Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact.

INTRODUCTION: For early detection of sepsis, automated systems within the electronic health record have evolved to alert emergency department (ED) personnel to the possibility of sepsis, and in some cases link them to suggested care pathways. We conducted a systematic review of automated sepsis-alert detection systems in the ED. METHODS: We searched multiple health literature databases from the earliest available dates to August 2018. Articles were screened based on abstract, again via manuscript, and further narrowed with set inclusion criteria: 1) adult patients in the ED diagnosed with sepsis, severe sepsis, or septic shock; 2) an electronic system that alerts a healthcare provider of sepsis in real or near-real time; and 3) measures of diagnostic accuracy or quality of sepsis alerts. The final, detailed review was guided by QUADAS-2 and GRADE criteria. We tracked all articles using an online tool (Covidence), and the review was registered with PROSPERO registry of reviews. A two-author consensus was reached at the article choice stage and final review stage. Due to the variation in alert criteria and methods of sepsis diagnosis confirmation, the data were not combined for meta-analysis. RESULTS: We screened 693 articles by title and abstract and 20 by full text; we then selected 10 for the study. The articles were published between 2009-2018. Two studies had algorithm-based alert systems, while eight had rule-based alert systems. All systems used different criteria based on systemic inflammatory response syndrome (SIRS) to define sepsis. Sensitivities ranged from 10-100%, specificities from 78-99%, and positive predictive value from 5.8-54%. Negative predictive value was consistently high at 99-100%. Studies showed some evidence for improved process-of-care markers, including improved time to antibiotics. Length of stay improved in two studies. One low quality study showed improved mortality. CONCLUSION: The limited evidence available suggests that sepsis alerts in the ED setting can be set to high sensitivity. No high-quality studies showed a difference in mortality, but evidence exists for improvements in process of care. Significant further work is needed to understand the consequences of alert fatigue and sensitivity set points.

Development and Validation of the COVID-NoLab and COVID-SimpleLab Risk Scores for Prognosis in 6 US Health Systems.

PURPOSE: Develop and validate simple risk scores based on initial clinical data and no or minimal laboratory testing to predict mortality in hospitalized adults with COVID-19. METHODS: We gathered clinical and initial laboratory variables on consecutive inpatients with COVID-19 who had either died or been discharged alive at 6 US health centers. Logistic regression was used to develop a predictive model using no laboratory values (COVID-NoLab) and one adding tests available in many outpatient settings (COVID-SimpleLab). The models were converted to point scores and their accuracy evaluated in an internal validation group. RESULTS: We identified 1340 adult inpatients with complete data for nonlaboratory parameters and 741 with complete data for white blood cell (WBC) count, differential, c-reactive protein (CRP), and serum creatinine. The COVID-NoLab risk score includes age, respiratory rate, and oxygen saturation and identified risk groups with 0.8%, 11.4%, and 40.4% mortality in the validation group (AUROCC = 0.803). The COVID-SimpleLab score includes age, respiratory rate, oxygen saturation, WBC, CRP, serum creatinine, and comorbid asthma and identified risk groups with 1.0%, 9.1%, and 29.3% mortality in the validation group (AUROCC = 0.833). CONCLUSIONS: Because they use simple, readily available predictors, developed risk scores have potential applicability in the outpatient setting but require prospective validation before use.

Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and mortality; large numbers of patients require intensive care, which is placing strain on health care systems worldwide. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. OBJECTIVE: The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. METHODS: Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, nonlaboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts the probability of mortality using biomarker measurements (C-reactive protein, procalcitonin, D-dimer) and age. Both the Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China, comprising 160 and 375 patients, respectively. RESULTS: All biomarkers were measured at significantly higher levels in patients who died vs those who were not hospitalized or discharged (P<.001). The Tier 1 and Tier 2 internal validations had areas under the curve (AUCs) of 0.79 (95% CI 0.74-0.84) and 0.95 (95% CI 0.92-0.98), respectively. The Tier 1 and Tier 2 external validations had AUCs of 0.79 (95% CI 0.74-0.84) and 0.97 (95% CI 0.95-0.99), respectively. CONCLUSIONS: Our results demonstrate the validity of the clinical decision support system and mobile app, which are now ready to assist health care providers in making evidence-based decisions when managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics and sites, where application of these tools could lead to improvements in patient outcomes and cost containment.

Triage of patients with venous and lymphatic diseases during the COVID-19 pandemic - The Venous and Lymphatic Triage and Acuity Scale (VELTAS) : A consensus document of the International Union of Phlebology (UIP), Australasian College of Phlebology (ACP), American Vein and Lymphatic Society (AVLS), American Venous Forum (AVF), European College of Phlebology (ECoP), European Venous Forum (EVF), Interventional Radiology Society of Australasia (IRSA), Latin American Venous Forum, Pan-American Society of Phlebology and Lymphology and the Venous Association of India (VAI) This consensus document has been co-published in Phlebology [DOI: 10.1177/0268355520930884] and Journal of Vascular Surgery: Venous and Lymphatic Disorders [DOI: 10.1016/j.jvsv.2020.05.002]. The publications are identical except for minor stylistic and spelling differences in keeping with each journal's style. The contribution has been published under a Attribution-Non Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0), (https://creativecommons.org/licenses/by-nc-nd/4.0/).

The coronavirus disease 2019 (COVID-19) global pandemic has resulted in diversion of healthcare resources to the management of patients infected with SARS-CoV-2 virus. Elective interventions and surgical procedures in most countries have been postponed and operating room resources have been diverted to manage the pandemic. The Venous and Lymphatic Triage and Acuity Scale was developed to provide an international standard to rationalise and harmonise the management of patients with venous and lymphatic disorders or vascular anomalies. Triage urgency was determined based on clinical assessment of urgency with which a patient would require medical treatment or surgical intervention. Clinical conditions were classified into six categories of: (1) venous thromboembolism (VTE), (2) chronic venous disease, (3) vascular anomalies, (4) venous trauma, (5) venous compression and (6) lymphatic disease. Triage urgency was categorised into four groups and individual conditions were allocated to each class of triage. These included (1) medical emergencies (requiring immediate attendance), example massive pulmonary embolism; (2) urgent (to be seen as soon as possible), example deep vein thrombosis; (3) semi-urgent (to be attended to within 30-90 days), example highly symptomatic chronic venous disease, and (4) discretionary/non-urgent- (to be seen within 6-12 months), example chronic lymphoedema. Venous and Lymphatic Triage and Acuity Scale aims to standardise the triage of patients with venous and lymphatic disease or vascular anomalies by providing an international consensus-based classification of clinical categories and triage urgency. The scale may be used during pandemics such as the current COVID-19 crisis but may also be used as a general framework to classify urgency of the listed conditions.