Literature DB >> 30496574

Risk prediction for acute kidney injury in acute medical admissions in the UK.

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Abstract

BACKGROUND: Acute Kidney Injury (AKI) is associated with adverse outcomes; therefore identifying patients who are at risk of developing AKI in hospital may lead to targeted prevention. AIM: We undertook a UK-wide study in acute medical units (AMUs) to define those who develop hospital-acquired AKI (hAKI); to determine risk factors associated with hAKI and to assess the feasibility of developing a risk prediction score.
DESIGN: Prospective multi-centre cohort study across 72 AMUs in the UK.
METHODS: Data collected from all patients who presented over a 24-h period. Chronic dialysis, community-acquired AKI (cAKI) and those with fewer than two creatinine measurements were excluded. Primary outcome was the development of h-AKI.
RESULTS: Two thousand four hundred and fourty-six individuals were admitted to the seventy-two participating centres. Three hundred and eighty-four patients (16%) sustained AKI of whom two hundred and eighty-seven (75%) were cAKI and ninety-seven (25%) were hAKI. After exclusions, chronic kidney disease [Odds Ratio (OR) 3.08, 95% Confidence Interval (CI) 1.96-4.83], diuretic prescription (OR 2.33, 95% CI 1.5-3.65), a lower haemoglobin concentration and elevated serum bilirubin were independently associated with development of hAKI. Multi-variable model discrimination was only moderate (c-statistic 0.75).
CONCLUSIONS: AKI in AMUs is common and associated with worse outcomes, with the majority of cases community acquired. Only a small proportion of patients develop hAKI. Prognostic risk factor modelling demonstrated only moderate discrimination implying that widespread adoption of such an AKI clinical risk score across all AMU admissions is not currently justified. More targeted risk assessment or automated methods of calculating individual risk may be more appropriate alternatives.
© The Author(s) 2018. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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Year:  2019        PMID: 30496574     DOI: 10.1093/qjmed/hcy277

Source DB:  PubMed          Journal:  QJM        ISSN: 1460-2393


  2 in total

1.  Development and validation of an interpretable clinical score for early identification of acute kidney injury at the emergency department.

Authors:  Yukai Ang; Siqi Li; Marcus Eng Hock Ong; Feng Xie; Su Hooi Teo; Lina Choong; Riece Koniman; Bibhas Chakraborty; Andrew Fu Wah Ho; Nan Liu
Journal:  Sci Rep       Date:  2022-05-02       Impact factor: 4.996

2.  Using electronic AKI alerts to define the epidemiology of acute kidney injury in renal transplants.

Authors:  Aled Jones; Jennifer Holmes; Michael Stephens; John Geen; John Williams; Kieron Donovan; Aled O Phillips
Journal:  J Nephrol       Date:  2020-12-01       Impact factor: 3.902

  2 in total

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