Rationale: The 2016 definitions of sepsis included the quick Sepsisrelated Organ Failure Assessment (qSOFA) score to identify highrisk patients outside the intensive care unit (ICU).Objectives: We sought to compare qSOFA with other commonly used early warning scores. . Using the highest non-ICU score of patients, >2 SIRS had a sensitivity of 91% and specificity of 13% for the composite outcome compared with 54% and 67% for qSOFA >2, 59% and 70% for MEWS >5, and 67% and 66% for NEWS >8, respectively. Most patients met >2 SIRS criteria 17 hours before the combined outcome compared with 5 hours for >2 and 17 hours for >1 qSOFA criteria.Conclusions: Commonly used early warning scores are more accurate than the qSOFA score for predicting death and ICU transfer in non-ICU patients. These results suggest that the qSOFA score should not replace general early warning scores when risk-stratifying patients with suspected infection.

OBJECTIVE Studies in sepsis are limited by heterogeneity regarding what constitutes suspicion of infection. We sought to compare potential suspicion criteria using antibiotic and culture order combinations in terms of patient characteristics and outcomes. We further sought to determine the impact of differing criteria on the accuracy of sepsis screening tools and early warning scores. DESIGN Observational cohort study SETTING Academic center from November 2008 until January 2016 PATIENTS Hospitalized patients outside the intensive care unit (ICU) INTERVENTIONS None MEASUREMENTS AND MAIN RESULTS Six criteria were investigated: 1) any culture; 2) blood culture; 3) any culture plus intravenous (IV) antibiotics; 4) blood culture plus IV antibiotics; 5) any culture plus IV antibiotics for at least four of seven days; and 6) blood culture plus IV antibiotics for at least four of seven days. Accuracy of the quick Sepsis-related Organ Failure Assessment (qSOFA) score, SOFA score, systemic inflammatory response system (SIRS) criteria, the National and Modified Early Earning Score (NEWS and MEWS), and the electronic Cardiac Arrest Risk Triage (eCART) score were calculated for predicting ICU transfer or death within 48 hours of meeting suspicion criteria. A total of 53,849 patients met at least one infection criteria. Mortality increased from 3% for group 1 to 9% for group 6 and percentage meeting Angus sepsis criteria increased from 20% to 40%. Across all criteria, score discrimination was lowest for SIRS (median AUC 0.60) and SOFA score (median AUC 0.62), intermediate for qSOFA (median AUC 0.65) and MEWS (median AUC 0.67), and highest for NEWS (median AUC 0.71) and eCART (median AUC 0.73). CONCLUSIONS The choice of criteria to define a potentially infected population significantly impacts on prevalence of mortality but has little impact on accuracy. SIRS was the least predictive and eCART the most predictive regardless of how infection was defined.

Medical ICU patients who developed new-onset AF experienced a 2-fold increase in the odds of in-hospital mortality and death at 60 days. Further research investigating contributing factors to new-onset AF and potential treatments is warranted.

Objective Prior research indicates off-label use is common in the intensive care unit (ICU); however the safety of off-label use has not been assessed. The study objective was to determine the incidence of adverse drug reactions (ADRs) associated with off-label use and evaluate off-label use as a risk factor for the development of ADRs in an adult ICU population. Setting Medical ICUs at three academic medical centers Patients Adult patients (age ≥ 18 years old) receiving medication therapy Interventions All administered medications were evaluated for Food and Drug Administration (FDA) approved or off-label use. Patients were assessed daily for the development of an ADR through active surveillance. Three ADR assessment instruments were used to determine the probability of an ADR resulting from drug therapy. Severity and harm of the ADR were also assessed. Cox proportional hazard regression was used to identify a set of covariates that influenced the rate of ADRs. Measurements and Main Results Overall, 1654 patient days (327 patients) and 16,391 medications were evaluated, with 43% of medications being used off-label. One hundred and sixteen ADRs were categorized dichotomously (FDA or off-label), with 56% and 44% being associated with FDA approved and off-label use, respectively. The number of ADRs for medications administered and number of harmful and severe ADRs did not differ for medications used for FDA approved or off-label use (0.74% vs 0.67%, p = 0.336; 33 vs. 31 events, p=0.567; 24 vs. 24 events, p = 0.276). Age, sex, number of high-risk medications, number of off-label medications, and severity of illness score were included in the Cox proportional hazard regression. It was found that the rate of ADRs increases by 8% for every one additional off-label medication (HR = 1.08; 95 % CI: 1.018–1.154). Conclusion While ADRs do not occur more frequently with off-label use, ADR risk increases with each additional off-label medication used.

Delays in lactate measurement are associated with delayed antibiotics and increased mortality in patients with initial intermediate or elevated lactate levels. Systematic early lactate measurement for all patients with sepsis will lead to a significant increase in lactate draws that may prompt more rapid physician intervention for patients with abnormal initial values.

Background Opioids and benzodiazepines are frequently used in hospitals, but little is known about outcomes among ward patients receiving these medications. Objective To determine the association between opioid and benzodiazepine administration and clinical deterioration. Design Observational cohort study. Setting 500-bed academic urban tertiary-care hospital. Patients All adults hospitalized on the wards from November 2008 to January 2016 were included. Patients who were “comfort care” status, had tracheostomies, sickle-cell disease, and patients at risk for alcohol withdrawal or seizures were excluded. Measurements The primary outcome was the composite of intensive care unit transfer or ward cardiac arrest. Discrete-time survival analysis was used to calculate the odds of this outcome during exposed time periods compared to unexposed time periods with respect to the medications of interest, with adjustment for patient demographics, comorbidities, severity of illness, and pain score. Results In total, 120,518 admissions from 67,097 patients were included, with 67% of admissions involving opioids, and 21% involving benzodiazepines. After adjustment, each equivalent of 15 mg oral morphine was associated with a 1.9% increase in the odds of the primary outcome within six hours (OR 1.019, 95% CI 1.013 – 1.026, p<0.001), and each 1 mg oral lorazepam equivalent was associated with a 29% increase in the odds of the composite outcome within six hours (OR 1.29, 1.16–1.45, p<0.001). Conclusions Among ward patients, opioids were associated with increased risk for clinical deterioration in the six hours after administration. Benzodiazepines were associated with even higher risk. These results have implications for ward monitoring strategies.

entire individual market to meet the Affordable Care Act's standard plans in 2014. California and 14 other states made this change-which all states were supposed to have completed by 2018, but with recent regulation by the Trump administration, many will never do. By not making this change, many healthier populations-because they previously underwent medical underwriting-have been excluded from the common risk pool.Regardless of the number of plans in a marketplace, a key and often forgotten issue in how to keep premiums lower is marketing. By aggressively marketing plans, providers are likely to have a better risk mix, which fosters lower premiums. Two data points support the importance of marketing plans. First, based on recently released data from the Centers for Medicare and Medicaid Services in 2016, markets that were under the federal facilitated marketplace faced a net decline in enrollment of about 15% from the beginning of the year to the end of the year; this compares to a net decline of only 6% for those in statebased marketplaces. 3 This decline matters because declining enrollment is likely to mean that healthier people are leaving to be uninsured. Understanding the reason does require further study, but a key difference between federal and state-based marketplaces is that states have invested more in marketing that supports initial enrollment, enrollment throughout the year during special periods, and retention.The second data point relates to the core difference in marketing. Zhu and colleagues mention an increase in premiums for single-issuer regions of 25% compared with 7.2% the prior year. Too often, rate analysis looks at too short a window of time and at too few variables. Examining the combined weighted coverage of the second-lowest-cost Silver plan for 2016 and 2017 reveals that, in all of the 38 federal marketplace states, weighted coverage premium rates increased approximately 32.5% over 2 years. Compare this with an increase in the same period in California of 9.9% for the Silver plan with the second-lowest cost. The reason that premiums increased by more than 22.6% in federal marketplace states compared with that in California during 2016 and 2017 surely has multiple factors. However, limited plan competition is likely far less of a reason than the difference in marketing spending. California invests heavily in marketing-a mean annual 1.7% of the premium during 2016 and 2017.Taken together with the recent data for enrollment year 2017 confirming that Covered California continues to have a strong, stable risk mix, these marketing investments seem to pay off in a big way to reduce premiums. 4,5 Diagnosing the reason for premium increase variation is important and provides tools to policy makers. Part of this investigation should include looking at factors that contribute to poor performance and, just as important, to the factors that explain why California and many other health insurance markets have continued to be stable and competitive.

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