Evidence map›Paper›PMID 33425943›Full record

ArticleFrontiers in medicine2020

Some Questions to Our Chinese Colleagues Pioneering Research Into Coronavirus Disease 2019 (COVID-19).

Claudia Stöllberger, Maria Winkler-Dworak

Abstract read
In one paragraph

Article in Frontiers in medicine, 2020. 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

2 authors.

Claudia StöllbergerMedizinische Abteilung, Klinik Landstrasse, Vienna, Austria.
Maria Winkler-DworakWittgenstein Centre for Demography and Global Human Capital, Vienna Institute of Demography of the Austrian Academy of Sciences, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A pandemic has developed, so physicians worldwide are particularly interested in the experiences of their Chinese Colleagues which are frequently cited. To assess the long-term pulmonary, cardiac, neurologic, and psychiatric consequences after COVID-19, the outcome of patients included in the early publications and the association with baseline findings is of particular interest. Thus, we review the methods of early Coronavirus disease 2019 (COVID-19) publications. Reports published before March 19th 2020, comprising >40 patients were included, considering especially cardiologic aspects. It remains unclear whether patients were described several times, or they were different patients. Only patients with confirmed COVID-19 were described, and no differences in findings of patients with initially suspected and later confirmed, or excluded infection. It remains unclear in how many cases information was missing, since missing values were not reported. Medication before hospital admission, level of education and occupation, household size and composition, weight or body mass index are lacking. No details about electrocardiographic findings are given. Patients still in follow-up, constituting the major part of observations, were excluded. The data should be re-analyzed. A comparison between confirmed and excluded cases could be carried out. By now, in November 2020, the reported patients will most probably have recovered. Thus, it would be possible to differentiate prognostic indicators more precisely. Laboratory tests and electrocardiograms could be analyzed in more detail to shed light on the spectrum of this disease and to solve some of the unanswered questions related with COVID-19.

Indexed as

cardiologyelectrocardiograminfectionmortalitystatistics

Identifiers

PMID33425943
PMCPMC7793802

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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.