Evidence map›Paper›PMID 36504959›Full record

Observational studyFrontiers in public health2022

Comparison of clinical characteristics between COVID-19 and H7N9 fatal cases: An observational study.

Hui Jiang, Fangchao Liu, Ta-Chien Chan, Jinfeng Yin, Ruowen Huang, Li Shen, Shengjin Tu, Liang Kang, Wen Liu, Na Zhao and 5 more

Open access · goldAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Frontiers in public health, 2022. 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, top 83% 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, 0 citations in OpenAlex.

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

15 authors at 9 institutions in 2 countries.

Hui JiangBeijing Chest Hospital, Capital Medical University, Beijing, China.
Fangchao LiuBeijing Chest Hospital, Capital Medical University, Beijing, China.
Ta-Chien ChanResearch Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.
Jinfeng YinBeijing Chest Hospital, Capital Medical University, Beijing, China.
Ruowen HuangBeijing Normal University School of Mathematical Sciences, Beijing, China.
Li ShenWuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shengjin TuWuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Liang KangWuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wen LiuWuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Na ZhaoSchool of Ecology and Environment, Anhui Normal University, Wuhu, China.
Di ZhangBeijing Chest Hospital, Capital Medical University, Beijing, China.
Wangli XuCenter for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China.
Weimin LiBeijing Chest Hospital, Capital Medical University, Beijing, China.
Shelan LiuDepartment of Infectious Diseases, Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Chaolin HuangWuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Capital Medical University · CNJinyintan Hospital · CNBeijing Chest Hospital · CNHuazhong University of Science and Technology · CNAnhui Normal University · CNBeijing Normal University · CNRenmin University of China · CNResearch Center for Humanities and Social Sciences, Academia Sinica · TWZhejiang Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The outbreak of COVID-19 in 2020 is reminiscent of the H7N9 outbreak in 2013, which poses a huge threat to human health. We aim to compare clinical features and survival factors in fatal cases of COVID-19 and H7N9. Methods: Data on confirmed COVID-19 and H7N9 fatal cases identified in mainland China were analyzed to compare demographic characteristics and clinical severity. Survival curves were estimated by the Kaplan-Meier method and compared using log-rank tests and a restricted mean survival time model. A Cox regression model was used to identify survival factors in fatal cases of COVID-19 and H7N9. Results: Similar demographic characteristics were observed in fatal cases of COVID-19 and H7N9. The proportion of fatal cases of H7N9 receiving antibiotics, antiviral drugs, and oxygen treatment was higher than that of COVID-19. The potential protective factors for fatal COVID-19 cases were receiving antibiotics (HR: 0.37, 95% CI: 0.22-0.61), oxygen treatment (HR: 0.66, 95% CI: 0.44-0.99), and corticosteroids (HR: 0.46, 95% CI: 0.35-0.62). In contrast, antiviral drugs (HR: 0.21, 95% CI: 0.08-0.56) and corticosteroids (HR: 0.45, 95% CI: 0.29-0.69) were the protective factors for H7N9 fatal cases. Conclusion: The proportion of males, those having one or more underlying medical condition, and older age was high in COVID-19 and H7N9 fatal cases. Offering antibiotics, oxygen treatment, and corticosteroids to COVID-19 cases extended the survival time. Continued global surveillance remains an essential component of pandemic preparedness.

Indexed as

COVID-19Influenza A Virus, H7N9 SubtypeAntiviral AgentsHumansMaleOxygenPandemicsAntiviral AgentsOxygenclinical courseCOVID-19fatal casesH7N9protective factorssurvival time

Identifiers

PMID36504959
PMCPMC9729836
OpenAlexW4309845388

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.