Co-Morbid States Are the Rule—Not the Exception—in Pain Practice
Anyone who treats chronic pain patients knows that the multiple complexity of this condition is not always obvious. As pain evolves from the acute to the chronic state—whether neurogenic or neuropathic in origin —it alters neuronal pathways, impacts mood and interferes with sleep. What drives these changes, the condition? The treatments? The patient’s beliefs? Anxiety and/or mood disorders? Genetic loading? Poor sleep?
The purposes of this article are:
- the need to understand our patient before we can understand their pain,
- a brief overview of several co-morbid elements that drive the expression of pain, independent of the original insult, and
- to assist the physician and their staff with a conceptual model for consideration of a multimodal approach.
Limitations of the Physician-Patient Interchange
Our thesis is that treatment begins with the initial physician-patient interchange and must include an understanding of how our patients express their subjective symptomatic experience. This mutual understanding helps us quantify what we are hearing and ensure that our treatments are in sync with how our patients experience their pain.
There are studies that demonstrate that predictors of treatment outcome can be dependent, in part, on the patient’s verbalizations. For example, Galli et al1 have shown that a patient believing that pain could have serious consequences on one’s life (IPQ2 subscale consequences) is one of the most important predictors for treatment outcome. They concluded that beliefs about pain are important predictors for treatment outcome—even when controlled for pain and mood. Further, both baseline pain-related disability and baseline pain intensity were only minor predictors for pain and mood—providing further evidence that severity of chronic pain is predicted mainly by psychological variables.
While we are not advocating that patients be treated with placebos, the placebo response may hold a key to how patients perceive and respond to treatment. Morton et al3 looked at the response of healthy, non-pain, volunteers to a sham laser procedure. Pre test they were given the State Trait Anxiety Inventory (STAI)4 to distinguish between state and trait anxiety; Marlow–Crowne Social Desirability Scale (MCSDS)5 measuring the subjects apparent social desirability tendency to give answers to make the respondent look good; the Eysenck Personality Questionnaire-Revised (EPQ-R)6 to specifically measure neuroticism and introversion/extraversion; and finally the Revised Life Orientation Test (LOT-R)7 to measure dispositional optimism.
Their findings suggest that placebo effects are moderated by a reduction in state anxiety which, in turn, decreases pain perception. However, it was unclear as to whether this reduction in anxiety is a cause or the consequence of the placebo response. Their results suggested that a placebo response in the first session was associated with a trend towards a decrease in state anxiety prior to starting the repeat session (see Figure 1).
Can our understanding of how a patient expresses their understanding of their illness and what they expect from treatment result in better outcomes? How does their history contribute to what they tell us about their pain and their expectations for recovery? Is there a way to use this information to amplify our results?
Let’s begin with the opposite: what do we know impedes treatment response? Celestin et al8 examined pretreatment psychosocial variables as predictors of outcomes following lumbar surgery and spinal cord stimulation. In a review of 753 study titles, 25 studies were identified, of which none were randomized controlled trials and only four spinal cord stimulation studies met inclusion criteria. Despite the large number of studies reviewed, the authors reported that the methodological quality of the studies varied and identified some important shortcomings. However, a positive relationship was found between one or more psychological factors and poor treatment outcome in 92.0% of the studies reviewed.
They found that self-reported levels of depression, anxiety, coping, somatization and hypochondriasis were found to be associated with greater risk for poor outcome in most studies and in the expected direction—e.g., higher pre-surgical levels of distress, somatization, etc., were generally associated with less treatment-related benefit. These findings were in agreement with past reviews. Pre-surgical levels of variables within the categories of pain and functional activity limitation were less (my emphasis) useful in predicting treatment outcome.
In their review of the literature, they noted that creating treatment paradigms based upon a patient’s expressed level of pain and limitations of function appears to be a poor predictor of outcome. Knowing the patient’s emotional state, coping skills, potential for optimism or use of hypochondriasis appears to be a better predictor of outcome.
What do we know about how the impact of these emotional states effect the body’s tolerance for pain? Our historic emotional programming evolves from the balance between our nature and our nurturing. The genetics of mood disorders and anxiety disorders are well enough established that they need no extensive discussion here. However, how we ask the questions and probe about historic data in these areas is critical.
Self report forms are mostly normalized in our language, English. Questions such as, “Are you depressed? Do you feel anxious?” may not translate cross-culturally, and sometimes not even inter-generationally.
Noguera, et al9 had Spanish patients with cancer complete the Hospital Anxiety and Depression Scale (HADS)10 and six Verbal Numerical Scales (VNS) exploring the level of anxiety using the terms ansioso (anxious), nervioso (nervous), or intranquilo (uneasy/disquiet), and the level of depression using the terms deprimido (depressed), desanimado (discouraged), or triste (sad). He found that the Spanish word, ‘desanimado,’ or discouraged, had a greater correlation to describing patients’ mood than depression. This study was limited in scope but underscores the point that what we think a patient means may not be what they are expressing. This example is given to stress that the interviewer must review the family history in patients with divergent cultures and ages in a way that captures the information accurately. Understanding the verbiage of mood and anxiety disorders isn’t the only challenge. Knowing how those conditions are perceived in some cultures—for example, having a consequence to a family’s community standing—is critically important.
Yang11 describes the issue of losing ‘face’ in Chinese society as it applies to mental illness, in general, and schizophrenia, in particular. The take-home lesson is clear as it relates to acquiring information from a patient from a different culture. Without properly understanding that the information is culturally embarrassing, you are less likely to get the genetic history you need.