response status
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Abstract Intelligent substations can accomplish deeper and more complex substation information exchange and processing by virtue of their equipment intelligence and data integration. In this paper, a relay protection equipment test system for intelligent substations is investigated for intelligent relay protection equipment. By applying data fusion technology in the testing process, functions such as automatically obtaining the action information of secondary devices and judging the response status of secondary devices can be accomplished. Applying the test system proposed in this paper to high-voltage line protection devices, the results show that the relay protection equipment test system can optimize the relay protection equipment test process, which further improves the accuracy and efficiency of relay protection equipment testing.

Synthetic glucocorticoids are used to treat many immune conditions, such as asthma and severe COVID-19. Single cell data capture fine-grained details of transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. We used single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated PBMCs from African American donors. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. We demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics separated cells by response status and identified dynamic transcriptional patterns along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.

BACKGROUND Patient reported outcome measures (PROMs) are commonly used to report outcomes after hip and knee arthroplasty but response rates are rarely complete. Given that pre-operative health status (as measured by PROMs) is a strong predictor of outcomes (using the same measures) and that these outcomes may influence the response rate, it is possible that post-operative response rates may be influenced by pre-operative health status. OBJECTIVE This study aims to test the association between pre-operative PROMs and post-operative response status following hip and knee arthroplasty. METHODS Data from the PROMs program of a large national registry were used. Pre-operative PROMs were the Oxford Hip Score or Oxford Knee Score, EQ5D Utility Index and the EQ visual analogue scale (VAS) for overall health. Logistic regression, adjusting for age, sex, body mass index (BMI) and American Society of Anesthesiologists (ASA) Physical Status Classification System, was used to test the association between each pre-operative PROM and response status for the 6-months post-surgery survey. RESULTS Data from 9,499 and 16,539 patients undergoing elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) for osteoarthritis, respectively, were included in the analysis. Adjusting for age, sex, BMI and ASA, there was no significant difference in response status at 6 months based on the pre-operative Oxford Hip or Knee Scores (OR 1.00, 95% CI 0.99 to 1.01 for both, p = 0.70 for THA, p = 0.85 for TKA). Healthier patients (based on the EQ VAS scores) pre-operatively were more likely to respond at 6 months, but this difference was negligible (OR 1.00, 95% CI 1.00 to 1.01 for THA and TKA, p = 0.004 for THA, p < 0.001 for TKA). Pre-operative EQ Utility Index was not associated with response rate at 6 months for THA (OR 1.14, 95% CI 0.96 to 1.36, p = 0.13) or TKA patients (OR 1.05, 95% CI 0.91 to 1.22, p = 0.49). CONCLUSIONS Patients who respond to PROMs surveys at 6 months post THA and TKA demonstrated similar pre-operative PROMs scores to those who did not respond. This can allay concerns that differences in pre-operative pain, function and quality of life might introduce bias when assessing surgical outcomes where there is loss to follow-up post-operatively.

Background: There is an urgent need for effective follow-up treatments after acute electroconvulsive therapy (ECT) in depressed patients. Preliminary evidence suggests psychotherapeutic interventions to be a feasible and efficacious follow-up treatment. However, there is a need for research on the long-term usefulness of such psychotherapeutic offers in a naturalistic setting that is more representative of routine clinical practice. Therefore, the aim of the current pilot study was to investigate the effects of a half-open continuous group cognitive behavioral therapy (CBT) with cognitive behavioral analysis system of psychotherapy elements as a follow-up treatment for all ECT patients, regardless of response status after ECT, on reducing depressive symptoms and promoting psychosocial functioning.Method: Group CBT was designed to support patients during the often-difficult transition from inpatient to outpatient treatment. In a non-controlled pilot trial, patients were offered 15weekly sessions of manualized group CBT (called EffECTiv 2.0). The Montgomery-Åsberg Depression Rating Scale was assessed as primary outcome; the Beck Depression Inventory, WHO Quality of Life Questionnaire–BREF, and the Cognitive Emotion Regulation Questionnaire were assessed as secondary outcomes. Measurements took place before individual group start, after individual group end, and 6months after individual group end.Results: During group CBT, Post-ECT symptom reduction was not only maintained but there was a tendency toward a further decrease in depression severity. This reduction could be sustained 6months after end of the group, regardless of response status after ECT treatment. Aspects of quality of life and emotion regulation strategies improved during group CBT, and these improvements were maintained 6months after the end of the group.Conclusion: Even though the interpretability of the results is limited by the small sample and the non-controlled design, they indicate that manualized group CBT with cognitive behavioral analysis system of psychotherapy elements might pose a recommendable follow-up treatment option after acute ECT for depressed patients, regardless of response status after ECT. This approach might not only help to further reduce depressive symptoms and prevent relapse, but also promote long-term psychosocial functioning by improving emotion regulation strategies and psychological quality of life and thus could be considered as a valuable addition to clinical routine after future validation.

AbstractIdentifying biomarkers of antidepressant response may advance personalized treatment of major depressive disorder (MDD). We aimed to identify longitudinal changes in gene expression associated with response to antidepressants in a sample of MDD patients treated with escitalopram. Patients (N = 153) from the CAN-BIND-1 cohort were treated for 8 weeks, and depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale at 0, 2, 4, 6, and 8 weeks. We identified three groups of patients according to response status: early responders (22.9%), later responders (32.0%), and nonresponders (45.1%). RNA sequencing was performed in blood obtained at weeks 0, 2, and 8. RNA expression was modeled using growth models, and differences in the longitudinal changes in expression according to response were investigated using multiple regression models. The expression of RNAs related to response was investigated in the brains of depressed individuals, as well as in neuronal cells in vitro. We identified four RNAs (CERCAM, DARS-AS1, FAM228B, HBEGF) whose change over time was independently associated with a response status. For all except HBEGF, responders showed higher expression over time, compared to nonresponders. While the change in all RNAs differentiated early responders from nonresponders, changes in DARS-AS1 and HBEGF also differentiated later responders from nonresponders. Additionally, HBEGF was downregulated in the brains of depressed individuals, and increased in response to escitalopram treatment in vitro. In conclusion, using longitudinal assessments of gene expression, we provide insights into biological processes involved in the intermediate stages of escitalopram response, highlighting several genes with potential utility as biomarkers of antidepressant response.

The Unified Protocols for Transdiagnostic Treatment of Emotional Disorders in Children and Adolescents (UP-C/A) have been adapted into a stepped care intervention (UP-C/A-SC) that may be delivered via telehealth. Stepped care models are a type of service delivery system designed to be efficient, effective, accessible, and cost-effective and to personalize service by matching clients to the most appropriate dosage or the best type of treatment for their needs. This chapter discusses the adaptations to the original interventions necessary to deliver UP-C/A-SC as a two-step intervention via telehealth. A case example of a child who responded to the first step of UP-C/A-SC illustrates the components of the stepped care model, including a collaborative decision-making process to determine treatment response status after the first step. To address common implementation issues, barriers to providing UP-C/A-SC and solutions are discussed.

e14041 Background: mRANO criteria form the basis for assessing treatment response in GBM clinical trials. mRANO measurements show variability due to limited sampling of the tumor morphology and reader estimations. Volumetrics may overcome limitations of linear measurements and improve our ability to detect changes reliably. Advanced MRI shed light on the mechanism of action and provide biomarkers, whose changes may precede any morphological alterations in the tumor. Methods: Six consecutive patients (3M, 3F, mean age 53.5 yrs) from an ongoing Phase-2 study on the effect of Temferon on recurrent GBM, were included and 3 consecutive MRI follow-up time points from each patient were entered in this interim analysis. The mRANO response status was determined by a central reader. Integrated volumetrics, two perfusion modalities (DSC/DCE) and diffusion analysis were performed on a proprietary platform after co-registering data in a common space to eliminate user bias and variability. Volumetrics and perfusion/diffusion biomarkers were estimated using state-of-the-art Artificial Intelligence (AI)-empowered algorithms. Statistical significance was set at p < 0.001. Results: At the time of the interim analysis, 3 patients experienced stable disease (SD) / partial response (pR) and 3 patients had progressive disease (PD). The tumor volume had significant correlation (r = 0.89) with the SPDP but the SPDP showed monotonously biased overestimation of the tumor burden in the Bland-Altman analysis with mean difference = 886 (95%CI: 64-1708). Changes assessed by SPDP in the tumor burden during the treatment were underestimated for low volume tumor and underestimated for sizeable tumors compared with the volumetrics. The optimal threshold to predict tumor progression was 26% volume increase (sensitivity/specificity: 67/93%, AUC = 0.85), whereas there was no statistically significant threshold for SPDP. The perfusion fractional tumor volumes (FTV) with low and intermediately elevated rCBV showed strong correlation with the SPDP and enhancement volumetrics (r = 0.92-0.98). ROC analysis showed that 14% increase in the high perfusion tumor could significantly predict progression (sensitivity/specificity: 79/71%, AUC = 0.71). The responders showed significant increase in mean DWI values (11±0.3%) vs decrease (-4±0.05%) in non-responders. The mean rCBV and Vp values in responders showed decrease (-3±0.45% and -33±0.1%) and were increased in non-responders (25±0.1% and 51±0.66%). Conclusions: We demonstrated significant bias in estimating treatment response by means of mRANO compared to tumor volumetrics. Distinct patterns of changes in tumor perfusion, diffusion and FTV correlated highly with treatment response and enhancing tumor burden. Volumetrics and perfusion/diffusion composite biomarkers predicted accurately the response status in our patients. Clinical trial information: NCT03866109.

Background:Therapy choice and therapy change depend on the ability to accurately assess patients’ disease activity. The clinical assessments used to evaluate treatment response in rheumatoid arthritis have inherent variability, normally considered as measurement error, intra-observer variability or within subject variability. Each contribute to variability in deriving response status as defined by composite measures such as the ACR or EULAR criteria, particularly when a one-time observed measurement lies near the boundary defining response or non-response. To select an optimal therapeutic strategy in the burgeoning age of precision medicine in rheumatology, achieve the lowest disease activity and maximize long-term health outcomes for each patient, improved treatment response definitions are needed.Objectives:Develop a high-confidence definition of treatment response and non-response in rheumatoid arthritis that exceeds the expected variability of subcomponents in the composite response criteria.Methods:A Monte Carlo simulation approach was used to assess ACR50 and EULAR response outcomes in 100 rheumatoid arthritis patients who had been treated for 6 months with a TNF inhibitor therapy. Monte Carlo simulations were run with 2000 iterations implemented with measurement variability derived for each clinical assessment: tender joint count, swollen joint count, Health Assessment Questionnaire disability index (HAQ-DI), patient pain assessment, patient global assessment, physician global assessment, serum C-reactive protein level (CRP) and disease activity score 28-joint count with CRP.1-3 Each iteration of the Monte Carlo simulation generated one outcome with a value of 0 or 1 indicating non-responder or responder, respectively.Results:A fidelity score, calculated separately for ACR50 and EULAR response, was defined as an aggregated score from 2000 iterations reported as a fraction that ranges from 0 to 1. The fidelity score depicted a spectrum of response covering strong non-responders, inconclusive statuses and strong responders. A fidelity score around 0.5 typified a response status with extreme variability and inconclusive clinical response to treatment. High-fidelity scores were defined as >0.7 or <0.3 for responders and non-responders, respectively, meaning that the simulated clinical response status label among all simulations agreed at least 70% of the time. High-confidence true responders were considered as those patients with high-fidelity outcomes in both ACR50 and EULAR outcomes.Conclusion:A definition of response to treatment should exceed the expected variability of the clinical assessments used in the composite measure of therapeutic response. By defining high-confidence responders and non-responders, the true impact of therapeutic efficacy can be determined, thus forging a path to development of better treatment options and advanced precision medicine tools in rheumatoid arthritis.References:[1]Cheung, P. P., Gossec, L., Mak, A. & March, L. Reliability of joint count assessment in rheumatoid arthritis: a systematic literature review. Semin Arthritis Rheum43, 721-729, doi:10.1016/j.semarthrit.2013.11.003 (2014).[2]Uhlig, T., Kvien, T. K. & Pincus, T. Test-retest reliability of disease activity core set measures and indices in rheumatoid arthritis. Ann Rheum Dis68, 972-975, doi:10.1136/ard.2008.097345 (2009).[3]Maska, L., Anderson, J. & Michaud, K. Measures of functional status and quality of life in rheumatoid arthritis: Health Assessment Questionnaire Disability Index (HAQ), Modified Health Assessment Questionnaire (MHAQ), Multidimensional Health Assessment Questionnaire (MDHAQ), Health Assessment Questionnaire II (HAQ-II), Improved Health Assessment Questionnaire (Improved HAQ), and Rheumatoid Arthritis Quality of Life (RAQoL). Arthritis Care Res (Hoboken) 63 Suppl 11, S4-13, doi:10.1002/acr.20620 (2011).Disclosure of Interests:Vibeke Strand Consultant of: Abbvie, Amgen, Arena, BMS, Boehringer Ingelheim, Celltrion, Galapagos, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen, Kiniksa, Lilly, Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Setpoint, UCB, Stanley Cohen: None declared, Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Alex Jones Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

ABSTRACT The availability of integrated remote sensing platforms and digital data collection and sharing tools is changing spill response. These tools facilitate a more effective and rapid decision-making process that can increase resource protection, improve responder safety, and reduce response costs. Early detection and response are a key to preventing smaller incidents from becoming larger. A variety of innovative tools now exist or are in development that could assist facilities and responders in the early stages and throughout an incident event to reduce human, environmental, and economic impacts. Real time field data collection for key parameters such as oil thickness and trajectory, SCAT data, oiled wildlife details, and resources at risk identification, allows for more robust data to be shared rapidly throughout the response operation. This information facilitates more effectively targeted deployment and re-deployment of human and mechanical response assets, and more immediate assessment of both environmental impacts and cleanup progress. Auto-population of incident command system forms as well as better document sharing and document retention through remote and cloud-based file saving platforms can improve the administrative and functional aspects of the response, contributing to enhanced efficiency. The ability to identify and effectively respond to rapidly changing circumstances provides the Unified Command with new tools to make better decisions and keep the public informed of progress. This paper considers new and emerging technologies as they may be applied to the work in a unified command setting, and how they may allow us to compress the operational period for decision-making and action, more accurately and more rapidly understand and share the spill response status, and how we may be able to enhance responder safety and recognize cost savings. We also consider some inherent risks associated with reliance on integrated technologies and digital information and will offer suggestions for drills and exercises to test and optimize these tools.