Pulmonary embolism (PE) is a life-threatening condition with significant morbidity and mortality. The relationship between psychiatric disorders and PE outcomes is complex and not well understood. This study aimed to determine the impact of psychiatric disorders on PE outcomes by comparing patients with and without these conditions.

Using the National Inpatient Sample database, we analysed 725 725 adult patients hospitalised with PE between 2016 and 2019. Patients were stratified based on the presence or absence of psychiatric disorders. Multivariable logistic regression models were used to examine associations between psychiatric disorders and in-hospital outcomes, adjusting for baseline differences.

Of the patients studied, 26.6% had psychiatric disorders. These patients were younger (59.80 vs 63.91 years, p

Psychiatric disorders are associated with distinct management and outcomes in PE. Recognising these unique characteristics may help optimise care for this population; further research is needed to clarify the best management strategies.

Selecting an optimal initial dosage of opioid agonist treatment (OAT) balances effectiveness and safety, as initial doses that are too low may be insufficient, potentially prompting clients to seek unregulated drugs to alleviate withdrawal symptoms, which may increase the likelihood of treatment discontinuation. Conversely, initial doses that are too high carry a risk of overdose. As opioid tolerance levels have risen in the fentanyl era, linked population-level data capturing initial doses in the real world provide a valuable opportunity to refine existing guidance on optimal OAT dosing at treatment initiation. Our objective is to determine the comparative effectiveness of alternative initial doses of methadone, buprenorphine-naloxone and slow-release oral morphine at OAT initiation, as observed in clinical practice in British Columbia (BC), Canada.

We propose a population-level retrospective observational study with a linkage of nine provincial health administrative databases in BC, Canada (1 January 2010 to 31 December 2022). Our study includes two time-to-event primary outcomes: OAT discontinuation and all-cause mortality during follow-up. We propose ‘initiator’ target trial analyses for each medication using both propensity score weighting and instrumental variable analyses to compare the effect of different initial OAT doses on the hazard of time-to-OAT discontinuation and all-cause mortality. A range of sensitivity analyses will be used to assess the robustness of the results.

The protocol, cohort creation and analysis plan have been classified and approved as a quality improvement initiative by Providence Health Care Research Ethics Board and the Simon Fraser University Office of Research Ethics. Results will be disseminated to local advocacy groups and decision-makers, national and international clinical guideline developers, presented at international conferences and published in peer-reviewed journals electronically and in print.

Prediction models for post-stroke mortality can support medical decision-making. Although numerous models have been developed, external validation studies determining the models’ transportability beyond the original settings are lacking. We aimed to assess the performance of two prediction models for post-stroke mortality in Berlin, Germany.

We used data from the Berlin-SPecific Acute Treatment in Ischaemic or hAemorrhagic stroke with Long-term follow-up (B-SPATIAL) registry.

Multicentre stroke registry in Berlin, Germany.

Adult patients admitted within 6 hours after symptom onset and with a 10th revision of the International Classification of Diseases discharge diagnosis of ischaemic stroke, haemorrhagic stroke or transient ischaemic attack at one of 15 hospitals with stroke units between 1 January 2016 and 31 January 2021.

We evaluated calibration (calibration-in-the-large, intercept, slope and plot) and discrimination performance (c-statistic) of Bray et al’s 30-day mortality and Smith et al’s in-hospital mortality prediction models. Information on mortality was supplemented by Berlin city registration office records.

For the validation of Bray et al’s model, we included 7879 patients (mean age 75; 55.0% men). We observed 763 (9.7%) deaths within 30 days of stroke compared with 680 (8.6%) predicted. The model’s c-statistic was 0.865 (95% CI: 0.851 to 0.879). For Smith et al’s model, we performed the validation among 1931 patients (mean age 75; 56.2% men), observing 105 (5.4%) in-hospital deaths compared with the 92 (4.8%) predicted. The c-statistic was 0.891 (95% CI: 0.864 to 0.918). The calibration plots of both models revealed an underestimation of the mortality risk for high-risk patients.

Among Berlin stroke patients, both models showed good calibration performance for low and medium-risk patients and high discrimination while underestimating risk among high-risk patients. The acceptable performance of Bray et al’s model in Berlin illustrates how a small number of routinely collected variables can be sufficient for valid prediction of post-stroke mortality.

Huge advances in rheumatoid arthritis (RA) treatment mean an increasing number of patients now achieve disease remission. However, long-term treatments can carry side effects and associated financial costs. In addition, some patients still experience painful and debilitating disease flares, the mechanisms of which are poorly understood. High rates of flare and a lack of effective prediction tools can limit attempts at treatment withdrawal. The BIOlogical Factors that Limit sustAined Remission in rhEumatoid arthritis (BIO-FLARE) experimental medicine study was designed to study flare and remission immunobiology. Here, we present the clinical outcomes and predictors of drug-free remission and flare, and develop a prediction model to estimate flare risk.

BIO-FLARE was a multicentre, prospective, single-arm, open-label experimental medicine study conducted across seven National Health Service Trusts in the UK. Participants had established RA in clinical remission (disease activity score in 28 joints with C reactive protein (DAS28-CRP)

The intervention was disease-modifying anti-rheumatic drug cessation, followed by observation for 24 weeks or until flare, with clinical and immune monitoring.

The primary outcome measure was the proportion of participants experiencing a confirmed flare, defined as DAS28-CRP≥3.2 or DAS28-CRP≥2.4 twice within 2 weeks, and time to flare. Exploratory predictive modelling was also performed using multivariable Cox regression to understand risk factors for flare.

121 participants were recruited between September 2018 and December 2020. Flare rate by week 24 was 52.3% (95% CI 43.0 to 61.7), with a median (IQR) time to flare of 63 (41–96) days. Female sex, baseline methotrexate use, anti-citrullinated peptide antibody level and rheumatoid factor level were associated with flare. An exploratory prediction model incorporating these variables allowed estimation of flare risk, with acceptable classification (C index 0.709) and good calibration performance.

The rate of flare was approximately 50%. Several baseline clinical parameters were associated with flare. The BIO-FLARE study design provides a robust experimental medicine model for studying flare and remission immunobiology.

ISRCTN registry 16371380