RESUMEN
ABSTRACT: Aging of population is characterized by multiple chronic conditions in the same individual. Health-related quality of life (HR-QOL) reflects the multidimensional impact of chronic disease on population and it is increasingly analysed as outcomes.The aim of this study was the evaluation of the predictors of quality of life among elderly patients hospitalized in internal medicine ward, investigating the effect of comorbidities on health-related quality of life.Data collected in this cross-sectional study were analysed. Socio-demographic, clinical characteristics, disease distribution and quality of life by the 12-Item Short Form Health Survey (SF-12) were evaluated.Of 240 inpatients, subjects with Barthel Index (BI)≤40 were 23.7%, 55% had a Geriatric Depression Scale (GDS)≥2. After categorizing mental component score (MCS) and physical component score (PCS) in five classes, we found that diabetics and patients with cancer were more frequent in the first class of MCS while patients with NYHA III-IV are significantly more frequent in the first class of PCS. When we classified patients according to GDS≥2 orâ<â2, subjects with GDS≥2 had BI and MCS significantly lower. In the multivariate analysis GDS score ≥2 was independently associated with first MCS class [16.32 (3.77-70.68)] while NYHA III-IV class and claudicatio intermittents were strong predictors of the worst PCS class [9.54 (1.97-47.40), 2.53 (1.16-5.49), respectively]. Liver disease was independently associated with GDS≥2 [5.26 (1.13-24.39)].Our study highlighted the impact of chronic diseases on health-related quality of life in elderly subjects hospitalized in an internal medicine ward pointing out the importance of taking into account patient's needs and perception and the setting up of a personalised health-care. Patients with diabetes and liver disease along with persons affected by cancer need psychological support to improve their quality of life. A GDS score ≥ 2 is a strong predictor of poor quality of life and should trigger an in-depth assessment of mental health in this kind of patients.
Asunto(s)
Depresión/psicología , Anciano Frágil/psicología , Hospitalización , Afecciones Crónicas Múltiples/psicología , Cuestionario de Salud del Paciente , Calidad de Vida , Anciano , Estudios Transversales , Diabetes Mellitus/psicología , Femenino , Departamentos de Hospitales , Humanos , Medicina Interna , Hepatopatías/psicología , Masculino , Neoplasias/psicología , Apoyo SocialRESUMEN
The outbreak of coronavirus disease 2019 (COVID-19) is posing a threat to global health. This disease has different clinical manifestations and different outcomes. The immune response to the novel 2019 coronavirus is complex and involves both innate and adaptive immunity. In this context, cell-mediated immunity plays a vital role in effective immunity against SARS-CoV-2. Significant differences have been observed when comparing severe and non-severe patients. Since these immunological characteristics have not been fully elucidated, we aimed to use cluster analysis to investigate the immune cell patterns in patients with COVID-19 who required hospitalization but not intensive care. We identified four clusters of different immunological patterns, the worst being characterized by total lymphocytes, T helper lymphocytes CD4+ (CD4+), T cytotoxic lymphocytes CD8+ (CD8+) and natural killer (NK) cells below the normal range, together with natural killer lymphocyte granzyme < 50% (NK granzyme+) and antibody-secreting plasma cells (ASCs) equal to 0 with fatal outcomes. In the worst group, 50% of patients died in the intensive care unit. Moreover, a negative trend was found among four groups regarding total lymphocytes, CD4+, CD8+ and B lymphocytes (p < 0.001, p < 0.005, p < 0.000, p < 0.044, respectively). This detailed analysis of immune changes may have prognostic value. It may provide a new perspective for identifying subsets of COVID-19 patients and selecting novel prospective treatment strategies. Notwithstanding these results, this is a preliminary report with a small sample size, and our data may not be generalizable. Further cohort studies with larger samples are necessary to quantify the prognostic value's weight, according to immunological changes in COVID-19 patients, for predicting prognoses and realizing improvements in clinical conditions.