Postanesthesia Care Unit and Anesthetic Management Outcomes Among Patients Undergoing Noncardiac Surgery: Differences by Race and Ethnicity.

PURPOSE: To investigate the association of patient race and ethnicity with postanesthesia care unit (PACU) outcomes in common, noncardiac surgeries requiring general anesthesia. DESIGN: Single tertiary care academic medical center retrospective matched cohort. METHODS: We matched 1:1 1836 adult patients by race and/or ethnicity undergoing common surgeries. We compared racial and ethnic minority populations (62 American Indian, 250 Asian, 315 Black or African American, 281 Hispanic, and 10 Pacific Islander patients) to 918 non-Hispanic White patients. The primary outcomes were: the use of an appropriate number of postoperative nausea and vomiting (PONV) prophylactics; the incidence of PONV; and the use of a propofol infusion as part of the anesthetic (PROP). Secondary outcomes were: the use of opioid-sparing multimodal analgesia, including the use of regional anesthesia for postoperative pain control; the use of any local anesthetic, including the use of liposomal bupivacaine; the duration until readiness for discharge from the PACU; the time between arrival to PACU and first pain score; and the time between the first PACU pain score of ≥4 and administration of an analgesic. Logistic and linear regression were used for relevant outcomes of interest. FINDINGS: Overall, there were no differences in the appropriate number of PONV prophylactics, nor the incidence of PONV between the two groups. There was, however, a decreased use of PROP (OR = 0.80; 95% CI: 0.69, 0.94; P = .005), PACU length of stay was 9.56 minutes longer (95% CI: 2.62, 16.49; P = .007), and time between arrival to PACU and first pain score was 2.30 minutes longer in patients from racial and ethnic minority populations (95% CI: 0.99, 3.61; P = .001). There were no statistically significant differences in the other secondary outcomes. CONCLUSIONS: The rate of appropriate number of PONV prophylactic medications as well as the incidence of PONV were similar in patients from racial and ethnic minority populations compared to non-Hispanic White patients. However, there was a lower use of PROP in racial and ethnic minority patients. It is important to have a health equity lens to identify differences in management that may contribute to disparities within each phase of perioperative care.

Perioperative Opioid Consumption and Clinical Outcomes in Surgical Patients With a Pre-existing Opioid-Based Intrathecal Drug Delivery System.

BACKGROUND: Intrathecal drug delivery systems (IDDS) have been utilized for over 3 decades for management of chronic pain and spasticity. Patients with IDDS may present for surgical procedures unrelated to the IDDS device, although data are limited regarding perioperative outcomes. METHODS: This is a historical matched cohort study conducted between January 1, 2007 and December 31, 2016 of patients with an opioid-based IDDS versus matched control patients undergoing surgery excluding interventional pain procedures. Patients in the IDDS group were matched with up to 2 patients without an IDDS. Multivariable regression analyses were utilized to assess differences in the primary outcome of cumulative perioperative opioid consumption (ie, intraoperative and postanesthesia care unit [PACU] opioid consumption), and opioid consumption during the first 24 and 72 postoperative hours. Postoperative clinical outcomes were also assessed including escalating oxygen requirements, naloxone administration, pain-sedation mismatch, and perioperative pain service consultation. RESULTS: A total of 321 surgeries were included, 112 with IDDS and 209 controls, with median (interquartile range [IQR]) age of 57 (49-64) years. Compared to matched controls, patients with an IDDS had greater perioperative opioid consumption (median [IQR] oral morphine milligram equivalents [OME] of 110 [60-163] vs 93 [IQR, 53-142]; adjusted multiplicative increase 1.28 [95% confidence interval {CI}, 1.03-1.59]; P = .026). IDDS patients also had greater opioid consumption in the first 24 and 72 postoperative hours (multiplicative increases of 2.23 [95% CI, 1.36-3.63], P = .001, and 2.46 [95% CI, 1.41-4.32], P = .002, respectively). There were no significant differences in postoperative oxygen requirements, naloxone administration, or pain-sedation mismatch. Inpatient pain medicine consultation was more frequent in IDDS patients compared to controls (51.8% vs 6.2%; P < .001). CONCLUSIONS: Patients with opioid-based IDDS received more perioperative opioids and were more likely to receive postoperative pain service consultation compared to matched controls. There were no significant differences in clinical safety outcomes, suggesting tolerance for higher opioid doses. Further research is warranted to optimize perioperative outcomes in those with IDDS.

Peripheral Nerve Blockade with Combined Standard and Liposomal Bupivacaine in Major Lower-Extremity Amputation.

BACKGROUND AND OBJECTIVES: Optimizing perioperative analgesia for patients undergoing major lower-extremity amputation remains a considerable challenge. The utility of liposomal bupivacaine as a component of peripheral nerve blockade for lower-extremity amputation is unknown. METHODS: We conducted an observational study comparing three different perioperative analgesic techniques for adults undergoing major lower-extremity amputation under general anesthesia between 2012 and 2017 at an academic medical center: (1) no regional anesthesia, (2) peripheral nerve blockade with standard bupivacaine, and (3) peripheral nerve blockade with a mixture of standard and liposomal bupivacaine. The primary outcome of cumulative opioid oral morphine milligram equivalent utilization in the first 72 hours postoperatively was compared across groups utilizing multivariable linear regression. RESULTS: A total of 631 unique anesthetics were included for 578 unique patients, including 416 (66%) without regional anesthesia, 131 (21%) with peripheral nerve blockade with a mixture of standard and liposomal bupivacaine, and 84 (13%) with peripheral nerve blockade with standard bupivacaine alone. Cumulative morphine equivalents were lower in those receiving peripheral nerve blockade with combined standard and liposomal bupivacaine compared with those not receiving regional anesthesia (multiplicative increase 0.67; 95% CI 0.50 to 0.90; P = 0.007). There were no significant differences in opioid utilization between peripheral nerve blockade groups (P = 0.59). CONCLUSIONS: Peripheral nerve blockade is associated with reduced opioid requirements after lower-extremity amputation compared with general anesthesia alone. However, the incorporation of liposomal bupivacaine is not significantly different to blockade employing only standard bupivacaine.

Extracorporeal membrane oxygenation and acute kidney injury: a single-center retrospective cohort.

To assess the relationship between acute kidney injury (AKI) with outcomes among patients requiring extracorporeal membrane oxygenation (ECMO). This is a single-center, retrospective cohort study of adult patients admitted to intensive care units (ICU) at a tertiary referral hospital requiring ECMO from July 1, 2015, to August 30, 2019. We assessed the temporal relationship of AKI and renal replacement therapy with ECMO type (VV vs. VA). The primary outcome was in-hospital mortality rates. We used Kruskal-Wallis or chi-square tests for pairwise comparisons, cause-specific Cox proportional hazards models were utilized for the association between AKI prevalence and in-hospital mortality, and a time-dependent Cox model was used to describe the association between AKI incidence and mortality. After the screening, 190 patients met eligibility criteria [133 (70%) AKI, 81 (43%) required RRT]. The median age was 61 years, and 61% were males. Among AKI patients, 48 (36%) and 85 (64%) patients developed AKI before and after ECMO, respectively. The SOFA Day 1, baseline creatinine, respiratory rate (RR), use of vasopressin, vancomycin, proton pump inhibitor, antibiotics, duration of mechanical ventilation and ECMO, and ICU length of stay were higher in AKI patients compared with those without AKI (P < 0.01). While ICU and in-hospital mortality rates were 46% and 50%, respectively, there were no differences based on the AKI status. The type and characteristics of ECMO support were not associated with AKI risk. Among AKI patients, 77 (58%) were oliguric, and 46 (60%) of them received diuretics. Urine output in the diuretic group was only higher on the first day than in those who did not receive diuretics (P = 0.03). Among ECMO patients, AKI was not associated with increased mortality but was associated with prolonged duration of mechanical ventilation and ICU length of stay.

Machine learning in data abstraction: A computable phenotype for sepsis and septic shock diagnosis in the intensive care unit.

BACKGROUND: With the recent change in the definition (Sepsis-3 Definition) of sepsis and septic shock, an electronic search algorithm was required to identify the cases for data automation. This supervised machine learning method would help screen a large amount of electronic medical records (EMR) for efficient research purposes. AIM: To develop and validate a computable phenotype via supervised machine learning method for retrospectively identifying sepsis and septic shock in critical care patients. METHODS: A supervised machine learning method was developed based on culture orders, Sequential Organ Failure Assessment (SOFA) scores, serum lactate levels and vasopressor use in the intensive care units (ICUs). The computable phenotype was derived from a retrospective analysis of a random cohort of 100 patients admitted to the medical ICU. This was then validated in an independent cohort of 100 patients. We compared the results from computable phenotype to a gold standard by manual review of EMR by 2 blinded reviewers. Disagreement was resolved by a critical care clinician. A SOFA score ≥ 2 during the ICU stay with a culture 72 h before or after the time of admission was identified. Sepsis versions as V1 was defined as blood cultures with SOFA ≥ 2 and Sepsis V2 was defined as any culture with SOFA score ≥ 2. A serum lactate level ≥ 2 mmol/L from 24 h before admission till their stay in the ICU and vasopressor use with Sepsis-1 and-2 were identified as Septic Shock-V1 and-V2 respectively. RESULTS: In the derivation subset of 100 random patients, the final machine learning strategy achieved a sensitivity-specificity of 100% and 84% for Sepsis-1, 100% and 95% for Sepsis-2, 78% and 80% for Septic Shock-1, and 80% and 90% for Septic Shock-2. An overall percent of agreement between two blinded reviewers had a k = 0.86 and 0.90 for Sepsis 2 and Septic shock 2 respectively. In validation of the algorithm through a separate 100 random patient subset, the reported sensitivity and specificity for all 4 diagnoses were 100%-100% each. CONCLUSION: Supervised machine learning for identification of sepsis and septic shock is reliable and an efficient alternative to manual chart review.