Department of Intensive Care Medicine, Peninsula Health, Frankston, VIC, Australia.
Department of Cardiology, Peninsula Health, Frankston, VIC, Australia.
Crit Care Med. 2019 Mar;47(3):428-435. doi: 10.1097/CCM.0000000000003577.
To investigate the ability of available delirium risk assessment tools to identify patients at risk of delirium in an Australian tertiary ICU.
Prospective observational study.
An Australian tertiary ICU.
All patients admitted to the study ICU between May 8, 2017, and December 31, 2017, were assessed bid for delirium throughout their ICU stay using the Confusion Assessment Method for ICU. Patients were included in this study if they remained in ICU for over 24 hours and were excluded if they were delirious on ICU admission, or if they were unable to be assessed using the Confusion Assessment Method for ICU during their ICU stay. Delirium risk was calculated for each patient using the prediction of delirium in ICU patients, early prediction of delirium in ICU patients, and Lanzhou models. Data required for delirium predictor models were obtained retrospectively from patients medical records.
None.
There were 803 ICU admissions during the study period, of which 455 met inclusion criteria. 35.2% (n = 160) were Confusion Assessment Method for ICU positive during their ICU admission. Delirious patients had significantly higher Acute Physiology and Chronic Health Evaluation III scores (median, 72 vs 54; p < 0.001), longer ICU (median, 4.8 vs 1.8 d; p < 0.001) and hospital stay (16.0 vs 8.16 d; p < 0.001), greater requirement of invasive mechanical ventilation (70% vs 21.4%; p < 0.001), and increased ICU mortality (6.3% vs 2.4%; p = 0.037). All models included in this study displayed moderate to good discriminative ability. Area under the receiver operating curve for the prediction of delirium in ICU patients was 0.79 (95% CI, 0.75-0.83); recalibrated prediction of delirium in ICU patients was 0.79 (95% CI, 0.75-0.83); early prediction of delirium in ICU patients was 0.72 (95% CI, 0.67-0.77); and the Lanzhou model was 0.77 (95% CI, 0.72-0.81).
The predictive models evaluated in this study demonstrated moderate to good discriminative ability to predict ICU patients' risk of developing delirium. Models calculated at 24-hours post-ICU admission appear to be more accurate but may have limited utility in practice.
调查现有谵妄风险评估工具在澳大利亚一家三级 ICU 识别谵妄风险患者的能力。
前瞻性观察性研究。
澳大利亚一家三级 ICU。
2017 年 5 月 8 日至 2017 年 12 月 31 日期间，所有入住研究 ICU 的患者均在 ICU 期间接受了 2 次/天的谵妄评估，使用 ICU 意识模糊评估法进行评估。如果患者在 ICU 中停留超过 24 小时且 ICU 入院时出现谵妄，或在 ICU 期间无法使用 ICU 意识模糊评估法进行评估，则将患者排除在本研究之外。使用谵妄预测 ICU 患者、早期预测 ICU 患者和兰州模型计算每位患者的谵妄风险。从患者病历中回顾性获得谵妄预测模型所需的数据。
无。
研究期间共有 803 例 ICU 入院，其中 455 例符合纳入标准。35.2%（n=160）在 ICU 住院期间被 ICU 意识模糊评估法确定为阳性。谵妄患者的急性生理学和慢性健康评估 III 评分明显更高（中位数，72 比 54；p＜0.001），ICU 住院时间（中位数，4.8 比 1.8 天；p＜0.001）和住院时间（中位数，16.0 比 8.16 天；p＜0.001）更长，更需要有创机械通气（70%比 21.4%；p＜0.001），ICU 死亡率增加（6.3%比 2.4%；p=0.037）。本研究纳入的所有模型均显示出中等至良好的区分能力。预测 ICU 患者谵妄的受试者工作特征曲线下面积为 0.79（95%CI，0.75-0.83）；重新校准的 ICU 患者谵妄预测为 0.79（95%CI，0.75-0.83）；早期预测 ICU 患者谵妄为 0.72（95%CI，0.67-0.77）；兰州模型为 0.77（95%CI，0.72-0.81）。
本研究评估的预测模型对预测 ICU 患者发生谵妄的风险具有中等至良好的区分能力。在 ICU 入院后 24 小时计算的模型似乎更准确，但在实践中可能具有有限的实用性。
