Factores asociados a calidad de vida en pacientes de hemodiálisis incidentes y prevalentes

Introducción: la insuficiencia renal crónica IRC ha aumentado su prevalencia en los últimos años pasando de 44.7 pacientes por millón en 1993 a 538.46 pacientes por millón en 2010, los pacientes quienes reciben terapia de remplazo renal hemodiálisis en Colombia cada vez tienen una mayor sobrevida. El incremento de los pacientes y el incremento de la sobrevida nos enfocan a mejorar la calidad de vida de los años de diálisis. Metodología: se comparó la calidad de vida por medio del SF-36 en 154 pacientes con IRC estadio terminal en manejo con hemodiálisis, 77 pacientes incidentes y 77 pacientes prevalentes, pertenecientes a una unidad renal en Bogotá, Colombia. Resultados: se encontró una disminución de la calidad de vida en los componentes físicos (PCS) y metales (MCS) de los pacientes de hemodiálisis en ambos grupos. En el modelo de regresión logística la incapacidad laboral (p=0.05), el uso de catéter (p= 0,000), el bajo índice de masa corporal (p=0.021), la hipoalbuminemia (p=0,033) y la anemia (p=0,001) fueron factores determinantes en un 78,9% de baja calidad de vida de PCS en los pacientes incidentes con respecto a los prevalentes. En el MCS de los pacientes incidentes vs. Prevalentes se encontró la hipoalbuminemia (p=0.007), la anemia (p=0.001) y el acceso por catéter (p=0.001) como factores determinantes en un 70.6% de bajo MCS Conclusiones: la calidad de vida de los pacientes de diálisis se encuentra afectada con mayor repercusión en el grupo de los pacientes incidentes, se debe mejorar los aspectos nutricionales, hematológicos y de acceso vascular en este grupo.

A prediction model for establishing the disability degree in adults with spinal cord injury: results based on WHO-DAS II perspective

Objective: To establish a prediction model of the degree of disability in adults with Spinal CordInjury (SCI ) based on the use of the WHO-DAS II . Methods: The disability degree was correlatedwith three variable groups: clinical, sociodemographic and those related with rehabilitation services.A model of multiple linear regression was built to predict disability. 45 people with sci exhibitingdiverse etiology, neurological level and completeness participated. Patients were older than 18 andthey had more than a six-month post-injury. The WHO-DAS II and the ASIA impairment scale(AIS ) were used. Results: Variables that evidenced a significant relationship with disability were thefollowing: occupational situation, type of affiliation to the public health care system, injury evolutiontime, neurological level, partial preservation zone, ais motor and sensory scores and number ofclinical complications during the last year. Complications significantly associated to disability werejoint pain, urinary infections, intestinal problems and autonomic disreflexia. None of the variablesrelated to rehabilitation services showed significant association with disability. The disability degreeexhibited significant differences in favor of the groups that received the following services: assistivedevices supply and vocational, job or educational counseling. Conclusions: The best predictiondisability model in adults with sci with more than six months post-injury was built with variablesof injury evolution time, AIS sensory score and injury-related unemployment.

Clinical prediction of occupational and non-specific low back pain

Non-specific Occupational Low Back Pain (NOLBP) is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 metthe purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.