1,721,037 research outputs found
Prediction of mortality for congestive heart failure patients: results from different wards of an italian teaching hospital
No full textCongestive heart failure (CHF) constitutes an important public health problem in Italy, evidenced by the high number of hospital admissions each year. Significant inter-hospital as well as interward differences in mortality rates for CHF patients that have been described may, in part, be explained by the differences in the severity of the illness of admitted patients. The goal of this study was to predict 30-day severity-adjusted mortality risk in patients with CHF admitted to wards of a teaching hospital in Siena, Italy, in 1997. A 30-day mortality was determined by linking hospital discharge files with the Tuscany Mortality Registry database. The 3M all patient refined diagnosis related group (APR-DRG) software was used as a risk assessment method. The relationships between death and the following variables were studied by univariate analyses: APR-severity risk, APR-mortality risk, age, sex, length of stay and, discharge ward. Multivariate analysis was also performed to verify the associations between death and those parameters found to be significant by univariate analysis. Unadjusted mortality proportions ranged from 4.3 to 44.0%. Logistic regression analysis demonstrated that APR-mortality risk, length of stay, and discharge ward were significantly and independently associated with 30-day mortality risk in patients with CHF. In summary, 30-day mortality risk varied significantly according to the ward of discharge in an Italian teaching hospital, even after adjustment for severity of illness
Confronto fra criteri di registrazione e verifiche di qualità in tre registri tumori: Genova, Firenze, Romagna.
No full textFatti e cifre dei tumori in Italia
No full textMonografia sui dati di incidenza, mortalità, sopravvivenza e prevalenza dei tumori in Italia
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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