Effect of Telemedicine Support for Intraoperative Anaesthesia Care on Postoperative Outcomes: The TECTONICS Randomised Clinical Trial.

Background: Novel applications of telemedicine can improve care quality and patient outcomes. Telemedicine for intraoperative decision support has not been rigorously studied. Methods: This single centre randomised clinical trial ( clinicaltrials.gov NCT03923699 ) of unselected adult surgical patients was conducted between July 1, 2019 and January 31, 2023. Patients received usual care or decision support from a telemedicine service, the Anesthesiology Control Tower (ACT). The ACT provided real-time recommendations to intraoperative anaesthesia clinicians based on case reviews, machine-learning forecasting, and physiologic alerts. ORs were randomised 1:1. Co-primary outcomes of 30-day all-cause mortality, respiratory failure, acute kidney injury (AKI), and delirium were analysed as intention-to-treat. Results: The trial completed planned enrolment with 71927 surgeries (35956 ACT; 35971 usual care). After multiple testing correction, there was no significant effect of the ACT vs. usual care on 30-day mortality [641/35956 (1.8%) vs 638/35971 (1.8%), risk difference 0.0% (95% CI -0.2% to 0.3%), p=0.96], respiratory failure [1089/34613 (3.1%) vs 1112/34619 (3.2%), risk difference -0.1% (95% CI -0.4% to 0.3%), p=0.96], AKI [2357/33897 (7%) vs 2391/33795 (7.1%), risk difference -0.1% (-0.6% to 0.4%), p=0.96], or delirium [1283/3928 (32.7%) vs 1279/3989 (32.1%), risk difference 0.6% (-2.0% to 3.2%), p=0.96]. There were no significant differences in secondary outcomes or in sensitivity analyses. Conclusions: In this large RCT of a novel application of telemedicine-based remote monitoring and decision support using real-time alerts and case reviews, we found no significant differences in postoperative outcomes. Large-scale intraoperative telemedicine is feasible, and we suggest future avenues where it may be impactful.

Effect of Machine Learning on Anaesthesiology Clinician Prediction of Postoperative Complications: The Perioperative ORACLE Randomised Clinical Trial.

BACKGROUND: Anaesthesiology clinicians can implement risk mitigation strategies if they know which patients are at greatest risk for postoperative complications. Although machine learning models predicting complications exist, their impact on clinician risk assessment is unknown. METHODS: This single-centre randomised clinical trial enrolled patients age ≥18 undergoing surgery with anaesthesiology services. Anaesthesiology clinicians providing remote intraoperative telemedicine support reviewed electronic health records with (assisted group) or without (unassisted group) also reviewing machine learning predictions. Clinicians predicted the likelihood of postoperative 30-day all-cause mortality and postoperative acute kidney injury within 7 days. Area under the receiver operating characteristic curve (AUROC) for the clinician predictions was determined. RESULTS: Among 5,071 patient cases reviewed by 89 clinicians, the observed incidence was 2% for postoperative death and 11% for acute kidney injury. Clinician predictions agreed with the models more strongly in the assisted versus unassisted group (weighted kappa 0.75 versus 0.62 for death [difference 0.13, 95%CI 0.10-0.17] and 0.79 versus 0.54 for kidney injury [difference 0.25, 95%CI 0.21-0.29]). Clinicians predicted death with AUROC of 0.793 in the assisted group and 0.780 in the unassisted group (difference 0.013, 95%CI -0.070 to 0.097). Clinicians predicted kidney injury with AUROC of 0.734 in the assisted group and 0.688 in the unassisted group (difference 0.046, 95%CI -0.003 to 0.091). CONCLUSIONS: Although there was evidence that the models influenced clinician predictions, clinician performance was not statistically significantly different with and without machine learning assistance. Further work is needed to clarify the role of machine learning in real-time perioperative risk stratification. TRIAL REGISTRATION: ClinicalTrials.gov NCT05042804.

An Intraoperative Telemedicine Program to Improve Perioperative Quality Measures: The ACTFAST-3 Randomized Clinical Trial.

Importance: Telemedicine for clinical decision support has been adopted in many health care settings, but its utility in improving intraoperative care has not been assessed. Objective: To pilot the implementation of a real-time intraoperative telemedicine decision support program and evaluate whether it reduces postoperative hypothermia and hyperglycemia as well as other quality of care measures. Design, Setting, and Participants: This single-center pilot randomized clinical trial (Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments [ACTFAST-3]) was conducted from April 3, 2017, to June 30, 2019, at a large academic medical center in the US. A total of 26 254 adult surgical patients were randomized to receive either usual intraoperative care (control group; n = 12 980) or usual care augmented by telemedicine decision support (intervention group; n = 13 274). Data were initially analyzed from April 22 to May 19, 2021, with updates in November 2022 and February 2023. Intervention: Patients received either usual care (medical direction from the anesthesia care team) or intraoperative anesthesia care monitored and augmented by decision support from the Anesthesiology Control Tower (ACT), a real-time, live telemedicine intervention. The ACT incorporated remote monitoring of operating rooms by a team of anesthesia clinicians with customized analysis software. The ACT reviewed alerts and electronic health record data to inform recommendations to operating room clinicians. Main Outcomes and Measures: The primary outcomes were avoidance of postoperative hypothermia (defined as the proportion of patients with a final recorded intraoperative core temperature >36 °C) and hyperglycemia (defined as the proportion of patients with diabetes who had a blood glucose level ≤180 mg/dL on arrival to the postanesthesia recovery area). Secondary outcomes included intraoperative hypotension, temperature monitoring, timely antibiotic redosing, intraoperative glucose evaluation and management, neuromuscular blockade documentation, ventilator management, and volatile anesthetic overuse. Results: Among 26 254 participants, 13 393 (51.0%) were female and 20 169 (76.8%) were White, with a median (IQR) age of 60 (47-69) years. There was no treatment effect on avoidance of hyperglycemia (7445 of 8676 patients [85.8%] in the intervention group vs 7559 of 8815 [85.8%] in the control group; rate ratio [RR], 1.00; 95% CI, 0.99-1.01) or hypothermia (7602 of 11 447 patients [66.4%] in the intervention group vs 7783 of 11 672 [66.7.%] in the control group; RR, 1.00; 95% CI, 0.97-1.02). Intraoperative glucose measurement was more common among patients with diabetes in the intervention group (RR, 1.07; 95% CI, 1.01-1.15), but other secondary outcomes were not significantly different. Conclusions and Relevance: In this randomized clinical trial, anesthesia care quality measures did not differ between groups, with high confidence in the findings. These results suggest that the intervention did not affect the targeted care practices. Further streamlining of clinical decision support and workflows may help the intraoperative telemedicine program achieve improvement in targeted clinical measures. Trial Registration: ClinicalTrials.gov Identifier: NCT02830126.

Telemedicine Critical Care-Mediated Mortality Reductions in Lower-Performing Patient Diagnosis Groups: A Prospective, Before and After Study.

OBJECTIVES: Studies evaluating telemedicine critical care (TCC) have shown mixed results. We prospectively evaluated the impact of TCC implementation on risk-adjusted mortality among patients stratified by pre-TCC performance. DESIGN: Prospective, observational, before and after study. SETTING: Three adult ICUs at an academic medical center. PATIENTS: A total of 2,429 patients in the pre-TCC (January to June 2016) and 12,479 patients in the post-TCC (January 2017 to June 2019) periods. INTERVENTIONS: TCC implementation which included an acuity-driven workflow targeting an identified "lower-performing" patient group, defined by ICU admission in an Acute Physiology and Chronic Health Evaluation diagnoses category with a pre-TCC standardized mortality ratio (SMR) of greater than 1.5. MEASUREMENTS AND MAIN RESULTS: The primary outcome was risk-adjusted hospital mortality. Risk-adjusted hospital length of stay (HLOS) was also studied. The SMR for the overall ICU population was 0.83 pre-TCC and 0.75 post-TCC, with risk-adjusted mortalities of 10.7% and 9.5% (p = 0.09). In the identified lower-performing patient group, which accounted for 12.6% (n = 307) of pre-TCC and 13.3% (n = 1671) of post-TCC ICU patients, SMR decreased from 1.61 (95% CI, 1.21-2.01) pre-TCC to 1.03 (95% CI, 0.91-1.15) post-TCC, and risk-adjusted mortality decreased from 26.4% to 16.9% (p < 0.001). In the remaining ("higher-performing") patient group, there was no change in pre- versus post-TCC SMR (0.70 [0.59-0.81] vs 0.69 [0.64-0.73]) or risk-adjusted mortality (8.5% vs 8.4%, p = 0.86). There were no pre- to post-TCC differences in standardized HLOS ratio or risk-adjusted HLOS in the overall cohort or either performance group. CONCLUSIONS: In well-staffed and overall higher-performing ICUs in an academic medical center, Acute Physiology and Chronic Health Evaluation granularity allowed identification of a historically lower-performing patient group that experienced a striking TCC-associated reduction in SMR and risk-adjusted mortality. This study provides additional evidence for the relationship between pre-TCC performance and post-TCC improvement.

Macrocyclisation of small peptides enabled by oxetane incorporation.

Cyclic peptides are an important source of new drugs but are challenging to produce synthetically. We show that head-to-tail peptide macrocyclisations are greatly improved, as measured by isolated yields, reaction rates and product distribution, by substitution of one of the backbone amide C[double bond, length as m-dash]O bonds with an oxetane ring. The cyclisation precursors are easily made by standard solution- or solid-phase peptide synthesis techniques. Macrocyclisations across a range of challenging ring sizes (tetra-, penta- and hexapeptides) are enabled by incorporation of this turn-inducing element. Oxetane incorporation is shown to be superior to other established amino acid modifications such as N-methylation. The positional dependence of the modification on cyclisation efficiency is mapped using a cyclic peptide of sequence LAGAY. We provide the first direct experimental evidence that oxetane modification induces a turn in linear peptide backbones, through the observation of d NN (i, i + 2) and d αN (i, i + 2) NOEs, which offers an explanation for these improvements. For cyclic peptide, cLAGAY, a combination of NMR derived distance restraints and molecular dynamics simulations are used to show that this modification alters the backbone conformation in proximity to the oxetane, with the flexibility of the ring reduced and a new intramolecular H-bond established. Finally, we incorporated an oxetane into a cyclic pentapeptide inhibitor of Aminopeptidase N, a transmembrane metalloprotease overexpressed on the surface of cancer cells. The inhibitor, cCNGRC, displayed similar IC50 values in the presence or absence of an oxetane at the glycine residue, indicating that bioactivity is fully retained upon amide C[double bond, length as m-dash]O bond replacement.

Inter-Rater Reliability and Impact of Disagreements on Acute Physiology and Chronic Health Evaluation IV Mortality Predictions.

Acute Physiology and Chronic Health Evaluation is a well-validated method to risk-adjust ICU patient outcomes. However, predictions may be affected by inter-rater reliability for manually entered elements. We evaluated inter-rater reliability for Acute Physiology and Chronic Health Evaluation IV manually entered elements among clinician abstractors and assessed the impacts of disagreements on mortality predictions. DESIGN: Cross-sectional. SETTING: Academic medical center. SUBJECTS: Patients admitted to five adult ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Acute Physiology and Chronic Health Evaluation IV manually entered elements were abstracted from a selection of charts (n = 41) by two clinician "raters" trained in Acute Physiology and Chronic Health Evaluation IV methodology. Rater agreement (%) was determined for each manually entered element, including Acute Physiology and Chronic Health Evaluation diagnosis, Glasgow Coma Scale score, admission source, chronic conditions, elective/emergency surgery, and ventilator use. Cohen's kappa (K) or intraclass correlation coefficient was calculated for nominal and continuous manually entered elements, respectively. The impacts of manually entered element choices on Acute Physiology and Chronic Health Evaluation IV mortality predictions were computed using published Acute Physiology and Chronic Health Evaluation IV equations, and observed to expected hospital mortality ratios were compared between rater groups. The majority of manually entered element inconsistency was due to disagreement in choice of Glasgow Coma Scale (63.8% agreement, 0.83 intraclass correlation coefficient), Acute Physiology and Chronic Health Evaluation diagnosis (68.3% agreement, 0.67 kappa), and admission source (90.2% agreement, 0.85 kappa). The difference in predicted mortality between raters related to Glasgow Coma Scale disagreements was significant (observed to expected mortality ratios for Rater 1 [1.009] vs Rater 2 [1.134]; p < 0.05). Differences related to Acute Physiology and Chronic Health Evaluation diagnosis or admission source disagreements were negligible. The new "unable to score" choice for Glasgow Coma Scale was used for 18% of Glasgow Coma Scale measurements but accounted for 63% of "major" Glasgow Coma Scale disagreements, and 50% of the overall difference in Acute Physiology and Chronic Health Evaluation-predicted mortality between raters. CONCLUSIONS: Inconsistent use among raters of the new "unable to score" choice for Glasgow Coma Scale introduced in Acute Physiology and Chronic Health Evaluation IV was responsible for important decreases in both Glasgow Coma Scale and Acute Physiology and Chronic Health Evaluation IV mortality prediction reliability in our study. A Glasgow Coma Scale algorithm we developed after the study to improve reliability related to use of this new "unable to score" choice is presented.

Decision-making skills improve with critical care training: Using simulation to measure progress.

PURPOSE: Health care professionals are expected to acquire decision-making skills during their training, but few methods are available to assess progress in acquiring these essential skills. The purpose of this study was to determine whether a simulation methodology could be used to assess whether decision-making skills improve during critical care training. MATERIALS AND METHODS: Sixteen simulated scenarios were designed to assess a critical care provider's ability to make decisions in the care of a critical ill patient. Seventeen (17) critical care providers managed 8 of the scenarios early during their training and then managed a second set of 8 scenarios (T2) at the conclusion of their training. RESULTS: Provider's mean global scenario scores (0-9) increased significantly fromT1 and T2 (5.64 ±â€¯0.74) and (6.54 ±â€¯0.64) with a large effect size (1.3). Acute care nurse practitioners and fellows achieved similar overall scores at the conclusion of their training (ACNP 6.43 ±â€¯0.57; Fellows 6.64 ±â€¯0.72). CONCLUSIONS: These findings provide evidence to support the validity of a simulation-based method to assess progress in decision-making skills. A simulation methodology could be used to establish a performance standard that determined a provider's ability to make independent decisions.

Simulation-Based Assessment of Critical Care "Front-Line" Providers.

OBJECTIVES: Develop a standardized simulation method to assess clinical skills of ICU providers. DESIGN: Simulation assessment. SETTING: Simulation laboratory. SUBJECTS: Residents, Critical Care Medicine fellows, acute care nurse practitioner students. INTERVENTIONS: Performance scoring in scenarios from multiple Critical Care Medicine competency domains. MEASUREMENTS AND MAIN RESULTS: Three-hundred eighty-four performances by 48 participants were scored using checklists (% correct) and holistic "global" ratings (1 [unprepared] to 9 [expert]). One-hundred eighty were scored by two raters. Mean checklist and global scores (± SD) ranged from 65.0% (± 16.3%) to 84.5% (± 17.3%) and 4.7 (± 1.4) to 7.2 (± 1.2). Checklist and global scores for Critical Care Medicine fellows and senior acute care nurse practitioner students (Experienced group, n = 26) were significantly higher than those for the Novice acute care nurse practitioner students (Novice group, n = 14) (75.6% ± 15.6% vs 68.8% ± 21.0% and 6.1 ± 1.6 vs 5.4 ± 1.5, respectively; p < 0.05). Residents (Intermediate group, n = 8) scored between the two (75.4% ± 18.3% and 5.7 ± 1.7). 38.5% of the Experienced group scored in the top quartile for mean global score, compared with 12.5% of the Intermediate and 7.1% of the Novice groups. Conversely, 50% of the Novice group scored in the lower quartile (< 5.3), compared with 37.5% of the Intermediate and 11.5% of the Experienced groups. Psychometric analyses yielded discrimination values greater than 0.3 for most scenarios and reliability for the eight-scenario assessments of 0.51 and 0.60, with interrater reliability of 0.71 and 0.75, for checklist and global scoring, respectively. CONCLUSIONS: The simulation assessments yielded reasonably reliable measures of Critical Care Medicine decision-making skills. Despite a wide range of performance, those with more ICU training and experience performed better, providing evidence to support the validity of the scores. Simulation-based assessments may ultimately prove useful to determine readiness to assume decision-making roles in the ICU.

NMR-based assignment of isoleucine vs. allo-isoleucine stereochemistry.

A simple 1H and 13C NMR spectrometric analysis is demonstrated that permits differentiation of isoleucine and allo-isoleucine residues by inspection of the chemical shift and coupling constants of the signals associated with the proton and carbon at the α-stereocentre. This is applied to the estimation of epimerisation during metal-free N-arylation and peptide coupling reactions.

Advances in the management of sepsis and the understanding of key immunologic defects.

Anesthesiologists are increasingly confronting the difficult problem of caring for patients with sepsis in the operating room and in the intensive care unit. Sepsis occurs in more than 750,000 patients in the United States annually and is responsible for more than 210,000 deaths. Approximately 40% of all intensive care unit patients have sepsis on admission to the intensive care unit or experience sepsis during their stay in the intensive care unit. There have been significant advances in the understanding of the pathophysiology of the disorder and its treatment. Although deaths attributable to sepsis remain stubbornly high, new treatment algorithms have led to a reduction in overall mortality. Thus, it is important for anesthesiologists and critical care practitioners to be aware of these new therapeutic regimens. The goal of this review is to include practical points on important advances in the treatment of sepsis and provide a vision of future immunotherapeutic approaches.