A risk score for identifying methicillin-resistant Staphylococcus aureus in patients presenting to the hospital with pneumonia.

Background Methicillin-resistant Staphylococcus aureus (MRSA) represents an important pathogen in healthcare-associated pneumonia (HCAP). The concept of HCAP, though, may not perform well as a screening test for MRSA and can lead to overuse of antibiotics. We developed a risk score to identify patients presenting to the hospital with pneumonia unlikely to have MRSA. Methods We identified patients admitted with pneumonia (Apr 2005 – Mar 2009) at 62 hospitals in the US. We only included patients with lab evidence of bacterial infection (e.g., positive respiratory secretions, blood, or pleural cultures or urinary antigen testing). We determined variables independently associated with the presence of MRSA based on logistic regression (two-thirds of cohort) and developed a risk prediction model based on these factors. We validated the model in the remaining population. Results The cohort included 5975 patients and MRSA was identified in 14%. The final risk score consisted of eight variables and a potential total score of 10. Points were assigned as follows: two for recent hospitalization or ICU admission; one each for age \u3c 30 or \u3e 79 years, prior IV antibiotic exposure, dementia, cerebrovascular disease, female with diabetes, or recent exposure to a nursing home/long term acute care facility/skilled nursing facility. This study shows how the prevalence of MRSA rose with increasing score after stratifying the scores into Low (0 to 1 points), Medium (2 to 5 points) and High (6 or more points) risk. When the score was 0 or 1, the prevalence of MRSA was \u3c 10% while the prevalence of MRSA climbed to \u3e 30% when the score was 6 or greater. Conclusions MRSA represents a cause of pneumonia presenting to the hospital. This simple risk score identifies patients at low risk for MRSA and in whom anti-MRSA therapy might be withheld

High-throughput mapping of regulatory DNA

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9–based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ~40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell–specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair–resolution functional motifs of regulatory elements.National Institutes of Health (U.S.) (1U01HG007037

A difficulty with oaths: On trust, trustworthiness, and signalling

Asymmetric information, Institutional signals, Oaths, Risk, Trust,

Development and validation of a bedside risk score for MRSA among patients hospitalized with complicated skin and skin structure infections

<p>Abstract</p> <p>Background</p> <p>Methicillin-resistant <it>Staphylococcus aureus</it> (MRSA) is a frequent cause of complicated skin and skin structure infections (cSSSI). Patients with MRSA require different empiric treatment than those with non-MRSA infections, yet no accurate tools exist to aid in stratifying the risk for a MRSA cSSSI. We sought to develop a simple bedside decision rule to tailor empiric coverage more accurately.</p> <p>Methods</p> <p>We conducted a large multicenter (N=62 hospitals) retrospective cohort study in a US-based database between April 2005 and March 2009. All adult initial admissions with ICD-9-CM codes specific to cSSSI were included. Patients admitted with MRSA vs. non-MRSA were compared with regard to baseline demographic, clinical and hospital characteristics. We developed and validated a model to predict the risk of MRSA, and compared its performance via sensitivity, specificity and other classification statistics to the healthcare-associated (HCA) infection risk factors.</p> <p>Results</p> <p>Of the 7,183 patients with cSSSI, 2,387 (33.2%) had MRSA. Factors discriminating MRSA from non-MRSA were age, African-American race, no evidence of diabetes mellitus, cancer or renal dysfunction, and prior history of cardiac dysrhythmia. The score ranging from 0 to 8 points exhibited a consistent dose–response relationship. A MRSA score of 5 or higher was superior to the HCA classification in all characteristics, while that of 4 or higher was superior on all metrics except specificity.</p> <p>Conclusions</p> <p>MRSA is present in 1/3 of all hospitalized cSSSI. A simple bedside risk score can help discriminate the risk for MRSA vs. other pathogens with improved accuracy compared to the HCA definition.</p