Clinical agreement of a novel algorithm to estimate radial artery blood pressure from the non-invasive finger blood pressure

Defining Postinduction Hemodynamic Instability With an Automated Classification Model

BACKGROUND

Postinduction hypotension (PIH) may be associated with increased morbidity and mortality. In earlier studies, the definition of PIH is solely based on different absolute or relative thresholds. However, the time-course (eg, how fast blood pressure drops during induction) is rarely incorporated, whereas it might represent the hemodynamic instability of a patient. We propose a comprehensive model to distinguish hemodynamically unstable from stable patients by combining blood pressure thresholds with the magnitude and speed of decline.

METHODS

This prospective study included 375 adult elective noncardiac surgery patients. Noninvasive blood pressure was continuously measured between 5 minutes before up to 15 minutes after the first induction agent had been administered. An expert panel rated whether the patient experienced clinically relevant hemodynamic instability or not. Interrater correlation coefficient and intraclass correlation were computed to check for consistency between experts. Next, an automated classification model for clinically relevant hemodynamic instability was developed using mean, maximum, minimum systolic, mean, diastolic arterial blood pressure (SAP, MAP, and DAP, respectively) and their corresponding time course of decline. The model was trained and tested based on the hemodynamic instability labels provided by the experts.

RESULTS

In total 78 patients were classified as having experienced hemodynamic instability and 279 as not. The hemodynamically unstable patients were significantly older (7 years, 95% confidence interval (CI), 4-11, P < .001), with a higher prevalence of chronic obstructive pulmonary disease (COPD) (3% higher, 95% CI, 1-8, P = .036). Before induction, hemodynamically unstable patients had a higher SAP (median (first-third quartile): 161 (145-175) mm Hg vs 150 (134-166) mm Hg, P < .001) compared to hemodynamic stable patients. Interrater agreement between experts was 0.92 (95% CI, 0.89-0.94). The random forest classifier model showed excellent performance with an area under the receiver operating curve (AUROC) of 0.96, a sensitivity of 0.84, and specificity of 0.94.

CONCLUSIONS

Based on the high sensitivity and specificity, the developed model is able to differentiate between clinically relevant hemodynamic instability and hemodynamic stable patients. This classification model will pave the way for future research concerning hemodynamic instability and its prevention.

Continuous non-invasive vs. invasive arterial blood pressure monitoring during neuroradiological procedure: a comparative, prospective, monocentric, observational study

BACKGROUND

In the perioperative setting, the most accurate way to continuously measure arterial blood pressure (ABP) is using an arterial catheter. Surrogate methods such as finger cuff have been developed to allow non-invasive measurements and are increasingly used, but need further evaluation. The aim of this study is to evaluate the accuracy and clinical concordance between two devices for the measurement of ABP during neuroradiological procedure.

METHODS

This is a prospective, monocentric, observational study. All consecutive patients undergoing a neuroradiological procedure were eligible. Patients who needed arterial catheter for blood pressure measurement were included. During neuroradiological procedure, ABP (systolic, mean and diatolic blood pressure) was measured with two different technologies: radial artery catheter and Nexfin. Bland-Altman and error grid analyses were performed to evaluate the accuracy and clinical concordance between devices.

RESULTS

From March 2022 to November 2022, we included 50 patients, mostly ASA 3 (60%) and required a cerebral embolization (94%) under general anaesthesia (96%). Error grid analysis showed that 99% of non-invasive ABP measures obtained with the Nexfin were located in the risk zone A or B. However, 65.7% of hypertension events and 41% of hypotensive events were respectively not detected by Nexfin. Compared to the artery catheter, a significant relationship was found for SAP (r2 = 0.78) and MAP (r2 = 0.80) with the Nexfin (p < 0.001). Bias and limits of agreement (LOA) were respectively 9.6 mmHg (- 15.6 to 34.8 mmHg) and - 0.8 mmHg (- 17.2 to 15.6 mmHg), for SAP and MAP.

CONCLUSIONS

Nexfin is not strictly interchangeable with artery catheter for ABP measuring. Further studies are needed to define its clinical use during neuroradiological procedure.

TRIAL REGISTRATION

Clinicaltrials.gov, registration number: NCT05283824.

Smartphone-Based versus Non-Invasive Automatic Oscillometric Brachial Cuff Blood Pressure Measurements: A Prospective Method Comparison Volunteer Study

Introduction: Mobile health diagnostics have demonstrated effectiveness in detecting and managing chronic diseases. This method comparison study aims to assess the accuracy and precision of the previously evaluated OptiBP™ technology over a four-week study period. This device uses optical signals recorded by placing a patient's fingertip on a smartphone's camera to estimate blood pressure (BP). Methods: In adult participants without cardiac arrhythmias and minimal interarm blood pressure difference (systolic arterial pressure (SAP) < 15 mmHg or diastolic arterial pressure (DAP) < 10 mmHg), three pairs of 30 s BP measurements with the OptiBP™ (test method) were simultaneously compared using three pairs of measurements with the non-invasive oscillometric brachial cuff (reference method) on the opposite arm over a period of four consecutive weeks at a rate of two measurements per week (one in the morning and one in the afternoon). The agreement of BP values between the two technologies was analyzed using Bland-Altman and error grid analyses. The performance of the smartphone application was investigated using the International Organization for Standardization (ISO) definitions, which require the bias ± standard deviation (SD) between two technologies to be lower than 5 ± 8 mmHg. Results: Among the 65 eligible volunteers, 53 participants had adequate OptiBP™ BP values. In 12 patients, no OptiBP™ BP could be measured due to inadequate signals. Only nine participants had known chronic arterial hypertension and 76% of those patients were treated. The mean bias ± SD between both technologies was -1.4 mmHg ± 10.1 mmHg for systolic arterial pressure (SAP), 0.2 mmHg ± 6.5 mmHg for diastolic arterial pressure (DAP) and -0.5 mmHg ± 6.9 mmHg for mean arterial pressure (MAP). Error grid analyses indicated that 100% of the pairs of BP measurements were located in zones A (no risk) and B (low risk). Conclusions: In a cohort of volunteers, we observed an acceptable agreement between BP values obtained with the OptiBPTM and those obtained with the reference method over a four-week period. The OptiBPTM fulfills the ISO standards for MAP and DAP (but not SAP). The error grid analyses showed that 100% measurements were located in risk zones A and B. Despite the need for some technological improvements, this application may become an important tool to measure BP in the future.