Obesity alters oestrogen metabolism and contributes to pulmonary arterial hypertension

Obesity is a common comorbidity for pulmonary arterial hypertension (PAH). Additionally, oestrogen and its metabolites are risk factors for the development of PAH. Visceral adipose tissue (VAT) is a major site of oestrogen production; however, the influence of obesity-induced changes in oestrogen synthesis and metabolism on the development of PAH is unclear. To address this we investigated the effects of inhibiting oestrogen synthesis and metabolism on the development of pulmonary hypertension (PH) in male and female obese mice. We depleted endogenous oestrogen in leptin deficient (ob/ob) mice with the oestrogen inhibitor anastrozole (ANA) and determined the effects on the development of PH, plasma oestradiol and urinary 16α-hydroxyestrone (16αOHE1). Oestrogen metabolism through CYP1B1 was inhibited with 2,2',4,6'-tetramethoxystilbene (TMS). Ob/ob mice spontaneously develop PH, pulmonary vascular remodelling and increased reactive oxygen species (ROS) production in the lung; these effects were attenuated by ANA. Oestradiol levels were decreased in obese male mice; however, VAT CYP1B1 and 16αOHE1 levels were increased. TMS also attenuated PH in male ob/ob mice. Intra-thoracic fat from ob/ob mice and VAT conditioned media produce 16αOHE1 and can contribute to oxidative stress; effects that are attenuated by both ANA and TMS. Obesity can induce PH and changes in oestrogen metabolism, resulting in increased production of 16αOHE1 from VAT that contributes to oxidative stress. Oestrogen inhibitors are now in clinical trials for PAH. This study has translational consequences as it suggests that oestrogen inhibitors may be especially beneficial in treating obese individuals with PA

Improving sleep after stroke: a randomised controlled trial of digital cognitive behavioural therapy for insomnia

Stroke is frequently accompanied by long-term sleep disruption. We therefore aimed to assess the efficacy of digital cognitive behavioural therapy for insomnia to improve sleep after stroke. A parallel group randomised controlled trial was conducted remotely in participant's homes/online. Randomisation was online with minimisation of between-group differences in age and baseline Sleep Condition Indicator-8 score. In total, 86 community-dwelling stroke survivors consented, of whom 84 completed baseline assessments (39 female, mean 5.5 years post-stroke, mean 59 years old), and were randomised to digital cognitive behavioural therapy or control (sleep hygiene information). Follow-up was at post-intervention (mean 75 days after baseline) and 8 weeks later. The primary outcome was self-reported insomnia symptoms, as per the Sleep Condition Indicator-8 (range 0–32, lower numbers indicate more severe insomnia, reliable change 7 points) at post-intervention. There were significant improvements in Sleep Condition Indicator-8 for digital cognitive behavioural therapy compared with control (intention-to-treat, digital cognitive behavioural therapy n = 48, control n = 36, 5 imputed datasets, effect of group p ≤ 0.02, η2p = 0.07–0.12 [medium size effect], pooled mean difference = −3.35). Additionally, secondary outcomes showed shorter self-reported sleep-onset latencies and better mood for the digital cognitive behavioural therapy group, but no significant differences for self-efficacy, quality of life or actigraphy-derived sleep parameters. Cost-effectiveness analysis found that digital cognitive behavioural therapy dominates over control (non-significant cost savings and higher quality-adjusted life years). No related serious adverse events were reported to the researchers. Overall, digital cognitive behavioural therapy for insomnia effectively improves sleep after stroke. Future research is needed to assess earlier stages post-stroke, with a longer follow-up period to determine whether it should be included as part of routine post-stroke care. Clinicaltrials.gov NCT04272892

Improving sleep and learning in rehabilitation after stroke, part 2 (INSPIRES2): study protocol for a home-based randomised control trial of digital cognitive behavioural therapy (dCBT) for insomnia

Introduction Consolidation of motor skill learning, a key component of rehabilitation post-stroke, is known to be sleep dependent. However, disrupted sleep is highly prevalent after stroke and is often associated with poor motor recovery and quality of life. Previous research has shown that digital cognitive behavioural therapy (dCBT) for insomnia can be effective at improving sleep quality after stroke. Therefore, the aim of this trial is to evaluate the potential for sleep improvement using a dCBT programme, to improve rehabilitation outcomes after stroke. Methods and analysis We will conduct a parallel-arm randomised controlled trial of dCBT (Sleepio) versus treatment as usual among individuals following stroke affecting the upper limb. Up to 100 participants will be randomly allocated (2:1) into either the intervention (6–8 week dCBT) or control (continued treatment as usual) group. The primary outcome of the study will be change in insomnia symptoms pre to post intervention compared with treatment as usual. Secondary outcomes include improvement in overnight motor memory consolidation and sleep measures between intervention groups, correlations between changes in sleep behaviour and overnight motor memory consolidation in the dCBT group and changes in symptoms of depression and fatigue between the dCBT and control groups. Analysis of covariance models and correlations will be used to analyse data from the primary and secondary outcomes. Ethics and dissemination The study has received approval from the National Research Ethics Service (22/EM/0080), Health Research Authority (HRA) and Health and Care Research Wales (HCRW), IRAS ID: 306 291. The results of this trial will be disseminated via presentations at scientific conferences, peer-reviewed publication, public engagement events, stakeholder organisations and other forms of media where appropriate. Trial registration number NCT05511285

Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context

Background: Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence. Aims: The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs. Method: An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health. Results: Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general. Conclusion: The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk

Depression prevalence using the HADS-D compared to SCID major depression classification:An individual participant data meta-analysis

Objectives: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale – depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. Results: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was −21.1% to 19.5%. Conclusions: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.This study was funded by the Canadian Institutes of Health Research (CIHR, KRS-144045 & PCG 155468). Ms. Neupane was supported by a G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University. Drs. Levis and Wu were supported by Fonds de recherche du Québec - Santé (FRQS) Postdoctoral Training Fellowships. Mr. Bhandari was supported by a studentship from the Research Institute of the McGill University Health Centre. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. Dr. Patten was supported by a Senior Health Scholar award from Alberta Innovates, Health Solutions. The primary study by Scott et al. was supported by the Cumming School of Medicine and Alberta Health Services through the Calgary Health Trust, and funding from the Hotchkiss Brain Institute. The primary study by Amoozegar et al. was supported by the Alberta Health Services, the University of Calgary Faculty of Medicine, and the Hotchkiss Brain Institute. The primary study by Cheung et al. was supported by the Waikato Clinical School, University of Auckland, the Waikato Medical Research Foundation and the Waikato Respiratory Research Fund. The primary study by Cukor et al. was supported in part by a Promoting Psychological Research and Training on Health-Disparities Issues at Ethnic Minority Serving Institutions Grants (ProDIGs) awarded to Dr. Cukor from the American Psychological Association. The primary study by De Souza et al. was supported by Birmingham and Solihull Mental Health Foundation Trust. The primary study by Honarmand et al. was supported by a grant from the Multiple Sclerosis Society of Canada. The primary study by Fischer et al. was supported as part of the RECODEHF study by the German Federal Ministry of Education and Research (01GY1150). The primary study by Gagnon et al. was supported by the Drummond Foundation and the Department of Psychiatry, University Health Network. The primary study by Akechi et al. was supported in part by a Grant-in-Aid for Cancer Research (11−2) from the Japanese Ministry of Health, Labour and Welfare and a Grant-in-Aid for Young Scientists (B) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. The primary study by Kugaya et al. was supported in part by a Grant-in-Aid for Cancer Research (9–31) and the Second-Term Comprehensive 10-year Strategy for Cancer Control from the Japanese Ministry of Health, Labour and Welfare. The primary study Ryan et al. was supported by the Irish Cancer Society (Grant CRP08GAL). The primary study by Keller et al. was supported by the Medical Faculty of the University of Heidelberg (grant no. 175/2000). The primary study by Love et al. (2004) was supported by the Kathleen Cuningham Foundation (National Breast Cancer Foundation), the Cancer Council of Victoria and the National Health and Medical Research Council. The primary study by Love et al. (2002) was supported by a grant from the Bethlehem Griffiths Research Foundation. The primary study by Löwe et al. was supported by the medical faculty of the University of Heidelberg, Germany (Project 121/2000). The primary study by Navines et al. was supported in part by the Spanish grants from the Fondo de Investigación en Salud, Instituto de Salud Carlos III (EO PI08/90869 and PSIGEN-VHC Study: FIS-E08/00268) and the support of FEDER (one way to make Europe). The primary study by O'Rourke et al. was supported by the Scottish Home and Health Department, Stroke Association, and Medical Research Council. The primary study by Sanchez-Gistau et al. was supported by a grant from the Ministry of Health of Spain (PI040418) and in part by Catalonia Government, DURSI 2009SGR1119. The primary study by Gould et al. was supported by the Transport Accident Commission Grant. The primary study by Rooney et al. was supported by the NHS Lothian Neuro-Oncology Endowment Fund. The primary study by Schwarzbold et al. was supported by PRONEX Program (NENASC Project) and PPSUS Program of Fundaçao de Amparo a esquisa e Inovacao do Estado de Santa Catarina (FAPESC) and the National Science and Technology Institute for Translational Medicine (INCT-TM). The primary study by Simard et al. was supported by IDEA grants from the Canadian Prostate Cancer Research Initiative and the Canadian Breast Cancer Research Alliance, as well as a studentship from the Canadian Institutes of Health Research. The primary study by Singer et al. (2009) was supported by a grant from the German Federal Ministry for Education and Research (no. 01ZZ0106). The primary study by Singer et al. (2008) was supported by grants from the German Federal Ministry for Education and Research (# 7DZAIQTX) and of the University of Leipzig (# formel. 1–57). The primary study by Meyer et al. was supported by the Federal Ministry of Education and Research (BMBF). The primary study by Stone et al. was supported by the Medical Research Council, UK and Chest Heart and Stroke, Scotland. The primary study by Turner et al. was supported by a bequest from Jennie Thomas through Hunter Medical Research Institute. The primary study by Walterfang et al. was supported by Melbourne Health. Drs. Benedetti and Thombs were supported by FRQS researcher salary awards. No other authors reported funding for primary studies or for their work on this study. No funder had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level