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18 Articles in Volume 11, Issue #9
Pain and Sleep: A Delicate Balance
Management of Insomnia: Considerations For Patients With Chronic Pain
PPM Editorial Board Outlines Management Strategies for Chronic Pain Patients With Insomnia
Attention Deficit Hyperactivity Disorder And Patients With Pain
Dry Needling Offers Relief From Chronic Low Back Pain
Etiology of Chronic Pain and Mental Illness: How To Assess Both
Temporomandibular Disorder: Examining the Cause And Treatments
Highlights From PAINWeek 2011
Is Your Patient Using Heroin?
Medications For Low Back Pain
Nonpharmacologic Treatments for Patients With Sleep Disorders and Pain
Man With Constant, Daily Headache Pain, Photophobia, Phonophobia, and Nausea
Successful Nonoperative Treatment of Persistently Painful Knees Following Total Knee Arthroplasty—A Case Series
Insomnia in Chronic Pain Patients
What Is Going Wrong With Research? Finding the Right Answer
Testing Positive for Marijuana in Urine
Hydrocodone, Carisoprodol, and Alprazolam—A Most Lethal Combination
Pro-inflammatory Diet

Highlights From PAINWeek 2011

Assessment and Risk Management in Chronic Opioid Therapy

A number of posters at this year’s PAINWeek1 examined how physicians can improve assessment and risk management in patients on chronic opioid therapy (COT). Some looked at screening tools, whereas others assessed physician knowledge and comfort regarding prescribing opioids.

In the first poster, Pain Paradox, a continuing medical education (CME) company, examined how much their programs affect physician behavior.2 The company examined the responses of participants both before and after participating in their “learning gallery” at five recent medical meetings (PainWeek [2009 and 2010], American Pain Society [2009 and 2010], and the American Academy of Pain Medicine [2010]).

The CME program consisted of a multimedia “education gallery” followed by faculty-led simulated case scenarios to improve clinician knowledge regarding best practices for risk assessment and management of patients on COT. A total of 428 attendees participated in the education gallery—the vast majority of whom were physicians (50%-52%), followed by nurses (14%-17%) and pharmacists (9%-10%). The activity focused on risk evaluation, including risk factors associated with addiction, urine drug testing (UDT), treatment agreements, legal requirements for prescribing controlled substances, and differential diagnoses related to aberrant behaviors.

The researchers reported that at baseline, a minority (29%) of clinicians correctly recognized that when federal and state regulations differ, the more stringent law applies. After the education gallery, a substantial minority (23%) still failed to recognize the appropriate regulations.

Interpreting UDT also remained problematic. At baseline, 56% of clinicians thought that unexpected UDT results were definitive evidence of diversion—as opposed to a broad differential that includes diversion. Even after education on the complexities of UDT, 32% of participants still interpreted a lack of opioid in UDT as definitive evidence of diversion.

When faced with clinical scenarios of aberrant opioid medication behavior, most participants (more than 90% of 638 clinicians) did not conclude diversion or addiction. They did, however, struggle to differentiate among pseudoaddiction (50%), medication tolerance (60%), and physical dependence (51%).

Also, when faced with initial presentation of aberrant behavior, participants did not appreciate the broad differential diagnosis driving the behavior—instead, they jumped to a definitive diagnosis before sufficient information was available.

Through the activities, however, clinician comfort in prescribing opioids significantly improved—from 67% at baseline (comfortable/very comfortable) to 87% after the activity (n=470; P<0.01). What’s more, the benefits endured: At 3 months, 86% of clinicians reported comfort with prescribing opioids.

The authors concluded that in order to help clinicians attain optimal performance when it comes to assessment and risk management in COT, there should be multiple iterations of educational and quality improvement activities.

Screening for Psychiatric Comorbidities


Undiagnosed or untreated psychiatric comorbidities may contribute to medication misuse, abuse, or diversion among patients with chronic pain. Personality traits are key factors that may contribute to aberrant behaviors and are of importance to prescribers of opioid regimens. Therefore, increasing numbers of practitioners are prescreening patients for psychosocial issues before starting them on a pain program. But which screening tools are most effective at predicting which behaviors?

In order to determine correlations between high-risk behaviors and personality type, investigators from Hattiesburg, Mississippi, examined a large outpatient sample of patients with chronic pain being screened for appropriateness of long-term opioid therapy.3 Ninety-six patients were administered the Millon Behavioral Medicine Diagnostic (MBMD), which measures psychosocial assets and liabilities that affect treatment response, and the Screener and Opioid Assessment for Patients with Pain–Revised (SOAPP-R), which is a measure designed to predict aberrant medication-related behavior.

The researchers found that when the psychiatric indicators of the MBMD were added, 42.7% of the variance in SOAPP-R scores (P<0.001) could be explained. Number of pain sites and emotional lability significantly predicted SOAPP-R score over other psychiatric indicators.

Identifying patients who are at risk for opioid misuse has significant importance, noted the investigators. “These findings suggest personality assessment serves as an effective adjunct to risk stratification. Personality factors such as emotional lability and traits of borderline personality may increase opioid misuse potential,” they added. Clinical interview, history taking, and psychological assessment are valid ways pain specialists can assess personality. Prescribing strategies such as prescreening, close monitoring, limit setting, and inclusion of psychological support can mitigate risk, they concluded.

Adherence to Hospital Policy On Screening

Opioid analgesics are effective for severe chronic pain, yet providers remain reluctant to prescribe them because of concerns about tolerance, dependence, and addiction. Guidelines for the management of chronic noncancer pain (CNCP) clearly emphasize certain assessment tools to help identify and prevent misuse, abuse, and diversion. But how well are these tools being implemented? According to a study by one institution, the majority of primary care physicians (PCPs) were using opioid treatment agreements and urine toxicology screening (UTS), but were less likely to implement baseline risk stratification and periodic risk assessment—including psychological assessment and SOAPP-R.4

The study, which was designed to identify the prevalence of risk assessment and management for patients following the implementation of an institution-wide opioid therapy policy at the Phyllis Jen Center for Primary Care at Brigham and Women’s Hospital in Boston, Massachusetts, contacted PCPs for a current list of patients with CNCP on COT. Patients who met the following criteria were included in the analysis: age at least 18 years, CNCP (defined as pain for at least 6 months unrelated to cancer or other malignancy), and taking COT between May 2008 (date of implementation of institution-wide opioid therapy policy) and May 2011.

To determine the prevalence of opioid risk assessment and adherence to policy guidelines, the following parameters were identified: use of pain assessment tools (verbal numeric rating scale, Brief Pain Inventory, McGill Pain Questionnaire), documentation of physical exam specific to pain, use of opioid treatment agreements, use of initial and subsequent UTS, use of SOAPP-R, use of Current Opioid Misuse Measure (COMM), and use of Addiction Behaviors Checklist (ABC). As a secondary analysis, correlations between patient demographics and risk assessment parameters were evaluated using Statistical Packages for Social Sciences (SPSS).

PCPs identified 93 patients; however, only 84 patients met the criteria for inclusion. The mean age was 59.5 years (range, 28-89), and the majority of patients were women (61.9%). Half of the patients were white (46.9%), with the remainder being black (38.1%) or Hispanic (14.3%). More than half of patients reported being unemployed, and 57.2% had a high school or college education. Most patients had low back pain (51.2%), followed by osteoarthritis (27.4%), and more than half reported pain at multiple sites. Slightly fewer than half of patients had comorbid depression and/or anxiety. Most patients did not have a history of substance abuse, and 14.3% of patients had a family history of substance abuse. Forty-four percent of patients had visited the emergency department (ED) at least once for a pain-related issue, and there were significant differences based on ethnicity.

With regard to adherence to policy guidelines, fewer than 10% of patients had their pain assessed with the use of a validated pain tool such as the verbal numeric rating scale. More than 60% of patients had a documented physical exam specific to pain on at least one occasion. Most patients had an opioid treatment agreement in place (84.5%) and had initial UTS (87%). Fewer than half of patients had one or more subsequent UTS. Very few patients had documented SOAPP-R (8%), COMM (3.5%), or ABC (0%) scores. Positive correlations were identified between various parameters, including gender and subsequent UTS and ethnicity and ED visits.

Data from this preliminary analysis will be used to support interventions that promote increased education on opioid use for chronic pain management as well as support the development of a pharmacist-run chronic pain management clinic embedded within the primary care center.

Helping Primary Care Physicians Identify Fibromyalgia

Despite established diagnostic criteria for fibromyalgia (FM), many clinicians still report difficulty with the differential diagnosis. A new FM diagnostic aid may help PCPs better identify patients with this painful disorder, according to its developer, Lesley Arnold, MD, of the University of Cincinnati College of Medicine.5

The Arnold Fibromyalgia Diagnostic Screen (AFDS) uses clear, simple language and illustrations to help familiarize physicians with tender points, key clinical evaluations, and important conditions to consider in the differential diagnosis of FM. The items in the AFDS were based on clinical and research experience with patients with FM, noted Dr. Arnold. The AFDS guides clinicians on how to perform an abbreviated tender point exam. Illustrations depict where on the body these eight tender points are located. The tool also guides users through joint and muscle strength evaluations.

To help evaluate for other conditions that could be causing widespread pain, users are directed to evaluate connective tissue. Photographic examples of alopecia and a rash are shown so that clinicians can determine whether the subject may or may not have signs suggestive of lupus erythematosus. Users are also directed to ask the patient questions that can help assess for multiple sclerosis and hepatitis.

Based on the results of the clinician exam, the AFDS refers clinicians to appropriate laboratory tests. The aid then instructs clinicians to determine whether or not the patient has FM based on 1) the summary of clinical findings from the previously outlined tasks and 2) the results of the patient-rated portion of the AFDS.

Dr. Arnold recently tested the effectiveness of the AFDS. He reported that “the aid can help clinicians who are unfamiliar with FM become better equipped to correctly diagnose patients and thus begin management of this common, painful condition.”

Neuropathic vs Nociceptive Pain—Which Is Worse?

Pain is a complex phenomenon affected by many factors, including the individual’s biology, psychology, and sociology. Recent mechanism-based studies suggest that neuropathic and nociceptive pain may have similar subjective features. The goal of this study was to evaluate pain, physical disability, and psychological factors in two distinct groups of patients with chronic pain using well-established self-assessment tools.6

A cross-sectional sample of 36 patients with chronic “neuropathic” pain from limb amputation (23 men, 13 women) and 37 patients with chronic “nociceptive” pain from osteoarthritis (OA) (9 men, 28 women) were included from two institutional review board–approved studies. Participants were compared for their self-reported global pain, sensory and affective components of pain, disability, depression, and anxiety using the visual analog scale (VAS), McGill Pain Questionnaire (MPQ-SF), Pain Disability Index (PDI), Beck Depression Inventory (BDI), and Pain Anxiety Symptoms Scale–20 (PASS-20), respectively.

The investigators found that VAS score was higher in amputees than in patients with OA (35.5±25 vs 22.2±24.3; P=0.026); however, the groups did not differ in MPQ-SF, PDI, BDI, and PASS-20 scores. For each group, higher VAS and MPQ-SF scores were correlated with higher PDI and PASS-20 scores, but not with BDI scores.

Although current VAS scores were higher in amputees than in patients with OA, other subjective features of chronic pain were similar between these models of “neuropathic” and “nociceptive” pain; thus, two mechanistically distinct chronic pain models can share many subjective psychometric features.

24-Hour Holter Monitor Better Predictor of QTc Prolongation

Because of its low cost, methadone has been increasingly used to treat patients with chronic pain. However, a recent rise in deaths in patients taking methadone has raised concerns about its safety—especially when given at higher dosages.

Adding to concerns have been contradictory reports on the effect of methadone on the QTc interval duration. Indeed, Eap et al7 and Cruciani8 reported a correlation between the QTc duration and the dose of methadone, whereas other investigators did not find such correlation. This has left many clinicians wondering about the best way to measure potential cardiac toxicity in patients on methadone.

To help examine this question, a group of investigators presented data of single electrocardiogram (ECG) studies on patients on methadone and compared them with 24-hour Holter monitoring.9 To date, 39 patients on methadone, all aged older than 50 years, have completed the study. Each had an ECG, a 24-hour Holter, and electrolytes (potassium, calcium, and magnesium) drawn during their first visit (visit 1). These tests were repeated 8 weeks later (visit 2, 20 of 36 completers). Participants also were grouped based on their methadone dosage: 0, 10 to 40, 41 to 120, and greater than 121 mg. A QTc prolongation (QTcP) greater than 500 milliseconds was considered definite risk for torsade de pointes. QTc greater than 430 and 450 in men and greater than 450 and 470 in women was considered increased and high risk, respectively. All data were analyzed by an experienced cardiologist.

The data from visit 1 were presented at PainWeek. According to the researchers, a single ECG detected QTcP in 15 of the 39 patients (5 of 15 >500 milliseconds). Of those 15 patients, 12 had at least one Holter reading and showed QTcP in 11 (5 of 11 >500 milliseconds). Of the five patients with QTc greater than 500 milliseconds by ECG, three had correlative Holter that detected two. Of the 36 patients who had at least one Holter reading, 21 showed QTcP. ECG detected it in 11 of these patients.

The investigators then compared QTcP detected at four different times of the day by Holter monitoring with a single ECG. The results were as follows: 12:00 am, 12/10; 6:00 am, 17/9; 12:00 noon, 15/7; and 6:00 pm, 13/9. The QTc prolongation is dose dependent. At baseline, the highest-dosage group (>120 mg) showed significantly higher QTc intervals than the three lower-dosage groups (479.3±82.5 vs 439.8±32.4; P=0.01). The three lower-dosage groups did not differ from each other. The QTc prolongation was dose dependent. The greater-than-120-mg group showed significantly higher QTcP than the three lower-dosage groups (467.3±42.6 vs 422.8±34.0; P=0.003).

The investigators concluded that a single ECG detected fewer patients with QTc interval prolongation (15 vs 20) compared with 24-hour Holter monitoring but detected the same number of patients with QTc greater than 500 milliseconds. Twenty-four-hour Holter monitoring detected twice as many patients with QTc interval prolongation than ECG at 12:00 noon, suggesting that one ECG might not be sufficient to identify patients at risk. There is a dose-dependent effect on QTc interval prolongation in patients taking greater than 120 mg per day compared with those on lower dosages.


Last updated on: April 18, 2018
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