Optimal Medical Therapy and Outcomes Among Patients With Chronic Heart Failure With Reduced Ejection Fraction.

BACKGROUND: Optimal medical therapy (OMT) scoring may stratify clinical risk in real-world chronic heart failure with reduced ejection fraction (HFrEF) by integrating use and dosing of guideline-directed medical therapy (GDMT) for HFrEF. OBJECTIVES: The purpose of this study was to characterize patients and associated long-term clinical outcomes by OMT score-derived treatment groups. METHODS: CHAMP-HF (Change the Management of Patients with Heart Failure) included U.S. outpatients with chronic HFrEF receiving ≥1 GDMT. OMT subgroups were defined as suboptimal (score <3), acceptable (score = 3), and optimal (score ≥4) by baseline use and dose of GDMT, as proposed by the HF Collaboratory consortium. Cox proportional hazard analyses were used to assess for all-cause and cardiovascular death across subgroups, after adjusting for demographic and clinical covariates. RESULTS: The authors studied 4,582 participants enrolled in CHAMP-HF with available 2-year follow-up. Median age was 68 years, 1,327 (29%) were women, and 2,842 (62%) were White, non-Hispanic. Median OMT score across the population was 4 (Q1-Q3: 2-5), and 1,628 (35%) had suboptimal, 665 (14%) had acceptable, and 2,289 (50%) had optimal therapy. Participants with optimal treatment were younger, had higher annual household income, and were enrolled from practices with dedicated HF clinics (all P < 0.001) than participants with acceptable or suboptimal treatment. Participants with optimal treatment had lower all-cause death (adjusted HR: 0.77; 95% CI: 0.64-0.92) and cardiovascular death (adjusted HR: 0.79; 95% CI: 0.65-0.96) than those with suboptimal treatment. CONCLUSIONS: Across a large cohort of chronic ambulatory HFrEF, OMT scores stratified risk of all-cause and cardiovascular death.

Heart Failure Drug Development Over the Eras: From the Heart Failure Collaboratory.

Over the past decade, the field of heart failure (HF) has witnessed remarkable progress in drug development, resulting in the approval of numerous groundbreaking drugs by the U.S. Food and Drug Administration. To address some of these challenges, the U.S. Food and Drug Administration has issued guidance documents that have been critical in contemporary HF drug development; however, there are still many challenges in need of investigation. This article leverages efforts of the Heart Failure Collaboratory and the scientific community to discuss the critical need for innovative trial designs, important concepts in clinical trials in the modern era, and the utilization of big data to accelerate HF drug development. At this inflection point in HF drug development, it is imperative that, as a global scientific community, we foster increased collaboration among researchers, clinicians, patients, and regulatory bodies. Only through such unified efforts can we navigate the complexities of HF, accelerate the development process, and ultimately deliver effective therapies that transform patient outcomes.

Biomarker profiles associated with reverse ventricular remodelling in patients with heart failure and a reduced ejection fraction: Insights from the echocardiographic substudy of the VICTORIA trial.

AIMS: Reverse ventricular remodelling, defined as a decrease in left ventricular end-systolic volume indexed to body surface area (LVESVI) or an increase in left ventricular ejection fraction (LVEF), is associated with improved clinical outcomes in patients with heart failure with reduced ejection fraction (HFrEF). However, the underlying pathophysiological mechanisms remain unclear. METHODS AND RESULTS: We evaluated paired core-lab assessed echocardiograms and measurements of 92 biomarkers at baseline and 8 months thereafter in 419 participants with HFrEF. Reverse ventricular remodelling was defined as a >5% LVEF increase or >15% LVESVI relative decrease between baseline and 8 months. We evaluated the association between baseline biomarkers and their changes with reverse ventricular remodelling in the prospectively randomized controlled VICTORIA (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction) trial. Of 419 patients (median age 66 [interquartile range 57-74] years, 27.4% women), 206 (49.2%) had reverse ventricular remodelling (either a 5% LVEF increase or a 15% LVESVI decrease). There were no differences in baseline biomarker concentrations between patients with versus those without reverse ventricular remodelling on follow-up. However, in patients with reverse ventricular remodelling there were significant decreases in biomarkers relating to inflammation and cardiac metabolism; particularly the tumour necrosis factor superfamily member 13B (ratio 0.82, 95% confidence interval [CI] 0.77-0.88), growth differentiation factor-15 (ratio 0.74, 95% CI 0.66-0.84), and insulin-like growth factor binding protein 7 (ratio 0.80, 95% CI 0.73-0.88). CONCLUSIONS: Reverse ventricular remodelling in patients with HFrEF is associated with a decrease of biomarkers related to inflammation and cardiac metabolism.

"Alexa, Cycle The Blood Pressure": A Voice Control Interface Method for Anesthesia Monitoring.

BACKGROUND: Anesthesia monitors and devices are usually controlled with some combination of dials, keypads, a keyboard, or a touch screen. Thus, anesthesiologists can operate their monitors only when they are physically close to them, and not otherwise task-loaded with sterile procedures such as line or block placement. Voice recognition technology has become commonplace and may offer advantages in anesthesia practice such as reducing surface contamination rates and allowing anesthesiologists to effect changes in monitoring and therapy when they would otherwise presently be unable to do so. We hypothesized that this technology is practicable and that anesthesiologists would consider it useful. METHODS: A novel voice-driven prototype controller was designed for the GE Solar 8000M anesthesia patient monitor. The apparatus was implemented using a Raspberry Pi 4 single-board computer, an external conference audio device, a Google Cloud Speech-to-Text platform, and a modified Solar controller to effect commands. Fifty anesthesia providers tested the prototype. Evaluations and surveys were completed in a nonclinical environment to avoid any ethical or safety concerns regarding the use of the device in direct patient care. All anesthesiologists sampled were fluent English speakers; many with inflections from their first language or national origin, reflecting diversity in the population of practicing anesthesiologists. RESULTS: The prototype was uniformly well-received by anesthesiologists. Ease-of-use, usefulness, and effectiveness were assessed on a Likert scale with means of 9.96, 7.22, and 8.48 of 10, respectively. No population cofactors were associated with these results. Advancing level of training (eg, nonattending versus attending) was not correlated with any preference. Accent of country or region was not correlated with any preference. Vocal pitch register did not correlate with any preference. Statistical analyses were performed with analysis of variance and the unpaired t -test. CONCLUSIONS: The use of voice recognition to control operating room monitors was well-received anesthesia providers. Additional commands are easily implemented on the prototype controller. No adverse relationship was found between acceptability and level of anesthesia experience, pitch of voice, or presence of accent. Voice recognition is a promising method of controlling anesthesia monitors and devices that could potentially increase usability and situational awareness in circumstances where the anesthesiologist is otherwise out-of-position or task-loaded.

Novel Initiative Increasing GDMT Use Among Patients With Heart Failure With Reduced Ejection Fraction.

Guideline-directed medical therapy utilization in patients with heart failure with reduced ejection fraction (HFrEF) remains low despite benefits in morbidity and mortality. The authors describe a unique quality improvement initiative designed to increase angiotensin receptor-neprilysin inhibitor (ARNI) and mineralocorticoid receptor antagonist (MRA) utilization in outpatients with HFrEF in a large cardiology practice, whereby eligible patients were identified in a standardized review process and medication utilization rates were linked to group quality metrics. Eligible HFrEF patients were defined as having a left ventricular ejection fraction (LVEF) ≤40% and NYHA functional class II to IV level of symptoms. Those with an LVEF >40%, no documented LVEF, or with NYHA functional class I symptoms were excluded. ARNI utilization was defined as any dose of sacubitril/valsartan prescribed, and MRA utilization was defined as any dose of either spironolactone or eplerenone prescribed. Group quality metric targets were set at >25% ARNI prescription and >60% MRA prescription in eligible patients. Following project implementation, ARNI utilization rose from 31% to 67% and MRA increased from 28% to 66%. Establishing clear quality metrics and formulating a proactive evaluation process was associated with a significant increase in prescription rates.

Deconvoluting the Individual Effects of Nanoparticle Proximity and Size in Thermocatalysis.

Nanoparticle (NP) size and proximity are two physical descriptors applicable to practically all NP-supported catalysts. However, with conventional catalyst design, independent variation of these descriptors to investigate their individual effects on thermocatalysis remains challenging. Using a raspberry-colloid-templating approach, we synthesized a well-defined catalyst series comprising Pd12Au88 alloy NPs of three distinct sizes and at two different interparticle distances. We show that NP size and interparticle distance independently control activity and selectivity, respectively, in the hydrogenation of benzaldehyde to benzyl alcohol and toluene. Surface-sensitive spectroscopic analysis indicates that the surfaces of smaller NPs expose a greater fraction of reactive Pd dimers, compared to inactive Pd single atoms, thereby increasing intrinsic catalytic activity. Computational simulations reveal how a larger interparticle distance improves catalytic selectivity by diminishing the local benzyl alcohol concentration profile between NPs, thus suppressing its readsorption and consequently, undesired formation of toluene. Accordingly, benzyl alcohol yield is maximized using catalysts with smaller NPs separated by larger interparticle distances, overcoming activity-selectivity trade-offs. This work exemplifies the high suitability of the modular raspberry-colloid-templating method as a model catalyst platform to isolate individual descriptors and establish clear structure-property relationships, thereby bridging the materials gap between surface science and technical catalysts.

Evaluation of the Hemocompatibility of the Direct Oral Anticoagulant Apixaban in Left Ventricular Assist Devices: The DOAC LVAD Study.

BACKGROUND: Patients receiving left ventricular assist device (LVAD) support require long-term anticoagulation to reduce the risk of thromboembolic complications. Apixaban is a direct oral anticoagulant that has become first-line therapy; however, its safety in LVAD recipients has not been well described. OBJECTIVES: This study sought to investigate whether, in patients with a fully magnetically levitated LVAD, treatment with apixaban would be feasible and comparable with respect to safety and freedom from the primary composite outcome of death or major hemocompatibility-related adverse events (HRAEs) (stroke, device thrombosis, major bleeding, aortic root thrombus, and arterial non-central nervous system thromboembolism) as compared with treatment with warfarin. METHODS: The DOAC LVAD (Evaluation of the Hemocompatibility of the Direct Oral Anti-Coagulant Apixaban in Left Ventricular Assist Devices) trial was a phase 2, open label trial of LVAD recipients randomized 1:1 to either apixaban 5 mg twice daily or warfarin therapy. All patients were required to take low-dose aspirin. Patients were followed up for 24 weeks to evaluate the primary composite outcome. RESULTS: A total of 30 patients were randomized: 14 patients to warfarin and 16 patients to apixaban. The median patient age was 60 years (Q1-Q3: 52-71 years), and 47% were Black patients. The median time from LVAD implantation to randomization was 115 days (Q1-Q3: 56-859 days). At 24 weeks, the primary composite outcome occurred in no patients receiving apixaban and in 2 patients (14%) receiving warfarin (P = 0.12); these 2 patients experienced major bleeding from gastrointestinal sources. CONCLUSIONS: Anticoagulation with apixaban was feasible in patients with an LVAD without an excess of HRAEs or deaths. This study informs future pivotal clinical trials evaluating the safety and efficacy of apixaban in LVAD recipients. (Evaluation of the Hemocompatibility of the Direct Oral Anti-Coagulant Apixaban in Left Ventricular Assist Devices [DOAC LVAD]; NCT04865978).

Iterative Bragg peak removal on X-ray absorption spectra with automatic intensity correction.

This study introduces a novel iterative Bragg peak removal with automatic intensity correction (IBR-AIC) methodology for X-ray absorption spectroscopy (XAS), specifically addressing the challenge of Bragg peak interference in the analysis of crystalline materials. The approach integrates experimental adjustments and sophisticated post-processing, including an iterative algorithm for robust calculation of the scaling factor of the absorption coefficients and efficient elimination of the Bragg peaks, a common obstacle in accurately interpreting XAS data, particularly in crystalline samples. The method was thoroughly evaluated on dilute catalysts and thin films, with fluorescence mode and large-angle rotation. The results underscore the technique's effectiveness, adaptability and substantial potential in improving the precision of XAS data analysis. While demonstrating significant promise, the method does have limitations related to signal-to-noise ratio sensitivity and the necessity for meticulous angle selection during experimentation. Overall, IBR-AIC represents a significant advancement in XAS, offering a pragmatic solution to Bragg peak contamination challenges, thereby expanding the applications of XAS in understanding complex materials under diverse experimental conditions.

Utilizing Quality of Life Adjusted Days Alive and Out of Hospital in Heart Failure Clinical Trials.

BACKGROUND: In heart failure (HF) trials, there has been an emphasis on utilizing more patient-centered outcomes, including quality of life (QoL) and days alive and out of hospital. We aimed to explore the impact of QoL adjusted days alive and out of hospital as an outcome in 2 HF clinical trials. METHODS: Using data from 2 trials in HF (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure [GUIDE-IT] and Study of Dietary Intervention under 100 mmol in Heart Failure [SODIUM-HF]), we determined treatment differences using percentage days alive and out of hospital (%DAOH) adjusted for QoL at 18 months as the primary outcome. For each participant, %DAOH was calculated as a ratio between days alive and out of hospital/total follow-up. Using a regression model, %DAOH was subsequently adjusted for QoL measured by the Kansas City Cardiomyopathy Questionnaire Overall Summary Score. RESULTS: In the GUIDE-IT trial, 847 participants had a median baseline Kansas City Cardiomyopathy Questionnaire Overall Summary Score of 59.0 (interquartile range, 40.8-74.3), which did not change over 18 months. %DAOH was 90.76%±22.09% in the biomarker-guided arm and 88.56%±25.27% in the usual care arm. No significant difference in QoL adjusted %DAOH was observed (1.09% [95% CI, -1.57% to 3.97%]). In the SODIUM-HF trial, 796 participants had a median baseline Kansas City Cardiomyopathy Questionnaire Overall Summary Score of 69.8 (interquartile range, 49.3-84.3), which did not change over 18 months. %DAOH was 95.69%±16.31% in the low-sodium arm and 95.95%±14.76% in the usual care arm. No significant difference was observed (1.91% [95% CI, -0.85% to 4.77%]). CONCLUSIONS: In 2 large HF clinical trials, adjusting %DAOH for QoL was feasible and may provide complementary information on treatment effects in clinical trials.

Training the Next Generation of Data Monitoring Committee Members: An Initiative of the Heart Failure Collaboratory.

Clinical trials are vital for assessing therapeutic interventions. The associated data monitoring committees (DMCs) safeguard patient interests and enhance trial integrity, thus promoting timely, reliable evaluations of those interventions. We face an urgent need to recruit and train new DMC members. The HFC (Heart Failure Collaboratory), a multidisciplinary public-private consortium of academics, trialists, patients, industry representatives, and government agencies, is working to improve the clinical trial ecosystem. The HFC aims to improve clinical trial efficiency and quality by standardizing concepts, and to help meet the demand for experienced individuals on DMCs by creating a standardized approach to training new members. This paper discusses the HFC's training workshop, and an apprenticeship model for new DMC members. It describes opportunities and challenges DMCs face, along with common myths and best practices learned through previous experiences, with an emphasis on data confidentiality and need for quality independent statistical reporting groups.

Clinical Trial Inclusion and Impact on Early Adoption of Medical Innovation in Diverse Populations.

BACKGROUND: Inadequate inclusion in clinical trial enrollment may contribute to health inequities by evaluating interventions in cohorts that do not fully represent target populations. OBJECTIVES: The aim of this study was to determine if characteristics of patients with heart failure (HF) enrolled in a pivotal trial are associated with who receives an intervention after approval. METHODS: Demographics from 2,017,107 Medicare patients hospitalized for HF were compared with those of the first 10,631 Medicare beneficiaries who received implantable pulmonary artery pressure sensors. Characteristics of the population studied in the pivotal CHAMPION (CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients) clinical trial (n = 550) were compared with those of both groups. All demographic data were analyzed nationally and in 4 U.S. regions. RESULTS: The Medicare HF cohort included 80.9% White, 13.3% African American, 1.9% Hispanic, 1.3% Asian, and 51.5% female patients. Medicare patients <65 years of age were more likely to be African American (33%) and male (58%), whereas older patients were mostly White (84%) and female (53%). Forty-one percent of U.S. HF hospitalizations occurred in the South; demographic characteristics varied significantly across all U.S. regions. The CHAMPION trial adequately represented African Americans (23% overall, 35% <65 years of age), Hispanic Americans (2%), and Asian Americans (1%) but underrepresented women (27%). The trial's population characteristics were similar to those of the first patients who received pulmonary artery sensors (82% White, 13% African American, 1% Asian, 1% Hispanic, and 29% female). CONCLUSIONS: Demographics of Centers for Medicare and Medicaid Services beneficiaries hospitalized with HF vary regionally and by age, which should be considered when defining "adequate" representation in clinical studies. Enrollment diversity in clinical trials may affect who receives early application of recently approved innovations.

Diuretic use and outcomes in patients with heart failure with reduced ejection fraction: Insights from the VICTORIA trial.

AIMS: In VICTORIA, vericiguat compared with placebo reduced the risk of cardiovascular death (CVD) and heart failure hospitalization (HFH) in patients enrolled after a worsening heart failure (WHF) event. We examined clinical outcomes and efficacy of vericiguat as it relates to background use of loop diuretics in patients with WHF. METHODS AND RESULTS: We calculated the total daily loop diuretic dose equivalent to furosemide dosing at randomization and categorized these as: no loop diuretic, 1-39, 41-80, 40, and >80 mg total daily dose (TDD). The primary composite outcome of CVD/HFH and its components were evaluated based on TDD loop diuretic and expressed as adjusted hazard ratios with 95% confidence intervals. Post-randomization rates of change in TDD were also examined. Of 4974 patients (98% of the trial) with diuretic dose information available at randomization, 540 (10.8%) were on no loop diuretic, 647 (13.0%) were on 1-39, 1633 (32.8%) were on 40, 1185 (23.8%) were on 41-80, and 969 (19.4%) were on >80 mg TDD. Patients with higher TDD had a higher rate of primary and secondary clinical outcomes. There were no significant interactions with TDD at randomization and efficacy of vericiguat versus placebo for any outcome (all pinteraction > 0.5). Post-randomization diuretic dose changes for vericiguat and placebo showed similar rates of up-titration (19.6 and 20.2/100 person-years), down-titration (16.8 and 18.1/100 person-years), and stopping diuretics (22.9 and 24.2/100 person-years). CONCLUSIONS: Loop diuretic TDD at randomization was independently associated with worse outcomes in this high-risk population. The efficacy of vericiguat was consistent across the range of diuretic doses.

See Elegans: Simple-to-use, accurate, and automatic 3D detection of neural activity from densely packed neurons.

In the emerging field of whole-brain imaging at single-cell resolution, which represents one of the new frontiers to investigate the link between brain activity and behavior, the nematode Caenorhabditis elegans offers one of the most characterized models for systems neuroscience. Whole-brain recordings consist of 3D time series of volumes that need to be processed to obtain neuronal traces. Current solutions for this task are either computationally demanding or limited to specific acquisition setups. Here, we propose See Elegans, a direct programming algorithm that combines different techniques for automatic neuron segmentation and tracking without the need for the RFP channel, and we compare it with other available algorithms. While outperforming them in most cases, our solution offers a novel method to guide the identification of a subset of head neurons based on position and activity. The built-in interface allows the user to follow and manually curate each of the processing steps. See Elegans is thus a simple-to-use interface aimed at speeding up the post-processing of volumetric calcium imaging recordings while maintaining a high level of accuracy and low computational demands. (Contact: enrico.lanza@iit.it).

Interrogating site dependent kinetics over SiO2-supported Pt nanoparticles.

A detailed knowledge of reaction kinetics is key to the development of new more efficient heterogeneous catalytic processes. However, the ability to resolve site dependent kinetics has been largely limited to surface science experiments on model systems. Herein, we can bypass the pressure, materials, and temperature gaps, resolving and quantifying two distinct pathways for CO oxidation over SiO2-supported 2 nm Pt nanoparticles using transient pressure pulse experiments. We find that the pathway distribution directly correlates with the distribution of well-coordinated (e.g., terrace) and under-coordinated (e.g., edge, vertex) CO adsorption sites on the 2 nm Pt nanoparticles as measured by in situ DRIFTS. We conclude that well-coordinated sites follow classic Langmuir-Hinshelwood kinetics, but under-coordinated sites follow non-standard kinetics with CO oxidation being barrierless but conversely also slow. This fundamental method of kinetic site deconvolution is broadly applicable to other catalytic systems, affording bridging of the complexity gap in heterogeneous catalysis.

Recurrent Hospitalizations and Response to Vericiguat in Heart Failure and Reduced Ejection Fraction.

BACKGROUND: In VICTORIA (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction), vericiguat compared with placebo reduced cardiovascular death or heart failure (HF) hospitalization in patients with HF with reduced ejection fraction. OBJECTIVES: This study explored the association between vericiguat and recurrent hospitalizations and subsequent mortality after HF hospitalization. METHODS: The treatment effect of vericiguat on the burden of HF hospitalizations was evaluated by assessing total HF hospitalization and cardiovascular death in the overall trial and based on baseline N-terminal pro-B-type natriuretic peptide levels with and without adjustment for VICTORIA model covariates (ie, baseline variables associated with the primary endpoint) assessed via the Andersen-Gill method. Associations between vericiguat and recurrent hospitalization and mortality adjusted for VICTORIA model covariates are reported. RESULTS: There were 1,222 total HF hospitalizations and cardiovascular deaths among 2,526 patients in the vericiguat group and 1,336 total events among 2,524 patients in the placebo group (unadjusted HR: 0.89 [95% CI: 0.81-0.97] and adjusted HR: 0.92 [95% CI: 0.84-1.01]). In the subgroup with N-terminal pro-B-type natriuretic peptide levels ≤2,816 pg/mL (ie, Q1 and Q2; median or below), there was a suggestion of a benefit with vericiguat (adjusted HRs of 0.80 [95% CI: 0.64-1.01] and 0.77 [95% CI: 0.62-0.94], respectively) compared with those above this value (adjusted HRs of 1.12 [95% CI: 0.93-1.34] and 0.87 [95% CI: 0.74-1.04] for Q3 and Q4). There was no significant difference in treatment effect between patients with vs without an HF hospitalization. After HF hospitalization, the all-cause mortality rate (events per 100 patient-years) was 48.6 for vericiguat and 44.1 for placebo. CONCLUSIONS: Additional investigation of the association between vericiguat and cardiovascular death and total HF hospitalizations by recurrent event analysis did not show a statistically significant reduction in events. Mortality was high after HF hospitalization, emphasizing the need for further therapies to reduce morbidity and mortality. (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction [VICTORIA]; NCT02861534).

Use of win time for ordered composite endpoints in clinical trials.

Consider the choice of outcome for overall treatment benefit in a clinical trial which measures the first time to each of several clinical events. We describe several new variants of the win ratio that incorporate the time spent in each clinical state over the common follow-up, where clinical state means the worst clinical event that has occurred by that time. One version allows restriction so that death during follow-up is most important, while time spent in other clinical states is still accounted for. Three other variants are described; one is based on the average pairwise win time, one creates a continuous outcome for each participant based on expected win times against a reference distribution and another that uses the estimated distributions of clinical state to compare the treatment arms. Finally, a combination testing approach is described to give robust power for detecting treatment benefit across a broad range of alternatives. These new methods are designed to be closer to the overall treatment benefit/harm from a patient's perspective, compared to the ordinary win ratio. The new methods are compared to the composite event approach and the ordinary win ratio. Simulations show that when overall treatment benefit on death is substantial, the variants based on either the participants' expected win times (EWTs) against a reference distribution or estimated clinical state distributions have substantially higher power than either the pairwise comparison or composite event methods. The methods are illustrated by re-analysis of the trial heart failure: a controlled trial investigating outcomes of exercise training.

Understanding New Machine Learning Architectures: Practical Generative Artificial Intelligence for Anesthesiologists.

Recent advances in neural networks have given rise to generative artificial intelligence, systems able to produce fluent responses to natural questions or attractive and even photorealistic images from text prompts. These systems were developed through new network architectures that permit massive computational resources to be applied efficiently to enormous data sets. First, this review examines autoencoder architecture and its derivatives the variational autoencoder and the U-Net in annotating and manipulating images and extracting salience. This architecture will be important for applications like automated x-ray interpretation or real-time highlighting of anatomy in ultrasound images. Second, this article examines the transformer architecture in the interpretation and generation of natural language, as it will be useful in producing automated summarization of medical records or performing initial patient screening. The author also applies the GPT-3.5 algorithm to example questions from the American Board of Anesthesiologists Basic Examination and find that, under surprisingly reasonable conditions, it correctly answers more than half the questions.