Evidence map›Paper›PMID 33708933›Full record

ArticleAnnals of translational medicine2021

An analytical study of drug utilization, disease progression, and adverse events among 165 COVID-19 patients.

Feng Sun, Hao Kou, Shengfeng Wang, Yun Lu, Houyu Zhao, Wenjing Li, Qingxin Zhou, Qiaoli Jiang, Yinchu Cheng, Kun Yang and 5 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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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 5 institutions in 2 countries.

Feng SunDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hao KouDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Shengfeng WangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yun LuDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Houyu ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Wenjing LiDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Qingxin ZhouDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Qiaoli JiangDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Yinchu ChengDepartment of Pharmacy, Peking University Third Hospital, Beijing, China.
Kun YangDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Lin ZhuoResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China.
Yang XuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Dongfang WuDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Siyan ZhanDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Hong ChengDepartment of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, China.
Peking University · CNWuhan University · CNPeking University Third Hospital · CNZhongnan Hospital of Wuhan University · CNKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) epidemic has lasted for nearly 4 months by this study was conducted. We aimed to describe drug utilization, disease progression, and adverse drug events of COVID-19.

methodsA retrospective, single-center case series study enrolled 165 consecutive hospitalized COVID-19 patients who were followed up until March 25, 2020, from a designated hospital in Wuhan. Patients were grouped by a baseline degree of severity: non-severe and severe. An analytical study of drug utilization, disease progression, and adverse events (AEs) of COVID-19 was conducted.

resultsOf the 165 COVID-19 cases, antivirals, antibacterials, glucocorticoids, and traditional Chinese medicine (TCM) were administered to 92.7%, 98.8%, 68.5%, and 55.2% of patients, respectively. The total kinds of drugs administered to the severe subgroup [26, interquartile range (IQR) 18-39] were 11 more than the non-severe subgroup (15, IQR 10-24), regardless of comorbidities. The 2 most common combinations of medications in the 165 cases were 'antiviral therapy + glucocorticoids + TCM' (81, 49.1%) and 'antiviral therapy + glucocorticoids' (23, 13.9%). Compared with non-severe cases, severe cases received more glucocorticoids (88.5%

conclusionsOf the 165 COVID-19 patients, the fatality rate remained high (14.5%). Drug utilization for COVID-19 was diverse and generally complied with the existing guidelines. Combination regimens containing antiviral drugs might be beneficial to assist COVID-19 recovery. Additionally, liver and kidney AEs should not be ignored.

Indexed as

adverse events (AEs)disease progressiondrug utilizationfatalityNovel coronavirus disease (COVID-19)

Identifiers

PMID33708933
PMCPMC7944318
OpenAlexW3126432127

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.