OBJECTIVES: Cardiac surgery is associated with perioperative complications, some of which might be attributable to hypotension. The Hypotension Prediction Index (HPI), a machine-learning-derived early warning tool for hypotension, has only been evaluated in noncardiac surgery. We investigated whether using HPI with diagnostic guidance reduced hypotension during cardiac surgery and in the ICU. DESIGN: Randomized clinical trial conducted between May 2021 and February 2023. SETTING: Single-center study conducted in an academic hospital in the Netherlands. PATIENTS: Adults undergoing elective on-pump coronary artery bypass grafting, with or without single heart valve surgery, were enrolled if a mean arterial pressure (MAP) greater than or equal to 65 mm Hg was targeted during the surgical off-pump phases and ICU stay. After eligibility assessment, 142 of 162 patients approached gave informed consent for participation. INTERVENTIONS: Patients randomized 1:1 received either diagnostic guidance in addition to standard care if HPI reached greater than or equal to 75 (n = 72) or standard care alone (n = 70). MEASUREMENTS AND MAIN RESULTS: The primary outcome was the severity of hypotension, measured as time-weighted average (TWA) of MAP less than 65 mm Hg. Secondary outcomes encompassed hypertension severity and intervention disparities. Of 142 patients randomized, 130 were included in the primary analysis. The HPI group showed 63% reduction in median TWA of hypotension compared with the standard care group, with a median of differences of –0.40 mm Hg (95% CI, –0.65 to –0.27; p < 0.001). In the HPI group, patients spent a median 28 minutes (95% CI, 17–44 min) less in hypotension, with a measurement duration of 322 minutes in the HPI group and 333 minutes in the standard care group. No significant differences were observed in hypertension severity, treatment choice, or fluid, vasopressors, and inotrope amounts. CONCLUSIONS: Using HPI combined with diagnostic guidance on top of standard care significantly decreased hypotension severity in elective cardiac surgery patients compared with standard care.

BACKGROUND: The hypotension prediction index (HPI) predicts hypotension, with randomised trials showing a significant reduction in hypotension-related metrics. However, the reliability of previous validation studies is debated, and it's unclear if mean arterial pressure (MAP) can be used interchangeably with HPI. OBJECTIVES: This study compared the effectiveness of HPI versus MAP thresholds in predicting intraoperative hypotension, focusing on three clinically relevant metrics: time from alert to event, positive predictive value (PPV), and proportion of missed hypotensive events. DESIGN: Prospective observational study conducted between 2018 and 2020. SETTING: Single-centre, academic hospital in the Netherlands. PARTICIPANTS: Adults scheduled for elective non-cardiac surgery lasting over two hours. Of the 105 eligible patients, 91 had sufficient data for analysis. MAIN OUTCOME MEASURES: The primary outcome was the time-to-hypotensive event intervals predicted by HPI popup alerts (≥85 for ≥40 s) and MAP-alerts (70–75 mmHg). Secondary analyses examined differences between these predictors regarding the PPV and missed event rates, as well as the difference in these metrics between instant HPI-85 alerts and the six MAP-alerts. RESULTS: The largest time-to-event difference was seen between HPI-85 popup and MAP-70 alerts, with a gain of 0.58 (95% confidence interval (CI), 0.57 to 0.58) min, favouring HPI. Higher MAP thresholds reduced this time difference, but worsened PPV values, with 20.5 (95% CI, 20.3 to 20.6)% at MAP-75 compared to 55.6 (95% CI, 55.4 to 55.8)% for HPI-85 popups. Missed event proportions were similar: between one to three percent. Instant HPI-85 and MAP-72 alerts showed comparable performance, but both had suboptimal PPV values around 30%. However, adding a 40-s time-dependence to MAP's alert definition levelled the differences across the three evaluated metrics, aligning more closely with HPI-85 popup alerts. CONCLUSIONS: Using HPI-85 popup alerts does not provide additional prediction time over MAP-alerts in the 70 to 75 mmHg range, but they may be preferred due to higher PPV values. Instant HPI-85 and MAP-alerts perform similarly, with MAP-72 being closest, though these alerts more frequently occur regardless of subsequent hypotension with the potential to introduce unnecessary treatment. Adding a 40-s time-dependence to MAP-alerts to match the HPI popup characteristic eliminates distinctions between prediction time and missed events, while maintaining the higher PPV. However, whether 40sec-MAP-alerts are clinically equivalent remains to be determined in prospective clinical trials. TRIAL REGISTRATION: Clinicaltrials.gov NCT03795831 on 10 January 2019.

Introduction Hypotension is common during cardiac surgery and often persists postoperatively in the intensive care unit (ICU). Still, treatment is mainly reactive, causing a delay in its management. The Hypotension Prediction Index (HPI) can predict hypotension with high accuracy. Using the HPI combined with a guidance protocol resulted in a significant reduction in the severity of hypotension in four non-cardiac surgery trials. This randomised trial aims to evaluate the effectiveness of the HPI in combination with a diagnostic guidance protocol on reducing the occurrence and severity of hypotension during coronary artery bypass grafting (CABG) surgery and subsequent ICU admission. Methods and analysis This is a single-centre, randomised clinical trial in adult patients undergoing elective on-pump CABG surgery with a target mean arterial pressure of 65 mm Hg. One hundred and thirty patients will be randomly allocated in a 1:1 ratio to either the intervention or control group. In both groups, a HemoSphere patient monitor with embedded HPI software will be connected to the arterial line. In the intervention group, HPI values of 75 or above will initiate the diagnostic guidance protocol, both intraoperatively and postoperatively in the ICU during mechanical ventilation. In the control group, the HemoSphere patient monitor will be covered and silenced. The primary outcome is the time-weighted average of hypotension during the combined study phases. Ethics and dissemination The medical research ethics committee and the institutional review board of the Amsterdam UMC, location AMC, the Netherlands, approved the trial protocol (NL76236.018.21). No publication restrictions apply, and the study results will be disseminated through a peer-reviewed journal. Trial registration number The Netherlands Trial Register (NL9449), ClinicalTrials.gov (NCT05821647).

Background: Hypotension is common in the post-anesthesia care unit (PACU) and intensive care unit (ICU), and is associated with adverse patient outcomes. The Hypotension Prediction Index (HPI) algorithm has been shown to accurately predict hypotension in mechanically ventilated patients in the OR and ICU and to reduce intraoperative hypotension (IOH). Since positive pressure ventilation significantly affects patient hemodynamics, we performed this validation study to examine the performance of the HPI algorithm in a non-ventilated PACU and ICU population. Materials & Methods: The performance of the HPI algorithm was assessed using prospectively collected blood pressure (BP) and HPI data from a PACU and a mixed ICU population. Recordings with sufficient time (≥3 h) spent without mechanical ventilation were selected using data from the electronic medical record. All HPI values were evaluated for sensitivity, specificity, predictive value, and time-to-event, and a receiver operating characteristic (ROC) curve was constructed. Results: BP and HPI data from 282 patients were eligible for analysis, of which 242 (86%) were ICU patients. The mean age (standard deviation) was 63 (13.5) years, and 186 (66%) of the patients were male. Overall, the HPI predicted hypotension accurately, with an area under the ROC curve of 0.94. The most used HPI threshold cutoff in research and clinical use, 85, showed a sensitivity of 1.00, specificity of 0.79, median time-to-event of 160 s [60–380], PPV of 0.85, and NPV of 1.00. Conclusion: The absence of positive pressure ventilation and the influence thereof on patient hemodynamics does not negatively affect the performance of the HPI algorithm in predicting hypotension in the PACU and ICU. Future research should evaluate the feasibility and influence on hypotension and outcomes following HPI implementation in non-ventilated patients at risk of hypotension.

Hypotension is a common and clinically significant issue in the intensive care unit (ICU), associated with increased morbidity and mortality. ICU nurses play a central role in its detection and initial management, yet their ability to act autonomously might be limited. Insights into their knowledge and perspectives regarding nurse-driven hypotension treatment are currently lacking. The aim of this study was to assess ICU nurses' knowledge and current practices in hypotension management and to identify perceived barriers to the implementation of nurse-driven hypotension management protocols. A single-centre, cross-sectional survey was conducted among ICU nurses at the Amsterdam University Medical Center between February and May 2021. A convenience sampling approach was used, inviting all eligible nurses attending a scheduled annual education day to participate. The questionnaire assessed knowledge, clinical practices, and attitudes towards nurse-driven hypotension management. Descriptive statistics were used for quantitative data; open-ended responses were analysed qualitatively using content analysis by two independent researchers. The response rate was 99% (140/142). Nurses reported encountering hypotension in 55.1% of ICU shifts. Over 80% supported nurse-led treatment, and 68.6% reported already initiating treatment independently in 70% of hypotensive events. Knowledge assessments showed high item-level correctness (>80%) in treatment-related questions. However, lower scores were observed in the interpretation of more complex haemodynamic cases, with correct response rates ranging between 36.4% and 48.1%. The most important perceived barrier to implement a nurse-driven protocol was potential uncertainty about patient inclusion and exclusion criteria. ICU nurses frequently manage hypotension independently and support nurse-driven protocols. Knowledge gaps, particularly in complex haemodynamic reasoning, highlight the need for structured education and clear, evidence-based protocols to ensure safe and effective nurse-driven interventions in high-acuity ICU settings.