Closing the Chasm: Understanding and Addressing the Anesthesia Workforce Supply and Demand Imbalance.

The imbalance in anesthesia workforce supply and demand has been exacerbated post-COVID due to a surge in demand for anesthesia care, especially in non-operating room anesthetizing sites, at a faster rate than the increase in anesthesia clinicians. The consequences of this imbalance or labor shortage compromise healthcare facilities, adversely affect the cost of care, worsen anesthesia workforce burnout, disrupt procedural and surgical schedules, and threaten academic missions and the ability to educate future anesthesiologists. In developing possible solutions, one must examine emerging trends that are affecting the anesthesia workforce, new technologies that will transform anesthesia care and the workforce, and financial considerations, including governmental payment policies. Possible practice solutions to this imbalance will require both short- and long-term multifactorial approaches that include increasing training positions and retention policies, improving capacity through innovations, leveraging technology, and addressing financial constraints.

Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.

The development of accurate transferable force fields is key to realizing the full potential of atomistic modeling in the study of biological processes such as protein-ligand binding for drug discovery. State-of-the-art transferable force fields, such as those produced by the Open Force Field Initiative, use modern software engineering and automation techniques to yield accuracy improvements. However, force field torsion parameters, which must account for many stereoelectronic and steric effects, are considered to be less transferable than other force field parameters and are therefore often targets for bespoke parametrization. Here, we present the Open Force Field QCSubmit and BespokeFit software packages that, when combined, facilitate the fitting of torsion parameters to quantum mechanical reference data at scale. We demonstrate the use of QCSubmit for simplifying the process of creating and archiving large numbers of quantum chemical calculations, by generating a dataset of 671 torsion scans for druglike fragments. We use BespokeFit to derive individual torsion parameters for each of these molecules, thereby reducing the root-mean-square error in the potential energy surface from 1.1 kcal/mol, using the original transferable force field, to 0.4 kcal/mol using the bespoke version. Furthermore, we employ the bespoke force fields to compute the relative binding free energies of a congeneric series of inhibitors of the TYK2 protein, and demonstrate further improvements in accuracy, compared to the base force field (MUE reduced from 0.560.390.77 to 0.420.280.59 kcal/mol and R2 correlation improved from 0.720.350.87 to 0.930.840.97).

Exploration and validation of force field design protocols through QM-to-MM mapping.

The scale of the parameter optimisation problem in traditional molecular mechanics force field construction means that design of a new force field is a long process, and sub-optimal choices made in the early stages can persist for many generations. We hypothesise that careful use of quantum mechanics to inform molecular mechanics parameter derivation (QM-to-MM mapping) should be used to significantly reduce the number of parameters that require fitting to experiment and increase the pace of force field development. Here, we design and train a collection of 15 new protocols for small, organic molecule force field derivation, and test their accuracy against experimental liquid properties. Our best performing model has only seven fitting parameters, yet achieves mean unsigned errors of just 0.031 g cm-3 and 0.69 kcal mol-1 in liquid densities and heats of vaporisation, compared to experiment. The software required to derive the designed force fields is freely available at https://github.com/qubekit/QUBEKit.

Perioperative Brain Health in the Older Adult: A Patient Safety Imperative.

While people 65 years of age and older represent 16% of the population in the United States, they account for >40% of surgical procedures performed each year. Maintaining brain health after anesthesia and surgery is not only important to our patients, but it is also an increasingly important patient safety imperative for the specialty of anesthesiology. Aging is a complex process that diminishes the reserve of every organ system and often results in a patient who is vulnerable to the stress of surgery. The brain is no exception, and many older patients present with preoperative cognitive impairment that is undiagnosed. As we age, a number of changes occur in the human brain, resulting in a patient who is less resilient to perioperative stress, making older adults more susceptible to the phenotypic expression of perioperative neurocognitive disorders. This review summarizes the current scientific and clinical understanding of perioperative neurocognitive disorders and recommends patient-centered, age-focused interventions that can better mitigate risk, prevent harm, and improve outcomes for our patients. Finally, it discusses the emerging topic of sleep and cognitive health and other future frontiers of scientific inquiry that might inform clinical best practices.

Anesthesia Patient Safety: Next Steps to Improve Worldwide Perioperative Safety by 2030.

Patient safety is a core principle of anesthesia care worldwide. The specialty of anesthesiology has been a leader in medicine for the past half century in pursuing patient safety research and implementing standards of care and systematic improvements in processes of care. Together, these efforts have dramatically reduced patient harm associated with anesthesia. However, improved anesthesia patient safety has not been uniformly obtained worldwide. There are unique differences in patient safety outcomes between countries and regions in the world. These differences are often related to factors such as availability, support, and use of health care resources, trained personnel, patient safety outcome data collection efforts, standards of care, and cultures of safety and teamwork in health care facilities. This article provides insights from national anesthesia society leaders from 13 countries around the world. The countries they represent are diverse geographically and in health care resources. The authors share their countries' current and future initiatives in anesthesia patient safety. Ten major patient safety issues are common to these countries, with several of these focused on the importance of extending initiatives into the full perioperative as well as intraoperative environments. These issues may be used by anesthesia leaders around the globe to direct collaborative efforts to improve the safety of patients undergoing surgery and anesthesia in the coming decade.

Anesthesiologists' Role in Value-based Perioperative Care and Healthcare Transformation.

Health care is undergoing major transformation with a shift from fee-for-service care to fee-for-value. The advent of new care delivery and payment models is serving as a driver for value-based care. Hospitals, payors, and patients increasingly expect physicians and healthcare systems to improve outcomes and manage costs. The impact of the coronavirus disease 2019 (COVID-19) pandemic on surgical and procedural practices further highlights the urgency and need for anesthesiologists to expand their roles in perioperative care, and to impact system improvement. While there have been substantial advances in anesthesia care, perioperative complications and mortality after surgery remain a key concern. Anesthesiologists are in a unique position to impact perioperative health care through their multitude of interactions and influences on various aspects of the perioperative domain, by using the surgical experience as the first touchpoint to reengage the patient in their own health care. Among the key interventions that are being effectively instituted by anesthesiologists include proactive engagement in preoperative optimization of patients' health; personalization and standardization of care delivery by segmenting patients based upon their complexity and risk; and implementation of best practices that are data-driven and evidence-based and provide structure that allow the patient to return to their optimal state of functional, cognitive, and psychologic health. Through collaborative relationships with other perioperative stakeholders, anesthesiologists can consolidate their role as clinical leaders driving value-based care and healthcare transformation in the best interests of patients.

The Evolution, Current Value, and Future of the American Society of Anesthesiologists Physical Status Classification System.

The American Society of Anesthesiologists (ASA) Physical Status classification system celebrates its 80th anniversary in 2021. Its simplicity represents its greatest strength as well as a limitation in a world of comprehensive multisystem tools. It was developed for statistical purposes and not as a surgical risk predictor. However, since it correlates well with multiple outcomes, it is widely used-appropriately or not-for risk prediction and many other purposes. It is timely to review the history and development of the system. The authors describe the controversies surrounding the ASA Physical Status classification, including the problems of interrater reliability and its limitations as a risk predictor. Last, the authors reflect on the current status and potential future of the ASA Physical Status system.

Implementation of the QUBE Force Field in SOMD for High-Throughput Alchemical Free-Energy Calculations.

The quantum mechanical bespoke (QUBE) force-field approach has been developed to facilitate the automated derivation of potential energy function parameters for modeling protein-ligand binding. To date, the approach has been validated in the context of Monte Carlo simulations of protein-ligand complexes. We describe here the implementation of the QUBE force field in the alchemical free-energy calculation molecular dynamics simulation package SOMD. The implementation is validated by demonstrating the reproducibility of absolute hydration free energies computed with the QUBE force field across the SOMD and GROMACS software packages. We further demonstrate, by way of a case study involving two series of non-nucleoside inhibitors of HIV-1 reverse transcriptase, that the availability of QUBE in a modern simulation package that makes efficient use of graphics processing unit acceleration will facilitate high-throughput alchemical free-energy calculations.

A machine learning based intramolecular potential for a flexible organic molecule.

Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time scales and large system sizes required of the computational model. Here, we employ the kernel regression machine learning technique to construct an analytical potential, using the Gaussian Approximation Potential software and framework, that reproduces the quantum mechanical potential energy surface of a small, flexible, drug-like molecule, 3-(benzyloxy)pyridin-2-amine. Challenges linked to the high dimensionality of the configurational space of the molecule are overcome by developing an iterative training protocol and employing a representation that separates short and long range interactions. The analytical model is connected to the MCPRO simulation software, which allows us to perform Monte Carlo simulations of the small molecule bound to two proteins, p38 MAP kinase and leukotriene A4 hydrolase, as well as in water. We demonstrate that our machine learning based intramolecular model is transferable to the condensed phase, and demonstrate that the use of a faithful representation of the quantum mechanical potential energy surface can result in corrections to absolute protein-ligand binding free energies of up to 2 kcal mol-1 in the example studied here.

Bifunctional Hydrogen Bonding of Imidazole with Water Explored by Rotational Spectroscopy and DFT Calculations.

Laser vaporization of imidazole in the presence of an argon buffer gas has allowed the generation and isolation of two isomers of an imidazole monohydrate complex, denoted herein as imid···H2O and H2O···imid, within a gas sample undergoing supersonic expansion. Imidazole and water are respectively proton-accepting and proton-donating in imid···H2O, but these roles are reversed in the H2O···imid complex. Both isomers have been characterized by chirped-pulse Fourier transform microwave spectroscopy between 7.0 and 18.5 GHz. The ground-state rotational spectra of four isotopologues of imid···H2O and three isotopologues of H2O···imid have been measured. All spectra have been assigned and fitted to determine rotational (A0, B0, C0), centrifugal distortion (DJ, DJK), and nuclear quadrupole coupling constants (χaa(N1), [χbb(N1) - χcc(N1)], χaa(N3), and [χbb(N3) - χcc(N3)]). Structural parameters (r0 and rs) have been accurately determined from measured rotational constants for each isomer. The imid···H2O complex contains a nonlinear hydrogen bond (∠(O-Hb···N3) = 172.1(26)° in the experimentally determined, r0 geometry) between the pyridinic nitrogen of imidazole and a hydrogen atom of H2O. The DFT calculations find that the H2O···imid complex also contains a nonlinear hydrogen bond between the oxygen atom of water and the hydrogen attached to the pyrrolic nitrogen of imidazole (∠(O···H1-N1) = 174.7°). Two states observed in the spectrum of H2O···imid, assigned as 0- and 0+ states, confirm that large amplitude motions occur on the time scale of the molecular rotation. Density functional theory has been performed to characterize these large amplitude motions.

First-Year Results of the American Board of Anesthesiology's Objective Structured Clinical Examination for Initial Certification.

In 2018, the American Board of Anesthesiology (ABA) became the first US medical specialty certifying board to incorporate an Objective Structured Clinical Examination (OSCE) into its initial certification examination system. Previously, the ABA's staged examination system consisted of 2 written examinations (the BASIC and ADVANCED examinations) and the Standardized Oral Examination (SOE). The OSCE and the existing SOE are now 2 separate components of the APPLIED Examination. This report presents the results of the first-year OSCE administration. A total of 1410 candidates took both the OSCE and the SOE in 2018. Candidate performance approximated a normal distribution for both the OSCE and the SOE, and was not associated with the timing of the examination, including day of the week, morning versus afternoon session, and order of the OSCE and the SOE. Practice-based Learning and Improvement was the most difficult station, while Application of Ultrasonography was the least difficult. The correlation coefficient between SOE and OSCE scores was 0.35 ([95% confidence interval {CI}, 0.30-0.39]; P < .001). Scores for the written ADVANCED Examination were modestly correlated with scores for the SOE (r = 0.29 [95% CI, 0.25-0.34]; P < .001) and the OSCE (r = 0.15 [95% CI, 0.10-0.20]; P < .001). Most of the candidates who failed the SOE passed the OSCE, and most of the candidates who failed the OSCE passed the SOE. Of the 1410 candidates, 77 (5.5%) failed the OSCE, 155 (11.0%) failed the SOE, and 25 (1.8%) failed both. Thus, 207 (14.7%) failed at least 1 component of the APPLIED Examination. Adding an OSCE to a board certification examination system is feasible. Preliminary evidence indicates that the OSCE measures aspects of candidate abilities distinct from those measured by other examinations used for initial board certification.

Development of an Objective Structured Clinical Examination as a Component of Assessment for Initial Board Certification in Anesthesiology.

With its first administration of an Objective Structured Clinical Examination (OSCE) in 2018, the American Board of Anesthesiology (ABA) became the first US medical specialty certifying board to incorporate this type of assessment into its high-stakes certification examination system. The fundamental rationale for the ABA's introduction of the OSCE is to include an assessment that allows candidates for board certification to demonstrate what they actually "do" in domains relevant to clinical practice. Inherent in this rationale is that the OSCE will capture competencies not well assessed in the current written and oral examinations-competencies that will allow the ABA to judge whether a candidate meets the standards expected for board certification more properly. This special article describes the ABA's journey from initial conceptualization through first administration of the OSCE, including the format of the OSCE, the process for scenario development, the standardized patient program that supports OSCE administration, examiner training, scoring, and future assessment of reliability, validity, and impact of the OSCE. This information will be beneficial to both those involved in the initial certification process, such as residency graduate candidates and program directors, and others contemplating the use of high-stakes summative OSCE assessments.

The ONETEP linear-scaling density functional theory program.

We present an overview of the onetep program for linear-scaling density functional theory (DFT) calculations with large basis set (plane-wave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the density matrix and the NGWFs are optimized with localization constraints. By taking advantage of localization, onetep is able to perform calculations including thousands of atoms with computational effort, which scales linearly with the number or atoms. The code has a large and diverse range of capabilities, explored in this paper, including different boundary conditions, various exchange-correlation functionals (with and without exact exchange), finite electronic temperature methods for metallic systems, methods for strongly correlated systems, molecular dynamics, vibrational calculations, time-dependent DFT, electronic transport, core loss spectroscopy, implicit solvation, quantum mechanical (QM)/molecular mechanical and QM-in-QM embedding, density of states calculations, distributed multipole analysis, and methods for partitioning charges and interactions between fragments. Calculations with onetep provide unique insights into large and complex systems that require an accurate atomic-level description, ranging from biomolecular to chemical, to materials, and to physical problems, as we show with a small selection of illustrative examples. onetep has always aimed to be at the cutting edge of method and software developments, and it serves as a platform for developing new methods of electronic structure simulation. We therefore conclude by describing some of the challenges and directions for its future developments and applications.

QUBEKit: Automating the Derivation of Force Field Parameters from Quantum Mechanics.

Modern molecular mechanics force fields are widely used for modeling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. However, for molecules outside the training set, the parameters are potentially inaccurate and it may be preferable to derive molecule-specific parameters. Here we present an intuitive parameter derivation toolkit, QUBEKit (QUantum mechanical BEspoke Kit), which enables the automated generation of system-specific small molecule force field parameters directly from quantum mechanics. QUBEKit is written in python and combines bond, angle, torsion, charge, and Lennard-Jones parameter derivation methodologies alongside a method for deriving the positions and charges of off-center virtual sites from the partitioned quantum mechanical electron density. As a proof of concept, we have rederived a complete set of parameters for 109 small organic molecules and assessed the accuracy by comparing computed liquid properties with experiments. QUBEKit gives competitive results when compared to standard transferable force fields, with mean unsigned errors of 0.024 g/cm3, 0.79 kcal/mol, and 1.17 kcal/mol for the liquid density, heat of vaporization, and free energy of hydration, respectively. This indicates that the derived parameters are suitable for molecular modeling applications, including computer-aided drug design.

Renormalization of myoglobin-ligand binding energetics by quantum many-body effects.

We carry out a first-principles atomistic study of the electronic mechanisms of ligand binding and discrimination in the myoglobin protein. Electronic correlation effects are taken into account using one of the most advanced methods currently available, namely a linear-scaling density functional theory (DFT) approach wherein the treatment of localized iron 3d electrons is further refined using dynamical mean-field theory. This combination of methods explicitly accounts for dynamical and multireference quantum physics, such as valence and spin fluctuations, of the 3d electrons, while treating a significant proportion of the protein (more than 1,000 atoms) with DFT. The computed electronic structure of the myoglobin complexes and the nature of the Fe-O2 bonding are validated against experimental spectroscopic observables. We elucidate and solve a long-standing problem related to the quantum-mechanical description of the respiration process, namely that DFT calculations predict a strong imbalance between O2 and CO binding, favoring the latter to an unphysically large extent. We show that the explicit inclusion of the many-body effects induced by the Hund's coupling mechanism results in the correct prediction of similar binding energies for oxy- and carbonmonoxymyoglobin.

Molecular dynamics and Monte Carlo simulations for protein-ligand binding and inhibitor design.

BACKGROUND: Non-nucleoside inhibitors of HIV reverse transcriptase are an important component of treatment against HIV infection. Novel inhibitors are sought that increase potency against variants that contain the Tyr181Cys mutation. METHODS: Molecular dynamics based free energy perturbation simulations have been run to study factors that contribute to protein-ligand binding, and the results are compared with those from previous Monte Carlo based simulations and activity data. RESULTS: Predictions of protein-ligand binding modes are very consistent for the two simulation methods; the accord is attributed to the use of an enhanced sampling protocol. The Tyr181Cys binding pocket supports large, hydrophobic substituents, which is in good agreement with experiment. CONCLUSIONS: Although some discrepancies exist between the results of the two simulation methods and experiment, free energy perturbation simulations can be used to rapidly test small molecules for gains in binding affinity. GENERAL SIGNIFICANCE: Free energy perturbation methods show promise in providing fast, reliable and accurate data that can be used to complement experiment in lead optimization projects. This article is part of a Special Issue entitled "Recent developments of molecular dynamics".