Daily Anesthesiology Research Analysis
Analyzed 43 papers and selected 3 impactful papers.
Summary
Analyzed 43 papers and selected 3 impactful articles.
Selected Articles
1. Effect of pericapsular nerve group block on postoperative cognitive function in older patients undergoing total hip arthroplasty.
In a double-blind RCT of 84 older THA patients, preoperative ultrasound-guided PENG block reduced day-7 POCD (14.6% vs 37.2%) while improving pain control, reducing opioid use, lowering NLR/PLR, and enabling earlier mobilization and discharge. Effects at days 30 and 90 were assessed but not detailed in the abstract.
Impact: This is a rigorous randomized, double-blind clinical trial linking a regional block to reduced early POCD—a meaningful patient-centered outcome—with plausible mechanistic correlates (analgesia and inflammation).
Clinical Implications: Consider incorporating preoperative PENG block in older THA patients to improve early cognitive outcomes and facilitate recovery, with attention to standardized techniques and monitoring for longer-term cognitive effects.
Key Findings
- Day-7 POCD incidence was lower with PENG block (14.6% vs 37.2%; p<0.05).
- Lower pain scores and opioid consumption in the first 24 hours postoperatively (p<0.001).
- Earlier mobilization and shorter hospital stay (p<0.001) with reduced NLR/PLR at 24–48 hours (p<0.05).
Methodological Strengths
- Prospective, randomized, double-blind design with sham control.
- Multidomain assessment including cognition (T‑MMSE), pain, opioids, inflammatory indices, and recovery milestones.
Limitations
- Single-center study with moderate sample size.
- Longer-term cognitive outcomes (30 and 90 days) not detailed in the abstract.
Future Directions: Multicenter trials with comprehensive neurocognitive batteries and biomarker panels are needed to assess durability and generalizability and to optimize dosing and timing.
PURPOSE: Postoperative cognitive dysfunction (POCD) is common in older patients undergoing orthopedic surgery and may hinder clinical recovery. This prospective study evaluated whether a preoperative pericapsular nerve group (PENG) block reduces POCD incidence in patients undergoing total hip arthroplasty (THA). METHODS: This prospective, randomized, double-blind study included older patients scheduled for elective THA under spinal anesthesia. Patients were randomized into 2 groups: PENG (group P) and control (group C). Group P underwent an ultrasound-guided PENG block containing 20 mL of 0.25% bupivacaine, while group C received a sham block. Cognitive performance was evaluated using the telephone version of the Mini-Mental State Examination (T-MMSE) preoperatively and on postoperative days 7, 30 and 90. We evaluated postoperative pain using the numerical rating scale (NRS) and recorded opioid consumption, time to mobilization, hospital stay duration, neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). RESULTS: The final analysis included 84 patients (41 in group P and 43 in group C). There were no significant differences in demographic characteristics or intraoperative data between the groups (p > 0.05). The incidence of POCD on postoperative day 7 was lower in the PENG group (14.6% vs. 37.2%; p < 0.05). In the first 24h postoperatively group P reported significantly lower pain scores and opioid use (p < 0.001), were mobilized earlier and discharged sooner (p < 0.001). The NLR and PLR were lower in the PENG group at 24 and 48h postoperatively (p < 0.05). CONCLUSION: Preoperative PENG block may preserve early postoperative cognitive function in THA patients, through improved analgesia, reduced opioid consumption, attenuation of systemic inflammation, early mobilization and shorter hospital stay.
2. Generative AI in preanesthetic consultations: Effects on efficiency, documentation workload, quality, and physician-patient interaction: A simulation trial.
In a randomized simulation crossover with 30 anesthesiologists, an LLM-based documentation tool reduced consultation time by 18% and markedly decreased screen fixation and typing, while clinicians perceived better patient engagement. Manual documentation scored higher on external quality ratings, underscoring the need for physician review of AI drafts.
Impact: Demonstrates measurable, workflow-level benefits of LLMs in a high-documentation perioperative setting with objective human-computer interaction metrics.
Clinical Implications: Institutions can pilot AI-assisted preanesthetic documentation to reduce screen time and improve patient interaction, while mandating clinician verification to ensure documentation completeness and accuracy.
Key Findings
- Consultation duration reduced by 252 seconds (-18%, p<0.0001) with AI assistance.
- Significant reductions in screen fixation (-78%), refixations (-73%), keyboard input (-87%), and mouse clicks (-19%).
- Manual notes scored higher on PDQI-9 (+4 points; p=0.004), despite 60% clinician preference for AI assistance.
Methodological Strengths
- Randomized within-subject crossover design with standardized simulated patient.
- Objective eye-tracking and human-computer interaction metrics complement subjective workload and quality ratings.
Limitations
- Simulation setting may overestimate efficiency gains compared to real-world clinical environments.
- External raters rated manual documentation higher quality; generalizability to diverse cases and languages requires testing.
Future Directions: Prospective clinical implementation studies assessing safety, accuracy, medico-legal aspects, and net time savings with supervised AI documentation across diverse patient populations.
BACKGROUND: Clinicians spend over 30% of their workday on electronic health records, reducing patient interaction and contributing to burnout. Preanesthetic consultations demand particularly detailed documentation, making them ideal for generative artificial intelligence (AI)-driven support. OBJECTIVE: This randomized simulation study evaluated a generative AI application based on a large language model (LLM) designed to automate documentation during preanesthetic consultations. We assessed its effects on consultation efficiency, clinician workload, physician-patient interaction, documentation quality, and user experience. METHODS: Thirty anesthesiologists at University Hospital Zurich each conducted two standardized consultations with the same simulated patient, once using the AI tool Isaac (Saipient AG, Zurich) and once with conventional manual documentation. Case order was randomized. The primary outcome was consultation duration. Secondary outcomes included visual attention (eye-tracking), human-computer interaction metrics, subjective workload (NASA-TLX), documentation quality (PDQI-9), self-assessed consultation quality, and workflow preferences. RESULTS: AI-assisted documentation reduced consultation duration by an average of 252 s (-18%, p < 0.0001), screen fixation (-78%, p = 0.0002), refixations (-73%, p < 0.0001), keyboard input (-87%, p < 0.0001), and mouse clicks (-19%, p = 0.01). Clinicians reported a trend toward lower workload (-16%, p = 0.07) and better patient engagement (median rating 87 vs. 69). However, external raters judged documentation quality to be higher for manual reports (+4 PDQI-9 points; p = 0.004), and clinicians expressed less confidence in AI-generated formatting. Still, 60% preferred AI assistance overall. CONCLUSIONS: LLM-based generative AI-supported documentation significantly improved efficiency and user experience in simulated preanesthetic consultations. While real-world use will require physicians to review and approve AI-generated drafts to ensure documentation quality, the structured outputs may still help reduce typing effort and screen interaction time, although the overall time savings may be smaller in clinical practice due to this additional review step.
3. Poor Agreement Between Intraoperative Transesophageal Echocardiography and Postoperative Transthoracic Echocardiography for Transmitral Mean Pressure Gradient After Mitral Valve Repair.
In a retrospective cohort (n=206 analyzed) after mitral repair, intraoperative post-repair TMPG on TEE showed poor agreement with immediate postoperative TTE (ICC 0.25; Spearman 0.15), while preoperative TMPG correlated better with intraoperative pre-repair values. The findings caution against relying on intraoperative TMPG cutoffs alone.
Impact: Challenges a common intraoperative decision metric in cardiac anesthesia, emphasizing the need for postoperative confirmation and nuanced interpretation.
Clinical Implications: Avoid rigid intraoperative TMPG thresholds to judge repair quality; incorporate routine postoperative TTE and consider hemodynamic context when interpreting intraoperative gradients.
Key Findings
- Poor agreement between intraoperative post-repair TEE TMPG and immediate postoperative TTE TMPG (ICC 0.25; Spearman 0.15).
- Preoperative TTE TMPG showed moderate agreement with intraoperative pre-repair TEE TMPG (ICC 0.79; Spearman 0.62).
- Bland-Altman analysis revealed wide limits of agreement for post-repair vs postoperative TMPGs (~+2.5 to -2.9 mmHg).
Methodological Strengths
- Relatively large single-center cohort with defined inclusion and use of multiple agreement statistics (ICC, Spearman, Bland-Altman).
- Granular reporting of mitral pathology distribution and detailed statistical confidence intervals.
Limitations
- Retrospective single-center design with potential selection and confounding biases.
- Hemodynamic differences between intraoperative and postoperative conditions may drive disagreement.
Future Directions: Prospective multicenter studies to define context-sensitive intraoperative TMPG targets and integrate adjunctive parameters (flow, heart rate, loading conditions) for decision-making.
OBJECTIVES: To assess the agreement between intraoperative post-repair transmitral mean pressure gradient (TMPG) on transesophageal echocardiography (TEE) and postoperative TMPG on transthoracic echocardiography (TTE) after mitral valve repair, as well as the agreement between preoperative TTE TMPG and intraoperative post-repair TMPG on TEE. DESIGN: A retrospective observational study. SETTING: A single tertiary academic medical center. PARTICIPANTS: Adult patients undergoing mitral valve repair. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 395 patients were included, with 206 in the final analysis; the median age was 64 years (interquartile range, 55-70 years), and 64% of patients were male. The average body mass index was 26.9 ± 4.7. Posterior mitral valve pathology was present in 196 patients, while 68 had anterior mitral valve pathology and 58 had both anterior and posterior valve pathology. The intraclass correlation coefficient (ICC) between the post-repair intraoperative mean gradient and the postoperative mean gradient was 0.25 (p = 0.02). The ICC between the preoperative mean pressure gradient and the post-repair pressure gradient was 0.79 (p < 0.001). Spearman correlation analysis between intraoperative post-repair TMPG and postoperative TMPG showed a correlation of 0.15 (95% confidence interval [CI], 0.02 to 0.28; p = 0.03). Bland-Altman analysis of post-repair and postoperative TMPGs showed a mean difference of -0.19 (95% CI, -0.38 to 0.00), with upper and lower limits of agreement of 2.5 (95% CI, 2.2 to 2.9) and -2.9 (95% CI, -3.2 to -2.6), respectively. Spearman correlation analysis between the preoperative mean TMPG and the intraoperative pre-repair mean TMPG showed a correlation coefficient of 0.62 (95% CI, 0.43 to 0.75; p < 0.001). Bland-Altman analysis of preoperative and pre-repair TMPGs revealed a mean difference of 0.46 (95% CI, 0.23 to 0.68), with upper and lower limits of agreement of -1.32 (95% CI, -1.7 to -0.9) and 2.24 (95% CI, 1.8 to 2.6), respectively. CONCLUSIONS: This study demonstrates that intraoperative post-repair TMPG has poor agreement with immediate postoperative TMPG while showing moderate agreement between preoperative and post-repair gradients. These findings challenge the reliance on intraoperative TMPG cutoffs and highlight the importance of postoperative echocardiographic follow-up.