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1.
Blood Transfus ; 9(4): 413-8, 2011 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-21839024

RESUMO

BACKGROUND: After years of surpluses in numerous blood components in the province of Ravenna, there is now evidence that the increased use of such products is leading to an ever less abundant self-sufficiency. The concern about the possible loss of self-sufficiency, in a province in which the population of donors does not seem to be adequate to compensate for transfusion domands, led us to verify consumption and future prospects in greater detail. MATERIALS AND METHODS: In order to plan future transfusion needs, past consumption was analysed dividing the population into several age groups. This historical use of blood products was projected into the scenario of the population in years to come to estimate needs and their increases over time. RESULTS: The use of transfusion products is very different in different age groups, increasing notably with age. Age factor was identified as the most important factor determining blood product consumption. DISCUSSION: It will, therefore, be the aging of the population that causes an increase in blood product requirements. Projections from the Italian Institute of Statistics considering age groups of the population up to 2051 enable predictions of transfusion needs, in the absence of drastic interventions on the appropriateness of transfusion practices. Considering that the public and private hospitals of Ravenna predominantly admit subjects from its own territory, these predictions appear realistic, provided that new reasons for consumption are not introduced.


Assuntos
Transfusão de Sangue/estatística & dados numéricos , Transfusão de Sangue/tendências , Avaliação das Necessidades , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Previsões , Humanos , Lactente , Itália , Pessoa de Meia-Idade , Adulto Jovem
2.
Blood Transfus ; 9(4): 383-7, 2011 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-21627924

RESUMO

BACKGROUND: Previous studies have shown the usefulness of combining information from different data sources to identify and analyse variations in transfusion practices. Good knowledge of the conditions leading to blood use is a fundamental requirement for the assessment of the appropriateness of blood transfusion. MATERIALS AND METHODS: In this study we combined blood transfusion data obtained from the Blood Bank information system with patients' data from the Hospital Discharge Database, based on the ICD9 classification system, from 1,827 surgical procedures performed in seven different orthopaedic divisions in the Ravenna area between January and December 2009. Hip and knee replacement surgery (primary or revision) and operations following femoral fractures (partial hip replacement and reduction with internal fixation) were considered. For a subgroup of patients clinical and transfusion data were also combined with haemoglobin values obtained from the laboratory information system. RESULTS: Of the 1,827 surgical procedures, 1,038 (56.8%) were followed by transfusion of red cells. The likelihood of receiving a transfusion varied depending on the patient's sex (49% for males, 60% for females), age, and on the surgical procedure, being higher for interventions following femoral fractures and for revisions of hip replacement: about 70% of patients undergoing these interventions required transfusion. A large variability in transfusion rates was observed between the seven divisions, which was only partially explained by the different types of surgery (post-traumatic or elective) performed by any of them: relevant variations were also observed for the same type of intervention. DISCUSSION: Combining information from different data sources could be a time-sparing way to gain useful information about transfusion practices, so contributing to optimising blood usage.


Assuntos
Artroplastia de Quadril , Artroplastia do Joelho , Benchmarking , Transfusão de Eritrócitos/normas , Fixação Interna de Fraturas , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Coleta de Dados , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Adulto Jovem
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