Evidence map›Paper›PMID 34555033›Full record

ArticlePloS one2021

Evaluation of reporting quality of randomized controlled trials in patients with COVID-19 using the CONSORT statement.

Yuhuan Yin, Fugui Shi, Yiyin Zhang, Xiaoli Zhang, Jianying Ye, Juxia Zhang

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuhuan YinSchool of Nursing, Gansu University of Chinese Medicine, Lanzhou, China.
Fugui ShiLanzhou Hand and Foot Surgery Hospital, Lanzhou, Gansu, China.
Yiyin ZhangSchool of Nursing, Gansu University of Chinese Medicine, Lanzhou, China.
Xiaoli ZhangSchool of Nursing, Gansu University of Chinese Medicine, Lanzhou, China.
Jianying YeSchool of Nursing, Gansu University of Chinese Medicine, Lanzhou, China.
Juxia ZhangClinical Educational Department, Gansu Provincial Hospital, Lanzhou, Gansu, China.ORCID 0000-0002-3993-7920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the reporting quality of randomized controlled trials (RCTs) regarding patients with COVID-19 and analyse the influence factors.

methodsPubMed, Embase, Web of Science and the Cochrane Library databases were searched to collect RCTs regarding patients with COVID-19. The retrieval time was from the inception to December 1, 2020. The CONSORT 2010 statement was used to evaluate the overall reporting quality of these RCTs.

results53 RCTs were included. The study showed that the average reporting rate for 37 items in CONSORT checklist was 53.85% with mean overall adherence score of 13.02±3.546 (ranged: 7 to 22). The multivariate linear regression analysis showed the overall adherence score to the CONSORT guideline was associated with journal impact factor (P = 0.006), and endorsement of CONSORT statement (P = 0.014).

conclusionAlthough many RCTs of COVID-19 have been published in different journals, the overall reporting quality of these articles was suboptimal, it can not provide valid evidence for clinical decision-making and systematic reviews. Therefore, more journals should endorse the CONSORT statement, authors should strictly follow the relevant provisions of the CONSORT guideline when reporting articles. Future RCTs should particularly focus on improvement of detailed reporting in allocation concealment, blinding and estimation of sample size.

Indexed as

COVID-19Data ManagementGuideline AdherenceHumansJournal Impact FactorPublicationsPublishingPubMedRandomized Controlled Trials as TopicSARS-CoV-2

Identifiers

PMID34555033
PMCPMC8460279

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.