Opioid requirements in primary versus revision reverse shoulder arthroplasty.

PURPOSE: The purpose of this study is to evaluate the inpatient pain medication use of patients who had a revision shoulder arthroplasty procedure performed and compare them to a cohort of patients who had a primary reverse total shoulder arthroplasty (rTSA) performed to determine whether revision shoulder arthroplasty requires more pain medication.. METHODS: A retrospective review was performed on patients undergoing revision arthroplasty (n = 75) and primary rTSA (n = 340). Inpatient medication records were reviewed to tabulate the visual analog pain (VAS) all narcotic medication use, and total morphine equivalent units (MEUs) were calculated for the duration of the inpatient stay. RESULTS: There was no significant difference between groups regarding age, sex, body mass index, Charlson Comorbidity Index, American Society of Anesthesiologists score, preoperative narcotic pain medication use, tobacco use, postoperative VAS scores or hospital length of stay. There were no predictors of total postoperative MEUs identified. Overall, patients in the revision arthroplasty group received significantly less total MEUs than those in the primary rTSA group, 134.96 MEUs vs. 69.79 MEUs, respectively (p < .0005). CONCLUSION: The perceived notion that revision shoulder arthroplasty is more painful may cause providers to be more inclined to increase narcotic use, or use more invasive pain control techniques. Based on these data, we found that revision shoulder arthroplasty did not require an increased opioid requirement, longer length of stay or increase VAS, suggesting that these patients can often be managed similarly to primary rTSA.

Barriers to Accurate Fluid Measurement in Perioperative Patients: A Mixed Methods Approach.

BACKGROUND: Surgeons depend on fluid intake and output (I/O) measurements for assessment of resuscitation and fluid balance during the perioperative period. Frequently, these measurements are taken by Registered Nurses (RNs) and/or Patient Care Technicians (PCTs). There is variability in the accuracy and consistency of these measurements across nursing units. The goal of this study is to establish what barriers exist in obtaining accurate fluid measurements and potential solutions. MATERIALS AND METHODS: A mixed-method, sequential study design was utilized. First, a survey was conducted at a tertiary care institution of 8 nonintensive care nursing units assessing the perceptions of RNs (n = 85) and PCTs (n = 38) regarding fluid intake and output measurements for surgical patients. Four focus groups were then conducted to expand upon the results of the survey. Fourteen participants (10 RNs and 4 PCTs) were interviewed, and transcripts were analyzed by three reviewers. Qualitative data were manually coded by reviewers using a hierarchical methodology. RESULTS: Survey response rate was 40.6%. The strongest barriers in the survey were patient load and staff time limitations. About half (49%) of the respondents acknowledged that fluid measurements were inaccurate half of the time. PCTs spend more time collecting and charting I/Os and have higher patient loads (P < 0.001) than RNs. PCTs noted more difficulty with complex patients (P = 0.017) and devices for outputs (P = 0.004). PCT's (94%) handwrite data prior to electronic entry. One-third of nurses reported direct electronic entry (P < 0.001). Overall, 71% would prefer to chart in patient's rooms. Most (80%) of respondents received <5 h of fluids-related training at the time they were hired. Cronbach's alpha for three focus group reviewers was 0.84 (95% CI 0.693-0.923). Themes included understaffing, lack of training, a high percentage of traveling nurses, and poor communication regarding new orders. Recommended solutions to improve I/Os included in-room kiosks for electronic entry and relief of staffing burdens. CONCLUSIONS: Fluid I/O measurement accuracy and efficiency may be improved by increased staffing, educational programs, and computer access, streamlining of order sets, simplicity of EMR data entry, and a standardized process for measuring, recording, and charting I/Os.

Exploring the Subtle Effect of Aliphatic Ring Size on Minor Actinide-Extraction Properties and Metal Ion Speciation in Bis-1,2,4-Triazine Ligands.

The synthesis and evaluation of three novel bis-1,2,4-triazine ligands containing five-membered aliphatic rings are reported. Compared to the more hydrophobic ligands 1-3 containing six-membered aliphatic rings, the distribution ratios for relevant f-block metal ions were approximately one order of magnitude lower in each case. Ligand 10 showed an efficient, selective and rapid separation of AmIII and CmIII from nitric acid. The speciation of the ligands with trivalent f-block metal ions was probed using NMR titrations and competition experiments, time-resolved laser fluorescence spectroscopy and X-ray crystallography. While the tetradentate ligands 8 and 10 formed LnIII complexes of the same stoichiometry as their more hydrophobic analogues 2 and 3, significant differences in speciation were observed between the two classes of ligand, with a lower percentage of the extracted 1:2 complexes being formed for ligands 8 and 10. The structures of the solid state 1:1 and 1:2 complexes formed by 8 and 10 with YIII , LuIII and PrIII are very similar to those formed by 2 and 3 with LnIII . Ligand 10 forms CmIII and EuIII 1:2 complexes that are thermodynamically less stable than those formed by ligand 3, suggesting that less hydrophobic ligands form less stable AnIII complexes. Thus, it has been shown for the first time how tuning the cyclic aliphatic part of these ligands leads to subtle changes in their metal ion speciation, complex stability and metal extraction affinity.

Novel 1-hydroxypyridin-2-one metal chelators prevent and rescue ubiquitin proteasomal-related neuronal injury in an in vitro model of Parkinson's disease.

Ubiquitin proteasome system (UPS) impairment, excessive cellular oxidative stress, and iron dyshomeostasis are key to substantia nigra dopaminergic neuronal degeneration in Parkinson's disease (PD); however, a link between these features remains unconfirmed. Using the proteasome inhibitor lactacystin we confirm that nigral injury via UPS impairment disrupts iron homeostasis, in turn increasing oxidative stress and promoting protein aggregation. We demonstrate the neuroprotective potential of two novel 1-hydroxy-2(1H)-pyridinone (1,2-HOPO) iron chelators, compounds C6 and C9, against lactacystin-induced cell death. We demonstrate that this cellular preservation relates to the compounds' iron chelating capabilities and subsequent reduced capacity of iron to form reactive oxygen species (ROS), where we also show that the ligands act as antioxidant agents. Our results also demonstrate the ability of C6 and C9 to reduce intracellular lactacystin-induced α-synuclein burden. Stability constant measurements confirmed a high affinity of C6 and C9 for Fe3+ and display a 3:1 HOPO:Fe3+ complex formation at physiological pH. Reducing iron reactivity could prevent the demise of nigral dopaminergic neurons. We provide evidence that the lactacystin model presents with several neuropathological hallmarks of PD related to iron dyshomeostasis and that the novel chelating compounds C6 and C9 can protect against lactacystin-related neurotoxicity.

Design and evaluation of bi-functional iron chelators for protection of dopaminergic neurons from toxicants.

While the etiology of non-familial Parkinson's disease (PD) remains unclear, there is evidence that increased levels of tissue iron may be a contributing factor. Moreover, exposure to some environmental toxicants is considered an additional risk factor. Therefore, brain-targeted iron chelators are of interest as antidotes for poisoning with dopaminergic toxicants, and as potential treatment of PD. We, therefore, designed a series of small molecules with high affinity for ferric iron and containing structural elements to allow their transport to the brain via the neutral amino acid transporter, LAT1 (SLC7A5). Five candidate molecules were synthesized and initially characterized for protection from ferroptosis in human neurons. The promising hydroxypyridinone SK4 was characterized further. Selective iron chelation within the physiological range of pH values and uptake by LAT1 were confirmed. Concentrations of 10-20 µM blocked neurite loss and cell demise triggered by the parkinsonian neurotoxicants, methyl-phenyl-pyridinium (MPP+) and 6-hydroxydopamine (6-OHDA) in human dopaminergic neuronal cultures (LUHMES cells). Rescue was also observed when chelators were given after the toxicant. SK4 derivatives that either lacked LAT1 affinity or had reduced iron chelation potency showed altered activity in our assay panel, as expected. Thus, an iron chelator was developed that revealed neuroprotective properties, as assessed in several models. The data strongly support the role of iron in dopaminergic neurotoxicity and suggests further exploration of the proposed design strategy for improving brain iron chelation.

National Cluster-Randomized Trial of Duty-Hour Flexibility in Surgical Training.

BACKGROUND: Concerns persist regarding the effect of current surgical resident duty-hour policies on patient outcomes, resident education, and resident well-being. METHODS: We conducted a national, cluster-randomized, pragmatic, noninferiority trial involving 117 general surgery residency programs in the United States (2014-2015 academic year). Programs were randomly assigned to current Accreditation Council for Graduate Medical Education (ACGME) duty-hour policies (standard-policy group) or more flexible policies that waived rules on maximum shift lengths and time off between shifts (flexible-policy group). Outcomes included the 30-day rate of postoperative death or serious complications (primary outcome), other postoperative complications, and resident perceptions and satisfaction regarding their well-being, education, and patient care. RESULTS: In an analysis of data from 138,691 patients, flexible, less-restrictive duty-hour policies were not associated with an increased rate of death or serious complications (9.1% in the flexible-policy group and 9.0% in the standard-policy group, P=0.92; unadjusted odds ratio for the flexible-policy group, 0.96; 92% confidence interval, 0.87 to 1.06; P=0.44; noninferiority criteria satisfied) or of any secondary postoperative outcomes studied. Among 4330 residents, those in programs assigned to flexible policies did not report significantly greater dissatisfaction with overall education quality (11.0% in the flexible-policy group and 10.7% in the standard-policy group, P=0.86) or well-being (14.9% and 12.0%, respectively; P=0.10). Residents under flexible policies were less likely than those under standard policies to perceive negative effects of duty-hour policies on multiple aspects of patient safety, continuity of care, professionalism, and resident education but were more likely to perceive negative effects on personal activities. There were no significant differences between study groups in resident-reported perception of the effect of fatigue on personal or patient safety. Residents in the flexible-policy group were less likely than those in the standard-policy group to report leaving during an operation (7.0% vs. 13.2%, P<0.001) or handing off active patient issues (32.0% vs. 46.3%, P<0.001). CONCLUSIONS: As compared with standard duty-hour policies, flexible, less-restrictive duty-hour policies for surgical residents were associated with noninferior patient outcomes and no significant difference in residents' satisfaction with overall well-being and education quality. (FIRST ClinicalTrials.gov number, NCT02050789.).

1,2,4-Triazines in the Synthesis of Bipyridine Bisphenolate ONNO Ligands and Their Highly Luminescent Tetradentate Pt(II) Complexes for Solution-Processable OLEDs.

This article describes a convenient method for the synthesis of ONNO-type tetradentate 6,6'-bis(2-phenoxy)-2,2'-bipyridine (bipyridine bisphenolate, BpyBph) ligands and their platinum(II) complexes. The methodology includes the synthesis of 1,2,4-triazine precursors followed by their transformation to functionalized pyridines by the Boger reaction. Two complementary routes employing 3,3'- and 5,5'-bis-triazines allow a modification of the central pyridine rings in different positions, which was exemplified by the introduction of cyclopentene rings. The new ligands were used to prepare highly luminescent ONNO-type Pt(II) complexes. The position of the cyclopentene rings significantly influences the solubility and photophysical properties of these complexes. Derivatives with closely positioned cyclopentene rings are soluble in organic solvents and proved to be the best candidate for solution-processable organic light-emitting devices (OLEDs), showing efficient single-dopant candlelight electroluminescence.

Who Makes It to the End?: A Novel Predictive Model for Identifying Surgical Residents at Risk for Attrition.

OBJECTIVE: We present 8-year follow-up data from the intern class of 2007 to 2008 using a novel, nonparametric predictive model to identify those residents who are at greatest risk of not completing their training. BACKGROUND: Nearly 1 in every 4 categorical general surgery residents does not complete training. There has been no study at a national level to identify individual resident and programmatic factors that can be used to accurately anticipate which residents are most at risk of attrition out. METHODS: A cross-sectional survey of categorical general surgery interns was conducted between June and August 2007. Intern data including demographics, attendance at US or Canadian medical school, proximity of family members, and presence of family members in medicine were de-identified and linked with American Board of Surgery data to determine residency completion and program characteristics. A Classification and Regression Tree analysis was performed to identify groups at greatest risk for non-completion. RESULTS: Of 1048 interns, 870 completed the initial survey (response rate 83%), 836 of which had linkage data (96%). Also, 672 residents had evidence of completion of residency (noncompletion rate 20%). On Classification and Regression Tree analysis, sex was the independent factor most strongly associated with attrition. The lowest noncompletion rate for men was among interns at small community programs who were White, non-Hispanic, and married (6%). The lowest noncompletion rate for women was among interns training at smaller academic programs (11%). CONCLUSIONS: This is the first longitudinal cohort study to identify factors at the start of training that put residents at risk for not completing training. Data from this study offer a method to identify interns at higher risk for attrition at the start of training, and next steps would be to create and test interventions in a directed fashion.

Factors influencing the decision of surgery residency graduates to pursue general surgery practice versus fellowship.

OBJECTIVES: Surgery residency serves 2 purposes-prepare graduates for general surgery (GS) practice or postresidency surgical fellowship, leading to specialty surgical practice (SS). This study was undertaken to elucidate factors influencing career choice for these 2 groups. METHODS: All US allopathic surgery residency graduates from 2009 to 2013 (n = 5512) were surveyed by the American Board of Surgery regarding confidence, autonomy, and reasons for career selection between GS and SS. Surveys were distributed by mail in November 2013, with follow-up mailings to initial nonrespondents. RESULTS: Sixty-one percent (3354) of graduates completed the survey; 26% pursued GS, and 74% SS. GS expressed greater levels of confidence than SS across the common surgical procedures queried. Confidence increased with each year after completion of residency for GS but not SS. The decision to pursue GS or SS was made during residency by 77% and 74%, respectively. Fifty-seven percent of those who chose GS indicated that a GS mentor significantly influenced their decision. GS rated procedural variety, opportunity for practice autonomy, choice of practice location, and influence of a mentor as reasons to pursue GS practice. SS listed control over scope of practice, prestige, salary, and specialty interest as reasons to pursue SF. Both groups expressed a high degree of satisfaction with their career choice (GS, 94%; SS, 90%). CONCLUSIONS: Most graduates who pursue GS practice are confident and content. The decision to pursue GS is strongly influenced by a GS mentor. Lack of confidence may be a more significant factor for choosing SS. These findings suggest opportunities for improvements in confidence and mentorship during residency.

Association of the 2011 ACGME resident duty hour reform with general surgery patient outcomes and with resident examination performance.

IMPORTANCE: In 2011, the Accreditation Council for Graduate Medical Education (ACGME) restricted resident duty hour requirements beyond those established in 2003, leading to concerns about the effects on patient care and resident training. OBJECTIVE: To determine if the 2011 ACGME duty hour reform was associated with a change in general surgery patient outcomes or in resident examination performance. DESIGN, SETTING, AND PARTICIPANTS: Quasi-experimental study of general surgery patient outcomes 2 years before (academic years 2009-2010) and after (academic years 2012-2013) the 2011 duty hour reform. Teaching and nonteaching hospitals were compared using a difference-in-differences approach adjusted for procedural mix, patient comorbidities, and time trends. Teaching hospitals were defined based on the proportion of cases at which residents were present intraoperatively. Patients were those undergoing surgery at hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). General surgery resident performance on the annual in-training, written board, and oral board examinations was assessed for this same period. EXPOSURES: National implementation of revised resident duty hour requirements on July 1, 2011, in all ACGME accredited residency programs. MAIN OUTCOMES AND MEASURES: Primary outcome was a composite of death or serious morbidity; secondary outcomes were other postoperative complications and resident examination performance. RESULTS: In the main analysis, 204,641 patients were identified from 23 teaching (n = 102,525) and 31 nonteaching (n = 102,116) hospitals. The unadjusted rate of death or serious morbidity improved during the study period in both teaching (11.6% [95% CI, 11.3%-12.0%] to 9.4% [95% CI, 9.1%-9.8%], P < .001) and nonteaching hospitals (8.7% [95% CI, 8.3%-9.0%] to 7.1% [95% CI, 6.8%-7.5%], P < .001). In adjusted analyses, the 2011 ACGME duty hour reform was not associated with a significant change in death or serious morbidity in either postreform year 1 (OR, 1.12; 95% CI, 0.98-1.28) or postreform year 2 (OR, 1.00; 95% CI, 0.86-1.17) or when both postreform years were combined (OR, 1.06; 95% CI, 0.93-1.20). There was no association between duty hour reform and any other postoperative adverse outcome. Mean (SD) in-training examination scores did not significantly change from 2010 to 2013 for first-year residents (499.7 [ 85.2] to 500.5 [84.2], P = .99), for residents from other postgraduate years, or for first-time examinees taking the written or oral board examinations during this period. CONCLUSIONS AND RELEVANCE: Implementation of the 2011 ACGME duty hour reform was not associated with a change in general surgery patient outcomes or differences in resident examination performance. The implications of these findings should be considered when evaluating the merit of the 2011 ACGME duty hour reform and revising related policies in the future.

Verification of resident bedside-procedure competency by intensive care nursing staff.

BACKGROUND: Recent efforts by the Accreditation Council for Graduate Medical Education to standardize resident education and demonstrate objective clinical proficiency have led toward more accurate documentation of resident competencies. Particularly with regard to bedside procedures, hospitals are now requiring certification of competency before allowing a provider to perform them independently. The current system at our institution uses a time-consuming, online verification system. This study provided an alternative method through an identification card with a list of bedside procedures. Our aim was an easier verification method for nurses, allowing fewer delays of bedside procedures and more time for nursing to patient care. METHODS: We performed a prospective, controlled study, using general surgical residents and surgical intensive care nurses. Subjects performed an initial survey of their experience with the current online system in place to identify resident bedside procedure competency. Phase I involved educating the subjects about this current system followed by another survey. Phase II involved introducing our proficiency card. After 3 months, we conducted a final survey to evaluate opinions on the proficiency card, comparing it with the online verification method. RESULTS: Nursing postintervention responses indicated that significantly less time was required to validate a resident's proficiency (P = .04). Prior to the introduction of the proficiency card, only 15% of nurses reported a verification time of 5 minutes or less, compared with 64% postintervention. In addition, nurses rated the card validation as an easier, more efficient method of verification (P = .02). CONCLUSIONS: We believe that its continued use will not only improve the adherence to a mandatory hospital policy but also result in a less-cumbersome verification process, allowing more time for physician and nurse-to-patient care.

Cooperative Control of Multiagent Systems: A Quantization Feedback-Based Event-Triggered Approach.

This article addresses the synchronization tracking problem for high-order uncertain nonlinear multiagent systems via intermittent feedback under a directed graph. By resorting to a novel storer-based triggering transmission strategy in the state channels, we propose an event-triggered neuroadaptive control method with quantitative state feedback that exhibits several salient features: 1) avoiding continuous control updates by making the parameter estimations updated intermittently at the trigger instants; 2) resulting in lower-frequency triggering transmissions by using one event detector to monitor the triggering condition such that each agent only needs to broadcast information at its own trigger times; and 3) saving communication and computation resources by designing the intermittent updating of neural network weights using a dual-phase technique during the triggering period. Besides, it is shown that the proposed scheme is capable of steering the tracking/disagreement errors into an adjustable neighborhood close to the origin, and the existence of a strictly positive dwell time is proved to circumvent Zeno behavior. Both theoretical analysis and numerical simulation authenticate and validate the efficiency of the proposed protocols.

Inverse Value Iteration and Q -Learning: Algorithms, Stability, and Robustness.

This article proposes a data-driven model-free inverse Q -learning algorithm for continuous-time linear quadratic regulators (LQRs). Using an agent's trajectories of states and optimal control inputs, the algorithm reconstructs its cost function that captures the same trajectories. This article first poses a model-based inverse value iteration scheme using the agent's system dynamics. Then, an online model-free inverse Q -learning algorithm is developed to recover the agent's cost function only using the demonstrated trajectories. It is more efficient than the existing inverse reinforcement learning (RL) algorithms as it avoids the repetitive RL in inner loops. The proposed algorithms do not need initial stabilizing control policies and solve for unbiased solutions. The proposed algorithm's asymptotic stability, convergence, and robustness are guaranteed. Theoretical analysis and simulation examples show the effectiveness and advantages of the proposed algorithms.

Policy Iteration-Based Learning Design for Linear Continuous-Time Systems Under Initial Stabilizing OPFB Policy.

Policy iteration (PI), an iterative method in reinforcement learning, has the merit of interactions with a little-known environment to learn a decision law through policy evaluation and improvement. However, the existing PI-based results for output-feedback (OPFB) continuous-time systems relied heavily on an initial stabilizing full state-feedback (FSFB) policy. It thus raises the question of violating the OPFB principle. This article addresses such a question and establishes the PI under an initial stabilizing OPFB policy. We prove that an off-policy Bellman equation can transform any OPFB policy into an FSFB policy. Based on this transformation property, we revise the traditional PI by appending an additional iteration, which turns out to be efficient in approximating the optimal control under the initial OPFB policy. We show the effectiveness of the proposed learning methods through theoretical analysis and a case study.

Inverse Q-Learning Using Input-Output Data.

This article addresses the problem of learning the objective function of linear discrete-time systems that use static output-feedback (OPFB) control by designing inverse reinforcement learning (RL) algorithms. Most of the existing inverse RL methods require the availability of states and state-feedback control from the expert or demonstrated system. In contrast, this article considers inverse RL in a more general case where the demonstrated system uses static OPFB control with only input-output measurements available. We first develop a model-based inverse RL algorithm to reconstruct an input-output objective function of a demonstrated discrete-time system using its system dynamics and the OPFB gain. This objective function infers the demonstrations and OPFB gain of the demonstrated system. Then, an input-output Q -function is built for the inverse RL problem upon the state reconstruction technique. Given demonstrated inputs and outputs, a data-driven inverse Q -learning algorithm reconstructs the objective function without the knowledge of the demonstrated system dynamics or the OPFB gain. This algorithm yields unbiased solutions even though exploration noises exist. Convergence properties and the nonunique solution nature of the proposed algorithms are studied. Numerical simulation examples verify the effectiveness of the proposed methods.

Model-Free Q-Learning for the Tracking Problem of Linear Discrete-Time Systems.

In this article, a model-free Q-learning algorithm is proposed to solve the tracking problem of linear discrete-time systems with completely unknown system dynamics. To eliminate tracking errors, a performance index of the Q-learning approach is formulated, which can transform the tracking problem into a regulation one. Compared with the existing adaptive dynamic programming (ADP) methods and Q-learning approaches, the proposed performance index adds a product term composed of a gain matrix and the reference tracking trajectory to the control input quadratic form. In addition, without requiring any prior knowledge of the dynamics of the original controlled system and command generator, the control policy obtained by the proposed approach can be deduced by an iterative technique relying on the online information of the system state, the control input, and the reference tracking trajectory. In each iteration of the proposed method, the desired control input can be updated by the iterative criteria derived from a precondition of the controlled system and the reference tracking trajectory, which ensures that the obtained control policy can eliminate tracking errors in theory. Moreover, to effectively use less data to obtain the optimal control policy, the off-policy approach is introduced into the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by a numerical simulation.

Data-Efficient Reinforcement Learning for Complex Nonlinear Systems.

This article proposes a data-efficient model-free reinforcement learning (RL) algorithm using Koopman operators for complex nonlinear systems. A high-dimensional data-driven optimal control of the nonlinear system is developed by lifting it into the linear system model. We use a data-driven model-based RL framework to derive an off-policy Bellman equation. Building upon this equation, we deduce the data-efficient RL algorithm, which does not need a Koopman-built linear system model. This algorithm preserves dynamic information while reducing the required data for optimal control learning. Numerical and theoretical analyses of the Koopman eigenfunctions for dataset truncation are discussed in the proposed model-free data-efficient RL algorithm. We validate our framework on the excitation control of the power system.

Inverse Reinforcement Learning for Trajectory Imitation Using Static Output Feedback Control.

This article studies the trajectory imitation control problem of linear systems suffering external disturbances and develops a data-driven static output feedback (OPFB) control-based inverse reinforcement learning (RL) approach. An Expert-Learner structure is considered where the learner aims to imitate expert's trajectory. Using only measured expert's and learner's own input and output data, the learner computes the policy of the expert by reconstructing its unknown value function weights and thus, imitates its optimally operating trajectory. Three static OPFB inverse RL algorithms are proposed. The first algorithm is a model-based scheme and serves as basis. The second algorithm is a data-driven method using input-state data. The third algorithm is a data-driven method using only input-output data. The stability, convergence, optimality, and robustness are well analyzed. Finally, simulation experiments are conducted to verify the proposed algorithms.