Anesthesia and analgesia最新文献

This consensus statement is a comprehensive update of the 2010 Society for Ambulatory Anesthesia (SAMBA) Consensus Statement on perioperative blood glucose management in patients with diabetes mellitus (DM) undergoing ambulatory surgery. Since the original consensus guidelines in 2010, several novel therapeutic interventions have been introduced to treat DM, including new hypoglycemic agents and increasing prevalence of insulin pumps and continuous glucose monitors. The updated recommendations were developed by an expert task force under the provision of SAMBA and are based on a comprehensive review of the literature from 1980 to 2022. The task force included SAMBA members with expertise on this topic and those contributing to the primary literature regarding the management of DM in the perioperative period. The recommendations encompass preoperative evaluation of patients with DM presenting for ambulatory surgery, management of preoperative oral hypoglycemic agents and home insulins, intraoperative testing and treatment modalities, and blood glucose management in the postanesthesia care unit and transition to home after surgery. High-quality evidence pertaining to perioperative blood glucose management in patients with DM undergoing ambulatory surgery remains sparse. Recommendations are therefore based on recent guidelines and available literature, including general glucose management in patients with DM, data from inpatient surgical populations, drug pharmacology, and emerging treatment data. Areas in need of further research are also identified. Importantly, the benefits and risks of interventions and clinical practice information were considered to ensure that the recommendations maintain patient safety and are clinically valid and useful in the ambulatory setting. What Other Guidelines Are Available on This Topic? Since the publication of the SAMBA Consensus Statement for perioperative blood glucose management in the ambulatory setting in 2010, several recent guidelines have been issued by the American Diabetes Association (ADA), the American Association of Clinical Endocrinologists (AACE), the Endocrine Society, the Centre for Perioperative Care (CPOC), and the Association of Anaesthetists of Great Britain and Ireland (AAGBI) on DM care in hospitalized patients; however, none are specific to ambulatory surgery. How Does This Guideline Differ From the Previous Guidelines? Previously posed clinical questions that were outdated were revised to reflect current clinical practice. Additional questions were developed relating to the perioperative management of patients with DM to include the newer therapeutic interventions.

Background: The American Heart Association (AHA) recently defined the cardiovascular-kidney-metabolic syndrome (CKM) as a new entity to address the complex interactions between heart, kidneys, and metabolism. The aim of this study was to assess the outcome impact of CKM syndrome in patients undergoing noncardiac surgery.

Methods: This is a secondary analysis of a prospective international cohort study including patients aged ≥45 years with increased cardiovascular risk undergoing noncardiac surgery. Main exposure was CKM syndrome according to the AHA definition. The primary end point was a composite of major adverse cardiovascular events (MACE) 30 days after surgery. Secondary end points included all-cause mortality and non-MACE complications (Clavien-Dindo class ≥3).

Results: This analysis included 14,634 patients (60.8% male, mean age = 72±8 years). MACE occurred in 308 patients (2.1%), and 335 patients (2.3%) died. MACE incidence by CKM stage was as follows: CKM 0: 5/367 = 1.4% (95% confidence interval [CI], 0.4%-3.2%); CKM 1: 3/367 = 0.8% (95% CI, 0.2%-2.4%); CKM 2: 102/7440 = 1.4% (95% CI, 1.1%-1.7%); CKM 3: 27/953 = 2.8% (95% CI, 1.9%-4.1%); CKM 4a: 164/5357 = 3.1% (95% CI, 2.6%-3.6%); CKM 4b: 7/150 = 4.7% (95% CI, 1.9%-9.4%). In multivariate logistic regression, CKM stage ≥3 was independently associated with MACE, mortality, and non-MACE complications, respectively (MACE: OR 2.26 [95% CI, 1.78-2.87]; mortality: OR 1.42 [95% CI: 1.13 -1.78]; non-MACE complications: OR 1.11 [95% CI: 1.03-1.20]).

Conclusion: The newly defined CKM syndrome is associated with increased morbidity and mortality after non-cardiac surgery. Thus, cardiovascular, renal, and metabolic disorders should be regarded in mutual context in this setting.

Background: During spinal surgery, the motor tracts can be monitored using muscle-recorded transcranial electrical stimulation motor-evoked potentials (mTc-MEPs). We aimed to investigate the association of anesthetic and physiological parameters with mTc-MEPs.

Methods: Intraoperative mTc-MEP amplitudes, mTc-MEP area under the curves (AUC), and anesthetic and physiological measurements were collected retrospectively from the records of 108 consecutive patients undergoing elective spinal surgery. Pharmacological parameters of interest included propofol and opioid concentration, ketamine and noradrenaline infusion rates. Physiological parameters recorded included mean arterial pressure (MAP), bispectral index (BIS), heart rate, hemoglobin O 2 saturation, temperature, and Et co2 . A forward selection procedure was performed using multivariable mixed model analysis.

Results: Data from 75 (69.4%) patients were included. MAP and BIS were significantly associated with mTc-MEP amplitude ( P < .001). mTc-MEP amplitudes increased by 6.6% (95% confidence interval [CI], 2.7%-10.4%) per 10 mm Hg increase in MAP and by 2.79% (CI, 2.26%-3.32%) for every unit increase in BIS. MAP ( P < .001), BIS ( P < .001), heart rate ( P = .01), and temperature ( P = .02) were significantly associated with mTc-MEP AUC. The AUC increased by 7.5% (CI, 3.3%-11.7%) per 10 mm Hg increase of MAP, by 2.98% (CI, 2.41%-3.54%) per unit increase in BIS, and by 0.68% (CI, 0.13%-1.23%) per beat per minute increase in heart rate. mTc-MEP AUC decreased by 21.4% (CI, -38.11% to -3.98%) per degree increase in temperature.

Conclusions: MAP, BIS, heart rate, and temperature were significantly associated with mTc-MEP amplitude and/or AUC. Maintenance of BIS and MAP at the high normal values may attenuate anesthetic effects on mTc-MEPs.

Background: The effect of intraoperative anesthetic regimen on pulmonary outcome after minimally invasive esophagectomy for esophageal cancer is yet undetermined. The aim of this study was to determine the effect of volatile anesthesia (sevoflurane or desflurane) compared with propofol-based intravenous anesthesia on pulmonary complications after minimally invasive esophagectomy.

Methods: Patients scheduled for minimally invasive esophagectomy were randomly assigned to 1 of 3 general anesthetic regimens (sevoflurane, desflurane, or propofol). The primary outcome was the incidence of pulmonary complications within the 7 days postoperatively, which was a collapsed composite end point, including respiratory infection, pleural effusion, pneumothorax, atelectasis, respiratory failure, bronchospasm, pulmonary embolism, and aspiration pneumonitis. The severity of pulmonary complications, surgery-related complications, and other secondary outcomes were also assessed.

Results: Of 647 patients assessed for eligibility, 558 were randomized, and 553 were analyzed. A total of 185 patients were assigned to the sevoflurane group, 185 in the desflurane, and 183 in the propofol group. Patients receiving a volatile anesthetic (sevoflurane or desflurane) had a significantly lower incidence (36.5% vs 47.5%; odds ratio, 0.63; 95% confidence interval, 0.44-0.91; P = .013) and lower severity grade of pulmonary complications ( P = .035) compared to the patients receiving propofol. There were no statistically significant differences in other secondary outcomes between the 2 groups.

Conclusions: In patients undergoing minimally invasive esophagectomy, the use of volatile anesthesia (sevoflurane or desflurane) resulted in the reduced risk and severity of pulmonary complications within the first 7 postoperative days as compared to propofol-based intravenous anesthesia.

Background: The effect of sevoflurane on left ventricular diastolic function is not well understood. We hypothesized that parameters of diastolic function may improve under sevoflurane anesthesia in patients with preexisting diastolic dysfunction compared to patients with normal diastolic function.

Methods: This observational study included 60 patients undergoing breast surgery or laparoscopic cholecystectomy. Patients were assigned to diastolic dysfunction (n = 34) or normal (n = 26) groups of septal e' < 8 or ≥ 8.0 cm/s on the first thoracic echocardiography (TTE) performed before anesthesia. During anesthesia, sevoflurane was maintained at 1 to 2 minimum alveolar concentration (MAC) to maintain the bispectral index at 40 to 50. At the end of surgery, the second TTE was performed under 0.8 to 1 MAC of sevoflurane with the patient breathing spontaneously without ventilator support. Primary end point was the percentage change (Δ) of e' on 2 TTEs (Δe'). Secondary end points were ΔE/e', Δleft atrial volume index (ΔLAVI), and Δtricuspid regurgitation maximum velocity (ΔTR Vmax). These percentage changes (Δ) were compared between diastolic dysfunction and normal groups.

Results: e' (Δe': 30 [6, 64] vs 0 [-18, 11]%; P < .001), mitral inflow E wave velocity (E), mitral inflow E/A ratio (E/A), and mitral E velocity deceleration time (DT) improved significantly in diastolic dysfunction group compared to normal group. LAVI decreased in diastolic dysfunction group but did not reach statistical significance between the 2 groups (ΔLAVI:-15 [-31, -3] vs -4 [-20, 10]%, P = .091). ΔE/e' was not different between the 2 groups (11 [-16, 26] vs 12 [-9, 22]%, P = .853) (all: median [interquartile range, IQR]). TR was minimal in both groups.

Conclusions: In this study, echocardiographic parameters of diastolic function, including septal e', E, E/A, and DT, improved with sevoflurane anesthesia in patients with preexisting diastolic dysfunction, but remained unchanged in patients with normal diastolic function.

Background: Anesthesia monitors and devices are usually controlled with some combination of dials, keypads, a keyboard, or a touch screen. Thus, anesthesiologists can operate their monitors only when they are physically close to them, and not otherwise task-loaded with sterile procedures such as line or block placement. Voice recognition technology has become commonplace and may offer advantages in anesthesia practice such as reducing surface contamination rates and allowing anesthesiologists to effect changes in monitoring and therapy when they would otherwise presently be unable to do so. We hypothesized that this technology is practicable and that anesthesiologists would consider it useful.

Methods: A novel voice-driven prototype controller was designed for the GE Solar 8000M anesthesia patient monitor. The apparatus was implemented using a Raspberry Pi 4 single-board computer, an external conference audio device, a Google Cloud Speech-to-Text platform, and a modified Solar controller to effect commands. Fifty anesthesia providers tested the prototype. Evaluations and surveys were completed in a nonclinical environment to avoid any ethical or safety concerns regarding the use of the device in direct patient care. All anesthesiologists sampled were fluent English speakers; many with inflections from their first language or national origin, reflecting diversity in the population of practicing anesthesiologists.

Results: The prototype was uniformly well-received by anesthesiologists. Ease-of-use, usefulness, and effectiveness were assessed on a Likert scale with means of 9.96, 7.22, and 8.48 of 10, respectively. No population cofactors were associated with these results. Advancing level of training (eg, nonattending versus attending) was not correlated with any preference. Accent of country or region was not correlated with any preference. Vocal pitch register did not correlate with any preference. Statistical analyses were performed with analysis of variance and the unpaired t -test.

Conclusions: The use of voice recognition to control operating room monitors was well-received anesthesia providers. Additional commands are easily implemented on the prototype controller. No adverse relationship was found between acceptability and level of anesthesia experience, pitch of voice, or presence of accent. Voice recognition is a promising method of controlling anesthesia monitors and devices that could potentially increase usability and situational awareness in circumstances where the anesthesiologist is otherwise out-of-position or task-loaded.

Background: Three settings are required on a programmed intermittent epidural bolus (PIEB) pump for labor analgesia: the PIEB next bolus (PIEBnb), PIEB interval (PIEBi), and PIEB volume (PIEBv). The ideal settings for these parameters are still unknown. We hypothesized a mathematical modeling tool, response surface methodology (RSM), could estimate 3 PIEB pump parameters while balancing 3 clinically important patient outcomes simultaneously. The study objective was to use RSM to estimate PIEB settings (PIEBnb, PIEBi, and PIEBv) while maximizing maternal satisfaction, minimizing the need for clinician-administered boluses, and optimizing the ratio of delivered/requested patient-controlled epidural analgesia (PCEA) boluses simultaneously.

Methods: With institutional ethics approval, a double-blind randomized trial was completed in a tertiary care labor and delivery center. Nulliparous, English-speaking American Society of Anesthesiologists (ASA) physical status II patients aged 18 to 45 years at full term, single gestation in vertex presentation, in spontaneous labor and ≤7 cm cervical dilation were included. Patients with comorbidities, contraindications to neuraxial analgesia, using chronic analgesics, <152 cm, or body mass index (BMI) >45 kg/m 2 were excluded. After informed consent, labor analgesia was initiated using 10 mL ropivacaine 0.2% with 10 µg/mL fentanyl solution and PCEA (volume 6 mL every 10 minutes). Patients were randomized to predetermined PIEB settings. RSM identified 3 pump settings that represented a stationary point that best maximized or minimized 3 outcomes simultaneously: PCEA ratio (a ratio closest to 1), clinician bolus (optimal is 0), and maternal satisfaction (visual analog scale, 0-100, ideal response is ≥90).

Results: Of 287 potential participants, 192 did not meet inclusion criteria or declined to participate, and 26 were withdrawn, leaving 69 patients for study inclusion. Using RSM, the suggested PIEB settings for all the primary study outcomes were as follows: PIEBnb = 29.4 minutes, PIEBi = 59.8 minutes, and PIEBv = 6.2 mL. These PIEB settings corresponded to the following clinical outcomes: maternal satisfaction at 93.9%, PCEA ratio at 0.77, and need for clinician bolus at 0.29. The dermatome sensory score was between T10 and T5 in 89% of the patients. The median lowest Bromage score was 4.

Conclusions: This novel study used a mathematical model to estimate PIEB pump settings while simultaneously maximizing 3 clinical outcomes. Equally weighted clinical outcomes prevent maximal outcome optimization and may not reflect patient priorities. Future studies or quality improvement endeavors could use RSM methodology to estimate PIEB pump settings targeting optimal values for a single clinical outcome of determined importance to parturients.