Myocardial injury after noncardiac surgery (MINS) impact in cancer is unclear. In a general population, high-sensitivity troponin-I assays (hsTnI) have better MINS detection than contemporary troponin-I (TnI) assays. This study summarizes MINS prevalence in cancer surgery patients using hsTnI and TnI. The primary endpoint was 30-day mortality. Secondary endpoints included 90-day mortality, and observed-to-expected length of stay ratio [O: E LOS]. MINS was explored using three postoperative elevation definitions: MINSTnI: TnI ≥ 0.06 ng/mL, MINShsTnI: hsTnI ≥ 17 ng/L (female) ≥ 35 ng/L (male), or MINSeither: MINSTnI or MINShsTnI. MINS and patient characteristics were analyzed for univariable associations with 30-day mortality using logistic regression. The association between MINS and cardiotoxic cancer therapy was assessed with Chi-squared test, and association with secondary endpoints were quantified with regression analyses. Among 4,278 patients, prevalence of MINSTnI, MINShsTnI, and MINSeither were 4.6

Interest in the potential applications of artificial intelligence in medicine, anesthesiology, and the world at large has never been higher. The Anesthesia Research Council steering committee formed an anesthesiologist artificial intelligence expert workgroup charged with evaluating the current state of artificial intelligence in anesthesiology, providing examples of future artificial intelligence applications and identifying barriers to artificial intelligence progress. The workgroup's findings are summarized here, starting with a brief introduction to artificial intelligence for clinicians, followed by overviews of current and anticipated artificial intelligence-focused research and applications in anesthesiology. Anesthesiology's progress in artificial intelligence is compared to that of other medical specialties, and barriers to artificial intelligence development and implementation in our specialty are discussed. The workgroup's recommendations address stakeholders in policymaking, research, development, implementation, training, and use of artificial intelligence-based tools for perioperative care.

BACKGROUND AND OBJECTIVE:Several observational studies have claimed that the use of neuraxial anesthesia reduces the risk of recurrence after urologic cancer surgery. However, its use is associated with age, comorbidity, and cancer stage, raising concerns of confounding. We aimed to assess the published literature to evaluate causal inference reporting. METHODS:We performed a systematic review of observational studies evaluating the association between anesthesia type and oncologic outcomes in urologic cancer surgery. We used a three-point scale to describe how causal inference was recorded on seven separate reporting criteria. To explore the issue of confounding directly, we evaluated the oncologic outcomes of patients undergoing radical cystectomy at a major cancer hospital according to the type of anesthesia received. KEY FINDINGS AND LIMITATIONS:We retrieved 18 studies on anesthesia and recurrence after urologic cancer surgery. Reference to causality was completely absent in more than half of the papers; all but one paper failed to assess the control of confounding in the Results section or addressed causal inference in the Discussion section. An analysis of the cohort at our own institution demonstrated large differences in age, comorbidity, and cancer stage, and inconsistent findings between overall, recurrence-free, and cancer-specific survival. CONCLUSIONS AND CLINICAL IMPLICATIONS:Reporting of causal inference is poor for observational studies of neuraxial anesthesia in urologic cancer surgery. The current literature is beset by residual and unmeasured confounding, and randomized controlled trials appear to be the only solution to this research question. However, these are unlikely to be a research priority given the weak biologic rationale. Reporting of causal inference in the urologic literature needs dramatic improvement.

The growth of interventional radiology (IR) procedures with anesthesia team care in increasingly medically complex populations points to the need for effective and efficient pre-procedure screening. We present an ongoing quality improvement project involving a brief online questionnaire disseminated to patients three to ten days before the day of their scheduled IR procedures. The questionnaire was developed by anesthesiologists and a nurse practitioner to increase pre-procedure awareness of relevant medical concerns, guide scheduling of procedures at outpatient versus inpatient locations, and improve patient pre-procedure management. The response rate after one year was 57% and indicated that at least 1 in 10 patient histories required review and discussion by the care team. The most common concerns were shortness of breath (8%), difficult airway (3%) and syncope (3%). Most procedures proceeded as scheduled, however, 18 procedures (0.4% of patients who responded), had to be rescheduled from an outpatient to the inpatient site due to medical concerns. The electronic pre-procedure screening has been feasible to implement at a busy clinical practice and has improved team communication, patient preparedness, and scheduling at appropriate locations. The team has since expanded the questionnaire to other non-operating room anesthesia procedures and added questions about opioids and glucagon-like peptide-1 receptor agonists use. Future work needs to evaluate whether the online pre-screening was associated with decreases in cancelation rates and cost savings.

Editorial| July 2024 Vital Sign Data Quality: Not Just a Retrospective Research Problem This article has an Audio Podcast Patrick J. McCormick, M.D., M.Eng. Patrick J. McCormick, M.D., M.Eng. 1Department of Anesthesiology and Critical Care Medicine, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Anesthesiology, Weill Cornell Medicine, New York, New York. https://orcid.org/0000-0002-7062-2409 Search for other works by this author on: This Site PubMed Google Scholar Author and Article Information Accepted for publication April 9, 2024. This editorial accompanies the article on p. 32. Address correspondence to Dr. McCormick: Anesthesiology July 2024, Vol. 141, 4–6. https://doi.org/10.1097/ALN.0000000000005012 Connected Content Article: A Comparison of Five Algorithmic Methods and Machine Learning Pattern Recognition for Artifact Detection in Electronic Records of Five Different Vital Signs: A Retrospective Analysis Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Cite Icon Cite Get Permissions Search Site Citation Patrick J. McCormick; Vital Sign Data Quality: Not Just a Retrospective Research Problem. Anesthesiology 2024; 141:4–6 doi: https://doi.org/10.1097/ALN.0000000000005012 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll PublicationsAnesthesiology Search Advanced Search Topics: vital signs, artifacts An essential skill of an experienced anesthesiologist is to quickly determine when a vital sign alarm is valid. When the oscillometric blood pressure cuff fails to detect pulsations during deflation, is that due to the surgeon leaning on the cuff or a sudden drop in cardiac output? If the automated arrhythmia detection alarm sounds, is the patient's heart fibrillating or is the junior surgical resident applying antiseptic a little too roughly? The anesthesiologist in the room has the benefit of context in these situations, but that context is left behind when we preserve vital sign data for later analysis. Vital sign data artifacts not only are a problem for retrospective observational research but also pose a threat to the accuracy of automated quality measures and pragmatic prospective clinical trial results. In this issue of Anesthesiology, Maleczek et al.1 at the Medical University of Vienna (Vienna, Austria) compare old... You do not currently have access to this content.

Introduction:Gabapentin has been used in enhanced recovery after surgery (ERAS) pathways for pain control for patients undergoing ambulatory uro-oncologic surgery; however, it may cause undesirable side effects. We studied the causal association between gabapentin and rapidity of recovery and perioperative pain management after minimally invasive uro-oncologic surgery.Methods:We identified 2397 patients <= 65 years undergoing prostatectomies or nephrectomies between 2018 and 2022; 131 (5.5%) did not receive gabapentin. We tested the effect of gabapentin use on time of discharge and perioperative opioid consumption, respectively, using multivariable linear regression adjusting for potential confounders including age, gender, BMI, American Society of Anesthesiologists score, and surgery type.Results:On adjusted analysis, we found no evidence of a difference in discharge time among those who did vs did not receive gabapentin (adjusted difference 0.07 hours shorter on gabapentin; 95% CI -0.17, 0.31; P = .6). There was no evidence of a difference in intraoperative opioid consumption by gabapentin receipt (adjusted difference -1.5 morphine milligram equivalents; 95% CI -4.2, 1.1; P = .3) or probability of being in the top quartile of postoperative opioid consumption within 24 hours (adjusted difference 4.2%; 95% CI -4.8%, 13%; P = .4). We saw no important differences in confounders by gabapentin receipt suggesting causal conclusions are justified.Conclusions:Our confidence intervals did not include clinically meaningful benefits from gabapentin, when used with an ERAS protocol, in terms of length of stay or perioperative opioid use. These results support the omission of gabapentin from ERAS protocols for minimally invasive uro-oncologic surgeries.

Background Autologous breast reconstruction is associated with significant pain impeding early recovery. Our objective was to evaluate the impact of replacing surgeon-administered local infiltration with preoperative paravertebral (PVB) and erector spinae plane (ESP) blocks for latissimus dorsi myocutaneous flap reconstruction. Methods Patients who underwent mastectomy with latissimus flap reconstruction from 2018 to 2022 were included in three groups: local infiltration, PVB, and ESP blocks. Block effect on postoperative length of stay (LOS) and the association between block status and pain, opioid consumption, time to first analgesic, and postoperative antiemetic administration were assessed. Results 122 patients met the inclusion criteria for this retrospective cohort study: no block (n=72), PVB (n=26), and ESP (n=24). On adjusted analysis, those who received a PVB block had a 20-hour shorter postoperative stay (95% CI 11 to 30; p<0.001); those who received ESP had a 24-hour (95% CI 15 to 34; p<0.001) shorter postoperative stay compared with the no block group, respectively. Using either block was associated with a reduction in intraoperative opioids (23 morphine milligram equivalents (MME)), 95% CI 14 to 31, p<0.001; ESP versus no block: 23 MME, 95% CI 14 to 32, p<0.001). Conclusions Replacing surgical infiltration with PVB and ESP blocks for autologous breast reconstruction reduces LOS. The comparable reduction in LOS suggests that ESP may be a viable alternative to PVB in patients undergoing latissimus flap breast reconstruction following mastectomy. Further research should investigate whether ESP or PVB have better patient outcomes in complex breast reconstruction.

Supplementary Methods, Figures, and Table legends

Figure S3. Tumors with high and low opioid pathway gene expression have differential pathologic stage in ccRCC.

Figure S7. Gene network enrichment for microenvironment cell-type specific gene signatures.

Figure S6. Correlation between TCGA and MSKCC gene expression for eight survival-associated networks.

Figure S9. Gene expression correlation between immune signature genes (y axis) and four ccRCC master regulator genes (x axis): (A) PLXNB1, (B) CREB5, (C) IL4R, (D) CLEC2D.

Supplementary Tables 1-8. Table S1. Mutations of the Reactome opioid signaling pathway in ccRCC. Table S2. Module membership for each module. Table S3. Gene ontology coexpression network enrichment. Table S4. Cox survival analysis for association of the 15 networks and survival endpoints. Table S5. Clinical and demographic overrepresentation in sample subgroups with high module eigengene expression. Table S6. List of hub genes for the eight cancer-specific survival-associated networks. Table S7. Master regulators of the transition from normal to disease state. Table S8. Gene expression correlation statistics between immune signature genes and four ccRCC master regulator genes involved in opioid immunomodulation (CREB5, IL4R, CLEC2D, PLXNB1).

Figure S1. Top gene ontology pathways enriched for differentially expressed genes in ccRCC.

Figure S4. Individual sample expression across module eigengenes.

Figure S8. Prediction of drug effects on a survival-associated network in bladder cancer (BLCA).

Figure S2. Comparing OPRM1, OPRK1, and OPRD1 gene expression between cases and controls.

Figure S5. Fisher's exact test overrepresentation between TCGA and MSKCC ccRCC networks.