Transcript Slide 1

Blood Glucose Control in a Schizophrenic
Population in an Outpatient Setting
DANIEL MOLLOY, MD
MENTOR: JAMES STEPHEN, MD
Schizophrenia
 Complex psychiatric disorder with many medical and
psychosocial complications.
 Characterized by a heterogeneous mixture of clinical
features  psychosis (1).
 Incidence: 10 to 40 / 100,000 population
 High risk for poverty, unemployment, homelessness or
inadequate housing, ill health, and poor access to health
care(1).
Meltzer H.Y., Bobo W.V., Heckers S.H., Fatemi H.S. (2008). Chapter 16. Schizophrenia. In M.H. Ebert, P.T. Loosen,
B. Nurcombe, J.F. Leckman (Eds), CURRENT Diagnosis & Treatment: Psychiatry, 2e.
Background
 Per DSM – IV TR (2), to diagnose schizophrenia, a
patient must have at least 2 of the following:
 Delusions
 Hallucinations
 Disorganized speech and/or
 Disorganized behavior,
 Negative symptoms (alogia, avolition, and flat affect).
 These must be at least 6 months in duration and produce
disturbances in work, self-care, and interpersonal
relations.
American Psychiatric Association. DSM-IV. Diagnostic and statistical manual of mental disorders. 4th ed. Washington:
American Psychiatric Association, 1994: 273-315
Background
Associated medical issues(3):
 20% decreased life expectancy
 Increased rates of cardiovascular and metabolic
abnormalities.
 Overall poorer health – related quality of life .
McGrath J, Saha S, Welham J, El Saadi O, Macauley C, Chant D. “ A systematic review of the incidence of
schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology.” BMC Med .
2:13 (2004).
Background
 Prevalence of type 2 diabetes in schizophrenic
populations can be 2–4 times higher than in the
general population, 15–18%(4).
 The exact reason in unclear, but likely to include
 Poor diet
 Sedentary lifestyle
 Substance abuse
 Family association - monozygotic twins/1st degree
relatives
‘Schizophrenia and Diabetes 2003’ Expert Consensus Meeting, Dublin, 3–4 October 2003: consensus summary, The
British Journal of Psychiatry (2004) 184: s112-s114.
Hemoglobin A1c
 Formed by the irreversible, nonenzymatic binding of
glucose to the terminal end of the beta chain of
hemoglobin
 Serves as a predictable measure of average blood
glucose over period of 90 – 120 days.
• ADA Clinical Practice Recommendations now
recommend using HbA1c to diagnose diabetes using
a NGSP-certified method and a cutoff of HbA1c
≥6.5%(5).
Diabetes Care January 2012 vol. 35 no. Supplement 1 S11-S63
Hemoglobin A1c
 Certain limitations to hemoglobin A1c are known:
 Dependent on lifespan of RBC
 Influenced by hemoglobin variety
 Laboratory –dependent  standardization
Antipsychotic medications
 Antipsychotic medications commonly used in the
treatment of schizophrenia have a well –
documented tendency to cause hyperglycemia
and/or insulin resistance (6).
 Particularly pronounced in patients receiving certain
members of the class of second – generation
antipsychotics(6).
 Cause is not entirely elucidated
Gautam, S., and PS Meena. "Drug-emergent Metabolic Syndrome in Patients with Schizophrenia Receiving Atypical
(second-generation) Antipsychotics." Indian Journal of Psychiatry 53.2 (2011): 128-33
Rationale
•
Quality outcome measurements are becoming an
increasingly important aspect of day – to –day
practice.
Rationale
 Bias towards mentally ill patients influences
healthcare provider decision making (4).
 One study with standardized patient showed HCP
less likely to prescribe appropriate
therapies/medications to schizophrenic
patients(4).
 Also includes mental health professionals (4).
Mittal, Dinesh, MD. "Does Serious Mental Illness Influence Treatment Decisions of Physicians and Nurses?"
Lecture. American Psychiatric Assocation 2012 Annual Meeting. San Francisco. 20 May 2013. APA 166th Meeting.
American Psychiatric Association, May 2013
Aims
 Primary Objective: To determine whether a
difference in average blood glucose control exists
between a schizophrenic and a non - schizophrenic
population in an outpatient setting.
Aims
 Secondary Objectives:
 To determine whether an association exists between
A1c levels and the number of healthcare contact
events during study period.
 To assess the prevalence of vascular disease between
schizophrenic and non – schizophrenic patients.
Methods
 Retrospective case – control study
 IRB approval obtained prior to study
commencement
 Data collected over a one year period from April
2012 to April 2013
 Chart – based; information obtained from EMR
Methods
 Inclusion criteria:
 Diagnosis of Schizophrenia
 Treated in outpatient setting
 At least one hemoglobin A1c obtained within the
study period
Methods
 Exclusion criteria:
 End stage renal disease
 Hemolytic anemia/ hemoglobinopathy
 No hemoglobin A1c within study period
Methods
245 Schizophrenic patients identified.
72 diagnoses of Diabetes mellitus.
7 excluded due to exclusion criteria
Total of 65 patients included
Methods
 A control cohort of 65 randomly sampled diabetic
patients was recruited based on several matching
variables:
 Age
 Race
 Gender.
Variables
 Age
 Medications for
 Gender
schizophrenia
 Use of Insulin therapy
 Anemia
 Kidney disease
 Vascular complications
 Race
 BMI
 LDL level
 Triglyceride level
 HDL level
 Smoking status
 Number of clinic visits
during study period
Statistical Analysis
 ANCOVA, t-tests, chi-square (χ2) tests as appropriate.
 SPSS software (SPSS Inc, Chicago, Illinois) was used for
data analysis.
 P<0.05 was considered significant
Variable
Schizophrenic
Nonschizophrenic
p-value
Age
56.46
56.02
0.81
Gender
M 28
F 37
M 30
F 35
0.72
Race
Caucasian
AA
Hisp
A1c
6.645
8.409
0.001
Number of
Clinic visits
4.6
4.83
0.71
Smoking
Y 29
N 36
Y 20
N 45
0.10
Kidney Disease Y 10
N 55
Y 10
N 55
N/A
36
22
6
Caucasian
AA
Hisp
38
22
5
0.76
Variable
Schizophrenic
Nonschizophrenic
p-value
Mean Age
56.46
56.02
0.81
Gender
M 28
F 37
M 30
F 35
0.72
Race
Caucasian
AA
Hisp
A1c
6.645
8.409
0.001
Number of
Clinic visits
4.6
4.83
0.71
Smoker
Y 29
N 36
Y 20
N 45
0.10
Kidney Disease Y 10
N 55
Y 10
N 55
N/A
36
22
6
Caucasian
AA
Hisp
38
22
5
0.76
Variable
Schizophrenic
Nonschizophrenic
P-value
LDL
103.5
102.9
0.93
HDL
44.3
44.9
0.84
Triglycerides
158.4
190.5
0.21
Anemia
Yes
No
BMI
34.0
35.0
Diabetes
treatment
Insulin 16
Oral
43
Diet
6
Insulin
Oral
Diet
15
50
Yes
No
10
55
0.266
0.736
36
25
4
0.002
0.008 (without
insulin)
Schizophrenia and diabetes – associated
vascular complications
Schizophrenia
Vascular
complications
Yes
No
Yes
6
22
No
59
43
P-value
0.001
Vascular complications defined as coronary artery disease,
peripheral vascular disease, and cerebrovascular disease
Hemoglobin A1c in
Schizophrenic patients treated with typical vs
Atypical Antipsychotics
Typical
Atypical
Other
Number of
Schizophrenics
14
45
6
A1c
6.45
6.94
7.40
p-value
0.323
No.
Variable
P – value
1
Age
0.006
2
Gender
0.820
3
Race
0.030
4
Smoking status
0.306
5
Anemia
0.516
6
Number of clinic visits
0.457
7
BMI
0.272
8
Schizophrenia
0.001
Limitations of Study
 Retrospective
 Chart based
 Multiple providers participating in patient care
Conclusions
1.
There was a significant difference in the
hemoglobin A1c between patients with
schizophrenia {mean A1c 6.6, SD =1.3} and
without schizophrenia {mean A1c 8.4, SD =2.6}
after controlling the effect of age, race, gender,
BMI, anemia and number of clinic visits (p
<0.001).
Conclusions
2. There was a significant difference in the
prevalence of vascular diseases between patients
with schizophrenia {9.2%} and without
schizophrenia {33.8%} after controlling the effect of
age, race, gender, BMI, anemia and number of clinic
visits (p <0.001).
Conclusions
3. There was no significant difference in the
hemoglobin A1c between schizophrenic patients
taking atypical antipsychotics {mean A1c 6.9, SD
=1.1} and patients taking typical antipsychotics{
mean A1c =6.4, SD = 1.6} (p<0.323).
Conclusion/Discussion
 A diagnosis of schizophrenia does not mean that a
patient is incapable of managing their medical
conditions.
 Caretakers must be careful to avoid letting bias
influence their decision – making.
 Further prospective study may uncover reasons for
this difference.
Acknowledgements
 Srikrishna Varun Malayala, MBBS
 Khalid J Qazi, MD, MACP
 Henri Woodman, MD
 Nikhil Satchidanand, PhD
Thank You