Definition and incidence of hypotension in intensive care unit patients, an international survey of the European Society of Intensive Care Medicine

Postoperative Hypotension After Cardiac Surgery Is Associated With Acute Kidney Injury

OBJECTIVES

To describe the incidence of postoperative hypotension in patients undergoing cardiac surgery during the first 12 hours in the intensive care unit (ICU) and any relationship between hypotension and the development of acute kidney injury (AKI).

DESIGN

This was a retrospective, observational cohort study.

SETTING

The study took place in a single-center tertiary teaching hospital in London, UK.

PARTICIPANTS

Adult patients (n = 100) who underwent elective cardiac surgery requiring intraoperative cardiopulmonary bypass between May and November 2021 were enrolled.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A hypotensive event was defined as mean arterial pressure <65 mmHg lasting at least 1 minute. Invasive blood pressure data was analyzed for the first 12 hours after surgery, and any association between postoperative hypotension and AKI was assessed. A total of 91% of patients experienced hypotension in the first 12 hours postprocedure. On average, patients experienced 9 hypotensive events, with events lasting an average of 5 minutes. A total of 16 patients (16%) developed at least stage 1 AKI. The average duration of hypotension was significantly higher in the AKI group (4.6 min [IQR 3.3, 8.0] v 8.1 min [IQR 5.2, 14.2], p = 0.029). Those suffering AKI had longer ICU and hospital stays.

CONCLUSIONS

This study demonstrated that hypotension in the first 12 hours following cardiac surgery is common and prolonged hypotensive events are associated with developing AKI. This emphasizes the importance of treating hypotension aggressively and highlights a target for further research and intervention.

Hypotension during intensive care stay and mortality and morbidity: a systematic review and meta-analysis

PURPOSE

The aim of this study is to provide a summary of the existing literature on the association between hypotension during intensive care unit (ICU) stay and mortality and morbidity, and to assess whether there is an exposure-severity relationship between hypotension exposure and patient outcomes.

METHODS

CENTRAL, Embase, and PubMed were searched up to October 2022 for articles that reported an association between hypotension during ICU stay and at least one of the 11 predefined outcomes. Two independent reviewers extracted the data and assessed the risk of bias. Results were gathered in a summary table and studies designed to investigate the hypotension-outcome relationship were included in the meta-analyses.

RESULTS

A total of 122 studies (176,329 patients) were included, with the number of studies varying per outcome between 0 and 82. The majority of articles reported associations in favor of 'no hypotension' for the outcomes mortality and acute kidney injury (AKI), and the strength of the association was related to the severity of hypotension in the majority of studies. Using meta-analysis, a significant association was found between hypotension and mortality (odds ratio: 1.45; 95% confidence interval (CI) 1.12-1.88; based on 13 studies and 34,829 patients), but not for AKI.

CONCLUSION

Exposure to hypotension during ICU stay was associated with increased mortality and AKI in the majority of included studies, and associations for both outcomes increased with increasing hypotension severity. The meta-analysis reinforced the descriptive findings regarding mortality but did not yield similar support for AKI.

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.

Feasibility of continuous non-invasive finger blood pressure monitoring in adult patients admitted to an intensive care unit: A retrospective cohort study

BACKGROUND

Arterial catheters are often used for blood pressure monitoring in the intensive care unit (ICU), but they can cause complications. Non-invasive continuous finger blood pressure monitors could serve as an alternative. However, failure to obtain finger blood pressure signals is reported in up to 12% of ICU patients.

OBJECTIVES

Our primary objective was to identify the success rate of finger blood pressure monitoring in ICU patients. Secondary objectives were to assess whether patient admission characteristics could be used to identify patients unsuitable for non-invasive blood pressure monitoring and to determine the quality of non-invasive blood pressure waveforms.

METHODS

Retrospective observational study conducted in a cohort of 499 ICU patients. When available, the signal quality of the first hour of finger measurement was determined using an open-source waveform algorithm.

RESULTS

Finger blood pressure signals were obtained in 94% of patients. These patients had a high quality blood pressure waveform for 84% of the measurement time. Patients without a finger blood pressure signal significantly more frequently had a history of kidney and vascular disease, were more often treated with inotropic agents, had lower hemoglobin levels, and had higher arterial lactate levels.

CONCLUSIONS

Finger blood pressure signals were obtained in nearly all ICU patients. Significant differences in baseline characteristics between patients with and without finger blood pressure signals were found, but they were not clinically relevant. The characteristics studied could therefore not be used to identify patients unsuitable for finger blood pressure monitoring.

Acute liver injury in COVID-19 patients hospitalized in the intensive care unit: Narrative review

In recent years, humanity has been confronted with a global pandemic due to coronavirus disease 2019 (COVID-19), which has caused an unprecedented health and economic crisis worldwide. Apart from the respiratory symptoms, which are considered the principal manifestations of COVID-19, it has been recognized that COVID-19 constitutes a systemic inflammatory process affecting multiple organ systems. Across the spectrum of organ involvement in COVID-19, acute liver injury (ALI) has been gradually gaining increasing attention by the international scientific community. COVID-19 associated liver impairment can affect a considerable proportion of COVID-19 patients and seems to correlate with the severity of the disease course. Indeed, COVID-19 patients hospitalized in the intensive care unit (ICU) run a greater risk of developing ALI due to the severity of their clinical condition and in the context of multi-organ failure. The putative pathophysiological mechanisms of COVID-19 induced ALI in ICU patients remain poorly understood and appear to be multifactorial in nature. Several theories have been proposed to explain the occurrence of ALI in the ICU setting, such as hypoperfusion and ischemia due to hemodynamic instability, passive liver congestion as a result of congestive heart failure, ischemia-reperfusion injury, hypoxia due to respiratory failure, mechanical ventilation itself, sepsis and septic shock, cytokine storm, endotheliitis with concomitant coagulopathy, drug-induced liver injury, parenteral nutrition and direct cytopathic viral effect. It should be noted that no specific therapy for COVID-19 induced ALI exists. Therefore, the therapeutic approach lies in preventive measures and is exclusively supportive once ALI ensues. The aim of the current review is to scrutinize the existing evidence on COVID-19 associated ALI in ICU patients, explore its clinical implications, shed light on the underlying pathophysiological mechanisms and propose potential therapeutic approaches. Ongoing research on the particular scientific field will further elucidate the pathophysiology behind ALI and address unresolved issues, in the hope of mitigating the tremendous health consequences imposed by COVID-19 on ICU patients.

Machine learning for predicting acute hypotension: A systematic review

An acute hypotensive episode (AHE) can lead to severe consequences and complications that threaten patients' lives within a short period of time. How to accurately and non-invasively predict AHE in advance has become a hot clinical topic that has attracted a lot of attention in the medical and engineering communities. In the last 20 years, with rapid advancements in machine learning methodology, this topic has been viewed from a different perspective. This review paper examines studies published from 2008 to 2021 that evaluated the performance of various machine learning algorithms developed to predict AHE. A total of 437 articles were found in four databases that were searched, and 35 full-text articles were included in this review. Fourteen machine learning algorithms were assessed in these 35 articles; the Support Vector Machine algorithm was studied in 12 articles, followed by Logistic Regression (six articles) and Artificial Neural Network (six articles). The accuracy of the algorithms ranged from 70 to 96%. The size of the study sample varied from small (12 subjects) to very large (3,825 subjects). Recommendations for future work are also discussed in this review.

Total Plasma Exchange in Neuromuscular Junction Disorders—A Single-Center, Retrospective Analysis of the Efficacy, Safety and Potential Diagnostic Properties in Doubtful Diagnosis

Neuromuscular junction disorders (NJDs) are a heterogeneous group of diseases including myasthenia gravis (MG). In some cases, patients are present with myasthenic symptoms without evidence of autoimmune antibodies, making diagnosis challenging. Total plasma exchange (TPE) has proven efficacy in NJDs. The objective is to describe the safety and efficacy of TPE in NJD patients with questionable disease activity or uncertain diagnosis in order to assess the diagnostic potential of TPE. We report an observational, retrospective cohort study of clinical routine data. All the data were derived from the electronic medical records of the Department of Neurology at University Hospital Essen. We searched for patients with NJDs between 1 July 2018 and 30 June 2021. Of the 303 patients who presented to the department with NJDs, 20 were treated with TPE; 9 patients did not show a measurable benefit from TPE (45%), 6 of whom were diagnosed with seronegative MG. Of these, 3 (50%) had long-standing ocular symptoms. There were decreases in the mean arterial pressure, hemoglobin, hematocrit and fibrinogen during treatment, which were not considered clinically relevant. In (seronegative) myasthenic patients, TPE may help to verify an uncertain diagnosis or to reveal possible muscle damage, allowing unnecessary therapy to be avoided.

Perioperative hypotension: causes and remedies

Background

Arterial hypotension is common in patients during surgery and those admitted to the intensive care unit (ICU) postoperatively. Perioperative arterial hypotension reportedly significantly affects surgical patients’ outcomes. Blood pressure level is the most crucial factor that influences organ perfusion. Hypoperfusion and organ dysfunction are correlated based on their severity associated with hypotension. As several factors can cause intraoperative hypotension, anesthetists must promptly identify the etiology for appropriate treatment and revert the patient’s hemodynamic profile.

Objectives

This review discusses the concept of perioperative hypotension, identifies its effects in clinical situations, and provides remedies and techniques to predict and avoid its significant consequences.

Conclusions

The primary determinant of organ perfusion is blood pressure. On the other hand, profound hypotension is common in surgical patients and is connected to hypoperfusion and organ failure. Currently, hypotension is addressed once low blood pressure levels are recorded. Early detection of oncoming hypotension or its clinical prediction is of paramount importance in allowing the clinician to treat hypotension and reduce the incidence and length of hypotensive episodes promptly and aggressively.

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.

Monitoring, management, and outcome of hypotension in Intensive Care Unit patients, an international survey of the European Society of Intensive Care Medicine

INTRODUCTION

Hypotension in the ICU is common, yet management is challenging and variable. Insight in management by ICU physicians and nurses may improve patient care and guide future hypotension treatment trials and guidelines.

METHODS

We conducted an international survey among ICU personnel to provide insight in monitoring, management, and perceived consequences of hypotension.

RESULTS

Out of 1464 respondents, 1197 (81.7%) were included (928 physicians (77.5%) and 269 nurses (22.5%)). The majority indicated that hypotension is underdiagnosed (55.4%) and largely preventable (58.8%). Nurses are primarily in charge of monitoring changes in blood pressure, physicians are in charge of hypotension treatment. Balanced crystalloids, dobutamine, norepinephrine, and Trendelenburg position were the most frequently reported fluid, inotrope, vasopressor, and positional maneuver used to treat hypotension. Reported complications believed to be related to hypotension were AKI and myocardial injury. Most ICUs do not have a specific hypotension treatment guideline or protocol (70.6%), but the majority would like to have one in the future (58.1%).

CONCLUSIONS

Both physicians and nurses report that hypotension in ICU patients is underdiagnosed, preventable, and believe that hypotension influences morbidity. Hypotension management is generally not protocolized, but the majority of respondents would like to have a specific hypotension management protocol.