48 research outputs found

    Variations and inter-relationship in outcome from emergency admissions in England: a retrospective analysis of Hospital Episode Statistics from 2005-2010.

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    BACKGROUND: The quality of care delivered and clinical outcomes of care are of paramount importance. Wide variations in the outcome of emergency care have been suggested, but the scale of variation, and the way in which outcomes are inter-related are poorly defined and are critical to understand how best to improve services. This study quantifies the scale of variation in three outcomes for a contemporary cohort of patients undergoing emergency medical and surgical admissions. The way in which the outcomes of different diagnoses relate to each other is investigated. METHODS: A retrospective study using the English Hospital Episode Statistics 2005-2010 with one-year follow-up for all patients with one of 20 of the commonest and highest-risk emergency medical or surgical conditions. The primary outcome was in-hospital all-cause risk-standardised mortality rate (in-RSMR). Secondary outcomes were 1-year all-cause risk-standardised mortality rate (1 yr-RSMR) and 28-day all-cause emergency readmission rate (RSRR). RESULTS: 2,406,709 adult patients underwent emergency medical or surgical admissions in the groups of interest. Clinically and statistically significant variations in outcome were observed between providers for all three outcomes (p < 0.001). For some diagnoses including heart failure, acute myocardial infarction, stroke and fractured neck of femur, more than 20% of hospitals lay above the upper 95% control limit and were statistical outliers. The risk-standardised outcomes within a given hospital for an individual diagnostic group were significantly associated with the aggregated outcome of the other clinical groups. CONCLUSIONS: Hospital-level risk-standardised outcomes for emergency admissions across a range of specialties vary considerably and cross traditional speciality boundaries. This suggests that global institutional infra-structure and processes of care influence outcomes. The implications are far reaching, both in terms of investigating performance at individual hospitals and in understanding how hospitals can learn from the best performers to improve outcomes

    Modeling risk factors and confounding effects in stroke

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    Viral, bacterial, and fungal infections of the oral mucosa:Types, incidence, predisposing factors, diagnostic algorithms, and management

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    Microbial carbon use efficiency: accounting for population, community, and ecosystem-scale controls over the fate of metabolized organic matter

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    Microbial carbon use efficiency (CUE) is a critical regulator of soil organic matter dynamics and terrestrial carbon fluxes, with strong implications for soil biogeochemistry models. While ecologists increasingly appreciate the importance of CUE, its core concepts remain ambiguous: terminology is inconsistent and confusing, methods capture variable temporal and spatial scales, and the significance of many fundamental drivers remains inconclusive. Here we outline the processes underlying microbial efficiency and propose a conceptual framework that structures the definition of CUE according to increasingly broad temporal and spatial drivers where (1) CUEP reflects population-scale carbon use efficiency of microbes governed by species-specific metabolic and thermodynamic constraints, (2) CUEC defines community-scale microbial efficiency as gross biomass production per unit substrate taken up over short time scales, largely excluding recycling of microbial necromass and exudates, and (3) CUEE reflects the ecosystem-scale efficiency of net microbial biomass production (growth) per unit substrate taken up as iterative breakdown and recycling of microbial products occurs. CUEE integrates all internal and extracellular constraints on CUE and hence embodies an ecosystem perspective that fully captures all drivers of microbial biomass synthesis and decay. These three definitions are distinct yet complementary, capturing the capacity for carbon storage in microbial biomass across different ecological scales. By unifying the existing concepts and terminology underlying microbial efficiency, our framework enhances data interpretation and theoretical advances
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