Abstract

Background Spinal anesthesia for cesarean delivery commonly causes maternal hypotension, which may compromise uteroplacental perfusion and maternal comfort. Guidelines recommend maintaining maternal blood pressure near baseline with prophylactic vasopressor strategies, yet titration remains reactive. We evaluated an autoregressive with exogenous input (ARX) decision-support algorithm that provides real-time forecasts of maternal mean arterial pressure (MAP) to support vasopressor management during cesarean delivery under spinal anesthesia.

Methods In this single-center, open-label, prospective pilot study, 20 pregnant patients at term undergoing elective cesarean delivery under spinal anesthesia received standard care supplemented by ARX-generated MAP predictions at 1-, 2- and 3-minute horizons. Clinicians titrated phenylephrine per institutional protocol while reviewing ARX predictions, retaining full autonomy for dosing decisions. Predictive performance was quantified using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), and fraction of improvement in total error (FIT). ARX-guided patients were matched 1:2 to nonconcurrent controls (n = 40) on attending anesthesiologist and intrathecal bupivacaine dose, with nearest-neighbor matching on age and body mass index. Exploratory outcomes included hypotension (MAP <80% of baseline), phenylephrine dose, maternal nausea, and neonatal outcomes. For minute-level hypotension classification performance, sensitivity/specificity (and related metrics) were estimated using generalized estimating equations (GEE) to account for within-patient clustering of repeated observations.

Results One-minute-ahead ARX predictions achieved a mean (±SD) RMSE of 3.71 ± 3.26 mmHg and MAE of 2.75 ± 2.52 mmHg, with R² 0.34 ± 0.63 and FIT 21.1% ± 18.7%. Predictive performance decreased at longer horizons. For hypotension prediction, one-minute-ahead GEE-estimated population-average sensitivity and specificity were 57.39% and 99.74%, respectively. During the observation window, in exploratory comparisons with matched nonconcurrent controls, ARX-guided patients had a shorter duration of hypotension (0.8 ± 1.9 vs 3.0 ± 3.8 minutes; P = .005) and a lower incidence of hypotension (25.0% vs 52.5%; P = .033), but a higher phenylephrine dose (1823 ± 659 vs 974 ± 328 µg; P = .001). Maternal nausea incidence was lower in the ARX group compared with matched nonconcurrent controls (5% vs 35%; P = .014), with similar neonatal outcomes.

Conclusions In this prospective pilot study, an ARX decision-support algorithm provided accurate 1-minute-ahead MAP forecasts and was associated with higher phenylephrine dosing and shorter maternal hypotension duration compared with matched nonconcurrent controls. These findings support further evaluation in larger, randomized trials.

Summary statement In this prospective pilot study of 20 patients undergoing cesarean delivery under spinal anesthesia, an autoregressive with exogenous input (ARX) decision-support algorithm provided real-time blood pressure forecasts and was associated with a shorter hypotension duration but higher phenylephrine dose compared with matched nonconcurrent controls. These preliminary data support further evaluation of ARX-guided, algorithmic vasopressor management in larger, multicenter trials.

Key Points

Question: In pregnant patients at term undergoing elective cesarean delivery under spinal anesthesia, can a real-time ARX algorithm accurately forecast MAP and support vasopressor management?

Findings: One-minute-ahead forecasts were accurate (RMSE 3.71 mmHg), and ARX-guided care was associated with a shorter duration of hypotension and a higher phenylephrine dose versus matched nonconcurrent controls

Meaning: Real-time MAP forecasting is feasible and warrants randomized evaluation to confirm clinical benefit and characterize trade-offs.

Competing Interest Statement

V.P.K. reports funding from the NIH/NHLBI grant 1K08HL161326-01A1, NIH Office of Data Science Strategy/Office of the NIH Director/Office of Research on Womens Health grant 1OT2OD038029-01 and Anesthesia Patient Safety Foundation (APSF). V.P.K. reports consulting fees from Avania CRO unrelated to the current work and patent #WO2021119593A1 for the control of a therapeutic delivery system assigned to Mass General Brigham. B.O. is currently an employee and shareholder of Insulet Corporation. Work performed on this study was independent of her employment with Insulet Corporation.

Funding Statement

Supported by the BWH IGNITE Award, the Womens Health Innovation Award from the Massachusetts Life Sciences Center, the Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Womens Hospital, and the UM1TR004408 award through Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health) with financial contributions from Harvard University and its affiliated academic healthcare centers.

Author Declarations

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Mass General Brigham Institutional Review Board, approval granted.

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Data Availability

In accordance with the Mass General Brigham Institutional Review Board requirements, the research data supporting this project may not be publicly shared.

AbbreviationsARXautoregressive with exogenous inputBMIbody mass indexFITfraction of improvement in total errorGEEgeneralized estimating equationsIRBInstitutional Review BoardIQRinterquartile rangeMAEmean absolute errorMAPmean arterial pressureNIBPnoninvasive blood pressureNICUneonatal intensive care unitNPVnegative predictive valuePPVpositive predictive valueRMSEroot mean square errorSDstandard deviationSMDstandardized mean difference