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Learning How to Improve the Treatment of Persecutory Delusions: Using a Principal Trajectories Analysis to Examine Differential Effects of Two Psychological Interventions (Feeling Safe, Befriending) in Distinct Groups of Patients.
BACKGROUND: A theory-driven cognitive therapy (Feeling Safe) has produced much better outcomes for patients with persecutory delusions. There are four distinct response classes: very high delusion conviction with large improvement, very high delusion conviction with no response, high delusion conviction with large improvement, and high delusion conviction with modest improvement. Our objective was to apply principal trajectories analysis, a novel statistical method, to original trial data to estimate whether these groups may have responded differently to a different intervention: befriending. DESIGN: One hundred and thirty patients with persistent persecutory delusions were randomised to six months of Feeling Safe or befriending. Baseline assessments were used to assign patients allocated to befriending (who did not receive Feeling Safe) into the four Feeling Safe response classes. The treatment effect, including on potential mediators, was then estimated for these classes. RESULTS: Patients in two treatment response classes (Very high conviction/large improvement, High conviction/large improvement) benefited more from Feeling Safe, patients in one group (Very high conviction/no improvement) benefited more from befriending, and patients in the remaining group (High conviction/moderate improvement) benefited equally from the interventions. Mechanism differences were detected when Feeling Safe was superior to befriending, but not when befriending was superior. CONCLUSIONS: There may be patients with psychosis who benefit more from one type of therapy than another, likely due to different change mechanisms. The application of principal trajectories has generated testable hypotheses and a potential step toward personalised treatment. We recommend an investigation of whether sequential provision of the treatment types could enhance patient outcomes. Keywords: persecutory, delusions, outcome trajectories, psychosis, cognitive therapy.
Reasoning to Justify Eating Animals Varies With Age.
The present study examined the justifications used by children, adolescents, and adults to justify eating animals. Children (n = 100, Mage = 9.82, SD = 0.77, female n = 49) as compared to adolescents (n = 76, Mage = 14.0, SD = 1.62, female n = 36) and adults (n = 113, Mage = 44.1, SD = 14.4, female n = 54) were more ambivalent or opposed to eating animals, and they showed a distinct reasoning pattern. Children relied less on arguments about meat eating being natural or with to humane slaughter practices. These findings align with recent theoretical perspectives that reasoning may be used to counter cognitive dissonance arising from knowledge of food production systems.
Comorbidities Are Associated With Unfavorable Outcome in Aquaporin-4 Antibody Positive Neuromyelitis Optica Spectrum Disorders and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease: Exploratory Study From the CROCTINO Cohort.
BACKGROUND: Comorbidities occur in aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and double seronegative NMOSD (DN-NMOSD), potentially contributing to a less favorable disease course. OBJECTIVES: To characterize comorbidities in AQP4-NMOSD, MOGAD, and DN-NMOSD and assess their association with optic neuritis (ON) outcomes by optical coherence tomography (OCT) in AQP4-NMOSD. METHODS: Four hundred and forty-two participants from the CROCTINO cohort were evaluated for comorbidities. RESULTS: In AQP4-NMOSD patients (n = 360), 43.5% (n = 161) had comorbidities, equally divided between single and multiple. In MOGAD (n = 49), 40.8% had comorbidities, with 75% (n = 15) single and 25% (n = 5) multiple. In DN-NMOSD (n = 33), 36.4% (n = 12) had comorbidities equally split. AQP4-NMOSD patients had more multiple comorbidities (50%, n = 81/161) than MOGAD (25%, n = 5/20, p = 0.03) and more autoimmune disorders (AID) (40.4%, n = 65) than MOGAD (20%, n = 4, p = 0.09) and DN-NMOSD (none, p = 0.004). Cardiovascular comorbidities and related risk factors (CVC/RF) occurred in 34.8% (n = 56) of AQP4-NMOSD, 50% (n = 10) of MOGAD, and 33.3% (n = 4) of DN-NMOSD. Expanded Disability Status Scale was higher in MOGAD (3.0 vs. 2.0, p = 0.006) and DN-NMOSD (5.0 vs. 2.0, p = 0.008) with comorbidities. AQP4-NMOSD patients with CVC/RF had higher ON relapse rates than those with AID (1.06 ± 3.33 vs. 0.49 ± 0.98, p
Submaximal 2-day cardiopulmonary exercise testing to assess exercise capacity and post-exertional symptom exacerbation in people with long COVID.
Long COVID has a complex pathology and a heterogeneous symptom profile that impacts quality of life and functional status. Post-exertional symptom exacerbation (PESE) affects one-third of people living with long COVID, but the physiological basis of impaired physical function remains poorly understood. Sixty-eight people (age (mean ± SD): 50 ± 11 years, 46 females (68%)) were screened for severity of PESE and completed two submaximal cardiopulmonary exercise tests separated by 24 h. Work rate was stratified relative to functional status and was set at 10, 20 or 30 W, increasing by 5 W/min for a maximum of 12 min. At the first ventilatory threshold (VT1), V ̇ O 2 ${\dot V_{{{\mathrm{O}}_2}}}$ was 0.73 ± 0.16 L/min on Day 1 and decreased on Day 2 (0.68 ± 0.16 L/min; P = 0.003). Work rate at VT1 was lower on Day 2 (Day 1 vs. Day 2; 28 ± 13 vs. 24 ± 12 W; P = 0.004). Oxygen pulse on Day 1 at VT1 was 8.2 ± 2.2 mL/beat and was reduced on Day 2 (7.5 ± 1.8 mL/beat; P = 0.002). The partial pressure of end tidal carbon dioxide was reduced on Day 2 (Day 1 vs. Day 2; 38 ± 3.8 vs. 37 ± 3.2 mmHg; P = 0.010). Impaired V ̇ O 2 ${\dot V_{{{\mathrm{O}}_2}}}$ is indicative of reduced transport and/or utilisation of oxygen. V ̇ O 2 ${\dot V_{{{\mathrm{O}}_2}}}$ at VT1 was impaired on Day 2, highlighting worsened function in the 24 h after submaximal exercise. The data suggest multiple contributing physiological mechanisms across different systems and further research is needed to investigate these areas.
Protocol for a prospective cohort study to determine the multimodal biomarkers of delirium and new dementia after acute illness in older adults: ORCHARD-PS
Introduction Delirium is common in the older hospital population and is often precipitated by acute illness. Delirium is associated with poor outcomes including subsequent cognitive decline and dementia and may therefore be a modifiable risk factor for dementia. However, the mechanisms underpinning the delirium-dementia relationship and the role of coexisting acute illness factors remain uncertain. Current biomarker studies of delirium have limitations including lack of detailed delirium characterisation with few studies on neurodegenerative or neuroimaging biomarkers especially in the acute setting. The Oxford and Reading Cognitive Health After Recovery from acute illness and Delirium - Prospective Study (ORCHARD-PS) aims to elucidate the pathophysiology of delirium and subsequent cognitive decline after acute illness in older adults, through acquisition of multimodal biomarkers for deep phenotyping of delirium and acute illness, and follow-up for incident dementia. Methods and analysis ORCHARD-PS is a bi-centre, prospective cohort study. Consecutive eligible patients requiring acute hospital admission or assessment are identified by the relevant acute clinical care team. All patients age >65 years without advanced dementia, nursing home residence, end-stage frailty or terminal illness are eligible. Details of potential participants are communicated to the research team and written informed consent or consultee agreement is obtained. Participants are interviewed as soon as possible after admission/assessment using a structured proforma. Data are collected on demographics, diagnosis and comorbidities, social and functional background. Delirium is assessed using the 4A's test, Confusion Assessment Method (long-form), Observational Scale of Level of Arousal, Richmond Agitation-Sedation Scale and Memorial Delirium Assessment Scale and diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Delirium is categorised by time of onset (prevalent vs incident), dementia status, motoric subtype, severity and duration. Cognitive tests include the 10-point Abbreviated Mental Test and Montreal Cognitive Assessment. Participants are reassessed every 48-72 hours if remaining in hospital. Informant questionnaire data and interview are supplemented by hand searching of medical records and linkage to electronic patient records for nursing risk assessments, vital observations, laboratory results and International Classification of Diseases, Tenth Revision diagnostic and procedure codes. In-person follow-up with more detailed cognitive testing and informant interview is undertaken at 3 months, and 1 and 3 years supplemented with indirect follow-up using medical records. Blood banking is performed at baseline and all follow-ups for future biomarker analyses. CT-brain and MRI-brain imaging acquired as part of standard care is obtained for quantification of brain atrophy and white matter disease/stroke supplemented by research CT-brain imaging. Outcomes include length of hospitalisation, change in care needs, institutionalisation, mortality, readmission, longitudinal changes in cognitive and functional status and incident dementia. Biomarker associations with delirium, and with incident dementia on follow-up, will be determined using logistic or Cox regression as appropriate, unadjusted and adjusted for covariates including demographics, baseline cognition, frailty, comorbidity and apolipoprotein E genotype. Ethics and dissemination ORCHARD-PS is approved by the South Central - Berkshire Research Ethics Committee (REC Reference: 23/SC/0199). Results will be disseminated through peer-reviewed publications and conference presentations.
Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal.
BACKGROUND: Blood tests used to identify patients at increased risk of undiagnosed cancer are commonly used in isolation, primarily by monitoring whether results fall outside the normal range. Some prediction models incorporate changes over repeated blood tests (or trends) to improve individualized cancer risk identification, as relevant trends may be confined within the normal range. OBJECTIVE: Our aim was to critically appraise existing diagnostic prediction models incorporating blood test trends for the risk of cancer. METHODS: MEDLINE and EMBASE were searched until April 3, 2025 for diagnostic prediction model studies using blood test trends for cancer risk. Screening was performed by 4 reviewers. Data extraction for each article was performed by 2 reviewers independently. To critically appraise models, we narratively synthesized studies, including model building and validation strategies, model reporting, and the added value of blood test trends. We also reviewed the performance measures of each model, including discrimination and calibration. We performed a random-effects meta-analysis of the c-statistic for a trends-based prediction model if there were at least 3 studies validating the model. The risk of bias was assessed using the PROBAST (prediction model risk of bias assessment tool). RESULTS: We included 16 articles, with a total of 7 models developed and 14 external validation studies. In the 7 models derived, full blood count (FBC) trends were most commonly used (86%, n=7 models). Cancers modeled were colorectal (43%, n=3), gastro-intestinal (29%, n=2), nonsmall cell lung (14%, n=1), and pancreatic (14%, n=1). In total, 2 models used statistical logistic regression, 2 used joint modeling, and 1 each used XGBoost, decision trees, and random forests. The number of blood test trends included in the models ranged from 1 to 26. A total of 2 of 4 models were reported with the full set of coefficients needed to predict risk, with the remaining excluding at least one coefficient from their article or were not publicly accessible. The c-statistic ranged 0.69-0.87 among validation studies. The ColonFlag model using trends in the FBC was commonly externally validated, with a pooled c-statistic=0.81 (95% CI 0.77-0.85; n=4 studies) for 6-month colorectal cancer risk. Models were often inadequately tested, with only one external validation study assessing model calibration. All 16 studies scored a low risk of bias regarding predictor and outcome details. All but one study scored a high risk of bias in the analysis domain, with most studies often removing patients with missing data from analysis or not adjusting the derived model for overfitting. CONCLUSIONS: Our review highlights that blood test trends may inform further investigation for cancer. However, models were not available for most cancer sites, were rarely externally validated, and rarely assessed calibration when they were externally validated.
Driving cognitive change: a guide to behavioural experiments in cognitive therapy for anxiety disorders and PTSD.
Behavioural experiments are experiential exercises used in Cognitive Behavioural Therapy to drive cognitive change by testing patients' idiosyncratic, emotionally linked beliefs. In this paper, we provide clinical guidance on how to deliver effective behavioural experiments that maximise cognitive change based on lessons learnt over the last 30 years from our work using Cognitive Therapy to treat Panic Disorder (CT-PD), Social Anxiety Disorder (CT-SAD) and Post-Traumatic Stress Disorder (CT-PTSD). We describe key steps for setting up and carrying out powerful experiments, including common blocks and barriers patients and therapists come across when using them.
Connectivity-based parcellation of grey matter
While with methodological advances a connectivity-based parcellation of the entire ... Relating connectional architecture to grey matter function using ...
Spatiotemporal dynamics of bimanual integration in human somatosensory cortex and their relevance to bimanual object manipulation
Little is known about the spatiotemporal dynamics of cortical responses that integrate slightly asynchronous somatosensory inputs from both hands. This study aimed to clarify the timing and magnitude of interhemispheric interactions during early integration of bimanual somatosensory information in different somatosensory regions and their relevance for bimanual object manipulation and exploration. Using multi-fiber probabilistic diffusion tractography and MEG source analysis of conditioning-test (C-T) median nerve somatosensory evoked fields in healthy human subjects, we sought to extract measures of structural and effective callosal connectivity between different somatosensory cortical regions and correlated them with bimanual tactile task performance. Neuromagnetic responses were found in major somatosensory regions, i.e., primary somatosensory cortex SI, secondary somatosensory cortex SII, posterior parietal cortex, and premotor cortex. Contralateral to the test stimulus, SII activity was maximally suppressed by 51% at C-T intervals of 40 and 60 ms. This interhemispheric inhibition of the contralateral SII source activity correlated directly and topographically specifically with the fractional anisotropy of callosal fibers interconnecting SII. Thus, the putative pathway that mediated inhibitory interhemispheric interactions in SII was a transcallosal route from ipsilateral to contralateral SII. Moreover, interhemispheric inhibition of SII source activity correlated directly with bimanual tactile task performance. These findings were exclusive to SII. Our data suggest that early interhemispheric somatosensory integration primarily occurs in SII, is mediated by callosal fibers that interconnect homologous SII areas, and has behavioral importance for bimanual object manipulation and exploration. © 2012 the authors.