Across 15 studies (n=3015), no significant differences were found between TIVA and volatile anesthesia—or versus conscious sedation—on 90-day functional recovery, mortality, successful recanalization, or recanalization time during endovascular stroke therapy. The analysis was underpowered for agent-specific effects.
Impact: Findings support flexibility in anesthetic strategy for EVT, focusing attention on workflow, monitoring, and patient selection rather than anesthetic class.
Clinical Implications: Both TIVA and volatile anesthesia (and conscious sedation) appear acceptable for EVT; choose based on patient factors, airway and hemodynamic control needs, and logistics, while recognizing current data are underpowered for agent-level differences.
Key Findings
- No significant difference between TIVA and volatile anesthesia in 90-day mRS≤2, mortality, recanalization success, or procedure time.
- No significant differences between conscious sedation and either TIVA or volatile on the same endpoints.
- Network meta-analysis suggests anesthetic regimen does not drive EVT outcomes, though the analysis was underpowered for agent-specific effects.
Methodological Strengths
- Comprehensive multi-database search and use of network meta-analysis to integrate varied comparisons.
- Large aggregate sample (n=3015) including both GA and conscious sedation comparators.
Limitations
- Only three studies directly compared TIVA vs volatile; heterogeneity and underpowering limit definitive conclusions.
- Mix of study designs; residual confounding and selection bias may remain.
Future Directions: Prospective randomized trials directly comparing anesthetic agents in EVT with stratification by patient and procedural factors; standardized peri-procedural management protocols.