The rationale behind systematic reviews in clinical medicine: a conceptual framework

Moosapour, Hamideh; Saeidifard, Farzane; Aalaa, Maryam; Soltani, Akbar; Larijani, Bagher

doi:10.1007/s40200-021-00773-8

Cited by 10 publications

(5 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) We developed the first generalisable approach to utilising selection criteria to enhance citation screening performance. (3) We performed the first comprehensive empirical study on well-known benchmark datasets and demonstrated the high potential of the proposed approach for citation screening.…”

Section: Introductionmentioning

confidence: 93%

See 1 more Smart Citation

A Novel Question-Answering Framework for Automated Abstract Screening Using Large Language Models

Akinseloyin,

Jiang,

Palade

2023

Preprint

View full text Add to dashboard Cite

ObjectiveThis paper aims to address the challenges in citation screening (a.k.a. abstract screening) within Systematic Reviews (SR) by leveraging the zero-shot capabilities of large language models, particularly ChatGPT.MethodsWe employ ChatGPT as a zero-shot ranker to prioritize candidate studies by aligning abstracts with the selection criteria outlined in an SR protocol. Citation screening was transformed into a novel question-answering (QA) framework, treating each selection criterion as a question addressed by ChatGPT. The framework involves breaking down the selection criteria into multiple questions, properly prompting ChatGPT to answer each question, scoring and re-ranking each answer, and combining the responses to make nuanced inclusion or exclusion decisions.ResultsLarge-scale validation was performed on the benchmark of CLEF eHealth 2019 Task 2: Technology Assisted Reviews in Empirical Medicine. Across 31 datasets of four categories of SRs, the proposed QA framework consistently outperformed other zero-shot ranking models. Compared with complex ranking approaches with iterative relevance feedback and fine-tuned deep learning-based ranking models, our ChatGPT-based zero-shot citation screening approaches still demonstrated competitive and sometimes better results, underscoring their high potential in facilitating automated systematic reviews.ConclusionInvestigation justified the indispensable value of leveraging selection criteria to improve the performance of automated citation screening. ChatGPT demonstrated proficiency in prioritizing candidate studies for citation screening using the proposed QA framework. Significant performance improvements were obtained by re-ranking answers using the semantic alignment between abstracts and selection criteria. This further highlighted the pertinence of utilizing selection criteria to enhance citation screening.

show abstract

Section: Introductionmentioning

confidence: 93%

“…Because of its thoroughness and reliability, SR underpins evidence-based medicine [2]. It shapes medical research and practice by informing researchers of the state-of-the-art knowledge and knowledge gaps as well as health practitioners and policymakers of the best clinical practice [3]. SR also faces tremendous challenges at each step.…”

Section: Introductionmentioning

confidence: 99%

A Novel Question-Answering Framework for Automated Abstract Screening Using Large Language Models

Akinseloyin,

Jiang,

Palade

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Se ha realizado una revisión sistemática, puesto que proporciona una estrategia de búsqueda con etapas complejas, a la vez que brinda transparencia en la recopilación de datos (Rethlefsen et al, 2021). Su carácter cualitativo permite sintetizar y contrastar conceptos, elaborando nuevas teorías o generando nuevas ideas (Moosapour et al, 2021). Para estructurar de forma idónea el proceso de selección, se hace uso de los lineamientos de PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis), el cual se caracteriza por proveer precisión y calidad a los procesos de selección, de manera que prevalezca la claridad investigativa en cada etapa del proceso (Page et al, 2021).…”

Section: Metodologíaunclassified

Métodos De Intervención Ambiental Universitaria Para Contrarrestar Los Efectos Del Cambio Climático

Terán,

Arnao,

Arnao

et al. 2024

View full text Add to dashboard Cite

This study has addressed the issue of climate change, which has now spread to the university environment. To this end, a systematic review has been carried out to try to answer the following research question: what are the environmental intervention methods implemented in higher education that counteract the effects of climate change? PRISMA methodology criteria were applied in order to structure the selection and discarding of articles. In this way, 15 articles were obtained that provide a significant contribution about the strategies and knowledge that teachers should have, as well as the students' perspectives on the affective and emotional level and on activities that are beneficial for climate change. Finally, the most prominent methods with significant impact are debates, reflection spaces and feedback workshops, as well as changes in the curriculum to create courses that encourage active student participation, and changes in students' lifestyles to reduce the level of pollution and overexploitation of natural resources.

show abstract

“…Systematic reviews are considered high‐level overviews of available evidence on any given healthcare topic. They are utilised as critical pieces for clinical decision‐making in modern healthcare practice [47]. Due to increasing primary evidence assessing outcomes following various autograft options in ACLR, there have been an abundance of systematic reviews comparing them against one another.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the quality of systematic reviews of comparative studies in autograft‐based anterior cruciate ligament reconstruction using the AMSTAR‐2 tool: A systematic umbrella review

Sritharan,

Milantoni,

Abdel Khalik

et al. 2024

Knee surg. sports traumatol. arthrosc.

View full text Add to dashboard Cite

PurposeThere remains a lack of consensus around autograft selection in anterior cruciate ligament reconstruction (ACLR), though there is a large body of overlapping systematic reviews and meta‐analyses. Systematic reviews and their methodological quality were aimed to be further assessed, using a validated tool known as assessing the methodological quality of systematic reviews (AMSTAR‐2).MethodsMEDLINE, Embase and CENTRAL were searched from inception to 23 April 2023 for systematic reviews (with/without meta‐analysis) comparing primary ACLR autografts. A final quality rating from AMSTAR‐2 was provided for each study (‘critically low’, ‘low’, ‘moderate’ or ‘high’ quality). Correlational analyses were conducted for ratings in relation to study characteristics.ResultsTwo thousand five hundred and ninety‐eight studies were screened, and 50 studies were ultimately included. Twenty‐four studies (48%) were rated as ‘critically low’, 17 (34%) as ‘low’, seven (14%) as ‘moderate’ and two (4%) as ‘high’ quality. The least followed domains were reporting on sources of funding (1/50 studies), the impact of risk of bias on results of meta‐analyses (11/36 studies) and publication bias (17/36 studies). There was a significant increase in the frequency of studies graded as ‘moderate’ compared to ‘low’ or ‘critically low’ quality over time (p = 0.020).ConclusionThe methodological quality of systematic reviews comparing autografts in ACLR is low, with many studies being rated lower due to commonly absent aspects of systematic review methodology such as investigating sources of funding and publication bias. More recent studies were generally more likely to be of higher quality. Authors are advised to consult AMSTAR‐2 prior to conducting systematic reviews in ACLR.Level of Evidence: Level IV.

show abstract

The rationale behind systematic reviews in clinical medicine: a conceptual framework

Cited by 10 publications

References 40 publications

A Novel Question-Answering Framework for Automated Abstract Screening Using Large Language Models

A Novel Question-Answering Framework for Automated Abstract Screening Using Large Language Models

Métodos De Intervención Ambiental Universitaria Para Contrarrestar Los Efectos Del Cambio Climático

Evaluating the quality of systematic reviews of comparative studies in autograft‐based anterior cruciate ligament reconstruction using the AMSTAR‐2 tool: A systematic umbrella review

Contact Info

Product

Resources

About