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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.

http://dx.doi.org/10.1016/j.eurpsy.2016.01.011

FC08

The impact of climate on risk of mania

C.R. Medici

1 , 2 ,

, C .H

. Vestergaard

3 ,

D. Hadzi-Pavlovic

4 , 5 , P . M

unk-Jørgensen

6 , G.

Parker

4 , 5

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.

http://dx.doi.org/10.1016/j.eurpsy.2016.01.012

FC09

Delays to diagnosis and treatment in

patients presenting to mental health

services with bipolar disorder

R. Patel

1 ,

, H. Shetty

2

, R. Jackson

3

, M. Broadbent

2

, R. Stewart

3

,

J. Boydell

1

, P. McGuire

1

, M. Taylor

1

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.

http://dx.doi.org/10.1016/j.eurpsy.2016.01.013

FC10

Trends of hospitalization for major

bipolar II in USA: A Nationwide

analysis

M. Rathod

1 ,

, Z. Mansuri

1

, S. Shambhu

1

, A. Sutaria

1

, K. Karnik

2

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, Chi

2

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