BMJ Evidence-Based Medicine最新文献

Objectives: Our objective was to develop and test prompts designed to generate balanced, evidence-based information from artificial intelligence (AI) for the development of patient decision aid (DA) content. We compared the outputs of this AI-enhanced strategy with those produced by an experienced human team using a traditional development approach.

Methods: We conducted a comparative, mixed-methods, multiple-case study, with each case being a DA. Eight DAs were randomly selected from the Ottawa Inventory, stratified by author type (commercial, academic, public institution, professional association). We then followed a systematic process involving two researchers working independently. One researcher described the topics of the selected DAs and extracted their content by listing the available options with their benefits and harms. The other researcher-blind to the DA-used the topic description to generate AI-enhanced DA content by iteratively refining the prompt structures based on the International Patient Decision Aids Standards until the generated content stabilised. Quantitative analyses compared the number of options, benefits and harms generated by the traditional and AI-enhanced strategies, while qualitative analyses examined the differences in content.

Results: The selected DAs targeted different populations (older adults, women, the general population, children) and were produced in Canada, the UK, the USA or Australia. One type of DA (n=6) focused on a specific option (eg, whether to get vaccinated against COVID-19), the other (n=2) focused on improving an outcome (eg, treating attention-deficit/hyperactivity disorder symptoms). For option-focused DAs, 66% of the benefits/harms were generated by the AI-enhanced strategy only and 6.2% by the traditional strategy only. For outcome-focused DAs, 47% of the options were generated by the AI-enhanced strategy only, and 4% by the traditional strategy only. An evidence search confirmed that the options generated only by the AI-enhanced strategy were indeed beneficial, ruling out hallucinations. However, the AI-enhanced strategy did not suggest optimal combinations. Qualitative analysis showed that AI-enhanced content was generally richer.

Conclusions: This study provides practical guidance on leveraging AI to improve the efficiency of DA development and improve their quality.

Objectives: First, investigate whether a long compared with a short abstract decreases readers' attention. Second, investigate differences regarding perceptions of informativeness, accuracy, attractiveness and conciseness.

Design: Two-arm, single-blinded, parallel-group, superiority randomised controlled trial with 1:1 allocation.

Setting/participants: Researchers worldwide who indexed any type of systematic review in PubMed with an English abstract between 1 January 2024 and 26 March 2024.

Interventions: Researchers were randomly assigned to two groups. Both groups received the same cover letter by email with a link to our survey, which was assigned to either the short (277 words) or long abstract (771 words) of the same systematic review published in two different journals.

Main outcome measures: Primary outcome was the proportion of trial participation after reading the abstract, indicating readers' attention. Secondary outcomes were researchers' perceptions of four indicators of a well-written abstract (informativeness, accuracy, attractiveness, conciseness), and general abstract characteristics.

Results: A total of 5397 authors were randomly assigned to the short (n=2691) or long abstract (n=2706). Trial participation did not differ between groups (37.8% vs 35.0%; p=0.1935). While the short abstract was considered more attractive (60.5% vs 46.6%; p=0.0034) and concise (82.3% vs 37.9%; p<0.0001), the length had no impact on its informativeness (85.5% vs 91.2%; p=0.0594) and accuracy (80.2% vs 86.3%; p=0.0868). Regarding general abstract characteristics, 76.0% preferred a maximum length of 250-300 words, nearly all a structured format and about half supported reporting funding and registration information.

Conclusions: Abstract length had no impact on readers' attention, but short abstracts were considered more attractive and concise. Guidelines like PRISMA-A should recommend a range of 250-300 words for abstracts, allowing authors to include key information while prioritising clarity and precision. With authors considering information on funding and registration as important, journals should update their author guidelines to include these by default.

Trial registration number: NCT06525805.FundingNone.

Objective: To compare the effects of early physical interventions on the prevention of intensive care unit-acquired weakness (ICUAW) and the improvement of relevant clinical outcomes in patients with critical illness.

Methods: We systematically searched the Web of Science, PubMed, Embase and the Cochrane Central Register of Controlled Trials from their inception until 20 August 2024, to identify randomised controlled trials (RCTs) enrolling patients ≥18 years old and implementing early physical intervention that commenced at any time point during mechanical ventilation (MV) use or within 7 days after intensive care unit (ICU) admission for review. We synthesised data using a random-effects model and analysed through network meta-analysis (NMA) and component network meta-analysis (CNMA).

Main outcome measures: Primary outcome is the incidence of ICUAW. Secondary outcomes included Medical Research Council sum score, length of stay in the ICU or hospital, duration of MV and mortality rates in the ICU or hospital.

Results: Our analyses included 63 RCTs involving 24 treatments and eight components. The NMA results revealed systematic early mobilisation (SEM) combined with neuromuscular electrical stimulation (NMES), SEM alone and NMES alone may lead to a moderate to large reduction in the incidence of ICUAW (odds ratios [ORs]=0.03, 0.09 and 0.12, 95% confidence intervals [CIs]=0.00 to 0.42, 0.01 to 0.97 and 0.03 to 0.44, respectively) and improved relevant clinical outcomes compared with routine care. The CNMA results further indicated that SEM (OR=0.14, 95% CI=0.02 to 0.83) and NMES (OR=0.22, 95% CI=0.09 to 0.52) effectively mitigated the ICUAW incidence.

Conclusions: SEM and NMES are optimal interventions for preventing ICUAW. Healthcare providers in ICUs should implement early mobilisation with structured protocols and patient assessments or apply NMES to specific muscle groups to prevent ICUAW in critically ill patients and improve relevant clinical outcomes.

Prospero registration number: CRD42024581173.

Objective: To assess evidence of overall survival (OS) benefits of cancer drugs listed in China's National Reimbursement Drug List (NRDL), the guiding standard for public insurance coverage of drugs and characterise the evolution of survival evidence after NRDL inclusion.

Design: Retrospective observational study.

Setting: China's NRDL and journal publications.

Participants: Adult cancer drug indications approved in China from 1 January 2005 to 30 June 2022.

Main outcome measures: The primary outcome was the availability of OS benefit evidence at the time of initial NRDL listing, defined as a statistically significant survival gain over the control arm in pivotal clinical trials. The secondary outcome was the availability of evidence on clinical benefits after NRDL inclusion as of 31 December 2023, measured by OS and the European Society for Medical Oncology-Magnitude of Clinical Benefit Scale (ESMO-MCBS) version 1.1. ESMO-MCBS scores A to B in the curative setting or 4 or 5 in the non-curative setting were considered a substantial clinical benefit.

Results: By 30 June 2022, 72.6% (175/241) of cancer indications approved in China were included in the NRDL. The median time interval between marketing authorisation and NRDL inclusion decreased from 9.4 years in 2005-2010 to 4.1 years in 2011-2016, and 1.1 years in 2017-2022. 62 (35.4%) and 4 (2.3%) indications had documented OS benefits at the time of NRDL assessment or after, respectively. The median survival benefit was 3.9 months. Of the 109 indications without documented OS benefits by the end of the observation, 21 (19.3%) had substantial clinical benefits as measured by the ESMO-MCBS.

Conclusions and relevance: The time interval from regulatory approval to NRDL listing in China decreased over time. However, more than half of cancer drug indications listed for public insurance reimbursement did not have confirmed survival gain or substantial clinical benefits at the time of NRDL inclusion or after. Payers should give sufficient consideration to clinical benefit evidence when making reimbursement and disinvestment decisions to avoid wasteful spending of public health insurance funds.

Objectives: The objective of our study was to assess the benefits and harms of tramadol vs placebo in adults with chronic pain.

Design: The research method was a systematic review of randomised clinical trials with meta-analysis. The review followed the Trial Sequential Analysis and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Data sources: The Cochrane Library, MEDLINE, Embase, Science Citation Index and BIOSIS were searched for trials published from inception to 6 February 2025.

Eligibility criteria for selecting studies: Studies were eligible for inclusion if they were published and unpublished randomised clinical trials comparing tramadol vs placebo in adults with any type of chronic pain. Risk of bias was assessed according to the Cochrane Handbook for Systematic Reviews of Interventions.

Main outcome measures: The main outcome measures were pain level, adverse events, quality of life, dependence, abuse and depressive symptoms.

Results: We included 19 randomised placebo-controlled clinical trials enrolling 6506 participants. All outcome results were at high risk of bias. Meta-analysis and Trial Sequential Analysis showed evidence of a beneficial effect of tramadol on chronic pain (mean difference numerical rating scale (NRS) -0.93 points; 97.5% CI -1.26 to -0.60; p<0.0001; low certainty of evidence). However, the effect size was below our predefined minimal important difference of 1.0 point on NRS. Beta binomial regression showed evidence of a harmful effect of tramadol on serious adverse events (OR 2.13; 97.5% CI 1.29 to 3.51; p=0.001; moderate certainty of evidence), mainly driven by a higher proportion of cardiac events and neoplasms. It was not possible to conduct a meta-analysis of the quality of life due to a lack of data. Meta-analysis and Trial Sequential Analysis showed that tramadol increased the risk of several non-serious adverse events including nausea (number needed to harm (NNH) 7), dizziness (NNH 8), constipation (NNH 9), and somnolence (NNH 13) (all very low certainty of evidence).

Conclusion: Tramadol may have a slight effect on reducing chronic pain levels (low certainty of evidence) while likely increasing the risk of both serious (moderate certainty of evidence) and non-serious adverse events (very low certainty of evidence). The potential harms associated with tramadol use for pain management likely outweigh its limited benefits.