Proactive Management of Intraoperative Hypotension Reduces Biomarkers of Organ Injury and Oxidative Stress during Elective Non-Cardiac Surgery: A Pilot Randomized Controlled Trial

Intraoperative Hypotension in Patients Having Major Noncardiac Surgery Under General Anesthesia: A Systematic Review of Blood Pressure Optimization Strategies

INTRODUCTION

Intraoperative hypotension is associated with increased risks of postoperative complications. Consequently, a variety of blood pressure optimization strategies have been tested to prevent or promptly treat intraoperative hypotension. We performed a systematic review to summarize randomized controlled trials that evaluated the efficacy of blood pressure optimization interventions in either mitigating exposure to intraoperative hypotension or reducing risks of postoperative complications.

METHODS

Medline, Embase, PubMed, and Cochrane Controlled Register of Trials were searched from database inception to August 2, 2023, for randomized controlled trials (without language restriction) that evaluated the impact of any blood pressure optimization intervention on intraoperative hypotension and/or postoperative outcomes.

RESULTS

The review included 48 studies (N = 46,377), which evaluated 10 classes of blood pressure optimization interventions. Commonly assessed interventions included hemodynamic protocols using arterial waveform analysis, preoperative withholding of antihypertensive medications, continuous blood pressure monitoring, and adjuvant agents (vasopressors, anticholinergics, anticonvulsants). These same interventions reduced intraoperative exposure to hypotension. Conversely, low blood pressure alarms had an inconsistent impact on exposure to hypotension. Aside from limited evidence that higher prespecified intraoperative blood pressure targets led to a reduced risk of complications, there were few data suggesting that these interventions prevented postoperative complications. Heterogeneity in interventions and outcomes precluded meta-analysis.

CONCLUSIONS

Several different blood pressure optimization interventions show promise in reducing exposure to intraoperative hypotension. Nonetheless, the impact of these interventions on clinical outcomes remains unclear. Future trials should assess promising interventions in samples sufficiently large to identify clinically plausible treatment effects on important outcomes.

The hypotension prediction index versus mean arterial pressure in predicting intraoperative hypotension: A clinical perspective

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.

Effectiveness of hypotension prediction index software in reducing intraoperative hypotension in prolonged prone-position spine surgery: a single-center clinical trial

Intraoperative hypotension (IOH) is associated with morbidity and mortality. The Hypotension Prediction Index (HPI), a machine learning-based tool, offers the opportunity for a proactive approach by predicting hypotensive events. This single center, single blind randomized clinical trial aimed to evaluate the hypothesis that an HPI software-guided approach to IOH management during prone position spine surgery could reduce its incidence compared to our standard care practices. 85 adult patients undergoing spine fusion surgery in the prone position were enrolled. Patients were randomized with a 1:1 allocation ratio. Participants were blinded to their group allocation. In the intervention group, the HPI software was actively used to guide IOH management. In the control group, HPI software readings were blinded, and standard care was administered. The primary outcome was the comparison of time-weighted average (TWA) of IOH between the two groups. Secondary outcomes included a comparison of the incidence of postoperative in-hospital events related to IOH between groups. 77 patients were included in the final analysis (39 in the intervention group), as 8 patients were excluded due to technical issues. No statistically significant difference was found between the intervention and control groups in the TWA of IOH (0.10 mmHg [0.05, 0.23] vs. 0.15 mmHg [0.09, 0.37], p-value 0.088). However, the total duration of hypotensive events per patient was significantly lower in the intervention group (4 min [0.5, 12.2] vs. 11.2 min [2.6, 20.1]; p-value 0.019). Postoperative complication rates did not differ significantly between the two groups. HPI-guided management did not significantly reduce the TWA of IOH compared to standard care in patients undergoing prone-position spine surgery. Complication rates were similar between the two groups.Clinical Trial Registration: This trial was registered with ClinicalTrials.gov (registration number: NCT05341167).

The hypotension prediction index in major abdominal surgery - A prospective randomised clinical trial protocol

Background

Patients undergoing major abdominal surgery are at increased risk of developing perioperative hypotension, which is associated with increased mortality and morbidity. Despite using advanced technologies such as evaluating arterial pressure derived cardiac output, anaesthetic management to maintain hemodynamic stability is still reactive when the clinical decision is made after hypotension has developed. Previous perioperative goal-directed studies have not proven the benefits of this approach with high certainty. A new, approved technology called the Hypotension Prediction Index (HPI) aims to prevent hypotension occurrence by allowing the precise hemodynamic monitoring of patients under general anaesthesia, significantly reducing intraoperative hypotension events. This prospective randomised clinical trial aims to compare the rate of perioperative hypotension in patients undergoing major abdominal surgery according to their type of hemodynamic monitoring.

Methods

and Analysis: Patients meeting the inclusion criteria will be randomly assigned to receive hemodynamic assessment with arterial pressure cardiac output (APCO) monitoring (group A) or hemodynamic monitoring with the HPI software (group B). The primary outcome is a time-weighted average (TWA) mean arterial pressure (MAP) of <65 mmHg: TWA MAP = (depth of hypotension [in mmHg] below a MAP of 65 mmHg × time [in minutes] spent below a MAP of 65 mmHg)/total duration of the operation (in minutes). Its secondary outcomes include perioperative hemodynamic management and the rate of postoperative complications.

Ethics and dissemination

This trial was approved by the Ethics Committee of the Poznan University of Medical Sciences (KB-559/220; date: 01/07/2022). Its results will be submitted for publication in a peer-reviewed journal.

Trial registration number

NCT06247384.

Effect of a Machine Learning-Derived Early Warning Tool With Treatment Protocol on Hypotension During Cardiac Surgery and ICU Stay: The Hypotension Prediction 2 (HYPE-2) Randomized Clinical Trial

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.

Just another tool in their repertoire: uncovering insights into public and patient perspectives on clinicians' use of machine learning in perioperative care

OBJECTIVES

Successful implementation of machine learning-augmented clinical decision support systems (ML-CDSS) in perioperative care requires the prioritization of patient-centric approaches to ensure alignment with societal expectations. We assessed general public and surgical patient attitudes and perspectives on ML-CDSS use in perioperative care.

MATERIALS AND METHODS

A sequential explanatory study was conducted. Stage 1 collected public opinions through a survey. Stage 2 ascertained surgical patients' experiences and attitudes via focus groups and interviews.

RESULTS

For Stage 1, a total of 281 respondents' (140 males [49.8%]) data were considered. Among participants without ML awareness, males were almost three times more likely than females to report more acceptance (OR = 2.97; 95% CI, 1.36-6.49) and embrace (OR = 2.74; 95% CI, 1.23-6.09) of ML-CDSS use by perioperative teams. Males were almost twice as likely as females to report more acceptance across all perioperative phases with ORs ranging from 1.71 to 2.07. In Stage 2, insights from 10 surgical patients revealed unanimous agreement that ML-CDSS should primarily serve a supportive function. The pre- and post-operative phases were identified explicitly as forums where ML-CDSS can enhance care delivery. Patients requested for education on ML-CDSS's role in their care to be disseminated by surgeons across multiple platforms.

DISCUSSION AND CONCLUSION

The general public and surgical patients are receptive to ML-CDSS use throughout their perioperative care provided its role is auxiliary to perioperative teams. However, the integration of ML-CDSS into perioperative workflows presents unique challenges for healthcare settings. Insights from this study can inform strategies to support large-scale implementation and adoption of ML-CDSS by patients in all perioperative phases. Key strategies to promote the feasibility and acceptability of ML-CDSS include clinician-led discussions about ML-CDSS's role in perioperative care, established metrics to evaluate the clinical utility of ML-CDSS, and patient education.

Goal-directed fluid therapy on the postoperative complications of laparoscopic hepatobiliary or pancreatic surgery: An interventional comparative study

BACKGROUND

Intraoperative fluid balance significantly affects patients' outcomes. Goal-directed fluid therapy (GDFT) has reduced the incidence of major postoperative complications by 20% for 30 days after open abdominal surgery. Little is known about GDFT during laparoscopic surgery.

AIM

We investigated whether GDFT affects the postoperative outcomes in laparoscopic hepatobiliary or pancreatic surgery compared with conventional fluid management.

METHODS

This interventional comparative study with a historical control group was performed in the tertiary care center. Patients were allocated to one of two groups. The GDFT (n = 147) was recruited prospectively and the conventional group (n = 228) retrospectively. In the GDFT group, fluid management was guided by the stroke volume (SV) and cardiac index (CI), whereas it had been performed based on vital signs in the conventional group. Propensity score (PS) matching was performed to reduce selection bias (n = 147 in each group). Postoperative complications were evaluated as primary outcome measures.

RESULTS

The amount of crystalloid used during surgery was less in the GDFT group than in the conventional group (5.1 ± 1.1 vs 6.3 ± 1.8 ml/kg/h, respectively; P <0.001), whereas the amount of colloid was comparable between the two groups. The overall proportion of patients who experienced any adverse events was 57.8% in the GDFT group and 70.1% in the conventional group (P = 0.038), of which the occurrence of pleural effusion was significantly lower in the GDFT group than in the conventional group (9.5% vs. 19.7%; P = 0.024). During the postoperative period, the proportion of patients admitted to the intensive care unit (ICU) was lower in the GDFT group than that in the conventional group after PS matching (4.1% vs 10.2%; P = 0.049).

CONCLUSIONS

GDFT based on SV and CI resulted in a lower net fluid balance than conventional fluid therapy. The overall complication rate in laparoscopic hepatobiliary or pancreatic surgery decreased after GDFT, and the frequency of pleural effusion was the most affected.

Beyond the debut: unpacking six years of Hypotension Prediction Index software in intraoperative hypotension prevention - a systematic review and meta-analysis

PURPOSE

Intraoperative hypotension (IOH) during general anesthesia is associated with higher morbidity and mortality, although randomized trials have not established a causal relation. Historically, our approach to IOH has been reactive. The Hypotension Prediction Index (HPI) is a machine learning software that predicts hypotension minutes in advance. This systematic review and meta-analysis explores whether using HPI alongside a personalized treatment protocol decreases intraoperative hypotension.

METHODS

A systematic search was performed in Pubmed and Scopus to retrieve articles published from January 2018 to February 2024 regarding the impact of the HPI software on reducing IOH in adult patients undergoing non-cardio/thoracic surgery. Excluded were case series, case reports, meta-analyses, systematic reviews, and studies using non-invasive arterial waveform analysis. The risk of bias was assessed by the Cochrane risk-of-bias tool (RoB 2) and the Risk Of Bias In Non-randomised Studies (ROBINS-I). A meta-analysis was undertaken solely for outcomes where sufficient data were available from the included studies.

RESULTS

9 RCTs and 5 cohort studies were retrieved. The overall median differences between the HPI-guided and the control groups were - 0.21 (95% CI:-0.33, -0.09) - p < 0.001 for the Time-Weighted Average (TWA) of Mean Arterial Pressure (MAP) < 65mmHg, -3.71 (95% CI= -6.67, -0.74)-p = 0.014 for the incidence of hypotensive episodes per patient, and - 10.11 (95% CI= -15.82, -4.40)-p = 0.001 for the duration of hypotension. Notably a large amount of heterogeneity was detected among the studies.

CONCLUSIONS

While the combination of HPI software with personalized treatment protocols may prevent intraoperative hypotension (IOH), the large heterogeneity among the studies and the lack of reliable data on its clinical significance necessitate further investigation.

Machine learning-augmented interventions in perioperative care: a systematic review and meta-analysis

BACKGROUND

We lack evidence on the cumulative effectiveness of machine learning (ML)-driven interventions in perioperative settings. Therefore, we conducted a systematic review to appraise the evidence on the impact of ML-driven interventions on perioperative outcomes.

METHODS

Ovid MEDLINE, CINAHL, Embase, Scopus, PubMed, and ClinicalTrials.gov were searched to identify randomised controlled trials (RCTs) evaluating the effectiveness of ML-driven interventions in surgical inpatient populations. The review was registered with PROSPERO (CRD42023433163) and conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Meta-analysis was conducted for outcomes with two or more studies using a random-effects model, and vote counting was conducted for other outcomes.

RESULTS

Among 13 included RCTs, three types of ML-driven interventions were evaluated: Hypotension Prediction Index (HPI) (n=5), Nociception Level Index (NoL) (n=7), and a scheduling system (n=1). Compared with the standard care, HPI led to a significant decrease in absolute hypotension (n=421, P=0.003, I2=75%) and relative hypotension (n=208, P<0.0001, I2=0%); NoL led to significantly lower mean pain scores in the post-anaesthesia care unit (PACU) (n=191, P=0.004, I2=19%). NoL showed no significant impact on intraoperative opioid consumption (n=339, P=0.31, I2=92%) or PACU opioid consumption (n=339, P=0.11, I2=0%). No significant difference in hospital length of stay (n=361, P=0.81, I2=0%) and PACU stay (n=267, P=0.44, I2=0) was found between HPI and NoL.

CONCLUSIONS

HPI decreased the duration of intraoperative hypotension, and NoL decreased postoperative pain scores, but no significant impact on other clinical outcomes was found. We highlight the need to address both methodological and clinical practice gaps to ensure the successful future implementation of ML-driven interventions.

SYSTEMATIC REVIEW PROTOCOL

CRD42023433163 (PROSPERO).

Hypotension prediction index for minimising intraoperative hypotension: A systematic review and meta-analysis of randomised controlled trials

Background and Aims

Reports on the utility of the hypotension prediction index (HPI) in reducing the occurrence of intraoperative hypotension are conflicting. Therefore, the aim of this systematic review and meta-analysis of randomised controlled trials (RCTs) was to evaluate the overall effect of using HPI on intraoperative hypotension outcomes of time-weighted average (TWA), area under the hypotension threshold (AUHT), incidence and duration of hypotension.

Methods

We searched the electronic databases of PubMed, ProQuest and Scopus from inception till 30 October 2023. The search strategy was refined for each database. No time or language restrictions were applied. Only RCTs were included. The systematic review protocol is registered with PROSPERO (ID: CRD42023478150). Statistical analysis was performed using Review Manager Software.

Results

Of 281 records, eight eligible RCTs (613 patients) were included. Significant differences were found between HPI and no HPI groups for the TWA of hypotension during surgery [mean difference (MD) = -0.19 mmHg, 95% confidence interval (95% CI): -0.31, -0.08, P = 0.001], AUHT [MD = -65.03 (mmHg × min), 95% CI: -105.47, -24.59, P = 0.002], incidence of hypotension (risk ratio = 0.83, 95% CI: 0.7, 0.99, P = 0.04), total hypotension duration (MD = -12.07 min, 95% CI: -17.49, -6.66, P < 0.001) and hypotension duration as a percentage of surgery time (MD = -6.30%, 95% CI: -10.23, -2.38, P = 0.002).

Conclusions

Available evidence supports the role of HPI in minimising hypotension outcomes during surgery. The certainty of evidence is low to moderate for studied 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.

Pilot Study to Optimize Goal-directed Hemodynamic Management During Pancreatectomy

INTRODUCTION

Intraoperative goal-directed hemodynamic therapy (GDHT) is a cornerstone of enhanced recovery protocols. We hypothesized that use of an advanced noninvasive intraoperative hemodynamic monitoring system to guide GDHT may decrease intraoperative hypotension (IOH) and improve perfusion during pancreatic resection.

METHODS

The monitor uses machine learning to produce the Hypotension Prediction Index to predict hypotensive episodes. A clinical decision-making algorithm uses the Hypotension Prediction Index and hemodynamic data to guide intraoperative fluid versus pressor management. Pre-implementation (PRE), patients were placed on the monitor and managed per usual. Post-implementation (POST), anesthesia teams were educated on the algorithm and asked to use the GDHT guidelines. Hemodynamic data points were collected every 20 s (8942 PRE and 26,638 POST measurements). We compared IOH (mean arterial pressure <65 mmHg), cardiac index >2, and stroke volume variation <12 between the two groups.

RESULTS

10 patients were in the PRE and 24 in the POST groups. In the POST group, there were fewer minimally invasive resections (4.2% versus 30.0%, P = 0.07), more pancreaticoduodenectomies (75.0% versus 20.0%, P < 0.01), and longer operative times (329.0 + 108.2 min versus 225.1 + 92.8 min, P = 0.01). After implementation, hemodynamic parameters improved. There was a 33.3% reduction in IOH (5.2% ± 0.1% versus 7.8% ± 0.3%, P < 0.01, a 31.6% increase in cardiac index >2.0 (83.7% + 0.2% versus 63.6% + 0.5%, P < 0.01), and a 37.6% increase in stroke volume variation <12 (73.2% + 0.3% versus 53.2% + 0.5%, P < 0.01).

CONCLUSIONS

Advanced intraoperative hemodynamic monitoring to predict IOH combined with a clinical decision-making tree for GDHT may improve intraoperative hemodynamic parameters during pancreatectomy. This warrants further investigation in larger studies.

A Comparison of Hypotension, Bradycardia, and Hypoxia Incidence between the Use of Remimazolam and Other Sedative Agents during Colonoscopy Procedures: A Systematic Review and Meta-Analysis

(1) Background: Remimazolam is a newly developed sedative agent. The results of previous meta-analyses highlight the strengths of remimazolam for use during colonoscopy procedures. The primary aim of the present study was to investigate whether, in patients undergoing colonoscopy procedures (P), the use of remimazolam (I) compared with other sedative agents (C) could lead to a greater incidence of hypotension, bradycardia, and hypoxia (O). (2) Methods: In the following study, we conducted an extensive literature search using two electronic databases. We included all randomized control trials, which involved a comparison of the hemodynamic changes in remimazolam versus a placebo and other sedative agents during colonoscopy procedures. Data extraction, data synthesis, and the assessment of risk of bias were performed by the authors. (3) Results: A total of seven articles met our inclusion criteria. The combined analysis of the selected studies revealed no statistically significant difference in hypotension, bradycardia, or hypoxia incidence when comparing remimazolam and the control group. However, in comparison with the group administered propofol, the pooled data of the selected studies revealed statistically significant differences in the incidence of both hypotension and bradycardia but not hypoxia. (4) Conclusions: Our findings indicate that there is no significant difference in hypotension, bradycardia, and hypoxia incidence when comparing remimazolam and other agents. Nevertheless, when comparing the remimazolam and propofol groups, the results demonstrated statistically significant differences in the incidence of both hypotension and bradycardia but not hypoxia.

Hypotension prediction index for prevention of intraoperative hypotension in patients undergoing general anesthesia: a randomized controlled trial

BACKGROUND

Intraoperative hypotension is a common side effect of general anesthesia. Here we examined whether the Hypotension Prediction Index (HPI), a novel warning system, reduces the severity and duration of intraoperative hypotension during general anesthesia.

METHODS

This randomized controlled trial was conducted in a tertiary referral hospital. We enrolled patients undergoing general anesthesia with invasive arterial monitoring. Patients were randomized 1:1 either to receive hemodynamic management with HPI guidance (intervention) or standard of care (control) treatment. Intraoperative hypotension treatment was initiated at HPI > 85 (intervention) or mean arterial pressure (MAP) < 65 mmHg (control). The primary outcome was hypotension severity, defined as a time-weighted average (TWA) MAP < 65 mmHg. Secondary outcomes were TWA MAP < 60 and < 55 mmHg.

RESULTS

Of the 60 patients who completed the study, 30 were in the intervention group and 30 in the control group. The patients' median age was 62 years, and 48 of them were male. The median duration of surgery was 490 min. The median MAP before surgery presented no significant difference between the two groups. The intervention group showed significantly lower median TWA MAP < 65 mmHg than the control group (0.02 [0.003, 0.08] vs. 0.37 [0.20, 0.58], P < 0.001). Findings were similar for TWA MAP < 60 mmHg and < 55 mmHg. The median MAP during surgery was significantly higher in the intervention group than that in the control group (87.54 mmHg vs. 77.92 mmHg, P < 0.001).

CONCLUSIONS

HPI guidance appears to be effective in preventing intraoperative hypotension during general anesthesia. Further investigation is needed to assess the impact of HPI on patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT04966364); 202105065RINA; Date of registration: July 19, 2021; The recruitment date of the first patient: July 22, 2021.

Incidence of intraoperative hypotension and its factors among adult traumatic head injury patients in comprehensive specialized hospitals, Northwest Ethiopia: a multicenter observational study

INTRODUCTION

Traumatic head injury (THI) poses a significant global public health burden, often contributing to mortality and disability. Intraoperative hypotension (IH) during emergency neurosurgery for THI can adversely affect perioperative outcomes, and understanding associated risk factors is essential for prevention.

METHOD

A multi-center observational study was conducted from February 10 to June 30, 2022. A simple random sampling technique was used to select the study participants. Patient data were analyzed using bivariate and multivariate logistic regression to identify significant factors associated with intraoperative hypotension (IH). Odds ratios with 95% confidence intervals were used to show the strength of association, and P value < 0.05 was considered as statistically significant.

RESULT

The incidence of intra-operative hypotension was 46.41% with 95%CI (39.2,53.6). The factors were duration of anesthesia ≥ 135 min with AOR: 4.25, 95% CI (1.004,17.98), severe GCS score with AOR: 7.23, 95% CI (1.098,47.67), intracranial hematoma size ≥ 15 mm with AOR: 7.69, 95% CI (1.18,50.05), and no pupillary abnormality with AOR: 0.061, 95% CI (0.005,0.732). CONCLUSION AND RECOMMENDATION: The incidence of intraoperative hypotension was considerably high. The duration of anesthesia, GCS score, hematoma size, and pupillary abnormalities were associated. The high incidence of IH underscores the need for careful preoperative neurological assessment, utilizing CT findings, vigilance for IH in patients at risk, and proactive management of IH during surgery. Further research should investigate specific mitigation strategies.

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.

AcumenTM hypotension prediction index guidance for prevention and treatment of hypotension in noncardiac surgery: a prospective, single-arm, multicenter trial

BACKGROUND

Intraoperative hypotension is common during noncardiac surgery and is associated with postoperative myocardial infarction, acute kidney injury, stroke, and severe infection. The Hypotension Prediction Index software is an algorithm based on arterial waveform analysis that alerts clinicians of the patient's likelihood of experiencing a future hypotensive event, defined as mean arterial pressure < 65 mmHg for at least 1 min.

METHODS

Two analyses included (1) a prospective, single-arm trial, with continuous blood pressure measurements from study monitors, compared to a historical comparison cohort. (2) A post hoc analysis of a subset of trial participants versus a propensity score-weighted contemporaneous comparison group, using external data from the Multicenter Perioperative Outcomes Group (MPOG). The trial included 485 subjects in 11 sites; 406 were in the final effectiveness analysis. The post hoc analysis included 457 trial participants and 15,796 comparison patients. Patients were eligible if aged 18 years or older, American Society of Anesthesiologists (ASA) physical status 3 or 4, and scheduled for moderate- to high-risk noncardiac surgery expected to last at least 3 h.

MEASUREMENTS

minutes of mean arterial pressure (MAP) below 65 mmHg and area under MAP < 65 mmHg.

RESULTS

Analysis 1: Trial subjects (n = 406) experienced a mean of 9 ± 13 min of MAP below 65 mmHg, compared with the MPOG historical control mean of 25 ± 41 min, a 65% reduction (p < 0.001). Subjects with at least one episode of hypotension (n = 293) had a mean of 12 ± 14 min of MAP below 65 mmHg compared with the MPOG historical control mean of 28 ± 43 min, a 58% reduction (p< 0.001). Analysis 2: In the post hoc inverse probability treatment weighting model, patients in the trial demonstrated a 35% reduction in minutes of hypotension compared to a contemporaneous comparison group [exponentiated coefficient: - 0.35 (95%CI - 0.43, - 0.27); p < 0.001].

CONCLUSIONS

The use of prediction software for blood pressure management was associated with a clinically meaningful reduction in the duration of intraoperative hypotension. Further studies must investigate whether predictive algorithms to prevent hypotension can reduce adverse outcomes.

TRIAL REGISTRATION

Clinical trial number: NCT03805217. Registry URL: https://clinicaltrials.gov/ct2/show/NCT03805217 . Principal investigator: Xiaodong Bao, MD, PhD. Date of registration: January 15, 2019.

The Incidence of Perioperative Hypotension in Patients Undergoing Major Abdominal Surgery with the Use of Arterial Waveform Analysis and the Hypotension Prediction Index Hemodynamic Monitoring-A Retrospective Analysis

Intraoperative hypotension (IH) is common in patients receiving general anesthesia and can lead to serious complications such as kidney failure, myocardial injury and increased mortality. The Hypotension Prediction Index (HPI) algorithm is a machine learning system that analyzes the arterial pressure waveform and alerts the clinician of an impending hypotension event. The purpose of the study was to compare the frequency of perioperative hypotension in patients undergoing major abdominal surgery with different types of hemodynamic monitoring. The study included 61 patients who were monitored with the arterial pressure-based cardiac output (APCO) technology (FloTrac group) and 62 patients with the Hypotension Prediction Index algorithm (HPI group). Our primary outcome was the time-weighted average (TWA) of hypotension below < 65 mmHg. The median TWA of hypotension in the FloTrac group was 0.31 mmHg versus 0.09 mmHg in the HPI group (p = 0.000009). In the FloTrac group, the average time of hypotension was 27.9 min vs. 8.1 min in the HPI group (p = 0.000023). By applying the HPI algorithm in addition to an arterial waveform analysis alone, we were able to significantly decrease the frequency and duration of perioperative hypotension events in patients who underwent major abdominal surgery.

Non-Invasive Monitoring during Caesarean Delivery: Prevalence of Hypotension and Impact on the Newborn

BACKGROUND

The aim of our study was to investigate the prevalence of perioperative hypotension after spinal anesthesia for cesarean section using non-invasive continuous hemodynamic monitoring and its correlation with neonatal well-being.

METHODS

We included 145 patients. Spinal anesthesia was performed with a combination of hyperbaric bupivacaine 0.5% (according to a weight/height scheme) and fentanyl 20 μg. Hypotension was defined as a mean arterial pressure (MAP) < 65 mmHg or <60 mmHg. We also evaluated the impact of hypotension on neonatal well-being.

RESULTS

Perioperative maternal hypotension occurred in 54.5% of cases considering a MAP < 65 mmHg and in 42.1% with the more conservative cut-off (<60 mmHg). Severe neonatal acidosis occurred in 1.4% of neonates, while an Apgar score ≥ 9 was observed in 95.9% at 1 min and 100% at 5 min.

CONCLUSIONS

Continuous non-invasive hemodynamic monitoring allowed an early detection of maternal hypotension leading to a prompt treatment with satisfactory results considering neonatal well-being.

Index of consciousness monitoring during general anesthesia may effectively enhance rehabilitation in elderly patients undergoing laparoscopic urological surgery: a randomized controlled clinical trial

BACKGROUND

Based on electroencephalogram (EEG) analysis, index of consciousness (IoC) monitoring is a new technique for monitoring anesthesia depth. IoC is divided into IoC1 (depth of sedation) and IoC2 (depth of analgesia). The potential for concurrent monitoring of IoC1 and IoC2 to expedite postoperative convalescence remains to be elucidated. We investigated whether combined monitoring of IoC1 and IoC2 can effectively enhances postoperative recovery compared with bispectral index (BIS) in elderly patients undergoing laparoscopic urological surgery under general anesthesia.

METHODS

In this prospective, controlled, double-blinded trail, 120 patients aged 65 years or older were arbitrarily assigned to either the IoC group or the control group (BIS monitoring). All patients underwent blood gas analysis at T1 (before anesthesia induction) and T2 (the end of operation). The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were administered to all patients at T0 (1 day before surgery) and T4 (7 days after surgery). Serum concentrations of C-reactive protein (CRP) and glial fibrillary acid protein (GFAP) were assessed at T1, T2, and T3 (24 h after surgery). Postoperative complications and the duration of hospitalization were subjected to comparative evaluation.

RESULTS

The incidence of postoperative cognitive dysfunction (POCD) was notably lower in the IoC group (10%) than in the control group (31.7%) (P = 0.003). Postoperative serum CRP and GFAP concentrations exhibited significant differences at time points T2 (CRP: P = 0.000; GFAP: P = 0.000) and T3 (CRP: P = 0.003; GFAP: P = 0.008). Postoperative blood glucose levels (P = 0.000) and the overall rate of complications (P = 0.037) were significantly lower in Group IoC than in Group control.

CONCLUSION

The employment of IoC monitoring for the management of elderly surgical patients can accelerate postoperative convalescence by mitigating intraoperative stress and reducing peripheral and central inflammatory injury.

TRIAL REGISTRATION

Chinese Clinical Trial Registry Identifier: ChiCTR1900025241 (17/08/2019).

Effects of different sponge implantation methods of negative pressure wound therapy on wound healing of deep surgical site infection after spinal surgery

PURPOSE

After spinal surgery, negative pressure wound treatment (NPWT) improves deep surgical site infection (DSSI) wound healing. This research compared the healing benefits of two sponge implantation strategies in NPWT for DSSI.

METHODS

21 patients with DSSI utilized NPWT to improve wound healing following spine surgery were followed from January 1, 2012 to December 31, 2021. After antibiotic treatment failure, all these patients with DSSI received extensive debridement and NPWT. They are grouped by sponge placement method: centripetal reduction and segment reduction. The two groups' hospital stays, NPWT replacement frequency, wound healing time, healing speed, and quality of wound healing (POSAS score) were compared.

RESULTS

All patients had been cured by the end of December 2022, and the mean follow-up time was 57.48 ± 29.6 months. Surgical incision length did not vary across groups (15.75±7.61 vs. 15.46±7.38 cm, P = 0.747). The segmental reduction approach had shorter hospital stay and NPWT treatment times than the centripetal reduction method (39.25±16.04 vs. 77.38±37.24 days, P = 0.027). Although there is no statistically significant difference, the mean wound healing duration of segmental reduction group is faster than that of centripetal reduction group (0.82±0.39 vs 0.45±0.28 cm/d, P = 0.238), wound healing quality (POSAS) (33.54±8.63 vs 48.13±12.17, P = 0.408) is better in segmental reduction group, and NPWT replacement frequency (2.62 ± 1.04 vs 3.88 ± 1.25, P < .915) is smaller in segmental reduction group.

CONCLUSIONS

NPWT heals wounds and controls infection. Segmental reduction method accelerates wound healing, reduces hospital stay, and improves wound quality compared to central reduction method.

Effects of intraoperative neuromonitoring (IONM) technology on early recovery quality in patients after thyroid surgery: A randomized controlled trial

BACKGROUND

Patient-focused evaluation of postoperative recover has been recognized as one of the most important concerns in postoperative medicine. Previous studies have shown that the Quality of Recovery-40 (QoR-40) Questionnaire can be used to accurately assess the quality of recovery from surgery. During thyroid surgery using intraoperative neuromonitoring (IONM) technology, the strategy of low dose of muscle relaxant, intubation of different endotracheal tubes and electrical stimulation on vocal cord are applied. Its still unknown if these performances would affect patients' postoperative recovery in thyroid surgery patients.

METHODS

82 patients were randomly assigned to the neuromonitoring group (NEURO Group) and the control group (CON Group). In the CON Group, rocuronium (0.6 mg / kg) was given for intubation and additional dose was injected if needed, while in the NEURO Group, only rocuronium (0.3 mg / kg) was given when induction. The primary outcome is the QoR-40 scores on postoperative day 1 (POD1) and postoperative day 3 (POD3). Other parameters, such as postoperative nausea or vomiting (PONV) and medical cost were also recorded.

RESULTS

One subject in each group was excluded, leaving 80 for analysis. In the NEURO Group, the global QoR-40 score, emotional state, physical comfort, physical independence and pain were significantly lower both on POD1 and POD3 (P<0.05). Patients in the NEURO Group had a higher incidence of PONV (P<0.05) and medical expense (P<0.05).

CONCLUSIONS

After thyroidectomy, the patients using IONM suffer worse quality of recovery, more risk of PONV and increased medical expense.

Harnessing Machine Learning for Prediction of Postoperative Pulmonary Complications: Retrospective Cohort Design

Postoperative pulmonary complications (PPCs) are significant causes of postoperative morbidity and mortality. This study presents the utilization of machine learning for predicting PPCs and aims to identify the important features of the prediction models. This study used a retrospective cohort design and collected data from two hospitals. The dataset included perioperative variables such as patient characteristics, preexisting diseases, and intraoperative factors. Various algorithms, including logistic regression, random forest, light-gradient boosting machines, extreme-gradient boosting machines, and multilayer perceptrons, have been employed for model development and evaluation. This study enrolled 111,212 adult patients, with an overall incidence rate of 8.6% for developing PPCs. The area under the receiver-operating characteristic curve (AUROC) of the models was 0.699-0.767, and the f1 score was 0.446-0.526. In the prediction models, except for multilayer perceptron, the 10 most important features were obtained. In feature-reduced models, including 10 important features, the AUROC was 0.627-0.749, and the f1 score was 0.365-0.485. The number of packed red cells, urine, and rocuronium doses were similar in the three models. In conclusion, machine learning provides valuable insights into PPC prediction, significant features for prediction, and the feasibility of models that reduce the number of features.

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.

Effects of Remimazolam Anesthesia with Two Induction Doses on Hemodynamics and Recovery Profile in Older Patients: Comparison with Propofol Anesthesia

Remimazolam has advantages such as hemodynamic stability and rapid onset. We investigated the effects of induction doses on hemodynamics and recovery profiles for remimazolam compared to propofol in older patients. Sixty-nine patients aged >65 years were randomly assigned to either the propofol anesthesia group (P group) or the remimazolam anesthesia group with an induction dose of 6 mg/kg/h (R6 group) or 12 mg/kg/h (R12 group), followed by 1 mg/kg/h. P group was anesthetized with 4 µg/mL of propofol effect-site concentration (Ce) with target-control infusion, followed by 2.5-3 µg/mL of Ce. The primary outcome was the difference between the baseline mean arterial pressure (MAP) and the lowest MAP during anesthesia (ΔMAP). ΔMAP was comparable between the P, R6, and R12 groups (43.8 ± 13.8 mmHg, 39.2 ± 14.3 mmHg, and 39.2 ± 13.5 mmHg, p = 0.443). However, the frequencies of vasoactive drug use were 54.5%, 17.4%, and 30.4% (p = 0.029), and the median doses of ephedrine 3 (0-6) mg, 0 (0-0) mg, and 0 (0-0) mg (p = 0.034), which were significantly different. This study showed remimazolam anesthesia with an induction dose of 6 mg/kg/h, rather than 12 mg/kg/h, could reduce the requirement for vasoactive drugs compared to propofol anesthesia.

The Impact of Blood Transfusion in Developing Postoperative Delirium in Patients with Hip Fracture Surgery

BACKGROUND

Many studies have been conducted to explore the risk factors associated with postoperative delirium (POD) in order to understand its underlying causes and develop prevention strategies, especially for hip fracture surgery. However, the relationship between blood transfusion and POD has been heatedly debated. The purpose of this study was to evaluate the risk factors of POD and the relationship between blood transfusions and the occurrence of POD in hip fracture surgery through big data analysis.

METHODS

Medical data (including medication history, clinical and laboratory findings, and perioperative variables) were acquired from the clinical data warehouse (CDW) of the five hospitals of Hallym University Medical Center and were compared between patients without POD and with POD.

RESULTS

The occurrence of POD was 18.7% (228 of 2398 patients). The risk factors of POD included old age (OR 4.38, 95% CI 2.77-6.91; p < 0.001), American Society of Anesthesiology physical status > 2 (OR 1.84 95% CI 1.4-2.42; p < 0.001), dementia (OR 1.99, 95% CI 1.53-2.6; p < 0.001), steroid (OR 0.53 95% CI 0.34-0.82; p < 0.001), Antihistamine (OR 1.53 95% CI 1.19-1.96; p < 0.001), and postoperative erythrocyte sedimentation rate (mm/h) (OR 0.97 95% CI 0.97-0.98; p < 0.001) in multivariate logistic regression analysis. The postoperative transfusion (OR 2.53, 95% CI 1.88-3.41; p < 0.001) had a significant effect on the incidence of POD.

CONCLUSIONS

big data analytics using a CDW was a good option to identify the risk factors of POD and to prevent POD in hip fracture surgery.

Impact of Intraoperative Fluid Balance and Norepinephrine on Postoperative Acute Kidney Injury after Cystectomy and Urinary Diversion over Two Decades: A Retrospective Observational Cohort Study

The use of norepinephrine and the restriction of intraoperative hydration have gained increasing acceptance over the last few decades. Recently, there have been concerns regarding the impact of this approach on renal function. The objective of this study was to examine the influence of norepinephrine, intraoperative fluid administration and their interaction on acute kidney injury (AKI) after cystectomy. In our cohort of 1488 consecutive patients scheduled for cystectomies and urinary diversions, the overall incidence of AKI was 21.6% (95%-CI: 19.6% to 23.8%) and increased by an average of 0.6% (95%-CI: 0.1% to 1.1%, p = 0.025) per year since 2000. The fluid and vasopressor regimes were characterized by an annual decrease in fluid balance (-0.24 mL·kg^-1·h^-1, 95%-CI: -0.26 to -0.22, p < 0.001) and an annual increase in the amount of norepinephrine of 0.002 µg·kg^-1·min^-1 (95%-CI: 0.0016 to 0.0024, p < 0.001). The interaction between the fluid balance and norepinephrine levels resulted in a U-shaped association with the risk of AKI; however, the magnitude and shape depended on the reference categories of confounders (age and BMI). We conclude that decreased intraoperative fluid balance combined with increased norepinephrine administration was associated with an increased risk of AKI. However, other potential drivers of the observed increase in AKI incidence need to be further investigated in the future.

Diagnostic Efficacy of Carotid Ultrasound for Predicting the Risk of Perioperative Hypotension or Fluid Responsiveness: A Meta-Analysis

Despite the acceptance of carotid ultrasound for predicting patients' fluid responsiveness in critical care and anesthesia, its efficacy for predicting hypotension and fluid responsiveness remains unclear in the perioperative setting. Electronic databases were searched from inception to May 2023 to identify observational studies focusing on the use of corrected blood flow time (FTc) and respirophasic variation in carotid artery blood flow peak velocity (ΔVpeak) for assessing the risks of hypotension and fluid responsiveness. Using FTc as a predictive tool (four studies), the analysis yielded a pooled sensitivity of 0.82 (95% confidence interval (CI): 0.72 to 0.89) and specificity of 0.94 (95% CI: 0.88 to 0.97) for the risk of hypotension (area under curve (AUC): 0.95). For fluid responsiveness, the sensitivity and specificity of FTc were 0.79 (95% CI: 0.72 to 0.84) and 0.81 (95% CI: 0.75 to 0.86), respectively (AUC: 0.87). In contrast, the use of ΔVpeak to predict the risk of fluid responsiveness showed a pooled sensitivity of 0.76 (95% CI: 0.63 to 0.85) and specificity of 0.74 (95% CI: 0.66 to 0.8) (AUC: 0.79). The current meta-analysis provides robust evidence supporting the high diagnostic accuracy of FTc in predicting perioperative hypotension and fluid responsiveness, which requires further studies for verification.

Effect of the machine learning-derived Hypotension Prediction Index (HPI) combined with diagnostic guidance versus standard care on depth and duration of intraoperative and postoperative hypotension in elective cardiac surgery patients: HYPE-2 - study protocol of a randomised clinical trial

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).

Intraoperative Hypotension Prediction—A Proactive Perioperative Hemodynamic Management—A Literature Review

Intraoperative hypotension (IH) is a frequent phenomenon affecting a substantial number of patients undergoing general anesthesia. The occurrence of IH is related to significant perioperative complications, including kidney failure, myocardial injury, and even increased mortality. Despite advanced hemodynamic monitoring and protocols utilizing goal directed therapy, our management is still reactive; we intervene when the episode of hypotension has already occurred. This literature review evaluated the Hypotension Prediction Index (HPI), which is designed to predict and reduce the incidence of IH. The HPI algorithm is based on a machine learning algorithm that analyzes the arterial pressure waveform as an input and the occurrence of hypotension with MAP <65 mmHg for at least 1 min as an output. There are several studies, both retrospective and prospective, showing a significant reduction in IH episodes with the use of the HPI algorithm. However, the level of evidence on the use of HPI remains very low, and further studies are needed to show the benefits of this algorithm on perioperative outcomes.

Agreement between Capillary Refill Time measured at Finger and Earlobe sites in different positions: a pilot prospective study on healthy volunteers

BACKGROUND

Capillary Refill Time (CRT) is a marker of peripheral perfusion usually performed at fingertip; however, its evaluation at other sites/position may be advantageous. Moreover, arm position during CRT assessment has not been fully standardized.

METHODS

We performed a pilot prospective observational study in 82 healthy volunteers. CRT was assessed: a) in standard position with participants in semi-recumbent position; b) at 30° forearm elevation, c and d) at earlobe site in semi-recumbent and supine position. Bland-Altman analysis was performed to calculate bias and limits of agreement (LoA). Correlation was investigated with Pearson test.

RESULTS

Standard finger CRT values (1.04 s [0.80;1.39]) were similar to the earlobe semi-recumbent ones (1.10 s [0.90;1.26]; p = 0.52), with Bias 0.02 ± 0.18 s (LoA -0.33;0.37); correlation was weak but significant (r = 0.28 [0.7;0.47]; p = 0.01). Conversely, standard finger CRT was significantly longer than earlobe supine CRT (0.88 s [0.75;1.06]; p < 0.001) with Bias 0.22 ± 0.4 s (LoA -0.56;1.0), and no correlation (r = 0,12 [-0,09;0,33]; p = 0.27]. As compared with standard finger CRT, measurement with 30° forearm elevation was significantly longer (1.17 s [0.93;1.41] p = 0.03), with Bias -0.07 ± 0.3 s (LoA -0.61;0.47) and with a significant correlation of moderate degree (r = 0.67 [0.53;0.77]; p < 0.001).

CONCLUSIONS

In healthy volunteers, the elevation of the forearm significantly prolongs CRT values. CRT measured at the earlobe in semi-recumbent position may represent a valid surrogate when access to the finger is not feasible, whilst earlobe CRT measured in supine position yields different results. Research is needed in critically ill patients to evaluate accuracy and precision at different sites/positions.

Effect of hypotension prediction index in the prevention of intraoperative hypotension during noncardiac surgery: A systematic review

Intraoperative hypotension (IOH) is common in noncardiac surgery and is associated with serious postoperative complications. Hypotension Prediction Index (HPI) has shown high sensitivity and specificity for predicting hypotension and may reduce IOH in noncardiac surgery. We conducted a systematic review of randomized controlled trials (RCTs) to evaluate the applications and effects of HPI in reducing hypotension during noncardiac surgery. We comprehensively searched the PubMed, Embase, Cochrane Library, Google Scholar, and http://ClinicalTrials.gov databases to identify RCTs conducted before May 2022. The primary outcome measures were the time-weighted average (TWA) of hypotension and the area under the hypotensive threshold (65 mmHg). Secondary outcomes were the incidence and duration of hypotension and the percentage of hypotensive time during surgery. The Cochrane Risk of Bias (RoB) tool was used to assess the quality of selected studies. We conducted data synthesis for median differences and assessed the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. We included five studies with a total of 461 patients. Limited evidence suggested that HPI-guided intraoperative hemodynamics management leads to lower a) TWA of hypotension (median of difference of medians [MDM], -0.27 mmHg; 95% confidence interval [CI], -0.38, -0.01), b) area under the hypotensive threshold (MDM, -60.28 mmHg*min; 95% CI, -74.00, -1.30), c) incidence of hypotension (MDM, -4.50; 95% CI, -5.00, -4.00), d) total duration of hypotension (MDM, -12.80 min; 95% CI, -16.11, -3.39), and e) percentage of hypotension (MDM, -5.80; 95% CI, -6.65, -4.82) than routine hemodynamic management during noncardiac surgery. However, only very low- to low-quality evidence on the benefit of intraoperative HPI-based hemodynamic management is available. Our review revealed that HPI has the potential to reduce the occurrence, duration, and severity of IOH during noncardiac surgery compared to standard intraoperative care with proper adherence to the protocol. Systematic review registration PROSPERO CRD42022333834.

Prediction and Prevention of Intraoperative Hypotension with the Hypotension Prediction Index: A Narrative Review

Intraoperative hypotension is common and has been associated with adverse events. Although association does not imply causation, predicting and preventing hypotension may improve postoperative outcomes. This review summarizes current evidence on the development and validation of an artificial intelligence predictive algorithm, the Hypotension Prediction (HPI) (formerly known as the Hypotension Probability Indicator). This machine learning model can arguably predict hypotension up to 15 min before its occurrence. Several validation studies, retrospective cohorts, as well as a few prospective randomized trials, have been published in the last years, reporting promising results. Larger trials are needed to definitively assess the usefulness of this algorithm in optimizing postoperative outcomes.

Persistent Depletion of Neuroprotective Factors Accompanies Neuroinflammatory, Neurodegenerative, and Vascular Remodeling Spectra in Serum Three Months after Non-Emergent Cardiac Surgery

We hypothesized that the persistent depletion of neuroprotective markers accompanies neuroinflammation and neurodegeneration in patients after cardiac surgery. A total of 158 patients underwent elective heart surgery with their blood collected before surgery (tbaseline) and 24 h (t24hr), seven days (t7d), and three months (t3m) post-surgery. The patients' serum was measured for markers of neurodegeneration (τau, τaup181-183, amyloid β1-40/β2-42, and S100), atypical neurodegeneration (KLK6 and NRGN), neuro-injury (neurofilament light/heavy, UC-HL, and GFAP), neuroinflammation (YKL-40 and TDP-43), peripheral nerve damage (NCAM-1), neuroprotection (apoE4, BDNF, fetuin, and clusterin), and vascular smoldering inflammation (C-reactive protein, CCL-28 IL-6, and IL-8). The mortality at 28 days, incidence of cerebrovascular accidents (CVA), and functional status were followed for three months. The levels of amyloid β1-40/β1-42 and NF-L were significantly elevated at all time points. The levels of τau, S100, KLK6, NRGN, and NCAM-1 were significantly elevated at 24 h. A cluster analysis demonstrated groupings around amyloids, KLK6, and NCAM-1. YKL-40, but not TDP-43, was significantly elevated across all time points. BDNF, apoE4, fetuin, and clusterin levels were significantly diminished long-term. IL-6 and IL-8 levles returned to baseline at t3m. The levels of CRP, CCL-28, and Hsp-70 remained elevated. At 3 months, 8.2% of the patients experienced a stroke, with transfusion volume being a significant variable. Cardiac-surgery patients exhibited persistent peripheral and neuronal inflammation, blood vessel remodeling, and the depletion of neuroprotective factors 3 months post-procedure.

Provisional Decision-Making for Perioperative Blood Pressure Management: A Narrative Review

Blood pressure (BP) is a basic determinant for organ blood flow supply. Insufficient blood supply will cause tissue hypoxia, provoke cellular oxidative stress, and to some extent lead to organ injury. Perioperative BP is labile and dynamic, and intraoperative hypotension is common. It is unclear whether there is a causal relationship between intraoperative hypotension and organ injury. However, hypotension surely compromises perfusion and causes harm to some extent. Because the harm threshold remains unknown, various guidelines for intraoperative BP management have been proposed. With the pending definitions from robust randomized trials, it is reasonable to consider observational analyses suggesting that mean arterial pressures below 65 mmHg sustained for more than 15 minutes are associated with myocardial and renal injury. Advances in machine learning and artificial intelligence may facilitate the management of hemodynamics globally, including fluid administration, rather than BP alone. The previous mounting studies concentrated on associations between BP targets and adverse complications, whereas few studies were concerned about how to treat and multiple factors for decision-making. Hence, in this narrative review, we discussed the way of BP measurement and current knowledge about baseline BP extracting for surgical patients, highlighted the decision-making process for BP management with a view to providing pragmatic guidance for BP treatment in the clinical settings, and evaluated the merits of an automated blood control system in predicting hypotension.