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Objectives: back to menu
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Describe
the interactions between the various neurotransmitters
and hormones that influence the homeostatic regulation
of energy intake and expenditure.
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Recognize
the psychotherapeutic and non-psychiatric pharmacotherapy
agents likely to predispose patients to a metabolic
syndrome characterized by dysfunctional glucose
and/or lipid regulation.
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Compare
and contrast the differing bodies of evidence concerning
the role of mental illness, antipsychotic medication,
and the other adverse effects of atypical antipsychotics
in glucose dysregulation.
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Describe
the effects of atypical antipsychotics in causing
changes in serum lipids and related factors and
their implications for monitoring.
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Describe
the role of insulin resistance and ß-cell
dysfunction in the metabolic syndrome, prediabetes,
and type 2 diabetes.
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Evaluate
the potential risk of hyperglycemic decompensation
due to atypical antipsychotics in patients with
the metabolic syndrome, prediabetes, and type 2
diabetes.
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Apply
metabolic syndrome and antipsychotic medication
information to create a comprehensive treatment
plan for a schizophrenic patient at risk for, or
comorbid with, diabetes.
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Differentiate
between methods of treatment for psychosis to enhance
outcomes while minimizing the risk of glucose dysregulation.
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| Michael
C. Angelini, PharmD |
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Dr.
Michael Angelini is an Assistant Professor of Clinical
Pharmacy at the Massachusetts College of Pharmacy and
Health Sciences in Boston, and a Clinical Pharmacist,
Psychopharmacology Specialist at the Veterans Affairs
Boston Healthcare System Outpatient Clinic.
After earning his doctorate in pharmacy from Massachusetts
College of Pharmacy and Allied Health Sciences, Dr.
Angelini completed an ASHP Accredited General Practice
Residency at the University of Massachusetts Medical
Center in Worcester.
Dr. Angelini is a member of the American Society of
Health-System Pharmacists, the American Association
of Colleges of Pharmacy, the Colleges of Psychiatric
and Neurologic Pharmacists, and the Massachusetts Society
of Health-System Pharmacists. The recipient of a number
of honors and awards, he has conducted research that
has resulted in the publication of his work, as well
as presentations at national meetings and extensive
lectures on topics ranging from, but not limited to,
migraine, anxiety disorders, bipolar disorder, and schizophrenia.
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| Robert
L. Dufresne, PhD |
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Dr.
Rob Dufresne is Professor of Pharmacy at the University
of Rhode Island College of Pharmacy in Kingston and a
Psychiatric Pharmacotherapy Specialist at the Providence
VA Medical Center. His educational background includes
his initial Pharmacy degree as well as earned doctorates
in both Pharmacology and Psychology. He is board certified
in both Pharmacotherapy and Psychiatric Pharmacy. He teaches
psychiatric and neurologic pharmacotherapy to students
of pharmacy, nursing, medicine, and various allied health
fields. Along with membership in the American College
of Clinical Pharmacy, he also is an active member of the
College of Psychiatric and Neurologic Pharmacists (CPNP).
He has recently served on the CPNP board of directors,
and is currently Editor of their journal. In addition
to these activities, he provides clinical service at the
Providence VAMC to psychiatric outpatients and often provides
consults for inpatients as well. His extensive research
has resulted in the publication of articles, book chapters,
reviews, and abstracts that have appeared in journals
such as Biological Psychiatry, the Annals of
Pharmacotherapy, the Journal of Clinical Psychiatry,
and the American Journal of Psychiatry, among others.
A prolific speaker, Dr. Dufresne has also given numerous
presentations at several national meetings. |
| Timothy
J. Maher, PhD |
 |
Dr.
Timothy Maher is the Sawyer Professor of Pharmaceutical
Sciences and a Professor of Pharmacology at the Massachusetts
College of Pharmacy and Health Sciences in Boston, Massachusetts.
After receiving his Bachelor’s degree from Boston State
College, Dr. Maher continued his studies, earning his
PhD in Pharmacology from the Massachusetts College of
Pharmacy and Health Sciences.
Dr. Maher is a member of a number of professional societies,
including the American Association of Colleges of Pharmacy,
the American Association of Pharmaceutical Scientists,
and the International Society for Neurochemistry, among
many others. He has conducted extensive research, and
possesses several patents. His countless abstracts, papers,
and articles have appeared in such publications as Lancet,
the American Journal of Cardiology, Brain Research,
the Annals of the New York Academy of Science,
and Pharmacology Research, to name only a few.
A prolific speaker, Dr. Maher has given presentations
both nationally and internationally. |
| Elliot
Sternthal, MD |
 |
Dr.
Elliot Sternthal is an Assistant Professor of Medicine
at the Boston University School of Medicine, as well as
Clinical Director of the Diabetes Services at Boston University
Medical Center, where he is an active staff member in
Endocrinology, Diabetes, and Nutrition.
After earning his medical degree from McGill University
in Montreal, Quebec, Canada, Dr. Sternthal served his
rotating internship at Jewish General Hospital in Montreal,
where he remained for the first two years of his residency.
He completed his residency at the University of Massachusetts
Medical Center, where he went on for his Fellowship in
Endocrinology and Metabolism. He is board certified in
Internal Medicine, and Endocrinology and Metabolism, and
is a certified Licentiate of the Medical Council of Canada.
He is also licensed to practice in both Massachusetts
and Connecticut.
Dr. Sternthal is a Fellow of the American College of Physicians
and the American College of Endocrinology, and a member
of several other professional societies, including, but
not limited to, the American Diabetes Association, the
Endocrine Society, and the American Association of Clinical
Endocrinologists. Based on his studies, he has authored
or co-authored a number of book chapters, and his articles
have appeared in journals such as the New England Journal
of Medicine, Psychosomatic Medicine, and Catheterization
and Cardiovascular Diagnosis, among others. |
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This introductory section of the monograph will provide
background information for the series of 4 articles addressing
the metabolic effects of second-generation antipsychotics
(SGAs), also known as atypical antipsychotics, and their
clinical management. One controversial effect of these medications
is weight gain. The physiologic and pathologic processes
that are involved with body weight regulation will be reviewed.
In the second section, an examination of the spectrum of
insulin resistance found during progression from metabolic
syndrome through prediabetes to type 2 diabetes will provide
a fuller understanding of the metabolic effects of SGAs.
Next, the possible effects of these drugs on weight gain,
glucose regulation, and dyslipidemia will be reviewed by
focusing on key articles in the current literature. Clinical
approaches for patients with schizophrenia and metabolic
syndrome, including treatment options and risk-versus-benefit
analysis, will conclude this continuing pharmaceutical education
program. |
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Physiologic and pathologic processes are involved with body
weight regulation; a number of these metabolic changes are
produced by SGAs. Underlying these metabolic changes are
the neural chemical processes that can occur following the
ingestion of such compounds and endogenous compounds that
regulate body weight, energy intake, and energy expenditure.
Second-generation antipsychotic drugs (Table 1) have
significantly improved patient care, particularly the 1%
of the US population suffering from schizophrenia. The cost
of care for schizophrenic patients is very high because
this patient population occupies 40.3% of mental health
facility beds, 11.4% of nursing home beds, and 8.8% of all
hospital beds.1
The mechanisms of action of the SGAs are not fully understood.
Many SGAs currently available have affinity for multiple
neurotransmitter receptors, and their action may be mediated
through a combination of dopamine and serotonin receptor
antagonism. Most of these agents exhibit antagonism at adrenergic,
cholinergic, and histaminergic receptors, while aripiprazole
and ziprasidone may also act as agonists at specific subtypes
of serotonin receptors (eg, 5HT1A and 5HT2C).
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Commonly used first-generation antipsychotics |
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Second-generation (atypical) antipsychotics |
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Chlorpromazine |
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Fluphenazine |
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Haloperidol |
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Perphenazine |
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Thiothixene |
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Trifluoperazine |
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Aripiprazole |
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Clozapine |
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Olanzapine |
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Quetiapine |
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Risperidone |
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Ziprasidone |
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*Adapted from the American Diabetes Association.6
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Body weight is a balancing act determined by the amount
of energy coming in and the amount of energy going
out. Energy intake is food consumed, and energy expenditure
is energy used in metabolizing food and maintaining
cell structure and electrical gradients (basal metabolic
rate). Energy expenditure is also that energy used
in exercise or physical activity. Body mass index
(BMI) is a tool used to evaluate obesity. Overweight
is considered to be a BMI ≥25 kg/m2,
and obese is considered by the World Health Organization
to be a BMI ≥30 kg/m2, although other
factors are also important, especially the percentage
and distribution of body fat present. Although adverse
health consequences may be associated with increases
in BMI, more accurate assessments of risk exist (eg,
intra-abdominal fat determined by a computed tomography
scan).
Based on Centers for Disease Control data from 1985
through 2001, obesity among US adults has increased
steadily (Figure 1).2,3 In 1985,
8 states had 10% to 14% of their populations being
obese. By 1989, approximately half of the states had
higher incidence rates in this range. In 1991, obesity
rates of 15% to 19% were reported in 4 states. By
2001, one state (Mississippi) had an incidence of
obesity ≥25%, and 27 states reported an incidence
rate of 20% to 24% in the adult population. The most
common adverse health consequence associated with
obesity and increased BMI is type 2 diabetes, with
61% of prevalence attributed to obesity.4
Uterine cancer (34%), gallbladder disease (30%), hypertension
(17%), and coronary artery disease (17%) are also
attributed to high BMI values (≥27 kg/m2).
Does this increase in the prevalence of obesity reflect
a genetic predisposition among humans? Genetically,
humans were designed to conserve energy. In ages past,
food was difficult to obtain, and survival was largely
dependent upon an individual’s ability to retain calories
and energy. Over the past 150 years, food availability
has not been much of a problem in developed countries.
The current day issue now has turned to surviving
obesity and diabetes, and not the availability of
food. |
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Many factors, both short-term and long-term, influence energy
input (consumption of food), as well as energy expenditure
(metabolism, thermogenesis; Table 2). The roles of
various monoamines in controlling appetite and food intake
have been recognized for more than 50 years. The effects
of activation of histamine-1 and alpha-1 adrenoceptors on
appetite have been widely investigated, and of particular
interest most recently, it has been found that activation
of serotonin-2c receptors decreases food intake. Some SGAs
antagonize this receptor, which may account for the observed
increase in food intake and resultant weight gain associated
with their use. Neuroactive compounds that have been identified
more recently, such as neuropeptide Y (NPY), may play a
significant role in controlling food intake. The release
of NPY is stimulated by ghrelin, a 28-amino acid peptide
with a unique structure having an n-octanoyl modification
at its third serine residue; ghrelin is apparently produced
by stomach endocrine cells and taken into the circulation
without first going into the stomach. Stomach bypass surgery
usually results in a significant reduction in ghrelin concentration.
Ghrelin also is found in the hypothalamus of the brain,
where it is associated with the release of growth hormone
and other peptides. When exogenous ghrelin is administered,
appetite is stimulated. Extremely high levels of ghrelin
are found in patients who have anorexia nervosa or bulimia.
Orexin is a neuroactive compound found in the hypothalamus
and having a structure similar to secretin in the gastrointestinal
tract. Food intake is increased after the administration
of orexin, a name derived from the Greek word for appetite.
Based on animal studies, some forms of human narcolepsy
may be characterized by low levels of orexin.
Endocannabinoids, derivatives of compounds that are similar
to the active ingredient in marijuana (delta-9 tetrahydrocannabinol),
increase appetite. Persons who use marijuana, or are passively
exposed to its smoke, usually report having increased appetite.
Neuroactive compounds that typically decrease food intake
include bombesin, calcitonin, cholecystokinin, enterostatin,
glucagon, histamine, neurotensin, and serotonin. A compound
of particular interest is leptin, which is produced in adipocytes,
fat cells in the periphery. Leptin acts within the central
nervous system to control energy intake and output. With
weight loss there is shrinkage of the adipocytes, a decrease
in leptin, a corresponding decrease in the concentration
of NPY, and a consequent increase in food intake and decrease
in energy expenditure. With weight gain, just the opposite
occurs: enlargement of the adipocytes, an increase in leptin,
a decrease in food intake, and an increase in energy expenditure.
Much excitement has been generated in anticipation of leptin’s
usefulness in humans, but it has not been very effective
except in limited situations. Other potential anti-obesity
drugs have been identified and are being pursued by numerous
investigators.
Patients who are receiving SGAs for the treatment of schizophrenia
may also be taking other medications that can contribute
to weight gain (eg, tricyclic antidepressants, lithium,
or anxiolytics; Table 3). On the other hand, fewer
medications are associated with weight loss, including psychostimulants,
some serotonin selective reuptake inhibitors, isocarboxazid,
and topiramate. Other factors that predispose schizophrenic
patients to weight gain may include poverty, poor nutritional
quality of foods, and lack of exercise. Overall, SGAs provide
obvious psychiatric benefits to patients, but there are
risks as with any drug. Selection of SGAs for the treatment
of schizophrenia should always take into consideration the
benefit-to-risk ratio. |
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A large increase in the incidence of diabetes in the
US population has occurred over the past 2 decades.
The number of states with a diabetes incidence of
≥6% has grown from 2 in 1994 to 28 in 2002 (Figure
2). Prevalence of diagnosed diabetes increased
by 70% in the 30–39 years age group, and by 40% in
the 40–49 years age group from 1990 to 1998.5
These continuing pharmacy education materials will
continue with examination of the spectrum of insulin
resistance to better understand the metabolic effects
of SGAs and also a review of the possible effects
of these drugs on glucose regulation and dyslipidemia.
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Short term |
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Long term |
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Sight of food |
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Smell |
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Taste |
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Gut hormones |
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Circulating nutrients |
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Stretch & chemoreceptors in gut |
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Circulating nutrients |
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Adipokines (leptin, timer necrosis factor-alpha)
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Hormones (cortisol, growth hormones, insulin,
T-4) |
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Short term |
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Long term |
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Meal size & duration |
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Digestion/absorption |
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Metabolism/storage |
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Thermogenesis |
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Hunger |
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Size of energy stores, hormonal signals |
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Thermogenesis |
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Tricyclic antidepressants |
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Beta-blockers |
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Sulfonylureas |
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Valproate |
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Carbamazepine |
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Vigabatrin |
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Gabapentin |
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Insulin |
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Monoamine oxidase inhibitors |
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Lithium |
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Lamotrigine |
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Selective serotonin reuptake inhibitors |
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Anxiolytics |
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Corticosteroids |
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Antipsychotics |
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Wyatt
RJ, Henter I, Leary MC, Taylor E. An economic evaluation
of schizophrenia—1991. Social Psychiatry Psychiatr
Epidemiol. 1995;30:196-205.
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Mokdad
AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan
JP. The spread of the obesity epidemic in the United
States, 1991-1998. JAMA. 1999;282:1519-1522.
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Mokdad
AH, Bowman BA, Ford ES, Vinicor F, Marks JS, Koplan
JP. The continuing epidemics of obesity and diabetes
in the United States. JAMA. 2001;286:1195-1200.
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Wolf
AM, Colditz GA. Current estimates of the economic
cost of obesity in the United States. Obes Res.
1998;6:97-106.
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Kenny
SJ, Aubert RE, Geiss LS, National Diabetes Data Group.
Prevalence and incidence of non–insulin-dependent
diabetes. In: Diabetes in America. 2nd ed.
National Institutes of Health; 1995:47-67.
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American
Diabetes Association. Consensus Development Conference
on Antipsychotic Drugs and Obesity and Diabetes. Diabetes
Care. 2004;27:596-601.
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The World Health Organization (WHO) and the National Cholesterol
Education Program (NCEP) have defined the metabolic syndrome
(Table 1).1,2 Diagnosis using the NCEP
definition is the presence of three or more characteristics:
elevated blood pressure, elevated plasma triglyceride level,
decreased high-density lipoprotein cholesterol, abdominal
obesity, and elevated fasting glucose level. Diagnosis using
the WHO definition requires type 2 diabetes or impaired
glucose tolerance (IGT) and any 2 of the other listed criteria,
or any 3 of the criteria with normal glucose tolerance (NGT).
The metabolic syndrome affects 25% of the US adult population.
Prevalence is >40% among persons over 60 years of age and
<20% among persons under the age of 40 years. Race/ethnicity
is another factor, and Hispanic/Latino Americans have a
higher age-adjusted prevalence than non-Hispanic whites
or African Americans.3
Persons affected by the metabolic syndrome are at risk for
developing diabetes and cardiovascular disease. The symptoms
of the metabolic syndrome are similar to those of prediabetes
and type 2 diabetes. Metabolic syndrome is prevalent (86%)
in people with type 2 diabetes,4 yet most persons
with metabolic syndrome are not diabetic. The metabolic
syndrome is not necessarily associated with elevated plasma
glucose levels; thus, the cardiovascular risk associated
with metabolic syndrome can occur even when blood glucose
level is normal. Other consequences of metabolic syndrome
include arterial stiffness and endothelial dysfunction.
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Characteristics |
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WHO |
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NCEP ATP III |
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Hypertension |
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Current antihypertensive therapy and/or BP >140/90
mmHg |
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BP medication or BP >130/85 mmHg |
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Dyslipidemia |
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Plasma triglycerides >1.7 mmol/L (150 mg/dL)
and/or HDL <0.9 mmol/L (35 mg/dL) in men and
<1.0 mmol/L (<40 mg/dL) in women |
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Plasma triglycerides >150 mg/dL, HDL cholesterol
<40 mg/dL in men and <50 mg/dL in women |
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Obesity |
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BMI >30 kg/m2 and/or waist/hip ratio
>0.90 in men, >0.85 in women |
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Waist circumference >102 cm (40 in) in men and
>88 cm (35 in) in women |
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Glucose |
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Type 2 diabetes or IGT |
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Fasting blood sugar >110 mg/dL |
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Other |
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Microalbuminuria = overnight urinary albumin
excretion rate >20 mg/min (30 mg/g creatinine)
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Requirements for diagnosis |
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Type 2 diabetes or IGT and any 2 of the above
criteria; if NGT, must demonstrate 3 other disorders
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Any 3 of the above disorders |
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BP = blood pressure; HDL = high-density lipoprotein;
BMI = body mass index; IGT = impaired glucose tolerance;
NGT = normal glucose tolerance. |
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Insulin resistance is defined as the condition in which
more insulin is required to produce an expected biological
response. During this condition, normoglycemia is maintained
at the cost of hyperinsulinemia. Measurement of fasting
levels of plasma glucose and insulin are the simplest and
most frequently used methods of diagnosing insulin resistance.
Insulin resistance can also be diagnosed by a hyperinsulinemic
clamp study (ie, maintenance of a constant normal blood
glucose level by intravenous glucose infusion during intravenous
hyperinsulinemia) and by an oral glucose tolerance test
with serial plasma samples measured for glucose and insulin
levels at fixed times after oral glucose loading. |
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Aging and genetics are only some of the factors that
may be involved in insulin resistance (Figure 1).
A genetic predisposition to developing insulin resistance
has been suggested; patients with diabetes may have
relatives who are nondiabetic, yet have an abnormal
response to insulin, such as impaired glycogen storage.
As people age, weight gain and obesity—the major cause
of insulin resistance—become more of a problem. With
weight gain comes an increase in free fatty acids
and the production by fat cells of cytokines and chemokines,
further potentiating insulin resistance and impairing
both insulin action and its secretion by ß-cells.
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Insulin resistance frequently is present in metabolic syndrome
and in conditions progressing to type 2 diabetes. In addition
to elevated blood pressure and lipid abnormalities, persons
with insulin resistance also have nontraditional cardiovascular
risk factors, including: a procoagulant state and reduced
fibrinolysis; elevated C-reactive protein, a marker of vascular
inflammation that seems to potentiate vascular damage; and
elevated uric acid levels. Low-density lipoprotein particles
tend to be smaller and denser in these individuals, reflecting
loss of cholesterol, which results from augmented reverse
cholesterol transport. These smaller particles more easily
penetrate the endothelium where they are oxidized and contribute
to formation of the fatty streak, the first stage of plaque
formation. An increased level of urine microalbumin is also
an important marker for cardiovascular disease and renal
dysfunction. Another abnormality associated with this condition
is elevated local cortisol production by visceral fat cells
resulting in proliferation of more visceral fat cells that
are insulin resistant and tend to release fatty acids, which
further potentiates insulin resistance. The cardiology literature
also suggests that cardiac autonomic dysfunction is also
a part of the insulin resistance syndrome. |
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In the initial stages of metabolic syndrome, pancreatic
ß-cells respond to insulin resistance by producing
enough insulin to maintain normal glucose levels. When the
ß-cells fatigue or are lost, a decrease in insulin
secretion results and the condition progresses to prediabetes,
which is initially recognized by glucose challenge. With
progressive ß-cell dysfunction or loss, the prediabetic
condition progresses to type 2 diabetes.
In the later stages of the metabolic syndrome, ß-cells
inadequately compensate for insulin resistance and may become
unresponsive (ie, desensitized to glucose). A genetic predisposition
may program ß-cells to fail in some persons. Intrauterine
influence and small birth weight appear to be associated
with impaired ß-cell development, and perhaps with
a greater loss of ß-cells over time. The lipids abnormalities
associated with increased weight not only interfere with
insulin action, but the lipids also can enter and harm the
ß-cells. Glucose, too, can enter the ß-cells,
causing oxidative stress and glycosylation of cellular proteins.
However, early treatment to decrease fatty acid and blood
glucose levels may reverse some of this damage and allow
partial recovery of the ß-cells. |
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In assessing insulin resistance, both insulin sensitivity
and insulin secretion must be considered, as shown by Kahn
and colleagues.5 Persons who are lean will, generally,
have high insulin sensitivity and relatively low secretion
of insulin by ß-cells. As we age or put on weight,
insulin sensitivity is lowered and ß-cells have to
secrete more insulin to maintain a normal level: a 4- to
5-fold increase in insulin secretion may be required. Normal
cells may be able to respond adequately. However, if ß-cells
cannot secrete sufficient insulin, then normoglycemia cannot
be maintained.
Inadequate ß-cell compensation for insulin resistance
was shown in a study of the Pima Indians in Arizona.6
About 40% of the Pima Indians become diabetic by middle
age. Some individuals have NGT; the ß-cell function
of these non-progressors is capable of generating more insulin
as their insulin sensitivity falls, thus staying on the
normal curve of ß-cell secretion as a function of
insulin sensitivity. For progressors (ie, those individuals
who are going to develop some abnormality of diabetes),
IGT becomes evident as the ß-cells begin to fail.
As ß-cell function gets worse, the fasting glucose
level increases (impaired fasting glucose, or IFG). Treatments
that reduce insulin resistance, such as lifestyle changes,
metformin or thiazolidinediones, sulfonylureas to stimulate
ß-cells, or even insulin, may help restore a normal
balance between insulin sensitivity and secretion. Some
individuals with IGT and/or IFG progress to diabetes. At
present, no medications are approved for preventing this
progression. |
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Predisposition to insulin resistance has three known components:
genetic; acquired obesity and inactivity; and metabolic,
the component that can progress rapidly. The greatest increase
in insulin resistance is found during progression from NGT
to prediabetes. Further progression from prediabetes to
type 2 diabetes is primarily a failure of ß-cells
in the pancreatic islets of Langerhans. A study by Reaven
et al7 showed a large drop in insulin sensitivity
as patients progressed from NGT to IGT, or prediabetes.
Little further change in insulin resistance was found with
progression to type 2 diabetes. Recent studies have investigated
this progression from NGT to IGT in greater detail, and
one study8 showed that the risk of developing
diabetes is greater in persons with low insulin sensitivity
and impaired secretion by ß-cells. Furthermore, it
seems that insulin resistance may be more important than
insulin secretion in progressing from NGT to prediabetes.
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The natural history of IGT over the course of 10 years shows
that some people revert to normal levels of insulin sensitivity
(33%), some stay the same (33%), and some progress to diabetes
(33%). These are average values, and the percentage of people
who progress can be higher in various ethnic groups.
The diagnosis of IFG, which represents a further progression
of ß-cell failure, is based on measurements of the
fasting level of glucose. Over the course of 10 years, 40%
of persons who have IFG will progress to diabetes. The percentage
of patients with IFG who develop diabetes is somewhat higher
than the percentage of patients with IGT who progress to
diabetes. |
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Diagnostic criteria of diabetes, IGT, and IFG are
shown in Figure 2. The American Diabetes Association
(ADA) has recently recommended that the cutoff between
normal and impaired fasting glucose be lowered to
100 mg/dL. For certain populations, values >95 mg/dL
may, in fact, be above normal. Values between 100
mg/dL and 125 mg/dL, if verified on a second occasion,
would indicate IFG. This is a risk category identified
by the ADA for diabetes, and it is also a risk category
for cardiovascular disease. Fasting glucose values
>125 mg/dL, if verified on another day, are diagnostic
for diabetes. The ADA recommends using the fasting
glucose test for population screening because it is
inexpensive and highly reproducible, but it is not
so sensitive as the glucose challenge.9
Some individuals with fasting glucose values below
the IFG cutoff can have diabetes; in such cases, a
glucose challenge would be suggested. If the post-load
glucose value is <140 mg/dL on two or more occasions,
the individual is normal. Glucose challenge results
between 140 mg/dL and 199 mg/dL indicate IGT, a category
known to indicate risk for developing diabetes and
cardiovascular disease. Values >200 mg/dL clearly
indicate diabetes.9 However, persons whose
glucose challenge values are indicative of diabetes
(>200 mg/dL) but whose fasting glucose levels are
normal or in the IFG range are grouped into a category
called isolated post-challenged hyperglycemia. About
half of patients over the age of 60 years who have
diabetes are in this category. If these patients receive
second-generation antipsychotics (SGAs)—or other medications
such as beta-blockers or steroids—they may progress
to fasting and postprandial hyperglycemia. |
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Who should be screened for type 2 diabetes? Screening serves
to identify any abnormality of glucose dysregulation, not
only type 2 diabetes. The ADA recommends screening for anyone
over the age of 45 years, as these persons may be more likely
to be overweight and insulin resistant.9 If the
results are normal, then a retest in 3 years is suggested.
However, persons who have any of the risk factors should
be screened more frequently. Risk factors include: 1) first-degree
relative with type 2 diabetes; 2) high-risk ethnic group;
3) arterial hypertension; 4) dyslipidemia; 5) previous IGT
or IFG; and 6) in females, a baby weighing more than nine
pounds at birth. |
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Patients with metabolic syndrome have the potential to progress
to prediabetes and those with prediabetes have a greater
potential for developing diabetes. For patients with diabetes,
their condition can become worse: patients with mild diabetes
can progress to hyperosmolar coma, and even diabetic ketoacidosis,
by treatment with some SGAs. Schizophrenic patients have
a 2- to 3-fold greater risk of diabetes before they receive
any medication, that suggests an intrinsic susceptibility.
Other possible risk factors for progression to diabetes
are weight gain, lipotoxicity due to increased visceral
fat, and inactivity.
What are the options for intervention to prevent metabolic
syndrome and prediabetes? Metabolic syndrome only recently
has been described, and limited data are available. Exercising,
eating appropriately, losing weight—the changes in lifestyle
known to prevent prediabetes from going onto diabetes—seem
to be important. These interventions can improve insulin
sensitivity and reduce many cardiac risk factors in these
patients. As mentioned previously, glucose levels are often
normal in cases of metabolic syndrome, but other risk factors
may be identified and must be addressed. One option is to
consider treating these patients as though they already
have developed type 2 diabetes: reduce blood pressure and
lipid levels to targets recommended by the ADA, stop smoking,
and take aspirin. Our understanding of the impact of SGAs
on the progression from metabolic syndrome to prediabetes
is limited by insufficient data, much of which is from case
reports or from retrospective reviews of insurance records
or health plan records. Prospective clinical trials are
lacking. Intuitively, high risk would be assigned to an
older, obese person who has higher insulin resistance, higher
blood sugars, and perhaps other risk factors. Conversely,
the literature indicates that some younger patients with
lower weight receiving SGAs are at greater risk for developing
diabetes. This suggests that weight gain is not the only
factor, and perhaps these agents are affecting the ß-cells
in some patients. As will be seen in the next article, the
results from available studies are contradictory, with some
studies suggesting that some SGA agents may cause weight
gain, while others find their effects to be neutral, and
some suggest that some agents cause weight loss. |
-
World Health Organization. Definition, Diagnosis
and Classification of Diabetes Mellitus and Its Complications:
Report of a WHO Consultation. Geneva, Switzerland:
Department of Noncommunicable Disease Surveillance,
World Health Organization; 1999:2-59
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National Cholesterol Education Program Expert Panel
on Detection, Evaluation, and Treatment of High Blood
Cholesterol in Adults. Executive Summary of the Third
Report of The National Cholesterol Education Program
(NCEP) Expert Panel on Detection, Evaluation, and
Treatment of High Blood Cholesterol in Adults (Adult
Treatment Panel III). JAMA. 2001;285:2486-2497.
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Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic
syndrome among US adults: Findings from the Third
National Health and Nutrition Examination Survey.
JAMA. 2002;287:356-359.
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Alexander CM, Landsman PB, Teutsch SM, Haffner SM.
NCEP-defined metabolic syndrome, diabetes, and prevalence
of coronary heart disease among NHANES III participants
age 50 years and older. Diabetes. 2003;52:1210-1214.
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Kahn SE, Prigeon RL, McCulloch DK, et al. Quantification
of the relationship between insulin sensitivity and
b-cell function in human subjects. Evidence for a
hyperbolic function. Diabetes. 1993;42:1663-1672.
-
Weyer C, Bogardus C, Mott DM, Pratley RE. The natural
history of insulin secretory dysfunction and insulin
resistance in the pathogenesis of type 2 diabetes
mellitus. J Clin Invest. 1999;104:787-794.
-
Reaven GM, Hollenbeck CB, Chen YD. Relationship between
glucose tolerance, insulin secretion, and insulin
action in non-obese individuals with varying degrees
of glucose tolerance. Diabetologia. 1989;32:52-55.
-
Weyer C, Tataranni PA, Bogardus C, Pratley RE. Insulin
resistance and insulin secretory dysfunction are independent
predictors of worsening of glucose tolerance during
each stage of type 2 diabetes development. Diabetes
Care. 2001;24:89-94.
-
American Diabetes Association. Clinical Practice Recommendations
2004. Diabetes Care. 2004;27(suppl 1):S1-S150.
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Atypical antipsychotics have revolutionized the treatment
of patients with schizophrenia or bipolar affective disorder.
However, while atypical second-generation antipsychotics
(SGAs) cause less motoric side effects than the typical
agents, there is some controversy concerning how these drugs
may affect glucose regulation, lipid metabolism, and induce
weight gain. Also, there is concern about how best to manage
these effects and their implications for choice of pharmacotherapy.
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A comprehensive, quantitative review was conducted in 1999
regarding the amount of weight gain associated with each
antipsychotic drug available or undergoing clinical trials
in the United States.1 A meta-analysis and random
effects meta-regression estimated the weight change after
10 weeks of treatment with each of 10 drugs at a standard
dose. Among typical agents, mean weight change ranged from
a reduction of 0.39 kg (0.9 lbs) with molindone to an increase
of 3.19 kg (7.0 lbs) with thioridazine. Mean weight increases
were found for SGAs as follows: clozapine, 4.45 kg (9.8
lbs); olanzapine, 4.15 kg (9.1 lbs); sertindole, 2.92 kg
(6.4 lbs); risperidone, 2.10 kg (4.6 lbs); and ziprasidone,
0.04 kg (0.1 lb). More recently, quetiapine, olanzapine,
and risperidone were found to have weight-gain liability
in the Canadian National Outcomes Measurement Study in Schizophrenia2;
weight gain >7% of baseline weight was observed in patients
receiving quetiapine (56% of patients), olanzapine (24%),
and risperidone (24%). Results of a study in Spain also
found weight gain >7% of baseline weight with olanzapine
and risperidone, but data for quetiapine were inconclusive.3
Short-term (4–6 wks) and long-term (26–52 wks) studies comparing
treatment with aripiprazole (2 to 30 mg/d) to placebo or
active comparator have shown minimal weight change.4,5
The pattern of weight gain is important. In a 47-week study,
Tohen and colleagues6 compared efficacy and safety
of olanzapine versus divalproex sodium for the treatment
of acute bipolar mania using a flexible-dose regimen. Weight
gain was significantly greater for the olanzapine patients
than for the divalproex sodium group (2.79 kg vs. 1.22 kg,
SE = 0.32, P < .001). Patients who were taking olanzapine
had the greatest weight increase during the first month
and reached a plateau after about 16 weeks, while the increase
in patients taking divalproex sodium appeared to rise steadily
during the 47 weeks. These data would suggest that once
patients have been maintained on olanzapine for four months
or more there is little additional weight gain. |
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The prevalence of type 2 diabetes is 2- to 4-fold greater
among patients with chronic mental illness.7
Many schizophrenic or bipolar patients may already have
some risk factors for diabetes (Table 1). Increased
rates of glucose dysregulation and insulin resistance were
noted in psychiatric patients even before the introduction
of antipsychotic or mood-stabilizing drugs.8
It is now established that patients who have some of these
risk factors for diabetes show a greater likelihood of developing
diabetes when taking antipsychotic drugs.
Most studies of glucose regulation in schizophrenia are
confounded by prior exposure to one or more antipsychotic
medications. One study examined glucose dysregulation in
first-episode, drug-naïve patients with schizophrenia compared
with healthy controls.9 Patients with schizophrenia
had significantly higher levels of fasting glucose, insulin,
and cortisol than the control group (P < .05). The
calculated insulin resistance was also higher, and 15% of
patients with schizophrenia had impaired fasting glucose
(fasting blood glucose >110 mg/dL and <126 mg/dL) compared
with none among controls. These results are consistent with
the idea that glucose dysregulation may be an inherent problem
in these patients, independent of drug effects.
The literature on diabetes mellitus and SGAs are often contradictory.
Case reports and summaries of annual data reports imply
causation or worsening of preexisting diabetes mellitus
in patients treated with SGAs, especially clozapine and
olanzapine. Epidemiological studies and clinical trial data
tend to show little difference between agents in the prevalence/incidence
of diabetes in the schizophrenic population. Basic science
studies (short-term “clamp” studies) show little or no direct
effects of SGAs on insulin release or resistance in healthy
subjects.10 |
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Risk Factors |
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Symptoms & Signs |
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Family history |
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Fatigue |
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Ethnic background |
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Frequent infections (skin, urinary tract infection,
yeast infections) |
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Overweight (central obesity) |
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Excessive thirst |
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Physical inactivity
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Excessive urination
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Hypertension |
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Nocturia |
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Low high-density lipoproteins/high triglycerides |
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Blurred vision |
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Polycystic ovary syndrome |
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Unexplained weight loss |
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Gestational diabetes or birth of infant >9 lbs |
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Acanthosis nigricans |
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History of impaired glucose tolerance or fasting glucose
>110 mg/dL |
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Retinopathy, neuropathy, nephropathy, vascular disease
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Koller and colleagues examined details of spontaneous cases
of diabetes reported to the FDA MedWatch Drug Surveillance
System that occurred in patients taking clozapine, olanzapine,
and risperidone.11-13 The data suggest that these
drugs may precipitate or unmask diabetes in susceptible
patients, and point out potentially severe problems such
as death due to complications of diabetes, a disease routinely
detected and treated. |
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Numerous studies have been conducted to examine the possible
association between diabetes mellitus and antipsychotic
medications, and 13 of these reports are summarized in Table
2. The greatest attention since 2001 has been given
to SGAs, with clozapine, olanzapine, and risperidone the
most frequently reported. Retrospective cohort studies and
reviews of claim records generally have grouped all first-generation
antipsychotics together for analysis, although haloperidol
and chlorpromazine have sometimes been singled out for analysis.
Generally, the retrospective analyses evaluated patient
records or claims from periods of a few months to 3 years.
The likelihood of patients receiving a given antipsychotic,
or class of antipsychotics, of developing diabetes compared
with the likelihood for another treatment group was reported
in terms of an odds ratio, relative risk, or hazard ratio.9
Overall, the studies have found that the risk of developing
diabetes is greater for patients receiving antipsychotics
than for untreated patients or a typical population; however,
the medications do not routinely differ significantly from
each other (Table 2). When significant differences
are found between different SGA, they tend to be small relative
differences. Also, some of the studies utilize small samples
of SGA-treated patients with results showing extreme confidence
intervals. Studies using logistic regression models sometimes
fail to provide statistical criteria used for including
covariates in the model. Despite the inherent limitations
of these pharmacoepidemiological studies, it appears that
patients maintained on antipsychotic medications are at
greater risk of diabetes mellitus than the general population
and that those receiving atypical antipsychotics may be
at an even greater risk for developing glucose dysregulation.
However, it appears that patients who already suffer from
diabetes mellitus may be safely treated with antipsychotics
so long as they receive proper care for their glucose dysregulation.14
If patients have diabetes, they can be treated with SGAs,
and their diabetes should be managed just as with any other
diabetic patient. Whether or not there is a direct effect
of olanzapine or risperidone treatment on b-cell function
in healthy volunteers was evaluated using a hyperglycemic
“clamp” procedure.10 After treatment for 15 to
17 days, an increase in the insulin response to hyperglycemia
and a decrease in the insulin sensitivity index were observed
in both treatment groups. The subjects in both groups exhibited
similar changes in insulin levels (fasting and clamp) that
appeared to be largely related to significant weight gain
(P < .01). Data from this study do not support a
direct effect of olanzapine or risperidone on decreasing
insulin sensitivity or impairing insulin secretion by the
pancreatic ß-cells.15 |
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Clozapine, olanzapine, and quetiapine appear to increase
serum triglycerides. Generally, they do not increase cholesterol
levels, although it may appear so because serum triglycerides
are part of total serum cholesterol values. This elevation
of triglycerides does not seem to be a problem with ziprasidone,
risperidone, and aripiprazole16-20 (Table
3). Fasting serum triglycerides >500–700 mg/dL can be
associated with pancreatitis, a potentially fatal complication,
and elevated serum triglycerides can also be predictive
of heart disease.
Resolution of elevated serum triglyceride levels associated
with specific antipsychotics has been investigated in some
patients. Elevated serum triglycerides in patients treated
with clozapine were reduced in 4 patients after switching
from clozapine to risperidone.21 In 2 patients,
re-treatment with clozapine again increased serum triglycerides.
Changes in total serum cholesterol were small or nonexistent.
A retrospective analysis by Wirshing et al22
showed significantly elevated triglyceride levels with clozapine
and olanzapine, but with drops in low-density lipoprotein
for olanzapine, risperidone, and quetiapine. A retrospective
review of more that 150 patients per medication treated
over the course of one year found significant increases
in serum triglycerides in patients treated with olanzapine.
Patients receiving risperidone in conjunction with lithium
or valproate had increased serum triglycerides as well.
Patients concurrently receiving mood stabilizers (lithium
or valproate) had double (risperidone, NS) or triple (olanzapine,
P < .05) the weight gain compared with patients not
receiving mood stabilizers, indicating that concomitant
drug use can be an important factor in causing metabolic
changes in patients receiving SGAs.23
Increases in serum triglycerides can occur without weight
changes, A strong association (P < .02) between increased
weight (12 lbs) and the increase in fasting triglycerides
(60 mg/dL, or 37% increase) with olanzapine after 12 weeks
has been reported,10 but three quarters of the
variation of changes in serum triglyceride were unrelated
to weight gain. Thus, serum lipids should be monitored even
in patients who do not gain weight while using atypical
antipsychotics. |
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Taken together, these reports point out t | | |
