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Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.
Quantum field theory predicts a nonlinear response of the vacuum to strong electromagnetic fields of macroscopic extent. This fundamental tenet has remained experimentally challenging and is yet to be tested in the laboratory. A particularly distinct signature of the resulting optical activity of the quantum vacuum is vacuum birefringence. This offers an excellent opportunity for a precision test of nonlinear quantum electrodynamics in an uncharted parameter regime. Recently, the operation of the high-intensity Relativistic Laser at the X-ray Free Electron Laser provided by the Helmholtz International Beamline for Extreme Fields has been inaugurated at the High Energy Density scientific instrument of the European X-ray Free Electron Laser. We make the case that this worldwide unique combination of an X-ray free-electron laser and an ultra-intense near-infrared laser together with recent advances in high-precision X-ray polarimetry, refinements of prospective discovery scenarios and progress in their accurate theoretical modelling have set the stage for performing an actual discovery experiment of quantum vacuum nonlinearity.
In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.
Methods:
A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.
Results:
We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.
Conclusion:
The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.
OBJECTIVES/GOALS: A barrier to the proliferation of team science is that academicians are often trained in disciplinary silos where “independent” research contributions are lauded. To tackle some of the most pressing scientific challenges, dismantling silos and increasing team science training efforts that focus on early career investigators is a must. METHODS/STUDY POPULATION: A team science training workshop for early career investigators from varied disciplinary backgrounds was informed by a 20-item needs assessment that addressed essential team science competencies and was completed by early career investigators participating in federally funded professional development programs on our campus. During the workshop, the benefits of cross-disciplinary teaming was discussed. Strategies including team formation, team effectiveness and/or dysfunction, diagnosing team strengths and weaknesses, and teaming in community settings were discussed. Instructional methods included short presentations, video clips, case studies, group discussions, pair and share activities, and panel discussions with expert role models encouraged active learning. RESULTS/ANTICIPATED RESULTS: The impact and value of the workshop series to participant’s professional development and knowledge of team science concepts will be evaluated before and after the workshop. Multiple Likert-scale items focused on team science competencies (e.g., confidence in your ability to carry out responsibilities specific to your role on a team, recognize when the team is not functioning well; engage team science practices in on-going research), and open-ended questions (e.g., importance of engaging community partners in academic research teams, vision of what factors contribute to an effective team science collaboration) will be completed by program participants before and after completing the workshop. DISCUSSION/SIGNIFICANCE: Effective collaboration among scientists with expertise in different disciplines is needed to address and solve complex scientific problems. We believe our interactive approach to team competency training sessions would work in a variety of settings and improve team skills.
Functional magnetic resonance imaging (fMRI) research has generally focused on drawing conclusions from average brain activation patterns. Importantly, the brain is inherently variable; growing literature has found that within-individual blood oxygen level-dependent (BOLD) signal variability may be meaningful, and not just “noise.” For example, recent research has identified increased BOLD signal variability in healthy younger and older adults during more effortful/complex task loads of n-back paradigms, commonly used tasks that involve important elements of executive function (e.g., attention, working memory, planning, inhibition, etc.). Verbal fluency is a complex cognitive domain that also involves similar processes to generate words given certain rules. As a result, the current study builds on existing literature to investigate within-individual BOLD signal variability patterns in peak coordinates of a verbal fluency network during different loads of a letter n-back task. Due to greater executive demands, greater variability was expected during more effortful/complex n-back task loads in regions of a verbal fluency network.
Participants and Methods:
Forty-eight healthy young adults (Mage(SD) = 22.41(4.47), 25 females) from the Atlanta area completed a letter n-back task in an MRI scanner. After standard processing in AFNI, images were corrected for motion and physiological artifacts, which may be confounding sources of variability. Volumes associated with each load of the letter n-back task (0-back, 1-back, 2-back, 3-back, crosshair) were identified. Task runs were normalized and respective run means were subtracted prior to concatenating all runs for each load type. Standard deviations were calculated across this mean-run corrected time series. Ten peak regions of interest (ROIs) were identified from a verbal fluency network generated from 84 peer-reviewed publications for this domain gathered on NeuroSynth. Paired samples t-tests with Benjamini-Hochberg correction for multiple comparisons were conducted to explore differences in variability during n-back task loads.
Results:
In several of the verbal fluency network ROIs, within-individual BOLD signal variability was significantly greater for 2-back versus 0-back loads with medium to large effect sizes (p’s < .001 - < .01, Cohen’s d range: .53-.93). Variability was also significantly greater for 3-back versus 0-back loads with small to medium effect sizes (p’s < .001 - < .01, Cohen’s d range: .48-.74). Specific regions that evidenced this pattern included ROIs in the left inferior frontal gyrus, left cingulate, right inferior frontal gyrus, left middle frontal gyrus, and left superior parietal lobule. Only two regions demonstrated increased variability in the 1-back load versus crosshair (left middle frontal gyrus, p < .001, d = .63; left lentiform nucleus, p < .05, d = .42). No regions demonstrated a significant difference in variability in the 0-back load versus crosshair.
Conclusions:
This study contributes to growing literature examining within-individual BOLD signal variability in healthy individuals by exploring variability patterns in a verbal fluency network. The observed pattern of results supports the hypothesis and is in line with previous research, demonstrating that greater variability occurs with greater executive task demands. Future research can use an inscanner task of verbal fluency and can extend variability findings during this in-scanner task to out-of-scanner measures of verbal fluency.
Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions.
Aims
To compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness.
Method
Data were collected from individuals aged 18–26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown.
Results
Mental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78–36.57) and 15.6% (95% CI 15.39–15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease.
Conclusions
Healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.
External natural events, such as the COVID-19 pandemic, can contribute to increased stress, depression and anxiety in pregnant persons. Thus far, studies on the impact of maternal mental health during the pandemic on perinatal outcomes have been conflicting.
Objectives
Assess the impact of prenatal mental health during the COVID-19 pandemic on preterm birth (PTB) and low birthweight (LBW).
Methods
Pregnant individuals, >18 years were recruited in Canada, their data were collected through a web-based questionnaire. Our analysis includes data on individuals recruited between 06/2020 and 08/2021, who completed questionnaires at baseline and 2-month post-partum. Data on maternal sociodemographic, comorbidities, medication, mental health measures (Edinburgh Perinatal Depression Scale, General Anxiety Disorder-7, stress), hardship (CONCEPTION study Assessment of Stress from COVID-19 –150 points), gestational age at delivery and birth weight were self-reported. PTB defined as delivery before 37 weeks of gestation. LBW defined as birth weight less than 2,500 grams.
Results
A total of 1,265 and 1,233 participants were included in the analyses of PTB and LBW, respectively. After adjusting for potential confounders, we found no differences between prenatal mental health and PTB ([depression [adjusted RR [aRR] 1.01, CI 95% 0.91 to 1.11], anxiety [aRR 1.04, CI 95% 0.93 to 1.17], stress [aRR 0.88, CI 95% 0.71 to 1.10], hardship [aRR 1.00, CI 95% 0.96 to 1.04]). However, we found that the risk of PTB was increased with ethnicity/race (aRR 3.85, CI 95% 1.35 to 11.00), obstetrician/gynecologist follow-up (aRR 2.77, CI 95% 1.12 to 6.83). We didn’t find any significant association between prenatal mental health and LBW. However, annual household income, previous delivery were associated with a decreased risk of LBW (aRR 0.15, CI 95% 0.05 to 0.49; aRR 0.39, CI 95% 0.20 to 0.77, respectively).
Conclusions
Conclusion: No association was found between prenatal mental health during the COVID-19 pandemic and the risk of PTB or LBW. However, it is imperative to continue the follow-up of mothers and their offspring in order to detect early any long-term health problems.
Psychiatry training programs vary in the degree to which they offer trainees with an opportunity to get involved in research. Exposure to research during the training period is critical, as this is usually when trainees start their own scientific research projects and gain their first experiences in academic publishing.
Objectives
We present the European Journal of Psychiatric Trainees (EJPT) (ejpt.scholasticahq.com), the official journal of the European Federation of Psychiatric Trainees (EFPT), including its scope, mission and vision and practical considerations.
Methods
Reflecting on the foundation and operation of the European Journal of Psychiatric Trainees.
Results
The European Journal of Psychiatric Trainees is an Open Access, double blind peer-reviewed journal which aims to publish original and innovative research as well as clinical, theory, perspective and policy articles, and reviews in the field of psychiatric training, psychiatry and mental health. Its mission is to encourage research on psychiatric training and inspire scientific engagement by psychiatric trainees. Work conducted by psychiatric trainees and studies of training in psychiatry are prioritized. The journal is open to submissions, and while articles from psychiatric trainees are prioritized, submissions within scope from others are also encouraged. The article processing fee is very low and waivable. It is planned to publish two issues yearly.
The first article was published in July 2022, titled “Fluoxetine misuse by snorting in a teenager: a case report” and it received 218 views as of 17 October 2022, which confirms the journal’s potential for visibility.
Conclusions
The European Journal of Psychiatric Trainees is a non-profit initiative designed to offer psychiatric trainees a platform to publish and gain experience in publishing. Thanks to its robust double blind peer reviewing system, it has the potential to contribute to scientific excellence.
The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.
We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.
Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.
Methods
Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.
Results
Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.
Conclusions
Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.
Introduction. People with mental health conditions (MHCs) are less likely to achieve long-term abstinence than people without MHCs. The Quit and Stay Quit Monday (QSQM) model offers a long-term approach to treating tobacco use by encouraging people to quit, requit, or recommit to quit smoking every Monday. Aim. To evaluate the efficacy, patient satisfaction, and patient engagement with an intervention that integrated the QSQM model into multicomponent smoking cessation services among people with an MHC. Methods. This was a randomized controlled pilot trial. Eligibility criteria were as follows: (1) ≥18 years old, (2) smoked a cigarette in the past 30 days, (3) diagnosis of an ICD-10 MHC, (4) interest in quitting smoking, (5) able to receive services in English, and (5) had an active email and a cell phone. The intervention group (n = 33) received QSQM-focused telephone coaching, a weekly QSQM email newsletter, a SmokefreeTXT anchored around a Monday quit date, and 4 weeks of nicotine replacement therapy (NRT). The control group (n = 36) received information about contacting their state Quitline for usual services. Primary outcomes were self-reported quit attempts, 7-day abstinence, and intervention satisfaction at 3 months. Results. Twenty-four participants (73%) in the intervention group began telephone coaching, 26 (79%) enrolled in the QSQM email newsletter, 19 (58%) enrolled in SmokefreeTXT, and 15 (46%) used NRT. Using a penalized intent-to-treat approach, quit attempts in the intervention and control groups were 63.6% and 38.9% (OR 2.75, 95% CI 1.03-7.30), respectively. Seven-day abstinence in the two groups was 12.1% and 5.6% (OR 2.35, 95% CI 0.40-13.74), respectively. Of the 15 intervention group participants who set a quit date during the intervention, 13 (86.7%) selected a Monday quit day. Qualitative interviews revealed positive participant experiences with picking a Monday quit day. On follow-up surveys, 89.5%, 69.3%, and 64.3% of intervention participants reported that the counseling, QSQM email, and text messaging, respectively, were very or somewhat helpful. Conclusions. The QSQM model was acceptable and potentially efficacious among people with MHCs, but intervention engagement and satisfaction were modest. Future research should adapt or develop new QSQM delivery approaches to improve patient engagement and potential efficacy of the model. This trial is registered with clinicaltrials.gov (NCT04512248).
The serotonin (5-HT) hypothesis of anorexia nervosa (AN) posits that individuals predisposed toward or recovered from AN (recAN) have a central nervous hyperserotonergic state and therefore restrict food intake as a means to reduce 5-HT availability (via diminished tryptophan-derived precursor supply) and alleviate associated negative mood states. Importantly, the 5-HT system has also been generally implicated in reward processing, which has also been shown to be altered in AN.
Methods
In this double-blind crossover study, 22 individuals recAN and 25 healthy control participants (HC) underwent functional magnetic resonance imaging (fMRI) while performing an established instrumental reward learning paradigm during acute tryptophan depletion (ATD; a dietary intervention that lowers central nervous 5-HT availability) as well as a sham depletion.
Results
On a behavioral level, the main effects of reward and ATD were evident, but no group differences were found. fMRI analyses revealed a group × ATD × reward level interaction in the ventral anterior insula during reward anticipation as well as in the medial orbitofrontal cortex during reward consumption.
Discussion
The precise pattern of results is suggestive of a ‘normalization’ of reward-related neural responses during ATD in recAN compared to HC. Our results lend further evidence to the 5-HT hypothesis of AN. Decreasing central nervous 5-HT synthesis and availability during ATD and possibly also by dieting may be a means to normalize 5-HT availability and associated brain processes.
Mobile technology offers unique opportunities for monitoring short-term suicide risk in daily life. In this study of suicidal adolescent inpatients, theoretically informed risk factors were assessed daily following discharge to predict near-term suicidal ideation and inform decision algorithms for identifying elevations in daily level risk, with implications for real-time suicide-focused interventions.
Methods
Adolescents (N = 78; 67.9% female) completed brief surveys texted daily for 4 weeks after discharge (n = 1621 observations). Using multi-level classification and regression trees (CARTSs) with repeated 5-fold cross-validation, we tested (a) a simple prediction model incorporating previous-day scores for each of 10 risk factors, and (b) a more complex model incorporating, for each of these factors, a time-varying person-specific mean over prior days together with deviation from that mean. Models also incorporated missingness and contextual (study week, day of the week) indicators. The outcome was the presence/absence of next-day suicidal ideation.
Results
The best-performing model (cross-validated AUC = 0.86) was a complex model that included ideation duration, hopelessness, burdensomeness, and self-efficacy to refrain from suicidal action. An equivalent model that excluded ideation duration had acceptable overall performance (cross-validated AUC = 0.78). Models incorporating only previous-day scores, with and without ideation duration (cross-validated AUC of 0.82 and 0.75, respectively), showed relatively weaker performance.
Conclusions
Results suggest that specific combinations of dynamic risk factors assessed in adolescents' daily life have promising utility in predicting next-day suicidal thoughts. Findings represent an important step in the development of decision tools identifying short-term risk as well as guiding timely interventions sensitive to proximal elevations in suicide risk in daily life.
We are grateful to DeFord et al. for the continued attention to our work and the crucial issues of fair representation in democratic electoral systems. Our response (Katz, King, and Rosenblatt Forthcoming) was designed to help readers avoid being misled by mistaken claims in DeFord et al. (Forthcoming-a), and does not address other literature or uses of our prior work. As it happens, none of our corrections were addressed (or contradicted) in the most recent submission (DeFord et al. Forthcoming-b).
Katz, King, and Rosenblatt (2020, American Political Science Review 114, 164–178) introduces a theoretical framework for understanding redistricting and electoral systems, built on basic statistical and social science principles of inference. DeFord et al. (2021, Political Analysis, this issue) instead focuses solely on descriptive measures, which lead to the problems identified in our article. In this article, we illustrate the essential role of these basic principles and then offer statistical, mathematical, and substantive corrections required to apply DeFord et al.’s calculations to social science questions of interest, while also showing how to easily resolve all claimed paradoxes and problems. We are grateful to the authors for their interest in our work and for this opportunity to clarify these principles and our theoretical framework.