Polypharmacy in the management of patients with schizophrenia on risperidone in a tertiary-care hospital in Malaysia

The present study was conducted primarily to determine the occurrence of polypharmacy in patients with schizophrenia on risperidone. The secondary aim was to ascertain the incidence of inappropriate prescribing with anticholinergics. A retrospective review of the medical records of all patients who were being followed up at the out-patient clinic of a tertiary-care hospital in Malaysia was conducted. Only patients who were being prescribed risperidone between 1 June 2008 and 31 December 2008 were included in the study. Demographic data such as patient’s age, gender and race were obtained from the patient’s medical records. In total, 113 patients met the selection criteria. Polypharmacy was found to occur in 34 patients (30.09%), with the majority (76.47%) being on two antipsychotics. In total, 27 patients (34.18%) on monotherapy with risperidone were prescribed an anticholinergic on scheduled dosing, while 19 patients (24.05%) were prescribed it on an as-needed basis. Of the patients on polypharmacy, 26 (76.47%) were on scheduled dosing of anticholinergics, while three (8.82%) were taking the medication on an as-needed basis. Polypharmacy should be avoided, and the use of anticholinergics should be closely reviewed. By adopting more efficient prescribing practices, costs can be reduced and financial resources can instead be channelled towards more beneficial areas for the patients.     

Positional changes of the frontoparietal ossification centers in perinatal craniosynostotic rabbits.

It has been suggested that craniosynostosis is caused by abnormally located ossification centers (i.e., bony tubers) in the developing skull prior to suture formation [Mathijssen et al., 1996, 1997]. The present study was designed to test this hypothesis in a rabbit model of human familial, nonsyndromic coronal suture (CS) synostosis. Calvariae were taken from 99 New Zealand White rabbit perinates (55 normal controls, 15 with delayed-onset CS synostosis, and 29 with bilateral or unilateral CS synostosis), ranging in age from 23 to 34 days postconception (synostosis occurs at approximately 23 days in this model). Frontoparietal, interfrontal, and interparietal ossification center distances were obtained using a Wild microscope with camera lucida attachment and a 2-D computer digitization technique. Linear regression analysis was used to compare age-related changes in the perinatal ossification centers among groups. Results revealed that frontoparietal ossification center regression line slopes had similar start points (24-day intercepts) with significantly (P < 0.05) diverging slopes over time. Normal and delayed-onset ossification center distance increased more rapidly than in synostosed perinates. No significant (P > 0.05) differences were noted in regression line slopes among groups for interparietal or interfrontal ossification center distances. Results demonstrated that, in synostosed perinates, frontoparietal ossification center location was similar to normals around the time of synostosis and became displaced later. These findings suggest that ossification center (i.e., bony tuber) displacement seen in infants with craniosynostosis is probably a secondary and compensatory, postsynostotic change and not a primary causal factor of synostosis in this rabbit model.     

Global leaf-trait mapping based on optimality theory

Aim

Leaf traits are central to plant function, and key variables in ecosystem models. However recently published global trait maps, made by applying statistical or machine-learning techniques to large compilations of trait and environmental data, differ substantially from one another. This paper aims to demonstrate the potential of an alternative approach, based on eco-evolutionary optimality theory, to yield predictions of spatio-temporal patterns in leaf traits that can be independently evaluated.

Innovation

Global patterns of community-mean specific leaf area (SLA) and photosynthetic capacity (V_cmax) are predicted from climate via existing optimality models. Then leaf nitrogen per unit area (N_area) and mass (N_mass) are inferred using their (previously derived) empirical relationships to SLA and V_cmax. Trait data are thus reserved for testing model predictions across sites. Temporal trends can also be predicted, as consequences of environmental change, and compared to those inferred from leaf-level measurements and/or remote-sensing methods, which are an increasingly important source of information on spatio-temporal variation in plant traits.

Main conclusions

Model predictions evaluated against site-mean trait data from > 2,000 sites in the Plant Trait database yielded R² = 73% for SLA, 38% for N_mass and 28% for N_area. Declining species-level N_mass, and increasing community-level SLA, have both been recently reported and were both correctly predicted. Leaf-trait mapping via optimality theory holds promise for macroecological applications, including an improved understanding of community leaf-trait responses to environmental change.