Evidence map›Paper›PMID 31048925›Full record

ArticlePloS one2019

Time to acute kidney injury and its predictors among newly diagnosed Type 2 diabetic patients at government hospitals in Harari Region, East Ethiopia.

Lemma Demissie Regassa, Yigzaw Kebede Gete, Fantahun Ayenew Mekonnen

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In one paragraph

Article in PloS one, 2019. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Outcome and Determining Characteristics of ICU Patients with Acute Kidney Injury in a Low-Income Country, a Multicenter Experience.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2024
    Article
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  7. Review
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Lemma Demissie RegassaDepartment of Epidemiology and Biostatistics, Collage of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia.
Yigzaw Kebede GeteDepartment of Epidemiology and Biostatistics, Institute of Public Health, Collage of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Fantahun Ayenew MekonnenDepartment of Epidemiology and Biostatistics, Institute of Public Health, Collage of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.ORCID 0000-0002-9330-0621

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncidence of Acute Kidney Injury (AKI) among Type 2 diabetic patients is significantly increasing. But, earlier studies has focused on the admitted patients which may hide the true nature of the Acute Kidney Injury among Type 2 Diabetic (T2D) patients. So, this study was conducted to determine the time to Acute Kidney Injury and its predictors among Type 2 Diabetic patients in Harari Region, East Ethiopia.

methodsWe conducted a retrospective cohort study among type 2 diabetic patients who had been receiving treatment at government hospitals of Harari region, Ethiopia from 2013 to 2017. We extracted data from patients' medical records. We estimated incidence rate and compared survival curves between different exposure groups using Kaplan-Meier and log-rank test. Weibull regression model was fitted to the data to identify the predictor variables. Variables with p-value <0.05 were considered statistically significant.

resultsOverall, 14.5% (95%CI: 11.7-17.9) of the study population developed acute kidney injury, with median survival time of 57 months. The significant predictors were physical activity [Adjusted Time Ratio (ATR):95%CI; 0.6 (0.49-0.75)], congestive heart failure [ATR:95%CI; 0.84 (0.71-0.99)], chronic kidney disease [ATR:95%CI; 0.77(0.65-0.91)], hypertension [ATR:95%CI; 0.78(0.65-0.91)], obesity [ATR:95%CI; 0.84(0.74-0.96)], diabetic nephropathy [ATR:95%CI; 0.80(0.65-0.98)], diuretics & beta blockers [ATR:95%CI; 0.85(0.74-0.97)], and delay of follow-up [ATR:95%CI; 0.97(0.96-0.98)].

conclusionsIncidence of acute kidney injury was high in our study area. Hence, identification and controlling of comorbidities along with regular monitoring of kidney function are needed to prevent or delay the risk of acute kidney injury in type 2 diabetic patients.

Indexed as

Acute Kidney InjuryAdolescentAdultAgedAged, 80 and overChildCohort StudiesDiabetes Mellitus, Type 2EthiopiaFemaleGovernmentHospitalsHumansIncidenceMaleMiddle Aged

Identifiers

PMID31048925
PMCPMC6497261

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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.