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.

The Predictors and Risk Factors of 2-Year Rejection in Renal Transplant Patients: A Multicenter Case-Control Study.

INTRODUCTION: Kidney transplantation is a definitive treatment for end-stage renal disease. It is associated with improved life expectancy and quality of life. One of the most common complications following kidney transplantation is graft rejection. To our knowledge, no previous study has identified rejection risk factors in kidney transplant recipients in Saudi Arabia. Therefore, this study aimed to determine the specific risk factors of graft rejection. METHODS: A multicenter case-control study was conducted at four transplant centers in Saudi Arabia. All adult patients who underwent a renal transplant between January 1, 2015 and December 31, 2021 were screened for eligibility. Included patients were categorized into two groups (cases and control) based on the occurrence of biopsy-proven rejection within 2 years. The primary outcome was to determine the risk factors for rejection within the 2 years of transplant. Exact matching was utilized using a 1:4 ratio based on patients' age, gender, and transplant year. RESULTS: Out of 1,320 screened renal transplant recipients, 816 patients were included. The overall prevalence of 2-year rejection was 13.9%. In bivariate analysis, deceased donor status, the presence of donor-specific antibody (DSA), intraoperative hypotension, Pseudomonas aeruginosa, Candida, and any infection within 2 years were linked with an increased risk of 2-year rejection. However, in the logistic regression analysis, the presence of DSA was identified as a significant risk for 2-year rejection (adjusted OR: 2.68; 95% CI: 1.10, 6.49, p = 0.03). Furthermore, blood infection, infected with Pseudomonas aeruginosa or BK virus within 2 years of transplant, were associated with higher odds of 2-year rejection (adjusted OR: 3.10; 95% CI: 1.48, 6.48, p = 0.003, adjusted OR: 3.23; 95% CI: 0.87, 11.97, p = 0.08 and adjusted OR: 2.76; 95% CI: 0.89, 8.48, p = 0.07, respectively). CONCLUSION: Our findings emphasize the need for appropriate prevention and management of infections following kidney transplantation to avoid more serious problems, such as rejection, which could significantly raise the likelihood of allograft failure and probably death. Further studies with larger sample sizes are needed to investigate the impact of serum chloride levels prior to transplant and intraoperative hypotension on the risk of graft rejection and failure.

Effect of machine learning-guided haemodynamic optimization on postoperative free flap perfusion in reconstructive maxillofacial surgery: A study protocol.

AIMS: Intraoperative hypotension and liberal fluid haemodynamic therapy are associated with postoperative medical and surgical complications in maxillofacial free flap surgery. The novel haemodynamic parameter hypotension prediction index (HPI) has shown good performance in predicting hypotension by analysing arterial pressure waveform in various types of surgery. HPI-based haemodynamic protocols were able to reduce the duration and depth of hypotension. We will try to determine whether haemodynamic therapy based on HPI can improve postoperative flap perfusion and tissue oxygenation by improving intraoperative mean arterial pressure and reducing fluid infusion. METHODS: We present here a study protocol for a single centre, randomized, controlled trial (n = 42) in maxillofacial patients undergoing free flap surgery. Patients will be randomized into an intervention or a control group. In the intervention, group haemodynamic optimization will be guided by machine learning algorithm and functional haemodynamic parameters presented by the HemoSphere platform (Edwards Lifesciences, Irvine, CA, USA), most importantly, HPI. Tissue oxygen saturation of the free flap will be monitored noninvasively by near-infrared spectroscopy during the first 24 h postoperatively. The primary outcome will be the average value of tissue oxygen saturation in the first 24 h postoperatively.

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.

Association between peripheral perfusion index and postoperative acute kidney injury in major noncardiac surgery patients receiving continuous vasopressors: a post hoc exploratory analysis of the VEGA-1 trial.

BACKGROUND: The peripheral perfusion index is the ratio of pulsatile to nonpulsatile static blood flow obtained by photoplethysmography and reflects peripheral tissue perfusion. We investigated the association between intraoperative perfusion index and postoperative acute kidney injury in patients undergoing major noncardiac surgery and receiving continuous vasopressor infusions. METHODS: In this exploratory post hoc analysis of a pragmatic, cluster-randomised, multicentre trial, we obtained areas and cumulative times under various thresholds of perfusion index and investigated their association with acute kidney injury in multivariable logistic regression analyses. In secondary analyses, we investigated the association of time-weighted average perfusion index with acute kidney injury. The 30-day mortality was a secondary outcome. RESULTS: Of 2534 cases included, 8.9% developed postoperative acute kidney injury. Areas and cumulative times under a perfusion index of 3% and 2% were associated with an increased risk of acute kidney injury; the strongest association was observed for area under a perfusion index of 1% (adjusted odds ratio [aOR] 1.32, 95% confidence interval [CI] 1.00-1.74, P=0.050, per 100%∗min increase). Additionally, time-weighted average perfusion index was associated with acute kidney injury (aOR 0.82, 95% CI 0.74-0.91, P<0.001) and 30-day mortality (aOR 0.68, 95% CI 0.49-0.95, P=0.024). CONCLUSIONS: Larger areas and longer cumulative times under thresholds of perfusion index and lower time-weighted average perfusion index were associated with postoperative acute kidney injury in patients undergoing major noncardiac surgery and receiving continuous vasopressor infusions. CLINICAL TRIAL REGISTRATION: NCT04789330.

Mortality following noncardiac surgery assessed by the Saint Louis University Score (SLUScore) for hypotension: a retrospective observational cohort study.

BACKGROUND: The Saint Louis University Score (SLUScore) was developed to quantify intraoperative blood pressure trajectories and their associated risk for adverse outcomes. This study examines the prevalence and severity of intraoperative hypotension described by the SLUScore and its relationship with 30-day mortality in surgical subtypes. METHODS: This retrospective analysis of perioperative data included surgical cases performed between January 1, 2010, and December 31, 2020. The SLUScore is calculated from cumulative time-periods for which the mean arterial pressure is below a range of hypotensive thresholds. After calculating the SLUScore for each surgical procedure, we quantified the prevalence and severity of intraoperative hypotension for each surgical procedure and the association between intraoperative hypotension and 30-day mortality. We used binary logistic regression to quantify the potential contribution of intraoperative hypotension to mortality. RESULTS: We analysed 490 982 cases (57.7% female; mean age 57 yr); 33.2% of cases had a SLUScore>0, a median SLUScore of 13 (inter-quartile range [IQR] 7-21), with 1.19% average mortality. The SLUScore was associated with mortality in 12/14 surgical groups. The increases in the odds ratio for death within 30 days of surgery per SLUScore increment were: all surgery types 3.5% (95% confidence interval [95% CI] 3.2-3.9); abdominal/transplant surgery 6% (95% CI 1.5-10.7); thoracic surgery1.5% (95% CI 1-3.3); vascular surgery 3.01% (95% CI 1.9-4.05); spine/neurosurgery 1.1% (95% CI 0.1-2.1); orthopaedic surgery 1.4% (95% CI 0.7-2.2); gynaecological surgery 6.3% (95% CI 2.5-10.1); genitourinary surgery 4.84% (95% CI 3.5-6.15); gastrointestinal surgery 5.2% (95% CI 3.9-6.4); gastroendoscopy 5.5% (95% CI 4.4-6.7); general surgery 6.3% (95% CI 5.5-7.1); ear, nose, and throat surgery 1.6% (95% CI 0-3.27); and cardiac electrophysiology (including pacemaker procedures) 6.6% (95% CI 1.1-12.4). CONCLUSIONS: The SLUScore was independently, but variably, associated with 30-day mortality after noncardiac surgery.

Association between postinduction hypotension and postoperative mortality: a single-centre retrospective cohort study.

PURPOSE: We aimed to elucidate whether postinduction hypotension (PIH), defined as hypotension between anesthesia induction and skin incision, and intraoperative hypotension (IOH) are associated with postoperative mortality. METHODS: We conducted a retrospective cohort study of adult patients with an ASA Physical Status I-IV who underwent noncardiac and nonobstetric surgery under general anesthesia between 2015 and 2021 at Nagoya City University Hospital. The primary and secondary outcomes were 30-day and 90-day postoperative mortality, respectively. We calculated four hypotensive indices (with time proportion of the area under the threshold being the primary exposure variable) to evaluate the association between hypotension (defined as a mean blood pressure < 65 mm Hg) and mortality using multivariable logistic regression models. We used propensity score matching and RUSBoost (random under-sampling and boosting), a machine-learning model for imbalanced data, for sensitivity analyses. RESULTS: Postinduction hypotension and IOH were observed in 82% and 84% of patients, respectively. The 30-day and 90-day postoperative mortality rates were 0.4% (52/14,210) and 1.0% (138/13,334), respectively. Postinduction hypotension was not associated with 30-day mortality (adjusted odds ratio [aOR], 1.03; 95% confidence interval [CI], 0.93 to 1.13; P = 0.60) and 90-day mortality (aOR, 1.01; 95% CI, 0.94 to 1.07; P = 0.82). Conversely, IOH was associated with 30-day mortality (aOR, 1.19; 95% CI, 1.12 to 1.27; P < 0.001) and 90-day mortality (aOR, 1.12; 95% CI, 1.06 to 1.19; P < 0.001). Sensitivity analyses supported the association of IOH but not PIH with postoperative mortality. CONCLUSION: Despite limitations, including power and residual confounding, postoperative mortality was associated with IOH but not with PIH.

RéSUMé: OBJECTIF: Nous avons cherché à déterminer si l'hypotension post-induction (HPI), définie comme une hypotension entre l'induction de l'anesthésie et l'incision cutanée, et l'hypotension peropératoire (HPO) étaient associées à la mortalité postopératoire. MéTHODE: Nous avons mené une étude de cohorte rétrospective de patient·es adultes ayant un statut physique I-IV selon l'ASA et ayant bénéficié d'une chirurgie non cardiaque et non obstétricale sous anesthésie générale entre 2015 et 2021 à l'Hôpital universitaire de la ville de Nagoya. Les critères d'évaluation principal et secondaire étaient la mortalité postopératoire à 30 et 90 jours, respectivement. Nous avons calculé quatre indices d'hypotension (la proportion temporelle de la zone sous le seuil étant la principale variable d'exposition) pour évaluer l'association entre l'hypotension (définie comme une tension artérielle moyenne < 65 mm Hg) et la mortalité à l'aide de modèles de régression logistique multivariée. Nous avons utilisé l'appariement par score de propension et le RUSBoost (sous-échantillonnage et boosting aléatoire), un modèle d'apprentissage automatique pour les données déséquilibrées, pour les analyses de sensibilité. RéSULTATS: Une HPI et une HPO ont été observées chez 82 % et 84 % des patient·es, respectivement. Les taux de mortalité postopératoire à 30 et 90 jours étaient respectivement de 0,4 % (52/14 210) et de 1,0 % (138/13 334). L'hypotension post-induction n'était pas associée à la mortalité à 30 jours (rapport de cotes ajusté [RCa], 1,03; intervalle de confiance [IC] à 95 %, 0,93 à 1,13; P = 0,60) et à la mortalité à 90 jours (RCa, 1,01; IC 95 %, 0,94 à 1,07; P = 0,82). À l'inverse, l'HPO était associée à une mortalité à 30 jours (RCa, 1,19; IC 95 %, 1,12 à 1,27; P < 0,001) et à la mortalité à 90 jours (RCa, 1,12; IC 95 %, 1,06 à 1,19; P < 0,001). Les analyses de sensibilité ont confirmé l'association de l'HPO, mais pas de l'HPI, avec la mortalité postopératoire. CONCLUSION: Malgré les limitations, y compris la puissance et persistance de facteurs confondants, la mortalité postopératoire était associée à l'hypotension peropératoire mais pas à l'hypotension post-induction seule.

Intraoperative short-term blood pressure variability and postoperative acute kidney injury: a single-center retrospective cohort study using sample entropy analysis.

BACKGROUND: To investigate if intraoperative very short-term variability in blood pressure measured by sample entropy improves discrimination of postoperative acute kidney injury after noncardiac surgery. METHODS: Adult surgical patients undergoing general, thoracic, urological, or gynecological surgery between August 2016 to June 2017 at Seoul National University Hospital were included. The primary outcome was acute kidney injury stage 1, defined by the Kidney Disease: Improving Global Outcomes guidelines. Exploratory and explanatory variables included sample entropy of the mean arterial pressure and standard demographic, surgical, anesthesia and hypotension over time indices known to be associated with acute kidney injury respectively. Random forest classification and L1 logistic regression were used to assess four models for discriminating acute kidney injury: (1) Standard risk factors which included demographic, anesthetic, and surgical variables (2) Standard risk factors and cumulative hypotension over time (3) Standard risk factors and sample entropy (4) Standard risk factors, cumulative hypotension over time and sample entropy. RESULTS: Two hundred and thirteen (7.4%) cases developed postoperative acute kidney injury. The median and interquartile range for sample entropy of mean arterial pressure was 0.34 and [0.26, 0.42] respectively. C-statistics were identical between the random forest and L1 logistic regression models. Results demonstrated no improvement in discrimination of postoperative acute kidney injury with the addition of the sample entropy of mean arterial pressure: Standard risk factors: 0.81 [0.76, 0.85], Standard risk factors and hypotension over time indices: 0.80 [0.75, 0.85], Standard risk factors and sample entropy of mean arterial pressure: 0.81 [0.76, 0.85] and Standard risk factors, sample entropy of mean arterial pressure and hypotension over time indices: 0.81 [0.76, 0.86]. CONCLUSION: Assessment of very short-term blood pressure variability does not improve the discrimination of postoperative acute kidney injury in patients undergoing non-cardiac surgery in this sample.

The impact of intraoperative hypotension on postoperative acute kidney injury, mortality and length of stay following off-pump coronary artery bypass grafting surgery: a single-center retrospective cohort study.

BACKGROUND: Off-pump coronary artery bypass grafting (OPCABG) presents distinct hemodynamic characteristics, yet the relationship between intraoperative hypotension and short-term adverse outcomes remains clear. Our study aims to investigate association between intraoperative hypotension and postoperative acute kidney injury (AKI), mortality and length of stay in OPCABG patients. METHODS: Retrospective data of 494 patients underwent OPCABG from January 2016 to July 2023 were collected. We analyzed the relationship between intraoperative various hypotension absolute values (MAP > 75, 65 < MAP ≤ 75, 55 < MAP ≤ 65, MAP ≤ 55 mmHg) and postoperative AKI, mortality and length of stay. Logistic regression assessed the impacts of exposure variable on AKI and postoperative mortality. Linear regression was used to analyze risk factors on the length of intensive care unit stay (ICU) and hospital stay. RESULTS: The incidence of AKI was 31.8%, with in-hospital and 30-day mortality at 2.8% and 3.5%, respectively. Maintaining a MAP greater than or equal 65 mmHg [odds ratio (OR) 0.408; p = 0.008] and 75 mmHg (OR 0.479; p = 0.024) was significantly associated with a decrease risk of AKI compared to MAP less than 55 mmHg for at least 10 min. Prolonged hospital stays were linked to low MAP, while in-hospital mortality and 30-day mortality were not linked to IOH but exhibited correlation with a history of myocardial infarction. AKI showed correlation with length of ICU stay. CONCLUSIONS: MAP > 65 mmHg emerges as a significant independent protective factor for AKI in OPCABG and IOH is related to length of hospital stay. Proactive intervention targeting intraoperative hypotension may provide a potential opportunity to reduce postoperative renal injury and hospital stay. TRIAL REGISTRATION: ChiCTR2400082518. Registered 31 March 2024. https://www.chictr.org.cn/bin/project/edit?pid=225349 .

Intraoperative Blood Pressure Management and Its Effects on Postoperative Delirium After Cardiac Surgery: A Single-Center Retrospective Cohort Study.

OBJECTIVES: There is accumulating evidence that blood pressure management might be associated with end-organ dysfunction after cardiac surgery. This study aimed to investigate the impact of intraoperative hypotension (IOH) on adverse neurologic outcomes and mortality. DESIGN: A single-center retrospective cohort study. SETTING: The Heart and Diabetes Centre Bad Oeynhausen NRW, Ruhr-University Bochum. PARTICIPANTS: This retrospective cohort study included 31,315 adult patients who underwent elective cardiac surgery at the authors' institution between January 2009 and December 2018. INTERVENTIONS: All cardiac surgery procedures except assist device implantation, organ transplantation, and emergency surgery. MEASUREMENTS AND MAIN RESULTS: Adverse neurologic outcomes were defined as postoperative delirium and stroke. IOH was defined as mean arterial pressure below 60 mmHg for >2 minutes. The frequency of IOH episodes and the cumulative IOH duration were recorded. The association between IOH and adverse neurologic outcomes was examined with unadjusted statistical analysis and multiple logistic regression analysis. Eight hundred forty-nine (2.9%) patients developed postoperative stroke, and 2,401 (7.7%) patients developed postoperative delirium. The frequency of IOH episodes was independently associated with postoperative delirium in the multiple logistic regression analysis (odds ratio 1.02, 95% CI 1.003-1.03, p < 0.001), whereas there was no association between it and stroke. CONCLUSION: This large retrospective monocentric cohort study revealed that increased episodes of IOH were associated with the risk of developing postoperative delirium after cardiac surgery. This might have important clinical implications with respect to careful and precise hemodynamic monitoring and proactive treatment, especially in patients with increased risk for postoperative delirium.

Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.

PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive arterial blood pressure monitors. This study tested whether routine non-invasive monitors could also predict intraoperative hypotension using deep learning algorithms. METHODS: An open-source database of non-cardiac surgery patients ( https://vitadb.net/dataset ) was used to develop the deep learning algorithm. The algorithm was validated using external data obtained from a tertiary Korean hospital. Intraoperative hypotension was defined as a systolic blood pressure less than 90 mmHg. The input data included five monitors: non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and bispectral index. The primary outcome was the performance of the deep learning model as assessed by the area under the receiver operating characteristic curve (AUROC). RESULTS: Data from 4754 and 421 patients were used for algorithm development and external validation, respectively. The fully connected model of Multi-head Attention architecture and the Globally Attentive Locally Recurrent model with Focal Loss function were able to predict intraoperative hypotension 5 min before its occurrence. The AUROC of the algorithm was 0.917 (95% confidence interval [CI], 0.915-0.918) for the original data and 0.833 (95% CI, 0.830-0.836) for the external validation data. Attention map, which quantified the contributions of each monitor, showed that our algorithm utilized data from each monitor with weights ranging from 8 to 22% for determining hypotension. CONCLUSIONS: A deep learning model utilizing multi-channel non-invasive monitors could predict intraoperative hypotension with high accuracy. Future prospective studies are needed to determine whether this model can assist clinicians in preventing hypotension in patients undergoing surgery with non-invasive monitoring.

Accuracy and clinical utility of heart rate variability derived from a wearable heart rate monitor in patients undergoing major abdominal surgery.

Low heart rate variability (HRV) can potentially identify patients at risk of intraoperative hypotension. However, it is unclear whether cheaper, readily accessible consumer heart rate (HR) monitors can provide similar utility to clinical Holter electrocardiograph (ECG) monitors. The objectives of this study were (1) to assess the validity of using the Polar H10 HR monitor as an alternative to a clinical Holter ECG and (2) to test total power (TP) as a predictor of intraoperative hypotension. The primary outcome was the level of agreement between Polar H10 and Holter ECG. Twenty-three patients undergoing major abdominal surgery with general anesthesia had 5-minute HR recordings taken concurrently with both devices during a pre-anesthetic consultation. Agreement between Polar H10 and Holter ECG was compared via Bland-Altman analysis and Lin's Concordance Correlation Coefficient. Patients were divided into groups based on TP < 500 m s 2 and TP > 500 m s 2 . Intraoperative hypotension was defined as MAP < 60 mmHg, systolic blood pressure < 80 mmHg, or 35% decrease in MAP from baseline. There was substantial agreement between Polar H10 and Holter ECG for average R-R interval, TP and other HRV indices. Reduced TP (< 500 ms 2 ) had a high sensitivity (80%) and specificity (100%) in predicting intraoperative hypotension. Patients with reduced TP were significantly more likely to require vasoactive drugs to maintain blood pressure.The substantial agreement between Polar H10 and Holter ECG may justify its use clinically. The use of preoperative recordings of HRV has the potential to become part of routine preoperative assessment as a useful screening tool to predict hemodynamic instability in patients undergoing general anesthesia.

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.

Intraoperative arterial pressure management: knowns and unknowns.

Preventing postoperative organ dysfunction is integral to the practice of anaesthesia. Although intraoperative hypotension is associated with postoperative end organ dysfunction, there remains ambiguity with regards to its definition, targets, thresholds for initiating treatment, and ideal treatment modalities.

Endotypes of intraoperative hypotension during major abdominal surgery: a retrospective machine learning analysis of an observational cohort study.

BACKGROUND: Intraoperative hypotension is associated with myocardial injury, acute kidney injury, and death. In routine practice, specific causes of intraoperative hypotension are often unclear. A more detailed understanding of underlying haemodynamic alterations of intraoperative hypotension may identify specific treatments. We thus aimed to use machine learning - specifically, hierarchical clustering - to identify underlying haemodynamic alterations causing intraoperative hypotension in major abdominal surgery patients. Specifically, we tested the hypothesis that there are distinct endotypes of intraoperative hypotension, which may help refine therapeutic interventions. METHODS: We conducted a secondary analysis of intraoperative haemodynamic measurements from a prospective observational study in 100 patients who had major abdominal surgery under general anaesthesia. We used stroke volume index, heart rate, cardiac index, systemic vascular resistance index, and pulse pressure variation measurements. Intraoperative hypotension was defined as any mean arterial pressure ≤65 mm Hg or a mean arterial pressure between 66 and 75 mm Hg requiring a norepinephrine infusion rate exceeding 0.1 µg kg-1 min-1. To identify endotypes of intraoperative hypotension, we used hierarchical clustering (Ward's method). RESULTS: A total of 615 episodes of intraoperative hypotension occurred in 82 patients (46 [56%] female; median age: 64 [57, 73] yr) who had surgery of a median duration of 270 (195, 335) min. Hierarchical clustering revealed six distinct intraoperative hypotension endotypes. Based on their clinical characteristics, we labelled these endotypes as (1) myocardial depression, (2) bradycardia, (3) vasodilation with cardiac index increase, (4) vasodilation without cardiac index increase, (5) hypovolaemia, and (6) mixed type. CONCLUSION: Hierarchical clustering identified six endotypes of intraoperative hypotension. If validated, considering these intraoperative hypotension endotypes may enable causal treatment of intraoperative hypotension.

Intraoperative hypotension and postoperative outcomes: a meta-analysis of randomised trials.

INTRODUCTION: Intraoperative hypotension is associated with adverse postoperative outcomes; however these findings are supported only by observational studies. The aim of this meta-analysis of randomised trials was to compare the postoperative effects permissive management with targeted management of intraoperative blood pressure. METHODS: We searched PubMed, Cochrane, and Embase up to June 2023 for studies comparing permissive (mean arterial pressure ≤60 mm Hg) with targeted (mean arterial pressure >60 mm Hg) intraoperative blood pressure management. Primary outcome was all-cause mortality at the longest follow-up available. Secondary outcomes were atrial fibrillation, myocardial infarction, acute kidney injury, delirium, stroke, number of patients requiring transfusion, time on mechanical ventilation, and length of hospital stay. RESULTS: We included 10 randomised trials including a total of 9359 patients. Mortality was similar between permissive and targeted blood pressure management groups (89/4644 [1.9%] vs 99/4643 [2.1%], odds ratio 0.88, 95% confidence interval [CI], 0.65-1.18, P=0.38, I2=0% with nine studies included). Atrial fibrillation (102/3896 [2.6%] vs 130/3887 [3.3%] odds ratio 0.71, 95% CI 0.53-0.96, P=0.03, I2=0%), and length of hospital stay (mean difference -0.20 days, 95% CI -0.26 to -0.13, P<0.001, I2=0%) were reduced in the permissive management group. No significant differences were found in subgroup analysis for cardiac and noncardiac surgery. CONCLUSION: Pooled randomised evidence shows that a target intraoperative mean arterial pressure ≤60 mm Hg is not associated with increased mortality; nevertheless it is surprisingly associated with a reduced rate of atrial fibrillation and of length of hospital stay. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42023393725.

Predicting intraoperative hypotension: from hope to hype and back to reality.

The analysis of arterial pressure waveforms with machine learning algorithms has been proposed to predict intraoperative hypotension. The ability to forecast arterial hypotension 5-15 min ahead of the fall in blood pressure allows clinicians to be pro-active instead of reactive, and could potentially decrease postoperative morbidity. However, the predictive value of machine learning algorithms has been overestimated due to selection bias in several clinical studies, and they might not be superior to mere observation of arterial pressure. Continuous blood pressure monitoring enables immediate detection of hypotension, and giving fluid, vasopressors or inotropes to patients who are not yet (and might never become) hypotensive based on an algorithm is questionable. Finally, recent prospective interventional studies suggest that reducing intraoperative hypotension does not improve postoperative outcomes.

Norepinephrine versus phenylephrine for treating hypotension during general anaesthesia in adult patients undergoing major noncardiac surgery: a multicentre, open-label, cluster-randomised, crossover, feasibility, and pilot trial.

BACKGROUND: Intraoperative hypotension is associated with postoperative complications. The use of vasopressors is often required to correct hypotension but the best vasopressor is unknown. METHODS: A multicentre, cluster-randomised, crossover, feasibility and pilot trial was conducted across five hospitals in California. Phenylephrine (PE) vs norepinephrine (NE) infusion as the first-line vasopressor in patients under general anaesthesia alternated monthly at each hospital for 6 months. The primary endpoint was first-line vasopressor administration compliance of 80% or higher. Secondary endpoints were acute kidney injury (AKI), 30-day mortality, myocardial injury after noncardiac surgery (MINS), hospital length of stay, and rehospitalisation within 30 days. RESULTS: A total of 3626 patients were enrolled over 6 months; 1809 patients were randomised in the NE group, 1817 in the PE group. Overall, 88.2% received the assigned first-line vasopressor. No drug infiltrations requiring treatment were reported in either group. Patients were median 63 yr old, 50% female, and 58% white. Randomisation in the NE group vs PE group did not reduce readmission within 30 days (adjusted odds ratio=0.92; 95% confidence interval, 0.6-1.39), 30-day mortality (1.01; 0.48-2.09), AKI (1.1; 0.92-1.31), or MINS (1.63; 0.84-3.16). CONCLUSIONS: A large and diverse population undergoing major surgery under general anaesthesia was successfully enrolled and randomised to receive NE or PE infusion. This pilot and feasibility trial was not powered for adverse postoperative outcomes and a follow-up multicentre effectiveness trial is planned. CLINICAL TRIAL REGISTRATION: NCT04789330 (ClinicalTrials.gov).

Hypotension prediction index guided versus conventional goal directed therapy to reduce intraoperative hypotension during thoracic surgery: a randomized trial.

PURPOSE: Intraoperative hypotension is linked to increased incidence of perioperative adverse events such as myocardial and cerebrovascular infarction and acute kidney injury. Hypotension prediction index (HPI) is a novel machine learning guided algorithm which can predict hypotensive events using high fidelity analysis of pulse-wave contour. Goal of this trial is to determine whether use of HPI can reduce the number and duration of hypotensive events in patients undergoing major thoracic procedures. METHODS: Thirty four patients undergoing esophageal or lung resection were randomized into 2 groups -"machine learning algorithm" (AcumenIQ) and "conventional pulse contour analysis" (Flotrac). Analyzed variables were occurrence, severity and duration of hypotensive events (defined as a period of at least one minute of MAP below 65 mmHg), hemodynamic parameters at 9 different timepoints interesting from a hemodynamics viewpoint and laboratory (serum lactate levels, arterial blood gas) and clinical outcomes (duration of mechanical ventilation, ICU and hospital stay, occurrence of adverse events and in-hospital and 28-day mortality). RESULTS: Patients in the AcumenIQ group had significantly lower area below the hypotensive threshold (AUT, 2 vs 16.7 mmHg x minutes) and time-weighted AUT (TWA, 0.01 vs 0.08 mmHg). Also, there were less patients with hypotensive events and cumulative duration of hypotension in the AcumenIQ group. No significant difference between groups was found in terms of laboratory and clinical outcomes. CONCLUSIONS: Hemodynamic optimization guided by machine learning algorithm leads to a significant decrease in number and duration of hypotensive events compared to traditional goal directed therapy using pulse-contour analysis hemodynamic monitoring in patients undergoing major thoracic procedures. Further, larger studies are needed to determine true clinical utility of HPI guided hemodynamic monitoring. TRIAL REGISTRATION: Date of first registration: 14/11/2022 Registration number: 04729481-3a96-4763-a9d5-23fc45fb722d.

Factors to consider during anesthesia in patients undergoing preemptive kidney transplantation: a propensity-score matched analysis.

BACKGROUND: International guidelines have recommended preemptive kidney transplantation (KT) as the preferred approach, advocating for transplantation before the initiation of dialysis. This approach is advantageous for graft and patient survival by avoiding dialysis-related complications. However, recipients of preemptive KT may undergo anesthesia without the opportunity to optimize volume status or correct metabolic disturbances associated with end-stage renal disease. In these regard, we aimed to investigate the anesthetic events that occur more frequently during preemptive KT compared to nonpreemptive KT. METHODS: This is a single-center retrospective study. Of the 672 patients who underwent Living donor KT (LDKT), 388 of 519 who underwent nonpreemptive KT were matched with 153 of 153 who underwent preemptive KT using propensity score based on preoperative covariates. The primary outcome was intraoperative hypotension defined as area under the threshold (AUT), with a threshold set at a mean arterial blood pressure below 70 mmHg. The secondary outcomes were intraoperative metabolic acidosis estimated by base excess and serum bicarbonate, electrolyte imbalance, the use of inotropes or vasopressors, intraoperative transfusion, immediate graft function evaluated by the nadir creatinine, and re-operation due to bleeding. RESULTS: After propensity score matching, we analyzed 388 and 153 patients in non-preemptive and preemptive groups. The multivariable analysis revealed the AUT of the preemptive group to be significantly greater than that of the nonpreemptive group (mean ± standard deviation, 29.7 ± 61.5 and 14.5 ± 37.7, respectively, P = 0.007). Metabolic acidosis was more severe in the preemptive group compared to the nonpreemptive group. The differences in the nadir creatinine value and times to nadir creatinine were statistically significant, but clinically insignificant. CONCLUSION: Intraoperative hypotension and metabolic acidosis occurred more frequently in the preemptive group during LDKT. These findings highlight the need for anesthesiologists to be prepared and vigilant in managing these events during surgery.