9 research outputs found
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Pragmatic phase II clinical trial to improve depression care in a real-world diverse MS cohort from an academic MS centre in Northern California: MS CATCH study protocol.
INTRODUCTION: Depression occurs in over 50% of individuals living with multiple sclerosis (MS) and can be treated using many modalities. Yet, it remains: under-reported by patients, under-ascertained by clinicians and under-treated. To enhance these three behaviours likely to promote evidence-based depression care, we engaged multiple stakeholders to iteratively design a first-in-kind digital health tool. The tool, MS CATCH (Care technology to Ascertain, Treat, and engage the Community to Heal depression in patients with MS), closes the communication loop between patients and clinicians. Between clinical visits, the tool queries patients monthly about mood symptoms, supports patient self-management and alerts clinicians to worsening mood via their electronic health record in-basket. Clinicians can also access an MS CATCH dashboard displaying patients mood scores over the course of their disease, and providing comprehensive management tools (contributing factors, antidepressant pathway, resources in patients neighbourhood). The goal of the current trial is to evaluate the clinical effect and usability of MS CATCH in a real-world clinical setting. METHODS AND ANALYSIS: MS CATCH is a single-site, phase II randomised, delayed start, trial enrolling 125 adults with MS and mild to moderately severe depression. Arm 1 will receive MS CATCH for 12 months, and arm 2 will receive usual care for 6 months, then MS CATCH for 6 months. Clinicians will be randomised to avoid practice effects. The effectiveness analysis is superiority intent-to-treat comparing MS CATCH to usual care over 6 months (primary outcome: evidence of screening and treatment; secondary outcome: Hospital Anxiety Depression Scale-Depression scores). The usability of the intervention will also be evaluated (primary outcome: adoption; secondary outcomes: adherence, engagement, satisfaction). ETHICS AND DISSEMINATION: University of California, San Francisco Institutional Review Board (22-36620). The findings of the study are planned to be shared through conferences and publishments in a peer-reviewed journal. The deidentified dataset will be shared with qualified collaborators on request, provision of CITI and other certifications, and data sharing agreement. We will share the results, once the data are complete and analysed, with the scientific community and patient/clinician participants through abstracts, presentations and manuscripts. TRIAL REGISTRATION NUMBER: NCT05865405
A Closed-Loop Digital Health Tool to Improve Depression Care in Multiple Sclerosis: Iterative Design and Cross-Sectional Pilot Randomized Controlled Trial and its Impact on Depression Care
BackgroundPeople living with multiple sclerosis (MS) face a higher likelihood of being diagnosed with a depressive disorder than the general population. Although many low-cost screening tools and evidence-based interventions exist, depression in people living with MS is underreported, underascertained by clinicians, and undertreated.
ObjectiveThis study aims to design a closed-loop tool to improve depression care for these patients. It would support regular depression screening, tie into the point of care, and support shared decision-making and comprehensive follow-up. After an initial development phase, this study involved a proof-of-concept pilot randomized controlled trial (RCT) validation phase and a detailed human-centered design (HCD) phase.
MethodsDuring the initial development phase, the technological infrastructure of a clinician-facing point-of-care clinical dashboard for MS management (BRIDGE) was leveraged to incorporate features that would support depression screening and comprehensive care (Care Technology to Ascertain, Treat, and Engage the Community to Heal Depression in people living with MS [MS CATCH]). This linked a patient survey, in-basket messages, and a clinician dashboard. During the pilot RCT phase, a convenience sample of 50 adults with MS was recruited from a single MS center with 9-item Patient Health Questionnaire scores of 5-19 (mild to moderately severe depression). During the routine MS visit, their clinicians were either asked or not to use MS CATCH to review their scores and care outcomes were collected. During the HCD phase, the MS CATCH components were iteratively modified based on feedback from stakeholders: people living with MS, MS clinicians, and interprofessional experts.
ResultsMS CATCH links 3 features designed to support mood reporting and ascertainment, comprehensive evidence-based management, and clinician and patient self-management behaviors likely to lead to sustained depression relief. In the pilot RCT (n=50 visits), visits in which the clinician was randomized to use MS CATCH had more notes documenting a discussion of depressive symptoms than those in which MS CATCH was not used (75% vs 34.6%; χ21=8.2; P=.004). During the HCD phase, 45 people living with MS, clinicians, and other experts participated in the design and refinement. The final testing round included 20 people living with MS and 10 clinicians including 5 not affiliated with our health system. Most scoring targets for likeability and usability, including perceived ease of use and perceived effectiveness, were met. Net Promoter Scale was 50 for patients and 40 for clinicians.
ConclusionsCreated with extensive stakeholder feedback, MS CATCH is a closed-loop system aimed to increase communication about depression between people living with MS and their clinicians, and ultimately improve depression care. The pilot findings showed evidence of enhanced communication. Stakeholders also advised on trial design features of a full year long Department of Defense–funded feasibility and efficacy trial, which is now underway.
Trial RegistrationClinicalTrials.gov NCT05865405; http://tinyurl.com/4zkvru9
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A Closed-Loop Digital Health Tool to Improve Depression Care in Multiple Sclerosis: Iterative Design and Cross-Sectional Pilot Randomized Controlled Trial and its Impact on Depression Care.
BackgroundPeople living with multiple sclerosis (MS) face a higher likelihood of being diagnosed with a depressive disorder than the general population. Although many low-cost screening tools and evidence-based interventions exist, depression in people living with MS is underreported, underascertained by clinicians, and undertreated.ObjectiveThis study aims to design a closed-loop tool to improve depression care for these patients. It would support regular depression screening, tie into the point of care, and support shared decision-making and comprehensive follow-up. After an initial development phase, this study involved a proof-of-concept pilot randomized controlled trial (RCT) validation phase and a detailed human-centered design (HCD) phase.MethodsDuring the initial development phase, the technological infrastructure of a clinician-facing point-of-care clinical dashboard for MS management (BRIDGE) was leveraged to incorporate features that would support depression screening and comprehensive care (Care Technology to Ascertain, Treat, and Engage the Community to Heal Depression in people living with MS [MS CATCH]). This linked a patient survey, in-basket messages, and a clinician dashboard. During the pilot RCT phase, a convenience sample of 50 adults with MS was recruited from a single MS center with 9-item Patient Health Questionnaire scores of 5-19 (mild to moderately severe depression). During the routine MS visit, their clinicians were either asked or not to use MS CATCH to review their scores and care outcomes were collected. During the HCD phase, the MS CATCH components were iteratively modified based on feedback from stakeholders: people living with MS, MS clinicians, and interprofessional experts.ResultsMS CATCH links 3 features designed to support mood reporting and ascertainment, comprehensive evidence-based management, and clinician and patient self-management behaviors likely to lead to sustained depression relief. In the pilot RCT (n=50 visits), visits in which the clinician was randomized to use MS CATCH had more notes documenting a discussion of depressive symptoms than those in which MS CATCH was not used (75% vs 34.6%; χ21=8.2; P=.004). During the HCD phase, 45 people living with MS, clinicians, and other experts participated in the design and refinement. The final testing round included 20 people living with MS and 10 clinicians including 5 not affiliated with our health system. Most scoring targets for likeability and usability, including perceived ease of use and perceived effectiveness, were met. Net Promoter Scale was 50 for patients and 40 for clinicians.ConclusionsCreated with extensive stakeholder feedback, MS CATCH is a closed-loop system aimed to increase communication about depression between people living with MS and their clinicians, and ultimately improve depression care. The pilot findings showed evidence of enhanced communication. Stakeholders also advised on trial design features of a full year long Department of Defense-funded feasibility and efficacy trial, which is now underway.Trial registrationClinicalTrials.gov NCT05865405; http://tinyurl.com/4zkvru9x
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A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis.
Central nervous system B cells have several potential roles in multiple sclerosis (MS): secretors of proinflammatory cytokines and chemokines, presenters of autoantigens to T cells, producers of pathogenic antibodies, and reservoirs for viruses that trigger demyelination. To interrogate these roles, single-cell RNA sequencing (scRNA-Seq) was performed on paired cerebrospinal fluid (CSF) and blood from subjects with relapsing-remitting MS (RRMS; n = 12), other neurologic diseases (ONDs; n = 1), and healthy controls (HCs; n = 3). Single-cell immunoglobulin sequencing (scIg-Seq) was performed on a subset of these subjects and additional RRMS (n = 4), clinically isolated syndrome (n = 2), and OND (n = 2) subjects. Further, paired CSF and blood B cell subsets (RRMS; n = 7) were isolated using fluorescence activated cell sorting for bulk RNA sequencing (RNA-Seq). Independent analyses across technologies demonstrated that nuclear factor kappa B (NF-κB) and cholesterol biosynthesis pathways were activated, and specific cytokine and chemokine receptors were up-regulated in CSF memory B cells. Further, SMAD/TGF-β1 signaling was down-regulated in CSF plasmablasts/plasma cells. Clonally expanded, somatically hypermutated IgM+ and IgG1+ CSF B cells were associated with inflammation, blood-brain barrier breakdown, and intrathecal Ig synthesis. While we identified memory B cells and plasmablast/plasma cells with highly similar Ig heavy-chain sequences across MS subjects, similarities were also identified with ONDs and HCs. No viral transcripts, including from Epstein-Barr virus, were detected. Our findings support the hypothesis that in MS, CSF B cells are driven to an inflammatory and clonally expanded memory and plasmablast/plasma cell phenotype
A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis
Central nervous system B cells have several potential roles in multiple sclerosis (MS): secretors of proinflammatory cytokines and chemokines, presenters of autoantigens to T cells, producers of pathogenic antibodies, and reservoirs for viruses that trigger demyelination. To interrogate these roles, single-cell RNA sequencing (scRNA-Seq) was performed on paired cerebrospinal fluid (CSF) and blood from subjects with relapsing-remitting MS (RRMS; n = 12), other neurologic diseases (ONDs; n = 1), and healthy controls (HCs; n = 3). Single-cell immunoglobulin sequencing (scIg-Seq) was performed on a subset of these subjects and additional RRMS (n = 4), clinically isolated syndrome (n = 2), and OND (n = 2) subjects. Further, paired CSF and blood B cell subsets (RRMS; n = 7) were isolated using fluorescence activated cell sorting for bulk RNA sequencing (RNA-Seq). Independent analyses across technologies demonstrated that nuclear factor kappa B (NF-κB) and cholesterol biosynthesis pathways were activated, and specific cytokine and chemokine receptors were up-regulated in CSF memory B cells. Further, SMAD/TGF-β1 signaling was down-regulated in CSF plasmablasts/plasma cells. Clonally expanded, somatically hypermutated IgM+ and IgG1+ CSF B cells were associated with inflammation, blood-brain barrier breakdown, and intrathecal Ig synthesis. While we identified memory B cells and plasmablast/plasma cells with highly similar Ig heavy-chain sequences across MS subjects, similarities were also identified with ONDs and HCs. No viral transcripts, including from Epstein-Barr virus, were detected. Our findings support the hypothesis that in MS, CSF B cells are driven to an inflammatory and clonally expanded memory and plasmablast/plasma cell phenotype
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Test performance evaluation of SARS-CoV-2 serological assays.
Background:Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method:We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. Results:Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. Conclusion:Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies
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Evaluation of SARS-CoV-2 serology assays reveals a range of test performance.
Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (>20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity
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Test performance evaluation of SARS-CoV-2 serological assays.
Background:Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. Method:We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. Results:Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. Conclusion:Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies