Evidence map›Paper›PMID 30999930›Full record

ArticleItalian journal of pediatrics2019

Prevalence, types, and malformations in congenital anomalies of the kidney and urinary tract in newborns: a retrospective hospital-based study.

Zhong-Yi Li, Yan-Min Chen, Li-Qian Qiu, Dan-Qing Chen, Chong-Gao Hu, Jian-Yun Xu, Xiao-Hui Zhang

Open access · goldAbstract read
In one paragraph

Article in Italian journal of pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 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

7 authors at 3 institutions in 1 country.

Zhong-Yi LiDepartment of Urology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China.
Yan-Min ChenDepartment of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, No.1 Xueshi Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China.
Li-Qian QiuDepartment of Women's Health, Women's Hospital, Zhejiang University School of Medicine, No.1 Xueshi Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China.
Dan-Qing ChenDepartment of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, No.1 Xueshi Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China.
Chong-Gao HuZhejiang Provincial Center for Disease Control and Prevention, 3399 Binsheng road, Hangzhou, People's Republic of China.
Jian-Yun XuDepartment of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, No.1 Xueshi Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China.
Xiao-Hui ZhangDepartment of Women's Health, Women's Hospital, Zhejiang University School of Medicine, No.1 Xueshi Road, Hangzhou, Zhejiang Province, 310006, People's Republic of China. zjfb_amy@zju.edu.cn.ORCID http://orcid.org/0000-0003-4803-9812
Women's Hospital, School of Medicine, Zhejiang University · CNSecond Affiliated Hospital of Zhejiang University · CNZhejiang Center for Disease Control and Prevention · CN

Funding

Application of Public Projects in Zhejiang Science and Technology Department 2017C22003Health and Family Planning Commission of Zhejiang Province 2018268607
6 · The paper itself

Abstract

backgroundCongenital anomalies of the kidney and urinary tract (CAKUTs) are some of the most common birth defects affecting newborns. CAKUTs often have poor birth outcomes owing to the limited experience of physicians in developing countries regarding antenatal and postnatal diagnosis. We aimed to estimate the epidemiology of CAKUTs using data from a hospital-based registry in Zhejiang Province, China.

methodsWe included a total of 2790 newborns with CAKUTs, identified among 1,748,038 births during 2010-2016. The prevalence and type of CAKUTs, maternal and neonatal characteristics, and associated malformations were analyzed.

resultsThe average prevalence of CAKUTs born to mothers overall and mothers aged ≥35 years were both around 1.60 per 1000 births (95% confidence interval (CI), 1.54-1.66; 95% CI, 1.44-1.83, respectively) during the study period. The prevalence of CAKUTs changed over time among all women and women of advanced maternal age, although no significant trends were observed. CAKUTs were more likely to occur in male than female newborns (odds ratio (OR) 1.28, 95% CI 1.18-1.38), in multiple births than singletons (OR 1.53, 95% CI 1.21-1.92) and in urban areas than rural areas (OR 1.27, 95% CI 1.18-1.37). The overall prenatal detection rate of CAKUTs was 73.87%. The average gestational age at antenatal diagnosis was 26.57 ± 8.70 weeks. A total 22.69% CAKUTs had associated malformations. Congenital heart defects were the most common anomalies, accounting for 8.89% of the whole population. The main proportion in subgroups was hydronephrosis, representing 31.79% of registered CAKUTs.

conclusionsThere was a nearly twofold increase in the prevalence of CAKUTs from 2010 to 2016 in Zhejiang Province. CAKUTs are strongly associated with male sex, multiple births, urban areas, and other nonurinary congenital malformations.

Indexed as

AdultChinaCongenital AbnormalitiesFemaleGestational AgeHumansInfant, NewbornKidneyMalePregnancyPregnancy, MultiplePrenatal DiagnosisPrevalenceRetrospective StudiesSex DistributionUrban PopulationAssociated malformationsCongenital anomalies of the kidney and urinary tract (CAKUTs)Prenatal detectionPrevalence

Identifiers

PMID30999930
PMCPMC6472003
OpenAlexW2946065036

What OpenQuestion holds

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LicenceCC BY
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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.