Future Episodes Research Articles

SAT147 A Pharmacist Driven Active Surveillance Program To Reduce Hypoglycemic Recurrences In The Inpatient Setting

Abstract Disclosure: S. Kim: None. H. Tran: None. R.Y. Gianchandani: None. Background: Hyper and hypoglycemia increase morbidity and mortality in hospitalized patients. Glucose excursions are time sensitive and require timely response to prevent future episodes of dysglycemia. As part of a quality improvement initiative, we implemented an Active Glycemic Surveillance (AGS) program in July 2022 targeting patients with hypoglycemia (BG <70 mg/dL) based on a preliminary evaluation that revealed recurrent hypoglycemia was an opportunity for improvement. Pharmacist involvement in glycemic management has been shown to improve clinical outcomes in the acute care setting. Our AGS program is unique in that pharmacist trained in inpatient glycemic management is empowered to directly intervene on antihyperglycemic medication orders under scope of practice by a protocol approved through the pharmacy and therapeutics committee. Intervention: The AGS team consists of an endocrinologist and a diabetes stewardship pharmacist. A policy was developed and approved by P and T that outlines the types of interventions and orders that the diabetes stewardship pharmacist is able to make under scope of practice. These interventions include the ability to order certain labs (POCT BG, HgbA1C), and to adjust or discontinue certain anti-hyperglycemic agents Hospitalized patients who have a BG <70 mg/dL in the last 24 hours are reviewed by the AGS team. Chart review is performed on each patient to identify contributing factors and complicated cases are discussed with the endocrinologist prior to contacting the providers or making changes to orders. Providers are given rationale for changes as well as any other recommendations related to glycemic management. Results: During a 3 month period between August and October 2022, 848 cases of hypoglycemia were evaluated. Of these, 450 (53%) were found to be caused by an antihyperglycemic agent and 401 interventions were made by either the AGS team or other providers. The AGS team made 167 (41.6%) interventions and had a 24 h recurrence rate of 8.3% compared to 16.3% for all other providers. The most common types of interventions made by the AGS team were adjusting the insulin correction scale (78), basal insulin (57), bolus/meal insulin (16), oral medications (10), and TPN insulin (3). Conclusion: Our preliminary data show that a pharmacist-driven active surveillance program can reduce hypoglycemic recurrences. In the short time our AGS program has been implemented we have seen in increased utilization of appropriate correction scales, a decreased reliance on basal insulin or correction scale as the sole means of glycemic management, and an increase in endocrinology consultation for glycemic guidance. Future data will show the impact of this program on our overall hypoglycemia and hyperglycemia rates in future. Presentation: Saturday, June 17, 2023

Magma plumbing architectures and timescales of magmatic processes during historical magmatism on the Reykjanes Peninsula, Iceland

In the past 4000 years, three rifting episodes have occurred on the Reykjanes Peninsula (RP, SW Iceland) at time intervals of about 800-1000 years, with the activation of four of the five volcanic systems on the peninsula: Reykjanes, Svartsengi, Krýsuvík and Brennisteinsfjöll. In 2021 AD, 2022 AD and 2023 AD, three eruptions occurred in the Fagradalsfjall volcanic system, the only volcanic system that remained inactive during these past rifting episodes. Considering the eruptive history of the peninsula, this could mark the onset of a new eruptive episode. Although extensive petrochemical datasets have emerged from past rifting episodes, little is known about magma plumbing configuration and timescales of pre-eruptive magmatic processes. In this work, we focus on 16 basaltic lava units erupted across RP during a well-established rifting episode: the 800-1240 AD Fires. We analysed major and minor element contents of glasses, mineral phases and melt inclusions, and we reconstruct plumbing system architecture and constrain mixing-to-eruption timescales, with the goal of assessing likely eruption scenarios of a possible future eruptive episode. Mineral-melt equilibria suggests that most of crystal cores are antecrysts that did not crystallize from the magmas that carried them to the surface, but instead were scavenged from disaggregating mush layers genetically related to the erupted magmas. Magmas erupted in the easternmost part of the RP reveal larger contributions from geochemically enriched mantle-derived melts. However, MIs that record various extents of mixing of geochemically enriched and depleted components throughout the entire peninsula appear devoid of any spatial control of the underlying mantle. Independent clinopyroxene-melt and melt-based barometry, after correction for microlite crystallization, show consistent results and suggest that magmas from the western part of the peninsula were extracted from reservoirs located at about 7-10 km depth. In contrast, and similar to observations from recent eruptions at Fagradalsfjall, the easternmost system, Brennisteinsfjöll, was fed from deeper crustal reservoirs, at about 14-21 km depth. Fe-Mg diffusion chronometry applied to olivine rims suggests short mixing-to-eruption timescales on the order of days to weeks and likely faster ascent rates of magmas underneath Brennisteinsfjöll. Compared to 2021 AD Fagradalsfjall, mixing-to-eruption timescales were considerably shorter during the 800-1240 AD Fires. With inferred eruption durations on the order of months, the short olivine rim diffusion records are consistent with several discrete eruptive phases, which eventually assembled the individual magmatic units. In the light of possible future eruptive episodes on the RP, our work suggests that magmas are likely to accumulate at persistent depths across the RP, with key implication for interpreting pre-eruptive signals and eruption mitigation.

Outcomes of Infant Supraventricular Tachycardia Management Without Medication.

Most infants presenting with supraventricular tachycardia (SVT) are treated with an antiarrhythmic, primarily to prevent unrecognized future episodes that could lead to tachycardia-induced cardiomyopathy. A common practice at our institution is to not treat after the first presentation of infant SVT and instead educate parents on heart rate monitoring and reasons to present to care. The goal of this study was to evaluate the outcomes of non-pharmacologic treatment of infant SVT at first presentation and compare to outcomes of infants treated with an antiarrhythmic. This was a retrospective single center study of all infants presenting with a first episode of SVT from 2014 to 2021. Excluded were patients with a non-reentry type tachyarrhythmia, atrial flutter, long-RP tachycardia, congenital heart disease, or abnormal ventricular function. Sixty-four infants were included in the study. Thirty-six were managed without an antiarrhythmic. SVT recurred in 28% of the non-treatment group vs 50% in those treated with antiarrhythmics, p = 0.12. Of the patients admitted to the hospital, those in the non-treatment group had a shorter length of stay, 1(IQR 1-1) vs 3(IQR 2-4) days, p < 0.01. Non-treated patients were less likely to present to the emergency department for recurrent SVT, 6% vs 32%, p < 0.01. Neither group had a patient develop tachycardia-induced cardiomyopathy. For infants with structurally and functionally normal hearts, non-treatment combined with parental education after the first episode of SVT does not lead to worse outcomes. This approach avoids the burden of medication administration in an infant and may have the added benefit of empowering parents to feel comfortable managing clinically insignificant tachycardia at home.

Rural lives during COVID-19: crisis, resilience and redistributing societal risk

ABSTRACT This paper explores the redistribution and rescaling of societal risk in rural Britain during the COVID-19 pandemic, as one episode of the permacrisis. Drawing on empirical work in three contrasting areas of Scotland and England, we analyse individuals’ experiences of risk and of the institutions which offer them support in times of crisis (markets, state, voluntary and community organisations, and family and friends). Our findings reveal the unequal distribution of societal risk during the pandemic, exacerbated by a legacy of precariatisation and individualisation in the labour market and welfare reforms. Although the state acted to mitigate risk and financial hardship during the lockdown, it was often voluntary and community organisations that filled the gaps left by the inability of the state to reach effectively into rural areas. Social infrastructure and institutional capital are therefore central to the mitigation of vulnerability and societal risk. This raises important questions about the capacity of institutions to provide support in times of crisis to rural citizens. Unless there is societal pooling of risk through such institutions to ensure social protection and that nobody is disadvantaged by where they live, future episodes of the permacrisis are likely to exacerbate inequalities and vulnerabilities in rural communities.

Inpatient Care Utilization Following Mobile Crisis Response Encounters Among Racial/Ethnic Minoritized Youth

There has been an increase in youth psychiatric emergencies and psychiatric inpatient hospitalizations in recent years. Mobile crisis response (MCR) services offer an opportunity to meet acute youth mental health needs in the community and to provide linkage to care. However, an understanding of MCR encounters as a care pathway is needed, including how patterns of subsequent care may vary by youth race/ethnicity. The current study examines racial/ethnic differences in the rates of inpatient care use following MCR among youth. Data included Los Angeles County Department of Mental Health (LACDMH) administrative claims for MCR in 2017 and psychiatric inpatient hospitalizations and outpatient services from 2017-2020 for youth aged 0 to 18 years. In this sample of 6,908 youth (70.4% racial/ethnic minoritized youth) who received an MCR, 3.2% received inpatient care within 30 days of their MCR, 18.6% received inpatient care beyond 30 days of their MCR, and 14.7% received repeated inpatient care episodes during the study period. Multivariate models revealed that Asian American/Pacific Islander (AAPI) youth were less likely to receive inpatient care, whereas American Indian/Alaska Native (AI/AN) youth were more likely to receive inpatient care following MCR. Youth age, primary language, primary diagnosis, and insurance status also predicted future inpatient episodes. Findings highlight differential rates of inpatient use following MCR among AAPI and AI/AN youth relative to youth from other groups. Alternative interpretations for the findings are offered related to differential levels of need and disparate penetration of community-based outpatient and prevention-focused services. The study investigates racial and ethnic differences in the rates of inpatient care receipt after youth experience a psychiatric emergency in Los Angeles County. A total of 6,908 youth received mobile crisis response services and participated in the study. No racial/ethnic differences emerged in inpatient care use within the first month of receiving mobile crisis response services, but in the longer-term, Asian American/Pacific Islander youth were the least likely to receive inpatient care, and American Indian/Alaska Native youth were the most likely to receive inpatient. No differences in inpatient care use were observed for Black and Latinx youth relative to other youth in the study. Given the high costs for inpatient care, it remains critical to connect high-risk minoritized youth to less costly community-based care.

A Prospective Cohort Study on Risk Factors for Cervico-Thoracic Pain in Military Aircrew.

BACKGROUND: Military aircrew frequently report cervico-thoracic pain and injury. The relationship between risk factors and future pain episodes is, however, uncertain. The aim of this study was to identify risk factors for cervico-thoracic pain and to determine the 1-yr cumulative incidence of such pain.METHODS: A total of 47 Swedish aircrew (fighter and helicopter pilots and rear crew) without pain in the cervico-thoracic region were surveyed about work-related and personal factors and pain prevalence using the Musculoskeletal Screening Protocol questionnaire. They also performed tests of movement control, active cervical range of motion, and isometric neck muscle strength and endurance. Aircrew were followed for a year with questionnaires. Logistic regressions were used to identify potential risk factors for future cervico-thoracic pain.RESULTS: Previous cervico-thoracic pain (OR: 22.39, CI: 1.79-280.63), lower cervical flexion range of motion (OR: 0.78, CI: 0.64-0.96), and lower neck flexor muscular endurance (OR: 0.91, CI: 0.83-0.99) were identified as risk factors for reporting cervico-thoracic pain. At follow-up, 23.4% (CI: 13.6-37.2) had reported cervico-thoracic pain during the 12-mo follow-up period.DISCUSSION: The Musculoskeletal Screening Protocol can identify risk factors for cervico-thoracic pain. The link between cervico-thoracic pain and previous pain, as well as lower performance of neck range of motion and muscular endurance, highlights the need for primary and secondary preventive action. The findings from this study can facilitate the development of such pain prevention programs for aircrew.Tegern M, Aasa U, Larsson H. A prospective cohort study on risk factors for cervico-thoracic pain in military aircrew. Aerosp Med Hum Perform. 2023; 94(7):500-507.

#4185 EPISODES OF AKI FOLLOWING HOSPITALISATION AND ASSOCIATION WITH ADVERSE OUTCOMES: ANALYSIS FROM A PROSPECTIVE COHORT STUDY

Abstract Background and Aims AKI is associated with adverse long-term outcomes, including mortality, cardiovascular events and CKD development and progression. Individuals who have sustained AKI are at increased risk of developing further AKI. This analysis presents the association of long-term risk related to recent and further episodes of AKI in a prospective cohort of recently hospitalised individuals. Method Two matched cohorts of hospitalised individuals who had survived to at least 90 days after hospital discharge were recruited. The cohorts consisted of people who had sustained AKI during hospital admission (exposed group), and those who had not (non-exposed group), and were matched 1:1 for age, baseline eGFR stage and diabetes. Renal function, albuminuria and new AKI episodes were measured at 3 months, one, three and five years after index hospitalisation. Mortality, further AKI episodes and episodes of heart failure were recorded. Kidney disease progression was defined as decrease in eGFR of ≥25% associated with a decline in eGFR stage. Multivariable analysis was performed with binary logistic regression to assess the associations between repeated AKI episodes and outcomes. Results 866 exposed and non-exposed participants were recruited and successfully matched. Over the 5-year follow-up period, 138 (34%) participants in the exposed group had ≥1 further AKI compared with 67 (16%) in the non-exposed group (OR 2.71 [95% CI 1.94 to 3.77]; p&amp;lt;0.001). Independent associations with developing AKI during the follow-up period were AKI during index admission, baseline eGFR, albuminuria at 3 months and smoking status. Binary logistic regression, including all matched participants, showed that AKI during follow-up was independently associated with 5-year kidney disease progression (adjusted OR 2.49, 95% CI 1.42-4.37, p = 0.002), mortality (adjusted OR 3.076 95% CI 2.039-4.639 p&amp;lt;0.001) and episodes of heart failure (adjusted OR 5.234 95% CI 3.355-8.164, p&amp;lt;0.001). There was an additive effect, with the frequency of adverse outcomes increasing as number of AKI exposures increased (Table 1). Exposure to AKI during index admission or follow-up episodes conferred similar risk of kidney disease progression. AKI during the follow-up period had a stronger association with mortality and heart failure episodes than AKI during the index admission in this survivor cohort. Conclusion Previous AKI episodes were associated with increased frequency of future AKI episodes. AKI episodes during follow up period were independently associated with adverse outcomes regardless of AKI exposure during index hospitalisation. Increasing number of exposures to AKI had an additive effect on the proportion of individuals showing kidney disease progression, mortality and heart failure episodes. In this cohort of AKI survivors, AKI during the follow-up period had a stronger association with these outcomes than exposure to AKI during the index admission. A strategy for improving long-term outcomes in AKI survivors may be improving the identification of those at greatest risk of future AKI and strategies to prevent or optimise early detection and management.

Protocolo de manejo de pacientes con enfermedad pulmonar obstructiva crónica tras agudización en urgencias

In chronic obstructive pulmonary disease, an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is an episode of clinical instability due to the worsening of expiratory airflow limitation or of the underlying inflammatory process. The severity of AECOPD depends on baseline risk stratification and the intensity of the acute episode. Primary Care is the epicenter of the AECOPD care circuit, but it can be extended to the out-of-hospital emergency department and the hospital itself depending on the clinical situation, the level of severity, the availability of complementary tests, and the therapeutic resources required for each patient. Recording clinical data, history, triggering factors, treatment, and evolution of previous episodes of AECOPD in the electronic medical record is an essential aspect to adjust current treatment and prevent the occurrence of future episodes.

Ultrafiltration in Heart Failure: A Review.

Ultrafiltration is an effective method to get rid of fluid retention and congestion in patients with acute decompensated heart failure (HF) without affecting the circulating volume. Although its efficacy in comparison to diuretics is debatable, the evaluation of our analysis is based on various studies that comprise published clinical trials on ultrafiltration and studies comparing the efficacy of diuretics and ultrafiltration. Apart from this, we also look at literature that provides shortcomings of the said procedure and its scope for future advancements. Heart failure ultimately leads to volume overload, which is a highly concerning complication. Diuretics have been used as a first-line treatment for fluid overload but are becoming inefficacious due to the development of resistance and renal dysfunction. Ultrafiltration, on the other hand, is an attractive alternative to counter volume overload and congestion, which are unresponsive to medical therapy. There is also evidence that it significantly decreases the probability of future episodes of decompensation. There are, however, disagreements about whether ultrafiltration is an effective method to improve mortality in these patients. There is a lack of conclusive studies demonstrating the superiority of one fluid removal method over another. Hence, it is imperative to continue searching for the most effective method to treat congestion. Priority should be given to more mechanistic studies regarding ultrafiltration.

Aspect sentiment mining of short bullet screen comments from online TV series

AbstractBullet screen comments (BSCs) are user‐generated short comments that appear as real‐time overlays on many video platforms, expressing the audience opinions and emotions about different aspects of the ongoing video. Unlike traditional long comments after a show, BSCs are often incomplete, ambiguous in context, and correlated over time. Current studies in sentiment analysis of BSCs rarely address these challenges, motivating us to develop an aspect‐level sentiment analysis framework. Our framework, BSCNET, is a pre‐trained language encoder‐based deep neural classifier designed to enhance semantic understanding. A novel neighbor context construction method is proposed to uncover latent contextual correlation among BSCs over time, and we also incorporate semi‐supervised learning to reduce labeling costs. The framework increases F1 (Macro) and accuracy by up to 10% and 10.2%, respectively. Additionally, we have developed two novel downstream tasks. The first is noisy BSCs identification, which reached F1 (Macro) and accuracy of 90.1% and 98.3%, respectively, through fine‐tuning the BSCNET. The second is the prediction of future episode popularity, where the MAPE is reduced by 11%–19.0% when incorporating sentiment features. Overall, this study provides a methodology reference for aspect‐level sentiment analysis of BSCs and highlights its potential for viewing experience or forthcoming content optimization.

The Ongoing Mental Health Plight of Depressed College Students: Clinical Recommendations and the Importance of Early Screening and Detection

The COVID-19 pandemic disrupted the lives of college students. The psychological distress from the pandemic increased risk for provisional rates of Major Depression Disorder (MDD) during an already crucial developmental period. Using an online survey, participants were assessed for a provisional diagnosis of MDD using a validated screening tool, along with Generalized Anxiety Disorder (GAD) and psychosocial correlates. Findings showed a significant increase in the prevalence of MDD, and significant differences in social support, loneliness, substance use, GAD and suicidality were identified. Early screening and detection for potential MDD symptoms can reduce the severity, duration, and reoccurrence of future MDD episodes for college students.

Contrasting T-Phase and P-Wave Patterns from the 2015 and 2017 Eruptions of the Submarine Volcano Kick-‘em-Jenny: Influence of Cardinal Direction on Recorded First Phase Arrival

ABSTRACT Kick-‘em-Jenny (KeJ)—the most active volcano in the Lesser Antilles and located about 8 km north of Grenada—is the only known, live submarine volcano in the region. Unrest and eruption episodes are approximately decadal. Typically, a KeJ episode, which may consist of several eruptions, is short-lived and rapidly returns to quiescence, with virtually no background seismicity. Although two previous eruptions broke the surface of the sea, and some have had seismic effects felt in northern Grenada and sometimes Martinique, instrumental recordings of T phases were considered to provide firm evidence of eruptions. T phases are hydroacoustic waves that propagate efficiently in the Sound Fixing and Ranging channel allowing long-range recording. The most recent episodes occurred on 29 April 2017 and 23, 24 July 2015, with no reported surface evidence. The 2015 hr-long seismic signals, among the longest durations ever recorded, manifested differences in the first phase arrivals at some of the same recording stations suggesting a fundamental difference in T-phase wave trains’ generation at KeJ. The single eruption in the 2017 volcanic episode had a duration similar to those prior to the 2015 eruptions; however, except for the four stations in the immediate vicinity of KeJ, the detected signals propagated only as T waves. Real-time and posteruption deductions that the episodes occurred from different cardinal directions on the volcano were found to be supported by the findings from bathymetric analyses done shortly after the episodes. This characteristic enhances the KeJ profile, possibly improving real-time activity assessments in future KeJ episodes, with a view to strengthening hazard and risk communication.

Predicting future onset of depression among middle-aged adults with no psychiatric history.

Depression is a major cause of disability worldwide. Recent data suggest that, in industrialised countries, the prevalence of depression peaks in middle age. Identifying factors predictive of future depressive episodes is crucial for developing prevention strategies for this age group. We aimed to identify future depression in middle-aged adults with no previous psychiatric history. To predict a diagnosis of depression 1 year or more following a comprehensive baseline assessment, we used a data-driven, machine-learning methodology. Our data-set was the UK Biobank of middle-aged participants (N = 245 036) with no psychiatric history. Overall, 2.18% of the study population developed a depressive episode at least 1 year following baseline. Basing predictions on a single mental health questionnaire led to an area under the curve of the receiver operating characteristic of 0.66, and a predictive model leveraging the combined results of 100 UK Biobank questionnaires and measurements improved this to 0.79. Our findings were robust to demographic variations (place of birth, gender) and variations in methods of depression assessment. Thus, machine-learning-based models best predict diagnoses of depression when allowing the inclusion of multiple features. Machine-learning approaches show potential for being beneficial for the identification of clinically relevant predictors of depression. Specifically, we can identify, with moderate success, people with no recorded psychiatric history as at risk for depression by using a relatively small number of features. More work is required to improve these models and evaluate their cost-effectiveness before integrating them into the clinical workflow.

Guideline on the investigation and management of acute transfusion reactions.

Guideline on the investigation and management of acute transfusion reactions.

Adverse childhood experiences and reoccurrence of illness impact the gut microbiome, which affects suicidal behaviours and the phenome of major depression: towards enterotypic phenotypes.

The first publication demonstrating that major depressive disorder (MDD) is associated with alterations in the gut microbiota appeared in 2008 (Maes et al., 2008). The purpose of the present study is to delineate a) the microbiome signature of the phenome of depression, including suicidal behaviours (SB) and cognitive deficits; the effects of adverse childhood experiences (ACEs) and recurrence of illness index (ROI) on the microbiome; and the microbiome signature of lowered high-density lipoprotein cholesterol (HDLc). We determined isometric log-ratio abundances or prevalences of gut microbiome phyla, genera, and species by analysing stool samples from 37 healthy Thai controls and 32 MDD patients using 16S rDNA sequencing. Six microbiome taxa accounted for 36% of the variance in the depression phenome, namely Hungatella and Fusicatenibacter (positive associations) and Butyricicoccus, Clostridium, Parabacteroides merdae, and Desulfovibrio piger (inverse association). This profile (labelled enterotype 1) indicates compositional dysbiosis, is strongly predicted by ACE and ROI, and is linked to SB. A second enterotype was developed that predicted a decrease in HDLc and an increase in the atherogenic index of plasma (Bifidobacterium, P. merdae, and Romboutsia were positively associated, while Proteobacteria and Clostridium sensu stricto were negatively associated). Together, enterotypes 1 and 2 explained 40.4% of the variance in the depression phenome, and enterotype 1 in conjunction with HDLc explained 39.9% of the variance in current SB. In conclusion, the microimmuneoxysome is a potential new drug target for the treatment of severe depression and SB and possibly for the prevention of future episodes.

Structured Immune Workup in Healthy Children With a First Episode of Severe Bacterial Infection: A 7-year Single-Center Study.

Severe bacterial infections (SBIs) in otherwise healthy children are rare and may represent an underlying impairment of the immune system, including primary immunodeficiency. However, it is unclear whether and how children should be assessed. We retrospectively analyzed data from hospital records of previously healthy children aged 3 days to 18 years with SBI, including pleuropneumonia, meningitis, and/or sepsis. Patients were diagnosed or immunologically followed up between 1 January 2013 and 31 March 2020. Among 432 children with SBI, findings could be analyzed in 360. Follow-up data were available for 265 children (74%), of whom 244 (92%) underwent immunological testing. Laboratory abnormalities were found in 51 of 244 patients (21%), with 3 deaths (1%). Fourteen children (6%) had immunodeficiency considered clinically relevant (3 complement deficiencies, 1 autoimmune neutropenia, 10 humoral immunodeficiencies), and 27 (11%) had milder humoral abnormalities or findings suggestive of delayed adaptive immune maturation. A substantial proportion of children with SBI may benefit from routine immunological testing, revealing (potentially) clinically relevant impaired immune function in 6%-17% of children. The identification of immune abnormalities allows for specific counseling of families and optimization of preventive measures, such as booster vaccinations, to avoid future SBI episodes.

Predicting future depressive episodes from resting-state fMRI with generative embedding

After a first episode of major depressive disorder (MDD), there is substantial risk for a long-term remitting-relapsing course. Prevention and early interventions are thus critically important. Various studies have examined the feasibility of detecting at-risk individuals based on out-of-sample predictions about the future occurrence of depression. However, functional magnetic resonance imaging (fMRI) has received very little attention for this purpose so far.Here, we explored the utility of generative models (i.e. different dynamic causal models, DCMs) as well as functional connectivity (FC) for predicting future episodes of depression in never-depressed adults, using a large dataset (N = 906) of task-free ("resting state") fMRI data from the UK Biobank (UKB). Connectivity analyses were conducted using timeseries from pre-computed spatially independent components of different dimensionalities. Over a three-year period, 50% of selected participants showed indications of at least one depressive episode, while the other 50% did not. Using nested cross-validation for training and a held-out test set (80/20 split), we systematically examined the combination of 8 connectivity feature sets and 17 classifiers. We found that a generative embedding procedure based on combining regression DCM (rDCM) with a support vector machine (SVM) enabled the best predictions, both on the training set (0.63 accuracy, 0.66 area under the curve, AUC) and the test set (0.62 accuracy, 0.64 AUC; p < 0.001). However, on the test set, rDCM was only slightly superior to predictions based on FC (0.59 accuracy, 0.61 AUC). Interpreting model predictions based on SHAP (SHapley Additive exPlanations) values suggested that the most predictive connections were widely distributed and not confined to specific networks. Overall, our analyses suggest (i) ways of improving future fMRI-based generative embedding approaches for the early detection of individuals at-risk for depression and that (ii) achieving accuracies of clinical utility may require combination of fMRI with other data modalities.

Systematic analysis of the pharmacological content of the Tatort (scene of crime) TV series from 2019 to 2021

Tatort (scene of crime) is a must-see programme on Sunday evenings for many Germans. With its enormous reach, the crime series also deals in more than half of its episodes with active pharmacological substances, surprisingly most of them are used curatively. There are lots of ways representing the active pharmacological substances: simply naming the preparation to details such as information on how to take it or how it is manufactured illegally. Diseases of great interest to the public such as hypertension or depression are taken up. In addition to the correct presentation, in 20% of cases the active pharmacological substances were presented incorrectly or implausibly. But even with correct presentation, it may yield a harmful influence on viewers: Stigmatisation of preparations occurred in 14%, especially in the case of active pharmacological substances that are used in psychiatric therapies; presentations that could be considered dangerous occurred in 21% of the mentions. In 29%, content was presented positively to the audience beyond the correct presentation. Analgesics and active pharmacological substances used in psychiatry are frequently titled. But drugs such as amiodarone, insulin or "cortisone" are also mentioned. The potential for misuse is also presented. Tatort also educates the audience about common diseases and their treatment, for example hypertension, depression or the use of antibacterial drugs. However, the series does not educate the general public on the mechanism of action of commonly used drugs. There is a natural dilemma between informing the public and guiding them to misuse medicines. Finally, we discuss how future episodes could be improved with respect to pharmacological content.

Generative models as computational assays for psychiatry

AbstractPsychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response. This has motivated novel approaches that aim to develop “computational assays” for inferring patient-specific disease processes from neuroimaging data, which can then be incorporated into decision making in everyday clinical practice. Such computational assays are often based on generative models, which describe how measured data may be caused by a particular mechanism. Combining generative models with machine learning allows translating the inferences from computational assays into patient-specific predictions, an approach referred to as generative embedding.Here, I illustrate the clinical potential of generative embedding for the exemplary case of a generative model of whole-brain effective (directed) connectivity: regression DCM (rDCM). First, I introduce rDCM to the audience and highlight its relevance for understanding the pathophysiology of psychiatric disorders. I then provide an initial demonstration of the clinical utility of rDCM. Specifically, we assessed the ability of rDCM for predicting future episodes of depression in never-depressed adults, using a large dataset (N=906) of resting-state fMRI data from the UK Biobank. Over a 3-year period, half of the participants showed indications of at least one depressive episode, while the other half did not. Using nested cross-validation for training and a held-out test set (80/20 split), we found that a generative embedding procedure based on rDCM in combination with a support vector machine enables statistically significant predictions of future depressive episodes, both on the training (accuracy: 0.63, area under the curve (AUC): 0.66, p&lt;0.001) and test set (accuracy: 0.62, AUC: 0.64, p&lt;0.001). Interpreting model predictions based on SHAP (Shapley Additive exPlanations) values suggested that the most predictive connections were widely distributed and not confined to specific networks.In summary, generative models of brain connectivity in general, and rDCM in particular, show initial promise to serve as computational assays for psychiatry. Our analyses suggest that (i) fMRI-based generative embedding approaches have some capacity for early detection of individuals at-risk for depression and (ii) achieving accuracies of clinical utility may require combination of fMRI with other data modalities.Disclosure of InterestNone Declared

Long-acting new generation antipsychotics in the maintenance treatment of bipolar disorders

IntroductionMaintaining remission, preventing from future episodes, better treatment adherence and improving the quality of life are main aims of long-term treatment in bipolar disorders (BD). In recent years, new generation long-acting injectable (LAI) antipsychotics have been frequently used in maintenance treatment for bipolar disorders.ObjectivesWe aimed to review socio-demographic and clinical characteristics of bipolar patients taking LAI treatment for maintenance treatment.MethodsClinical records of 56 bipolar patients who are on LAI treatment and followed in Mazhar Osman Mood Clinic (MOMC) of Selcuk University Medical Faculty were evaluated. Descriptive statistical analysis was performed with Statistical Package for the Social Sciences (SPSS).ResultsNearly half of the patients were male (n:29, 52%). 49,1% of the patients were married. The mean age was 37.1±12.2 years and the mean duration of education was 11.1±4.2 years. All of the patients were diagnosed with bipolar 1 disorder. Most of the patients (64,7%) was on aripiprazole LAI while remaining was receiving paliperidone LAI for maintenance treatment. We found a significant reduction in the number of manic episodes after long-acting treatment (p&lt;0.001), but we could not find any difference for depression. Ten of the patients discontinued the treatment due to the side effects, extrapyramidal side effects were the most common side effects. Eight of the patients were switched from paliperidone treatment to aripiprazole treatment due to side effects, especially hyperprolactinemia. Relapse was observed in 46,4% of the patients and there was no difference between aripiprazole and paliperidone in terms of relapse rate.ConclusionsLAI new generation antipsychotics are taking place in long-term treatment of bipolar disorder via improving treatment adherence. Side effect profile of aripiprazole and paliperidone are different. However, we could not find any difference between two drugs in terms of side effects and relapse rates. Small sample size and shorter duration of follow-up should be considered as limitations.Disclosure of InterestNone Declared