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Gram negative bloodstream infections (GN BSI) are a leading cause of mortality worldwide, and antibiotic treatment approaches remain understudied. BALANCE+ is a perpetual Bayesian adaptive platform trial to test multiple treatment questions for hospitalised patients with GN BSI. The vanguard phase objective was to test the feasibility of the main trial.
Adaptive platform trial with five initial domains of investigation, each with open label 1:1 randomisation.
Ten hospitals across four Canadian provinces.
Individuals admitted to hospital with blood cultures yielding Gram negative bacteria.
The five initial domains of investigation included: antibiotic de-escalation versus no de-escalation; oral transition to beta-lactam versus non-beta-lactam treatment; routine versus no routine follow-up blood cultures (FUBCs); central vascular catheter replacement versus retention; and, ceftriaxone versus carbapenem treatment for low risk AmpC organisms.
Domain-specific recruitment rates and protocol adherence.
During the vanguard phase, 719 patients were screened, of whom 563 (78.3%) were eligible, with 179 (31.8%) enrolled into the platform. The platform recruitment rate was 1.37 patients/site-week. Recruitment varied by domain: routine versus no FUBC domain 1.23 patients/site-week; oral beta-lactam versus non-beta-lactam domain 0.48; de-escalation versus no de-escalation domain 0.28; low risk AmpC domain 0.02; catheter replacement versus retention domain 0.01. Domain specific protocol adherence rates were 145/158 (91.8%) for routine versus no routine FUBC, 53/60 (88.3%) for oral beta-lactam versus non-beta-lactam, 26/33 (78.8%) for de-escalation versus no de-escalation, 3/3 (100%) for low risk AmpC, and 0/1 (0%) for line replacement versus retention. There was complete ascertainment of all study outcomes in hospital 170/170 (100%) and near complete ascertainment at 90 days 162/170 (95.3%).
The vanguard phase demonstrated overall trial feasibility by recruitment rate and protocol adherence, with differences across interventions, leading to a transition to the main BALANCE+ platform trial with minimal protocol modifications.
Methotrexate (MTX) effectively controls rheumatoid arthritis (RA) but often leads to side effects (SE) such as gastrointestinal (GI) issues, liver toxicity and bone marrow suppression. To develop clinically interpretable machine learning (ML) models that accurately predict MTX-related SE in patients with RA taking MTX. The aim was to enhance predictive accuracy and to identify patient-specific risk factors using explainable artificial intelligence (XAI), thereby enabling transparent clinical interpretation. We specifically sought to address the unmet need for individualised risk stratification using real-world, multicentre observational data.
Retrospective case-control study.
Across 23 rheumatology clinics in South Korea, based on data from a nationwide multicentre cohort.
A total of 5077 patients with RA were initially enrolled from the Korean Observational Study Network for Arthritis. After excluding those with missing clinical, demographic or prescription data and those not receiving MTX, 2375 patients remained eligible. Among these, 1654 and 1218 patients were included in the overall SE and GI SE analysis groups, respectively, after 1:1 propensity score matching. All patients were aged ≥18 years and met the 1987 American College of Rheumatology classification criteria.
The primary outcome was the presence of SE in patients with RA taking MTX, categorised into overall SE and GI SE, based on standardised patient questionnaires and clinical assessments. The secondary outcome was the identification of key predictors using SHapley Additive exPlanations (SHAP) to enhance the interpretability of ML predictions.
Among six ML classifiers, extreme gradient boosting demonstrated the highest performance in predicting overall SE (area under the curve (AUC) 0.781, F1 score 0.672, area under the precision-recall curve (AUPRC) 0.757) and GI SE (AUC 0.701, F1 score 0.690, AUPRC 0.670). SHAP analysis identified key predictive features including age, physician visual analogue scale score, alanine aminotransferase, Health Assessment Questionnaire score, celecoxib use and drug adherence. Logistic regression confirmed statistical significance for multiple variables (eg, OR 4.63; 95% CI 1.41 to 20.90 for non-adherence >30 days; OR 1.45; 95% CI 1.14 to 1.85 for celecoxib use). DeLong’s test indicated that boosting models significantly outperformed support vector machine (p
Interpretable ML models using real-world clinical data can accurately predict SE in patients with RA taking MTX. These models may facilitate early identification of high-risk individuals and inform personalised treatment strategies. Integration into clinical decision support systems could improve MTX safety monitoring. Further prospective validation in external cohorts is warranted.
Post-traumatic neck pain is common, representing a substantial human and societal burden. About 15%–25% of individuals involved in an accident causing whiplash continue to experience moderate-to-severe symptoms and functional impairment 1 year post-trauma. Factors such as age, high pain intensity, hypersensitivity to pain and early post-traumatic hyperarousal are associated with persistent neck pain. However, multiple questions remain unanswered regarding how best to improve early care. As such, research on recovery patterns (including indicators for health economic burden) and their predictors is still needed, including biomarkers for pre-traumatic and peri-traumatic stress, and the value of early prediction tools.
This prospective cohort study will include 100 participants (≥18 years) suffering from post-traumatic neck pain sustained within 72 hours of an accident. At baseline (a combination of inclusion and 1 week assessment), eligible participants will undergo a thorough evaluation, including assessment of descriptive characteristics, self-reported variables (eg, pain, disability, sleep quality and post-traumatic stress), biomarkers (eg, heart rate variability (HRV) and hair cortisol) and clinical tests (eg, cervical range of motion). Follow-up will be conducted at 3, 6 and 12 months post-trauma. Further, register data (eg, data on labour market attachment) will be added for the period. Among other methods, a receiver operating characteristic (ROC) curve and multivariable regression analyses will be used to evaluate performance and associations of the prediction tools and their associations with measures of HRV.
The sample size calculation is based on previous studies, estimating that 15% of participants will develop moderate-to-severe ongoing symptoms. Using a conservative estimate, 64 participants are needed to achieve a statistical power of 90% with an expected area under the curve of 0.80. Accounting for a 25% loss to follow-up, 80 participants are required. For regression analysis, 100 participants will be included. The prediction tool will be validated using ROC analysis, sensitivity and specificity. Logistic regression models will be performed with and without biomarkers and pain sensitivity. Health economic costs will be compared across groups. Multivariable regression will examine the link between HRV and post-traumatic stress disorder, adjusting for confounders and a moderation analysis will assess hair cortisol as a potential moderator.
The study is approved by the Regional Committee on Health Research Ethics of Southern Denmark (S-20230037). Due to the acute nature of recruitment, the study design does not allow for a 24-hour reflection period; however, this approach has been approved by the Committee.
Study results will be published in peer-reviewed journals and disseminated through non-scientific outlets, including patient and professional publications, press releases and social media. If effective, workshops for clinicians will be organised. Results will be published regardless of outcome, with coauthorships following ICMJE guidelines.
In Tanzania, acute myocardial infarction (AMI) is underdiagnosed, and uptake of evidence-based care is suboptimal. Using an implementation science approach, an intervention was developed to address local barriers to care: the Multicomponent Intervention for Improving Myocardial Infarction Care in Tanzania (MIMIC).
This sequential cohort design trial was conducted in a single northern Tanzanian emergency department (ED). During the preintervention phase (February–August 2023) and the postintervention phase (September 2023–August 2024), adults presenting with chest pain and/or dyspnoea were prospectively enrolled and their ED care was observed. AMI was defined by the Fourth Universal Definition criteria. Telephone follow-ups were conducted to ascertain 30-day mortality. Pearson’s ² was used to compare care before and after MIMIC implementation.
A total of 275 participants were enrolled in the preintervention phase and 577 were enrolled in the postintervention phase. Following MIMIC implementation, significant increases were observed in ECG testing (89.4% of postintervention participants vs 55.3% preintervention, OR 6.82, 95% CI 4.79 to 9.79, p
The MIMIC intervention was associated with large increases in uptake of AMI testing, case identification and evidence-based treatment in a single Tanzanian ED. Multisite studies are needed to evaluate the effect of MIMIC on AMI care in diverse settings across Tanzania.
To explore how pre-existing conditions affect the diagnostic process for potential cancer in primary care patients.
Qualitative interview study using thematic analysis underpinned by a critical realist approach.
Primary care practices recruited through four Clinical Research Networks and UK health charities across England.
Interviews were conducted with 75 patients with one or more pre-existing conditions (anxiety/depression, diabetes, obesity, chronic obstructive pulmonary disease, Parkinson’s disease or multiple long-term conditions (four or more)) and 28 primary care professionals (general practitioners and nurses).
The study identified legitimacy as a central theme influencing patient trajectories in the health system while trying to receive a diagnosis for symptoms with which they presented to primary care. Patients engaged in self-triage to determine whether symptoms were ‘legitimate’ enough to seek care. Subsequent triaging steps (by receptionists, nurses and online systems) acted as gatekeepers, with decisions influenced by effectiveness of describing the symptom and subjective impressions. During consultations, clinicians relied on a mix of symptom narrative clarity, medical history and objective ‘metrics’ (eg, blood results, family history) to determine legitimacy for further investigations. Pre-existing conditions could either lower the threshold for referrals or obscure potential cancer symptoms. The stigma associated with mental health diagnoses often undermined perceived legitimacy and contributed to delays.
Legitimacy is continuously negotiated throughout the diagnostic pathway. It is shaped by social, moral and biomedical judgements. To promote early cancer diagnosis for patients with pre-existing conditions, clinicians must make legitimacy assessments explicit, reduce stigma especially around mental health and standardise triage processes.
Muscle-invasive bladder cancer (MIBC) is an aggressive type of cancer. About 50% of patients will die from the disease within 5 years despite radical treatment. This implies that in many patients, the disease has already spread at the time of radical treatment, even though imaging shows no signs of metastasis. We hypothesise that the standard local staging method, transurethral resection of the bladder tumour (TURBT), is partly responsible for tumour cell spread. Furthermore, TURBT (and re-TURBT in many patients) contributes to a significant delay to definitive therapy. The aim of this randomised study is to determine whether multiparametric MRI (mpMRI) of the bladder, in combination with a single outpatient bladder tumour biopsy for histological confirmation, is a safer, faster, less costly and, therefore, more cost-effective diagnostic pathway than TURBT to detect or rule out MIBC.
BladParadigm is a two-arm multicentre randomised controlled trial (RCT) conducted in the Netherlands. Over a 3-year period, patients with clinically suspected MIBC without evidence of metastases will be recruited and randomised 1:1 to either TURBT or 3-Tesla mpMRI with same-day outpatient bladder biopsy. The Vesical Imaging Reporting and Data System (VI-RADS) will be used to standardise mpMRI reporting. Patients will undergo definitive treatment based on the results of the TURBT or mpMRI. The study is powered to demonstrate that the mpMRI-based strategy is at least non-inferior to standard TURBT in patients treated with radical cystectomy alone, assuming a relative hazard of 0.55. The required sample size is 360 patients (180 TURBT, 180 mpMRI). The primary outcome is 2-year progression-free survival. Progression will be assessed by imaging, according to the current standard of care. Secondary outcome measures are time to definitive treatment, quality of life (EuroQol 5D-5L), healthcare costs and cost-effectiveness.
This study has received ethical approval from the Medical Ethical Committee Oost-Nederland (NL83685.091.23). All participants will provide written informed consent prior to inclusion. Findings of this study will be disseminated through peer-reviewed, open-access publications, presentations at scientific conferences and stakeholder briefings.
The global burden of chronic immune-mediated inflammatory diseases (IMIDs) is increasing, and rising prevalence rates significantly affect socioeconomic factors and quality of life. Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), along with ankylosing spondylitis (AS), are prominent chronic IMIDs that share overlapping pathophysiological mechanisms. Recent research has highlighted the importance of the gut microbiota in the pathogenesis of these diseases, suggesting that shared microbial dysbiosis may contribute to their development. Comprehensive research focusing on the gut and oral microbial characteristics and environmental factors is essential to elucidate the fundamental pathophysiology and develop personalised management strategies for IBD and AS. In-depth analyses and insights based on multiomics approaches are required to achieve these objectives.
This protocol describes a nationwide prospective observational study of CD, UC and AS in a Korean population. Over 5 years, we aim to recruit at least 900 patients with IBD and 200 first-degree relatives (FDRs), 500 patients with AS and 200 of their FDRs, and 2244 healthy controls. We will systematically collect clinical data and biological samples, including saliva, stool, blood and tissue biopsies, for integrative multiomics analyses focusing primarily on the microbiome. Highly advanced full-length 16S ribosomal RNA gene sequencing and shotgun metagenomics will be used to characterise the microbial composition of saliva and stool samples. Quantitative microbiome profiling will be used to address the pathological, physiological and ecological differences between microbial groups that may be masked by their relative abundance. Metabolomic analyses will be conducted on saliva, stool and plasma samples to assess functional metabolic profiles. Culturomics will be used to isolate, identify and characterise the diversity of microbial species, including rare or previously unrecognised species, to provide a comprehensive understanding of the microbiota associated with these diseases.
Ethical approval was obtained from the Ethics Committee of Kyung Hee University Hospital, Hanyang University Hospital, Kangbuk Samsung Hospital, Yeungnam University Hospital, Kyungpook National University Hospital, Chonnam National University Hospital, Wonkwang University Hospital, Catholic University Daejeon St. Mary’s Hospital, Soon Chun Hyang University Hospital Cheonan, Chung-Ang University Hospital, Inje University Haeundae Paik Hospital, Dankook University Hospital, Hanyang University Guri Hospital, Kyung Hee University Hospital at Gangdong, Chung-Ang University Gwangmyeong Hospital and Keimyung University Dongsan Hospital. Our research team will provide detailed information about the study, including an information sheet explaining its aims and procedures, prior to enrolment. Prospective participants will be informed that they have the right to withdraw from the study at any time, without penalty. Participants will be assured of the anonymity and confidentiality of any data they provide throughout the study, using participant numbers and the storage of sensitive data in locked cabinets. Participants will be enrolled in the study only after providing written informed consent to the research staff. The results of this study will be disseminated to healthcare and academic professionals through publications in peer-reviewed journals and presentations at international conferences.
This prospective observational study is registered at ClinicalTrials.gov ((ID: NCT06124833, data first posted: 9 November 2023); (ID:
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