Use of viscoelastic tests to predict clinical thromboembolic events: A systematic review and meta-analysis

We aimed to assess whether whole-blood viscoelastic tests are useful to identify patients who are hypercoagulable and at increased risk of thromboembolism. Two investigators independently analyzed studies in the MEDLINE, EMBASE, and Cochrane controlled trial register databases to determine the ability of viscoelastic tests to identify a hypercoagulable state that is predictive of objectively proven thromboembolic events. Forty-one eligible studies, including 10,818 patients, were identified and subject to meta-analysis. The majority of the studies (n = 36, 88%) used the maximum clot strength to identify a hypercoagulable state which had a moderate ability to differentiate between patients who developed thromboembolic events and those who did not (area under the summary receiver operating characteristic [sROC] curve = 0.70, 95% confidence interval [CI]: 0.65-0.75). The pooled sensitivity, specificity, and diagnostic odds ratio to predict thromboembolism were 56% (95%CI: 44-67), 76% (95%CI: 67-83), and 3.6 (95%CI: 2.6-4.9), respectively. The predictive performance did not vary substantially between patient populations, and publication bias was not observed. Current evidence suggests that whole-blood viscoelastic tests have a moderate ability to identify a variety of patient populations with an increased risk of thromboembolic events and can be considered as a useful adjunct to clinical judgment to stratify a patient's risk of developing thromboembolism

Predicting contrast-induced nephropathy after CT pulmonary angiography in the critically ill: a retrospective cohort study

Background It is uncertain whether we can predict contrast-induced nephropathy (CIN) after CT pulmonary angiography (CTPA). This study compared the ability of a validated CIN prediction score with the Pulmonary Embolism Severity Index (PESI) in predicting CIN after CTPA. Methods This cohort study involved critically ill adult patients who required a CTPA to exclude acute pulmonary embolism (PE). Patients with end-stage renal failure requiring dialysis were excluded. CIN was defined as an elevation in plasma creatinine concentrations > 44.2μmol/l (or 0.5 mg/dl) within 48 h after CTPA. Results Of the 137 patients included, 77 (51%) were hypotensive, 54 (39%) required inotropic support, and 68 (50%) were mechanically ventilated prior to the CTPA. Acute PE was confirmed in 21 patients (15%) with 14 (10%) being bilateral. CIN occurred in 56 patients (41%) with 35 (26%) required dialysis subsequent to CTPA. The CIN prediction score had a good ability to discriminate between patients with and without developing CIN (Area under the receiver-operating-characteristic (AUROC) curve 0.864, 95% confidence interval [CI] 0.795–0.916) and requiring subsequent dialysis (AUROC 0.897, 95% CI 0.833–0.942) and was better than the PESI in predicting both outcomes (AUROC 0.731, 95% CI 0.649–0.804 and 0.775, 95% CI 0.696–0.842, respectively). A CIN risk score > 10 and 12 had an 82.1 and 85.7% sensitivity and 81.5 and 78.4% specificity to predict subsequent CIN and dialysis, respectively. The CIN prediction model tended to underestimate the observed risks of dialysis, but this was improved after recalibrating the slope and intercept of the original prediction equation. Conclusions The CIN prediction score had a good ability to discriminate between critically ill patients with and without developing CIN after CTPA. Used together for critically ill patients with suspected acute PE, the CIN prediction score and PESI may be useful to inform clinicians when the benefits of a CTPA scan will outweigh its potential harms

Development and Utility of Quality Metrics for Ambulatory Pediatric Cardiology in Kawasaki Disease.

The Adult Congenital and Pediatric Cardiology (ACPC) Section of the American College of Cardiology sought to develop quality indicators/metrics for ambulatory pediatric cardiology practice. The objective of this study was to report the creation of metrics for patients with Kawasaki disease. Over a period of 5 months, 12 pediatric cardiologists developed 24 quality metrics based on the most relevant statements, guidelines, and research studies pertaining to Kawasaki disease. Of the 24 metrics, the 8 metrics deemed the most important, feasible, and valid were sent on to the ACPC for consideration. Seven of the 8 metrics were approved using the RAND method by an expert panel. All 7 metrics approved by the ACPC council were accepted by ACPC membership after an "open comments" process. They have been disseminated to the pediatric cardiology community for implementation by the ACPC Quality Network

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available

mRNA Coronavirus Disease 2019 Vaccine-Associated Myopericarditis in Adolescents: A Survey Study

In this survey study of institutions across the US, marked variability in evaluation, treatment, and follow-up of adolescents 12 through 18 years of age with mRNA coronavirus disease 2019 (COVID-19) vaccine-associated myopericarditis was noted. Only one adolescent with life-threatening complications was reported, with no deaths at any of the participating institutions

Optimizing the utility of secondary outcomes in randomized controlled trials

Randomized controlled trials (RCTs) are the cornerstone of evidence based medicine and are often considered the most important piece of evidence to guide clinical practice. To make sure RCTs are fit for their purpose, the design of such trials must be both statistically robust and clinically relevant. The sample size and statistical power of a study are mathematically related; it is widely accepted that the sample size should be sufficiently large to ensure a power of 80% or greater to avoid initiating a study that is destined to fail in rejecting the null hypothesis. In general, the predicted incidence of the primary outcome (in the control group) and the effect size (conferred by the test intervention) are the two most important elements that determine the mathematical relationship between sample size and the power of the study. Secondary outcomes are common in RCTs. There are many reasons why researchers want to include a secondary outcome, including the interest to answer as many clinical questions as possible by doing only one trial—that is, as ‘niceties’. It is now a standard practice for researchers to predefine all secondary outcomes a priori in the trial’s protocol and also in the trial registry to avoid the temptation to conduct multiple post hoc analyses in an attempt to find a significant P value. What has not been thoroughly considered and widely adopted is how we can maximize the utility of secondary outcomes in RCTs

Using patient admission characteristics alone to predict mortality of critically ill patients: A comparison of 3 prognostic scores

Purpose: This study compared the performance of 3 admission prognostic scores in predicting hospital mortality. Materials and methods: Patient admission characteristics and hospital outcome of 9549 patients were recorded prospectively. The discrimination and calibration of the predicted risks of death derived from the Simplified Acute Physiology Score (SAPS III), Admission Mortality Prediction Model (MPM0 III), and admission Acute Physiology and Chronic Health Evaluation (APACHE) II were assessed by the area under the receiver operating characteristic curve and a calibration plot, respectively. Measurements and main results: Of the 9549 patients included in the study, 1276 patients (13.3%) died after intensive care unit admission. Patient admission characteristics were significantly different between the survivors and nonsurvivors. All 3 prognostic scores had a reasonable ability to discriminate between the survivors and nonsurvivors (area under the receiver operating characteristic curve for SAPS III, 0.836; MPM0 III, 0.807; admission APACHE, 0.845), with best discrimination in emergency admissions. The SAPS III model had a slightly better calibration and overall performance (slope of calibration curve, 1.03; Brier score, 0.09; Nagelkerke R-2, 0.297) compared to the MPM0 III and admission APACHE II model. Conclusions: All 3 intensive care unit admission prognostic scores had a good ability to predict hospital mortality of critically ill patients, with best discrimination in emergency admissions