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Abstract The clinical development of novel vaccines, injectable therapeutics, and oral chemoprevention drugs has the potential to deliver significant advancements in the prevention of Plasmodium falciparum malaria. These innovations could support regions in accelerating malaria control, transforming existing intervention packages by supplementing interventions with imperfect effectiveness or offering an entirely new tool. However, to layer new medical tools as part of an existing programme, malaria researchers must come to an agreement on the gaps that currently limit the effectiveness of medical interventions for moderate to low transmission settings. In this perspective, three crucial gaps that may prevent new therapeutics from being used to their fullest extent are presented. First, do burden reduction outcomes, which are typically monitored in studies of new medical products, sufficiently capture the broader goal of accelerating malaria control? Layering novel malaria products requires monitoring health outcomes that reflect the novel product’s targeted stage of the parasite life cycle, in addition to all-infection and prevalence-based outcomes. Second, what public health outcome does a novel medical prevention tool provide that existing malaria interventions cannot fully deliver? Novel medical tools should be developed not just for an incremental improvement in preventive efficacy over an existing product, but also to meet a gap in protection. Specifically, this means designing products with components that target parts of the parasite life cycle beyond the scope of existing therapeutics, and better addressing populations and settings not well covered by existing tools. Finally, when do the population-level benefits of a multi-tool prevention programme justify the individual-level outcomes from receiving multiple interventions? An individual-level perspective should be key for exploring when and how layering a novel prevention intervention can accelerate efforts towards P. falciparum malaria control.

Summary: Background: Suboptimal diet quality is a key risk factor for premature death. Assuming relatively stable energy intake among individuals, changes in nutrient intakes occur by exchanging different nutrients. Therefore we aimed to examine the association of isocaloric substitution of dietary (macro)nutrients with all-cause mortality using network meta-analysis (NMA). Methods: For this systematic review and NMA of prospective observational studies MEDLINE, Embase, and Scopus were searched from inception to February 13th, 2024. Eligible studies reported substitution analyses for quantity and/or quality of macronutrients, including carbohydrates, proteins, and fatty acids on all-cause mortality. Random-effects NMA were used in order to evaluate the pooled hazard ratios (HR) and 95% confidence intervals (CI) of substituting each included nutrient with another. We assessed risk of bias with the ROBINS-E tool, and the certainty of evidence (CoE) using the Grading of Recommendations Assessment, Development and Evaluations (GRADE) approach. This study is registered with PROSPERO (CRD42023450706). Findings: Thirty-nine studies with 1,737,644 participants, 395,491 deaths, 297 direct comparisons, and seven nutrient-specific networks were included. Moderate CoE was found for an association with lower mortality risk when replacing 5% of energy intake from carbohydrates with polyunsaturated fatty acids (PUFA; HR: 0.90; 95%CI: 0.84, 0.95), n-6 PUFA (0.85; 0.77, 0.94), n-3 PUFA (0.72; 0.59, 0.86), and plant monounsaturated fatty acids (MUFA; 0.90; 0.85, 0.95), and when replacing 5% of energy from saturated fatty acids (SFA) and trans-fatty acids (TFA), with PUFA, MUFA, and plant-MUFA (HRrange: 0.75 to 0.91). A lower mortality risk was additionally found when 5% of animal-MUFA was replaced with plant-MUFA, and when replacing animal protein, and SFA with plant protein (HRrange: 0.81 to 0.87, moderate CoE). Interpretation: Our results provide practical knowledge for public health professionals and can inform upcoming dietary guidelines. The beneficial association of increasing PUFA (both n-3 and n-6) and (plant-) MUFA intake while reducing carbohydrates, SFA and TFA, along with replacing animal protein and animal-MUFA with plant-based sources of protein and fat (MUFA) on the all-cause mortality risk, underscores the importance of plant-based dietary recommendations. Funding: None.

Introduction Large language model (LLM)-linked chatbots are being increasingly applied in healthcare due to their impressive functionality and public availability. Studies have assessed the ability of LLM-linked chatbots to provide accurate clinical advice. However, the methods applied in these Chatbot Assessment Studies are inconsistent due to the lack of reporting standards available, which obscures the interpretation of their study findings. This protocol outlines the development of the Chatbot Assessment Reporting Tool (CHART) reporting guideline.Methods and analysis The development of the CHART reporting guideline will consist of three phases, led by the Steering Committee. During phase one, the team will identify relevant reporting guidelines with artificial intelligence extensions that are published or in development by searching preprint servers, protocol databases, and the Enhancing the Quality and Transparency of health research Network. During phase two, we will conduct a scoping review to identify studies that have addressed the performance of LLM-linked chatbots in summarising evidence and providing clinical advice. The Steering Committee will identify methodology used in previous Chatbot Assessment Studies. Finally, the study team will use checklist items from prior reporting guidelines and findings from the scoping review to develop a draft reporting checklist. We will then perform a Delphi consensus and host two synchronous consensus meetings with an international, multidisciplinary group of stakeholders to refine reporting checklist items and develop a flow diagram.Ethics and dissemination We will publish the final CHART reporting guideline in peer-reviewed journals and will present findings at peer-reviewed meetings. Ethical approval was submitted to the Hamilton Integrated Research Ethics Board and deemed “not required” in accordance with the Tri-Council Policy Statement (TCPS2) for the development of the CHART reporting guideline (#17025).Registration This study protocol is preregistered with Open Science Framework: https://doi.org/10.17605/OSF.IO/59E2Q.

Public health and social measures (PHSM) have been central to the COVID-19 response. Consequently, there has been much pressure on decision-makers to make evidence-informed decisions and on researchers to synthesize the evidence regarding these measures. This article describes our experiences, responses and lessons learnt regarding key challenges when planning and conducting rapid reviews of PHSM during the COVID-19 pandemic. Stakeholder consultations and scoping reviews to obtain an overview of the evidence inform the scope of reviews that are policy-relevant and feasible. Multiple complementary reviews serve to examine the benefits and harms of PHSM across different populations and contexts. Conceiving reviews of effectiveness as adaptable living reviews helps to respond to evolving evidence needs and an expanding evidence base. An appropriately skilled review team and good planning, coordination and communication ensures smooth and rigorous processes and efficient use of resources. Scientific rigor, the practical implications of PHSM-related complexity and likely time savings should be carefully weighed in deciding on methodological shortcuts. Making the best possible use of modeling studies represents a particular challenge, and methods should be carefully chosen, piloted and implemented. Our experience raises questions regarding the nature of rapid reviews and regarding how different types of evidence should be considered in making decisions about PHSM during a global pandemic. We highlight the need for readily available protocols for conducting studies on the effectiveness, unintended consequences and implementation of PHSM in a timely manner, as well as the need for rapid review standards tailored to "rapid" versus "emergency" mode reviewing.

Abstract Background The prevalence of multi-morbidity is increasing globally. Integrated models of care present a potential intervention to improve patient and health system outcomes. However, the intervention components and concepts within different models of care vary widely and their effectiveness remains unclear. We aimed to describe and map the definitions, characteristics, components, and reported effects of integrated models of care in systematic reviews (SRs). Methods We conducted a scoping review of SRs according to pre-specified methods (PROSPERO 2019 CRD42019119265). Eligible SRs assessed integrated models of care at primary health care level for adults and children with multi-morbidity. We searched in PubMed (MEDLINE), Embase, Cochrane Database of Systematic Reviews, Epistemonikos, and Health Systems Evidence up to 3 May 2022. Two authors independently assessed eligibility of SRs and extracted data. We identified and described common components of integrated care across SRs. We extracted findings of the SRs as presented in the conclusions and reported on these verbatim. Results We included 22 SRs, examining data from randomised controlled trials and observational studies conducted across the world. Definitions and descriptions of models of integrated care varied considerably. However, across SRs, we identified and described six common components of integrated care: (1) chronic conditions addressed, (2) where services were provided, (3) the type of services provided, (4) healthcare professionals involved in care, (5) coordination and organisation of care and (6) patient involvement in care. We observed differences in the components of integrated care according to the income setting of the included studies. Some SRs reported that integrated care was beneficial for health and process outcomes, while others found no difference in effect when comparing integrated care to other models of care. Conclusions Integrated models of care were heterogeneous within and across SRs. Information that allows the identification of effective components of integrated care was lacking. Detailed, standardised and transparent reporting of the intervention components and their effectiveness on health and process outcomes is needed.

BackgroundSickle cell disease (SCD) is a life-limiting inherited hemoglobinopathy that results in significant complications and affects quality of life. Hematopoietic stem cell transplantation (HSCT) is currently the only curative intervention for SCD; however, guidelines are needed to inform how to apply HSCT in clinical practice.ObjectiveThese evidence-based guidelines of the American Society of Hematology (ASH) are intended to support patients, clinicians, and health professionals in their decisions about HSCT for SCD.MethodsThe multidisciplinary guideline panel formed by ASH included 2 patient representatives and was balanced to minimize potential bias from conflicts of interest. The Mayo Evidence-Based Practice Research Program supported the guideline development process, including performing systematic evidence reviews (through 2019). The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients. The panel used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, including GRADE Evidence-to-Decision frameworks, to assess evidence and make recommendations, which were subject to public comment.ResultsThe panel agreed on 8 recommendations to help patients and providers assess how individuals with SCD should consider the timing and type of HSCT.ConclusionsThe evidence review yielded no randomized controlled clinical trials for HSCT in SCD; therefore, all recommendations are based on very low certainty in the evidence. Key recommendations include considering HSCT for those with neurologic injury or recurrent acute chest syndrome at an early age and to improve nonmyeloablative regimens. Future research should include the development of a robust SCD registry to serve as a comparator for HSCT studies.

A considerable proportion of quantitative research remains unpublished once completed. Little research has documented non-dissemination and dissemination bias in qualitative research. This study aimed to generate evidence on the extent of non-dissemination in qualitative research. We followed a cohort of qualitative studies presented as conference abstracts to ascertain their subsequent publication status. We searched for subsequent full publication in MEDLINE, in the Cumulative Index to Nursing & Allied Health Literature and in Google Scholar. We matched abstracts to subsequent publications according to authors, method of data collection and phenomenon of interest. Fisher's exact test was calculated to examine associations between study characteristics and publication. Factors potentially associated with time to publication were evaluated with Cox regression analysis. For 91 of 270 included abstracts (33.70%; 95% CI 28.09%-39.68%), no full publication was identified. Factors that were found to be associated with subsequent full publication were oral presentation (OR 4.62; 95% CI 2.43-8.94) and university affiliation (OR 1.96; 95% CI 1.05-3.66). Compared to oral presentations, studies presented as posters took longer time to reach full publication (hazard ratio 0.35, 95% CI 0.21-0.58). This study shows that it was not possible to retrieve a full publication for over one-third of abstracts. Our findings suggest that where this non-dissemination is systematic, it may lead to distortions of the qualitative evidence-base for decision-making through dissemination bias. Our findings are congruent with those of other studies. Further research might investigate non-dissemination of qualitative studies in other disciplines to consolidate our findings.

Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July 2019. We included systematic reviews reporting a statistically significant meta-analysis of at least four randomized controlled trials in advanced cancer patients using either a fixed-effect or random-effects model. We investigated the impact of switching from fixed-effect to random-effects meta-analysis and of using the recommended Hartung-Knapp method in random-effects meta-analyses. Furthermore, we calculated 95% PIs for all included meta-analyses. We identified 6234 hits, of which 261 statistically significant meta-analyses were included. Our recalculations of these 261 meta-analyses produced statistically significant results in 132 of 138 fixed-effect and 114 of 123 random-effects meta-analyses. When switching to a random-effects model, 19 of 132 fixed-effect meta-analyses (14.4%) were no longer statistically significant. Using the Hartung-Knapp method in random-effects meta-analyses resulted in 34 of 114 nonsignificant meta-analyses (29.8%). In the full sample (N = 261), the "null effect" was included by the 95% PI in 195 (74.7%) and the "opposite effect" (e.g., hazard ratio 0.5, opposite effect 2) in 98 meta-analyses (37.5%). Using the Hartung-Knapp method and PIs substantially influenced the interpretation of many published, statistically significant meta-analyses. We strongly encourage researchers to check if using the Hartung-Knapp method and reporting 95% PIs is appropriate in random-effects meta-analyses.

OBJECTIVE: Back pain is common in the working population. This systematic review with network meta-analysis (NMA) aimed to compare the effects of interventions for preventing back pain among office workers. METHODS: We searched eight databases and additional sources up to March 2021. We included randomized controlled trials (RCT) and cluster RCT focusing on office workers, comparing work-related interventions aimed at preventing back pain (defined as pain in any part of the spine) to a control condition and assessing back pain and/or work absence. Further outcomes considered were adverse events and participants’ satisfaction. We performed both frequentist and component NMA. Risk of bias (RoB) was evaluated using RoB 2 and certainty of the evidence (CoE) was assessed using GRADE. RESULTS: We screened 9809 records and included 24 studies with a total of 7080 participants. RoB was assessed as “some concerns” or “high” for all studies and outcomes. Included studies investigated multicomponent interventions, ergonomics, physical activity, education, behavioral interventions and no/minimal interventions. Effects were mostly not statistically significant and based on low/very low CoE. Physical activity probably reduces days of work absence slightly [mean difference (MD) -1.10, 95% confidence interval (CI) -2.07– -0.13], and combining physical activity and ergonomics may reduce back pain intensity (standardized MD -0.41, 95% CI -0.80– -0.02) when compared to no/minimal intervention. A large proportion of participants were satisfied with the interventions, adverse events were rarely assessed. CONCLUSIONS: We observed mostly minor effects of interventions on back pain and work absence among office workers. The practical relevance of these effects is questionable.

BackgroundDonors other than matched siblings and low-intensity conditioning regimens are increasingly used in haematopoietic stem cell transplantation. We aimed to compare the relative risk of donor type and conditioning regimen intensity on the transplantation outcomes of in patients with sickle cell disease.MethodsFor this retrospective cohort study, we collected data from 90 US centres reported to the Center for International Blood and Marrow Transplant Research. Eligible patients were younger than 50 years, had genetically confirmed sickle cell disease (Hb SS) or sickle beta thalassemia (Hb Sβ), and underwent allogeneic haematopoietic cell transplantation between Jan 15, 2008, and Dec 28, 2017. We considered transplants from donor-recipient pairs matched at the allele-level (HLA-A, HLA-B, HLA-C, and HLA-DRB1), including HLA-matched sibling donors, haploidentical related donors, matched unrelated donors, or mismatched unrelated donors. The main outcome was event-free survival. The effect of donor type, conditioning regimen intensity (myeloablative, non-myeloablative, and reduced-intensity regimens), age (≤12 or 13-49 years), sex, performance score, comorbidity index, recipient cytomegalovirus serostatus, graft type (bone marrow, peripheral blood, or umbilical cord blood), and transplantation period (2008-12 and 2013-17) on outcomes was studied using Cox regression models.FindingsOf 996 patients with sickle cell disease and who underwent transplantation in 2008-17, 910 (91%) were included (558 [61%] patients had HLA-matched sibling donors, 137 [15%] haploidentical related donors, 111 [12%] matched unrelated donors, and 104 [11%] mismatched unrelated donors). The median follow-up was 36 months (IQR 18-60) after transplantation from HLA-matched siblings, 25 months (12-48) after transplantation from haploidentical related donors, 37 months (23-60) after transplantation from HLA-matched unrelated donors, and 47 months (24-72) after transplantation from mismatched unrelated donors. Event-free survival was worse in recipients aged 13 years or older than in those younger than 13 years (hazard ratio 1·74, 95% CI 1·24-2·45; p=0·0014) and in those who received a transplant from haploidentical related donors (5·30, 3·17-8·86; p

BackgroundClinical practice guidelines are systematically developed statements intended to optimize patient care. However, a gapless implementation of guideline recommendations requires health care personnel not only to be aware of the recommendations and to support their content but also to recognize every situation in which they are applicable. To not miss situations in which recommendations should be applied, computerized clinical decision support can be provided through a system that allows an automated monitoring of adherence to clinical guideline recommendations in individual patients. ObjectiveThis study aims to collect and analyze the requirements for a system that allows the monitoring of adherence to evidence-based clinical guideline recommendations in individual patients and, based on these requirements, to design and implement a software prototype that integrates guideline recommendations with individual patient data, and to demonstrate the prototype’s utility in treatment recommendations. MethodsWe performed a work process analysis with experienced intensive care clinicians to develop a conceptual model of how to support guideline adherence monitoring in clinical routine and identified which steps in the model could be supported electronically. We then identified the core requirements of a software system to support recommendation adherence monitoring in a consensus-based requirements analysis within the loosely structured focus group work of key stakeholders (clinicians, guideline developers, health data engineers, and software developers). On the basis of these requirements, we designed and implemented a modular system architecture. To demonstrate its utility, we applied the prototype to monitor adherence to a COVID-19 treatment recommendation using clinical data from a large European university hospital. ResultsWe designed a system that integrates guideline recommendations with real-time clinical data to evaluate individual guideline recommendation adherence and developed a functional prototype. The needs analysis with clinical staff resulted in a flowchart describing the work process of how adherence to recommendations should be monitored. Four core requirements were identified: the ability to decide whether a recommendation is applicable and implemented for a specific patient, the ability to integrate clinical data from different data formats and data structures, the ability to display raw patient data, and the use of a Fast Healthcare Interoperability Resources–based format for the representation of clinical practice guidelines to provide an interoperable, standards-based guideline recommendation exchange format. ConclusionsOur system has advantages in terms of individual patient treatment and quality management in hospitals. However, further studies are needed to measure its impact on patient outcomes and evaluate its resource effectiveness in different clinical settings. We specified a modular software architecture that allows experts from different fields to work independently and focus on their area of expertise. We have released the source code of our system under an open-source license and invite for collaborative further development of the system.

Abstract Background Randomized controlled trials (RCTs) and cohort studies are the most common study design types used to assess the treatment effects of medical interventions. To evaluate the agreement of effect estimates between bodies of evidence (BoE) from randomized controlled trials (RCTs) and cohort studies and to identify factors associated with disagreement. Methods Systematic reviews were published in the 13 medical journals with the highest impact factor identified through a MEDLINE search. BoE-pairs from RCTs and cohort studies with the same medical research question were included. We rated the similarity of PI/ECO (Population, Intervention/Exposure, Comparison, Outcome) between BoE from RCTs and cohort studies. The agreement of effect estimates across BoE was analyzed by pooling ratio of ratios (RoR) for binary outcomes and difference of mean differences for continuous outcomes. We performed subgroup analyses to explore factors associated with disagreements. Results One hundred twenty-nine BoE pairs from 64 systematic reviews were included. PI/ECO-similarity degree was moderate: two BoE pairs were rated as “more or less identical”; 90 were rated as “similar but not identical” and 37 as only “broadly similar”. For binary outcomes, the pooled RoR was 1.04 (95% CI 0.97–1.11) with considerable statistical heterogeneity. For continuous outcomes, differences were small. In subgroup analyses, degree of PI/ECO-similarity, type of intervention, and type of outcome, the pooled RoR indicated that on average, differences between both BoE were small. Subgroup analysis by degree of PI/ECO-similarity revealed high statistical heterogeneity and wide prediction intervals across PI/ECO-dissimilar BoE pairs. Conclusions On average, the pooled effect estimates between RCTs and cohort studies did not differ. Statistical heterogeneity and wide prediction intervals were mainly driven by PI/ECO-dissimilarities (i.e., clinical heterogeneity) and cohort studies. The potential influence of risk of bias and certainty of the evidence on differences of effect estimates between RCTs and cohort studies needs to be explored in upcoming meta-epidemiological studies.