Between 4 and 22% of burn patients presenting to the emergency department are admitted to critical care. Burn injury is characterised by a hypermetabolic response with physiologic, catabolic and immune effects. Burn care has seen renewed interest in colloid resuscitation, a change in transfusion practice and the development of anti-catabolic therapies. A literature search was conducted with priority given to review articles, meta-analyses and well-designed large trials; paediatric studies were included where adult studies were lacking with the aim to review the advances in adult intensive care burn management and place them in the general context of day-to-day practical burn management.
Introduction The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing COVID-19 with federated analyses of electronic health record (EHR) data. Objective We sought to develop and validate a computable phenotype for COVID-19 severity. Methods Twelve 4CE sites participated. First we developed an EHR-based severity phenotype consisting of six code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of ICU admission and/or death. We also piloted an alternative machine-learning approach and compared selected predictors of severity to the 4CE phenotype at one site. Results The full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability - up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean AUC 0.903 (95% CI: 0.886, 0.921), compared to AUC 0.956 (95% CI: 0.952, 0.959) for the machine-learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared to chart review. Discussion We developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine-learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly due to heterogeneous pandemic conditions. Conclusion We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.
Introduction. The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) includes hundreds of hospitals internationally using a federated computational approach to COVID-19 research using the EHR. Objective. We sought to develop and validate a standard definition of COVID-19 severity from readily accessible EHR data across the Consortium. Methods. We developed an EHR-based severity algorithm and validated it on patient hospitalization data from 12 4CE clinical sites against the outcomes of ICU admission and/or death. We also used a machine learning approach to compare selected predictors of severity to the 4CE algorithm at one site. Results. The 4CE severity algorithm performed with pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of single code categories for acuity were unacceptably inaccurate - varying by up to 0.65 across sites. A multivariate machine learning approach identified codes resulting in mean AUC 0.956 (95% CI: 0.952, 0.959) compared to 0.903 (95% CI: 0.886, 0.921) using expert-derived codes. Billing codes were poor proxies of ICU admission, with 49% precision and recall compared against chart review at one partner institution. Discussion. We developed a proxy measure of severity that proved resilient to coding variability internationally by using a set of 6 code classes. In contrast, machine-learning approaches may tend to overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold standard outcomes, possibly due to pandemic conditions. Conclusion. We developed an EHR-based algorithm for COVID-19 severity and validated it at 12 international sites.
The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09–1.55), heart failure (RR 1.22, 95% CI 1.10–1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07–1.31), and fatigue (RR 1.18, 95% CI 1.07–1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58–2.76), venous embolism (RR 1.34, 95% CI 1.17–1.54), atrial fibrillation (RR 1.30, 95% CI 1.13–1.50), type 2 diabetes (RR 1.26, 95% CI 1.16–1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09–1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90–3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21–2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04–1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.
BackgroundDental injury is a common perioperative complication, but there are no country specific data available, especially with the use of supraglottic airway devices (SAD). The aims of our study are to report the incidence, risk factors, and local practices in the management of perioperative dental injuries in Singapore.MethodsWe analyzed data from the departmental database from 2011 to 2014, noting the anticipated difficulty of airway instrumentation, intubation grade, pre-existing dental risk factors, location of dental trauma discovery, position of teeth injured and presence of dental referral. The risk factors for dental trauma were then identified using logistic regression (between 51 dental trauma patients and 55,107 patients without dental trauma).ResultsThe rate of dental injury was 0.092% for general anaesthesia cases. The most significant patient risk factor is the presence of pre-existing dental risk factors (OR 12.55). Anaesthetic risk factors include McGrath MAC usage (OR 2.51) and a Cormack and Lehane grade of 3 or more (OR 7.25). Most of the dental injuries were discovered in the operating theatre. 7 (13.7%) patients had SAD inserted and only 23 (45.1%) cases were referred to dental services.ConclusionVideolaryngoscopy with the McGrath MAC is associated with an increased likelihood of dental injury. This could be either because videolarygoscopes were used when increased risk of dental trauma was anticipated, or due to incorrect technique of laryngoscopy. Future studies should be done to establish the causality. The management of dental injuries could be improved with development of departmental guidelines.
The term PRIS-propofol infusion syndromewas originally coined by Bray in 1998 to describe the adverse effects associated with the use of propofol in the paediatric population. PRIS was defined as acute refractory bradycardia leading to asystole in the presence of one or more of the following: metabolic acidosis (base excess of 210 mmol litre 21), rhabdomyolysis or myoglobinuria, lipaemic plasma, or enlarged liver or fatty liver. 1 Although first described in the paediatric population, it has been increasingly reported in adult intensive care patients, particularly in neurointensive care. The safe dose of propofol infusion for sedation in intensive care is considered to be 1-4 mg kg 21 h 21 , but fatal cases of PRIS have been reported after infusion doses as low as 1.9-2.6 mg kg 21 h 21 as well, promoting the idea that genetic factors may have a role to play.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.