Evidence map›Paper›PMID 35047039›Full record

ArticleInternational journal of endocrinology2022

Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes.

Yuanyuan Fu, Ling Hu, Hong-Wei Ren, Yi Zuo, Shaoqiu Chen, Qiu-Shi Zhang, Chen Shao, Yao Ma, Lin Wu, Jun-Jie Hao and 4 more

Erratum issuedAbstract read
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In one paragraph

Article in International journal of endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Observational
  6. Article
  7. Article
  8. Review
  9. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Yuanyuan FuDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.
Ling HuTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Hong-Wei RenTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Yi ZuoDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.
Shaoqiu ChenDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.
Qiu-Shi ZhangTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Chen ShaoTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Yao MaTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Lin WuTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Jun-Jie HaoTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Chuan-Zhen WangTianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China.
Zhanwei WangCancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA.
Richard YanagiharaDepartment of Pediatrics, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.
Youping DengDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA.ORCID https://orcid.org/0000-0002-5951-8213

Funding

University of Hawaii Cancer Center CCSGP30CA071789 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI Pallav Pokhrel · 1996 to 2026
$56.2M
NCI NIH HHS P30 CA071789
6 · The paper itself

Abstract

backgroundType 2 diabetes (T2D) as a worldwide chronic disease combined with the COVID-19 pandemic prompts the need for improving the management of hospitalized COVID-19 patients with preexisting T2D to reduce complications and the risk of death. This study aimed to identify clinical factors associated with COVID-19 outcomes specifically targeted at T2D patients and build an individualized risk prediction nomogram for risk stratification and early clinical intervention to reduce mortality.

methodsIn this retrospective study, the clinical characteristics of 382 confirmed COVID-19 patients, consisting of 108 with and 274 without preexisting T2D, from January 8 to March 7, 2020, in Tianyou Hospital in Wuhan, China, were collected and analyzed. Univariate and multivariate Cox regression models were performed to identify specific clinical factors associated with mortality of COVID-19 patients with T2D. An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration.

resultsNearly 15% (16/108) of hospitalized COVID-19 patients with T2D died. Twelve risk factors predictive of mortality were identified. Older age (HR = 1.076, 95% CI = 1.014-1.143,

conclusionsBy incorporating specific prognostic factors, this study provided a user-friendly graphical risk prediction tool for clinicians to quickly identify high-risk T2D patients hospitalized for COVID-19.

Identifiers

PMID35047039
PMCPMC8763039

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