Evidence map›Paper›PMID 32459574›Full record

ReviewThe Libyan journal of medicine2020

The world is waiting, use sequential analysis and get us the evidence-based treatment we need for COVID-19.

Adel El Taguri, Aisha Nasef

Abstract readReview
In one paragraph

Review in The Libyan journal of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Article
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

2 authors.

Adel El TaguriNational Center for Accreditation of Health Establishments- , Tripoli-Libya, Libya.
Aisha NasefAuthority of Natural Science Research and Technology , Tripoli-Libya, Libya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In spite of the relatively high morbidity and mortality, there is no approved medication yet for COVID-19. There are more than 200 ongoing trials on different drugs or vaccines, but new medications may take until 2021 to develop. Defining the optimal number of patients to be included in a study is a considerable challenge in these interventional researches. Ethical considerations prompt researchers to minimize the number of patients included in a trial. This gains particular importance when the disease is rare or lethal which is particularly so in the case of COVID-19. It is of paramount importance to explore some of the available tools that could help accelerate the adoption of any or some of the many proposed modalities for the treatment of diseases. These tools should be effective, yet efficient, for rapid testing of such treatments. Sequential analysis has not been frequently used in many clinical trials where it should have been used. None of the authors in published literature, as far as we know, used sequential analysis techniques to test potential drugs for COVID-19. In addition to its usefulness when the results of new forms of treatment are quickly needed, other important benefit of sequential analysis includes the ability to reach a similar conclusion about the utility of a new drug without unduly exposing more patients to the side effect of the old drug, in particularly, for the treatment of a rare disease.

Indexed as

BetacoronavirusDrug DiscoveryAntiviral AgentsClinical Trials as TopicCoronavirus InfectionsCOVID-19Evidence-Based MedicineGlobal HealthHumansPandemicsPneumonia, ViralSARS-CoV-2Antiviral Agentsclinical trialsCOVID-19Sequential analysistreatment

Identifiers

PMID32459574
PMCPMC7646536

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.