Evidence map›Paper›PMID 38205173›Full record

ArticleInfectious medicine2023

SUPER Score Contributes to Warning and Management in Early-Stage COVID-19.

Yuan Bian, Qi Han, Yue Zheng, Yu Yao, Xinhui Fan, Ruijuan Lv, Jiaojiao Pang, Feng Xu, Yuguo Chen

Open access · goldAbstract read
In one paragraph

Article in Infectious medicine, 2023. 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
0.2field-weighted citation impact, top 40% of its field
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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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

9 authors at 2 institutions in 1 country.

Yuan BianDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Qi HanDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Yue ZhengDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Yu YaoDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Xinhui FanDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Ruijuan LvDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Jiaojiao PangDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Feng XuDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Yuguo ChenDepartment of Emergency Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.
Qilu Hospital of Shandong University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Some COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases. Methods: We consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2). Results: The SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897-1.000), sensitivity of 1.00 (95% CI 0.715-1.000), and specificity of 0.92 (95% CI 0.775-0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895-1.000, sensitivity 0.91; 95% CI 0.587-0.998, specificity 0.97; 95% CI 0.858-0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels. Conclusions: In conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.

Indexed as

COVID-19Early warningNEWS2SUPER score

Identifiers

PMID38205173
PMCPMC10774654
OpenAlexW4387766173

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.