Warner, David O.

Objective The Pulmonary Embolism Severity Index (PESI) and simplified PESI (sPESI) predict mortality for patients with PE. We compared PESI/sPESI to the Acute Physiology and Chronic Health Evaluation IV (APACHE-IV) in predicting mortality in patients with PE admitted to the intensive care unit (ICU). Additionally, we assessed the performance of a novel ICU-sPESI score created by adding three clinical variables associated with acuity of PE presentation (intubation, confusion [altered mental status], use of vasoactive infusions) to sPESI. Materials and Methods Using the eICU Collaborative Research Database from 2014 to 2015, we conducted a large retrospective cohort study of adult patients admitted to the ICU with a primary diagnosis of PE. We calculated APACHE-IV, PESI, sPESI, and ICU-sPESI scores and compared their performance for predicting in-hospital mortality using area under the receiver operating characteristic (AUROC) curve. Score thresholds for >99% negative predictive values (NPV) were calculated for each score. Survival was estimated using the Kaplan–Meier method. Results We included 1424 PE cases. In-hospital mortality was 6.3% [95% CI: 5.1%-7.6%]. AUROC for APACHE-IV, PESI, and sPESI were 0.870, 0.848, and 0.777, respectively. APACHE-IV and PESI outperformed sPESI (P < 0.01 for both comparisons), while APACHE-IV and PESI demonstrated similar performance (P = 0.322). The ICU-sPESI performance was similar to APACHE-IV and PESI (AUROC = 0.847; AUROC comparison: APACHE-IV vs ICU-sPESI: P = 0.396; PESI vs ICU-sPESI: P = 0.945). Hospital mortality for ICU-sPESI scores 0-2 was 1.1%, and for scores 3, 4, 5, 6, and ≥7 was 8.6%, 11.7%, 29.2%, 37.5%, and 76.9%, respectively. Score thresholds for >99% NPV were ≤48 for APACHE-IV, ≤115 for PESI, and 0 points for sPESI and ICU-sPESI. Conclusions By accounting for severity of PE presentation, our newly proposed ICU-sPESI score provided improved PE mortality prediction compared to the original sPESI score and offered excellent discrimination of mortality risk.

435 Background: Assessing tobacco use and providing cessation support is recommended by the American Society for Clinical Oncology (ASCO). As part of the National Cancer Institute Cancer Center Cessation Initiative, we established an electronic health record based "opt-out" approach to refer patients to tobacco treatment specialists. However, the role of oncologists in contributing to the “opt-out” approach to patients has not been explored. We tested the hypothesis that a multi-component educational program for oncologists would increase the proportion of patients who completed tobacco treatment appointments. Methods: As a quality improvement initiative, oncology providers at the Rochester Mayo Clinic Cancer Center were educated using a multimodal academic detailing approach with group and individual educational sessions. Its effectiveness was tested using a modified step-wedge implementation design. The primary outcomes were patient behaviors that could plausibly be changed by conversations with their provider: the rate at which cancer patients identified as current tobacco users scheduled an appointment in the Nicotine Dependence Center, and the rate at which patients scheduled for a NDC appointment completed their appointment. Comparisons were made before, during, and after the education period (from July through Dec 2019) and with a separate group of providers who did not complete education (results examined over a similar time period). Results: Education intervention did not improve outcomes among providers who received education; indeed, the rate of appointment scheduling decreased, although this may reflect other concurrent changes in the tobacco treatment referral process (Table 1). Outcomes were similar between oncology providers who did and did not receive multicomponent education intervention. Conclusions: Smoking cessation efforts can be successfully integrated into routine cancer care. The implementation of the “opt-out” referral system resulted in approximately 1 in 5 patients being seen for tobacco use, but a multicomponent education intervention designed to equip oncologists to encourage patients to complete appointments was not effective. Novel approaches are needed to increase the uptake of tobacco treatment among patients.[Table: see text]

BACKGROUND: Whether volatile anesthetic solubility affects postanesthesia recovery time in clinical practice is unclear. We investigated the association among 3 volatile agents and 2 clinically relevant outcomes—postanesthesia care unit (PACU) recovery time (time from PACU admission to fulfillment of discharge criteria) and oversedation (Richmond Agitation-Sedation Scale score ≤−3)—as a potential contributor to delaying PACU discharge. The volatile agents studied were isoflurane, desflurane, and sevoflurane. We hypothesized that increased solubility of the volatile agent (isoflurane versus desflurane or sevoflurane) would be associated with longer PACU recovery time and higher rates of oversedation. METHODS: This retrospective observational study included adults (≥18 years) who underwent surgical procedures under general anesthesia with a volatile agent and were admitted to the PACU from May 5, 2018, to December 31, 2020. The primary outcome was PACU recovery time, and the secondary outcome was oversedation. PACU recovery time was log-transformed and analyzed with linear regression. Oversedation was analyzed by using logistic regression. To account for potential confounding, inverse probability of treatment weighting (IPTW) was used. Pairwise comparisons of the 3 agents were performed, with P < .017 (Bonferroni-adjusted) considered significant. RESULTS: Of 47,847 patients included, 11,817 (24.7%) received isoflurane, 11,286 (23.6%) received desflurane, and 24,744 (51.7%) received sevoflurane. Sevoflurane had an estimated 4% shorter PACU recovery time (IPTW-adjusted median [interquartile range {IQR}], 61 [42–89] minutes) than isoflurane (64 [44–92] minutes) (ratio of geometric means [98.3% confidence interval {CI}], 0.96 [0.95–0.98]; P < .001). Differences in PACU recovery time between desflurane and the other agents were not significant. The IPTW-adjusted frequency of oversedation was 8.8% for desflurane, 12.2% for sevoflurane, and 16.7% for isoflurane; all pairwise comparisons were observed to be significant (odds ratio [98.3% CI], 0.70 [0.62–0.79] for desflurane versus sevoflurane, 0.48 [0.42–0.55] for desflurane vs isoflurane, and 0.69 [0.63–0.76] for sevoflurane versus isoflurane; all P < .001). Although oversedated patients had longer PACU recovery time, differences in the oversedation rate across agents did not result in meaningful differences in time to PACU recovery. CONCLUSIONS: In clinical practice, only small, clinically unimportant differences in PACU recovery time were observed between the volatile anesthetics. Although oversedation was associated with increased PACU recovery time, differences in the rate of oversedation among agents were insufficient to produce meaningful differences in overall PACU recovery time across the 3 volatile agents. Practical attempts to decrease PACU recovery time should address factors other than volatile agent selection.

e22500 Background: Oncologists are change agents to improve tobacco cessation among patients. As part of the National Cancer Institute Cancer Center Cessation Initiative, we established an electronic health record (EHR, Epic)-based "opt-out" approach to refer patients to tobacco treatment specialist without active involvement by oncologists. However, the role of oncologists in contributing to the “opt-out” approach to patients has not been explored. We tested the hypothesis that a multi-component educational program for oncologists would increase the proportion of patients who completed tobacco treatment appointments. Methods: As a quality improvement initiative, oncology providers at the Rochester Mayo Clinic Cancer Center were educated using a multimodal academic detailing approach with group and individual educational sessions. Its effectiveness was tested using a modified step-wedge implementation design. The primary outcomes were patient behaviors that could plausibly be changed by conversations with their provider: the rate at which cancer patients identified as current tobacco users scheduled an appointment in the Nicotine Dependence Center (NDC) (which required active patient involvement), and the rate at which patients scheduled for a NDC appointment completed their appointment. Comparisons were made before, during, and after the education period (from July through Dec 2019) and with a separate group of providers who did not complete education (results examined over a similar time period). Results: Education did not improve outcomes in providers who received education; indeed, the rate of appointment scheduling decreased, although this may reflect other concurrent changes in the referral process (Table). Outcomes were similar between providers who did and did not receive education. Conclusions: Tobacco cessation efforts should be routinely integrated into cancer care to improve outcomes. The “opt-out” program resulted in approximately 1 in 5 cancer patients being seen for tobacco use, but an academic detailing approach designed to equip oncology providers to encourage their patients to complete appointments was not effective. Other approaches are needed to increase the uptake of tobacco treatment in these patients. [Table: see text]

Abstract Introduction We determined whether a tobacco cessation intervention targeting brief perioperative abstinence (“quit for a bit”) increased engagement of surgical patients with treatment compared with an intervention targeting long-term postoperative abstinence (“quit for good”). Aims and Methods Surgical patients who smoke were stratified according to intended duration of postoperative abstinence, and then randomized within strata to receive either a “quit for a bit” or a “quit for good” intervention. Both employed initial brief counseling and short message service (SMS) to deliver treatment up to 30 days after surgery. The primary outcome of treatment engagement was defined as the rate at which subjects actively responded to system requests delivered via SMS. Results The engagement index did not differ between intervention groups (median [25th, 75th] of 23.7% [8.8, 46.0] for “quit for a bit” group (n = 48) and 22.2% [4.8, 46.0] for “quit for good” group (n = 50), p = .74), nor did the proportion of patients continuing SMS use after study completion (33% and 28%, respectively). Exploratory abstinence outcomes on the morning of surgery and 7 and 30 days after surgery did not differ between groups. Program satisfaction was high in both groups and did not differ. There was no significant interaction between intended abstinence duration and any outcome, ie, alignment of intent with intervention did not affect engagement. Conclusions Tobacco cessation treatment delivered via SMS was well accepted by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. Implications Treatment of surgical patients for tobacco use is efficacious and reduces postoperative complications. However, implementation in clinical practice has proved challenging, and new methods of engaging these patients in cessation treatment are needed. We found that tobacco use treatment delivered via SMS was feasible and well utilized by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. Clinical Trial Number NCT03839043. Registry URL: https://clinicaltrials.gov/ct2/show/NCT03839043

Although the harmful effects of smoking after a cancer diagnosis have been clearly demonstrated, many patients continue to smoke cigarettes during treatment and beyond. The NCCN Guidelines for Smoking Cessation emphasize the importance of smoking cessation in all patients with cancer and seek to establish evidence-based recommendations tailored to the unique needs and concerns of patients with cancer. The recommendations contained herein describe interventions for cessation of all combustible tobacco products (eg, cigarettes, cigars, hookah), including smokeless tobacco products. However, recommendations are based on studies of cigarette smoking. The NCCN Smoking Cessation Panel recommends that treatment plans for all patients with cancer who smoke include the following 3 tenets that should be done concurrently: (1) evidence-based motivational strategies and behavior therapy (counseling), which can be brief; (2) evidence-based pharmacotherapy; and (3) close follow-up with retreatment as needed.

Abstract Opioids are frequently prescribed to alleviate pain symptoms in older adults, yet the relationships between prescription opioid availability and long-term cognitive function are incompletely defined. We evaluated the associations between prescription opioid availability and neuropsychological function and incident mild cognitive impairment (MCI) by performing a secondary analysis of the Mayo Clinic Study of Aging (MCSA), a longitudinal population-based observational cohort study with participants enrolled between 11/1/2004 and 4/1/2019 aged 65 years or older at the time of enrollment and without dementia. A total of 4,218 participants (51% male) were included with median age of 76 (interquartile range 72, 82) years. In multivariable analyses, each receipt of an opioid prescription, regardless of duration, resulted in an additional -0.007 (95% CI: -0.009, -0.005) change in global cognitive z-score (p&lt; 0.001), with significant effects seen in the domains of memory (-0.005, 95% CI: -0.007, -0.003; p&lt; 0.001), language (-0.002, 95% CI -0.003, 0.000; p=0.024) and attention (-0.004, 95% CI: -0.006, -0.002; p&lt; 0.001) but not visual-spatial function (0.000, 95% CI: -0.001, 0.001; p=0.897). Among 2,963 cognitively unimpaired subjects with longitudinal follow-up, 769 (26%) developed incident MCI. Receipt of any opioid prescription during follow-up was associated with incident MCI in adjusted analysis (hazard ratio 1.21, 95% CI: 1.04, 1.42; p=0.014). In conclusion, prescription opioid availability was associated with cognitive decline across multiple domains and with incident MCI. These findings suggest that prescription opioid availability may have long-term effects on cognitive function.

Tobacco use will kill a projected 1 billion people in the 21st century in one of the deadliest pandemics in history. Tobacco use disorder is a disease with a natural history, pathophysiology, and effective treatment options. Anesthesiologists can play a unique role in fighting this pandemic, providing both immediate (reduction in perioperative risk) and long-term (reduction in tobacco-related diseases) benefits to their patients who are its victims. Receiving surgery is one of the most powerful stimuli to quit tobacco. Tobacco treatments that combine counseling and pharmacotherapy (e.g., nicotine replacement therapy) can further increase quit rates and reduce risk of morbidity such as pulmonary and wound-related complications. The perioperative setting provides a great opportunity to implement multimodal perianesthesia tobacco treatment, which combines multiple evidence-based tactics to implement the four core components of consistent ascertainment and documentation of tobacco use, advice to quit, access to pharmacotherapy, and referral to counseling resources.

Abstract Background Opioids are frequently prescribed to alleviate pain in older adults, yet the relationships between prescription opioids and long‐term cognitive function are unclear. Methods In this analysis of the Mayo Clinic Study of Aging, a longitudinal population‐based cohort study of older adults with formal neuropsychological testing and cognitive evaluations performed every 15 months, the associations between prescription opioids, global and domain‐specific cognitive function, and mild cognitive impairment were evaluated through time‐dependent linear mixed effects and Cox proportional hazards models. Results Four thousand two hundred eighteen participants (51% male) were included with enrollment between 11/1/2004 and 4/1/2019 and median age of 76 (interquartile range 72, 82) years. Two thousand nine hundred seventy‐seven subjects (71%) received at least 1 opioid prescription during a median follow‐up of 7.5 (5.0, 10.7) years. Overall, there was an estimated 0.096 reduction in the global cognitive Z ‐score per year, including decreases of 0.050 in memory, 0.080 in language, 0.044 in visual–spatial cognition, and 0.112 in attention. In multivariable analyses, each receipt of an opioid prescription resulted in an additional −0.007 (95% CI −0.009, −0.005) change in global cognitive Z ‐score ( p < 0.001), with significant effects seen in the domains of memory (−0.005, 95% CI −0.007, −0.003; p < 0.001), language (−0.002, 95% CI −0.003, 0.000; p = 0.024) and attention (−0.004, 95% CI −0.006, −0.002; p < 0.001) but not visual–spatial function (0.000, 95% CI −0.001, 0.001; p = 0.897). Opioid prescriptions were associated with incident mild cognitive impairment (MCI) in adjusted analysis (hazard ratio 1.21, 95% CI 1.04, 1.42; p = 0.014). Conclusion Prescription opioids are associated with small but statistically significant declines in long‐term cognitive function in older adults, which may represent effects of opioids or other related factors.