Evidence map›Paper›PMID 34733709›Full record

ArticleQatar medical journal2021

COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers.

Sameer A Pathan, Jibin Moinudheen, Katie Simon, Stephen H Thomas

Abstract read
In one paragraph

Article in Qatar medical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Sameer A Pathan
Jibin MoinudheenCorporate Department of Emergency Medicine, Hamad Medical Corporation, Qatar E-mail: SPathan@hamad.qa.
Katie SimonCorporate Department of Emergency Medicine, Hamad Medical Corporation, Qatar E-mail: SPathan@hamad.qa.
Stephen H ThomasCorporate Department of Emergency Medicine, Hamad Medical Corporation, Qatar E-mail: SPathan@hamad.qa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this short communication, we summarized the analyses, models, and interpretations of the corporate department of emergency medicine's (CDEM) COVID-19 numbers and their relationship to predict the national COVID-19 trends and numbers in Qatar. Data included in this analysis were obtained between March 1, 2020 and July 31, 2021. It included the number of COVID-19 cases that presented to four major EDs under the Hamad Medical Corporation CDEM umbrella and published data from the Qatar Ministry of public health (MoPH). On plotting weighted scatterplot smoothing (lowess) trend lines, there were striking similarities between CDEM and national COVID-19

Indexed as

COVID-19emergency medicinenational trendsprediction

Identifiers

PMID34733709
PMCPMC8542101

What OpenQuestion holds

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Registered trials

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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.