Evidence map›Paper›PMID 36324072›Full record

ArticleBMC nephrology2022

Incidence and predictors of acute kidney injury among women with severe pre-eclampsia at Mbarara Regional Referral Hospital.

Mariam Hassan, Roland Mayanja, Wasswa G M Ssalongo, Natumanya Robert, Lugobe Henry Mark, Okello Samson, Rose Muhindo

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07040696 (Accuracy of the Venous Excess Ultrasound Score at Hospital Admission to Predict Acute Kidney Injury in Preeclampsia With Severe Features), which is not on this map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% 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.

NCT07040696 completednot on this mapstarted 2025, after this paper: background citation

Accuracy of the Venous Excess Ultrasound Score at Hospital Admission to Predict Acute Kidney Injury in Preeclampsia With Severe Features: A Prospective Observational Study

TypeobservationalSponsorCairo UniversityRan2025 to 2026Enrolled70ConditionsPreeclampsia, Acute Kidney InjuryArmsVenous excess ultrasound score (VEXUS)
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

7 authors at 2 institutions in 1 country.

Mariam HassanDepartment of Obstetrics and Gynecology, Mbarara University of Science and Technology, Mbarara, Uganda.
Roland Mayanja *Department of Obstetrics and Gynecology, Mbarara University of Science and Technology, Mbarara, Uganda.
Wasswa G M SsalongoDepartment of Obstetrics and Gynecology, Mbarara Regional Referral Hospital, Mbarara, Uganda.
Natumanya RobertDepartment of Medicine, Mbarara Regional Referral Hospital, Mbarara, Uganda.
Lugobe Henry MarkDepartment of Obstetrics and Gynecology, Mbarara University of Science and Technology, Mbarara, Uganda.
Okello SamsonDepartment of Internal Medicine, Mbarara University of Science and Technology, Mbarara, Uganda.
Rose Muhindo *Department of Internal Medicine, Mbarara University of Science and Technology, Mbarara, Uganda. rosie@must.ac.ug.
Mbarara University of Science and Technology · UGMbarara National Referral Hospital · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe presence of acute kidney injury (AKI) in pre-eclampsia complicates treatment including; increasing length of hospital stay and a need to access services like dialysis which are largely expensive in resource-limited settings. We aimed to determine incidence and predictors of acute kidney injury among women with severe pre-eclampsia at Mbarara Regional Referral Hospital in southwestern Uganda.

methodsWe carried out a hospital-based prospective cohort study from 16 November  2018 to 18 April 2019, among pregnant women with severe pre-eclampsia followed up in the hospital. We enrolled 70 mothers with severe pre-eclampsia and eclampsia; we excluded patients with a history of chronic kidney disease, chronic hypertension, and gestational hypertension. Data on socio-demographics, laboratory parameters, health system, obstetric and medical factors were collected. Baseline serum creatinine, complete blood count, and CD4 T-cell count were all done at admission (0-hour). A second serum creatinine was done at 48-hours to determine the presence of AKI and AKI was defined as a relative change of serum creatinine value at least 1.5 times the baseline (i.e., at admission) within 48 h. The proportion of women diagnosed with acute kidney injury among the total number of women with severe pre-eclampsia was reported as incidence proportion. Univariate and multivariate logistic regression was used to establish the association between acute kidney injury and severe pre-eclampsia.

resultsIncidence of acute kidney injury was high (42.86%) among women with severe pre-eclampsia. Antenatal care attendance was protective with an odds ratio of 0.14 (0.03, 0.73), p-value 0.020 at bivariate analysis but had no statistical significance at multivariate analysis. Eclampsia was an independent risk factor for acute kidney injury. (aOR 5.89 (1.51, 38.88), p-value 0.014.

conclusionThe incidence of acute kidney injury in patients with severe pre-eclampsia is high. Eclampsia is an independent risk factor of acute kidney injury. The findings of this study highlight the urgent need for more research and better perinatal care for these women.

Indexed as

Acute Kidney InjuryEclampsiaPre-EclampsiaCreatinineFemaleHospitalsHumansIncidencePregnancyProspective StudiesReferral and ConsultationRenal DialysisRisk FactorsUgandaCreatinineAcute kidney injuryEclampsiaSevere pre-eclampsia

Identifiers

PMID36324072
PMCPMC9632010
OpenAlexW4308139562

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Registered trials

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.