61 research outputs found

    The Procedural Index for Mortality Risk (PIMR): an index calculated using administrative data to quantify the independent influence of procedures on risk of hospital death

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    <p>Abstract</p> <p>Background</p> <p>Surgeries and other procedures can influence the risk of death in hospital. All published scales that predict post-operative death risk require clinical data and cannot be measured using administrative data alone. This study derived and internally validated an index that can be calculated using administrative data to quantify the independent risk of hospital death after a procedure.</p> <p>Methods</p> <p>For all patients admitted to a single academic centre between 2004 and 2009, we estimated the risk of all-cause death using the Kaiser Permanente Inpatient Risk Adjustment Methodology (KP-IRAM). We determined whether each patient underwent one of 503 commonly performed therapeutic procedures using Canadian Classification of Interventions codes and whether each procedure was emergent or elective. Multivariate logistic regression modeling was used to measure the association of each procedure-urgency combination with death in hospital independent of the KP-IRAM risk of death. The final model was modified into a scoring system to quantify the independent influence each procedure had on the risk of death in hospital.</p> <p>Results</p> <p>275 460 hospitalizations were included (137,730 derivation, 137,730 validation). In the derivation group, the median expected risk of death was 0.1% (IQR 0.01%-1.4%) with 4013 (2.9%) dying during the hospitalization. 56 distinct procedure-urgency combinations entered our final model resulting in a Procedural Index for Mortality Rating (PIMR) score values ranging from -7 to +11. In the validation group, the PIMR score significantly predicted the risk of death by itself (c-statistic 67.3%, 95% CI 66.6-68.0%) and when added to the KP-IRAM model (c-index improved significantly from 0.929 to 0.938).</p> <p>Conclusions</p> <p>We derived and internally validated an index that uses administrative data to quantify the independent association of a broad range of therapeutic procedures with risk of death in hospital. This scale will improve risk adjustment when administrative data are used for analyses.</p

    Research activity and the association with mortality.

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    INTRODUCTION: The aims of this study were to describe the key features of acute NHS Trusts with different levels of research activity and to investigate associations between research activity and clinical outcomes. METHODS: National Institute for Health Research (NIHR) Comprehensive Clinical Research Network (CCRN) funding and number of patients recruited to NIHR Clinical Research Network (CRN) portfolio studies for each NHS Trusts were used as markers of research activity. Patient-level data for adult non-elective admissions were extracted from the English Hospital Episode Statistics (2005-10). Risk-adjusted mortality associations between Trust structures, research activity and, clinical outcomes were investigated. RESULTS: Low mortality Trusts received greater levels of funding and recruited more patients adjusted for size of Trust (n = 35, 2,349 £/bed [95% CI 1,855-2,843], 5.9 patients/bed [2.7-9.0]) than Trusts with expected (n = 63, 1,110 £/bed, [864-1,357] p<0.0001, 2.6 patients/bed [1.7-3.5] p<0.0169) or, high (n = 42, 930 £/bed [683-1,177] p = 0.0001, 1.8 patients/bed [1.4-2.1] p<0.0005) mortality rates. The most research active Trusts were those with more doctors, nurses, critical care beds, operating theatres and, made greater use of radiology. Multifactorial analysis demonstrated better survival in the top funding and patient recruitment tertiles (lowest vs. highest (odds ratio & 95% CI: funding 1.050 [1.033-1.068] p<0.0001, recruitment 1.069 [1.052-1.086] p<0.0001), middle vs. highest (funding 1.040 [1.024-1.055] p<0.0001, recruitment 1.085 [1.070-1.100] p<0.0001). CONCLUSIONS: Research active Trusts appear to have key differences in composition than less research active Trusts. Research active Trusts had lower risk-adjusted mortality for acute admissions, which persisted after adjustment for staffing and other structural factors

    Development, standardization and refinement of procedures for evaluating effects of endocrine active compounds on development and sexual differentiation of Xenopus laevis

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    Xenopus laevis has been introduced as a model to study effects of endocrine-active compounds (EAC) on development and sexual differentiation. However, variable and inconsistent data have raised questions about the reliability of the test methods applied. The current study was conducted in two laboratories to develop, refine, and standardize procedures and protocols. Larvae were exposed in flow-through systems to 17β-estradiol (E2), at concentrations from 0.2 to 6.0 μg E2 L−1 in Experiment 1A, and 0.015 to 2.0 μg E2 L−1 in Experiment 1B. In both studies survival (92%, 99%) and percentage of animals that completed metamorphosis (97%, 99%) indicated reproducible biological performance. Furthermore, minor variations in husbandry led to significant differences in snout-to-vent length, weight, and gonad size. In Experiment 1A, almost complete feminization occurred in all E2 treatment groups whereas a concentration response was observed in Experiment 1B resulting in an EC50 of 0.12 μg E2 L−1. The final verified protocol is suitable for determining effects of EAC on development and sexual differentiation in X. laevis

    Contrasting predictors of poor antiretroviral therapy outcomes in two South African HIV programmes: a cohort study

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    BACKGROUND: Many national antiretroviral therapy (ART) programmes encourage providers to identify and address baseline factors associated with poor treatment outcomes, including modifiable adherence-related behaviours, before initiating ART. However, evidence on such predictors is scarce, and providers judgement may often be inaccurate. To help address this evidence gap, this observational cohort study examined baseline factors potentially predictive of poor treatment outcomes in two ART programmes in South Africa, with a particular focus on determinants of adherence. METHODS: Treatment-naïve patients starting ART were enrolled from a community and a workplace ART programme. Potential baseline predictors associated with poor treatment outcomes (defined as viral load > 400 copies/ml or having discontinued treatment by six months) were assessed using logistic regression. Exposure variables were organised for regression analysis using a hierarchical framework. RESULTS: 38/227 (17%) of participants in the community had poor treatment outcomes compared to 47/117 (40%) in the workplace. In the community, predictors of worse outcomes included: drinking more than 20 units of alcohol per week, having no prior experience of chronic medications, and consulting a traditional healer in the past year (adjusted odds ratio [aOR] 15.36, 95% CI 3.22-73.27; aOR 2.30, 95%CI 1.00-5.30; aOR 2.27, 95% CI 1.00-5.19 respectively). Being male and knowing someone on ART were associated with better outcomes (aOR 0.25, 95%CI 0.09-0.74; aOR 0.44, 95%CI 0.19-1.01 respectively). In the workplace, predictors of poor treatment outcomes included being uncertain about the health effects of ART and a traditional healer's ability to treat HIV (aOR 7.53, 95%CI 2.02-27.98; aOR 4.40, 95%CI 1.41-13.75 respectively). Longer pre-ART waiting time (2-12 weeks compared to <2 weeks) predicted better treatment outcomes (aOR 0.13, 95% CI 0.03-0.56). CONCLUSION: Baseline predictors of poor treatment outcomes were largely unique to each programme, likely reflecting different populations and pathways to HIV care. In the workplace, active promotion of HIV testing may have extended ART to individuals who, without provider initiation, would not have spontaneously sought care. As provider-initiated testing makes ART available to individuals less motivated to seek care, patients may need additional adherence support, especially addressing uncertainty about the health benefits of ART

    CD34-related coexpression of MDR1 and BCRP indicates a clinically resistant phenotype in patients with acute myeloid leukemia (AML) of older age

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    Clinical resistance to chemotherapy in acute myeloid leukemia (AML) is associated with the expression of the multidrug resistance (MDR) proteins P-glycoprotein, encoded by the MDR1/ABCB1 gene, multidrug resistant-related protein (MRP/ABCC1), the lung resistance-related protein (LRP), or major vault protein (MVP), and the breast cancer resistance protein (BCRP/ABCG2). The clinical value of MDR1, MRP1, LRP/MVP, and BCRP messenger RNA (mRNA) expression was prospectively studied in 154 newly diagnosed AML patients ≥60 years who were treated in a multicenter, randomized phase 3 trial. Expression of MDR1 and BCRP showed a negative whereas MRP1 and LRP showed a positive correlation with high white blood cell count (respectively, p < 0.05, p < 0.001, p < 0.001 and p < 0.001). Higher BCRP mRNA was associated with secondary AML (p < 0.05). MDR1 and BCRP mRNA were highly significantly associated (p < 0.001), as were MRP1 and LRP mRNA (p < 0.001) expression. Univariate regression analyses revealed that CD34 expression, increasing MDR1 mRNA as well as MDR1/BCRP coexpression, were associated with a lower complete response (CR) rate and with worse event-free survival and overall survival. When adjusted for other prognostic actors, only CD34-related MDR1/BCRP coexpression remained significantly associated with a lower CR rate (p = 0.03), thereby identifying a clinically resistant subgroup of elderly AML patients

    Mapping Helminth Co-Infection and Co-Intensity: Geostatistical Prediction in Ghana

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    Urinary schistosomiasis and hookworm infections cause considerable morbidity in school age children in West Africa. Severe morbidity is predominantly observed in individuals infected with both parasite types and, in particular, with heavy infections. We investigated for the first time the distribution of S. haematobium and hookworm co-infections and distribution of co-intensity of these parasites in Ghana. Bayesian geostatistical models were developed to generate a national co-infection map and national intensity maps for each parasite, using data on S. haematobium and hookworm prevalence and egg concentration (expressed as eggs per 10 mL of urine for S. haematobium and expressed as eggs per gram of faeces for hookworm), collected during a pre-intervention baseline survey in Ghana, 2008. In contrast with previous findings from the East Africa region, we found that both S. haematobium and hookworm infections are highly focal, resulting in small, localized clusters of co-infection and areas of high co-intensity. Overlaying on a single map the co-infection and the intensity of multiple parasite infections allows identification of areas where parasite environmental contamination and morbidity are at its highest, while providing an evidence base for the assessment of the progress of successive rounds of mass drug administration (MDA) in integrated parasitic disease control programs
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