Slices of the unitary spread

We prove that slices of the unitary spread of Q(+)(7, q), q equivalent to 2 (mod 3), can be partitioned into five disjoint classes. Slices belonging to different classes are non-equivalent under the action of the subgroup of P Gamma O+(8, q) fixing the unitary spread. When q is even, there is a connection between spreads of Q(+)(7, q) and symplectic 2-spreads of PG(5, q) (see Dillon, Ph.D. thesis, 1974 and Dye, Ann. Mat. Pura Appl. (4) 114, 173-194, 1977). As a consequence of the above result we determine all the possible non-equivalent symplectic 2-spreads arising from the unitary spread of Q(+)(7, q), q = 2(2h+1). Some of these already appeared in Kantor, SIAM J. Algebr. Discrete Methods 3(2), 151-165, 1982. When q = 3(h), we classify, up to the action of the stabilizer in P Gamma O(7, q) of the unitary spread of Q(6, q), those among its slices producing spreads of the elliptic quadric Q(-)(5, q)

Using alternative or direct anthropometric measurements to assess risk for malnutrition in nursing homes.

AbstractObjectiveThe aim of this study was to use the Malnutrition Universal Screening Tool (MUST) to assess the applicability of alternative versus direct anthropometric measurements for evaluating the risk for malnutrition in older individuals living in nursing homes (NHs).MethodsWe conducted a cross-sectional survey in 67 NHs in Tuscany, Italy. We measured the weight, standing height (SH), knee height (KH), ulna length (UL), and middle-upper-arm circumference of 641 NH residents. Correlations between the different methods for calculating body mass index (BMI; using direct or alternative measurements) were evaluated by the intraclass correlation coefficient and the Bland-Altman method; agreement in the allocation of participants to the same risk category was assessed by squared weighted kappa statistic and indicators of internal relative validity.ResultsThe intraclass correlation coefficient for BMI calculated using KH was 0.839 (0.815–0.861), whereas those calculated by UL were 0.890 (0.872–0.905). The limits of agreement were ±6.13 kg/m2 using KH and ±4.66 kg/m2 using UL. For BMI calculated using SH, 79.9% of the patients were at low risk, 8.1% at medium risk, and 12.2% at high risk for malnutrition. The agreement between this classification and that obtained using BMI calculated by alternative measurements was “fair-good.”ConclusionWhen it is not possible to determine risk category by using SH, we suggest using the alternative measurements (primarily UL, due to its highest sensitivity) to predict the height and to compare these evaluations with those obtained by using middle-upper-arm-circumference to predict the BMI

A cross-sectional survey to investigate the quality of care in Tuscan (Italy) nursing homes: the structural, process and outcome indicators of nutritional care

BACKGROUND: Previous studies have investigated process and structure indicators of nutritional care as well as their use in nursing homes (NHs), but the relative weight of these indicators in predicting the risk of malnutrition remains unclear. Aims of the present study are to describe the quality indicators of nutritional care in older residents in a sample of NHs in Tuscany, Italy, and to evaluate the predictors of protein-energy malnutrition risk. METHODS: A cross-sectional survey was conducted in 67 NHs. Information was collected to evaluate quality indicators of nutritional care and the individual risk factors for malnutrition, which was assessed using the Malnutrition Universal Screening Tool. A multilevel model was used to analyse the association between risk and predictors. RESULTS: Out of 2395 participants, 23.7 % were at high, 11 % at medium, and 65.3 % at low risk for malnutrition. Forty-two percent of the NHs had only a personal scale to weigh residents; 88 % did not routinely use a screening test/tool for malnutrition; 60 % used some standardized approach for weight measurement; 43 % did not assess the severity of dysphagia; 12 % were not staffed with dietitians. Patients living in NHs where a chair or platform scale was available had a significantly lower risk of malnutrition (OR = 0.73; 95 % CI = 0.56–0.94). None of the other structural or process quality indicators showed a statistically significant association with malnutrition risk. CONCLUSIONS: Of all the process and structural indicators considered, only the absence of an adequate scale to weigh residents predicted the risk of malnutrition, after adjusting for case mix. These findings prompt the conduction of further investigations on the effectiveness of structural and process indicators that are used to describe quality of nutritional care in NHs