Articles: mechanical-ventilation.
-
Severe burn patients undergo prolonged administration of sedatives and analgesics for burn care. There are currently no guidelines for the dose adaptation of sedation-analgesia in severe burn patients. ⋯ Scale-based lightening of continuous sedation-analgesia with repeated short general anesthesia for dressing is feasible in severe burn patients but failed to demonstrate a decrease in the duration of invasive mechanical ventilation.
-
Am. J. Respir. Crit. Care Med. · Sep 2020
Observational StudyPulmonary Angiopathy in Severe COVID-19: Physiologic, Imaging and Hematologic Observations.
Rationale: Clinical and epidemiologic data in coronavirus disease (COVID-19) have accrued rapidly since the outbreak, but few address the underlying pathophysiology. Objectives: To ascertain the physiologic, hematologic, and imaging basis of lung injury in severe COVID-19 pneumonia. Methods: Clinical, physiologic, and laboratory data were collated. ⋯ Dilated peripheral vessels were present in 21/33 (63.6%) patients with at least two assessable lobes (including 10/21 [47.6%] with no evidence of acute pulmonary emboli). Perfusion defects on DECT (assessable in 18/20 [90%]) were present in all patients (wedge-shaped, n = 3; mottled, n = 9; mixed pattern, n = 6). Conclusions: Physiologic, hematologic, and imaging data show not only the presence of a hypercoagulable phenotype in severe COVID-19 pneumonia but also markedly impaired pulmonary perfusion likely caused by pulmonary angiopathy and thrombosis.
-
COVID-19 is devastating health systems globally and causing severe ventilator shortages. Since the beginning of the outbreak, the provision and use of ventilators has been a key focus of public discourse. Scientists and engineers from leading universities and companies have rushed to develop low-cost ventilators in hopes of supporting critically ill patients in developing countries. ⋯ Health care workers in many low-resource settings are already exceedingly overburdened, and pulling these essential human resources away from other critical patient needs could reduce the overall quality of patient care. When deploying medical devices, it is vital to align the technological intervention with the clinical reality. Low-income settings often will not benefit from resource-intensive equipment, but rather from contextually appropriate devices that meet the unique needs of their health systems.
-
Multicenter Study Clinical Trial
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial.
Currently, physicians are limited in their ability to provide an accurate prognosis for COVID-19 positive patients. Existing scoring systems have been ineffective for identifying patient decompensation. Machine learning (ML) may offer an alternative strategy. A prospectively validated method to predict the need for ventilation in COVID-19 patients is essential to help triage patients, allocate resources, and prevent emergency intubations and their associated risks. ⋯ In the first clinical trial of a machine learning algorithm for ventilation needs among COVID-19 patients, the algorithm demonstrated accurate prediction of the need for mechanical ventilation within 24 h. This algorithm may help care teams effectively triage patients and allocate resources. Further, the algorithm is capable of accurately identifying 16% more patients than a widely used scoring system while minimizing false positive results.