RESUMO
Aim: The aim of this randomized, prospective study was to investigate whether the use of the structured epidural teaching model (SETM) may affect the learning curve for lumbar epidural block in novice trainees when compared with a standard teaching module. Introduction: There is a paucity of literature regarding the efficacy of teaching epidural blocks and comparisons between the different educational approaches. Method: Forty-four PGY3 anesthesia trainees were randomized to receive (study group) or to not receive (control group) the SDM (structured didactic model) before the beginning of their 6 months clinical practice rotation in labor and delivery suites. A CUSUM learning curve was built for every trainee. The scores were assigned by the staff instructor, who was unaware of the group to which the trainee belonged. Results: The number of subjects who achieved an improvement in performance was 8 trainees from the control group and 14 from the study group. The probability of achieving an improvement was higher (p < 05) in the study group than in the control group, with an aOR of 3.25 (CI: 1.01; 12.1). The proportion of subjects in the study group who completed the epidural without help was 1.21 (1.05-1.41) times the proportion of subjects who completed the epidural without help in the control group. The probability of completing the epidural block without any assistance was 21% higher in the study group than in the control group (p < 05). Conclusion: We have demonstrated that the use of the structured epidural teaching model (SETM) may improve the learning curve (CUSUM) for lumbar epidural block in novice, entirely inexperienced, anesthesia trainees.
RESUMO
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.
