European Society of Cardiology 0/1-hour algorithm (high-sensitivity cardiac troponin T) performance across distinct age groups.

BACKGROUND: To determine if the European Society of Cardiology 0/1-hour (ESC 0/1-h) algorithm with high-sensitivity cardiac troponin T (hs-cTnT) meets the ≥99% negative predictive value (NPV) safety threshold for 30-day cardiac death or myocardial infarction (MI) in older, middle-aged and young subgroups. METHODS: We conducted a subgroup analysis of adult emergency department patients with chest pain prospectively enrolled from eight US sites (January 2017 to September 2018). Patients were stratified into rule-out, observation and rule-in zones using the hs-cTnT ESC 0/1-h algorithm and classified as older (≥65 years), middle aged (46-64 years) or young (21-45 years). Patients had 0-hour and 1-hour hs-cTnT measures (Roche Diagnostics) and a History, ECG, Age, Risk factor and Troponin (HEART) score. Fisher's exact tests compared rule-out and 30-day cardiac death or MI rates between ages. NPVs with 95% CIs were calculated for the ESC 0/1-h algorithm with and without the HEART score. RESULTS: Of 1430 participants, 26.9% (385/1430) were older, 57.4% (821/1430) middle aged and 15.7% (224/1430) young. Cardiac death or MI at 30 days occurred in 12.8% (183/1430). ESC 0/1-h algorithm ruled out 35.6% (137/385) of older, 62.1% (510/821) of middle-aged and 79.9% of (179/224) young patients (p<0.001). NPV for 30-day cardiac death or MI was 97.1% (95% CI 92.7% to 99.2%) among older patients, 98.4% (95% CI 96.9% to 99.3%) in middle-aged patients and 99.4% (95% CI 96.9% to 100%) among young patients. Adding a HEART score increased NPV to 100% (95% CI 87.7% to 100%) for older, 99.2% (95% CI 97.2% to 99.9%) for middle-aged and 99.4% (95% CI 96.6% to 100%) for young patients. CONCLUSIONS: In older and middle-aged adults, the hs-cTnT ESC 0/1-h algorithm was unable to reach a 99% NPV for 30-day cardiac death or MI unless combined with a HEART score. TRIAL REGISTRATION NUMBER: NCT02984436.

Performance of the European Society of Cardiology 0/1-hour algorithm with high-sensitivity cardiac troponin T at 90 days among patients with known coronary artery disease.

BACKGROUND: The European Society of Cardiology (ESC) 0/1-h high sensitivity troponin T (hs-cTnT) algorithm does not differentiate risk based on known coronary artery disease (CAD: prior myocardial infarction [MI], coronary revascularization, or ≥ 70% coronary stenosis). We recently evaluated its performance among patients with known CAD at 30-days, but little is known about its longer-term risk prediction. The objective of this study is to determine and compare the performance of the algorithm at 90-days among patients with and without known CAD. METHODS: We performed a pre-planned subgroup analysis of the STOP-CP cohort, which prospectively enrolled ED patients ≥21 years old with symptoms suggestive of ACS without ST-elevation on initial ECG across 8 US sites (1/25/2017-9/6/2018). Participants with 0- and 1-h hs-cTnT measures (Roche, Basel, Switzerland) were stratified into rule-out, observe, and rule-in groups using the ESC 0/1-h algorithm. Algorithm performance was tested among patients with or without known CAD, as determined by the treating provider. The primary outcome was cardiac death or MI at 90-days. Fisher's exact tests were used to compare 90-day event and rule-out rates between patients with and without known CAD. Negative predictive values (NPVs) for 90-day cardiac death or MI with exact 95% confidence intervals were calculated and compared using Fisher's exact test. RESULTS: The STOP-CP study accrued 1430 patients, of which 31.4% (449/1430) had known CAD. Cardiac death or MI at 90 days was more common in patients with known CAD than in those without [21.2% (95/449) vs. 10.0% (98/981); p < 0.001]. Using the ESC 0/1-h algorithm, 39.6% (178/449) of patients with known CAD and 66.1% (648/981) of patients without known CAD were ruled-out (p < 0.001). Among rule-out patients, 90-day cardiac death or MI occurred in 3.4% (6/178) of patients with known CAD and 1.2% (8/648) without known CAD (p = 0.09). NPV for 90-day cardiac death or MI was 96.6% (95%CI 92.8-98.8) among patients with known CAD and 98.8% (95%CI 97.6-99.5) in patients without known CAD (p = 0.09). CONCLUSION: Patients with known CAD who were ruled-out using the ESC 0/1-h hs-cTnT algorithm had a high rate of missed 90-day cardiac events, suggesting that the ESC 0/1-h hs-cTnT algorithm may not be safe for use among patients with known CAD. TRIAL REGISTRATION: High-Sensitivity Cardiac Troponin T to Optimize Chest Pain Risk Stratification (STOP-CP; ClinicalTrials.gov: NCT02984436; https://clinicaltrials.gov/ct2/show/NCT02984436).

Sex and race differences in the performance of the European Society of Cardiology 0/1-h algorithm with high-sensitivity troponin T.

The diagnostic performance of the high-sensitivity troponin T (hs-cTnT) European Society of Cardiology (ESC) 0/1-h algorithm in sex and race subgroups of US Emergency Department (ED) patients is unclear. A pre-planned subgroup analysis of the STOP-CP cohort study was conducted. Participants with 0- and 1-h hs-cTnT measures from eight US EDs (1/2017 to 9/2018) were stratified into rule-out, observation, and rule-in zones using the hs-cTnT ESC 0/1 algorithm. The primary outcome was adjudicated 30-day cardiac death or MI. The proportion with the primary outcome in each zone was compared between subgroups with Fisher's exact tests. The negative predictive value (NPV) of the ESC 0/1 rule-out zone for 30-day CDMI was calculated and compared between subgroups using Fisher's exact tests. Of the 1422 patients enrolled, 54.2% (770/1422) were male and 58.1% (826/1422) white with a mean age of 57.6 ± 12.8 years. At 30 days, cardiac death or myocardial infarction (MI) occurred in 12.9% (183/1422) of participants. Among patients stratified to the rule-out zone, 30-day cardiac death or MI occurred in 1.1% (5/436) of women versus 2.1% (8/436) of men (p = .40) and 1.2% (4/331) of non-white patients versus 1.8% (9/490) of white patients (p = .58). The NPV for 30-day cardiac death or MI was similar among women versus men (98.9% [95% confidence interval, CI: 97.3-99.6] vs. 97.9% [95% CI: 95.9-99.1]; p = .40) and among white versus non-white patients (98.8% [95% CI: 96.9-99.7] vs. 98.2% [95% CI: 96.5-99.2]; p = .39). NPVs <99% in each subgroup suggest the hs-cTnT ESC 0/1-h algorithm may not be safe for use in US EDs. Trial Registration: High-Sensitivity Cardiac Troponin T to Optimize Chest Pain Risk Stratification (STOP-CP; ClinicalTrials.gov: NCT02984436; https://clinicaltrials.gov/ct2/show/NCT02984436).

Outcomes of an integrated practice unit for vulnerable emergency department patients.

BACKGROUND: An integrated practice unit (IPU) that provides a multidisciplinary approach to patient care, typically involving a primary care provider, registered nurse, social worker, and pharmacist has been shown to reduce healthcare utilization among high-cost super-utilizer (SU) patients or multi-visit patients (MVP). However, less is known about differences in the impact of these interventions on insured vs. uninsured SU patients and super high frequency SUs ([Formula: see text]8 ED visits per 6 months) vs. high frequency SUs (4-7 ED visits per 6 months). METHODS: We assessed the percent reduction in ED visits, ED cost, hospitalizations, hospital days, and hospitalization costs following implementation of an IPU for SUs located in an academic tertiary care facility. We compared outcomes for publicly insured with uninsured patients, and super high frequency SUs with high frequency SUs 6 months before vs. 6 months after enrollment in the IPU. RESULTS: There was an overall 25% reduction in hospitalizations (p < 0.001), and 23% reduction in hospital days (p = 0.0045), when comparing 6 months before vs. 6 months after enrollment in the program. There was a 26% reduction in average total direct hospitalization costs per patient (p = 0.002). Further analysis revealed a greater reduction in health care utilization for uninsured SU patients compared with publicly insured patients. The program reduced hospitalizations for super high frequency SUs. However, there was no statistically significant impact on overall health care utilization of super high frequency SUs when compared with high frequency SUs. CONCLUSIONS: Our study supports existing evidence that dedicated IPUs for SUs can achieve significant reductions in acute care utilization, particularly for uninsured and high frequency SU patients. TRIAL REGISTRATION: IRB201500212. Retrospectively registered.

Performance of the 0/2-hour high-sensitivity cardiac troponin T diagnostic protocol in a multisite United States cohort.

BACKGROUND: The diagnostic performance of the high-sensitivity troponin T (hs-cTnT) 0/2-h algorithm is unclear among U.S. emergency department (ED) patients with acute chest pain. METHODS: A preplanned subgroup analysis of the STOP-CP cohort study was conducted. Participants with 0- and 2-h hs-cTnT measures prospectively enrolled at eight U.S. EDs from January 2017 to September 2018 were stratified into rule-out, observation, and rule-in zones using the hs-cTnT 0/2-h algorithm alone and combined with the history, electrocardiogram, age, and risk factor (HEAR) score. The primary outcome was adjudicated 30-day cardiac death or myocardial infarction (CDMI). The sensitivity and negative predictive value (NPV) of the 0/2-h rule-out zone and specificity and positive predictive value (PPV) of the rule-in zone for 30-day CDMI were calculated. RESULTS: Of the 1307 patients accrued, 53.6% (700/1307) were male and 58.6% (762/1307) were White, with a mean ± SD age of 57.5 ± 12.7 years. At 30 days, CDMI occurred in 12.9% (168/1307) of participants. The 0/2-h algorithm ruled out 61.4% (802/1307) of patients. Among rule-out patients, 1.9% (15/802) experienced 30-day CDMI, resulting in a sensitivity of 91.1% (95% confidence interval [CI] 85.7%-94.9%) and NPV of 98.1% (95% CI 96.9%-98.9%). The 0/2-h algorithm ruled in 12.4% (162/1307) patients of whom 61.7% (100/162) experienced 30-day CDMI. The rule-in zone specificity was 94.6% (95% CI 93.1%-95.8%) and PPV was 61.7% (95% CI 53.8%-69.2%) for 30-day CDMI. The 0/2-h algorithm combined with HEAR score ruled out 30.7% (401/1307) of patients with a sensitivity and NPV for 30-day CDMI of 98.2% (95% CI 94.9%-99.6%) and 99.3% (95% CI 97.8%-99.8%), respectively. CONCLUSIONS: The hs-cTnT 0/2-h algorithm ruled out most patients. With NPV of <99% for 30-day CDMI, the hs-cTnT 0/2-h algorithm, many emergency physicians may not consider it safe to use for U.S. ED patients. When combined with a low-risk HEAR score, NPV was >99% for 30-day CDMI at the cost of reduced efficacy.

Methods of the PivotaL triAl of the Atellica VTLi point of care emergencY dePartment high sensitivity troponin evalUationS.

BACKGROUND: The Atellica® VTLi point-of-care (POC) High Sensitivity Cardiac Troponin-I (hs-cTnI) assay is intended for use as an aid in the diagnosis of myocardial infarction (MI). Our primary objective is to assess its diagnostic performance in patients presenting with suspected acute coronary syndrome (ACS). METHODS: This prospective observational study will enrol ∼1500 patients at ∼20 U.S. Emergency Departments. After informed consent, adults (>21 years of age) with suspected ACS, and no prior enrollment in this study, will provide a fingerstick and venous blood sample within 2 h of ED presentation, >2 to ≤4 h, and >4 to ≤9 h (max. blood draw = 60 mL). HEART and EDACS scores will be prospectively documented. Patients without the first blood draw may be enrolled if the second draw was obtained. Capillary and venous whole blood will undergo Atellica VTLi assay testing, with remaining venous sample processed to plasma and run. All results will be blinded to the clinical care team. Site operators will undergo a 3-day familiarization period. Quality control testing will be performed daily. At 30 ± 3 days, patient mortality status, major adverse cardiac events, and rehospitalizations will be determined. A clinical endpoint adjudication committee, blinded to hs-cTnI VTLi result, will define the final diagnosis. Sensitivity, specificity, and predictive values will describe the assay performance. RESULTS: We expect study completion within 114 weeks of enrollment of the first patient. CONCLUSIONS: It is anticipated that the Atellica VTLi hs-cTnI assay validation study will define a performance equivalent to lab-based hs-cTnI, with results within ∼8 min at the point of care.

Effects of COVID-19 stress, proximity, and adverse childhood experiences on healthcare workers' mental health.

Past research has shown that healthcare workers (HCWs) experience high levels of psychological distress during epidemics and pandemics, resulting in cascading effects that have led to chronically understaffed hospitals and healthcare centers. Due to the nature of their responsibilities and workplace stress, HCWs are among vulnerable groups especially during global health crises. During COVID-19 many healthcare workers reported greater symptoms of anxiety, depression, and COVID-19 related worries. Furthermore, adverse childhood experiences increase vulnerability for psychological conditions, especially during pandemics. This study sets out to (1) investigate the moderating effects of adverse childhood experiences on healthcare workers' COVID-19 related stressors and depression/anxiety symptoms, and (2) investigate the moderating effects of adverse childhood experiences on proximity to the COVID-19 virus and depression/anxiety symptoms. Participants included 438 employed HCWs recruited from academic medical centers and smaller healthcare agencies in northcentral Florida between October to December 2020. Mean age of participants was 38.23 (SD = 11.5) with most of the HCWs being white (72.1%), non-Hispanic (86.8%) and female (82%). Healthcare workers completed several online questionnaires, including the Adverse Childhood Experiences scale, Patient Health Questionnaire, Generalized Anxiety Disorder Scale, a COVID-19 specific worries scale, and a Social Proximity to COVID-19 scale. Healthcare workers experiencing specific COVID-19 worries reported experiencing anxiety and depressive symptoms. A significant positive interaction was seen between childhood adverse experiences globally and COVID-19 worries on anxiety symptoms. A significant positive interaction was observed between childhood maltreatment specifically and COVID-19 worries on depressive symptoms. Additionally, a positive interaction effect was seen between childhood adverse experiences and COVID-19 social proximity for both depression symptoms and anxiety symptoms. Findings from the present study indicate that adverse childhood experiences strengthen the relationship between COVID-19 worry/proximity and negative psychological symptoms. Vulnerable populations such as individuals who have experienced ACEs could benefit from targeted and specific interventions to cope with the collective trauma experienced globally due to COVID-19. As COVID-19 becomes endemic, hospital leadership and authorities should continue addressing COVID-19 worries and HCWs' psychological symptoms through mental health support and organizational interventions.

Resilient, but for how long? The relationships between temperament, burnout, and mental health in healthcare workers during the Covid-19 pandemic.

Introduction: Dispositional traits of wellbeing and stress-reaction are strong predictors of mood symptoms following stressful life events, and the COVID-19 pandemic introduced many life stressors, especially for healthcare workers. Methods: We longitudinally investigated the relationships among positive and negative temperament group status (created according to wellbeing and stress-reaction personality measures), burnout (exhaustion, interpersonal disengagement), COVID concern (e.g., health, money worries), and moral injury (personal acts, others' acts) as predictors of generalized anxiety, depression, and post-traumatic stress symptoms in 435 healthcare workers. Participants were employees in healthcare settings in North Central Florida who completed online surveys monthly for 8 months starting in October/November 2020. Multidimensional Personality Questionnaire subscale scores for stress-reaction and wellbeing were subjected to K-means cluster analyses that identified two groups of individuals, those with high stress-reaction and low wellbeing (negative temperament) and those with the opposite pattern defined as positive temperament (low stress-reaction and high wellbeing). Repeated measures ANOVAs assessed all time points and ANCOVAs assessed the biggest change at timepoint 2 while controlling for baseline symptoms. Results and Discussion: The negative temperament group reported greater mood symptoms, burnout, and COVID concern, than positive temperament participants overall, and negative participants' scores decreased over time while positive participants' scores increased over time. Burnout appeared to most strongly mediate this group-by-time interaction, with the burnout exhaustion scale driving anxiety and depression symptoms. PTSD symptoms were also related to COVID-19 health worry and negative temperament. Overall, results suggest that individuals with higher stress-reactions and more negative outlooks on life were at risk for anxiety, depression, and PTSD early in the COVID-19 pandemic, whereas individuals with positive temperament traits became more exhausted and thus more symptomatic over time. Targeting interventions to reduce mood symptoms in negative temperament individuals and prevent burnout/exhaustion in positive temperament individuals early in an extended crisis may be an efficient and effective approach to reduce the mental health burden on essential workers.

MDiGest: A Python package for describing allostery from molecular dynamics simulations.

Many biological processes are regulated by allosteric mechanisms that communicate with distant sites in the protein responsible for functionality. The binding of a small molecule at an allosteric site typically induces conformational changes that propagate through the protein along allosteric pathways regulating enzymatic activity. Elucidating those communication pathways from allosteric sites to orthosteric sites is, therefore, essential to gain insights into biochemical processes. Targeting the allosteric pathways by mutagenesis can allow the engineering of proteins with desired functions. Furthermore, binding small molecule modulators along the allosteric pathways is a viable approach to target reactions using allosteric inhibitors/activators with temporal and spatial selectivity. Methods based on network theory can elucidate protein communication networks through the analysis of pairwise correlations observed in molecular dynamics (MD) simulations using molecular descriptors that serve as proxies for allosteric information. Typically, single atomic descriptors such as α-carbon displacements are used as proxies for allosteric information. Therefore, allosteric networks are based on correlations revealed by that descriptor. Here, we introduce a Python software package that provides a comprehensive toolkit for studying allostery from MD simulations of biochemical systems. MDiGest offers the ability to describe protein dynamics by combining different approaches, such as correlations of atomic displacements or dihedral angles, as well as a novel approach based on the correlation of Kabsch-Sander electrostatic couplings. MDiGest allows for comparisons of networks and community structures that capture physical information relevant to allostery. Multiple complementary tools for studying essential dynamics include principal component analysis, root mean square fluctuation, as well as secondary structure-based analyses.

Race differences in cardiac testing rates for patients with chest pain in a multisite cohort.

BACKGROUND: Identifying and eliminating racial health care disparities is a public health priority. However, data evaluating race differences in emergency department (ED) chest pain care are limited. METHODS: We conducted a secondary analysis of the High-Sensitivity Cardiac Troponin T to Optimize Chest Pain Risk Stratification (STOP-CP) cohort, which prospectively enrolled adults with symptoms suggestive of acute coronary syndrome without ST-elevation from eight EDs in the United States from 2017 to 2018. Race was self-reported by patients and abstracted from health records. Rates of 30-day noninvasive testing (NIT), cardiac catheterization, revascularization, and adjudicated cardiac death or myocardial infarction (MI) were determined. Logistic regression was used to evaluate the association between race and 30-day outcomes with and without adjustment for potential confounders. RESULTS: Among 1454 participants, 42.3% (615/1454) were non-White. At 30 days NIT occurred in 31.4% (457/1454), cardiac catheterization in 13.5% (197/1454), revascularization in 6.0% (87/1454), and cardiac death or MI in 13.1% (190/1454). Among Whites versus non-Whites, NIT occurred in 33.8% (284/839) versus 28.1% (173/615; odds ratio [OR] 0.76, 95% confidence interval [CI] 0.61-0.96) and catheterization in 15.9% (133/839) versus 10.4% (64/615; OR 0.62, 95% CI 0.45-0.84). After covariates were adjusted for, non-White race remained associated with decreased 30-day NIT (adjusted OR [aOR] 0.71, 95% CI 0.56-0.90) and cardiac catheterization (aOR 0.62, 95% CI 0.43-0.88). Revascularization occurred in 6.9% (58/839) of Whites versus 4.7% (29/615) of non-Whites (OR 0.67, 95% CI 0.42-1.04). Cardiac death or MI at 30 days occurred in 14.2% of Whites (119/839) versus 11.5% (71/615) of non-Whites (OR 0.79 95% CI 0.57-1.08). After adjustment there was still no association between race and 30-day revascularization (aOR 0.74, 95% CI 0.45-1.20) or cardiac death or MI (aOR 0.74, 95% CI 0.50-1.09). CONCLUSIONS: In this U.S. cohort, non-White patients were less likely to receive NIT and cardiac catheterization compared to Whites but had similar rates of revascularization and cardiac death or MI.

Personalized diagnosis in suspected myocardial infarction.

BACKGROUND: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays. METHODS: In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability (ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients. RESULTS: Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline-recommended strategy. CONCLUSION: We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care. TRIAL REGISTRATION NUMBERS: Data of following cohorts were used for this project: BACC ( www. CLINICALTRIALS: gov ; NCT02355457), stenoCardia ( www. CLINICALTRIALS: gov ; NCT03227159), ADAPT-BSN ( www.australianclinicaltrials.gov.au ; ACTRN12611001069943), IMPACT ( www.australianclinicaltrials.gov.au , ACTRN12611000206921), ADAPT-RCT ( www.anzctr.org.au ; ANZCTR12610000766011), EDACS-RCT ( www.anzctr.org.au ; ANZCTR12613000745741); DROP-ACS ( https://www.umin.ac.jp , UMIN000030668); High-STEACS ( www. CLINICALTRIALS: gov ; NCT01852123), LUND ( www. CLINICALTRIALS: gov ; NCT05484544), RAPID-CPU ( www. CLINICALTRIALS: gov ; NCT03111862), ROMI ( www. CLINICALTRIALS: gov ; NCT01994577), SAMIE ( https://anzctr.org.au ; ACTRN12621000053820), SEIGE and SAFETY ( www. CLINICALTRIALS: gov ; NCT04772157), STOP-CP ( www. CLINICALTRIALS: gov ; NCT02984436), UTROPIA ( www. CLINICALTRIALS: gov ; NCT02060760).

The potential of trait data to increase the availability of bioindicators: A case study using plant conservatism values.

Biological indicators are commonly used to evaluate ecosystem condition. However, their use is often constrained by the availability of information with which to assign species-specific indicator values, which reflect species' responses to the environmental conditions being evaluated by the indicator. As these responses are driven by underlying traits, and trait data for numerous species are available in publicly accessible databases, one possible approach to approximating missing bioindicator values is through traits. We used the Floristic Quality Assessment (FQA) framework and its component indicator of disturbance sensitivity, species-specific ecological conservatism scores (C-scores), as a study system to test the potential of this approach. We tested the consistency of relationships between trait values and expert-assigned C-scores and the trait-based predictability of C-scores across five regions. Furthermore, as a proof-of-concept exercise, we used a multi-trait model to try to reconstruct C-scores, and compared the model predictions to expert-assigned scores. Out of 20 traits tested, there was evidence of regional consistency for germination rate, growth rate, propagation type, dispersal unit, and leaf nitrogen. However, the individual traits showed low predictability (R2 = 0.1-0.2) for C-scores, and a multi-trait model produced substantial classification errors; in many cases, >50% of species were misclassified. The mismatches may largely be explained by the inability to generalize regionally varying C-scores from geographically neutral/naive trait data stored in databases, and the synthetic nature of C-scores. Based on these results, we recommend possible next steps for expanding the availability of species-based bioindication frameworks such as the FQA. These steps include increasing the availability of geographic and environmental data in trait databases, incorporating data about intraspecific trait variability into these databases, conducting hypothesis-driven investigations into trait-indicator relationships, and having regional experts review our results to determine if there are patterns in the species that were correctly or incorrectly classified.

Mapping N- to C-terminal allosteric coupling through disruption of a putative CD74 activation site in D-dopachrome tautomerase.

The macrophage migration inhibitory factor (MIF) protein family consists of MIF and D-dopachrome tautomerase (also known as MIF-2). These homologs share 34% sequence identity while maintaining nearly indistinguishable tertiary and quaternary structure, which is likely a major contributor to their overlapping functions, including the binding and activation of the cluster of differentiation 74 (CD74) receptor to mediate inflammation. Previously, we investigated a novel allosteric site, Tyr99, that modulated N-terminal catalytic activity in MIF through a "pathway" of dynamically coupled residues. In a comparative study, we revealed an analogous allosteric pathway in MIF-2 despite its unique primary sequence. Disruptions of the MIF and MIF-2 N termini also diminished CD74 activation at the C terminus, though the receptor activation site is not fully defined in MIF-2. In this study, we use site-directed mutagenesis, NMR spectroscopy, molecular simulations, in vitro and in vivo biochemistry to explore the putative CD74 activation region of MIF-2 based on homology to MIF. We also confirm its reciprocal structural coupling to the MIF-2 allosteric site and N-terminal enzymatic site. Thus, we provide further insight into the CD74 activation site of MIF-2 and its allosteric coupling for immunoregulation.

Performance of the European Society of Cardiology 0/1-Hour Algorithm With High-Sensitivity Cardiac Troponin T Among Patients With Known Coronary Artery Disease.

Importance: The European Society of Cardiology (ESC) 0/1-hour algorithm is a validated high-sensitivity cardiac troponin (hs-cTn) protocol for emergency department patients with possible acute coronary syndrome. However, limited data exist regarding its performance in patients with known coronary artery disease (CAD; prior myocardial infarction [MI], coronary revascularization, or ≥70% coronary stenosis). Objective: To evaluate and compare the diagnostic performance of the ESC 0/1-hour algorithm for 30-day cardiac death or MI among patients with and without known CAD and determine if the algorithm could achieve the negative predictive value rule-out threshold of 99% or higher. Design, Setting, and Participants: This was a preplanned subgroup analysis of the STOP-CP prospective multisite cohort study, which was conducted from January 25, 2017, through September 6, 2018, at 8 emergency departments in the US. Patients 21 years or older with symptoms suggestive of acute coronary syndrome without ST-segment elevation on initial electrocardiogram were included. Analysis took place between February and December 2022. Interventions/Exposures: Participants with 0- and 1-hour high-sensitivity cardiac troponin T (hs-cTnT) measures were stratified into rule-out, observation, and rule-in zones using the ESC 0/1-hour hs-cTnT algorithm. Main Outcomes and Measures: Cardiac death or MI at 30 days determined by expert adjudicators. Results: During the study period, 1430 patients were accrued. In the cohort, 775 individuals (54.2%) were male, 826 (57.8%) were White, and the mean (SD) age was 57.6 (12.8) years. At 30 days, cardiac death or MI occurred in 183 participants (12.8%). Known CAD was present in 449 (31.4%). Among patients with known CAD, the ESC 0/1-hour algorithm classified 178 of 449 (39.6%) into the rule-out zone compared with 648 of 981 (66.1%) without CAD (P < .001). Among rule-out zone patients, 30-day cardiac death or MI occurred in 6 of 178 patients (3.4%) with known CAD and 7 of 648 (1.1%) without CAD (P < .001). The negative predictive value for 30-day cardiac death or MI was 96.6% (95% CI, 92.8-98.8) among patients with known CAD and 98.9% (95% CI, 97.8-99.6) in patients without known CAD (P = .04). Conclusions and Relevance: Among patients with known CAD, the ESC 0/1-hour hs-cTnT algorithm was unable to safely exclude 30-day cardiac death or MI. This suggests that clinicians should be cautious if using the algorithm in patients with known CAD. The negative predictive value was significantly higher in patients without a history of CAD but remained less than 99%.

Technological Advances in Spine Surgery: Navigation, Robotics, and Augmented Reality.

Accurate screw placement is critical to avoid vascular or neurologic complications during spine surgery and to maximize fixation for fusion and deformity correction. Computer-assisted navigation, robotic-guided spine surgery, and augmented reality surgical navigation are currently available technologies that have been developed to improve screw placement accuracy. The advent of multiple generations of new technologies within the past 3 decades has presented surgeons with a diverse array of choices when it comes to pedicle screw placement. Considerations for patient safety and optimal outcomes must be paramount when selecting a technology.

Valproate-coenzyme A conjugate blocks opening of receptor binding domains in the spike trimer of SARS-CoV-2 through an allosteric mechanism.

The receptor-binding domains (RBDs) of the SARS-CoV-2 spike trimer exhibit "up" and "down" conformations often targeted by neutralizing antibodies. Only in the "up" configuration can RBDs bind to the ACE2 receptor of the host cell and initiate the process of viral multiplication. Here, we identify a lead compound (3-oxo-valproate-coenzyme A conjugate or Val-CoA) that stabilizes the spike trimer with RBDs in the down conformation. Val-CoA interacts with three R408 residues, one from each RBD, which significantly reduces the inter-subunit R408-R408 distance by ∼ 13 Å and closes the central pore formed by the three RBDs. Experimental evidence is presented that R408 is part of a triggering mechanism that controls the prefusion to postfusion state transition of the spike trimer. By stabilizing the RBDs in the down configuration, this and other related compounds can likely attenuate viral transmission. The reported findings for binding of Val-CoA to the spike trimer suggest a new approach for the design of allosteric antiviral drugs that do not have to compete for specific virus-receptor interactions but instead hinder the conformational motion of viral membrane proteins essential for interaction with the host cell. Here, we introduce an approach to target the spike protein by identifying lead compounds that stabilize the RBDs in the trimeric "down" configuration. When these compounds trimerize monomeric RBD immunogens as co-immunogens, they could also induce new types of non-ACE2 blocking antibodies that prevent local cell-to-cell transmission of the virus, providing a novel approach for inhibition of SARS-CoV-2.

Derivation and validation of a high sensitivity troponin-T HEART pathway.

BACKGROUND: The HEART Pathway is widely used for chest pain risk stratification but has yet to be optimized for high sensitivity troponin T (hs-cTnT) assays. METHODS: We conducted a secondary analysis of STOP-CP, a prospective cohort study enrolling adult ED patients with symptoms suggestive of acute coronary syndrome at 8 sites in the United States (US). Patients had a 0- and 1-hour hs-cTnT measured and a HEAR score completed. A derivation set consisting of 729 randomly selected participants was used to derive a hs-cTnT HEART Pathway with rule-out, observation, and rule-in groups for 30-day cardiac death or myocardial infarction (MI). Optimal baseline and 1-hour troponin cutoffs were selected using generalized cross validation to achieve a negative predictive value (NPV) >99% for rule out and positive predictive value (PPV) >60% or maximum Youden index for rule-in. Optimal 0-1-hour delta values were derived using generalized cross validation to maximize the NPV for the rule-out group and PPV for the rule-in group. The hs-cTnT HEART Pathway performance was validated in the remaining cohort (n = 723). RESULTS: Among the 1452 patients, 30-day cardiac death or MI occurred in 12.7% (184/1452). Within the derivation cohort the optimal hs-cTnT HEART Pathway classified 36.5% (266/729) into the rule-out group, yielding a NPV of 99.2% (95% CI: 98.2-100) for 30-day cardiac death or MI. The rule-in group included 15.4% (112/729) with a PPV of 55.4% (95% CI: 46.2-64.6). In the validation cohort, the hs-cTnT HEART Pathway ruled-out 37.6% (272/723), of which 2 had 30-day cardiac death or MI, yielding a NPV of 99.3% (95% CI: 98.3-100). The rule-in group included 14.5% (105/723), yielding a PPV of 57.1% (95% CI: 47.7-66.6). CONCLUSIONS: A novel hs-cTnT HEART Pathway with serial 0- and 1-hour hs-cTnT measures has high NPV and moderate PPV for 30-day cardiac death or MI.

Protective and risk factors associated with substance use coping among healthcare workers during the COVID-19 pandemic.

Background: Healthcare workers (HCWs) experienced high levels of stress and mental health consequences associated with the COVID-19 pandemic, which may have contributed to unhealthy coping behaviors, such as substance use coping (SUC). This study aimed to understand the extent of and predictors of SUC. Methods: The sample consisted of 263 HCWs in North Central Florida. Univariable and multivariable logistic regression analyses investigated whether moral injury and other work risk factors, protective factors, and clinically relevant symptoms (i.e., work exhaustion, interpersonal disengagement, depression, anxiety, and/or PTSD) were associated with likelihood of SUC. Results: Clinically relevant levels of interpersonal disengagement and anxiety increased the likelihood of SUC. Mediational analyses found that interpersonal disengagement and anxiety explained 54.3% of the relationship between Self Moral Injury and SUC and explained 80.4% of the relationship between professional fulfillment and SUC. Conclusion: Healthcare supervisors should be aware that providers who are experiencing moral injury and less professional fulfillment may be experiencing significant interpersonal disengagement and anxiety, which could lead to SUC. Future studies should examine the effects of implementing targeted prevention and treatment interventions, along with longitudinal outcomes related to SUC behaviors.

Opioid use after elective spine surgery: Do spine surgery patients consume less than prescribed today?

Background: The opioid epidemic in the US has led prescribers to reevaluate postoperative pain control particularly in the field of spine surgery, where postoperative analgesia requirements and consumption have historically been high. There is a need to mitigate the quantity of unused pills after surgery by adjusting prescribing practices. Achieving the balance of pain control after surgery without overprescribing opioids may be accomplished by developing a modified approach to prescribing practices; however, there is a need to first understand the opioid requirements of the modern spine surgery patient with respect to their elective spine surgery. Therefore, the primary aim of this study was to determine the percentage of opioids not utilized at 90-days after elective spine surgery. Secondary aims were to identify differences in the percentage of unused opioids between surgical subgroups and preoperative opioid status, to determine factors associated with opioid utilization, and to estimate the distribution of opioids consumed to control pain up to the 90th percentile in each surgical subgroup. Methods: In this prospective, observational cohort study, adults undergoing elective spine surgery at a multi-surgeon, single center were prospectively enrolled and divided into subgroups: anterior cervical, lumbar decompression, and short-segment lumbar fusion. Prescribed MMEs were identified from prescriptions, consumed MMEs were obtained from pill counts, and the percent leftover was calculated. Distributions of MMEs consumed were analyzed to compare utilization between preoperative opioid users or non-users within each surgical subgroup. Results: Of 117 patients, 41.9% were preoperative opioid users. The percentage of unused opioids by surgical subgroup was: 45.4% cervical, 57.3% lumbar decompression, and 37.4% lumbar fusion (p=0.066). The percentage of unused opioids by preoperative opioid exposure was greater in the opioid non-users (58.0%) than users (28.4%, p<0.001)). Regression analysis showed that surgical subgroup and preoperative opioid exposure were associated with leftover opioids. Conclusions: At 90-days, the percentage of unused opioids was over 45% in this cohort of elective spine surgery patients and was nearly double in the group without preoperative opioid exposure. These results suggest the modern elective spine surgery patient is using less opioids than prescribed, supporting the conclusion that the number of MMEs prescribed can be reduced to minimize quantities of leftover pills available for diversion, without sacrificing the priority of appropriate postoperative pain control.