A prospective observational study of outcomes from rehabilitation of elderly patients with moderate to severe cognitive impairment

OBJECTIVES: To evaluate rehabilitation outcomes in patients with moderate to severe cognitive impairment. DESIGN: Prospective observational cohort study. SETTING: Rehabilitation unit for older people. SUBJECTS: A total of 116 patients (70F) mean age (SD) 86.3 (6.4). Group 1: 89 patients with moderate cognitive impairment (Mini-Mental State Examination 11-20); and Group 2: 27 patients with severe cognitive impairment (Mini-Mental State Examination 0-10). INTERVENTION: A personalised rehabilitation plan. MAIN MEASURES: Barthel Activity of Daily Living score on admission and discharge, length of stay and discharge destination. RESULTS: Of 116 patients, 64 (55.2%) showed an improvement in Barthel score. Mini-Mental State Examination was significantly higher in those who improved, 15.4 (SD 3.7) vs.13.2 (SD 5.1): p = 0.01. The mean Barthel score improved in both groups; Group 1 - 14.7 (SD 19.1) vs. Group 2 - 9.3 (SD 16.3): p = 0.17. Of 84 home admissions in Group 1, more patients returning home showed improvements of at least 5 points in the Barthel score compared with nursing/residential home discharges (32/37 - 86.5% vs. 10/28 - 35.7%: p = 0.0001). In Group 2 of 17 home admissions, 6/6 (100%) home discharges showed improvement compared with 3/7 (42.8%) discharges to nursing/residential home (p = 0.07). In Group 1, a discharge home was associated with significantly greater improvement in number of Barthel items than a nursing/residential home discharge (3.27 (SD 2.07) vs. 1.86 (SD 2.32): p = 0.007). A similar non-significant pattern was noted for severe cognitive impairment patients (3.5 (3.06) vs. 1.14 (1.06); p = 0.1). CONCLUSION: Patients with moderate to severe cognitive impairment demonstrated significant improvements in Barthel score and Barthel items showing that such patients can and do improve with rehabilitation.published_or_final_versio

Diploids in the Cryptococcus neoformans Serotype A Population Homozygous for the α Mating Type Originate via Unisexual Mating

The ubiquitous environmental human pathogen Cryptococcus neoformans is traditionally considered a haploid fungus with a bipolar mating system. In nature, the α mating type is overwhelmingly predominant over a. How genetic diversity is generated and maintained by this heterothallic fungus in a largely unisexual α population is unclear. Recently it was discovered that C. neoformans can undergo same-sex mating under laboratory conditions generating both diploid intermediates and haploid recombinant progeny. Same-sex mating (α-α) also occurs in nature as evidenced by the existence of natural diploid αADα hybrids that arose by fusion between two α cells of different serotypes (A and D). How significantly this novel sexual style contributes to genetic diversity of the Cryptococcus population was unknown. In this study, ∼500 natural C. neoformans isolates were tested for ploidy and close to 8% were found to be diploid by fluorescence flow cytometry analysis. The majority of these diploids were serotype A isolates with two copies of the α MAT locus allele. Among those, several are intra-varietal allodiploid hybrids produced by fusion of two genetically distinct α cells through same-sex mating. The majority, however, are autodiploids that harbor two seemingly identical copies of the genome and arose via either endoreplication or clonal mating. The diploids identified were isolated from different geographic locations and varied genotypically and phenotypically, indicating independent non-clonal origins. The present study demonstrates that unisexual mating produces diploid isolates of C. neoformans in nature, giving rise to populations of hybrids and mixed ploidy. Our findings underscore the importance of same-sex mating in shaping the current population structure of this important human pathogenic fungus, with implications for mechanisms of selfing and inbreeding in other microbial pathogens

A comparative study of the use of three cognitive function screening tests on rehabilitation wards for older people

Background Cognitive function tests are often used to predict rehabilitation outcomes. We aimed to determine how predictive the MMSE, CLOX and a short Frontal Lobe Assessment (sFLA) were in determining likely improvement in activities of daily living and discharge home. Materials and methods In a prospective observational study, we evaluated a cohort of 241 patients [97 Male mean (SD) median age: 84.4 (7.27) 85 years]. Functional ability was assessed using the Barthel Activities of Daily Living (BADL) scale. Outcomes were an improvement in one domain on the BADL and discharge home. Results Whatever the tool, abnormal cognition was an independent factor for lack of improvement in BADL [MMSE – P = 0.000 (B = 1.11; 95%CI: 1.05–1.17); CLOX – P = 0.007 (B = 1.13; 95% CI: 1.06–1.22) and sFLA – P = 0.0001 (B = 1.19; 95% CI: 1.09–1.31)] and for failure to discharge home [MMSE – P = 0.0001 (B = 1.13; 95%CI: 1.06–1.19); CLOX – P = 0.007 (B = 1.12; 95%CI: 1.03–1.21) and sFLA – P = 0.002 (B = 1.18; 95%CI: 1.06–1.31)]. The MMSE correlated positively with the CLOX and sFLA (r = 0.54: P = 0.000 and r = 0.7: P = 0.000 respectively) and a weaker positive correlation between the CLOX and sFLA (r = 0.43: P = 0.000). The Receiver Operative Characteristic (ROC) Curves for all tests mirrored each other across the range of scores with similar and modest areas under the curves for the prediction of improvement in BADL and discharge home (BADL: range 0.65–0.68 and discharge home: range 0.70–0.77). Conclusion Although the MMSE, CLOX and sFLA assess different aspects of cognition, there seems little benefit of one test over another. Over reliance on these tests alone, to determine the likely outcome of rehabilitation is unjustified and patients should not be denied rehabilitation just because they may be abnormal

Econometric Forecasting

Several principles are useful for econometric forecasters: keep the model simple, use all the data you can get, and use theory (not the data) as a guide to selecting causal variables. But theory gives little guidance on dynamics, that is, on which lagged values of the selected variables to use. Early econometric models failed in comparison with extrapolative methods because they paid too little attention to dynamic structure. In a fairly simple way, the vector autoregression (VAR) approach that first appeared in the 1980s resolved the problem by shifting emphasis towards dynamics and away from collecting many causal variables. The VAR approach also resolves the question of how to make long-term forecasts where the causal variables themselves must be forecast. When the analyst does not need to forecast causal variables or can use other sources, he or she can use a single equation with the same dynamic structure. Ordinary least squares is a perfectly adequate estimation method. Evidence supports estimating the initial equation in levels, whether the variables are stationary or not. We recommend a general-to-specific model-building strategy: start with a large number of lags in the initial estimation, although simplifying by reducing the number of lags pays off. Evidence on the value of further simplification is mixed. If cointegration among variables, then error-correction models (ECMs) will do worse than equations in levels. But ECMs are only sometimes an improvement eve