A systematic review that is ``rapid'' and ``living'': A specific answer to the COVID-19 pandemic

Négrini, Stefano; Ceravolo, Maria Gabriella; Côté, Pierre; Arienti, Chiara

doi:10.1016/j.jclinepi.2021.05.025

Cited by 20 publications

(20 citation statements)

References 23 publications

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“…Despite the relatively quick turnaround in conduct and subsequent publication of COVID-19 SRs, the question of the utility of these reviews remains, especially for reviews assessing the effects of potential treatments for COVID-19 [17]. The popularity of preprints [18,19] and the proliferation of living reviews [20] have been notable features of the pandemic, and are an attempt to speed up the transfer of information. But even these approaches (in the case of living and rapid reviews) can still seem sluggish.…”

Section: Discussionmentioning

confidence: 99%

Are COVID-19 systematic reviews up to date and can we tell? A cross-sectional study

McDonald

Turner

Nguyen

et al. 2022

Preprint

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BackgroundCOVID-19 led to a rapid acceleration in the number of systematic reviews. Readers need to know how up to date evidence is when selecting reviews to inform decisions. This cross-sectional study aimed to evaluate how easily the currency of COVID-19 systematic reviews published early in the pandemic could be determined and how up to date these reviews were at the time of publication.MethodsWe searched for systematic reviews and meta-analyses relevant to COVID-19 added to PubMed in July 2020 and January 2021, including any that were first published as preprints. We extracted data on the date of search, number of included studies, and date first published online. For the search date, we noted the format of the date and where in the review this was reported. A sample of non-COVID-19 systematic reviews from November 2020 served as a comparator.ResultsWe identified 246 systematic reviews on COVID-19. In the abstract of these reviews, around half (48%) reported the complete search date (day/month/year) and 43% failed to report any date. In the full text, the complete date and no date were reported in 82% and 6% of reviews, respectively. The median time from last search to publication online was 91 days (IQR 63–130). Time from search to publication was similar for the subset of 15 rapid or living reviews (92 days) but shorter for the 29 reviews published as preprints (37 days). The median number of studies or publications included per review was 23 (IQR 12–40). In the sample of 290 non-COVID SRs, around a quarter (27%) reported the complete search date and a third (34%) did not include any date in the abstract. The median time from search to publication online was 253 days (IQR 153–381) and each review included a median of 12 studies (IQR 8–21).ConclusionsDespite the context of the pandemic and the need to easily ascertain the currency of systematic reviews, reporting of the search date information for COVID-19 reviews was suboptimal. Reviews were conducted and published more quickly than non-COVID reviews but potentially at the expense of adequate reporting.

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Section: Discussionmentioning

confidence: 99%

Are COVID-19 systematic reviews up to date and can we tell? A cross-sectional study

McDonald

Turner

Nguyen

et al. 2022

Preprint

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Section: Introductionmentioning

confidence: 99%

“…7,12 However, some studies showed that LSRs might face unexpected challenges and difficulties under the COVID-19 pandemic with a changeable epidemiological landscape and substantial clinical uncertainty. 13,14 Therefore, this systematic review analyzes and summarizes the characteristics of LSRs for COVID-19, which aims to identify potential problems and provide references to further improve the quality of LSRs for COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Living Systematic Review for COVID-19

Chen¹,

Luo²,

Li³

et al. 2022

CLEP

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Purpose The systematic review aims to analyze and summarize the characteristics of living systematic review (LSR) for coronavirus disease 2019 (COVID-19). Methods Six databases including Medline, Excerpta Medica (Embase), Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science, and Technology Journal Database (VIP), were searched as the source of basic information and methodology of LSR. Descriptive analytical methods were used to analyze the included COVID-19 LSRs, and the study characteristics of COVID-19 LSRs were further assessed. Results Sixty-four COVID-19 LSRs were included. Eighty-nine point one percent of LSRs were published on Science Citation Index (SCI) journals, and 64.1% publication with an impact factor (IF) >5 and 17.2% with an IF >15 among SCI journals. The first unit of the published LSRs for COVID-19 came from 19 countries, with the largest contribution from the UK (17.2%, 11/64). Forty point six percent of LSRs for COVID-19 were related to therapeutics topic which was considered the most concerned perspective for LSRs for COVID-19. Seventy-six point six percent of LSRs focused on the general population, with less attention to children, pregnant women and the elderly. However, the LSR for COVID-19 was reported incomplete on “living” process, including 40.6% of studies without search frequency, 79.7% of studies without screening frequency, 20.3% of studies without update frequency, and 65.6% of studies without the timing or criteria of transitioning LSR out of living mode. Conclusion Although researchers in many countries have applied LSRs to COVID-19, most of the LSRs for COVID-19 were incomplete in reporting on the “living” process and less focused on special populations. This could reduce the confidence of health-care providers and policy makers in the results of COVID-19 LSR, thereby hindering the translation of evidence on COVID-19 LSR into clinical practice. It was necessary to explicitly enact preferred reporting items for systematic reviews and meta-analyses (PRISMA) to improve the reporting quality of LSR and support ongoing efforts of therapeutics research for special patients with COVID-19.

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“…Finally, technology itself can dramatically accelerate review processes, from online platforms that manage review processes to the use of artificial intelligence and machine learning to replace time-consuming manual tasks with increasing precision 22,23. These technology developments have led to the advent of “living” reviews and CPGs, which harness distributed human resources and machine effort to create reviews and update them continuously 10,24,25. Living INCOG guidelines would facilitate a process to update recommendations as soon as relevant new information becomes available.…”

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confidence: 99%