Safety of the Combination of PERC and YEARS Rules in Patients With Low Clinical Probability of Pulmonary Embolism: A Retrospective Analysis of Two Large European Cohorts

BACKGROUND: This study aimed to determine the failure rate of a combination of the PERC and the YEARS rules for the diagnosis of pulmonary embolism (PE) in the emergency department (ED). METHODS: We performed a retrospective analysis of two European cohorts of emergency patients with low gestalt clinical probability of PE (PROPER and PERCEPIC). All patients we included were managed using a conventional strategy (D-dimer test, followed, if positive, by computed tomographic pulmonary angiogram (CTPA). We tested a diagnostic strategy that combined PERC and YEARS to rule out PE. The primary endpoint was a thromboembolic event diagnosed in the ED or at 3-months follow-up. Secondary endpoints included a thromboembolic event at baseline in the ED and a CTPA in the ED. Ninety-five percent confidence intervals (CIs) of proportions were calculated with the use of Wilson\u27s continuity correction. RESULTS: We analyzed 1,951 patients (mean ± SD age = 47 ± 18 years, 56% women) with an overall proportion of patients with PE of 3.5%. Both PERC and YEARS strategies were associated with 11 missed PE in the ED: failure rate 0.57 (95% CI = 0.32-1.02). At 3-month follow-up, the overall failure rate was 0.83% (95% CI = 0.51-1.35). Among the 503 patients who underwent a CTPA (26%), the use of the PERC-YEARS combination would have ruled out PE without CTPA in 249 patients (50% [95%CI = 45%-54%], absolute reduction 13% (95% CI = 11%-14%]). CONCLUSION: The combination of PERC then YEARS was associated with a low risk of PE diagnostic failure and would have resulted in a relative reduction of almost half of CTPA

Improved ChIP-chip analysis by a mixture model approach

<p>Abstract</p> <p>Background</p> <p>Microarray analysis of immunoprecipitated chromatin (ChIP-chip) has evolved from a novel technique to a standard approach for the systematic study of protein-DNA interactions. In ChIP-chip, sites of protein-DNA interactions are identified by signals from the hybridization of selected DNA to tiled oligomers and are graphically represented as peaks. Most existing methods were designed for the identification of relatively sparse peaks, in the presence of replicates.</p> <p>Results</p> <p>We propose a data normalization method and a statistical method for peak identification from ChIP-chip data based on a mixture model approach. In contrast to many existing methods, including methods that also employ mixture model approaches, our method is more flexible by imposing less restrictive assumptions and allowing a relatively large proportion of peak regions. In addition, our method does not require experimental replicates and is computationally efficient. We compared the performance of our method with several representative existing methods on three datasets, including a spike-in dataset. These comparisons demonstrate that our approach is more robust and has comparable or higher power than the other methods, especially in the context of abundant peak regions.</p> <p>Conclusion</p> <p>Our data normalization and peak detection methods have improved performance to detect peak regions in ChIP-chip data.</p