Takaki Shunsuke, Kadiman Suhaini Bin, Tahir Sharifah Suraya, Ariff M Hassan, Kurahashi Kiyoyasu, Goto Takahisa
Department of Anesthesiology, Yokohama City University Hospital, Japan.
Department of Anesthesiology, National Heart Center in Malaysia (Institute Jantung Negara), Malaysia.
J Cardiothorac Vasc Anesth. 2015 Feb;29(1):64-8. doi: 10.1053/j.jvca.2014.06.022.
The aim of this study was to determine the best predictors of successful extubation after cardiac surgery, by modifying the rapid shallow breathing index (RSBI) based on patients' anthropometric parameters.
Single-center prospective observational study.
Two general intensive care units at a single research institute.
Patients who had undergone uncomplicated cardiac surgery.
None.
The following parameters were investigated in conjunction with modification of the RSBI: Actual body weight (ABW), predicted body weight, ideal body weight, body mass index (BMI), and body surface area. Using the first set of patient data, RSBI threshold and modified RSBI for extubation failure were determined (threshold value; RSBI: 77 breaths/min (bpm)/L, RSBI adjusted with ABW: 5.0 bpm×kg/mL, RSBI adjusted with BMI: 2.0 bpm×BMI/mL). These threshold values for RSBI and RSBI adjusted with ABW or BMI were validated using the second set of patient data. Sensitivity values for RSBI, RSBI modified with ABW, and RSBI modified with BMI were 91%, 100%, and 100%, respectively. The corresponding specificity values were 89%, 92%, and 93%, and the corresponding receiver operator characteristic values were 0.951, 0.977, and 0.980, respectively.
Modified RSBI adjusted based on ABW or BMI has greater predictive power than conventional RSBI.
本研究旨在通过基于患者人体测量参数修改快速浅呼吸指数(RSBI),确定心脏手术后成功拔管的最佳预测指标。
单中心前瞻性观察性研究。
单个研究所的两个普通重症监护病房。
接受了无并发症心脏手术的患者。
无。
结合RSBI的修改对以下参数进行了研究:实际体重(ABW)、预测体重、理想体重、体重指数(BMI)和体表面积。利用第一组患者数据,确定了拔管失败的RSBI阈值和修改后的RSBI(阈值;RSBI:77次呼吸/分钟(bpm)/升,经ABW调整的RSBI:5.0 bpm×千克/毫升,经BMI调整的RSBI:2.0 bpm×BMI/毫升)。使用第二组患者数据对这些RSBI阈值以及经ABW或BMI调整的RSBI进行了验证。RSBI、经ABW修改的RSBI和经BMI修改的RSBI的敏感性值分别为91%、100%和100%。相应的特异性值分别为89%、92%和93%,相应的受试者工作特征值分别为0.951、0.977和0.980。
基于ABW或BMI调整的改良RSBI比传统RSBI具有更强的预测能力。