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Titles and abstracts of all retrieved articles were screened for inclusion. Relevant full-length articles were retrieved and reviewed to declare if they met the predetermined inclusion criteria by one author (J.L.). A second author (K.L.) confirmed the applicability of the criteria to the selected articles. Any disagreement was settled by consensus between the authors. For inclusion, articles had to compare routinely collected hospital discharge information in administrative databases with an individualized patient or medical records review. Studies could be either prospective or retrospective and be in any adult or paediatric populations in primary, secondary or tertiary healthcare settings. At least one or more of the following validity measures had to be reported click here or calculable from the data contained in the report for specific co-morbidities: specificity (Sp), sensitivity (Sn), positive predictive value (PPV) and negative predictive value (NPV). With regard to co-morbidity indexes, hospital discharge information as coded by general medical records staff was defined as adapted co-morbidity indexes for use with the classification selleck inhibitor of the International Classification of Diseases versions 9, 9-CM, or 10 and were compared with indices calculated using patient or clinical records review by healthcare professionals, study investigators or content experts. Population characteristics, co-morbidity and adapted ICD-based indexes were used, and results were abstracted from each review article onto a standardized collection form. Because a potentially very large number of co-morbidities could be evaluated, we selected 21 co-morbid conditions to focus upon in analysis. These 21 conditions were selected a priori and were based on the individual components of the Charlson Co-morbidity Index, our experience and ten co-morbidities most commonly assessed in population-based studies of invasive infections [including cancer (including any malignancy and metastatic solid tumour), heart disease (including myocardial infarction, MI; and congestive heart failure, CHF), diabetes mellitus, stroke (CVD), lung disease, rheumatoid arthritis, chronic renal dysfunction and/or failure, alcoholism, organ/bone marrow transplant and AIDS] as determined by a non-structured literature review [3,13,20,22,23]. Where possible, validity measures were calculated for administrative data Sitaxentan as compared with conventionally determined values. Meta-DiSc (Madrid, Spain 2006) was used to calculate corresponding confidence intervals [24]. Administrative database systems with overall validity measures ��95% were a priori defined as excellent; 80�C94% as very good; 60�C79% as moderate; and