Evidence map›Paper›PMID 32234061›Full record

ArticleBMC medicine2020

Risk of long-term renal disease in women with a history of preterm delivery: a population-based cohort study.

Peter M Barrett, Fergus P McCarthy, Marie Evans, Marius Kublickas, Ivan J Perry, Peter Stenvinkel, Karolina Kublickiene, Ali S Khashan

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.0field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 16 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

8 authors at 2 institutions in 2 countries.

Peter M BarrettSchool of Public Health, Western Gateway Building, University College Cork, Cork, Ireland. peter.barrett@ucc.ie.ORCID 0000-0002-9637-9603
Fergus P McCarthyIrish Centre for Maternal and Child Health Research, Cork University Maternity Hospital, University College Cork, Cork, Ireland.
Marie EvansDivision of Renal Medicine, Department of Clinical Intervention, Science and Technology (CLINTEC), Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Marius KublickasDepartment of Obstetrics & Gynaecology, Karolinska University Hospital, Stockholm, Sweden.
Ivan J PerrySchool of Public Health, Western Gateway Building, University College Cork, Cork, Ireland.
Peter StenvinkelDivision of Renal Medicine, Department of Clinical Intervention, Science and Technology (CLINTEC), Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Karolina KublickieneDivision of Renal Medicine, Department of Clinical Intervention, Science and Technology (CLINTEC), Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Ali S KhashanSchool of Public Health, Western Gateway Building, University College Cork, Cork, Ireland.
Karolinska University Hospital · SEUniversity College Cork · IE

Funding

Health Research Board 203930/B/16/ZSwedish Research Council 2009-1068Swedish Research Council 2018-00932Wellcome TrustWellcome Trust 203930/B/16/Z
6 · The paper itself

Abstract

backgroundPreterm delivery is an independent risk factor for maternal cardiovascular disease. Little is known about the association between preterm delivery and maternal renal function. This study aimed to examine whether women who experience preterm delivery are at increased risk of subsequent chronic kidney disease (CKD) and end-stage kidney disease (ESKD).

methodsUsing data from the Swedish Medical Birth Register, singleton live births from 1973 to 2012 were identified and linked to data from the Swedish Renal Register and National Patient Register (up to 2013). Gestational age at delivery was the main exposure and treated as a time-dependent variable. Primary outcomes were maternal CKD or ESKD. Cox proportional hazard regression models were used for analysis.

resultsThe dataset included 1,943,716 women who had 3,760,429 singleton live births. The median follow-up was 20.6 (interquartile range 9.9-30.0) years. Overall, 162,918 women (8.4%) delivered at least 1 preterm infant (< 37 weeks). Women who had any preterm delivery (< 37 weeks) were at increased risk of CKD (adjusted hazard ratio (aHR) 1.39, 95% CI 1.32-1.45) and ESKD (aHR 2.22, 95% CI 1.90-2.58) compared with women who only delivered at term (≥ 37 weeks). Women who delivered an extremely preterm infant (< 28 weeks) were at increased risk of CKD (aHR 1.84, 95% CI 1.52-2.22) and ESKD (aHR 3.61, 95% CI 2.03-6.39). The highest risk of CKD and ESKD was in women who experienced preterm delivery + preeclampsia (vs. non-preeclamptic term deliveries, for CKD, aHR 2.81, 95% CI 2.46-3.20; for ESKD, aHR 6.70, 95% CI 4.70-9.56). However, spontaneous preterm delivery was also associated with increased risk of CKD (aHR 1.32, 95% CI 1.25-1.39) and ESKD (aHR 1.99, 95% CI 1.67-2.38) independent of preeclampsia or small for gestational age (SGA).

conclusionsWomen with history of preterm delivery are at increased risk of CKD and ESKD. The risk is higher among women who had very preterm or extremely preterm deliveries, or whose preterm delivery was medically indicated. Women who experience spontaneous preterm delivery are at increased risk of long-term renal disease independent of preeclampsia or SGA. Preterm delivery may act as a risk marker for adverse maternal renal outcomes.

Indexed as

AdultCohort StudiesFemaleHumansInfantInfant, NewbornKidney Failure, ChronicPregnancyPremature BirthRisk FactorsYoung AdultChronic kidney diseaseEnd-stage kidney diseaseEpidemiologyPreeclampsiaPregnancyPreterm delivery

Identifiers

PMID32234061
PMCPMC7110747
OpenAlexW3014926930

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.