Intraoperative prediction of postanaesthesia care unit hypotension.

BACKGROUND: Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinician prediction of PACU hypotension, clinician acceptance of prediction models is poorly understood. METHODS: We developed a clinically informed gradient boosting machine learning model using preoperative and intraoperative data from 88 446 surgical patients from 2015 to 2019. Nine anaesthesiologists each made 192 predictions of PACU hypotension using a web-based visualisation tool with and without input from the machine learning model. Questionnaires and interviews were analysed using thematic content analysis for model acceptance by anaesthesiologists. RESULTS: The model predicted PACU hypotension in 17 029 patients (area under the receiver operating characteristic [AUROC] 0.82 [95% confidence interval {CI}: 0.81-0.83] and average precision 0.40 [95% CI: 0.38-0.42]). On a random representative subset of 192 cases, anaesthesiologist performance improved from AUROC 0.67 (95% CI: 0.60-0.73) to AUROC 0.74 (95% CI: 0.68-0.79) with model predictions and information on risk factors. Anaesthesiologists perceived more value and expressed trust in the prediction model for prospective planning, informing PACU handoffs, and drawing attention to unexpected cases of PACU hypotension, but they doubted the model when predictions and associated features were not aligned with clinical judgement. Anaesthesiologists expressed interest in patient-specific thresholds for defining and treating postoperative hypotension. CONCLUSIONS: The ability of anaesthesiologists to predict PACU hypotension was improved by exposure to machine learning model predictions. Clinicians acknowledged value and trust in machine learning technology. Increasing familiarity with clinical use of model predictions is needed for effective integration into perioperative workflows.

Initial Clinical Impressions of the Critical Care of COVID-19 Patients in Seattle, New York City, and Chicago.

Since the first recognition of a cluster of novel respiratory viral infections in China in late December 2019, intensivists in the United States have watched with growing concern as infections with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus-now named coronavirus disease of 2019 (COVID-19)-have spread to hospitals in the United States. Because COVID-19 is extremely transmissible and can progress to a severe form of respiratory failure, the potential to overwhelm available critical care resources is high and critical care management of COVID-19 patients has been thrust into the spotlight. COVID-19 arrived in the United States in January and, as anticipated, has dramatically increased the usage of critical care resources. Three of the hardest-hit cities have been Seattle, New York City, and Chicago with a combined total of over 14,000 cases as of March 23, 2020.In this special article, we describe initial clinical impressions of critical care of COVID-19 in these areas, with attention to clinical presentation, laboratory values, organ system effects, treatment strategies, and resource management. We highlight clinical observations that align with or differ from already published reports. These impressions represent only the early empiric experience of the authors and are not intended to serve as recommendations or guidelines for practice, but rather as a starting point for intensivists preparing to address COVID-19 when it arrives in their community.

Closed-loop strategies for patient care systems.

Military operations, mass casualty events, and remote work sites present unique challenges to providers of immediate medical care, who may lack the necessary skills for optimal clinical management. Moreover, the number of patients in these scenarios may overwhelm available health care resources. Recent applications of closed-loop control (CLC) techniques to critical care medicine may offer possible solutions for such environments. Here, feedback of a monitored variable or group of variables is used to control the state or output of a dynamic system. Some potential advantages of CLC in patient management include limiting task saturation when there is simultaneous demand for cognitive and active clinical intervention, improving quality of care through optimization of the titration of medications, conserving limited consumable supplies, preventing secondary insults in traumatic brain injury, shortening the duration of mechanical ventilation, and achieving appropriate goal-directed resuscitation. The uses of CLC systems in critical care medicine have been increasingly explored across a wide range of therapeutic modalities. This review will provide an overview of control system theory as applied to critical care medicine that must be considered in the design of autonomous CLC systems, and introduce a number of clinical applications under development in the context of deployment of such applications to austere environments.

Considerations in the aeromedical evacuation of a critically ill blast victim: lessons learned.

Rationale for the decision to transport and assessment of available resources are integral components of the decision for aeromedical evacuation of critically ill patients. We present the case of a 20-year-old man who sustained significant trauma after his vehicle struck a land mine. This case reviews and emphasizes the factors to consider in arriving at the decision to transport as well as the accurate assessment of available equipment and personnel resources.

High Dose, Prolonged Epsilon Aminocaproic Acid Infusion, and Recombinant Factor VII for Massive Postoperative Retroperitoneal Hemorrhage following Splenectomy.

The antifibrinolytic agent ε-aminocaproic acid is used to decrease procedural blood loss in a variety of high risk surgeries. The utility of recombinant factor VII administration in massive hemorrhage has also been reported in a variety of settings, though the impact in a surgical context remains unclear. We describe the case of a patient who underwent massive open splenectomy and developed diffuse retroperitoneal bleeding on postoperative day one. Massive transfusion was initiated, but attempts to control hemorrhage with surgical and interventional radiology approaches were unsuccessful, as was recombinant factor VII administration. Commencement of a high dose aminocaproic acid infusion was followed by a prominent rise in fibrinogen levels and stabilization of the hemorrhage. Indications, dosages, and adverse effects of ε-aminocaproic acid as described in the literature are reviewed.

Case report: vancomycin-induced thrombocytopenia in a burn patient.

OBJECTIVE: Report an unusual cause of thrombocytopenia in a burn patient and provide a brief review of causes of thrombocytopenia in critically ill patients. METHODS: Case report format and selected review of PubMed search including the search terms thrombocytopenia, critical illness, and vancomycin. RESULTS: Reports of vancomycin-induced thrombocytopenia are uncommon. CONCLUSION: Drug-induced thrombocytopenia is a rare but important consideration in the evaluation of thrombocytopenia in critically ill patients. An increasing number of patients are treated with potentially causative agents including vancomycin and the diagnosis may be easily overlooked.

Economic stress and misaligned incentives in critical care medicine in the United States.

OBJECTIVES: This review will provide an overview of issues with economic ramifications intrinsic to the management of intensive care resources and identify some of the external pressures that ultimately influence the provision of intensive care services. DESIGN: A review of the current literature was performed. RESULTS: Economic stress is a reality of the management of intensive care resources. The nature of critical care medicine as a technologically heavy, labor intensive, high-cost, limited resource, combined with a projected increase in demand in an era of cost containment, presents an array of challenges. CONCLUSIONS: It is in the best interest of the care of our patients that critical care providers increase awareness of the many factors influencing our practice economically. It is through such understanding that challenges can be met, solutions can be found, and the quality of intensive care can be improved in a financially sustainable environment.

Recovery room delirium predicts postoperative delirium after hip-fracture repair.

UNLABELLED: In this study, we sought to determine the incidence of recovery room delirium in elderly patients having hip-fracture repair under general anesthesia and to discover whether recovery room delirium is associated with continuing postoperative delirium. In this prospective study, patients undergoing hip-fracture repair were anesthetized using a standardized protocol. In addition, postoperative pain management was standardized in both the postoperative anesthesia care unit and in the hospital ward. The presence of delirium was determined using the confusion assessment method (CAM) score. Recovery room delirium was assessed by obtaining a CAM score at 60 min after discontinuation of isoflurane. Postoperative delirium was assessed by obtaining a daily CAM score during the postoperative in-hospital recovery period. Fifty patients consented to the study and 47 patients were included in the analysis (surgery cancelled postinduction n = 1; nonadherence to protocol n = 2). Average patient age was 77 +/- 1 (mean +/- SE) yr (range, 56-98 yr). Seventy-seven percent of the study patients were ASA class III or more. The prevalence of recovery room delirium was 45%. The prevalence of postoperative delirium was 36%. Recovery room delirium predicted postoperative delirium (P < 0.001, Fisher's exact test) with a sensitivity of 100% and a specificity of 85%. Analgesic doses administered in the postoperative anesthesia care unit and ward were similar in patients with or without postoperative delirium. Results of this study show that recovery room delirium is a strong predictor of postoperative delirium. IMPLICATIONS: In patients undergoing hip-fracture repair, recovery room delirium is a strong predictor of postoperative delirium when using a standardized protocol for general anesthesia and postoperative pain management.