[Factors associated with prehospital delay in men and women with acute coronary syndrome]. / Factores asociados a la demora prehospitalaria en hombresy mujeres con síndrome coronario agudo.

OBJECTIVE: To identify factors associated with prehospital delay in people who have had an acute coronary syndrome. METHODS: Using a survey we studied patients admitted due to acute coronary syndrome in the 33 Andalusian public hospitals, obtaining information about different types of variables: socio-demographic, contextual,clinical, perception, action, and transportation.Multivariate logistic regression models were applied to calculate the odds ratios for the delay. RESULTS: Of the 1,416 patients studied, more than half had a delay of more than an hour. This is associated to distance to the hospital and means of transport: when the event occurs in the same city,using the patient's own means of transport increases the delay, odds ratio = 1.51 (1.02 to 2.23); if the distance is 1 to 25 kilometers from the hospital,there is no difference between the patient's own means of transport and an ambulance, odds ratio =1.41 and odds ratio =1.43 respectively; and when the distance exceeds 25 kilometers transport by ambulance means more delay, odds ratio = 3.13 and odds ratio = 2.20 respectively. Also, typical symptoms reduce delay amongst men but increase amongst women. Also, not caring and waiting for the resolution of symptoms, seeking health care other than a hospital or emergency services, previous clinical history, being away from home, and having an income under 1,500 euros, all increase delay. Respiratory symptoms reduce delay. CONCLUSIONS: Prehospital delay times do not meet health recommendations. The physical and social environment,in addition to clinical, perceptual and attitudinal factors, are associated with this delay.

Factores asociados a la demora prehospitalaria en hombres y mujeres con síndrome coronario agudo / Factors associated with prehospital delay in men and women with acute coronary syndrome

Fundamento: Identificar factores asociados a la demora prehospitalaria en personas que han tenido un síndrome coronario agudo Material y métodos: Se estudiaron mediante encuesta pacientes ingresados por síndrome coronario agudo en los 33 hospitales públicos andaluces, obteniéndose información sobre diferentes tipos de variables: socio-demográficas, contextuales, clínicas, percepción, actuaciones, y transporte. Se aplicaron modelos de regresión logística multivariante para calcular las odds ratio para la demora. Resultados: De los 1.416 pacientes en total, más de la mitad tuvieron una demora superior a la hora. Se asocia a la distancia al hospital y al medio de transporte: cuando el evento ocurre en la misma ciudad del hospital, utilizar medios propios aumenta la demora, odds ratio= 1,51 (1,02-2,23); si la distancia es entre 1-25 kilómetros, no hay una diferencia entre medios propios y ambulancia, odds ratio = 1,41 y odds ratio = 1,43 respectivamente; y cuando supera los 25 kilómetros la ambulancia implica mayor demora, odds ratio = 3,13 y odds ratio = 2,20 respectivamente. Además, la sintomatología típica reduce la demora entre los hombres, pero la aumenta entre las mujeres. Asimismo, no darle importancia, esperar a la resolución de los síntomas, buscar atención sanitaria diferente a urgencias hospitalarias o al 061, tener antecedentes, encontrarse fuera de la vivienda habitual, y tener ingresos menores de 1.500 euros aumentan la demora. Tener síntomas respiratorios la reduce. Conclusiones: La demora prehospitalaria no se ajusta a las recomendaciones sanitarias, asociándose al entorno físico y social, a factores clínicos, y de percepción y actitudinales de los sujetos (AU)

Objective. To identify factors associated with prehospital delay in people who have had an acute coronary syndrome. Methods. Using a survey we studied patients admitted due to acute coronary syndrome in the 33 Andalusian public hospitals, obtaining information about different types of variables: socio-demographic, contextual, clinical, perception, action, and transportation. Multivariate logistic regression models were applied to calculate the odds ratios for the delay. Results. Of the 1,416 patients studied, more than half had a delay of more than an hour. This is associated to distance to the hospital and means of transport: when the event occurs in the same city, using the patient’s own means of transport increases the delay, odds ratio = 1.51 (1.02 to 2.23); if the distance is 1 to 25 kilometers from the hospital, there is no difference between the patient’s own means of transport and an ambulance, odds ratio = 1.41 and odds ratio =1.43 respectively; and when the distance exceeds 25 kilometers transport by ambulance means more delay, odds ratio = 3.13 and odds ratio = 2.20 respectively. Also, typical symptoms reduce delay amongst men but increase amongst women. Also, not caring and waiting for the resolution of symptoms, seeking health care other than a hospital or emergency services, previous clinical history, being away from home, and having an income under 1,500 euros, all increase delay. Respiratory symptoms reduce delay. Conclusions. Prehospital delay times do not meet health recommendations. The physical and social environment, in addition to clinical, perceptual and attitudinal factors, are associated with this delay (AU)