BackgroundWe aimed to determine whether sepsis is associated with neurocognitive outcomes 4.5 years after congenital heart disease surgery in early infancy.Methods and ResultsA secondary analysis from a prospective inception cohort included all children having congenital heart disease surgery done at ≤6 weeks of age with cardiopulmonary bypass at the Western Canadian referral center from 1996 to 2009. Follow-up at the referral center determined the primary outcomes at 4.5 years with full-scale, performance, and verbal intelligence quotients on the Wechsler Preschool and Primary Scale of Intelligence. Perioperative variables were collected prospectively, and confirmation of blood culture–positive sepsis was done retrospectively. Multiple linear regression models for neurocognitive outcomes and multiple Cox proportional hazards regression for mortality were determined. Sepsis occurred in 97 of 502 patients (19%) overall and in 76 of 396 survivors (19%) with 4.5-year follow-up. By 4.5 years, there were 91 (18%) deaths, and 396 of 411 survivors (96%) had follow-up completed. Extracorporeal membrane oxygenation was associated with worse scores on all neurocognitive outcomes on multivariable regression; the association between extracorporeal membrane oxygenation and full-scale intelligence quotient had a regression coefficient of −13.6 (95% CI −21.3 to −5.9; P =0.001). Sepsis perioperatively was associated with performance and verbal intelligence quotients, with a trend for full-scale intelligence quotient (P =0.058) on multivariable regression. The regression coefficient for sepsis was strongest for performance intelligence quotient (−5.31; 95% CI −9.84 to −0.78; P =0.022). Sepsis was not but extracorporeal membrane oxygenation was associated with mortality by 4.5 years.ConclusionsPerioperative sepsis and extracorporeal membrane oxygenation were associated with adverse neurocognitive outcomes on multivariable regression. Quality improvement to prevent sepsis has the potential to improve long-term neurocognitive outcomes in infants after surgery for congenital heart disease.

Two-hour hsTnT algorithms can rule out AMI with very high sensitivity and NPV. The algorithm developed by Reichlin et al. had superior classification performance. Reichlin and colleagues' 2-hour rule-in algorithm had poor positive predictive value and might not be suitable for early rule-in decision-making.

BackgroundThe objective of this study was to quantify the sensitivity of very low concentrations of high‐sensitivity cardiac troponin T (hsTnT) at ED arrival for acute myocardial infarction (AMI) in a large cohort of chest pain patients evaluated in real‐world clinical practice.MethodsThis retrospective study included consecutive ED patients with suspected cardiac chest pain evaluated in four urban EDs, excluding those with ST‐elevation AMI, cardiac arrest or abnormal kidney function. The primary outcomes were AMI at 7, 30, and 90 days. Secondary outcomes included major adverse cardiac events (MACE; all‐cause mortality, AMI, and revascularization) and the individual MACE components. Test characteristics were calculated for hsTnT values from 3 to 200 ng/L .ResultsA total of 7,130 patients met inclusion criteria. AMI incidences at 7, 30, and 90 days were 5.8, 6.0, and 6.2%. When the hsTnT assay was performed at ED arrival, the limit of blank of the assay (3 ng/L) ruled out 7‐day AMI in 15.5% of patients with 100% sensitivity and negative predictive value (NPV). The limit of detection of the assay (5 ng/L) ruled out AMI in 33.6% of patients with 99.8% sensitivity and 99.95% NPV for 7‐day AMI. The limit of quantification (the Food and Drug Administration [FDA]‐approved cutoff for lower the reportable limit) of 6 ng/L ruled out AMI in 42.2% of patients with 99.8% sensitivity and 99.95% NPV. The sensitivities of the cutoffs of <3, <5, and <6 ng/L for 7‐day MACE were 99.6, 97.4, and 96.6%, respectively. The NPVs of the cutoffs of <3, <5, and <6 ng/L for 7‐day MACE were 99.8, 99.5, and 99.4%, respectively. A secondary analysis was performed in a subgroup of 3,549 higher‐risk patients who underwent serial troponin testing. In this subgroup, a cutoff of 3 ng/L ruled out 7‐day AMI in 9.6% of patients with 100% sensitivity and NPV, a cutoff of 5 ng/L ruled out 7‐day AMI in 23.3% of patients with 99.7% sensitivity and 99.9% NPV, and a cutoff of 6 ng/L ruled out 7‐day AMI in 29.8% of patients with 99.7 and 99.9% NPV. In the higher‐risk subgroup, the sensitivities of cutoffs of <3, <5, and <6 ng/L for 7‐day MACE were 99.8, 97.4, and 96.6%, respectively. In this higher‐risk subgroup, the NPV of cutoffs of <3, <5, and <6 ng/L for 7‐day MACE were 99.7, 98.5, and 98.4%, respectively.ConclusionsWhen used in real‐world clinical practice conditions, hsTnT concentrations < 6 ng/L (below the lower reportable limit for an FDA‐approved assay) at the time of ED arrival can rule out AMI with very high sensitivity and NPV. The sensitivity for MACE is unacceptably low, and thus a single‐troponin rule‐out strategy should only be used in the context of a structured risk evaluation.

BackgroundGene set analysis (GSA) methods test the association of sets of genes with a phenotype in gene expression microarray studies. Many GSA methods have been proposed, especially methods for use with a binary phenotype. Equally, if not more importantly however, is the ability to test the enrichment of a gene signature or pathway against the continuous phenotypes which are routinely and commonly observed in, for example, clinicopathological measurements. It is not always easy or meaningful to dichotomize continuous phenotypes into two classes, and attempting to do this may lead to the inaccurate classification of samples, which would affect the downstream enrichment analysis. In the present study, we have build on recent efforts to incorporate correlation structure within gene sets and pathways into the GSA test statistic. To address the issue of continuous phenotypes directly without the need for artificial discrete classification and thus increase the power of the test while ensuring computational efficiency and rigor, new GSA methods that can incorporate a covariance matrix estimator for a continuous phenotype may present an effective approach.ResultsWe have designed a new method by extending the GSA approach called Linear Combination Test (LCT) from a binary to a continuous phenotype. Simulation studies and a real microarray dataset were used to compare the proposed LCT for a continuous phenotype, a modification of LCT (referred to as LCT2), and two publicly available GSA methods for continuous phenotypes.ConclusionsWe found that the LCT methods performed better than the other two GSA methods; however, this finding should be understood in the context of our specific simulation studies and the real microarray dataset that were used to compare the methods. Free R-codes to perform LCT for binary and continuous phenotypes are available at http://www.ualberta.ca/~yyasui/homepage.html. The R-code to perform LCT for a continuous phenotype is available as Additional file 1.

ObjectivesTo develop and validate a clinical risk score that can accurately quantify the probability of SARS-CoV-2 infection in patients presenting to an emergency department without the need for laboratory testing.DesignCohort study of participants in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry. Regression models were fitted to predict a positive SARS-CoV-2 test result using clinical and demographic predictors, as well as an indicator of local SARS-CoV-2 incidence.Setting32 emergency departments in eight Canadian provinces.Participants27 665 consecutively enrolled patients who were tested for SARS-CoV-2 in participating emergency departments between 1 March and 30 October 2020.Main outcome measuresPositive SARS-CoV-2 nucleic acid test result within 14 days of an index emergency department encounter for suspected COVID-19 disease.ResultsWe derived a 10-item CCEDRRN COVID-19 Infection Score using data from 21 743 patients. This score included variables from history and physical examination and an indicator of local disease incidence. The score had a c-statistic of 0.838 with excellent calibration. We externally validated the rule in 5295 patients. The score maintained excellent discrimination and calibration and had superior performance compared with another previously published risk score. Score cut-offs were identified that can rule-in or rule-out SARS-CoV-2 infection without the need for nucleic acid testing with 97.4% sensitivity (95% CI 96.4 to 98.3) and 95.9% specificity (95% CI 95.5 to 96.0).ConclusionsThe CCEDRRN COVID-19 Infection Score uses clinical characteristics and publicly available indicators of disease incidence to quantify a patient’s probability of SARS-CoV-2 infection. The score can identify patients at sufficiently high risk of SARS-CoV-2 infection to warrant isolation and empirical therapy prior to test confirmation while also identifying patients at sufficiently low risk of infection that they may not need testing.Trial registration numberNCT04702945.