Evidence map›Paper›PMID 37457244›Full record

ArticleFrontiers in public health2023

Risk assessment and disease burden of extreme precipitation on hospitalizations for acute aortic dissection in a subtropical coastal Chinese city.

Yanhu Ji, Jianping Xiong, Zhongjia Yuan, Zepeng Huang, Liping Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

5 authors at 5 institutions in 1 country.

Yanhu JiSchool of Public Health, Shantou University, Shantou, China.
Jianping XiongThe First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Zhongjia YuanShantou Central Hospital, Shantou, China.
Zepeng HuangThe Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
Liping LiSchool of Public Health, Shantou University, Shantou, China.
First Affiliated Hospital of Shantou University Medical College · CNSecond Affiliated Hospital of Shantou University Medical College · CNShantou Central Hospital · CNShantou University · CNShantou University Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Extreme precipitation events are becoming more frequent due to climate change. The present study aimed to explore the impacts of extreme precipitation on hospitalizations for acute aortic dissection (AAD) and to identify susceptible populations and quantify the corresponding disease burden. Methods: The present study used a distributed lag nonlinear model (DLNM) with a quasi-Poisson function to investigate the association between extreme precipitation (≥95th percentile) and the risk of hospitalizations for AAD from 2015 to 2020 in Shantou, Guangdong Province, China. Results: The significant adverse effects of extreme precipitation (relative to no precipitation) on daily AAD hospitalizations lasted from lag 5 [relative risk (RR): 1.0318, 95% confidence interval (CI): 1.0067-1.0575] to lag 9 (RR: 1.0297, 95% CI: 1.0045-1.0555) and reached its maximum at lag 7 (RR: 1.0382, 95% CI: 1.0105-1.0665). Males and older adult individuals (≥60 years) were more susceptible to extreme precipitation. A total of 3.68% (118 cases) of AAD hospitalizations were due to extreme precipitation. Conclusion: Extreme precipitation was significantly correlated with AAD hospitalizations. Government departments should actively implement extreme precipitation intervention measures to strengthen the protection of males and the older adult (≥60 years) and effectively reduce AAD hospitalizations.

Indexed as

Aortic DissectionAgedChinaCitiesHospitalizationHumansMaleRisk Assessmentacute aortic dissectiondisease burdendistributed lag nonlinear modelextreme precipitationtime series

Identifiers

PMID37457244
PMCPMC10343949
OpenAlexW4382777007

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.