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.

Stratospheric Night Sky Imaging Payload for Space Situational Awareness (SSA).

Space situational awareness (SSA) refers to collecting, analyzing, and keeping track of detailed knowledge of resident space objects (RSOs) in the space environment. With the rapidly increasing number of objects in space, the need for SSA grows as well. Traditional methods rely heavily on imaging RSOs from large, narrow field-of-view (FOV), ground-based telescopes. This research outlines the technology demonstration payload, Resident Space Object Near-space Astrometric Research (RSONAR)-a star tracker-like, wide FOV camera combined with commercial off-the-shelf (COTS) hardware to image RSOs from the stratosphere, overcoming the disadvantages of ground-based observations. The hardware components and software algorithm are described and evaluated. The eligibility of the payload for SSA is proven by the image processing algorithms, which detect the RSOs in the images captured during flight and the survival of the COTS components in the near-space environment. The payload features a low-resolution, wide FOV camera coupled with a Field Programmable Gate Array (FPGA)-based platform that houses the altitude and time-based image capture algorithm. The newly developed payload in a 2U-CubeSat form factor was flown as a space-ready payload on the CSA/CNES stratospheric balloon research platform to carry out algorithm and functionality tests in August 2022.

RSOnet: An Image-Processing Framework for a Dual-Purpose Star Tracker as an Opportunistic Space Surveillance Sensor.

A catalogue of over 22,000 objects in Earth's orbit is currently maintained, and that number is expected to double within the next decade. Novel data collection regimes are needed to scale our ability to detect, track, classify and characterize resident space objects in a crowded low Earth orbit. This research presents RSOnet, an image-processing framework for space domain awareness using star trackers. Star trackers are cost-effective, flight proven, and require basic image processing to be used as an attitude-determination sensor. RSOnet is designed to augment the capabilities of a star tracker by becoming an opportunistic space-surveillance sensor. Our research demonstrates that star trackers are a feasible source for RSO detections in LEO by demonstrating the performance of RSOnet on real detections from a star-tracker-like imager in space. RSOnet convolutional-neural-network model architecture, graph-based multi-object classifier and characterization results are described in this paper.

Simulation of RSO Images for Space Situation Awareness (SSA) Using Parallel Processing.

With the rapid increase in resident space objects (RSO), there is a growing demand for their identification and characterization to advance space simulation awareness (SSA) programs. Various AI-based technologies are proposed and demonstrated around the world to effectively and efficiently identify RSOs from ground and space-based observations; however, there remains a challenge in AI training due to the lack of labeled datasets for accurate RSO detection. In this paper, we present an overview of the starfield simulator to generate a realistic representation of images from space-borne imagers. In particular, we focus on low-resolution images such as those taken with a commercial-grade star tracker that contains various RSO in starfield images. The accuracy and computational efficiency of the simulator are compared to the commercial simulator, namely STK-EOIR to demonstrate the performance of the simulator. In comparing over 1000 images from the Fast Auroral Imager (FAI) onboard CASSIOPE satellite, the current simulator generates both stars and RSOs with approximately the same accuracy (compared to the real images) as STK-EOIR and, an order of magnitude faster in computational speed by leveraging parallel processing methodologies.

Cardiopulmonary Resuscitation in Intensive Care Unit Patients With Coronavirus Disease 2019.

Cardiopulmonary resuscitation (CPR) in patients with severe acute respiratory syndrome coronavirus-2-associated disease (coronavirus disease 2019) poses a unique challenge to health- care providers due to the risk of viral aerosolization and disease transmission. This has caused some centers to modify existing CPR procedures, limit the duration of CPR, or consider avoiding CPR altogether. In this review, the authors propose a procedure for CPR in the intensive care unit that minimizes the number of personnel in the immediate vicinity of the patient and conserves the use of scarce personal protective equipment. Highlighting the low likelihood of successful resuscitation in high-risk patients may prompt patients to decline CPR. The authors recommend the preemptive placement of central venous lines in high-risk patients with intravenous tubing extensions that allow for medication delivery from outside the patients' rooms. During CPR, this practice can be used to deliver critical medications without delay. The use of a mechanical compression system for CPR further reduces the risk of infectious exposure to health- care providers. Extracorporeal membrane oxygenation should be reserved for patients with few comorbidities and a single failing organ system. Reliable teleconferencing tools are essential to facilitate communication between providers inside and outside the patients' rooms. General principles regarding the ethics and peri-resuscitative management of coronavirus 2019 patients also are discussed.

Real time three-dimensional stress echocardiography: a new approach for assessing diastolic function.

OBJECTIVE: To assess the feasibility of utilizing real time three-dimensional echocardiography (RT3DE) for assessment of diastolic function during stress. METHODS: Rest and stress volumes were acquired in 24 patients and parameters of diastolic function-peak ventricular filling rate (PFR) and time to peak filling rate (TPFR)-were calculated. RESULTS: Calculation of diastolic parameters was feasible in all patients. Resting PFR correlated with end-diastolic (EDV) and stroke volumes and inversely with TPFR (r = 0.53, 0.66, -0.5). With stress, PFR increased by 93% and TPFR decreased by 23% (P < 0.001). Stress PFR correlated with stress heart rate, EDV and stroke volume (r = 0.52, 0.50, 0.62) while TPFR correlated inversely with heart rate (r =-0.71). The change in PFR with stress correlated with the change in stroke volume (r = 0.42), while the change in TPFR correlated with the change in end-systolic volume (ESV) (r = 0.43) and inversely with the change in diastolic blood pressure (r =-0.41). Rest and stress PFR and TPFR are independent of age, gender and blood pressure and the change in PFR is independent of stress heart rate or blood pressure. E/E' correlated with stress TPFR (r = 0.72) and change in TPFR (r = 0.67) and inversely with change in PFR (r =-0.67). CONCLUSIONS: RT3DE can assess diastolic function during stress by detecting changes in PFR and TPFR, independent of gender, age, and blood pressure. The changes in these parameters with stress are influenced by baseline filling pressures. Larger studies are required to validate the clinical significance of these observations.

Takotsubo Cardiomyopathy in a Coronavirus Disease-2019-Positive Patient: A Case Report.

Coronavirus disease 2019 (COVID-19) has a high incidence of cardiac involvement, commonly described as a new-onset cardiomyopathy. In this report, we describe a patient with a new manifestation of cardiac involvement in the setting of a COVID-19 diagnosis: that of takotsubo cardiomyopathy.