Medical Intensive Care Unit, AP-HP, Saint-Louis Hospital, Paris, France.
Medicine University, Paris 5 University, Paris, France.
Crit Care Med. 2021 Jul 1;49(7):e683-e692. doi: 10.1097/CCM.0000000000005008.
Acute kidney injury, acute kidney injury severity, and acute kidney injury duration are associated with both short- and long-term outcomes. Despite recent definitions, only few studies assessed pattern of renal recovery and time-dependent competing risks are usually disregarded. Our objective was to describe pattern of acute kidney injury recovery, change of transition probability over time and their risk factors.
Monocenter retrospective cohort study. Acute kidney injury was defined according to Kidney Disease Improving Global Outcomes definition. Renal recovery was defined as normalization of both serum creatinine and urine output criteria. Competing risk analysis, time-inhomogeneous Markov model, and group-based trajectory modeling were performed.
Monocenter study.
Consecutive patients admitted in ICU from July 2018 to December 2018 were included.
None.
Three-hundred fifty patients were included. Acute kidney injury occurred in 166 patients at ICU admission, including 64 patients (38.6%) classified as acute kidney disease according to Acute Disease Quality Initiative definition and 44 patients (26.5%) who could not be classified. Cumulative incidence of recovery was 25 % at day 2 (95% CI, 18-32%) and 35% at day 7 (95% CI, 28-42%). After adjustment, need for mechanical ventilation (subdistribution hazard ratio, 0.42; 95% CI, 0.23-0.74) and severity of the acute kidney injury (stage 3 vs stage 1 subdistribution hazard ratio, 0.11; 95% CI, 0.03-0.35) were associated with lack of recovery. Group-based trajectory modeling identified three clusters of temporal changes in this setting, associated with both acute kidney injury recovery and patients' outcomes.
In this study, we demonstrate Acute Disease Quality Initiative to allow recovery pattern classification in 75% of critically ill patients. Our study underlines the need to take into account competing risk factors when assessing recovery pattern in critically ill patients.
急性肾损伤、急性肾损伤严重程度和急性肾损伤持续时间与短期和长期预后均相关。尽管最近有了新的定义，但仅有少数研究评估了肾损伤恢复的模式，且通常忽略了时间依赖性竞争风险。本研究旨在描述急性肾损伤恢复的模式，以及随时间推移的转换概率变化及其危险因素。
单中心回顾性队列研究。急性肾损伤按照改善全球肾脏病预后组织的定义进行诊断。肾损伤恢复定义为血清肌酐和尿量标准均恢复正常。进行竞争风险分析、时变非齐次马尔可夫模型和基于群组的轨迹建模。
单中心研究。
2018 年 7 月至 12 月入住 ICU 的连续患者。
无。
共纳入 350 例患者。入住 ICU 时发生急性肾损伤的患者有 166 例，其中根据急性疾病质量倡议定义分类为急性肾疾病的患者有 64 例（38.6%），无法分类的患者有 44 例（26.5%）。第 2 天恢复的累积发生率为 25%（95%CI，18%-32%），第 7 天为 35%（95%CI，28%-42%）。调整后，机械通气需求（亚分布风险比，0.42；95%CI，0.23-0.74）和急性肾损伤严重程度（3 期与 1 期亚分布风险比，0.11；95%CI，0.03-0.35）与未恢复相关。基于群组的轨迹建模在该设定中确定了三组急性肾损伤恢复的时间变化模式，与急性肾损伤恢复和患者预后均相关。
本研究中，我们应用急性疾病质量倡议能够对 75%的危重症患者进行恢复模式分类。我们的研究强调了在评估危重症患者的恢复模式时需要考虑竞争风险因素。
