Sawhney Simon, Marks Angharad, Fluck Nick, McLernon David J, Prescott Gordon J, Black Corri
University of Aberdeen, Institute of Applied Health Sciences, Aberdeen, UK.
NHS Grampian, Aberdeen, UK.
BMC Nephrol. 2017 Jan 6;18(1):9. doi: 10.1186/s12882-016-0430-4.
Reducing readmissions is an international priority in healthcare. Acute kidney injury (AKI) is common, serious and also a global concern. This analysis evaluates AKI as a candidate risk factor for unplanned readmissions and determines the reasons for readmissions.
GLOMMS-II is a large population cohort from one health authority in Scotland, combining hospital episode data and complete serial biochemistry results through data-linkage. 16453 people (2623 with AKI and 13830 without AKI) from GLOMMS-II who survived an index hospital admission in 2003 were used to identify the causes of and predict readmissions. The main outcome was "unplanned readmission or death" within 90 days of discharge. In a secondary analysis, the outcome was limited to readmissions with acute pulmonary oedema. 26 candidate predictors during the index admission included AKI (defined and staged 1-3 using an automated e-alert algorithm), prior AKI episodes, baseline kidney function, index admission circumstances and comorbidities. Prediction models were developed and assessed using multivariable logistic regression (stepwise variable selection), C statistics, bootstrap validation and decision curve analysis.
Three thousand sixty-five (18.6%) patients had the main outcome (2702 readmitted, 363 died without readmission). The outcome was strongly predicted by AKI. Multivariable odds ratios for AKI stage 3; 2 and 1 (vs no AKI) were 2.80 (2.22-3.53); 2.23 (1.85-2.68) and 1.50 (1.33-1.70). Acute pulmonary oedema was the reason for readmission in 26.6% with AKI and eGFR < 60; and 4.0% with no AKI and eGFR ≥ 60. The best stepwise model from all candidate predictors had a C statistic of 0.698 for the main outcome. In a secondary analysis, a model for readmission with acute pulmonary oedema had a C statistic of 0.853. In decision curve analysis, AKI improved clinical utility when added to any model, although the incremental benefit was small when predicting the main outcome.
AKI is a strong, consistent and independent risk factor for unplanned readmissions - particularly readmissions with acute pulmonary oedema. Pre-emptive planning at discharge should be considered to minimise avoidable readmissions in this high risk group.
减少再入院率是医疗保健领域的一项国际重点工作。急性肾损伤（AKI）很常见且病情严重，也是全球关注的问题。本分析将AKI评估为计划外再入院的潜在风险因素，并确定再入院的原因。
GLOMMS-II是来自苏格兰一个卫生部门的大型人群队列，通过数据链接将医院病历数据和完整的系列生化检查结果相结合。来自GLOMMS-II的16453人（2623例有AKI，13830例无AKI）在2003年经历了首次住院治疗并存活下来，用于确定再入院原因并预测再入院情况。主要结局是出院后90天内“计划外再入院或死亡”。在一项次要分析中，结局仅限于因急性肺水肿而再入院的情况。首次住院期间的26个候选预测因素包括AKI（使用自动电子警报算法定义并分为1-3期）、既往AKI发作、基线肾功能、首次住院情况和合并症。使用多变量逻辑回归（逐步变量选择）、C统计量、自助验证和决策曲线分析来开发和评估预测模型。
3065例（18.6%）患者出现主要结局（2702例再入院，363例未再入院即死亡）。AKI对结局有很强的预测作用。AKI 3期、2期和1期（与无AKI相比）的多变量优势比分别为2.80（2.22-3.53）；2.23（1.85-2.68）和1.50（1.33-1.70）。急性肺水肿是26.6%的AKI且估算肾小球滤过率（eGFR）<60患者再入院的原因；而在eGFR≥60的无AKI患者中，这一比例为4.0%。所有候选预测因素中最佳的逐步模型对主要结局的C统计量为0.698。在次要分析中，急性肺水肿再入院模型的C统计量为0.853。在决策曲线分析中，AKI添加到任何模型中均能提高临床实用性，尽管在预测主要结局时增量效益较小。
AKI是计划外再入院，尤其是因急性肺水肿而再入院的一个强大、一致且独立的风险因素。应考虑在出院时进行前瞻性规划，以尽量减少这一高危人群中可避免的再入院情况。
