Daily Anesthesiology Research Analysis
Analyzed 39 papers and selected 3 impactful papers.
Summary
Analyzed 39 papers and selected 3 impactful articles.
Selected Articles
1. Efficacy of esketamine in reducing nausea and vomiting after anesthesia: a systematic review and meta-analysis of randomized controlled trials.
Across 38 RCTs (3,425 patients), perioperative esketamine significantly reduced postoperative nausea and vomiting and accelerated gastrointestinal recovery but prolonged anesthesia recovery and PACU stay. The net clinical value will depend on dosing, patient selection, and integration with multimodal antiemetic protocols.
Impact: This comprehensive meta-analysis consolidates the antiemetic profile of esketamine while quantifying recovery trade-offs, directly informing perioperative decision-making.
Clinical Implications: Esketamine can be considered as part of PONV prophylaxis, particularly in high-risk patients, but clinicians should anticipate potential delays in recovery and adjust PACU throughput, dosing, and multimodal antiemetic regimens accordingly.
Key Findings
- Esketamine reduced nausea (RR 0.69, 95% CI 0.53-0.90) and vomiting (RR 0.75, 95% CI 0.57-0.98)
- Shortened time to first flatus (SMD -0.81) and reduced rescue analgesic needs within 2 days (SMD 0.32)
- Prolonged anesthesia recovery (SMD 0.97) and PACU stay (SMD 0.76)
Methodological Strengths
- Comprehensive synthesis of 38 randomized trials with sensitivity and subgroup analyses
- PROSPERO process dates reported, and dual software platforms (RevMan, STATA) used
Limitations
- Heterogeneity in dosing regimens, surgical populations, and antiemetic co-interventions
- Potential publication bias and limited data on functional recovery endpoints beyond PACU
Future Directions: Prospective dose-finding RCTs should optimize esketamine's antiemetic benefit while minimizing recovery delays, and evaluate integration into ERAS pathways with standardized co-antiemetics.
2. Application of ultrasound-guided regional blocks in the perioperative period of hip arthroplasty: A systematic review and network meta-analysis.
Across 18 RCTs (n=1,424), periarticular injection, PENG, and QLB reduced movement-evoked pain after THA, while QLB consistently reduced opioid consumption within 24 hours and over the hospital stay and decreased PONV versus placebo. No technique dominated all outcomes, underscoring the need to individualize block choice.
Impact: This Bayesian network meta-analysis informs block selection for THA by synthesizing head-to-head and indirect comparisons, highlighting QLB’s opioid-sparing advantage.
Clinical Implications: Consider QLB to minimize opioid use and PONV after THA; PENG and PAI are effective alternatives for movement-evoked pain. Tailor block strategy based on surgical approach, resources, and local anesthetic choice (e.g., bupivacaine).
Key Findings
- PAI, PENG, and QLB significantly lowered movement-evoked pain at 12 and 24 hours postoperatively
- QLB reduced morphine consumption within 24 hours (bupivacaine subgroup) and had the lowest in-hospital opioid use
- Regional blocks reduced PONV versus saline control; no single technique was superior across all outcomes
Methodological Strengths
- Bayesian network meta-analysis integrating direct and indirect evidence across 18 RCTs
- Predefined primary and secondary outcomes with standardized time points (12 and 24 hours)
Limitations
- Heterogeneity in block techniques, local anesthetics, and perioperative co-analgesia
- Limited evidence for superiority across all outcomes; some subgroup findings (e.g., bupivacaine) may not generalize
Future Directions: Conduct large multicenter head-to-head RCTs comparing QLB, PENG, and PAI with standardized anesthetic regimens and functional recovery endpoints.
3. Fusion of clinical magnet resonance images and electronic health records promotes multimodal predictions of postoperative delirium.
In two surgical cohorts, multimodal fusion of clinical MRI morphometry with EHR data enabled robust prediction of postoperative delirium with AUROC up to 0.86, especially benefiting less critically ill patients. Neuroanatomical correlates included temporal cortical thickness and thalamic/brainstem volumes, highlighting structural brain vulnerability.
Impact: Introduces clinically obtainable neuroimaging features into perioperative risk modeling, advancing precision prediction of POD beyond EHR-only approaches.
Clinical Implications: Preoperative MRI-based morphometry fused with EHRs could enhance POD risk stratification to target prevention (e.g., delirium-safe anesthesia plans, non-pharmacologic protocols), pending external validation and workflow integration.
Key Findings
- Multimodal models (MRI morphometry + EHR) achieved AUROC up to 0.86 for POD prediction
- Temporal cortical thickness and thalamic/brainstem volumes were key POD-related features
- Multimodal fusion provided pronounced predictive gains in less critically ill patients
Methodological Strengths
- Integration of imaging and EHR with appropriate confounding control (mixed-effects models)
- Comparison of multiple machine-learning classifiers and feature interpretability via model weights
Limitations
- Observational design with potential residual confounding and selection bias
- Generalizability limited by MRI availability and need for external validation across institutions
Future Directions: Prospective, multicenter validation with pragmatic MRI protocols and integration into perioperative clinical decision support to test impact on POD incidence.