Journal of Anesthesia最新文献

Purpose: This study retrospectively assessed blood loss during cesarean deliveries for twin and singleton pregnancies using two distinct methods, quantitative estimation measured during cesarean sections and hematocrit-based calculated estimation.

Methods: We included scheduled cesarean deliveries for twin or singleton pregnancies at ≥ 34 weeks of gestation. Quantitative blood loss was recorded based on the blood volume in the graduated collector bottle and by weighing the blood-soaked textiles during cesarean sections. The blood loss was calculated using the change in hematocrit levels before and after the cesarean delivery.

Results: We evaluated 403 cases including 44 twins and 359 singletons. Quantitative blood loss during cesarean section was significantly higher in twin pregnancies than that in singleton pregnancies (1117 [440] vs 698 [378] mL; p < 0.001). However, no significant differences were observed in the calculated blood loss between the two groups on the day after delivery (487 mL [692 mL] vs 507 mL [522 mL]; p = 0.861). On post-delivery days 4-5, twin pregnancies were associated with a significantly higher calculated blood loss than singleton pregnancies (725 [868] mL vs 444 [565] mL, p = 0.041). Although a significant moderate correlation between quantitative and calculated blood loss was observed in singleton pregnancies (r = 0.473, p < 0.001), no significant correlation was observed between twin pregnancies (r = 0.053, p = 0.735).

Conclusion: Quantitative blood loss measurements during cesarean section may be clinically insufficient in twin pregnancies. Incorporating blood tests and continuous assessments are warranted for enhanced blood loss evaluation, especially in twin pregnancies, owing to the risk of persistent bleeding.

Purpose: To assess the importance of appropriate opioid administration methods according to nociceptive monitoring.

Methods: We conducted a randomized controlled trial involving 54 patients who underwent robot-assisted laparoscopic radical prostatectomy at our hospital. Patients were randomly allocated to either receive nociception level (NOL)-directed intraoperative opioid management with a minimum flow of remifentanil (NOL group) or conventional intraoperative analgesic management (control group). The primary outcome was the mean intraoperative remifentanil infusion flow rate (intraoperative remifentanil usage [μg]/ideal body weight [kg]/operation time [min]). The main secondary outcomes were plasma concentrations of three perioperative inflammatory biomarkers (interleukin-6, C-reactive protein [CRP], and cortisol levels) and postoperative pain (Numeric Rating Scale [NRS]) scores 2 h postoperatively and on postoperative days 1, 2, 3, and 7.

Results: Compared with standard analgesia management, NOL-directed analgesic management reduced remifentanil consumption by 20% ( - 0.038; 95% confidence interval, - 0.059 to - 0.017; p = 0.0007). NOL-directed management did not lead to an increase in IL-6, CRP, or cortisol levels compared with conventional analgesic management. Furthermore, this protocol led to improvements in the NRS scores at rest 2 h postoperatively and upon movement up to postoperative day 3.

Conclusion: NOL-directed analgesic management reduced remifentanil consumption by 20% and the NRS scores at rest 2 h postoperatively and upon movement up to postoperative day 3 without an increase in inflammatory marker levels.

Registry number: Japan Registry of Clinical Trials, JRCTs052220034.

Purpose: To explored the impact of dexmedetomidine and esketamine in mitigating restlessness during the postoperative recovery phase following laparoscopic surgery in children.

Methods: 102 individuals aged 1 to 7 years experiencing laparoscopic surgery were randomly allocated into three groups, each accepting 1 μg/kg of dexmedetomidine, 0.3 mg/kg of esketamine, or saline immediately at the end of carbon dioxide pneumoperitoneum. Emergence agitation (EA) occurrence was assessed by PAED scale and 5-point agitation scale. Pain was judged using Face, Legs, Activity, Cry, and Consolability (FLACC) scale. The recovery time, extubation time, and post-anesthesia care unit (PACU) stay time were recorded for all three groups.

Results: Patients administered 1 μg/kg of dexmedetomidine (8.8%) and individuals given 0.3 mg/kg of esketamine (11.8%) showed lower incidences of emergence agitation compared to those receiving saline (35.5%; P = 0.009). There was no statistically significant difference in the time to discharge from the PACU among the three groups of patients (P > 0.05). The recovery time and extubation time were notably extended in the dexmedetomidine group (40.88 ± 12.95 min, 42.50 ± 13.38 min) when compared to the saline group (32.56 ± 13.05 min, 33.29 ± 11.30 min; P = 0.009, P = 0.010).

Conclusion: Following CO₂ pneumoperitoneum in pediatric laparoscopic surgeries, the intravenous administration of 1 μg/kg dexmedetomidine or 0.3 mg/kg esketamine effectively lowers EA occurrence without extending PACU time.

In this research methods tutorial of clinical anesthesia, we will explore techniques to estimate the influence of a myriad of factors on patient outcomes. Big data that contain information on patients, treated by individual anesthesiologists and surgical teams, at different hospitals, have an inherent multi-level data structure (Fig. 1). While researchers often attempt to determine the association between patient factors and outcomes, that does not provide clinicians with the whole story. Patient care is clustered together according to clinicians and hospitals where they receive treatment. Therefore, multi-level regression models are needed to validly estimate the influence of each factor at each level. In addition, we will explore how to estimate the influence that variability—for example, one anesthesiologist deciding to do one thing, while another takes a different approach—has on outcomes for patients, using the intra-class correlation coefficient for continuous outcomes and the median odds ratio for binary outcomes. From this tutorial, you should acquire a clearer understanding of how to perform and interpret multi-level regression modeling and estimate the influence of variable clinical practices on patient outcomes in order to answer common but complex clinical questions.