Citations

AbstractObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) emerged as a global pandemic in early 2020 with rapidly evolving approaches to diagnosing the clinical illness called coronavirus disease (COVID‐19). The primary objective of this scoping review is to synthesize current research of the diagnostic accuracy of history, physical examination, routine laboratory tests, real‐time reverse transcription–polymerase chain reaction (rRT‐PCR), immunology tests, and computed tomography (CT) for the emergency department (ED) diagnosis of COVID‐19. Secondary objectives included a synopsis of diagnostic biases likely with current COVID‐19 research as well as corresponding implications of false‐negative and false‐positive results for clinicians and investigators.MethodsA Preferred Reporting Items for Systematic Reviews and Meta‐Analyses–Scoping Review (PRISMA‐ScR)–adherent synthesis of COVID‐19 diagnostic accuracy through May 5, 2020, was conducted. The search strategy was designed by a medical librarian and included studies indexed by PubMed and Embase since January 2020.ResultsA total of 1,907 citations were screened for relevance. Patients without COVID‐19 are rarely reported, so specificity and likelihood ratios were generally unavailable. Fever is the most common finding, while hyposmia and hypogeusia appear useful to rule in COVID‐19. Cough is not consistently present. Lymphopenia is the mostly commonly reported laboratory abnormality and occurs in over 50% of COVID‐19 patients. rRT‐PCR is currently considered the COVID‐19 criterion standard for most diagnostic studies, but a single test sensitivity ranges from 60% to 78%. Multiple reasons for false‐negatives rRT‐PCR exist, including sample site tested and disease stage during which sample was obtained. CT may increase COVID‐19 sensitivity in conjunction with rRT‐PCR, but guidelines for imaging patients most likely to benefit are emerging. IgM and IgG serology levels are undetectable in the first week of COVID‐19, but sensitivity (range = 82% to 100%) and specificity (range = 87% to 100%) are promising. Whether detectable COVID‐19 antibodies correspond to immunity remains unanswered. Current studies do not adhere to accepted diagnostic accuracy reporting standards and likely report significantly biased results if the same tests were to be applied to general ED populations with suspected COVID‐19.ConclusionsWith the exception of fever and disorders of smell/taste, history and physical examination findings are unhelpful to distinguish COVID‐19 from other infectious conditions that mimic SARS‐CoV‐2 like influenza. Routine laboratory tests are also nondiagnostic, although lymphopenia is a common finding and other abnormalities may predict severe disease. Although rRT‐PCR is the current criterion standard, more inclusive consensus‐based criteria will likely emerge because of the high false‐negative rate of PCR tests. The role of serology and CT in ED assessments remains undefined.

Study Design: Prospective cohort study. Objective: Reconstruction with microvascular free flaps is quite predictable but excessive fluids intraoperatively and excessive use of vasopressors have been implicated in postoperative complications. However, vasopressors assist in limiting fluid administration and counteract vasodilatory effects of general anesthetics, while maintaining proper intravascular volume. This is of paramount importance during surgery to ensure adequate tissue and organ perfusion. The purpose of this study is to quantify perfusion changes in free flaps at specific time points during peri- and postoperative periods, incorporating SPY technology. Methods: A prospective study of patients who underwent free flap reconstruction was conducted (n = 9), using SPY laser angiography with indocyanine green to assess effects of general anesthetics and vasopressors on flap perfusion. Free flaps were evaluated prior to pedicle division, after inset and anastomosis, and in the immediate postoperative setting. Mean perfusion, mean arterial pressure, total operative time, fluid shifts, and vasopressor use were recorded. Data were analyzed with univariate and multivariable analyses. Results: Those with major complications in this cohort, on average received less vasopressors, had shorter operation times and less blood loss, however, they received more fluids intraoperatively. Conclusion: Changes in mean perfusion to the free flap during the intraoperative and immediate postoperative period are nominal.

Abstract An estimated 14.1 million patients survive sepsis each year. Many survivors experience poor long-term outcomes, including new or worsened neuropsychological impairment; physical disability; and vulnerability to further health deterioration, including recurrent infection, cardiovascular events, and acute renal failure. However, clinical trials and guidelines have focused on shorter-term survival, so there are few data on promoting longer-term recovery. To address this unmet need, the International Sepsis Forum convened a colloquium in February 2018 titled “Understanding and Enhancing Sepsis Survivorship.” The goals were to identify gaps and limitations of current research and shorter- and longer-term priorities for understanding and enhancing sepsis survivorship. Twenty-six experts from eight countries participated. The top short-term priorities identified by nominal group technique culminating in formal voting were to better leverage existing databases for research, develop and disseminate educational resources on postsepsis morbidity, and partner with sepsis survivors to define and achieve research priorities. The top longer-term priorities were to study mechanisms of long-term morbidity through large cohort studies with deep phenotyping, build a harmonized global sepsis registry to facilitate enrollment in cohorts and trials, and complete detailed longitudinal follow-up to characterize the diversity of recovery experiences. This perspective reviews colloquium discussions, the identified priorities, and current initiatives to address them.

Abstract Rationale Noninvasive ventilation (NIV) is increasingly used in patients with acute respiratory distress syndrome (ARDS). The evidence supporting NIV use in patients with ARDS remains relatively sparse. Objectives To determine whether, during NIV, the categorization of ARDS severity based on the PaO2/FiO2 Berlin criteria is useful. Methods The LUNG SAFE (Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure) study described the management of patients with ARDS. This substudy examines the current practice of NIV use in ARDS, the utility of the PaO2/FiO2 ratio in classifying patients receiving NIV, and the impact of NIV on outcome. Measurements and Main Results Of 2,813 patients with ARDS, 436 (15.5%) were managed with NIV on Days 1 and 2 following fulfillment of diagnostic criteria. Classification of ARDS severity based on PaO2/FiO2 ratio was associated with an increase in intensity of ventilatory support, NIV failure, and intensive care unit (ICU) mortality. NIV failure occurred in 22.2% of mild, 42.3% of moderate, and 47.1% of patients with severe ARDS. Hospital mortality in patients with NIV success and failure was 16.1% and 45.4%, respectively. NIV use was independently associated with increased ICU (hazard ratio, 1.446 [95% confidence interval, 1.159–1.805]), but not hospital, mortality. In a propensity matched analysis, ICU mortality was higher in NIV than invasively ventilated patients with a PaO2/FiO2 lower than 150 mm Hg. Conclusions NIV was used in 15% of patients with ARDS, irrespective of severity category. NIV seems to be associated with higher ICU mortality in patients with a PaO2/FiO2 lower than 150 mm Hg. Clinical trial registered with www.clinicaltrials.gov (NCT 02010073).

Objective: The Lung Injury Prediction Score identifies patients at risk for acute respiratory distress syndrome in the emergency department, but it has not been validated in non-emergency department hospitalized patients. We aimed to evaluate whether Lung Injury Prediction Score identifies non-emergency department hospitalized patients at risk of developing acute respiratory distress syndrome at the time of critical care contact. Design: Retrospective study. Setting: Five academic medical centers. Patients: Nine hundred consecutive patients (≥ 18 yr old) with at least one acute respiratory distress syndrome risk factor at the time of critical care contact. Interventions: None. Measurements and Main Results: Lung Injury Prediction Score was calculated using the worst values within the 12 hours before initial critical care contact. Patients with acute respiratory distress syndrome at the time of initial contact were excluded. Acute respiratory distress syndrome developed in 124 patients (13.7%) a median of 2 days (interquartile range, 2–3) after critical care contact. Hospital mortality was 22% and was significantly higher in acute respiratory distress syndrome than non-acute respiratory distress syndrome patients (48% vs 18%; p < 0.001). Increasing Lung Injury Prediction Score was significantly associated with development of acute respiratory distress syndrome (odds ratio, 1.31; 95% CI, 1.21–1.42) and the composite outcome of acute respiratory distress syndrome or death (odds ratio, 1.26; 95% CI, 1.18–1.34). A Lung Injury Prediction Score greater than or equal to 4 was associated with the development of acute respiratory distress syndrome (odds ratio, 4.17; 95% CI, 2.26–7.72), composite outcome of acute respiratory distress syndrome or death (odds ratio, 2.43; 95% CI, 1.68–3.49), and acute respiratory distress syndrome after accounting for the competing risk of death (hazard ratio, 3.71; 95% CI, 2.05–6.72). For acute respiratory distress syndrome development, the Lung Injury Prediction Score has an area under the receiver operating characteristic curve of 0.70 and a Lung Injury Prediction Score greater than or equal to 4 has 90% sensitivity (misses only 10% of acute respiratory distress syndrome cases), 31% specificity, 17% positive predictive value, and 95% negative predictive value. Conclusions: In a cohort of non-emergency department hospitalized patients, the Lung Injury Prediction Score and Lung Injury Prediction Score greater than or equal to 4 can identify patients at increased risk of acute respiratory distress syndrome and/or death at the time of critical care contact but it does not perform as well as in the original emergency department cohort.