Evidence map›Paper›PMID 38385134›Full record

ArticleFrontiers in cardiovascular medicine2024

Impact of the COVID-19 pandemic on cardiovascular mortality and contrast analysis within subgroups.

Shoufang Song, Chen Guo, Ruiyun Wu, Hong Zhao, Qiang Li, Jia-Hao Dou, Fan-Shun Guo, Jin Wei

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

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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

8 authors.

Shoufang SongDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Chen GuoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Ruiyun WuDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Hong ZhaoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Qiang LiDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Jia-Hao DouDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Fan-Shun GuoDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.
Jin WeiDepartment of Cardiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: An increase in deaths has been perceived during the pandemic, which cannot be explained only by COVID-19. The actual number of deaths far exceeds the recorded data on deaths directly related to SARS-CoV-2 infection. Data from early and short-lived pandemic studies show a dramatic shift in cardiovascular mortality. Grounded in the post-pandemic era, macroscopic big data on cardiovascular mortality during the pandemic need to be further reviewed and studied, which is crucial for cardiovascular disease prevention and control. Methods: We retrieved and collected data associated with cardiovascular disease mortality from the National Vital Statistic System from the Center for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) platform based on the ICD-10 codes. We applied regression analysis to characterize overall cardiovascular disease mortality trends from 2010 to 2023 and built a time series model to predict mortality for 2020-2023 based on mortality data from 2010 to 2019 in order to affirm the existence of the excess deaths by evaluating observed vs. predicted mortality. We also conducted subgroup analyses by sex, age and race/ethnicity for the purpose of obtaining more specific sociodemographic information. Results: All-cause age-standardised mortality rates (ASMRs) for CVD dramatically increased between 2019 and 2021[annual percentage change (APC) 11.27%, Conclusions: All-cause ASMRs for CVD increased notably during the initial two years of the COVID-19 pandemic and then witnessed a decline in 2021-2023. The cohorts (the young, males and minorities) with the steepest rise in mortality decreased at the fastest rate instead. Previous initiatives to promote cardiovascular health were effective, but further research on cardiovascular healthcare for the elderly and racial disparities should be attached to priority considering the presence of sociodemographic differences in CVD death.

Indexed as

cardiovascular diseasesCOVID- 19disparitymortalitypredictive analysis

Identifiers

PMID38385134
PMCPMC10879411

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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.