A Computational Framework for Multivariate Convex Regression and Its Variants

We study the nonparametric least squares estimator (LSE) of a multivariate convex regression function. The LSE, given as the solution to a quadratic program with O(n²) linear constraints (n being the sample size), is difficult to compute for large problems. Exploiting problem specific structure, we propose a scalable algorithmic framework based on the augmented Lagrangian method to compute the LSE. We develop a novel approach to obtain smooth convex approximations to the fitted (piecewise affine) convex LSE and provide formal bounds on the quality of approximation. When the number of samples is not too large compared to the dimension of the predictor, we propose a regularization scheme—Lipschitz convex regression—where we constrain the norm of the subgradients, and study the rates of convergence of the obtained LSE. Our algorithmic framework is simple and flexible and can be easily adapted to handle variants: estimation of a nondecreasing/nonincreasing convex/concave (with or without a Lipschitz bound) function. We perform numerical studies illustrating the scalability of the proposed algorithm—on some instances our proposal leads to more than a 10,000-fold improvement in runtime when compared to off-the-shelf interior point solvers for problems with n = 500. Keywords: Augmented Lagrangian method; Lipschitz convex regression; Non parametric least squares estimator; Scalable quadratic programming; Smooth convex regressionUnited States. Office of Naval Research (Grant N00014-15-1-2342

Risk, Benefit, and Cost Thresholds for Emergency Department Testing: A Cross‐sectional, Scenario‐based Study

BackgroundWhile diagnostic testing is common in the emergency department, the value of some testing is questionable. The purpose of this study was to assess how varying levels of benefit, risk, and costs influenced an individual’s desire to have diagnostic testing.MethodsA survey through Amazon Mechanical Turk presented hypothetical clinical situations: low‐risk chest pain and minor traumatic brain injury. Each scenario included three given variables (benefit, risk, and cost), that was independently randomly varied over four possible values (0.1, 1, 5, and 10% for benefit and risk and $0,$100, $500, and$1,000 for the individual’s personal cost for receiving the test). Benefit was defined as the probability of finding the target disease (traumatic intracranial hemorrhage or acute coronary syndrome).ResultsOne‐thousand unique respondents completed the survey. With an increased benefit from 0.1% to 10%, the percentage of respondents who accepted a diagnostic test went from 28.4% to 53.1%. (odds ratio [OR] = 3.42; 95% confidence interval [CI] = 2.57–4.54). As risk increased from 0.1% to 10%, this number decreased from 52.5% to 28.5%. (OR = 0.33; 95% CI = 0.25–0.44). Increasing cost from $0 to$1,000 had the greatest change of those accepting the test from 61.1% to 21.4%, respectively (OR = 0.15; 95% CI = 0.11–0.2).ConclusionsThe desire for testing was strongly sensitive to the benefits, risks, and costs. Many participants wanted a test when there was no added cost, regardless of benefit or risk levels, but far fewer elected to receive the test as cost increased incrementally. This suggests that out‐of‐pocket costs may deter patients from undergoing diagnostic testing with low potential benefit.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137417/1/acem13148_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137417/2/acem13148.pd

Patient Preferences for Diagnostic Testing in the Emergency Department: A Crossâ sectional Study

BackgroundDiagnostic testing is common during emergency department (ED) visits. Little is understood about patient preferences for such testing. We hypothesized that a patient’s willingness to undergo diagnostic testing is influenced by the potential benefit, risk, and personal cost.MethodsWe conducted a cross sectional survey among ED patients for diagnostic testing in two hypothetical scenarios: chest pain (CP) and mild traumatic brain injury (mTBI). Each scenario defined specific risks, benefits, and costs of testing. The odds of a participant desiring diagnostic testing were calculated using a series of nested multivariable logistic regression models.ResultsParticipants opted for diagnostic testing 68.2% of the time, including 69.7% of CP and 66.7% of all mTBI scenarios. In the CP scenario, 81% of participants desired free testing versus 59% when it was associated with a $100 copay (difference = 22$100 copayment (difference = 17%, 95% CI = 11% to 24%). Benefit and risk had mixed effects across the scenarios. In fully adjusted models, the association between cost and desire for testing persisted in the CP (odds ratio [OR] = 0.33, 95% CI = 0.23 to 0.47) and adult mTBI (OR = 0.47, 95% CI = 0.33 to 0.67) scenarios.ConclusionsIn this EDâ based study, patient preferences for diagnostic testing differed significantly across levels of risk, benefit, and cost of diagnostic testing. Cost was the strongest and most consistent factor associated with decreased desire for testing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144652/1/acem13404.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144652/2/acem13404_am.pd

Assessment of Disparities Associated with a Crisis Standards of Care Resource Allocation Algorithm for Patients in 2 US Hospitals during the COVID-19 Pandemic

Importance: Significant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity. Objective: To evaluate whether unanticipated disparities by race or ethnicity arise from a single institution\u27s resource allocation policy. Design, Setting, and Participants: This cohort study included adults (aged ≥18 years) who were cared for on a coronavirus disease 2019 (COVID-19) ward or in a monitored unit requiring invasive or noninvasive ventilation or high-flow nasal cannula between May 26 and July 14, 2020, at 2 academic hospitals in Miami, Florida. Exposures: Race (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic). Main Outcomes and Measures: The primary outcome was based on a resource allocation priority score (range, 1-8, with 1 indicating highest and 8 indicating lowest priority) that was assigned daily based on both estimated short-term (using Sequential Organ Failure Assessment score) and longer-term (using comorbidities) mortality. There were 2 coprimary outcomes: maximum and minimum score for each patient over all eligible patient-days. Standard summary statistics were used to describe the cohort, and multivariable Poisson regression was used to identify associations of race and ethnicity with each outcome. Results: The cohort consisted of 5613 patient-days of data from 1127 patients (median [interquartile range {IQR}] age, 62.7 [51.7-73.7]; 607 [53.9%] men). Of these, 711 (63.1%) were White patients, 323 (28.7%) were Black patients, 8 (0.7%) were Asian patients, and 31 (2.8%) were multiracial patients; 480 (42.6%) were non-Hispanic patients, and 611 (54.2%) were Hispanic patients. The median (IQR) maximum priority score for the cohort was 3 (1-4); the median (IQR) minimum score was 2 (1-3). After adjustment, there was no association of race with maximum priority score using White patients as the reference group (Black patients: incidence rate ratio [IRR], 1.00; 95% CI, 0.89-1.12; Asian patients: IRR, 0.95; 95% CI. 0.62-1.45; multiracial patients: IRR, 0.93; 95% CI, 0.72-1.19) or of ethnicity using non-Hispanic patients as the reference group (Hispanic patients: IRR, 0.98; 95% CI, 0.88-1.10); similarly, no association was found with minimum score for race, again with White patients as the reference group (Black patients: IRR, 1.01; 95% CI, 0.90-1.14; Asian patients: IRR, 0.96; 95% CI, 0.62-1.49; multiracial patients: IRR, 0.81; 95% CI, 0.61-1.07) or ethnicity, again with non-Hispanic patients as the reference group (Hispanic patients: IRR, 1.00; 95% CI, 0.89-1.13). Conclusions and Relevance: In this cohort study of adult patients admitted to a COVID-19 unit at 2 US hospitals, there was no association of race or ethnicity with the priority score underpinning the resource allocation policy. Despite this finding, any policy to guide altered standards of care during a crisis should be monitored to ensure equitable distribution of resources

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Gut-Induced Inflammation during Development May Compromise the Blood-Brain Barrier and Predispose to Autism Spectrum Disorder

Recently, the gut microbiome has gained considerable interest as one of the major contributors to the pathogenesis of multi-system inflammatory disorders. Several studies have suggested that the gut microbiota plays a role in modulating complex signaling pathways, predominantly via the bidirectional gut-brain-axis (GBA). Subsequent in vivo studies have demonstrated the direct role of altered gut microbes and metabolites in the progression of neurodevelopmental diseases. This review will discuss the most recent advancements in our understanding of the gut microbiome's clinical significance in regulating blood-brain barrier (BBB) integrity, immunological function, and neurobiological development. In particular, we address the potentially causal role of GBA dysregulation in the pathophysiology of autism spectrum disorder (ASD) through compromising the BBB and immunological abnormalities. A thorough understanding of the complex signaling interactions between gut microbes, metabolites, neural development, immune mediators, and neurobiological functionality will facilitate the development of targeted therapeutic modalities to better understand, prevent, and treat ASD

Gene therapy for neurological disorders: challenges and recent advancements

Major advancements in targeted gene therapy have opened up avenues for the treatment of major neurological disorders through a range of versatile modalities varying from expression of exogenous to suppression of endogenous genes. Recent technological innovations for improved gene sequence delivery have focussed on highly specific viral vector designs, plasmid transfection, nanoparticles, polymer-mediated gene delivery, engineered microRNA and in vivo clustered regulatory interspaced short palindromic repeats (CRISPR)-based therapeutics. These advanced techniques have profound applications in treating highly prevalent neurological diseases and neurodevelopmental disorders including Parkinson's disease, Alzheimer's disease and autism spectrum disorder, as well as rarer diseases such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy, lysosomal storage diseases, X-linked adrenoleukodystrophy and oncological diseases. In this article, we present an overview of the latest advances in targeted gene delivery and discuss the challenges and future direction of gene therapy in the treatment of neurological disorders