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Individual differences in delay discounting—how much we discount future compared to immediate rewards—are associated with general life outcomes, psychopathology, and obesity. Here, we use machine learning on fMRI activity during an intertemporal choice task to develop a functional brain marker of these individual differences in human adults. Training and cross-validating the marker in one dataset (Study 1,N = 110 male adults) resulted in a significant prediction–outcome correlation (r = 0.49), generalized to predict individual differences in a completely independent dataset (Study 2:N = 145 male and female adults,r = 0.45), and predicted discounting several weeks later. Out-of-sample responses of the functional brain marker, but not discounting behavior itself, differed significantly between overweight and lean individuals in both studies, and predicted fasting-state blood levels of insulin, c-peptide, and leptin in Study 1. Significant predictive weights of the marker were found in cingulate, insula, and frontoparietal areas, among others, suggesting an interplay among regions associated with valuation, conflict processing, and cognitive control. This new functional brain marker is a step toward a generalizable brain model of individual differences in delay discounting. Future studies can evaluate it as a potential transdiagnostic marker of altered decision-making in different clinical and developmental populations.SIGNIFICANCE STATEMENTPeople differ substantially in how much they prefer smaller sooner rewards or larger later rewards such as spending money now versus saving it for retirement. These individual differences are generally stable over time and have been related to differences in mental and bodily health. What is their neurobiological basis? We applied machine learning to brain-imaging data to identify a novel brain activity pattern that accurately predicts how much people prefer sooner versus later rewards, and which can be used as a new brain-based measure of intertemporal decision-making in future studies. The resulting functional brain marker also predicts overweight and metabolism-related blood markers, providing new insight into the possible links between metabolism and the cognitive and brain processes involved in intertemporal decision-making.

The purpose of this study was to determine how malingered PTSD behavior affects the performance of a continuous performance task (CPT). An analog trauma group, two malingering groups (with or without educational intervention), and a control group were organized according to simulation design. During the CPT, the numbers of errors and response time indicators along with post-error slowing (PES) and recovery (PER) process were measured. Results are as follows: First, the analog trauma group showed deficits of response inhibition and a higher level of PES compared to the control group. Second, malingered PTSD caused a significant number of errors, inconsistent performance, and no PES. Third, there was a significantly more impaired and inconsistent performance in the low level of knowledge of disability. Finally, a discriminant accuracy of more than 90% appeared in the discriminant analysis of all group comparison conditions. Taken together, the results of this study show that post-error behavior indicators are affected by malingered PTSD, and differences according to the degree of knowledge of PTSD can also be confirmed. These results are expected to be used as basic data for the development of tasks for the detection of malingerers in clinical scenes in the future.

Since traditional derivative-based optimization for noisy simulation shows bad performance, evolutionary algorithms are considered as substitutes. Especially in case when outputs are binary, more simulation trials are needed to get near-optimal solution since the outputs are discrete and have high and heterogeneous variance. In this paper, we propose a genetic algorithm called SARAGA which adopts dynamic resampling and fitness approximation using surrogate. SARAGA reduces unnecessary numbers of expensive simulations to estimate success probabilities estimated from binary simulation outputs. SARAGA allocates number of samples to each solution dynamically and sometimes approximates the fitness without additional expensive experiments. Experimental results show that this novel approach is effective and proper hyper parameter choice of surrogate and resampling can improve the performance of algorithm.

Purpose Breast cancer has been reported to be common in middle-age, but little is known about the relationship between menopausal stage and the severity of chemotherapy-induced nausea and vomiting (CINV) in breast cancer patients. Therefore, we examined the association between menopausal stage and CINV severity.Methods Participants were prospectively enrolled from a tertiary general hospital. We evaluated CINV severity of 187 breast cancer patients receiving adjuvant chemotherapy, using a Likert scale from 1 to 10, before chemotherapy (W0), 4 weeks after the first chemotherapy (W4), and 12 weeks (W12) after the first chemotherapy. Premenopause, perimenopause, and postmenopause period were classified by age 45 and 55 years, respectively. CINV severity at different time-points and change values in CINV severity (cCIN, cCIV) at each time point, relative to W0, were compared using a linear mixed modelResults Significant group-by-time interactions were observed for CIN (p = 0.011), CIV (p = 0.027), and cCIN (p = 0.030). In postmenopausal period women, unlike in premenopausal and perimenopausal period women, the mean change values for CIN and CIV at each time point relative to W0 were not significantly different. In the post-hoc analysis, there was a significant difference (p = 0.007) in cCIN at W4 between perimenopausal and postmenopausal period women.Conclusions Changes in CINV severity in breast cancer patients follow different patterns according to menopausal stage. Perimenopausal period women seem to be particularly susceptible to CINV. During chemotherapy, it is necessary to manage CINV with consideration of menopausal stage.

This systematic review was conducted to evaluate any interventions to prevent incident delirium, or shorten the duration of prevalent delirium, in older adults presenting to the emergency department (ED).Health sciences librarian designed electronic searches were conducted from database inception through September 2021. Two authors reviewed studies, and included studies that evaluated interventions for the prevention and/or treatment of delirium and excluded non-ED studies. The risk of bias (ROB) was evaluated by the Cochrane ROB tool or the Newcastle-Ottawa (NOS) scale. Meta-analysis was conducted to estimate a pooled effect of multifactorial programs on delirium prevention.Our search strategy yielded 11,900 studies of which 10 met study inclusion criteria. Two RCTs evaluated pharmacologic interventions for delirium prevention; three non-RCTs employed a multi-factorial delirium prevention program; three non-RCTs evaluated regional anesthesia for hip fractures; and one study evaluated the use of Foley catheter, medication exposure, and risk of delirium. Only four studies demonstrated a significant impact on delirium incidence or duration of delirium-one RCT of melatonin reduced the incidence of delirium (OR 0.19, 95% CI 0.06 to 0.62), one non-RCT study on a multi-factorial program decreased inpatient delirium prevalence (41% to 19%) and the other reduced incident delirium (RR 0.37, 95% CI 0.22 to 0.61). One case-control study on the use of ED Foley catheters in the ED increased the duration of delirium (proportional OR 3.1, 95% CI 1.3 to 7.4). A pooled odds ratio for three multifactorial programs on delirium prevention was 0.46 (95% CI 0.31-0.68, IFew interventions initiated in the ED were found to consistently reduce the incidence or duration of delirium. Delirium prevention and treatment trials in the ED are still rare and should be prioritized for future research.

Throughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available.This systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19.Searches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and May 2021 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized.A primary review found 445 articles relevant based on title and abstract. After further review, 366 were excluded based on the defined inclusion and exclusion criteria. Seventy-nine articles were included in the qualitative analysis. Inter observer agreement on inclusion 0.84 (95%CI 0.78-0.89). When the PROBAST tool was applied, 70 of the 79 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Nine studies reported prediction models that were rated as low risk of bias and low concerns for applicability.Several prognostic models for COVID-19 were identified, with varying clinical score performance. Nine studies that had a low risk of bias and low concern for applicability, one from a general public population and hospital setting. The most promising and well-validated scores include Clift et al.

Why do people discount future rewards? Multiple theories in psychology argue that one reason is that future events are imagined less vividly than immediate events, thereby diminishing their perceived value. Here we provide neuroscientific evidence for this proposal. First, we construct a neural signature of the vividness of prospective thought, using an fMRI dataset where the vividness of imagined future events is orthogonal to their valence by design. Then, we apply this neural signature in two additional fMRI datasets, each using a different delay-discounting task, to show that neural measures of vividness decline as rewards are delayed farther into the future.

Delirium, altered mental status (AMS), or confusion among older adults are common presentations to the emergency department (ED). We aimed to report the proportion of older ED patients presenting with delirium who have acute abnormal findings on head imaging. We also assessed whether anticoagulation, neurological deficits, trauma, or headache were associated with head imaging abnormalities in these patients.A systematic review was performed using Ovid Medline, Embase, Clinicaltrials.gov, Web of Science, and Cochrane Central from conception to April 8, 2021. Citations were included if they described patients aged 65 years or older who received neuroimaging at the time of ED assessment for delirium, confusion, or AMS. Screening, data extraction, and bias assessment were performed in duplicate. The estimated proportion of patients with abnormal neuroimaging and odds ratios (ORs) for each predictor were calculated.The search strategy identified 3014 unique citations, of which six studies reporting on 909 patients with confusion or AMS were included. None of the studies formally diagnosed delirium. Overall, the proportions of older ED patients with AMS or confusion were found to have an abnormal head computed tomography (CT) was 15.6% (95% confidence interval [CI] 7.3%-26.2%). The prevalence of focal neurologic findings was 13.0% (66/506) and for anticoagulation was 9.8% (33/337) among the studies who reported them. The presence of a focal neurological deficit was associated with abnormal head CT (OR 101.8, 95% CI 30.5-340.1). Anticoagulation was not associated with abnormal head CT (OR 1.2, 95% CI 0.4-3.3). No studies reported on the association between headache or trauma and abnormal neuroimaging.The proportion of abnormal findings on CT neuroimaging in older ED patients with AMS or confusion was 15.6%. The presence of a focal neurological deficit was a strong predictor for the presence of acute abnormality, whereas anticoagulation was not.

OBJECTIVES: The objective was to evaluate the impact of an emergency psychiatric assessment, treatment, and healing (EmPATH) unit in the emergency department (ED) on hospital admissions, ED length of stay, and 30-day follow-up for patients presenting with suicidal ideation or attempt. METHODS: This study was a before-and-after analysis of introducing the EmPATH unit within a Midwestern academic medical center on outcomes of adult patients (≥18 years) presenting with suicidal ideation or suicidal attempt. The primary outcome in this study was the change in proportion of inpatient psychiatric admission of suicidal patients presenting to the ED before and after implementation of the EmPATH unit. Secondary outcomes compared were changes in proportion of any admission, incomplete admission defined as discharge from the ED after admission request placed, outpatient follow-up, return ED visits within 30 days of admission, and ED boarding time. Association between the EmPATH unit implementation and categorical outcomes were determined using log-binomial regression to estimate relative risks (RRs) and 95% confidence intervals (CIs). Continuous outcomes were log-transformed and generalized estimating equations were used to examine as the mean difference by time period. RESULTS: There were 962 patients presenting with suicidal ideation (n = 435 before EmPATH unit, n = 527 after EmPATH unit). Compared to the pre-EmPATH-unit period, there was a reduction in psychiatric admission (RR = 0.48, 95% CI = 0.40 to 0.56), any admission (RR = 0.65, 95% CI = 0.58 to 0.73), incomplete admission (RR = 0.22, 95% CI = 0.11 to 0.43), and 30-day return to the ED (RR = 0.74, 95% CI = 0.56 to 0.98). ED boarding time among admitted patients was reduced by approximately two-thirds both in admitted patients (RR = 0.34, 95% CI = 0.30 to 0.39) and among those with incomplete admissions (RR = 0.37, 95% CI = 0.23 to 0.61). There was a 60% increase in a 30-day follow-up care established at the time of discharge (RR = 1.60, 95% CI = 1.40 to 1.82). CONCLUSIONS: The introduction of the EmPATH unit has improved management of patients presenting to the ED with suicidal attempts/ideation by reducing ED boarding and unnecessary admissions and establishing post-ED follow-up care.

Introduction: Mental health and substance use disorder (MHSUD) patients in the emergency department (ED) have been facing increasing lengths of stay due to a shortage of inpatient beds. Previous research indicates mobile crisis outreach (MCO) reduces long ED stays for MHSUD patients. Our objective was to assess the impact of MCO contact on future ED utilization. Methods: We conducted a retrospective chart review of patients presenting to a large Midwest university ED with an MHSUD chief complaint from 2015–2018. We defined the exposure as those who had MCO contact and any MHSUD-related ED visit within 30 days of MCO contact. The MCO patients were 2:1 propensity score–matched by demographic data and comorbidities matched to patients with no MCO contact. Outcomes were all-cause and psychiatric-specific reasons for return to the ED within one year of the index ED visit. We report descriptive statistics and odds ratios (OR) to describe the difference between the two groups, and hazard ratios (HR) to estimate the risk of return ED visit. Results: The final sample included 106 MCO and 196 non-MCO patients. The MCO patients were more likely to be homeless (OR 14.8; 95% confidence interval [CI],1.87, 117), less likely to have adequate family or social support (OR 0.51; 95% CI, 0.31, 0.84), and less likely to have a hospital bed requested for them in the index visit by ED providers (OR 0.50; 95% CI, 0.29, 0.88). For those who returned to the ED, the median time for all-cause return to the ED was 28 days (interquartile range [IQR]: 6–93 days) for the MCO patients and 88 days (IQR: 20–164 days) for non-MCO patients. The risk of all-cause return to the ED was greater among MCO patients (67%) compared to non-MCO patients (49%) (adjusted HR: 1.66; 95% CI, 1.22, 2.27). Conclusion: The MCO patients had less family and social support; however, they were less likely to require hospitalization for each visit, likely due to MCO involvement. Patients with MCO contact presented to the ED more frequently than non-MCO patients, which implies a strong linkage between the ED and MCO in our community. An effective referral to community service from the ED and MCO and collaboration could be the next step to improve healthcare utilization.

It has been suggested that aging and inflammation play key roles in the development of delirium. In the present study, we investigated the differences of the DNAm patterns in the TNF gene between patients with delirium and without. The data and samples derived from previous and ongoing cohort studies were analyzed. DNAm levels of the TNF gene were analyzed using the Illumina EPIC array genome-wide method and pyrosequencing method. Correlations between age and DNAm levels of each CpG were calculated. Several CpG in the TNF gene in blood showed negative correlation between their DNAm and age in delirium cases both with the EPIC array and by the pyrosequencing method. However, there was no CpG that had significant correlation between their DNAm and age regardless of delirium status among buccal samples. On the other hand, among peripheral blood mononuclear cells samples, it was found that several CpG showed negative correlation between their DNAm and age in delirium cases. The evidence of DNAm change in the TNF gene among delirious subjects was demonstrated.

Motivation plays a critical role in human cognitive function, while acting as a driving force for the necessary behavior to achieve a desired goal and success (i.e., achievement motivation). Based on the theoretical background of achievement motivation, this study designed an incentive delay task with four motivational orientations (i.e., promotion, prevention, mastery/self, and performance/other). To investigate whether people would have their behavioral patterns toward achievement motivation orientation, we applied an unsupervised clustering algorithm to classify individuals’ behavioral responses acquired from the task by categorizing certain behavioral similarities. As a result, this hierarchical clustering approach classified subjects into two distinctive subgroups: Group#1 (i.e., the pro/pre group, n = 52) and Group#2 (i.e., the self/other group, n = 48). Based on clustering, Group#1 showed significantly better performance with promotion/prevention orientations, whereas Group#2 exhibited significantly higher performance with self/other orientations. Structural brain analyses discovered increased gray matter volume and sulcal depth in the posterior parietal cortex (PPC) in the pro/pre group compared to the self/other group. With resting-state functional magnetic resonance imaging data, we found higher local brain fluctuations in the medial prefrontal cortex (mPFC) in the self/other group compared to the pro/pre group. Furthermore, mPFC seed-based functional connectivity showed significantly increased functional coupling with the posterior cingulate cortex in the self/other group relative to the pro/pre group. Taken together, these results shed light on structural and functional neural mechanisms related to achievement motivation and, furthermore, provide novel insights regarding PPC’s role in motivational processing toward promotion- and prevention-focused orientation.

As the population of older adults increases, appropriate deprescribing becomes increasingly important for emergency geriatric care. Older adults represent the sickest patients with chronic medical conditions, and they are often exposed to high-risk medications. We need to provide an evidence-based, standardized deprescribing program in the acute care setting, yet the evidence base is lacking and standardized medication programs are needed.We conducted a qualitative study with the goal to understand the perspective of healthcare workers, patients, and caregivers on deprescribing high-risk medications in the context of emergency care practices, provider preferences, and practice variability, along with the facilitators and barriers to an effective deprescribing program in the emergency department (ED). To ensure rich, contextual data, the study utilized two qualitative methods: (1) a focus group with physicians, advanced practice providers, nurses, pharmacists, and geriatricians involved in care of older adults and their prescriptions in the acute care setting; (2) semi-structured interviews with patients and caregivers involved in treatment and emergency care. Transcriptions were coded using thematic content analysis, and the principal investigator (S.L.) and trained research staff categorized each code into themes.Data collection from a focus group with healthcare workers (n = 8) and semi-structured interviews with patients and caregivers (n = 20) provided evidence of a potentially promising ED medication program, aligned with the vision of comprehensive care of older adults, that can be used to evaluate practices and develop interventions. We identified four themes: (1) Challenges in medication history taking, (2) missed opportunities in identifying high-risk medications, (3) facilitators and barriers to deprescribing recommendations, and (4) how to coordinate deprescribing recommendations.Our focus group and semi-structured interviews resulted in a framework for an ED medication program to screen, identify, and deprescribe high-risk medications for older adults and coordinate their care with primary care providers.

Metformin has been reported to improve age-related disorders, including dementia, and to lower mortality. This study was conducted to investigate whether metformin use lower delirium risk, as well as long-term mortality.In this retrospective cohort study, previously recruited 1,404 subjects were analyzed. The relationship between metformin use and delirium, and the relationship between metformin use and 3-year mortality were investigated.242 subjects were categorized into a type 2 diabetes mellitus (DM)-without-metformin group, and 264 subjects were categorized into a DM-with-metformin group. Prevalence of delirium was 36.0% in the DM-without-metformin group, and 29.2% in the DM-with-metformin group. A history of metformin use reduced the risk of delirium in patients with DM (OR, 0.50 [95% CI, 0.32 to 0.79]) after controlling for confounding factors. The 3-year mortality in the DM-without-metformin group (survival rate, 0.595 [95% CI, 0.512 to 0.669]) was higher than in the DM-with-metformin group (survival rate, 0.695 [95% CI, 0.604 to 0.770]) (p=0.035). A history of metformin use decreased the risk of 3-year mortality after adjustment for confounding factors (HR, 0.69 [95% CI, 0.48 to 0.98]).Metformin use may lower the risk of delirium and mortality in DM patients.

ObjectiveTo investigate the relationship between history of metformin use and delirium risk, as well as long-term mortality.MethodsIn this retrospective cohort study, subjects recruited between January 2016 and March 2020 were analyzed. Logistic regression analysis was performed to investigate the relationship between metformin use and delirium. Log-rank analysis and Cox proportional hazards model were used to investigate the relationship between metformin use and 3-year mortality.ResultsThe data from 1404 subjects were analyzed. 242 subjects were categorized into a DM-without-metformin group, and 264 subjects were categorized into a DM-with-metformin group. Prevalence of delirium was 36.0% in the DM-without-metformin group, and 29.2% in the DM-with-metformin group. A history of metformin use reduced the risk of delirium in patients with DM (OR, 0.50 [95% CI, 0.32 to 0.79]) after controlling for age, sex, and dementia status, body mass index (BMI), and insulin use. The 3-year mortality in the DM-without-metformin group (survival rate, 0.595 [95% CI, 0.512 to 0.669]) was higher than in the DM-with-metformin group (survival rate, 0.695 [95% CI, 0.604 to 0.770]) (p=0.035). A history of metformin use decreased the risk of 3-year mortality after adjustment for age, sex, Charlson Comorbidity Index, BMI, history of insulin use, and delirium status (HR, 0.69 [95% CI, 0.48 to 0.98]).ConclusionsIt was found that metformin usage was associated with decreased delirium prevalence and lower 3-year mortality. The potential benefit of metformin on delirium risk and mortality were shown.

Main text The CCQM-P172 comparison was designed to evaluate the level of compatibility of laboratories' spectroscopic methods for trace gas quantification using nitric acid (HNO3) as a model system. Because it is present in NO2 gas standards as an impurity, HNO3 was chosen as the analyte for study. As primary reference gas mixtures of HNO3/N2 are (generally) unavailable for calibration, traceability for spectroscopic measurements will rely on the use of referenced molecular parameters (such as tabulated in the HITRAN database, acronym for high-resolution transmission molecular absorption database). Laboratories that took part in this pilot study CCQM‐P172 were required to submit one secondary standard of NO2 in nitrogen at a nominal amount fraction of 10 μmol mol−1 with a requirement that the HNO3 amount fraction present in the mixture is between 100 nmol mol−1 and 1000 nmol mol−1. As the mixtures are similar to the ones compared in the Key Comparison CCQM-K74.2018, also coordinated by the BIPM during the same period, a similar linear decrease of the main component NO2 and a correlated linear increase of the major impurity HNO3 was initially foreseen. The CCQM-P172 protocol was designed to deal with standards that followed a well-behaved decay profile, allowing BIPM measurements to be compared to interpolated values for participants' standards. However, as with CCQM-K74.2018, the behavior of the standards deviated from this expectation, showing nonlinear variations of the components. The study was further complicated with deviations from the protocol which have been recorded and described in this report. The complications resulted in a reduced number of analyses by the coordinating laboratory for two of the five participants. The first version of this report distributed in May 2021 between participants described only the measurements performed by the BIPM and the results submitted by participants, without attempting to provide reference values. Nevertheless, a number of important observations and conclusions were drawn as reported below: 1) The BIPM operated two methods for FTIR quantification of HNO3, the first based on direct reference to HITRAN parameters, the second based on calibration with a permeation system. Whilst both methods demonstrate very good correlation and linearity with respect to each other, the HITRAN method provided measurement results 23% higher than for the permeation system calibrated FTIR method. 2) The fitting of HNO3 FTIR spectra was often complicated by the presence of other species, in particular the considerable NO2 absorption band for gas mixtures from cylinders, and the presence of considerable amounts of water in the case of the BIPM permeation calibration gas mixtures in the 1550 cm-1 to 1750 cm-1 spectral window. The effect of the spectral windows used for fitting deserves further consideration. 3) Stabilization of the FTIR signal in the BIPM system (45 m gas cell) with the flows of gas that are permissible from gas cylinders for HNO3 resulted in residual drift in signal that varied between standards submitted, and in the best cases was characterized by an additional uncertainty component with magnitude of 20 nmol mol−1 (standard uncertainty), and a compromise between increased signal sensitivity and its stability. 4) Due to the complications in the study, the set of results obtained, which had sufficiently complete sets of measurements to compare data, were for the cylinders received from NPL and VSL. In the case of the NPL standard, BIPM and NPL FTIR measurements were performed with similar HITRAN based methods, and agreement of results can be concluded if the rise in HNO3 levels can be considered to have stabilized in the standard at the time of measurement at the BIPM. The VSL method fits individual absorption lines within a different band from BIPM and NPL. For the VSL standards the absolute change in HNO3 amount fractions between their measurement periods is of the same order of magnitude as the uncertainties reported for the BIPM FTIR measurement methods. As a result both of the BIPM and the VSL results could be considered in agreement, without being able to readily differentiate for which of the BIPM results the agreement is better. During the GAWG meeting of June 2021, participants agreed to complete the study with the following actions: • reanalysis of participants' FTIR spectra when feasible: CENAM and NPL spectra were reanalysed using the submitted participants parameters, and the recalculated nitric acid mole fractions. Unfortunately, NMISA and KRISS could not provide enough information to reanalyse their spectra. VSL did not use FTIR for the analysis. The reanalysis confirmed good agreement with NPL and revealed differences with CENAM. • reanalysis using different regions: the impact of fitting HNO3 amount fractions in alternative regions, 1240 to 1400 cm-1 and 1240 to 1800 cm-1, was studied. The maximum difference in amount fractions calculated was dependant on the database used. • the Pacific Northwest National Laboratory (PNNL) database was used as alternative infrared database to retrieve HNO3 amount fractions of calibration mixtures produced by the permeation facility. A bias of 6.7 %, contrasting with 23 % identified using HITRAN, was found against HNO3 permeation-based values. Based on the measurements performed at the BIPM using FTIR calibrated with dynamic standards on one hand, and with molecular parameters found in the two databases HITRAN and PNNL, a strategy to further calibrate HNO3 values measured by FTIR in standards of NO2 in nitrogen is proposed. This is based on applying a correction to amount fraction values determined by the FTIR-HITRAN method, with the correction factor determined from the comparison with values from the Permeation system method, considered as the reference method. The corrected FTIR-HITRAN method, with traceability of values to the permeation method, can be applied reproducibly, provided that the FTIR gas cell's pathlength is regularly verified, and the spectral region fitted is defined. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Main text The knowledge of natural gas composition is relevant for custody transfer operations. The determination of its composition is often used as the basis for the calculation of the calorific value. This report is a supplementary comparison organized for the Latin American region at SIM for components from methane to n-hexane, nitrogen, and carbon dioxide with a total of ten components. The traveling standards were obtained from an external source and checked for homogeneity and stability by CENAM before and after the measurements by participants and confirming the values under the involvement of two coordinating laboratories (CENAM and KRISS). The level of uncertainties of this comparison were not the traditional lower uncertainties for natural gas by long-established NMIs. Nevertheless, the results from the comparison are a useful official starting point for the SIM region. All results usually agree at levels higher than 0.6 % with the comparison reference value. The combination of the complexity of the samples being obtained from an external provider, the loss of performance of methods and instruments used by CENAM, and the use of traveling standards all contributed to the unexpectedly higher uncertainties of measurement results of this study. It should also be noted that some participating laboratories did not consider normalizing their results and did not apply all appropriate corrections. For the reference value, all normalized amount fractions have been used and uncertainties propagated appropriately. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Introduction African Americans (AAs) experience disparities in chronic pain care. This study aimed to identify the rates of emergency department (ED) utilization for visits associated with chronic pain diagnoses among AAs compared to Whites and to determine variables that accounted for any differences. Methods This retrospective observational study used national Veterans Affairs (Veteran’s Health Administration) administrative data to identify Veterans with chronic pain diagnoses in 2018. Race/ethnicity was self-reported and assessed to examine if differences exist in ED utilization. Differences between AAs and Whites were examined using negative binomial regression models, controlling for ethnicity. Multivariable models (including demographics, pain characteristics, psychiatric comorbidities, medical comorbidities, pain-related health care utilization, and medication utilization) were examined to determine factors that contributed to these disparities. Results Among the 2,261,030 patients, 22% (n = 492,138) were AA. The incidence rate ratio of ED utilization for AAs, relative to Whites, was 1.58 (95% CI: 1.56–1.59). The only independent variable that produced a clinically meaningful reduction in the race effect on ED use was rurality, which was associated with reduced ED use. Post hoc model including all variables reduced the race effect to 1.37 (95% CI: 1.36–1.38). Conclusion AA Veterans had a 58% greater risk of ED utilization for visits associated with chronic pain diagnoses relative to White Veterans, which remained meaningfully elevated after adjustment for observable confounders (37%). This observation may reflect disparities in outpatient chronic pain care for AAs. Future research could focus on enhancing therapeutic alliance in primary care to improve chronic pain treatment for AAs.

BackgroundWe have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes.AimsTo improve the BSEEG method by introducing a new EEG device.MethodIn a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed.ResultsWe enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality.ConclusionsWe confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

The objective was to measure the impact of the Society for Academic Emergency Medicine Foundation's (SAEMF) Research Training Grant (RTG) by comparing academic success in grant recipients versus non-recipient applicants. Our primary outcome was subsequent federal funding as a principal investigator (PI) or multiple principal investigator (MPI). Our secondary outcomes included subsequent K-award funding, R-series funding, R01 funding, and academic productivity measured by first author peer-reviewed publications.The authors examined all SAEMF RTG applicants from 2002 through 2019 (n = 109). Data were collected using the National Institutes of Health RePORTER database, a literature search using PubMed, and an online survey sent to all RTG applicants. Relative risks (RRs) with 95% confidence intervals (95% CI) were calculated.Over 18 years, 18 of 109 (16.5%) RTG applicants were awarded by SAEMF. Subsequent federal funding as PI or MPI was obtained by 11 of the 18 RTG recipients compared to 29 of the 91 nonrecipients (61% vs. 33%, RR = 1.9; 95% CI = 1.2-3.1). The RTG award was also associated with increased probability of receiving a federal Career Development Award (K-series) (RR 2.0; 95% CI 1.1-3.9) and R-series award (RR 2.0; 95% CI 1.1-3.9) but not an R01 award (RR 2.1; 95% CI 0.8-5.3). The median number of first-authored peer reviewed manuscripts did not differ between RTG award recipients (14, IQR 8,44) and nonrecipients (14, IQR 6,30) (p = 0.5) though RTG recipients had a higher percentage of their publications as a first author (49% vs. 33%, p = 0.04).SAEMF RTG awards were associated with increased probability of future federal funding, including career development awards and R-series awards but not R01 awards. RTG recipients also had a higher percentage of their peer reviewed publications as first author.

Deficits in motivation and pleasure are common across many psychiatric disorders, and manifest as symptoms of amotivation and anhedonia, which are prominent features of both mood and psychotic disorders. Here we provide evidence for an association between neural value signals and symptoms of amotivation and anhedonia across adults with major depression, bipolar disorder, schizophrenia, or no psychiatric diagnosis. We found that value signals in the ventromedial prefrontal cortex (vmPFC) during intertemporal decision-making were dampened in individuals with greater motivational and hedonic deficits, after accounting for primary diagnosis. This relationship remained significant while controlling for diagnosis-specific symptoms of mood and psychosis, such as depression as well as positive and negative symptoms. Our results demonstrate that dysfunction in the vmPFC during value-based decision-making is specifically linked to motivational and hedonic impairments. These findings provide a quantitative neural target for the potential development of novel treatments for amotivation and anhedonia.

Researchers often seek to decode mental states from brain activity measured with functional MRI. Rigorous decoding requires the use of formal neural prediction models, which are likely to be the most accurate if they use the whole brain. However, the computational burden and lack of interpretability of off-the-shelf statistical methods can make whole-brain decoding challenging. Here, we propose a method to build whole-brain neural decoders that are both interpretable and computationally efficient. We extend the partial least squares algorithm to build a regularized model with variable selection that offers a unique "fit once, tune later" approach: users need to fit the model only once and can choose the best tuning parameters post hoc. We show in real data that our method scales well with increasing data size and yields interpretable predictors. The algorithm is publicly available in multiple languages in the hope that interpretable whole-brain predictors can be implemented more widely in neuroimaging research.