Evidence map›Paper›PMID 33547290›Full record

ArticleScientific data2021

Electronic healthcare records and external outcome data for hospitalized patients with heart failure.

Zhongheng Zhang, Linghong Cao, Rangui Chen, Yan Zhao, Lukai Lv, Ziyin Xu, Ping Xu

Abstract readDataset
In one paragraph

Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
–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

52 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

7 authors.

Zhongheng Zhang *Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China. zh_zhang1984@zju.edu.cn.ORCID 0000-0002-2336-5323
Linghong Cao *Emergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China.
Rangui ChenEmergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China.
Yan ZhaoEmergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China.
Lukai LvEmergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China.
Ziyin XuEmergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China.
Ping XuEmergency Department, Zigong Fourth People's Hospital, 19 Tanmulin Road, Zigong, Sichuan, China. xp1657@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart failure is one of the most important reasons for hospitalization among elderly individuals and is associated with significant mortality and morbidity. Epidemiological studies require the establishment of high-quality databases. Several datasets that primarily involve heart failure populations have been established in Western countries and have generated many high-quality studies. However, no such dataset is available from China. Due to differences in genetic background and healthcare systems between China and Western countries, the establishment of a heart failure database for the Chinese population is urgently needed. We performed a retrospective single-center observational study to collect data regarding the characteristics of heart failure patients in China by integrating electronic healthcare records and follow-up outcome data. The study collected information for a total of 2,008 patients with heart failure, containing 166 attributes.

Indexed as

Electronic Health RecordsHospitalizationAgedAged, 80 and overChinaFemaleHeart FailureHumansMaleRetrospective Studies

Identifiers

PMID33547290
PMCPMC7865067

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.