Performance of a Machine Learning Algorithm to Predict Hypotension in Spontaneously Breathing Non-Ventilated Post-Anesthesia and ICU Patients.

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

Chronic post amputation pain: pathophysiology and prevention options for a heterogenous phenomenon.

PURPOSE OF REVIEW: Chronic postamputation pain (cPAP) remains a clinical challenge, and current understanding places a high emphasis on prevention strategies. Unfortunately, there is still no evidence-based regimen to reliably prevent chronic pain after amputation. RECENT FINDINGS: Risk factors for the development of phantom limb pain have been proposed. Analgesic preventive interventions are numerous and no silver bullet has been found. Novel techniques such as neuromodulation and cryoablation have been proposed. Surgical techniques focusing on reimplantation of the injured nerve might reduce the incidence of phantom limb pain after surgery. SUMMARY: Phantom limb pain is a multifactorial process involving profound functional and structural changes in the peripheral and central nervous system. These changes interact with individual medical, psychosocial and genetic patient risk factors. The patient collective of amputees is very heterogeneous. Available evidence suggests that efforts should focus on prevention of phantom limb pain, since treatment is notoriously difficult. Questions as yet unanswered include the evidence-base of specific analgesic interventions, their optimal "window of opportunity" where they may be most effective, and whether patient stratification according to biopsychosocial risk factors can help guide preventive therapy.

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).

Feasibility to estimate mean systemic filling pressure with inspiratory holds at the bedside.

Background: A decade ago, it became possible to derive mean systemic filling pressure (MSFP) at the bedside using the inspiratory hold maneuver. MSFP has the potential to help guide hemodynamic care, but the estimation is not yet implemented in common clinical practice. In this study, we assessed the ability of MSFP, vascular compliance (Csys), and stressed volume (Vs) to track fluid boluses. Second, we assessed the feasibility of implementation of MSFP in the intensive care unit (ICU). Exploratory, a potential difference in MSFP response between colloids and crystalloids was assessed. Methods: This was a prospective cohort study in adult patients admitted to the ICU after cardiac surgery. The MSFP was determined using 3-4 inspiratory holds with incremental pressures (maximum 35 cm H2O) to construct a venous return curve. Two fluid boluses were administered: 100 and 500 ml, enabling to calculate Vs and Csys. Patients were randomized to crystalloid or colloid fluid administration. Trained ICU consultants acted as study supervisors, and protocol deviations were recorded. Results: A total of 20 patients completed the trial. MSFP was able to track the 500 ml bolus (p < 0.001). In 16 patients (80%), Vs and Csys could be determined. Vs had a median of 2029 ml (IQR 1605-3164), and Csys had a median of 73 ml mmHg-1 (IQR 56-133). A difference in response between crystalloids and colloids was present for the 100 ml fluid bolus (p = 0.019) and in a post hoc analysis, also for the 500 ml bolus (p = 0.010). Conclusion: MSFP can be measured at the bedside and provides insights into the hemodynamic status of a patient that are currently missing. The clinical feasibility of Vs and Csys was judged ambiguously based on the lack of required hemodynamic stability. Future studies should address the clinical obstacles found in this study, and less-invasive alternatives to determine MSFP should be further explored. Clinical Trial Registration: ClinicalTrials.gov Identifier NCT03139929.

Incidence, Severity and Clinical Factors Associated with Hypotension in Patients Admitted to an Intensive Care Unit: A Prospective Observational Study.

Background: The majority of patients admitted to the intensive care unit (ICU) experience severe hypotension which is associated with increased morbidity and mortality. At present, prospective studies examining the incidence and severity of hypotension using continuous waveforms are missing. Methods: This study is a prospective observational cohort study in a mixed surgical and non-surgical ICU population. All patients over 18 years were included and continuous arterial pressure waveforms data were collected. Mean arterial pressure (MAP) below 65 mmHg for at least 10 s was defined as hypotension and a MAP below 45 mmHg as severe hypotension. The primary outcome was the incidence of hypotension. Secondary outcomes were the severity of hypotension expressed in time-weighted average (TWA), factors associated with hypotension, the number and duration of hypotensive events. Results: 499 patients were included. The incidence of hypotension (MAP < 65 mmHg) was 75% (376 out of 499) and 9% (46 out of 499) experienced severe hypotension. Median TWA was 0.3 mmHg [0−1.0]. Associated clinical factors were age, male sex, BMI and cardiogenic shock. There were 5 (1−12) events per patients with a median of 52 min (5−170). Conclusions: In a mixed surgical and non-surgical ICU population the incidence of hypotension is remarkably high.

Autologous red blood cell transfusion does not result in a more profound increase in pulmonary capillary wedge pressure compared to saline in critically ill patients: A randomized crossover trial.

BACKGROUND AND OBJECTIVES: Transfusion-associated circulatory overload (TACO) is a major cause of severe transfusion-related morbidity. Transfusion of red blood cells (RBCs) has been shown to induce hydrostatic pressure overload. It is unclear which product-specific factors contribute. We set out to determine the effect of autologous RBC transfusion versus saline on pulmonary capillary wedge pressure (PCWP) change. MATERIALS AND METHODS: In a randomized crossover trial, patients who had undergone coronary bypass surgery were allocated to treatment post-operatively in the intensive care unit with either an initial 300 ml autologous RBC transfusion (salvaged during surgery) or 300 ml saline infusion first, followed by the other. Primary outcome was the difference in PCWP change. Secondary outcome measures were the difference in extra-vascular lung water index (EVLWI) and pulmonary vascular permeability index (PVPI). RESULTS: Change in PCWP was not higher after autologous RBC transfusion compared to saline (ΔPCWP 0.3 ± 0.4 vs. 0.1 ± 0.4 mmHg). ΔEVLWI and ΔPVPI were significantly decreased after autologous RBC transfusion compared to saline (ΔEVLWI -1.6 ± 0.6 vs. 0.2 ± 0.4, p = 0.02; ΔPVPI -0.3 ± 0.1 vs. 0.0 ± 0.1, p = 0.01). Haemodynamic variables and colloid osmotic pressure were not different for autologous RBC transfusion versus saline. CONCLUSION: Transfusion of autologous RBCs did not result in a more profound increase in PCWP compared to saline. RBC transfusion resulted in a decrease of EVLWI and PVPI compared to saline. Our data suggest that transfusing autologous RBCs may lead to less pulmonary oedema compared to saline. Future studies with allogeneic RBCs are needed to investigate other factors that may mediate the increase of PCWP, resulting in TACO.

Anesthesia Considerations in Infective Endocarditis.

The management of infective endocarditis is complex and inherently requires multidisciplinary cooperation. About half of all patients diagnosed with infective endocarditis will meet the criteria to undergo cardiac surgery, which regularly takes place in urgent or emergency settings. The pathophysiology and clinical presentation of infective endocarditis make it a unique disorder within cardiac surgery that warrants a thorough understanding of specific characteristics in the perioperative period. This includes, among others, echocardiography, coagulation, bleeding management, or treatment of organ dysfunction. In this narrative review article, the authors summarize the current knowledge on infective endocarditis relevant for the clinical anesthesiologist in perioperative management of respective patients. Furthermore, the authors advocate for the anesthesiologist to become a structural member of the endocarditis team.

Performance of a machine-learning algorithm to predict hypotension in mechanically ventilated patients with COVID-19 admitted to the intensive care unit: a cohort study.

The Hypotension Prediction Index (HPI) is a commercially available machine-learning algorithm that provides warnings for impending hypotension, based on real-time arterial waveform analysis. The HPI was developed with arterial waveform data of surgical and intensive care unit (ICU) patients, but has never been externally validated in the latter group. In this study, we evaluated diagnostic ability of the HPI with invasively collected arterial blood pressure data in 41 patients with COVID-19 admitted to the ICU for mechanical ventilation. Predictive ability was evaluated at HPI thresholds from 0 to 100, at incremental intervals of 5. After exceeding the studied threshold, the next 20 min were screened for positive (mean arterial pressure (MAP) < 65 mmHg for at least 1 min) or negative (absence of MAP < 65 mmHg for at least 1 min) events. Subsequently, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and time to event were determined for every threshold. Almost all patients (93%) experienced at least one hypotensive event. Median number of events was 21 [7-54] and time spent in hypotension was 114 min [20-303]. The optimal threshold was 90, with a sensitivity of 0.91 (95% confidence interval 0.81-0.98), specificity of 0.87 (0.81-0.92), PPV of 0.69 (0.61-0.77), NPV of 0.99 (0.97-1.00), and median time to event of 3.93 min (3.72-4.15). Discrimination ability of the HPI was excellent, with an area under the curve of 0.95 (0.93-0.97). This validation study shows that the HPI correctly predicts hypotension in mechanically ventilated COVID-19 patients in the ICU, and provides a basis for future studies to assess whether hypotension can be reduced in ICU patients using this algorithm.

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.