Citations

Abstract Background Anxiety is a common symptom experienced by patients with cancer, who are increasingly interested in non-pharmacologic symptom management. Acupressure, a noninvasive intervention thought to impact the neurohormonal axis, has shown promise in reducing anxiety. However, research on acupressure for anxiety in patients with cancer has been limited. Methods Individuals receiving chemotherapy, who reported baseline anxiety, were eligible for this study. Consenting participants received one 15-minute nurse-led acupressure session and completed pre- and post-intervention surveys. The primary endpoint was a change in anxiety. Participants were also asked about symptoms of nausea, pain, well-being, relaxation, worry, and distress. Participants were invited to learn self-acupressure techniques. These participants were asked to complete a final survey 1-week post-intervention. Results Thirty adult patients participated in this study. Mean baseline anxiety was 5 on a 0 to 10 Likert scale. Immediate post-intervention anxiety scores significantly improved for all thirty patients to an average of 2.0 (P < .001). Mean nausea scores improved from 1.5 at baseline to 0 post-intervention (P < .001), and pain scores improved from 2.0 at baseline to 1.0 post-intervention (P = .001). Participants reported significant improvement in sense of wellbeing (P = .0004), distress (P < .001), ability to achieve relaxation (P < .001), and ability to control their worries (P < .001). The improvement in anxiety, well-being, and relaxation was sustained at one week. 100% of participants stated that they would recommend acupressure for symptom management. Conclusion Acupressure is a promising non-pharmacologic intervention for the management of cancer-associated anxiety.

Abstract Background/Aims The aim of this prospective cohort study was to evaluate the extent that kinesiophobia at baseline contributed to pain intensity at follow-up after starting first line treatments in patients with a range of musculoskeletal conditions, including rheumatoid arthritis (RA), fibromyalgia (FM) and knee osteoarthritis (OA). Methods 469 patients (RA n = 156, FM n = 149, OA n = 164) recruited from the Nuffield Orthopaedic Centre, Oxford University Hospitals, participated in this study. Pain was assessed with the pain detect questionnaire, with the item average pain severity over the last 4 weeks used for the primary analysis. The Tampa Scale for Kinesiophobia (TSK) was administered to assess fear of movement. The association between TSK and pain at baseline was investigated by analysing their correlation using Pearson’s Product-Moment Correlation. RA, FM and OA groups were treated with standard care, which consisted of DMARDs, pain rehabilitation therapy, and total knee arthroplasty, respectively. The correlation between baseline TSK and change from baseline in 4-week average pain severity was calculated at 3-, 6- and 12-month follow-up using Pearson’s Product-Moment Correlation. A simple linear regression model was used for each cohort to evaluate the extent TSK contributed to change in pain from baseline. Results At baseline, mean TSK was 38.8±7.0 and mean 4-week average pain severity was 6.6±2.0 (all conditions pooled), with a Pearson’s Product-Moment Correlation of 0.28 [95% CI: 0.18-0.37], representing a small positive correlation (p < 0.01) between baseline TSK and baseline pain. The results were similar for all 3 conditions independently (RA correlation 0.30 [95% CI: 0.14-0.44], FM correlation 0.31 [95% CI: 0.15-0.46], OA correlation 0.25 [95% CI: 0.06-0.41], all ps < 0.01). No correlation was found between TSK and change from baseline in pain severity for the RA or FM cohorts at any follow-up. A weak negative correlation between TSK and change in pain severity was found in the knee OA group at 3 months (correlation: -0.18 [95% CI: -0.39-0.04]) and 12 months (correlation: -0.16 [95% CI: -0.39-0.08]); however, these results were not statistically significant (p = 0.12 and 0.19 respectively). The linear regression analysis showed that TSK was not associated with change in pain from baseline for any condition at any timepoint. Mean pain decreased in the RA and OA groups irrespective of TSK, with no improvement in pain seen in the FM group (RA mean pain at baseline: 6.5±2.1, at 12 months: 4.3±2.6; FM mean pain at baseline: 6.6±1.6, at 12 months: 6.6±1.8; OA mean pain at baseline: 6.5±2.2, at 12 months: 1.9±2.6). Conclusion Whilst kinesiophobia and pain severity were correlated at baseline, kinesiophobia did not negatively influence change in pain with treatment in any of the cohorts studied. Disclosure R.C. Murphy: None. A. Irani: None. E. Kelleher: None. A.J. Wall: None.

Abstract Background/Aims Sleep disturbance is a defining feature of fibromyalgia (FM), contributing to pain, fatigue, cognitive dysfunction, and reduced quality of life. Effective management options remain limited. Cognitive behavioural therapy for insomnia (CBT-I) is effective in primary insomnia, but evidence in FM is sparse and access to face-to-face therapy is limited. Digital CBT-I (dCBT-I) offers a scalable, self-directed solution that may overcome these barriers. We conducted the first randomised controlled trial of dCBT-I in FM to evaluate its impact on quality of life and associated symptoms. Methods This single-blind randomised controlled trial evaluated Sleepio, a validated dCBT-I programme of six self-directed 20-minute sessions delivered over 12 weeks. Participants with a clinical diagnosis of FM, self-reported sleep disturbance, and cognitive complaints were recruited in Oxford, UK. After baseline assessment, participants were randomized to dCBT-I or a control group. All participants also received standardised sleep hygiene advice. The primary outcome was disease-specific quality of life measured by the revised Fibromyalgia Impact Questionnaire (FIQR). Secondary outcomes included insomnia severity (Insomnia Severity Index), actigraphy-derived sleep parameters, pain (SF36 Bodily Pain Scale), cognitive complaints (British Columbia Cognitive Complaints Inventory), sustained attention, and fear of movement (Tampa Scale of Kinesiophobia). Outcomes were collected online at baseline, 3 months, and 6 months. Analyses followed the intention-to-treat principle using constrained longitudinal data analysis. Ethical approval was obtained from South Central - Oxford B Research Ethics Committee (19/SC/0168). The study was pre-registered with clinicaltrials.gov (NCT05962138). Results Of 514 individuals contacted, 241 were screened, 132 were eligible, and 80 were randomised (42 dCBT-I, 38 control). The mean age was 46.6 (SD 14.5) years; 93.8% were female. Retention was high: 97.5% of participants provided outcomes at 3 months, and 83.8% at 6 months. In the dCBT-I group, 90.5% initiated the programme, and 54.8% reached the core session on sleep restriction therapy. At 3 months, there was no significant difference between groups in FIQR (mean difference −2.79; p = 0.3). At 6 months, however, dCBT-I participants demonstrated greater improvement in FIQR compared with controls (mean difference −5.45; 95% CI − 10.5 to − 0.4; p = 0.035), corresponding to a small-to-moderate effect size (Cohen’s d = −0.31). No significant between-group differences were observed for secondary outcomes. Conclusion In adults with FM, dCBT-I produced a sustained, clinically meaningful improvement in disease-related quality of life at 6 months compared with a sleep hygiene control. Although benefits were not observed across secondary outcomes, this trial provides the first controlled evidence that dCBT-I can address an important unmet need in FM. Digital behavioural therapies represent scalable, accessible, non-pharmacological interventions with potential for rapid integration into clinical care. Disclosure E. Kelleher: Grants/research support; National Institute for Health Research (NIHR) Pfizer Doctoral Fellowship (NIHR301808). A.J. Wall: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA. V. Wanigasekera: None. R. Sharman: None. S. Kyle: None. I. Tracey: None. B. Seymour: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA. A. Irani: Grants/research support; Grant is funded by UKRI and Versus Arthritis as part of the UKRI Strategic Priorities Fund (SPF) Advanced Pain Discovery Platform (APDP), a co-funded initiative by UKRI (MRC, BBSRC, ESRC), VA.

ABSTRACT Myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) are clonal myeloid neoplasms shaped by genetic lesions and immune dysregulation, both of which contribute to disease progression and poor outcomes. Existing prognostic systems, such as IPSS‐R and IPSS‐M, do not incorporate immune alterations. We assessed the biological and clinical relevance of an immune dysfunction signature (IDS) across multi‐center MDS and CMML cohorts. IDS scores, derived from bulk transcriptomic data, were significantly associated with inferior leukemia‐free and overall survival. In multivariable analyses, IDS retained independent prognostic value alongside IPSS‐R, IPSS‐M, and bi‐allelic TP53 inactivation. Incorporation of IDS into existing models improved prognostic discrimination and time‐dependent predictive accuracy. Longitudinal analyses revealed that rising IDS scores paralleled disease progression and acute transformation, whereas declining scores were observed in remission. Biologically, IDS‐high cases demonstrated reduced cytotoxic T‐cell activity, expansion of regulatory T cells, enrichment of primitive progenitor signals, and increased expression of checkpoint pathway genes. These findings were validated across multiple independent MDS cohorts and consistently reproduced in CMML, where IDS also stratified risk and tracked disease evolution. Finally, integration with drug response signatures from the BeatAMLv2 cohort suggested potential therapeutic vulnerability of IDS‐high cases to multikinase and NF‐κB pathway inhibitors. These results establish IDS as a robust and dynamic biomarker in MDS and CMML, with applications in refined risk stratification, longitudinal disease monitoring, and guiding personalized therapeutic strategies targeting immune dysfunction. Trial Registration: #201709072RINC, #202109078RINB, #202207050RINB

Abstract Objectives: Community-acquired intra-abdominal infections (CA-IAIs) are a leading cause of US hospitalizations. Piperacillin-tazobactam is often used to empirically treat CA-IAIs, despite national guidelines recommending narrower-spectrum antibiotics for these infections. The overuse of broad-spectrum agents such as piperacillin-tazobactam contributes to antibiotic resistance, which poses serious public health challenges. This resident-led quality improvement initiative aimed to reduce unnecessary piperacillin-tazobactam use for treating CA-IAIs measured as DOT/1,000 patient-days by 10% without adversely affecting hospital length of stay (LOS). Methods: Using the DMAIC (define, measure, analyze, improve, control) framework, we identified barriers to appropriate antibiotic use and developed a treatment algorithm for CA-IAIs that included clear guidelines and exclusion criteria. This algorithm was disseminated to internal medicine residents and emergency department physicians along with educational sessions to highlight updated CA-IAI treatment recommendations, antibiotic resistance, and appropriate antibiotic ordering via the electronic health record. Antimicrobial stewardship pharmacists provided overnight support to assist with de-escalation. Data were collected over a 10-month period spanning 2 intervention phases. The primary outcome was piperacillin-tazobactam use, measured as days of therapy (DOT) per 1,000 patient-days and DOT per patient LOS. Mean LOS served as the balancing measure. Results: Piperacillin-tazobactam use was significantly reduced ( P < .001) after the interventions without increasing the mean LOS. Conclusion: This project raised awareness of antibiotic resistance and led to lasting improvements in reducing the inappropriate use of piperacillin-tazobactam to treat CA-IAIs, without affecting the mean LOS. This was attributed to the strong collaboration among a multidisciplinary team of infectious disease physicians, antimicrobial stewardship team members, residents, emergency department physicians, and faculty.

ABSTRACT Aims To evaluate the real‐world associations between semaglutide 2.4 mg and cardiometabolic comorbidities, biomarkers and cardiovascular risk among adults with overweight or obesity. Methods This retrospective cohort study used US claims data and laboratory measurements from the Komodo Research Database (2016–2024). Adults with obesity or with overweight and ≥ 1 obesity‐related comorbidity were included. Patients on semaglutide 2.4 mg for ≥ 12 months were compared with non‐users (including users of other obesity medications) using propensity score weighting with residual imbalances adjusted in regression model. Outcomes included time to onset of cardiometabolic comorbidities, change in cardiometabolic biomarkers and changes in 10‐year ASCVD risk score at 12 months. Results 25 783 semaglutide 2.4 mg users and 8 948 913 non‐users were identified. Semaglutide 2.4 mg was associated with significantly lower risks for incident prediabetes or type 2 diabetes, type 2 diabetes only, hypertension, ASCVD, heart failure and CVD (HRs 0.45–0.75; all p < 0.05), as well as greater improvements in BMI (−4.1 kg/m 2 ), SBP (−6.2 mmHg), HbA1c (−0.4%), LDL cholesterol (−7.7 mg/dL), triglycerides (−28.6 mg/dL) and HDL cholesterol (+1.9 mg/dL; all p < 0.001). At 12 months, semaglutide 2.4 mg users ( N = 161) demonstrated a greater reduction in ASCVD risk score (−0.7% vs. +0.3%; between‐group difference −1.0%, p < 0.001), with a decrease in the proportion at intermediate‐high ASCVD risk (14.9%–9.3% vs. 17.7%–18.7%; OR 0.3 [95% CI: 0.1, 0.6], p < 0.001). Conclusions Semaglutide 2.4 mg was associated with lower risk of multiple cardiometabolic comorbidities, favourable changes in biomarkers, and lower estimated ASCVD risk in this population.

Abstract Unsupervised molecular clustering is fundamental to precision medicine, yet most published subtyping studies lack standardized validation criteria, making it impossible to distinguish biological signal from statistical artifact. We present the Pathway Subtyping Framework, which enforces four mandatory validation gates—label shuffle, random gene set, bootstrap stability with adaptive thresholds, and ancestry independence—before any clustering result is reported. On TCGA-COAD (n=452), the framework independently recovered CMS4 (Mesenchymal) with 75.9% CMS4 enrichment (Fisher OR=16.71, p=1.4×10⁻²⁵), outperforming PCA+k-means (67%), gene-level k-means (50%), and NMF (32%) on the same data. Applied to autism (n=56) and schizophrenia (n=281) as pilot demonstrations, the framework produced replicable subtypes across platforms (ARI=0.870) and achieved the strongest gate performance across all datasets (bootstrap ARI=0.923). Cross-disease analysis reveals that molecular subtypes are independent of DSM diagnosis (Cramér's V=0.036) but strongly dependent on brain region (V=0.528); within-region concordance is 84% (ARI=0.862), decomposing the 87% global concordance into disease-agnostic and anatomical components. The adaptive bootstrap threshold model, calibrated on 47 independent benchmarks (R²=0.889, LOOCV RMSE=0.051), replaces arbitrary fixed thresholds with data-driven, silhouette-calibrated gates. The framework is open-source (PyPI, Docker, Codeberg; 1,054 tests; DOI:10.5281/zenodo.18867165).