European Psychiatry - Volume 33 - March 2016

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24th European Congress of Psychiatry / European Psychiatry 33S (2016) S72–S115 S75
billions of dollars every year. Focused efforts are needed to establish
preventive measures for B-I related hospitalization.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
FC08
The impact of climate on risk of mania
C.R. Medici ∗ . Vestergaard
D. Hadzi-Pavlovic unk-Jørgensen Parker
1 Aarhus University Hospital, Psychiatric Research Academy,
Department of Affective Disorders, Aarhus, Denmark
2 Aarhus University Hospital, Department of Clinical Epidemiology,
Aarhus, Denmark
3 Aarhus University, Research Unit for General Practice and Section
for General Practice, Department of Public Health, Aarhus, Denmark
4 University of New South Wales, School of Psychiatry, Sydney,
Australia
5 Black Dog Institute, Research Unit, Sydney, Australia
6 Aarhus University Hospital, Risskov, Aarhus, Denmark
∗ Corresponding author.
Introduction Bipolar disorder varies with season: admissions for
depression peak in winter and mania peak in summer. Sunlight
presumably increases the risk of mania through suppression of
melatonin. If so, we expect admissions for mania to vary in accor-
dance with climate variations.
Objectives To investigate how climate and climate changes
affects admissions for mania.
Aims To identify which climate variables – sunshine, ultraviolet
radiation, rain and snow cover – affect admissions for mania.
To examinewhether year-to-yearweather variation aswell as long-
termclimate changes reflects the variation innumber of admissions
for mania.
Methods This register-based nationwide cohort study covers all
patients admitted for mania (ICD-10 code F31 or F30.0–F30.2)
between 1995 and 2012 in Denmark. Climate data, obtained from
the Danish Meteorological Institute, were merged with admission
data and correlated using anUnobserved ComponentModel regres-
sion model.
Preliminary results In total, 8893 patients were admitted 24,313
times between 1995 and 2012: 6573 first-admissions and 17,740
readmissions. Linear regression shows significant association
between admissions per day and hours of sunshine (P < 0.01) and
ultraviolet radiation (UV) dose (P < 0.01). Average days with snow
cover and rain were not significantly correlated with admissions.
Analyses on year-to-year variation and long-term change are not
yet available.
Preliminary conclusions Admissions formania are correlatedwith
sunshine and UV, but not rain and snow cover. If more patients are
admitted during very sunny summers compared with less sunny
summers this implies a relationwith light itself and not just season.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
FC09
Delays to diagnosis and treatment in
patients presenting to mental health
services with bipolar disorder
R. Patel ∗, H. Shetty , R. Jackson , M. Broadbent , R. Stewart ,
J. Boydell , P. McGuire , M. Taylor
1 Institute of Psychiatry, Psychology and Neuroscience, Department of
Psychosis Studies, London, United Kingdom
2 South London and Maudsley NHS Foundation Trust, Biomedical
Research Centre Nucleus, London, United Kingdom
3 Institute of Psychiatry, Psychology and Neuroscience, Department of
Psychological Medicine, London, United Kingdom
∗ Corresponding author.
Introduction There are often substantial delays before diagnosis
and initiation of treatment in people bipolar disorder. Increased
delays are a source of considerable morbidity among affected indi-
viduals.
Aims To investigate the factors associated with delays to diagno-
sis and treatment in people with bipolar disorder.
Methods Retrospective cohort study using electronic health
record data from the South London and Maudsley NHS Foundation
Trust (SLaM) from 1364 adults diagnosed with bipolar disorder.
The following predictor variables were analysed in a multivariable
Cox regression analysis on diagnostic delay and treatment delay
from first presentation to SLaM: age, gender, ethnicity, compul-
sory admission to hospital under the UK Mental Health Act, marital
status and other diagnoses prior to bipolar disorder.
Results The median diagnostic delay was 62 days (interquar-
tile range: 17–243) and median treatment delay was 31 days
(4–122). Compulsory hospital admission was associated with a sig-
nificant reduction in both diagnostic delay (hazard ratio 2.58, 95% CI
2.18–3.06) and treatment delay (4.40, 3.63–5.62). Prior diagnoses
of other psychiatric disorders were associated with increased diag-
nostic delay, particularly alcohol (0.48, 0.33–0.41) and substance
misuse disorders (0.44, 0.31–0.61). Prior diagnosis of schizophrenia
and psychotic depression were associated with reduced treatment
delay.
Conclusions Some individuals experience a significant delay in
diagnosis and treatment of bipolar disorder, particularly those
with alcohol/substance misuse disorders. These findings highlight
a need to better identify the symptoms of bipolar disorder and offer
appropriate treatment sooner in order to facilitate improved clini-
cal outcomes. This may include the development of specialist early
intervention services.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
FC10
Trends of hospitalization for major
bipolar II in USA: A Nationwide
analysis
M. Rathod ∗, Z. Mansuri , S. Shambhu , A. Sutaria , K. Karnik
1 Drexel University, School of Public Health, Philadelphia, USA
2 Children Hospital at San Antonio - Texas, Department of Pediatrics,
San Antonio, Texas, USA
∗ Corresponding author.
Objectives Bipolar II (B-II) is an important cause of morbidity and
mortality in hospitalized patients. While B-II has been extensively
studied in the past, the contemporary data for impact of B-II on cost
of hospitalization are largely lacking.
Methods We queried the Healthcare Cost and Utilization
Project’s Nationwide Inpatient Sample (HCUP-NIS) dataset
between 1998–2011 using the ICD-9 codes. Severity of comorbid
conditions was defined by Deyo modification of Charlson comor-
bidity index. Primary outcome was in-hospital mortality and
secondary outcome was total charges for hospitalization. Using
SAS 9.2, Chi2 test, t-test and Cochran-Armitage test were used to
test significance.
Results A total of 107,152 patients were analyzed; 62.61% were
female and 31.39% were male ( P< 0.0001); 78.19% were white,
11.44% black and 10.37% of other race (P < 0.0001). Rate of hospi-
talization increased from 866.87/million to 8156.03/million from
1998–2011. Overall mortality was 0.32% and mean cost of hos-
pitalization was 19,447.89$. The in-hospital mortality increased
from 0.00% to 0.07% (P < 0.0001) and mean cost of hospitalization
increased from 7565.20$ to 26,511.95$. Total yearly spending on