1,720,969 research outputs found
Medication use and polypharmacy in Rehabilitation Center inpatients following Acquired Brain Injury: a cross-sectional survey in Italy
The accuracy of discharge diagnosis coding for Amyotrophic Lateral Sclerosis in a large teaching hospital
To evaluate the accuracy of hospital discharge data as a source of Amyotrophic Lateral Sclerosis (ALS) cases for epidemiological studies or disease registries, a validation study was performed. All records of patients discharged in 2005 and 2006 with principal or secondary International Classification of Diseases, 9th rev., Clinical Modification (ICD 9 CM) diagnosis code of ALS (335.20), other anterior horn cell disease (335), spinal cord disease (336), hereditary and idiopathic peripheral neuropathy (356), inflammatory and toxic neuropathy (357), myoneural disorders (358), muscular dystrophies and myopathies (359), were selected from the electronic archive of discharge data of the University Hospital of Udine, Friuli Venezia Giulia Region, North East Italy. Corresponding clinical documentation was reviewed to ascertain the presence of El Escorial criteria, the gold standard. Sensitivity of the ICD 9 CM discharge code 335.20 was 93% (95%CI: 82-99%) and decreased to 91% (95%CI: 77-98%) when suspect ALS was excluded. Specificity was 99% (95%CI: 97-99%). The ICD 9 CM discharge code 335.20 can identify a high percentage of hospitalizations of patients truly affected by ALS and of patients with no ALS, among selected neurological diagnostic codes. To ensure complete ALS case ascertainment, prospective population-based registries or epidemiologic studies require active prospective surveillance and use of multiple sources, among them hospital discharge archives can provide accurate information
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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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