Performance of the Hypotension Prediction Index With Noninvasive Arterial Pressure Waveforms in Awake Cesarean Delivery Patients Under Spinal Anesthesia

医学 麻醉 接收机工作特性 置信区间 血压 平均动脉压 血流动力学 心率 内科学
作者
Luciano Frassanito,Chiara Sonnino,Alessandra Piersanti,Bruno Antonio Zanfini,Stefano Catarci,Pietro Paolo Giuri,Marco Scorzoni,Gian Luigi Gonnella,Massimo Antonelli,Gaetano Draisci
出处
期刊:Anesthesia & Analgesia [Lippincott Williams & Wilkins]
卷期号:134 (3): 633-643 被引量:55
标识
DOI:10.1213/ane.0000000000005754
摘要

BACKGROUND: Arterial hypotension is common after spinal anesthesia (SA) for cesarean delivery (CD), and to date, there is no definitive method to predict it. The hypotension prediction index (HPI) is an algorithm that uses the arterial waveform to predict early phases of intraoperative hypotension. The aims of this study were to assess the diagnostic ability of HPI working with arterial waveforms detected by ClearSight system in predicting impending hypotension in awake patients, and the agreement of pressure values recorded by ClearSight with conventional noninvasive blood pressure (NIBP) monitoring in patients undergoing CD under SA. METHODS: In this retrospective analysis of pregnant patients scheduled for elective CD under SA, continuous hemodynamic data measured with the ClearSight monitor until delivery were downloaded from an Edwards Lifesciences HemoSphere platform and analyzed. Receiver operating characteristic (ROC) curves were constructed to evaluate the performance of HPI algorithm working on the ClearSight pressure waveform in predicting hypotensive events, defined as mean arterial pressure (MAP) <65 mm Hg for >1 minute. The sensitivity, specificity, positive predictive value, and negative predictive value were computed at the optimal cutpoint, selected as the value that minimizes the difference between sensitivity and specificity. ClearSight MAP values were compared to NIBP MAP values by linear regression and Bland-Altman analysis corrected for repeated measurements. RESULTS: Fifty patients undergoing CD were included in the analysis. Hypotension occurred in 23 patients (48%). Among patients experiencing hypotension, the HPI disclosed 71 alerts. The HPI predicted hypotensive events with a sensitivity of 83% (95% confidence interval [CI], 69-97) and specificity of 83% (95% CI, 70-95) at 3 minutes before the event (area under the curve [AUC] 0.913 [95% CI, 0.837-0.99]); with a sensitivity of 97% (95% CI, 92-100) and specificity of 97% (95% CI, 92-100) at 2 minutes before the event (AUC 0.995 [95% CI, 0.979-1.0]); and with a sensitivity of 100% (95% CI, 100-100) and specificity 100% (95% CI, 100-100) 1 minute before the event (AUC 1.0 [95% CI, 1.0-1.0]). A total of 2280 paired NIBP MAP and ClearSight MAP values were assessed. The mean of the differences between the ClearSight and NIBP assessed using Bland-Altman analysis (±standard deviation [SD]; 95% limits of agreement with respective 95% CI) was -0.97 mm Hg (±4.8; -10.5 [-10.8 to -10.1] to 8.5 [8.1-8.8]). CONCLUSIONS: HPI provides an accurate real time and continuous prediction of impending intraoperative hypotension before its occurrence in awake patients under SA. We found acceptable agreement between ClearSight MAP and NIBP MAP.
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