Visualizing Opioid-Use Variation in a Pediatric Perioperative Dashboard.

BACKGROUND: Anesthesiologists integrate numerous variables to determine an opioid dose that manages patient nociception and pain while minimizing adverse effects. Clinical dashboards that enable physicians to compare themselves to their peers can reduce unnecessary variation in patient care and improve outcomes. However, due to the complexity of anesthetic dosing decisions, comparative visualizations of opioid-use patterns are complicated by case-mix differences between providers. OBJECTIVES: This single-institution case study describes the development of a pediatric anesthesia dashboard and demonstrates how advanced computational techniques can facilitate nuanced normalization techniques, enabling meaningful comparisons of complex clinical data. METHODS: We engaged perioperative-care stakeholders at a tertiary care pediatric hospital to determine patient and surgical variables relevant to anesthesia decision-making and to identify end-user requirements for an opioid-use visualization tool. Case data were extracted, aggregated, and standardized. We performed multivariable machine learning to identify and understand key variables. We integrated interview findings and computational algorithms into an interactive dashboard with normalized comparisons, followed by an iterative process of improvement and implementation. RESULTS: The dashboard design process identified two mechanisms-interactive data filtration and machine-learning-based normalization-that enable rigorous monitoring of opioid utilization with meaningful case-mix adjustment. When deployed with real data encompassing 24,332 surgical cases, our dashboard identified both high and low opioid-use outliers with associated clinical outcomes data. CONCLUSION: A tool that gives anesthesiologists timely data on their practice patterns while adjusting for case-mix differences empowers physicians to track changes and variation in opioid administration over time. Such a tool can successfully trigger conversation amongst stakeholders in support of continuous improvement efforts. Clinical analytics dashboards can enable physicians to better understand their practice and provide motivation to change behavior, ultimately addressing unnecessary variation in high impact medication use and minimizing adverse effects.

The effects of practice schedules on the process of motor adaptation.

OBJECTIVES: Walking is a well-practiced skill but requires adapting steps online to meet external constraints. The objective of this study was to examine the effects of types of practice schedules (i.e., blocked versus random practice) on the process of adapting and generalizing motor actions. METHODS: To examine how practice schedules influence the process of adaptation and generalization during walking, 60 young, healthy adults walked to normal, slow, and fast metronome paces: 30 with blocked practice and 30 with random practice. Paces were interspersed with 2 carryover trials with no beat. Subsequent paces were a test of generalizing adaptation from the old to the new metronome pace. RESULTS: The results showed that participants who received blocked practice acclimated more quickly to the metronome beat. Specifically, the blocked practice group altered their walking more quickly during the fast metronome pace. In contrast, the random practice group matched the metronome beat more quickly during the slow pace. Participants who received blocked practice demonstrated carryover effects during carryover trials after walking to the metronome. CONCLUSIONS: These findings extend an understanding of how the process of adaptation unfolds over time with the imposition of timing constraints.

Changes in motor actions in the face of varying task constraints.

BACKGROUND: Walking is an everyday activity that requires modifying patterns based on constraints posed by the environment. Meeting multiple constraints at once increases the challenge of modifying motor actions. RESEARCH QUESTION: We asked if adults' strategies in adapting to spatial and temporal constraints were similar and if they would prioritize one constraint over the other when completing both. METHODS: Across three tasks, we investigated how adults altered their walking to cope with crossing obstacles (Task 1; N = 30), walking to a metronome beat (Task 2; N = 32), and crossing obstacles while walking to a metronome beat (Task 3; N = 30). RESULTS: Adults recalibrated to their baseline gait, but showed carryover effects after meeting a temporal constraint (allps>.05). We found an effect on the magnitude of deviation from metronome paces (F(262) = 58.86, p<.01). At the slow pace, participants stepped sooner than the beat, and at the fast pace they stepped later than the beat (all ps<.01). Adults altered the kinematics of their walking in response to a spatial constraint, but changed both the kinematics and kinetics of their walking patterns to meet temporal and combined spatial and temporal constraints. When attempting to meet both a spatial and temporal constraint simultaneously, they stepped sooner than the beat at all metronome paces (all ps<.01). SIGNIFICANCE: Our findings show separate walking strategies in adapting to spatial and temporal constraints. The presence of more than one constraint leads to prioritizing one over the other (i.e., a spatial constraint over a temporal constraint). These findings highlight that strategies for meeting constraints are dependent upon the type and number of constraints presented.

A Comprehensive TALEN-Based Knockout Library for Generating Human-Induced Pluripotent Stem Cell-Based Models for Cardiovascular Diseases.

RATIONALE: Targeted genetic engineering using programmable nucleases such as transcription activator-like effector nucleases (TALENs) is a valuable tool for precise, site-specific genetic modification in the human genome. OBJECTIVE: The emergence of novel technologies such as human induced pluripotent stem cells (iPSCs) and nuclease-mediated genome editing represent a unique opportunity for studying cardiovascular diseases in vitro. METHODS AND RESULTS: By incorporating extensive literature and database searches, we designed a collection of TALEN constructs to knockout 88 human genes that are associated with cardiomyopathies and congenital heart diseases. The TALEN pairs were designed to induce double-strand DNA break near the starting codon of each gene that either disrupted the start codon or introduced a frameshift mutation in the early coding region, ensuring faithful gene knockout. We observed that all the constructs were active and disrupted the target locus at high frequencies. To illustrate the utility of the TALEN-mediated knockout technique, 6 individual genes (TNNT2, LMNA/C, TBX5, MYH7, ANKRD1, and NKX2.5) were knocked out with high efficiency and specificity in human iPSCs. By selectively targeting a pathogenic mutation (TNNT2 p.R173W) in patient-specific iPSC-derived cardiac myocytes, we demonstrated that the knockout strategy ameliorates the dilated cardiomyopathy phenotype in vitro. In addition, we modeled the Holt-Oram syndrome in iPSC-cardiac myocytes in vitro and uncovered novel pathways regulated by TBX5 in human cardiac myocyte development. CONCLUSIONS: Collectively, our study illustrates the powerful combination of iPSCs and genome editing technologies for understanding the biological function of genes, and the pathological significance of genetic variants in human cardiovascular diseases. The methods, strategies, constructs, and iPSC lines developed in this study provide a validated, readily available resource for cardiovascular research.

Transcriptome Profiling of Patient-Specific Human iPSC-Cardiomyocytes Predicts Individual Drug Safety and Efficacy Responses In Vitro.

Understanding individual susceptibility to drug-induced cardiotoxicity is key to improving patient safety and preventing drug attrition. Human induced pluripotent stem cells (hiPSCs) enable the study of pharmacological and toxicological responses in patient-specific cardiomyocytes (CMs) and may serve as preclinical platforms for precision medicine. Transcriptome profiling in hiPSC-CMs from seven individuals lacking known cardiovascular disease-associated mutations and in three isogenic human heart tissue and hiPSC-CM pairs showed greater inter-patient variation than intra-patient variation, verifying that reprogramming and differentiation preserve patient-specific gene expression, particularly in metabolic and stress-response genes. Transcriptome-based toxicology analysis predicted and risk-stratified patient-specific susceptibility to cardiotoxicity, and functional assays in hiPSC-CMs using tacrolimus and rosiglitazone, drugs targeting pathways predicted to produce cardiotoxicity, validated inter-patient differential responses. CRISPR/Cas9-mediated pathway correction prevented drug-induced cardiotoxicity. Our data suggest that hiPSC-CMs can be used in vitro to predict and validate patient-specific drug safety and efficacy, potentially enabling future clinical approaches to precision medicine.