Intraoperative hypotension when using hypotension prediction index software during major noncardiac surgery: a European multicentre prospective observational registry (EU HYPROTECT)

A bundle to prevent postinduction hypotension in high-risk noncardiac surgery patients: the ZERO-HYPOTENSION single-arm interventional proof-of-concept study

Background

Postinduction hypotension is common and associated with organ injury but might be largely preventable by careful anaesthetic management. We thus aimed to quantify the severity and duration of postinduction hypotension in high-risk noncardiac surgery patients treated with a hypotension prevention bundle.

Methods

In this prospective single-arm interventional proof-of-concept study, 107 high-risk noncardiac surgery patients were treated with a hypotension prevention bundle. The bundle included continuous intra-arterial blood pressure monitoring, a hypotension alarm set at a mean arterial pressure (MAP) of 75 mm Hg, careful administration of anaesthetic drugs, and continuous administration of norepinephrine when MAP decreased below 75 mm Hg. The primary endpoint, AUC65, was derived from a plot of MAP over time for the first 15 min after induction of general anaesthesia as the area of the plot under a MAP of 65 mm Hg .

Results

Of 107 patients, 55 (51%) had at least one MAP reading <65 mm Hg, but only 16/107 patients (15%) had a MAP <65 mm Hg for at least one continuous minute. Patients had a MAP <65 mm Hg for a median (25% percentile, 75% percentile; minimum-maximum) of 0.2 min (0.0, 0.8; 0.0-5.2 min). The median AUC65 was 0.1 mm Hg . min (0.0, 4.1; 0.0-40.6 mm Hg min).

Conclusions

We observed minimal postinduction hypotension in high-risk noncardiac surgery patients treated with a hypotension prevention bundle. However, randomised trials are needed to confirm that using the hypotension prevention bundle helps reduce postinduction hypotension.

Perioperative goal-directed therapy with artificial intelligence to reduce the incidence of intraoperative hypotension and renal failure in patients undergoing lung surgery: A pilot study

STUDY OBJECTIVE

The aim of this study was to investigate whether goal-directed treatment using artificial intelligence, compared to standard care, can reduce the frequency, duration, and severity of intraoperative hypotension in patients undergoing single lung ventilation, with a potential reduction of postoperative acute kidney injury (AKI).

DESIGN

single center, single-blinded randomized controlled trial.

SETTING

University hospital operating room.

PATIENTS

150 patients undergoing lung surgery with single lung ventilation were included.

INTERVENTIONS

Patients were randomly assigned to two groups: the Intervention group, where a goal-directed therapy based on the Hypotension Prediction Index (HPI) was implemented; the Control group, without a specific hemodynamic protocol.

MEASUREMENTS

The primary outcome measures include the frequency, duration of intraoperative hypotension, furthermore the Area under MAP 65 and the time-weighted average (TWA) of MAP of 65. Other outcome parameters are the incidence of AKI and myocardial injury after non-cardiac surgery (MINS).

MAIN RESULTS

The number of hypotensive episodes was lower in the intervention group compared to the control group (0 [0-1] vs. 1 [0-2]; p = 0.01), the duration of hypotension was shorter in the intervention group (0 min [0-3.17] vs. 2.33 min [0-7.42]; p = 0.01). The area under the MAP of 65 (0 mmHg * min [0-12] vs. 10.67 mmHg * min [0-44.16]; p < 0.01) and the TWA of MAP of 65 (0 mmHg [0-0.08] vs. 0.07 mmHg [0-0.25]; p < 0.01) were lower in the intervention group. The incidence of postoperative AKI showed no differences between the groups (6.7 % vs.4.2 %; p = 0.72). There was a trend to lower incidence of MINS in the intervention group (17.1 % vs. 31.8 %; p = 0.07). A tendency towards reduced postoperative infection was seen in the intervention group (16.0 % vs. 26.8 %; p = 0.16).

CONCLUSIONS

The implementation of a treatment algorithm based on HPI allowed us to decrease the duration and severity of hypotension in patients undergoing lung surgery. It did not result in a significant reduction in the incidence of AKI, however we observed a tendency towards lower incidence of MINS in the intervention group, along with a slight reduction in postoperative infections.

Impact of Predictive Hemodynamic Monitoring on Intraoperative Hypotension and Postoperative Complications in Multi-level Spinal Fusion Surgery

STUDY DESIGN

Prospective longitudinal comparative cohort.

OBJECTIVES

To determine if the use of predictive hemodynamic monitoring (PHM) during elective multi-level posterior instrumented spine fusions decreases episodes of intraoperative hypotension (IOH) and complications.

BACKGROUND

A recent study showed an association between complications and duration of IOH in patients undergoing multi-level spine fusions. Whether the use of PHM to maintain hemodynamic stability intraoperatively decreases postoperative complications has not been evaluated.

METHODS

Adults undergoing elective multi-level posterior thoracolumbar fusion with arterial line blood pressure monitoring were identified and stratified into those in which predictive hemodynamic monitoring (PHM) was used and those in which it was not. Number of minutes of hypotension (MAP <65 mm Hg) and hypertension (MAP ≥100 mm Hg), volume of fluids, blood products and vasopressors administered intraoperatively and within the first 4 hours postoperatively as well as the number and type of postoperative complications were collected.

RESULTS

The 47 cases in the PHM group and 70 in the non-PHM group had similar demographic and operative characteristics. A shorter duration of IOH was seen in the PHM group (8.13 min) compared with the non-PHM group (13.28 min, P=0.029); and a shorter duration of intraoperative hypertension seen in the PHM group (0.46 min) compared with the non-PHM group (1.38 min, P=0.032). There was a smaller number of patients in the PHM group who had a surgical site infection (2.% vs. 13%, P=0.027), postoperative nausea and vomiting (0 vs. 14%, P=0.004) and postoperative cognitive dysfunction (6% vs. 19%, P=0.049) compared with the non-PHM group. There was also a statistically significant shorter length of hospitalization in the PHM (4.62 d) compared with the non-PHM group (5.99 d, P=0.017).

CONCLUSION

Predictive hemodynamic monitoring to manage intraoperative hemodynamic instability is associated with a shorter duration of intraoperative hypotension, a lower prevalence of complications, and a decreased hospital stay in multi-level spinal fusion surgery.

Electroconvulsive therapy generates a postictal wave of spreading depolarization in mice and humans

Electroconvulsive therapy (ECT) is a fast-acting, highly effective, and safe treatment for medication-resistant depression. Historically, the clinical benefits of ECT have been attributed to generating a controlled seizure; however, the underlying neurobiology is understudied and unresolved. Using optical neuroimaging of neural activity and hemodynamics in a mouse model of ECT, we demonstrated that a second brain event follows seizure: cortical spreading depolarization (CSD). We found that ECT pulse parameters and electrode configuration directly shaped the wave dynamics of seizure and subsequent CSD. To translate these findings to human patients, we used non-invasive diffuse optical monitoring of cerebral blood flow and oxygenation during routine ECT treatments. We observed that human brains reliably generate hyperemic waves after ECT seizure which are highly consistent with CSD. These results challenge a long-held assumption that seizure is the primary outcome of ECT and point to new opportunities for optimizing ECT stimulation parameters and treatment outcomes.

Implementation of an Evidence-based Protocol to Increase the Use of Goal-directed Hemodynamic Therapy

PURPOSE

This quality improvement project aimed to increase goal-directed hemodynamic therapy (GHDT) utilization in adult patients undergoing coronary artery bypass grafts (CABG) by implementing an evidence-based intraoperative GDHT protocol.

DESIGN

A quality improvement project.

METHODS

The team implemented a training bundle to raise awareness of complications associated with IOH, educate providers about GDHT benefits, and explain how to incorporate the protocol to guide intraoperative hemodynamic management. The team performed retrospective chart reviews to determine baseline and post-implementation GDHT protocol utilization and IOH incidence.

FINDINGS

After receiving the education and protocol implementation, anesthesia providers began using the GDHT monitors on 100% of CABG procedures at this facility. A total of 60 patient charts were reviewed. Average cumulative hypotensive time decreased by 16.8%, from 26.37 minutes to 21.93 minutes (P = .375, 95% CI [-5.49, 13.35]).

CONCLUSIONS

Although there was no significant reduction in IOH, the training bundle and team support increased anesthesia providers' interest in using GDHT monitors. This led to a significant rise in its utilization. A future project is planned to expand the GDHT monitors and protocol to the entire operating room. Post-anesthesia care and intensive care units desiring to increase GDHT use may benefit from similar projects.

Artificial intelligence in obstetric anaesthesiology - the future of patient care?

The use of artificial intelligence (AI) in obstetric anaesthesiology shows great potential in enhancing our practice and delivery of care. In this narrative review, we summarise the current applications of AI in four key areas of obstetric anaesthesiology (perioperative care, neuraxial procedures, labour analgesia and obstetric critical care), where AI has been employed to varying degrees for decision support, event prediction, risk stratification and procedural assistance. We also identify gaps in current practice and propose areas for further research. While promising, AI cannot replace the expertise and clinical judgement of a trained obstetric anaesthesiologist. It should, instead, be viewed as a valuable tool to facilitate and support our practice.

Intraoperative Hypotension Is an Important Modifiable Risk Factor for Major Complications in Spinal Fusion Surgery

STUDY DESIGN

Retrospective observational cohort.

OBJECTIVES

This study explores the impact of Intraoperative hypotension (IOH) on postoperative complications for major thoracolumbar spine fusion procedures.

SUMMARY OF BACKGROUND DATA

IOH with mean arterial pressure (MAP) <65 mm Hg is associated with postoperative acute kidney injury (AKI) in general surgery. In spinal deformity surgery, IOH is a contributing factor to MEP changes and spinal cord dysfunction with deformity correction.

METHODS

A total of 539 thoracolumbar fusion cases, more than six surgical levels and >3 hours duration, were identified. Anesthetic/surgical data included OR time, fluid volume, blood loss, blood product replacement and use of vasopressors. Arterial-line based MAP data was collected at 1-minute intervals. Cummulative duration of MAP <65 mm Hg was recorded. IOH within the first hour of surgery vs. the entire case was determined. Post-op course and complications including SSI, GI complications, pulmonary complications, MI, DVT, PE, AKI, and encephalopathy were noted. Cumulative complications were grouped as none, one to two complications, or more than three complications.

RESULTS

There was a significant association between occurrence of complications and duration of IOH within the first hour of surgery (8.2 vs . 5.6 min, P <0.001) and across the entire procedure (28.1 vs . 19.3 min, P =0.008). This association persisted for individual major complications including SSI, acute respiratory failure, PE, ileus requiring NGT, and postoperative cognitive dysfunction. Comparison of patients with zero versus one to two versus three or more complications demonstrated that patients with three or more complications had a longer duration of IOH in the first hour of the surgery and that patients who had no complications received less vasopressor than patients who had one to two or three or more complications.

CONCLUSION

This study identifies duration of IOH during the first hour of surgery as a previously unrecognized modifiable risk associated with major complications for multilevel lumbar fusion surgery.

LEVEL OF EVIDENCE

III.

Association of intraoperative hypotension and cumulative norepinephrine dose with postoperative acute kidney injury in patients having noncardiac surgery: a retrospective cohort analysis

BACKGROUND

Intraoperative hypotension is associated with acute kidney injury (AKI). Clinicians thus frequently use vasopressors, such as norepinephrine, to maintain blood pressure. However, vasopressors themselves might promote AKI. We sought to determine whether both intraoperative hypotension and cumulative intraoperative norepinephrine dose are independently associated with postoperative AKI in patients undergoing noncardiac surgery.

METHODS

This was a retrospective cohort analysis of 38 338 adult male and female patients who had noncardiac surgery. The primary outcome was AKI within the first 7 postoperative days. We performed adjusted multivariable logistic regression analysis to determine whether intraoperative hypotension (quantified as area under a mean arterial pressure [MAP] of 65 mm Hg) and cumulative intraoperative norepinephrine dose were independently associated with AKI.

RESULTS

The median (25th percentile, 75th percentile) area under a MAP of 65 mm Hg was 0.09 (0.02, 0.22) mm Hg∗day in patients with AKI and 0.05 (0.01, 0.14) mm Hg∗day in patients without AKI (P<0.001). The cumulative intraoperative norepinephrine dose was 1.92 (0.00, 13.09) μg kg-1 in patients with AKI and 0.00 (0.00, 0.00) μg kg-1 in patients without AKI (P<0.001). Both the area under a MAP of 65 mm Hg (odds ratio 1.55 [95% confidence interval 1.17-2.02] per mm Hg∗day; P=0.002) and the cumulative intraoperative norepinephrine dose (odds ratio 1.02 [95% confidence interval 1.01-1.02] per μg kg-1; P<0.001) were independently associated with AKI.

CONCLUSIONS

Both intraoperative hypotension and cumulative intraoperative norepinephrine dose were independently associated with postoperative AKI in patients undergoing noncardiac surgery. Pending results of trials testing whether these relationships are causal, it seems prudent to avoid both profound hypotension and high norepinephrine doses in adults undergoing noncardiac surgery.

Mitigating Intraoperative Hypotension: A Review and Update on Recent Advances

Intraoperative hypotension (IOH) is a common occurrence during anesthesia administration for various surgical procedures and is linked to postoperative adverse outcomes. Factors contributing to IOH include hypovolemia, vasodilation, and impaired contractility, often combined with patient comorbidities. Strategies for mitigating IOH have been developed and are continually being updated with new research and technological advancements. These strategies include personalized blood pressure thresholds, pharmacologic measures, and the use of predictive tools. However, the management of IOH also requires careful consideration of patient-specific comorbidities and the use of appropriate treatment options.

Intraoperative Hypotension Prediction: Current Methods, Controversies, and Research Outlook

Intraoperative hypotension prediction has been increasingly emphasized due to its potential clinical value in reducing organ injury and the broad availability of large-scale patient datasets and powerful machine learning tools. Hypotension prediction methods can mitigate low blood pressure exposure time. However, they have yet to be convincingly demonstrated to improve objective outcomes; furthermore, they have recently become controversial. This review presents the current state of intraoperative hypotension prediction and makes recommendations on future research. We begin by overviewing the current hypotension prediction methods, which generally rely on the prevailing mean arterial pressure as one of the important input variables and typically show good sensitivity and specificity but low positive predictive value in forecasting near-term acute hypotensive events. We make specific suggestions on improving the definition of acute hypotensive events and evaluating hypotension prediction methods, along with general proposals on extending the methods to predict reduced blood flow and treatment effects. We present a start of a risk-benefit analysis of hypotension prediction methods in clinical practice. We conclude by coalescing this analysis with the current evidence to offer an outlook on prediction methods for intraoperative hypotension. A shift in research toward tailoring hypotension prediction methods to individual patients and pursuing methods to predict appropriate treatment in response to hypotension appear most promising to improve outcomes.

Hypotension Prediction Index Is Equally Effective in Predicting Intraoperative Hypotension during Noncardiac Surgery Compared to a Mean Arterial Pressure Threshold: A Prospective Observational Study

BACKGROUND

The Hypotension Prediction Index is designed to predict intraoperative hypotension in a timely manner and is based on arterial waveform analysis using machine learning. It has recently been suggested that this algorithm is highly correlated with the mean arterial pressure itself. Therefore, the aim of this study was to compare the index with mean arterial pressure-based prediction methods, and it is hypothesized that their ability to predict hypotension is comparable.

METHODS

In this observational study, the Hypotension Prediction Index was used in addition to routine intraoperative monitoring during moderate- to high-risk elective noncardiac surgery. The agreement in time between the default Hypotension Prediction Index alarm (greater than 85) and different concurrent mean arterial pressure thresholds was evaluated. Additionally, the predictive performance of the index and different mean arterial pressure-based methods were assessed within 5, 10, and 15 min before hypotension occurred.

RESULTS

A total of 100 patients were included. A mean arterial pressure threshold of 73 mmHg agreed 97% of the time with the default index alarm, whereas a mean arterial pressure threshold of 72 mmHg had the most comparable predictive performance. The areas under the receiver operating characteristic curve of the Hypotension Prediction Index (0.89 [0.88 to 0.89]) and concurrent mean arterial pressure (0.88 [0.88 to 0.89]) were almost identical for predicting hypotension within 5 min, outperforming both linearly extrapolated mean arterial pressure (0.85 [0.84 to 0.85]) and delta mean arterial pressure (0.66 [0.65 to 0.67]). The positive predictive value was 31.9 (31.3 to 32.6)% for the default index alarm and 32.9 (32.2 to 33.6)% for a mean arterial pressure threshold of 72 mmHg.

CONCLUSIONS

In clinical practice, the Hypotension Prediction Index alarms are highly similar to those derived from mean arterial pressure, which implies that the machine learning algorithm could be substituted by an alarm based on a mean arterial pressure threshold set at 72 or 73 mmHg. Further research on intraoperative hypotension prediction should therefore include comparison with mean arterial pressure-based alarms and related effects on patient outcome.

EDITOR’S PERSPECTIVE

Predictive ability of hypotension prediction index and machine learning methods in intraoperative hypotension: a systematic review and meta-analysis

INTRODUCTION

Intraoperative Hypotension (IOH) poses a substantial risk during surgical procedures. The integration of Artificial Intelligence (AI) in predicting IOH holds promise for enhancing detection capabilities, providing an opportunity to improve patient outcomes. This systematic review and meta analysis explores the intersection of AI and IOH prediction, addressing the crucial need for effective monitoring in surgical settings.

METHOD

A search of Pubmed, Scopus, Web of Science, and Embase was conducted. Screening involved two-phase assessments by independent reviewers, ensuring adherence to predefined PICOS criteria. Included studies focused on AI models predicting IOH in any type of surgery. Due to the high number of studies evaluating the hypotension prediction index (HPI), we conducted two sets of meta-analyses: one involving the HPI studies and one including non-HPI studies. In the HPI studies the following outcomes were analyzed: cumulative duration of IOH per patient, time weighted average of mean arterial pressure < 65 (TWA-MAP < 65), area under the threshold of mean arterial pressure (AUT-MAP), and area under the receiver operating characteristics curve (AUROC). In the non-HPI studies, we examined the pooled AUROC of all AI models other than HPI.

RESULTS

43 studies were included in this review. Studies showed significant reduction in IOH duration, TWA-MAP < 65 mmHg, and AUT-MAP < 65 mmHg in groups where HPI was used. AUROC for HPI algorithms demonstrated strong predictive performance (AUROC = 0.89, 95CI). Non-HPI models had a pooled AUROC of 0.79 (95CI: 0.74, 0.83).

CONCLUSION

HPI demonstrated excellent ability to predict hypotensive episodes and hence reduce the duration of hypotension. Other AI models, particularly those based on deep learning methods, also indicated a great ability to predict IOH, while their capacity to reduce IOH-related indices such as duration remains unclear.

PeriOperative Quality Initiative (POQI) international consensus statement on perioperative arterial pressure management

Arterial pressure monitoring and management are mainstays of haemodynamic therapy in patients having surgery. This article presents updated consensus statements and recommendations on perioperative arterial pressure management developed during the 11th POQI PeriOperative Quality Initiative (POQI) consensus conference held in London, UK, on June 4-6, 2023, which included a diverse group of international experts. Based on a modified Delphi approach, we recommend keeping intraoperative mean arterial pressure ≥60 mm Hg in at-risk patients. We further recommend increasing mean arterial pressure targets when venous or compartment pressures are elevated and treating hypotension based on presumed underlying causes. When intraoperative hypertension is treated, we recommend doing so carefully to avoid hypotension. Clinicians should consider continuous intraoperative arterial pressure monitoring as it can help reduce the severity and duration of hypotension compared to intermittent arterial pressure monitoring. Postoperative hypotension is often unrecognised and might be more important than intraoperative hypotension because it is often prolonged and untreated. Future research should focus on identifying patient-specific and organ-specific hypotension harm thresholds and optimal treatment strategies for intraoperative hypotension including choice of vasopressors. Research is also needed to guide monitoring and management strategies for recognising, preventing, and treating postoperative hypotension.

Artificial intelligence and nonoperating room anesthesia

PURPOSE OF REVIEW

The integration of artificial intelligence (AI) in nonoperating room anesthesia (NORA) represents a timely and significant advancement. As the demand for NORA services expands, the application of AI is poised to improve patient selection, perioperative care, and anesthesia delivery. This review examines AI's growing impact on NORA and how it can optimize our clinical practice in the near future.

RECENT FINDINGS

AI has already improved various aspects of anesthesia, including preoperative assessment, intraoperative management, and postoperative care. Studies highlight AI's role in patient risk stratification, real-time decision support, and predictive modeling for patient outcomes. Notably, AI applications can be used to target patients at risk of complications, alert clinicians to the upcoming occurrence of an intraoperative adverse event such as hypotension or hypoxemia, or predict their tolerance of anesthesia after the procedure. Despite these advances, challenges persist, including ethical considerations, algorithmic bias, data security, and the need for transparent decision-making processes within AI systems.

SUMMARY

The findings underscore the substantial benefits of AI in NORA, which include improved safety, efficiency, and personalized care. AI's predictive capabilities in assessing hypoxemia risk and other perioperative events, have demonstrated potential to exceed human prognostic accuracy. The implications of these findings advocate for a careful yet progressive adoption of AI in clinical practice, encouraging the development of robust ethical guidelines, continual professional training, and comprehensive data management strategies. Furthermore, AI's role in anesthesia underscores the need for multidisciplinary research to address the limitations and fully leverage AI's capabilities for patient-centered anesthesia care.

Haemodynamic monitoring during noncardiac surgery: past, present, and future

During surgery, various haemodynamic variables are monitored and optimised to maintain organ perfusion pressure and oxygen delivery - and to eventually improve outcomes. Important haemodynamic variables that provide an understanding of most pathophysiologic haemodynamic conditions during surgery include heart rate, arterial pressure, central venous pressure, pulse pressure variation/stroke volume variation, stroke volume, and cardiac output. A basic physiologic and pathophysiologic understanding of these haemodynamic variables and the corresponding monitoring methods is essential. We therefore revisit the pathophysiologic rationale for intraoperative monitoring of haemodynamic variables, describe the history, current use, and future technological developments of monitoring methods, and finally briefly summarise the evidence that haemodynamic management can improve patient-centred outcomes.

Closed-loop anesthesia: foundations and applications in contemporary perioperative medicine

A closed-loop automatically controls a variable using the principle of feedback. Automation within anesthesia typically aims to improve the stability of a controlled variable and reduce workload associated with simple repetitive tasks. This approach attempts to limit errors due to distractions or fatigue while simultaneously increasing compliance to evidence based perioperative protocols. The ultimate goal is to use these advantages over manual care to improve patient outcome. For more than twenty years, clinical studies in anesthesia have demonstrated the superiority of closed-loop systems compared to manual control for stabilizing a single variable, reducing practitioner workload, and safely administering therapies. This research has focused on various closed-loops that coupled inputs and outputs such as the processed electroencephalogram with propofol, blood pressure with vasopressors, and dynamic predictors of fluid responsiveness with fluid therapy. Recently, multiple simultaneous independent closed-loop systems have been tested in practice and one study has demonstrated a clinical benefit on postoperative cognitive dysfunction. Despite their advantages, these tools still require that a well-trained practitioner maintains situation awareness, understands how closed-loop systems react to each variable, and is ready to retake control if the closed-loop systems fail. In the future, multiple input multiple output closed-loop systems will control anesthetic, fluid and vasopressor titration and may perhaps integrate other key systems, such as the anesthesia machine. Human supervision will nonetheless always be indispensable as situation awareness, communication, and prediction of events remain irreplaceable human factors.

Impact of clinicians' behavior, an educational intervention with mandated blood pressure and the hypotension prediction index software on intraoperative hypotension: a mixed methods study

PURPOSE

Intraoperative hypotension (IOH) is associated with adverse outcomes. We therefore explored beliefs regarding IOH and barriers to its treatment. Secondarily, we assessed if an educational intervention and mandated mean arterial pressure (MAP), or the implementation of the Hypotension Prediction Index-software (HPI) were associated with a reduction in IOH.

METHODS

Structured interviews (n = 27) and questionnaires (n = 84) were conducted to explore clinicians' beliefs and barriers to IOH treatment, in addition to usefulness of HPI questionnaires (n = 14). 150 elective major surgical patients who required invasive blood pressure monitoring were included in three cohorts to assess incidence and time-weighted average (TWA) of hypotension (MAP < 65 mmHg). Cohort one received standard care (baseline), the clinicians of cohort two had a training on hypotension and a mandated MAP > 65 mmHg, and patients of the third cohort received protocolized care using the HPI.

RESULTS

Clinicians felt challenged to manage IOH in some patients, yet they reported sufficient knowledge and skills. HPI-software was considered useful and beneficial. No difference was found in incidence of IOH between cohorts. TWA was comparable between baseline and education cohort (0.15 mmHg [0.05-0.41] vs. 0.11 mmHg [0.02-0.37]), but was significantly lower in the HPI cohort (0.04 mmHg [0.00 to 0.11], p < 0.05 compared to both).

CONCLUSIONS

Clinicians believed they had sufficient knowledge and skills, which could explain why no difference was found after the educational intervention. In the HPI cohort, IOH was significantly reduced compared to baseline, therefore HPI-software may help prevent IOH.

TRIAL REGISTRATION

ISRCTN 17,085,700 on May 9th, 2019.

Individualized Perioperative Hemodynamic Management Using Hypotension Prediction Index Software and the Dynamics of Troponin and NTproBNP Concentration Changes in Patients Undergoing Oncological Abdominal Surgery

INTRODUCTION

Abdominal oncologic surgeries pose significant risks due to the complexity of the surgery and patients' often weakened health, multiple comorbidities, and increased perioperative hazards. Hypotension is a major risk factor for perioperative cardiovascular complications, necessitating individualized management in modern anesthesiology.

AIM

This study aimed to determine the dynamics of changes in troponin and NTproBNP levels during the first two postoperative days in patients undergoing major cancer abdominal surgery with advanced hemodynamic monitoring including The AcumenTM Hypotension Prediction Index software (HPI) (Edwards Lifesciences, Irvine, CA, USA) and their association with the occurrence of postoperative cardiovascular complications.

METHODS

A prospective study was conducted, including 50 patients scheduled for abdominal cancer surgery who, due to the overall risk of perioperative complications (ASA class 3 or 4), were monitored using the HPI software. Hypotension was qualified as at least one ≥ 1 min episode of a MAP < 65 mm Hg. Preoperatively and 24 and 48 h after the procedure, the levels of NTproBNP and troponin were measured, and an ECG was performed.

RESULTS

We analyzed data from 46 patients and found that 82% experienced at least one episode of low blood pressure (MAP < 65 mmHg). However, the quality indices of hypotension were low, with a median time-weighted average MAP < 65 mmHg of 0.085 (0.03-0.19) mmHg and a median of 2 (2-1.17) minutes spent below MAP < 65 mmHg. Although the incidence of perioperative myocardial injury was 10%, there was no evidence to suggest a relationship with hypotension. Acute kidney injury was seen in 23.9% of patients, and it was significantly associated with a number of episodes of MAP < 50 mmHg. Levels of NTproBNP were significantly higher on the first postoperative day compared to preoperative values (285.8 [IQR: 679.8] vs. 183.9 [IQR: 428.1] pg/mL, p < 0.001). However, they decreased on the second day (276.65 [IQR: 609.4] pg/mL, p = 0.154). The dynamics of NTproBNP were similar for patients with and without heart failure, although those with heart failure had significantly higher preoperative concentrations (435.9 [IQR: 711.15] vs. 87 [IQR: 232.2] pg/mL, p < 0.001). Patients undergoing laparoscopic surgery showed a statistically significant increase in NTproBNP.

CONCLUSIONS

This study suggests that advanced HPI monitoring in abdominal cancer surgery effectively minimizes intraoperative hypotension with no significant NTproBNP or troponin perioperative dynamics, irrespective of preoperative heart failure.

Role of artificial intelligence in haemodynamic monitoring

This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWSTM and CircEWS-lite TM showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety.

Personalized Predictive Hemodynamic Management for Gynecologic Oncologic Surgery: Feasibility of Cost-Benefit Derivatives of Digital Medical Devices

BACKGROUND

Intraoperative hypotension is associated with increased perioperative complications, hospital length of stay (LOS) and healthcare expenditure in gynecologic surgery. We tested the hypothesis that the adoption of a machine learning-based warning algorithm (hypotension prediction index-HPI) might yield an economic advantage, with a reduction in adverse outcomes that outweighs the costs for its implementation as a medical device.

METHODS

A retrospective-matched cohort cost-benefit Italian study in gynecologic surgery was conducted. Sixty-six female patients treated with standard goal-directed therapy (GDT) were matched in a 2:1 ratio with thirty-three patients treated with HPI based on ASA status, diagnosis, procedure, surgical duration and age.

RESULTS

The most relevant contributor to medical costs was operating room occupation (46%), followed by hospital stay (30%) and medical devices (15%). Patients in the HPI group had EURO 300 greater outlay for medical devices without major differences in total costs (GDT 5425 (3505, 8127), HPI 5227 (4201, 7023) p = 0.697). A pre-specified subgroup analysis of 50% of patients undergoing laparotomic surgery showed similar medical device costs and total costs, with a non-significant saving of EUR 1000 in the HPI group (GDT 8005 (5961, 9679), HPI 7023 (5227, 11,438), p = 0.945). The hospital LOS and intensive care unit stay were similar in the cohorts and subgroups.

CONCLUSIONS

Implementation of HPI is associated with a scenario of cost neutrality, with possible economic advantage in high-risk settings.

Hypotension Prediction Index and Incidence of Perioperative Hypotension: A Single-Center Propensity-Score-Matched Analysis

(1) Background: Intraoperative hypotension is common and is associated with increased morbidity and mortality. The Hypotension Prediction Index (HPI) is an advancement of arterial waveform analysis and allows preventive treatments. We used a propensity-score-matched study design to test whether application of the HPI reduces hypotensive events in non-cardiac surgery patients; (2) Methods: 769 patients were selected for propensity score matching. After matching, both HPI and non-HPI groups together comprised n = 136 patients. A goal-directed treatment protocol was applied in both groups. The primary endpoint was the incidence and duration of hypotensive events defined as MAP < 65 mmHg, evaluated by the time-weighted average (TWA) of hypotension. (3) Results: The median TWA of hypotension below 65 mmHg in the matched cohort was 0.180 mmHg (IQR 0.060, 0.410) in the non-HPI group vs. 0.070 mmHg (IQR 0.020, 0.240) in the HPI group (p < 0.001). TWA was higher in patients with ASA classification III/IV (0.170 mmHg; IQR 0.035, 0.365) than in patients with ASA status II (0.100; IQR 0.020, 0.250; p = 0.02). Stratification by intervention group showed no differences in the HPI group while TWA values in the non-HPI group were more than twice as high in patients with ASA status III/IV (p = 0.01); (4) Conclusions: HPI reduces intraoperative hypotension in a matched cohort seen for TWA below 65 mmHg and relative time in hypotension. In addition, non-HPI patients with ASA status III/IV showed a higher TWA compared with HPI-patients, indicating an advantageous effect of using HPI in patients at higher risk.