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1.
Rheumatology (Oxford) ; 51(5): 841-51, 2012 May.
Artigo em Inglês | MEDLINE | ID: mdl-22258388

RESUMO

OBJECTIVE: Frequent genetic variants may be associated with GCA. Existing studies have analysed a limited number of candidate genes and genetic variants. To expand this information, we performed a case-control study genotyping 130 single nucleotide polymorphisms (SNPs) in 82 biopsy-proven GCA patients and 166 healthy controls from the Spanish population. METHODS: SNPs in coding and regulatory gene regions of 14 candidate genes (CCL2, CCR7, IL10, IL12A, IL1A, IL1B, IL1RN, IL6, IL8, INFG, LTA, NOS2, TNF and VEGF) were explored using the Illumina Bead Array System. Multivariate methods based on logistic regression were used for statistical analysis. RESULTS: Nine SNPs located in five genes had significant association with GCA risk (P < 0.05). These SNPs were located in the NOS2 (rs2779251), VEGF (rs1885657, rs2010963, rs699946 and rs699947), IL1RN (rs17207494), IL6 (rs7805828 and rs1546766) and CCL2 (rs1860190) genes. The strongest associations were seen for rs2779251, rs1885657 and rs2010963 (P = 2.3 × 10(-5), P = 0.0078 and P = 0.0097, respectively). The presence of the minor allele of NOS2 variant rs2779251 had a protective effect on the risk for GCA [odds ratio (OR) = 0.27, 95% CI 0.14, 0.52]. Risk alleles for three of the four SNPs in the VEGF gene (rs2010963, rs699946 and rs699947) were associated in homozygosis with increased risk (OR = 4.22, 95% CI 1.38, 12.87; OR = 9.04, 95% CI 1.58, 51.81; and OR = 2.38, 95% CI 1.05, 5.38, respectively), whereas a minor allele for the other SNP (rs1885657) had a protective effect (OR = 0.46, 95% CI 0.26, 0.84). CONCLUSION: Common genetic variants in NOS2, VEGF, IL6, ILRN1 and CCL2 genes are associated with GCA, indicating a polygenic influence on disease susceptibility.


Assuntos
Quimiocina CCL2/genética , Arterite de Células Gigantes/genética , Proteína Antagonista do Receptor de Interleucina 1/genética , Interleucina-6/genética , Óxido Nítrico Sintase Tipo II/genética , Polimorfismo de Nucleotídeo Único , Fator A de Crescimento do Endotélio Vascular/genética , Idoso , Idoso de 80 Anos ou mais , Alelos , Estudos de Casos e Controles , Feminino , Estudos de Associação Genética , Predisposição Genética para Doença , Genótipo , Haplótipos , Humanos , Masculino , Pessoa de Meia-Idade
2.
Am J Emerg Med ; 25(8): 865-72, 2007 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-17920969

RESUMO

AIM: The aim of the study was to establish a triage flowchart to rule out acute coronary syndrome (ACS) among patients with chest pain (CP) arriving on an Emergency Department (ED). PATIENTS AND METHOD: This prospective observational study included 1000 consecutive patients with CP arriving on an ED CP unit. Demographic and clinical characteristics along with vital signs were recorded as independent variables. After CP unit protocol completion and 1-month follow-up, patients were classified as (dependent variable) (1) true non-ACS (all noncoronary patients at the first visit that kept this condition when called 1 month later) or (2) true ACS (all the remaining patients). Relationship among variables was assessed by multiple logistic regression analysis. A triage flowchart was obtained from significant variables and applied to patients with CP who were then grouped in "triage non-ACS" and "triage ACS." Validity indexes to exclude ACS for triage flowchart were measured. RESULTS: Variables significantly associated with non-ACS and included in the triage flowchart were age <40 years (odds ratio 3.61, 95% CI 1.63-7.99), absence of diabetes (2.74, 1.53-4.88), no previously known coronary artery disease (5.46, 3.42-8.71), nonoppressive pain (10.63, 6.04-18.70), and nonretrosternal pain (5.16, 2.82-9.42). For the triage flowchart, both specificity and positive predictive value to rule out ACS were 100%. CONCLUSIONS: The triage flowchart is able to accurately identify patients with CP not having an ACS. It may help triage nurses make quick decisions on who should be immediately seen and who could safely wait when delays in medical attention are unavoidable. Prospective validation is needed.


Assuntos
Angina Instável/diagnóstico , Dor no Peito/etiologia , Infarto do Miocárdio/diagnóstico , Triagem/métodos , Adulto , Fatores Etários , Idoso , Algoritmos , Análise de Variância , Estudos de Coortes , Diagnóstico Diferencial , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Curva ROC , Sensibilidade e Especificidade
5.
Med Clin (Barc) ; 121(5): 161-72, 2003 Jul 05.
Artigo em Espanhol | MEDLINE | ID: mdl-12867001

RESUMO

BACKGROUND AND OBJECTIVE: Emergency department (ED) overcrowding has been increasing over the last years. The aims are to define ED overcrowding, and to determine and quantify which factors explain it. PATIENTS AND METHOD: For 3 consecutive weeks throughout 3 years (2000-2002), we recorded every 3-hour period, the arrivals, the occupancy rate (OR) of patients in ED, in first aid area (FAA), and in observation area (OA) according to the reason for their stay. The data was subjected to multiple logistic regression analysis including as a dependent variable non overcrowding/overcrowding for each area (ED, FAA, and OA). Overcrowding was defined as an OR >= 100%. Models from the three areas were calculated according to goodness of fit and were discriminated by ROC methodology. Models were set up after randomizing data in two groups: selection set (88% of data) and validation set (12% of data). RESULTS: Variables associated with overcrowding in the ED model were OR of patients waiting for test results, for a bed going to be left, to find a bed, for test performed out of ED, and for outcome. In the FAA model, they were OR of patients being seen, and waiting for test results. Finally, in the OA model they were OR of patients waiting for a bed going to be left, to find a bed, for test performed out of ED, and for outcome. For all models sensitivity and specificity were greater than 85%, with a ROC area greater than 0.97. We did not find any relationship between number of arrivals and overcrowding for none model. Results were corroborated on the validation data set. CONCLUSIONS: Patients remaining in the ED due to factors related to both hospital (waiting for a bed going to be left, or to find a bed), and ED itself (waiting for outcome) are the main reason for ED overcrowding.


Assuntos
Serviço Hospitalar de Emergência/organização & administração , Serviço Hospitalar de Emergência/estatística & dados numéricos , Humanos , Análise de Regressão , Espanha/epidemiologia
6.
Med. clín (Ed. impr.) ; 121(5): 167-172, mayo 2003.
Artigo em Espanhol | IBECS | ID: ibc-23819

RESUMO

FUNDAMENTO Y OBJETIVO: La utilización de los servicios de urgencias hospitalarios (SUH) es cada vez mayor, lo que conduce a su masificación. El objetivo del presente trabajo es definir la "saturación" de un SUH y determinar y cuantificar los factores que la condicionan. PACIENTES Y MÉTODO: Durante tres semanas consecutivas de años distintos (2000-2002) se contabilizaron cada 3 h las entradas, el índice de ocupación (IO) de los pacientes que permanecían en el SUH, en el área de primera asistencia (APA) y en el área de observación (AO) según la causa de dicha permanencia. Los datos se sometieron a análisis de regresión logística múltiple con la variable dependiente "saturación/no saturación" de cada una de las áreas (SUH, APA y AO). Se definió la saturación cuando el IO era igual o superior al 100 por ciento. Los modelos de cada área se calibraron por la prueba de Hosmer-Lemeshow y se discriminaron por metodología ROC. Los modelos explicativos se armaron separando aleatoriamente dos grupos: selección (88 por ciento de datos) y validación (12 por ciento de datos).RESULTADOS: Las variables que se asociaron de forma significativa a la saturación en el modelo del SUH fueron el IO debido a los pacientes que esperaban resultados, ir a una cama, encontrar cama, exploraciones complementarias y en evolución. En el modelo del APA, lo fueron el IO debido a los que estaban visitándose y esperaban resultados. Finalmente, para el modelo del AO lo fueron el IO debido a los que esperaban ir a una cama, encontrar cama, exploraciones complementarias y en evolución. Todos los modelos mostraron sensibilidad y especificidad superiores al 85 por ciento y un área ROC superior a 0,97. En ningún caso el número de pacientes que acuden a urgencias participó del modelo explicativo final. En el grupo de validación se confirmaron estos resultados. CONCLUSIONES: Los pacientes que permanecen en el servicio de urgencias por factores dependientes tanto del hospital (esperando ir a una cama o encontrar una cama) como del propio servicio de urgencias (esperando evolución) son la principal causa de saturación de los SUH (AU)


Assuntos
Criança , Masculino , Feminino , Humanos , Dieta , Espanha , Inquéritos e Questionários , Ingestão de Energia , Estudos Transversais
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