Detecting aortic valve stenosis based on the non-invasive blood pressure waveform-a proof of concept study.

The incidence of aortic valve stenosis (AoS) increases with age, and once diagnosed, symptomatic severe AoS has a yearly mortality rate of 25%. AoS is diagnosed with transthoracic echocardiography (TTE), however, this gold standard is time consuming and operator and acoustic window dependent. As AoS affects the arterial blood pressure waveform, AoS-specific waveform features might serve as a diagnostic tool. Aim of the present study was to develop a novel, non-invasive, AoS detection model based on blood pressures waveforms. This cross-sectional study included patients with AoS undergoing elective transcatheter or surgical aortic valve replacement. AoS was determined using TTE, and patients with no or mild AoS were labelled as patients without AoS, while patients with moderate or severe AoS were labelled as patients with AoS. Non-invasive blood pressure measurements were performed in awake patients. Ten minutes of consecutive data was collected. Several blood pressure-based features were derived, and the median, interquartile range, variance, and the 1st and 9th decile of the change of these features were calculated. The primary outcome was the development of a machine-learning model for AoS detection, investigating multiple classifiers and training on the area under the receiver-operating curve (AUROC). In total, 101 patients with AoS and 48 patients without AoS were included. Patients with AoS showed an increase in left ventricular ejection time (0.02 s, p = 0.001), a delayed maximum upstroke in the systolic phase (0.015 s, p < 0.001), and a delayed maximal systolic pressure (0.03 s, p < 0.001) compared to patients without AoS. With the logistic regression model, a sensitivity of 0.81, specificity of 0.67, and AUROC of 0.79 were found. The majority of the population without AoS was male (85%), whereas in the population with AoS this was evenly distributed (54% males). Age was significantly (5 years, p < 0.001) higher in the population with AoS. In the present study, we developed a novel model able to distinguish no to mild AoS from moderate to severe AoS, based on blood pressure features with high accuracy. Clinical registration number: The study entailing patients with TAVR treatment was registered at ClinicalTrials.gov (NCT03088787, https://clinicaltrials.gov/ct2/show/NCT03088787 ). The study with elective cardiac surgery patients was registered with the Netherland Trial Register (NL7810, https://trialsearch.who.int/Trial2.aspx?TrialID=NL7810 ).

Differences in the Incidence of Hypotension and Hypertension between Sexes during Non-Cardiac Surgery: A Systematic Review and Meta-Analysis.

Background: Major determinants of blood pressure (BP) include sex and age. In youth, females have lower BP than males, yet in advanced age, more pronounced BP increases result in higher average BPs in females over 65. This hypothesis-generating study explored whether age-related BP divergence impacts the incidence of sex-specific intraoperative hypotension (IOH) or hypertension. Methods: We systematically searched PubMed and Embase databases for studies reporting intraoperative BP in males and females in non-cardiac surgery. We analyzed between-sex differences in the incidence of IOH and intraoperative hypertension (primary endpoint). Results: Among 793 identified studies, 14 were included in this meta-analysis, comprising 1,110,636 patients (56% female). While sex was not associated with IOH overall (females: OR 1.10, 95%CI [0.98-1.23], I2 = 99%), a subset of studies with an average age ≥65 years showed increased exposure to IOH in females (OR 1.17, 95%CI [1.01-1.35], I2 = 94%). One study reported sex-specific differences in intraoperative hypertension, with a higher incidence in females (31% vs. 28%). Conclusions: While sex-specific reporting on intraoperative BP was limited, IOH did not differ between sexes. However, an exploratory subgroup analysis offers the hypothesis that females of advanced age may face an increased risk of IOH, warranting further investigation.

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).

Dynamic cerebral autoregulation during step-wise increases in blood pressure during anaesthesia: A nonrandomised interventional trial.

BACKGROUND: Classically, cerebral autoregulation (CA) entails cerebral blood flow (CBF) remaining constant by cerebrovascular tone adapting to fluctuations in mean arterial pressure (MAP) between ∼60 and ∼150 mmHg. However, this is not an on-off mechanism; previous work has suggested that vasomotor tone is proportionally related to CA function. During propofol-based anaesthesia, there is cerebrovascular vasoconstriction, and static CA remains intact. Sevoflurane-based anaesthesia induces cerebral vasodilation and attenuates CA dose-dependently. It is unclear how this translates to dynamic CA across a range of blood pressures in the autoregulatory range. OBJECTIVE: The aim of this study was to quantify the effect of step-wise increases in MAP between 60 and 100 mmHg, using phenylephrine, on dynamic CA during propofol- and sevoflurane-based anaesthesia. DESIGN: A nonrandomised interventional trial. SETTING: Single centre enrolment started on 11 January 2019 and ended on 23 September 2019. PATIENTS: We studied American Society of Anesthesiologists (ASA) I/II patients undergoing noncardiothoracic, nonneurosurgical and nonlaparoscopic surgery under general anaesthesia. INTERVENTION: In this study, cerebrovascular tone was manipulated in the autoregulatory range by increasing MAP step-wise using phenylephrine in patients receiving either propofol- or sevoflurane-based anaesthesia. MAP and mean middle cerebral artery blood velocity (MCA Vmean ) were measured in ASA I and II patients, anaesthetised with either propofol ( n  = 26) or sevoflurane ( n  = 28), during 10 mmHg step-wise increments of MAP between 60 and 100 mmHg. Static CA was determined by plotting 2-min averaged MCA Vmean versus MAP. Dynamic CA was determined using transfer function analysis and expressed as the phase lead (°) between MAP and MCA Vmean oscillations, created with positive pressure ventilation with a frequency of 6 min -1 . MAIN OUTCOMES: The primary outcome of this study was the response of dynamic CA during step-wise increases in MAP during propofol- and sevoflurane-based anaesthesia. RESULTS: MAP levels achieved per step-wise increments were comparable between anaesthesia regiment (63 ±â€Š3, 72 ±â€Š2, 80 ±â€Š2, 90 ±â€Š2, 100 ±â€Š3 mmHg, and 61 ±â€Š4, 71 ±â€Š2, 80 ±â€Š2, 89 ±â€Š2, 98 ±â€Š4 mmHg for propofol and sevoflurane, respectively). MCA Vmean increased more during step-wise MAP increments for sevoflurane compared to propofol ( P ≤0.001). Dynamic CA improved during propofol (0.73° mmHg -1 , 95% CI 0.51 to 0.95; P  ≤ 0.001)) and less pronounced during sevoflurane-based anaesthesia (0.21°â€ŠmmHg -1 (95% CI 0.01 to 0.42, P  = 0.04). CONCLUSIONS: During general anaesthesia, dynamic CA is dependent on MAP, also within the autoregulatory range. This phenomenon was more pronounced during propofol anaesthesia than during sevoflurane. TRIAL REGISTRATION: NCT03816072 ( https://clinicaltrials.gov/ct2/show/NCT03816072 ).

Surveillance of high-risk early postsurgical patients for real-time detection of complications using wireless monitoring (SHEPHERD study): results of a randomized multicenter stepped wedge cluster trial.

Background: Vital signs measurements on the ward are performed intermittently. This could lead to failure to rapidly detect patients with deteriorating vital signs and worsens long-term outcome. The aim of this study was to test the hypothesis that continuous wireless monitoring of vital signs on the postsurgical ward improves patient outcome. Methods: In this prospective, multicenter, stepped-wedge cluster randomized study, patients in the control group received standard monitoring. The intervention group received continuous wireless monitoring of heart rate, respiratory rate and temperature on top of standard care. Automated alerts indicating vital signs deviation from baseline were sent to ward nurses, triggering the calculation of a full early warning score followed. The primary outcome was the occurrence of new disability three months after surgery. Results: The study was terminated early (at 57% inclusion) due to COVID-19 restrictions. Therefore, only descriptive statistics are presented. A total of 747 patients were enrolled in this study and eligible for statistical analyses, 517 patients in the control group and 230 patients in the intervention group, the latter only from one hospital. New disability at three months after surgery occurred in 43.7% in the control group and in 39.1% in the intervention group (absolute difference 4.6%). Conclusion: This is the largest randomized controlled trial investigating continuous wireless monitoring in postoperative patients. While patients in the intervention group seemed to experience less (new) disability than patients in the control group, results remain inconclusive with regard to postoperative patient outcome due to premature study termination. Clinical trial registration: ClinicalTrials.gov, ID: NCT02957825.

Reducing postoperative fasting times by implementing a food service in the Post Anaesthesia Care Unit (PACU).

BACKGROUND & AIMS: Early oral postoperative nutrition is a proven beneficial element of postoperative care, resulting in improvement in quality of life and a shorter hospital stay. Guidelines state that postoperative oral nutrition can safely be started within the first hours after surgery. However, oral nutrition is mainly investigated starting from postoperative day one (POD1). This pragmatic study assessed whether a food service in the Post Anaesthesia Care Unit (PACU) may reduce postoperative fasting times on postoperative day zero (POD0) early after surgery on this high care unit. The primary outcome was postoperative fasting time in the PACU. Secondary outcomes were postoperative patient experiences and nutritional tolerance. METHODS: This pragmatic prospective before-after study, included adult patients with a planned overnight stay in the PACU, and without anticipated postoperative dietary restrictions. A food service was developed, allowing re-uptake of oral nutrition early after surgery, already at POD0. Postoperative fasting time in the PACU was defined as the duration of time between the moment of arrival at the PACU, until first postoperative intake or until 9 a.m. on POD1, when most patients were discharged to the surgical ward. Secondary outcomes such as postoperative patient experiences and nutritional tolerance were scored on POD0 at 8 p.m. and on POD1 at 8 a.m. RESULTS: A total of 235 patients were included, 119 in the pre-implementation (control) and 116 in the post-implementation (intervention) group. Mean postoperative fasting time was reduced by a mean of 6.0 h (95% CI 4.8-7.4, p-value ≤ .001), from 17.5 h in controls to 11.5 h in the intervention group. In the intervention group, 45% of patients had nutritional intake on POD0 (8 p.m.), increasing to 80% of patients on POD1 (8 a.m.), compared to no intake at both time-points in the control group. In the intervention group, average patient satisfaction increased over time. Flatus frequency was higher in the intervention group on POD1 (45% vs. 22%, p-value ≤ .001), while postoperative nausea and/or vomiting, and usage of anti-emetic medication were not different between groups. CONCLUSIONS: In a heterogeneous group of adult post-surgical patients with a planned overnight stay in the PACU, implementation of a food service resulted in a significant and clinically relevant reduction of postoperative fasting time, and increased patient satisfaction without compromising nutritional tolerance. Registered at www.isrctn.org with study ID ISRCTN17976930.

Effect of Hypotension Prediction Index-guided intraoperative haemodynamic care on depth and duration of postoperative hypotension: a sub-study of the Hypotension Prediction trial.

BACKGROUND: Intraoperative and postoperative hypotension are associated with morbidity and mortality. The Hypotension Prediction (HYPE) trial showed that the Hypotension Prediction Index (HPI) reduced the depth and duration of intraoperative hypotension (IOH), without excess use of intravenous fluid, vasopressor, and/or inotropic therapies. We hypothesised that intraoperative HPI-guided haemodynamic care would reduce the severity of postoperative hypotension in the PACU. METHODS: This was a sub-study of the HYPE study, in which 60 adults undergoing elective noncardiac surgery were allocated randomly to intraoperative HPI-guided or standard haemodynamic care. Blood pressure was measured using a radial intra-arterial catheter, which was connected to a FloTracIQ sensor. Hypotension was defined as MAP <65 mm Hg, and a hypotensive event was defined as MAP <65 mm Hg for at least 1 min. The primary outcome was the time-weighted average (TWA) of postoperative hypotension. Secondary outcomes were absolute incidence, area under threshold for hypotension, and percentage of time spent with MAP <65 mm Hg. RESULTS: Overall, 54/60 (90%) subjects (age 64 (8) yr; 44% female) completed the protocol, owing to failure of the FloTracIQ device in 6/60 (10%) patients. Intraoperative HPI-guided care was used in 28 subjects; 26 subjects were randomised to the control group. Postoperative hypotension occurred in 37/54 (68%) subjects. HPI-guided care did not reduce the median duration (TWA) of postoperative hypotension (adjusted median difference, vs standard of care: 0.118; 95% confidence interval [CI], 0-0.332; P=0.112). HPI-guidance reduced the percentage of time with MAP <65 mm Hg by 4.9% (adjusted median difference: -4.9; 95% CI, -11.7 to -0.01; P=0.046). CONCLUSIONS: Intraoperative HPI-guided haemodynamic care did not reduce the TWA of postoperative hypotension.

Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial.

Importance: Intraoperative hypotension is associated with increased morbidity and mortality. A machine learning-derived early warning system to predict hypotension shortly before it occurs has been developed and validated. Objective: To test whether the clinical application of the early warning system in combination with a hemodynamic diagnostic guidance and treatment protocol reduces intraoperative hypotension. Design, Setting, and Participants: Preliminary unblinded randomized clinical trial performed in a tertiary center in Amsterdam, the Netherlands, among adult patients scheduled for elective noncardiac surgery under general anesthesia and an indication for continuous invasive blood pressure monitoring, who were enrolled between May 2018 and March 2019. Hypotension was defined as a mean arterial pressure (MAP) below 65 mm Hg for at least 1 minute. Interventions: Patients were randomly assigned to receive either the early warning system (n = 34) or standard care (n = 34), with a goal MAP of at least 65 mm Hg in both groups. Main Outcomes and Measures: The primary outcome was time-weighted average of hypotension during surgery, with a unit of measure of millimeters of mercury. This was calculated as the depth of hypotension below a MAP of 65 mm Hg (in millimeters of mercury) × time spent below a MAP of 65 mm Hg (in minutes) divided by total duration of operation (in minutes). Results: Among 68 randomized patients, 60 (88%) completed the trial (median age, 64 [interquartile range {IQR}, 57-70] years; 26 [43%] women). The median length of surgery was 256 minutes (IQR, 213-430 minutes). The median time-weighted average of hypotension was 0.10 mm Hg (IQR, 0.01-0.43 mm Hg) in the intervention group vs 0.44 mm Hg (IQR, 0.23-0.72 mm Hg) in the control group, for a median difference of 0.38 mm Hg (95% CI, 0.14-0.43 mm Hg; P = .001). The median time of hypotension per patient was 8.0 minutes (IQR, 1.33-26.00 minutes) in the intervention group vs 32.7 minutes (IQR, 11.5-59.7 minutes) in the control group, for a median difference of 16.7 minutes (95% CI, 7.7-31.0 minutes; P < .001). In the intervention group, 0 serious adverse events resulting in death occurred vs 2 (7%) in the control group. Conclusions and Relevance: In this single-center preliminary study of patients undergoing elective noncardiac surgery, the use of a machine learning-derived early warning system compared with standard care resulted in less intraoperative hypotension. Further research with larger study populations in diverse settings is needed to understand the effect on additional patient outcomes and to fully assess safety and generalizability. Trial Registration: ClinicalTrials.gov Identifier: NCT03376347.