Intraoperative Prophylaxis with Palonosetron for Postoperative Nausea and/or Vomiting in Adults Undergoing Cardiothoracic Surgery Under General Anesthesia: A Single-Center Retrospective Study.

OBJECTIVE: This study assessed the efficacy of palonosetron, alone or with dexamethasone, in reducing postoperative nausea and/or vomiting (PONV) and its impact on hospitalization duration in patients who undergo adult cardiothoracic surgery (CTS) under general anesthesia. DESIGN: This retrospective analysis involved 540 adult patients who underwent CTS from a single-center cohort, spanning surgeries between September 2021 and March 2023. Sensitivity, logistic, and Cox regression analyses evaluated antiemetic effects, PONV risk factors, and outcomes. SETTING: At the Virginia Mason Medical Center (VMMC), Seattle, WA. PARTICIPANTS: Adults undergoing cardiothoracic surgery at VMMC during the specified period. INTERVENTIONS: Patients were categorized into the following 4 groups based on antiemetic treatment: dexamethasone, palonosetron, dexamethasone with palonosetron, and no antiemetic. MEASUREMENTS AND MAIN RESULTS: Primary outcomes encompassed PONV incidence within 96 hours postoperatively. Secondary outcomes included intensive care unit stay duration and postoperative opioid use. Palonosetron recipients showed a significantly lower PONV rate of 42% (v controls at 63%). The dexamethasone and palonosetron combined group also demonstrated a lower rate of 40%. Sensitivity analysis revealed a notably lower 0- to 12-hour PONV rate for palonosetron recipients (9% v control at 28%). Logistic regression found decreased PONV risk (palonosetron odds ratio [OR]: 0.24; dexamethasone and palonosetron OR: 0.26). Cox regression identified varying PONV hazard ratios related to female sex, PONV history, and lower body mass index. CONCLUSIONS: This single-center retrospective study underscored palonosetron's efficacy, alone or combined with dexamethasone, in managing PONV among adult patients who undergo CTS. These findings contribute to evolving antiemetic strategies in cardiothoracic surgery, potentially impacting patient outcomes and satisfaction positively.

Evaluation of machine learning models as decision aids for anesthesiologists.

Machine Learning (ML) models have been developed to predict perioperative clinical parameters. The objective of this study was to determine if ML models can serve as decision aids to improve anesthesiologists' prediction of peak intraoperative glucose values and postoperative opioid requirements. A web-based tool was used to present actual surgical case and patient information to 10 practicing anesthesiologists. They were asked to predict peak glucose levels and post-operative opioid requirements for 100 surgical patients with and without presenting ML model estimations of peak glucose and opioid requirements. The accuracies of the anesthesiologists' estimates with and without ML estimates as reference were compared. A questionnaire was also sent to the participating anesthesiologists to obtain their feedback on ML decision support. The accuracy of peak glucose level estimates by the anesthesiologists increased from 79.0 ± 13.7% without ML assistance to 84.7 ± 11.5% (< 0.001) when ML estimates were provided as reference. The accuracy of opioid requirement estimates increased from 18% without ML assistance to 42% (p < 0.001) when ML estimates were provided as reference. When ML estimates were provided, predictions of peak glucose improved for 8 out of the 10 anesthesiologists, while predictions of opioid requirements improved for 7 of the 10 anesthesiologists. Feedback questionnaire responses revealed that the anesthesiologist primarily used the ML estimates as reference to modify their clinical judgement. ML models can improve anesthesiologists' estimation of clinical parameters. ML predictions primarily served as reference information that modified an anesthesiologist's clinical estimate.

Using Lean tools to improve the efficiency of awake fibreoptic intubation setup.

BACKGROUND: Awake fibreoptic intubation is a complex advanced airway technique used by anaesthesiologists in the management of a difficult airway. The time to setup this important procedure can be significant which may dissuade its use by some providers. In our institution, the awake intubation setup process was highly variable and error prone. METHODS: We deployed Lean methods to improve the efficiency and accuracy of the awake fibreoptic intubation setup process. A 2-day improvement event with a multidisciplinary team addressed the setup process, tested solutions and created standard work documents. Twenty awake fibreoptic intubation simulations were conducted before and after the intervention to quantify gains in setup efficiency and error reduction. RESULTS: Variability in the setup process, including clinical locations visited, was reduced through creating a standardised process. The average time to for an awake fibreoptic intubation setup was reduced by approximately 50%, from 23 min to 11 min (p<0.001). In addition, awake fibreoptic intubation equipment set out without error increased in the postintervention simulations from 59% to 85% (p=0.003). CONCLUSION: Using Lean tools, we were able to make the setup of awake fibreoptic intubation not only more efficient, but also more accurate. A similar methodological approach may have value for other complex anaesthesia procedures.

Incidence and Classification of Nonroutine Events during Anesthesia Care.

BACKGROUND: A nonroutine event is any aspect of clinical care perceived by clinicians or trained observers as a deviation from optimal care based on the context of the clinical situation. The authors sought to delineate the incidence and nature of intraoperative nonroutine events during anesthesia care. METHODS: The authors prospectively collected audio, video, and relevant clinical information on 556 cases at three academic hospitals from 1998 to 2004. In addition to direct observation, anesthesia providers were surveyed for nonroutine event occurrence and details at the end of each study case. For the 511 cases with reviewable video, 400 cases had no reported nonroutine events and 111 cases had at least one nonroutine event reported. Each nonroutine event was analyzed by trained anesthesiologists. Rater reliability assessment, comparisons (nonroutine event vs. no event) of patient and case variables were performed. RESULTS: Of 511 cases, 111 (21.7%) contained 173 nonroutine events; 35.1% of event-containing cases had more than one nonroutine event. Of the 173 events, 69.4% were rated as having patient impact and 12.7% involved patient injury. Longer case duration (25th vs. 75th percentile; odds ratio, 1.83; 95% CI, 1.15 to 2.93; P = 0.032) and presence of a comorbid diagnosis (odds ratio, 2.14; 95% CI, 1.35 to 3.40; P = 0.001) were associated with nonroutine events. Common contributory factors were related to the patient (63.6% [110 of 173]) and anesthesia provider (59.0% [102 of 173]) categories. The most common patient impact events involved the cardiovascular system (37.4% [64 of 171]), airway (33.3% [57 of 171]), and human factors, drugs, or equipment (31.0% [53 of 171]). CONCLUSIONS: This study describes characteristics of intraoperative nonroutine events in a cohort of cases at three academic hospitals. Nonroutine event-containing cases were commonly associated with patient impact and injury. Thus, nonroutine event monitoring in conjunction with traditional error reporting may enhance our understanding of potential intraoperative failure modes to guide prospective safety interventions.

Mental health conditions and the risk of chronic opioid therapy among patients with rheumatoid arthritis: a retrospective veterans affairs cohort study.

OBJECTIVE: Patients with rheumatoid arthritis (RA) often receive opioid analgesics for pain management. We examined the association between mental health conditions and the risk of chronic opioid therapy. METHODS: A retrospective cohort of veterans with RA initiating opioid use was assembled using Veterans Health Administration databases (2001-2012). Mental health conditions included anxiety (N = 1108, 12.9%), depression (N = 1912, 22.2%), bipolar disease (N = 131, 1.5%), and post-traumatic stress disorder (N = 768, 8.9%) and were identified by ICD coded diagnoses and use of specific medications. Cohort members were followed from opioid initiation through chronic opioid therapy, defined as the continuous availability of opioids for at least 90 days. Multivariable Cox proportional hazard regression models assessed the association between mental health conditions and chronic opioid therapy accounting for relevant covariates. Subgroup analyses examined whether the strength of the observed association varied by the duration of the initial opioid prescription. RESULTS: We identified 14,767 patients with RA with 22,452 episodes of opioid use initiation. Mental health conditions were identified in 8607 (38.3%) patients. Compared with patients without mental health conditions, patients with mental health conditions have a higher risk of developing chronic opioid therapy (469.3 vs 378.1 per 1000 person-years, adjusted hazard ratio [aHR] 1.18, 95% CI 1.09, 1.29). The increased risk was highest for those with a history of opioid use disorder (aHR 1.94, 95% CI 1.09, 3.46) and also elevated for those with other substance use disorders (aHR 1.35, 95% CI 1.05, 1.73). Duration of the initial opioid prescription was independently associated with chronic opioid therapy, regardless of the estimated opioid daily dose. CONCLUSIONS: History of mental health conditions and duration of the initial opioid prescription were associated with an increased risk of chronic opioid therapy among patients with RA.Key Points• Approximately a third of patients with RA are exposed to opioid analgesics.• Patients with RA and history of mental health disease, especially substance use disorders, who initiate opioid use have an increased risk of chronic opioid therapy.• This study provides insight in an underrepresented population of mainly male patients with RA.

Opioid Prescriptions at Hospital Discharge Are Associated With More Postdischarge Healthcare Utilization.

Background Many patients use opioids for nonmalignant pain, and opioid use in the general population has been associated with poor long-term outcomes. The use of high-risk medications, including opioid analgesics, may increase the risk of unplanned healthcare utilization. Methods and Results We performed a nested evaluation in the VICS (Vanderbilt Inpatient Cohort Study) (N=3000) on patients with an admitting diagnosis of acute coronary syndrome and/or acute decompensated heart failure. Patient enrollment occurred from October 2011 until December 2015 and involved a single investigational site, Vanderbilt University Medical Center (Nashville, TN). Of the 2495 eligible patients, 501 (20%) were discharged with an opioid prescription and were predominantly white and men, with a median age of 59 (interquartile range, 53-67) years. Our primary outcome was unplanned healthcare utilization, which included emergency department presentation or readmission. Secondary outcomes included mortality and a composite of planned utilization behaviors: cardiac rehabilitation and provider follow-up within 30 days. Cox proportional hazards models did not show a statistically significant association with increased unplanned utilization (adjusted hazard ratio, 1.06; 95% CI, 0.87-1.28) or mortality (adjusted hazard ratio, 1.08; 95% CI , 0.84-1.39), compared with those without opioids at discharge. Patients discharged with opioids were less likely to complete planned healthcare utilization (adjusted odds ratio, 0.69; 95% CI , 0.52-0.91). Conclusions There are decreased odds of planned healthcare utilization among patients with acute coronary syndrome and acute decompensated heart failure discharged with opioid medication. It is imperative to understand how opioid use can affect a patient's relationship with the healthcare system.

Difficult Ventilation After Successful Intubation in the Emergency Setting due to a Ball Valve Clot.

The inability to ventilate a patient after successful intubation is a rare but emergent situation and may be caused by obstruction of the endotracheal tube, bilateral tension pneumothorax, esophageal intubation, severe bronchospasm, or mainstem bronchus intubation. We describe an increase in mean airway pressure, inability to ventilate, and loss of cardiac output secondary to a blood clot acting as a ball valve at the end of an endotracheal tube.

Determination of the active site of Sphingobium chlorophenolicum 2,6-dichlorohydroquinone dioxygenase (PcpA).

2,6-Dichlorohydroquinone 1,2-dioxygenase (PcpA) from Sphingobium chlorophenolicum ATCC 39723 is a member of a class of Fe(II)-containing hydroquinone dioxygenases that is involved in the mineralization of the pollutant pentachlorophenol. This enzyme has not been extensively characterized, despite its interesting ring-cleaving activity and use of Fe(II), which are reminiscent of the well-known extradiol catechol dioxygenases. On the basis of limited sequence homology to the extradiol catechol dioxygenases, the residues ligating the Fe(II) center were originally proposed to be H159, H227, and E276 (Xu et al. in Biochemistry 38:7659-7669, 1999). However, PcpA has higher sequence homology to a newly reported, crystallographically characterized zinc metalloenzyme that has a similar predicted fold. We generated a homology model of the structure of PcpA based upon the structure of this zinc metalloenzyme. The homology model predicts that the tertiary structure of PcpA differs significantly from that of the extradiol dioxygenases, and that the residues ligating the Fe(II) are H11, H227, and E276. This structural model was tested by mutating each of H11, H159, H227, and E276 to alanine. An additional residue that is predicted to lie near the active site and is conserved among PcpA, its closest homologues, and the extradiol dioxygenases, Y266, was mutated to phenylalanine. Of these mutants, only H159A retained significant activity, thus confirming the active-site location predicted by the homology-based structural model. The model provides an important basis for understanding the origin of the unique function of PcpA.