Sean Prabhu, MD

Now in its fifth edition, DSM has served as our guide to identifying, communicating, and guiding treatment for the great variety of psychiatric illnesses with which our patients have been afflicted. Among our core principles is to treat the patient and not necessarily the diagnostic label or radiological or laboratory findings. Although looking at both a patient’s symptoms and the diagnostic label that best describes his or her clinical picture in tandem generally improves clarity and treatment planning, this doesn’t always happen to the degree we would like.

For example, over the last 4 years of my residency (we began training under DSM-IV), the overwhelming subtype of schizophrenia I encountered was “chronic undifferentiated.” over the last 4 years of residency, the The utility of this diagnostic label is questionable given the vast differences in presentation of signs and symptoms among this diverse group of patients. In large part, this is why we no longer find this model of classification in DSM-5.

My first impression of this change was that things had been simplified for the better. However, I was taken aback when I came across the specifier for “current severity” for which we are to refer to the Clinician-Rated Dimensions of 

 under “Assessment Measures” and assign numerical values from 0-4 to the domains of the following:

I) Hallucinations
II) Delusions
III) Disorganized Speech
IV) Abnormal Psychomotor Behavior
V) Negative Symptoms
VI) Impaired Cognition
VII) Depression
VIII) Mania

I felt as if we might be moving backwards and rigidly categorizing this impressively heterogenous group of patients.

Dr Rajiv Tandon’s talk on Advances in Diagnosis and Phenomenology at 

 showed us how these cold and rigid numbers could actually be used to customize treatment effectively for this patient population. We would be better equipped to track progress in symptom severity across each specific domain.

For instance, a patient who reducted symptom severity in the domains of hallucinations, delusions, and depression but who does not show as impressive an improvement in the domain of cognition might lead the clinician to reevaluate the medications for the possibility of anticholinergic adverse effects or more closely examine quality of sleep, etc. If no cause for impaired cognition can be found, the clinician can move on to pursuing appropriate treatment avenues to optimize cognitive function.

Likewise, particularly in our case as resident physicians in which we often cover for each other during post-call days, if this information is available for our review, we have a better idea of relative treatment progress as well as heightened vigilance for areas of poor response. This information is crucial for making treatment plan modifications to address the specific needs of the individual patient optimally. These “numbers” now begin to feel less cold and rigid.

During related talks throughout the conference, the heterogeneity of the disease known as schizophrenia was referenced repeatedly. The talk given by Dr Matcheri Keshavan highlighted cognitive dysfunction among this patient population. The discussion included concepts such as the Redox theory, cellular membrane and mitochondrial dysfunction as possible underlying mechanisms, but more pertinent to our discussion, the theoretical existence of identifiable cognitive phenotypes. This led into the proposition of re-thinking how we categorize patients within the spectrum of psychotic illness.

Our current model focuses on 3 main diagnoses: schizophrenia, schizoaffective disorder, and mood disorders with 

. However, if we group patients using different conceptual criteria (ie, having certain combinations of genetic polymorphisms for immune related and glutamate regulation functions implicated in the pathological model for this disease spectrum) who share common phenotypic presentations, the composition of our new categorically identified patient groups or “biotypes” may differ greatly from that delineated using our current categories. Is it possible that patients who do not respond as well to the same treatments that proved effective for their DSM-categorized peers show better response to alternate treatments akin to their new peers who fall under the same biotype?

While shifts in conceptualization of disease pathology, diagnosis, and treatment take time to demonstrate validity, these discussions encourage us to continually question the basis of our medical decision making, to keep in mind the big picture, and to focus on the intimately unique needs of each individual patient.

Dr Prabhu is Chief Resident in the Department of Psychiatry and Neuroscience at Detroit Medical Center/Wayne State University.

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An analysis of symptom severity across domains may enable us to reevaluate how we categorize symptoms within the spectrum of psychotic illness.

Subtle Nuances in Diagnosis of Schizophrenia

The risk of metabolic side effects has long been a prominent concern when determining optimal treatment for a variety of psychiatric disorders. This is perhaps most significant for patients with disorders of mood instability and psychosis since the second generation antipsychotics (SGA) have proven to be extremely effective. These medications present varying risks for causing or contributing to metabolic syndrome.

 highlighted the significance of poor blood glucose control on psychiatric morbidity and mortality. They emphasize our roles as physicians to look at the whole picture: body, brain, and mind. As the field begins to unravel the intricate relationship between impaired glycemic control and bipolar disorder, the possible directions for treatment options continue to expand.

In some of the studies discussed, it was found that up to 53% of bipolar disorder patients have 

 or diabetes. More alarming yet is that up to 75% of these patients did not know they had impaired glycemic control. The gravity of these numbers really hits home when we keep in mind that the leading cause of death among patients with bipolar spectrum disorders is cardiovascular disease. It is often easier to remember to screen for suicidal risk factors, such as access to firearms that threaten the well-being of our patients here and now. However, the long-term poorly-controlled blood sugars of many patients will end up claiming more lives.
 

Screening for Metabolic Syndrome in Bipolar Disorder

From this point forward, I for one will look at poor glycemic control among this patient population as a loaded gun (pun intended).

While the neurotoxic effects of hyperglycemia are well known, a prominent theme heard at the APA is the direct effect of insulin on neuronal function. I learned that insulin is believed to serve as a neurotropic factor, similar in some respects to brain-derived neurotropic factor (BDNF). Insulin may play a role in inhibiting neuronal apoptosis, regulating beta amyloid plaque deposition and tau protein function, broadening the scope of patients to those with neurocognitive disorders for whom this is of particular importance.

It is not hard to imagine that compromised insulin function could detrimentally affect neuronal health and function, leading to prominent neurocognitive symptoms. Studies discussed showed reduced hippocampal size and poorer cognitive performance among bipolar patients with type 2 diabetes mellitus compared with patients who had bipolar disorder alone. Conversely, bipolar patients with optimal glycemic control showed increased grey matter volume compared with their less optimally glycemic controlled peers.

We also heard how insulin resistance was shown to reduce patient response to lithium for treatment of bipolar disorder. There does appear to be a relationship between insulin resistance and bipolar disorder but its nature is unclear. More than likely, the mechanism will be complex, involving numerous other variables.

Might there be a common etiology underlying both insulin resistance and bipolar disorder (or at least a subset)? A few of the clues that connect the two include a relationship with the hypothalamic-pituitary axis, increased noradrenergic tone, and elevated markers for neuro-inflammation. Etiological considerations for a number of psychiatric illnesses including major depression, bipolar disorder, and schizophrenia have begun to look more closely at the role of the latter.

Given the plethora of anti-inflammatory tools already being used by many of our medical peers, optimism for continued improvement in the treatment of our patient population grows each day.

As the intricate relationship between impaired glycemic control and bipolar disorder begins to unravel, possible directions for treatment options for the mood disorder continue to expand.

The Impact of Impaired Glycemic Control on Bipolar Disorder

[[{"type":"media","view_mode":"media_crop","fid":"38388","attributes":{"alt":"Terence-Mendoza-shutterstock","class":"media-image media-image-right","id":"media_crop_3001469650029","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"3866","media_crop_rotate":"0","media_crop_scale_h":"200","media_crop_scale_w":"133","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"float: right;","title":"Terence-Mendoza/shutterstock.com","typeof":"foaf:Image"}}]]As a fourth-year psychiatry resident, the thought of completing training and entering the “real world” can be quite daunting. For me, a symposium at APA 2015, “Evidence-Based Psychopharmacology: Algorithms to Guide Clinical Decisions for Treating Bipolar Disorder,” translated into “if you’re worried about making mistakes, follow these key points and you should at least be okay for treating patients with bipolar disorder.”

Walking into the symposium, I figured we would simply be following along some type of flow diagram or decision tree. What I didn’t see coming was a tectonic shift in my conception of the disorder-particularly the depressed phase.

From the first day of training, we are repeatedly cautioned about the use of antidepressants in patients with bipolar disorder and the risk of causing a switch from a depressed phase into a manic phase. The state of irritability, impulsivity, poor judgment, and potential compromise in reality testing is feared for its potential to bring harm to the patient and to others. While the manic phase is arguably the “sexier” of the two poles, we may not always focus closely enough on the target of euthymia instead of simply “getting out of mania.” This may have been the first time I can recall being formerly cautioned about causing a switch from a manic to a depressed state.

Patients can be weighed down with the negative emotional and cognitive cloak of depressed mood while still having the leftover goal-directed and physical energy of the manic phase from which they came. This can be disastrous for obvious reasons. We may have helped our inpatients out of a manic phase before they are discharged. However, the stability we see at this time may be a temporary state and may herald a depressive episode. Thus, it is crucial to have a high level of vigilance for depressed features and to ensure follow-up within 7 days-at which time we can still intervene if needed.

On average, patients with bipolar disorder spend approximately two-thirds of their time in a depressed or euthymic state. Thus, effective treatment of depressive symptoms is paramount to preserving safety and quality of life. To this end, Drs Dana Wang, David Osser, Arash Ansari, and Othman Mohammad presented a beautifully detailed algorithm for treatment options-for the depressed phase of the illness as well as the manic phase.

The algorithms are available on the Psychopharmacology Algorithm Project Web site (

), and I highly recommend taking advantage of them.

Some of the key points discussed regarding treatment of bipolar depression:

1. Is there a clinical argument for ECT (are patients acutely suicidal)?

• In most cases, patients with bipolar depression require fewer treatments than those with unipolar depression.

2. What is the best option for the patient who demonstrates psychotic symptoms?

• An atypical antipsychotic is preferred for initial mood stabilization. Olanzapine is not the first choice, given its metabolic adverse effects. Typical antipsychotics can increase the risk of depressive symptoms.

3. Initiation of therapy with a mood stabilizer is recommended if the patient is not alreadytaking a mood stabilizer.

• Lithium remains the first choice (barring any contraindications), given its proven efficacy (even as monotherapy) in reducing suicidality and its likely neuroprotective effects (thought to reduce neuronal apoptosis and glutamate-mediated excitotoxicity). The number needed to harm for causing long-term renal impairment is about 300.

• Quetiapine is the next best choice (barring any contraindications) and is FDA-approved for bipolar depression. Evidence demonstrating its use as monotherapy for bipolar disorder is still lacking.

• Lamotrigine is not FDA-approved for acute bipolar depression but is approved for bipo-lar depression maintenance therapy. It has a more favorable adverse-effect profile than many other options and has been shown to increase the time between manic episodes.

• Lurasidone is also a valid option, and it en-joys a more reasonable adverse-effect profile. It has FDA approval for treating bipolar depression. Its relative novelty to many clinicians and fewer number of clinical trials are likely holding it back from receiving even higher recommendations for use.

These points are but a fraction of the suggestions and recommendations for treating this patient population. The speakers covered other topics-including possible treatment options for failed trials, when to augment with a second agent, and the lack of overall clinical evidence to support the use of adjunct antidepressants. These algorithms are wonderful tools for all clinicians because they are based on the scientific evidence available to date.

This article was originally posted on May 20, 2015 and has since been updated.

A beautifully detailed algorithm for treatment options in bipolar disorder is described.

Sean Prabhu, MD

Articles

Subtle Nuances in Diagnosis of Schizophrenia

The Impact of Impaired Glycemic Control on Bipolar Disorder

Tectonic Shift in the Conception of Bipolar Disorder