Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI

被引:115
作者
Sawhney, Simon
Fraser, Simon D.
机构
[1] Univ Aberdeen, Kidney Dis Farr Collaborat, Aberdeen, Scotland
[2] Univ Southampton, Kidney Dis Farr Collaborat, Southampton, Hants, England
基金
英国医学研究理事会; 英国惠康基金; 英国经济与社会研究理事会; 英国工程与自然科学研究理事会;
关键词
Acute kidney injury; Incidence; Prognosis; Big-data; Quality improvement; ACUTE KIDNEY INJURY; ACUTE-RENAL-FAILURE; SEVERE MATERNAL MORBIDITY; LONG-TERM OUTCOMES; REQUIRING DIALYSIS; SERUM CREATININE; INTERNATIONAL SOCIETY; HOSPITALIZED ADULTS; CARDIAC-SURGERY; TRENDS;
D O I
10.1053/j.ackd.2017.05.001
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Large observational databases linking kidney function and other routine patient health data are increasingly being used to study acute kidney injury (AKI). Routine health care data show an apparent rise in the incidence of population AKI and an increase in acute dialysis. Studies also report an excess in mortality and adverse renal outcomes after AKI, although with variation depending on AKI severity, baseline, definition of renal recovery, and the time point during follow-up. However, differences in data capture, AKI awareness, monitoring, recognition, and clinical practice make comparisons between health care settings and periods difficult. In this review, we describe the growing role of large databases in determining the incidence and prognosis of AKI and evaluating initiatives to improve the quality of care in AKI. Using examples, we illustrate this use of routinely collected health data and discuss the strengths, limitations, and implications for researchers and clinicians. (c) 2017 The Authors. Published by Elsevier Inc. on behalf of the National Kidney Foundation, Inc.
引用
收藏
页码:194 / 204
页数:11
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