Normal levels of prepulse inhibition in the euthymic phase of bipolar disorder.

BACKGROUND:Deficits in prepulse inhibition (PPI) of the acoustic startle response have been suggested as a potentially useful endophenotype for schizophrenia spectrum disorders and may explain certain symptoms and cognitive deficits observed in the psychoses. PPI deficits have also been found in mania, but it remains to be confirmed whether this dysfunction is present in the euthymic phase of bipolar disorder.METHOD: Twenty-three adult patients with DSM-IV bipolar disorder were compared to 20 controls on tests of acoustic startle reactivity and PPI of the startle response. Sociodemographic and treatment variables were recorded and symptom scores assessed using the Hamilton Depression Inventory and the Young Mania Rating Scale.RESULTS:Overall, the patient and control groups demonstrated similar levels of startle reactivity and PPI, although there was a trend for the inter-stimulus interval to differentially affect levels of PPI in the two groups.CONCLUSIONS: In contrast to bipolar patients experiencing a manic episode, general levels of PPI were normal in this euthymic sample. Further studies are required to confirm this finding and to determine the mechanisms by which this potential disruption/normalization occurs. It is suggested that an examination of PPI in a high-risk group is required to fully discount dysfunctional PPI as a potentially useful endophenotype for bipolar disorder.

Addressing Bed Costs for the Elderly: A New Methodology for Modelling Patient Outcomes and Length of Stay

The proportion of elderly in the population has dramatically increased and will continue to do so for at least the next 50 years. Medical resources throughout the world are feeling the added strain of the increasing proportion of elderly in the population. The effective care of elderly patients in hospitals may be enhanced by accurately modelling the length of stay of the patients in hospital and the associated costs involved. This paper examines previously developed models for patient length of stay in hospital and describes the recently developed conditional phase-type distribution (C-Ph) to model patient duration of stay in relation to explanatory patient variables. The Clinics data set was used to demonstrate the C-Ph methodology. The resulting model highlighted a strong relationship between Barthel grade, patient outcome and length of stay showing various groups of patient behaviour. The patients who stay in hospital for a very long time are usually those that consume the largest amount of hospital resources. These have been identified as the patients whose resulting outcome is transfer. Overall, the majority of transfer patients spend a considerably longer period of time in hospital compared to patients who die or are discharged home. The C-Ph model has the potential for considering costs where different costs are attached to the various phases or subgroups of patients and the anticipated cost of care estimated in advance. It is hoped that such a method will lead to the successful identification of the most cost effective case-mix management of the hospital ward.