ABSTRACT
ObjetivoEl dolor crónico es un proceso complejo que puede variar dependiendo de factores como el tiempo de evolución, estado de ánimo o incluso experiencias previas vividas. Nuestro objetivo es describir las características de los pacientes que acuden con diagnóstico de lumbalgia a una primera visita en la Unidad del Dolor (UD) y buscar aquellos factores que pueden interferir en la percepción del dolor.MétodosSe realiza un análisis inferencial de los pacientes que acuden por primera vez a la UD del Hospital de la Santa Creu y Sant Pau de Barcelona con diagnóstico de lumbalgia crónica durante el periodo de Noviembre 2012 a Noviembre 2018. La intensidad del dolor promedio en las últimas 24 horas se cuantifica utilizando datos del cuestionario Brief Pain Inventory (BPI). Utilizando regresión linear múltiple, se valoran los factores predictivos independientes de intensidad de dolor EVN24.ResultadosLa variable de mayor impacto fue el grado de depresión según HAD_D. Utilizando regresión logística binaria para el análisis multivariado, se obtuvo un modelo que se relaciona (r = 0,354, p < 0,001) de manera significativa con la intensidad del dolor (EVN24).ConclusionesEl tratamiento especializado de la lumbalgia en las UD debe tener en cuenta el perfil de paciente y en especial los trastornos afectivos y las comorbilidades asociadas ya que predicen una mayor intensidad del dolor. En consecuencia, la comorbilidad asociada no solo repercute en la mayor intensidad del dolor, sino que las características físicas que acompañan al paciente durante todo el proceso pueden influir o incluso comprometer el tratamiento. (AU)
ObjectivesChronic pain is a complex process that can vary depending on factors such as time evolution, mood, or even previous experiences. Our objective is to describe patient's characteristics from those who were referred with a diagnosis of low back pain in their first Pain Unit (PU) visit, and identify those factors that may interfere with their pain perception.MethodsInferential analysis was carried out from data recorded in the PU database of the Hospital de la Santa Creu y Sant Pau in Barcelona, from November 2012 to November 2018. The average pain intensity during the last 24 hours (EVN24) was quantified using data from the BPI (Brief Pain Inventory) questionnaire. Using multiple linear regression, the independent predictive factors related to pain intensity (EVN24) were assessed.ResultsMood disorders (Degree of depresión acording HAD_D level) was the variable with the highest impact in pain perception. Using binary logistic regression for multivariate analysis, a model of variables related to pain intensity (EVN24) was obtained (R = 0.354, P < 0.001).ConclusionsThe specialized treatment of low back pain in PUs must take into account the patient's profile and especially the affective disorders and associated comorbidities since they predict a greater intensity of pain. Consequently, the associated comorbidity not only affects the greater intensity of pain, but the physical characteristics that accompany the patient throughout the process can influence or even compromise treatment. (AU)
Subject(s)
Humans , Chronic Pain/epidemiology , Low Back Pain/epidemiology , Pain , Patients , Comorbidity , Surveys and QuestionnairesABSTRACT
OBJECTIVES: Chronic pain is a complex process that can vary depending on factors such as time evolution, mood, or even previous experiences. Our objective is to describe patient's characteristics from those who were referred with a diagnosis of low back pain in their first Pain Unit (PU) visit, and identify those factors that may interfere with their pain perception. METHODS: Inferential analysis was carried out from data recorded in the PU database of the Hospital de la Santa Creu y Sant Pau in Barcelona, from November 2012 to November 2018. The average pain intensity during the last 24 hours (EVN24) was quantified using data from the BPI (Brief Pain Inventory) questionnaire. Using multiple linear regression, the independent predictive factors related to pain intensity (EVN24) were assessed. RESULTS: Mood disorders (Degree of depresión acording HAD_D level) was the variable with the highest impact in pain perception. Using binary logistic regression for multivariate analysis, a model of variables related to pain intensity (EVN24) was obtained (R = 0.354, P < 0.001). CONCLUSIONS: The specialized treatment of low back pain in PUs must take into account the patient's profile and especially the affective disorders and associated comorbidities since they predict a greater intensity of pain. Consequently, the associated comorbidity not only affects the greater intensity of pain, but the physical characteristics that accompany the patient throughout the process can influence or even compromise treatment.
