Esther Francia

Assessing nutritional status in the elderly: evaluation of Chumlea´s equations for weight

BACKGROUND Weight is one of the most important parameters in assessing nutritional status. However, weight can be difficult to measure in elderly people who are unable to stand. Chumlea et al. created two equations to estimate weight in non-ambulatory patients using readily available body measurements. OBJECTIVE The aim of the study is to analyze the usefulness of Chumlea equations in assessing nutritional status of elderly hospitalized patients. METHODS We measured weight, height, arm and calf circumference, subscapular skinfold and knee height of 82 hospitalized elderly patients, all of whom were able to stand. Estimated weight (EW) was obtained by Chumlea equations. Body mass index (BMI) and Mini Nutritional Assessment test (MNA) were calculated using actual weight and EW. Bland-Altmann analysis and intraclass correlation coefficient (ICC) between real and estimated parameters were assessed. RESULTS We found a statistically significant ICC between actual weight and EW (r = 0.926), real BMI and estimated BMI (r = 0.910) and real MNA and estimated MNA (r = 0.982) (p < 0.001). Chumlea equations, however, underestimated weight: 54.05 (DS 11.88) vs 61.46 (DS 13.08); BMI: 22.30 (DS 4.61) vs 25.36 (DS 5.17) and MNA: 22.73 (DS 4.43) vs 23.30 (DS 4.33) (P<0.001). In spite of this underestimation, estimated MNA detected 100% of patients malnourished and 96% of those at risk of malnutrition. CONCLUSIONS Results obtained by Chumlea equations showed a good ICC with actual body weight and real BMI and MNA, but values were underestimated. These equations can be useful to detect undernourished hospitalized elderly patients.

Effect of prophylactic treatment with low-molecular-weight heparin bemiparin sodium on serum potassium levels: a prospective observational study.

BackgroundHyperkalaemia is a serious adverse effect of unfractionated heparin, but the effect of low-molecular-weight heparins (LMWHs) on potassium levels is not clear. Previous studies have shown a disparity of results depending on the dose and type of LMWH used.ObjectiveTo analyse potassium level variations in medical and surgical inpatients receiving the LMWH bemiparin sodium at prophylactic doses and assess the consequent effective risk of hyperkalaemia in a real-life setting.MethodsThis was a prospective observational study conducted over a 9-month period in a university teaching hospital. Patients consecutively admitted to internal medicine wards for general medical conditions (n = 145) or to traumatology wards for hip fractures (n = 98) and who received prophylactic bemiparin sodium were enrolled in the study. The intervention consisted of daily dosages of bemiparin sodium (Hibor®) 3500IU (56%)or2500IU (44%) for a minimum of 5 days. The mean age of participants was 80.5 years, with 91.8% being aged ≥65 years. Eighty-six percent of patients had co-morbidities and 79.4% were taking medication affecting potassium homeostasis. The main outcome measures were variations in serum potassium levels observed within 4–8 days of starting bemiparin sodium and the presence of hyperkalaemia (serum potassium >5.1 mmol/L) while on bemiparin sodium treatment.ResultsAfter patients had received bemiparin sodium for a median 6-day period, the mean (±SD) serum potassium level increased from 4.1 ± 0.5 to 4.3 ± 0.5mmol/L(p < 0.001). Hyperkalaemia >5.1 mmol/L developed in ten patients (4.1%), but serum potassium levels >5.5 mmol/L related to bemiparin sodium were present in only two (0.8%). Laboratory tests between the fourth and eighth days identified all but one case of hyperkalaemia. Patients were not symptomatic and discontinuation of bemiparin sodium treatment was not required. There were no statistically significant differences in potassium disturbances between older (aged ≥65 years) and younger (aged <65 years) patients. The maximum serum potassium level showed a significant inverse correlation with bodyweight (R = −0.731; p = 0.016) and creatinine clearance (R = −0.640; p = 0.046), and a positive correlation with the individual variation in serum potassium levels (R = 0.692; p = 0.027) and with serum potassium levels after 4–8 days on bemiparin sodium treatment (R = 0.741; p = 0.014). Baseline potassium level (odds ratio [OR] 26.5, 95% CI 4.7, 150.3; p < 0.001) and treatment with ACE inhibitors (OR 10.5, 95% CI 1.9, 57.8; p = 0.007) were the only predictors of hyperkalaemia at admission (c-statistic 0.88,95% CI 0.78, 0.99). For patients not receiving ACE inhibitors, a baseline serum potassium >4.6 mmol/L was considered the cut-off value for predicting hyperkalaemia (sensitivity 90% and specificity 70%).ConclusionsSerum potassium levels in in-hospital traumatology and medical patients increased significantly with bemiparin sodium prophylaxis but the incidence of relevant hyperkalaemia was low. Patients taking bemiparin sodium who are treated with ACE inhibitors or who have a baseline potassium level >4.6 mmol/L should be monitored for serum potassium levels between days 4 and 8 of hospital admission.

Ability of physiological parameters versus clinical categories to predict mortality on admission to an internal medicine ward

BACKGROUND The prediction of mortality in internal medicine departments may help in taking diagnostic and therapeutic decisions. We analyzed the usefulness of two mortality prediction models, one physiological and the other mainly clinical, and determined whether one approach is better than the other to predict mortality at admission. METHODS This is a prospective observational cohort study in patients admitted to an acute internal medicine ward in a tertiary care, urban, university teaching hospital in Spain. Five hundred consecutive patients either electively admitted or coming from the emergency department from May to December 2008 were analyzed. Medical history, physical examination and routine clinical laboratory tests were performed on admission. At discharge, diagnosis and dead or survived status was recorded. Logistic regression analyses were used to test variables that emerged as independent predictors of mortality. The area under the curve was used to determine which model best predicted mortality. RESULTS Mortality in the ward was 13.0%. Age, chronic respiratory failure, creatinine, mean arterial pressure, respiratory rate and Glasgow coma scale independently predicted mortality. ROC curves showed that the physiological model was superior to the clinical model, but differences were not statistically significant. The predictive capacity improved when the two models were combined but the improvement was not significant. CONCLUSIONS Both models are satisfactory predictors of in-hospital mortality for management purposes but neither proved to be a useful tool for individual predictions. Complementary approaches need to be considered.

Hip fractures in the oldest old. Comparative study of centenarians and nonagenarians and mortality risk factors

INTRODUCTION Centenarians and nonagenarians constitute a rapidly growing age group in Western countries and they are expected to be admitted to hospital with hip fractures. The aim of this study was to compare outcomes of centenarian and nonagenarian patients following a hip fracture and to identify risk factors related to in-hospital and post-discharge mortality in both groups. PATIENTS AND METHODS A prospective evaluation of centenarian patients and nonagenarian controls admitted to a tertiary university hospital in Barcelona with hip fractures over a period of 5 years and 9 months. Baseline characteristics and outcomes in both patient groups were compared. Variables associated with in-hospital, 30-day, 3-month and 1-year mortality were also analyzed. RESULTS Thirty-three centenarians and 82 nonagenarians were included. The most relevant statistically significant differences found were: Barthel index at admission (61.90 vs. 75.22), number of drugs before admission (4.21vs 5.55), in-hospital complication rates (97 vs. 78%), readmissions at 3 months and 1 year (0 vs 11.7% and 3.4 vs. 19.5% respectively) and mortality at 3 months and 1 year (41.4 vs. 20.8% and 62.1 vs. 29.9%, respectively). Mean number of complications, rapid atrial fibrillation, mean age, and urinary tract infection were risk factors associated with mortality. CONCLUSIONS Centenarian patients had similar in-hospital outcomes to nonagenarians, but experienced more complications and twice the 3-month and 1-year mortality rate. The mean number of complications was the risk factor most consistently related to in-hospital and post-discharge mortality. These findings emphasize the need to improve care in very old patients to prevent complications.

Influencia de la edad en los índices probabilísticos de mortalidad al ingreso en salas convencionales de Medicina Interna

BACKGROUND AND OBJECTIVE The predictive models of in-hospital mortality in the departments of Internal Medicine have not reached a generalized use. Our hypothesis is that the very elderly patients interfere in the models currently in use. PATIENTS AND METHOD In this observational, prospective cohort study, 1,500 patients admitted consecutively in the department of Internal Medicine were analysed. A logistic regression analysis based on the REMS model was used for the whole series and after segmenting it according to if the age of patients was 85 years or less, or more than 85 years. RESULTS The global in-hospital mortality of the patients was 12%. Although the REMS model predicted a global mortality of 11.9%, sensitivity and specificity for an individual prediction were not satisfactory because the AUC was only 0.704. When the sample was split according to the age of patients, the model gained precision for the group ≤ 85 years (AUC 0.799), whereas it lost sensitivity and specificity for the group of patients > 85 years (AUC 0.66). CONCLUSIONS Age of patients interferes in the general models of prediction of mortality in departments of Internal Medicine. There may be important variables in advanced age not taken into account in the predictive models nowadays available. We think that specific predictive models of in-hospital mortality in Internal Medicine should be designed for patients of advanced age.