The Growth of Unidimensional Pain Assessment Tools

A subjective and personal experience, pain remains difficult to quantify within the confines of empirically based medical tradition. Regardless of this challenge, however, management still necessitates accurate and timely assessment, particularly in the perioperative patient. The promotion of pain as a fifth vital sign in the 1990s has been criticized for its potential unintended consequences, however, this initiative also highlighted the limitations of our assessment tools and encouraged the development of improved methods to evaluate pain and its modifying factors.

As the Numeric Rating Scale (NRS) and Visual Analog Scale (VAS) became common standards for the regular interval assessment of patients in the perioperative setting, it was evident that these self-reporting tools were superior to health professional estimates and minimized the impact of cultural and racial bias. Multiple studies comparing the NRS and VAS scales consistently demonstrated similar sensitivities and superiority to the Verbal Rating Scales (VRS) in their ability to detect differences in both acute and cancer pain. Temporally-based assessments and measurement of pain trajectory have also become increasingly commonplace.

However, it has become increasingly evident that single-dimension pain tools lack the sophistication needed to guide effective therapies. In fact, a large retrospective review of medical records before and after the implementation of the “Pain as the 5th Vital Sign” initiative did not find any improvement in quality of pain care, especially with individuals with severe pain documented on NRS. Clinicians and investigators increasingly appreciated the impact of anxiety, depression, addiction, and the psychosocial context of the experience. For example, in the primary care setting, the NRS was found to have only modest accuracy for identifying patients with clinically important pain, defined as pain that interferes with function or intense enough to require a physician visit. Single dimension pain tools were inherently subjective and also not generalizable. Despite qualifying descriptions, patient A’s pain score of 4 may equate to patient B’s pain score of 6. These limitations in the unidimensional assessment of perioperative pain necessitated a new approach.

The Importance of Multidimensional Assessment

In response to these shortcomings, a focus on multidimensional assessment models has grown to evaluate properly the complexity, the modifying factors, and the associated disability of pain. Traditionally used in the chronic pain setting, tools such as the McGill Pain Questionnaire and Brief Pain Inventory (BPI) have been further validated in the postoperative setting. The McGill Pain Questionnaire provides a description of not only the intensity, but also quality of pain a patient is experiencing and can be used to monitor the efficacy of interventions and pain trajectory (ideal for the perioperative setting). The BPI accurately assesses pain severity and self-perceived functional limitations. Similar to the McGill Pain Questionnaire, BPI can monitor responsiveness to both behavioral and pharmacologic interventions. Another tool, the Multidimensional Affect and Pain Survey (MAPS) was designed to assess three main clusters: somatosensory pain, emotional pain, and well-being. The preoperative use of MAPS has shown to predict postoperative opioid usage. An additional instrument, the Pain Catastrophizing Scale (PCS) is an important predictor of functionality and disability. PCS scores measure catastrophic thinking related to pain and have been shown to correlate significantly with postoperative pain scores, particularly during activity following various types of surgeries. Lastly, it is well known that concomitant psychological factors such as anxiety and depression modulate the experience and perception of pain in the perioperative period and the chronification of acute pain. Consistently, preoperative anxiety as measured by the Hospital Anxiety and Depression Scale (HADS) and State-Trait Anxiety Inventory have also been shown to correlate with the severity of postoperative pain.

An Increased Focus on Perioperative Functional Outcomes

The most valuable assessments in the perioperative period may be those that measure function along with pain. The evaluation of functional limitation during required postoperative physical activities is noted as critical to the recovery trajectory. For example, measuring whether pain limits a patient’s ability to take deep breaths, cough after thoracic surgery, or ambulate after orthopedic surgery may be more important to overall outcomes than simply measuring pain during rest. With a growing focus on function and recovery along with the psychological comorbidities associated with pain, the use of these multidimensional tools has assumed a prominent role in guiding the prediction of pain in the perioperative period.

Table 41.1 is a summary and comparison of common multidimensional pain outcome tools that we recommend to assess and predict pain more fully in perioperative period.

Table 41.2 provides appropriate clinical settings and populations for commonly used psychological assessment tools.

As shown, there are a variety of useful and predictive tools that can be used in the perioperative period with the opportunity to tailor choices to the particular needs of both patient population and health system. We recommend the use of these multidimensional pain assessments in conjunction with functional activity outcomes to assess complicated patients properly in the perioperative setting.

Future Directions: Risk Predictive Tools and Personalized Pain Medicine

A critical aspect in improving perioperative outcomes is the ability to identify patients at risk of delayed recovery or the development of chronic postsurgical pain. This concept is further supported by growing evidence that health-care utilization is reduced with intensive multidisciplinary management programs for patients on chronic opioids, a major risk factor for chronic postsurgical pain. Systematic identification of patients at risk is an important step in the process of focusing resources where needed to improve perioperative care.

Clinical Phenotyping: Cluster Analysis

Beyond the multidimensional assessment instruments discussed, there are several perioperative risk predictive tools that are based on systemic disease severity, as well as organ-specific practice guidelines for surgical patients with cardiac, liver, and renal disease. Research to date has established that chronic opioid use and psychological traits such as anxiety, depression, catastrophizing are associated with an exaggerated burden of chronic postsurgical pain. In particular, the psychological constructs such as catastrophizing and depression appear to be key drivers of pain chronification and disability following surgery. As nearly 50% of chronic pain patients have a coexisting psychological disorder, it is intuitive that preexisting psychological status has a significant impact on the incidence and severity of postsurgical chronic pain.

The importance of accurate diagnosis in painful conditions has been highlighted in recent years. A granular diagnostic approach has been successful in generating therapeutic advances in other medical arenas and is a critical step for the development of personalized pain therapies. Recent progress has been made with improved classifications of peripheral neuropathy and complex regional pain syndrome, and diagnostic improvements are beginning to drive disease-specific therapies founded upon mechanistically defined phenotypes.

It is additionally evident that certain traits and psychological comorbidities cluster together, creating the basis for pain and symptom amplification. Utilizing validated questionnaire instruments and one psychophysical measure (algometry to the trapezius) a methodology has recently been developed that defines a phenotype “cluster” for patients with subsequent chronic pain risk predictive capabilities. Although to date this process has been used more in patients with orofacial pain conditions, the methodologies are not diagnosis or body region specific and promise great utility when applied to the perioperative patient.

Genetic Risks Predictors

Our knowledge of the human genetic code and polymorphisms associated with specific chronic pain syndromes has grown significantly in past decades. In addition to risk prediction, initial hopes were that genetic profiling would develop the foundation for individualized medicine, optimizing therapy for each patient based on his/her specific genomic structure. There are clear associations between inflammation, degenerative conditions, the perception of pain, and individual genetic variability. Furthermore, there is evidence that genetic factors influence the trajectory of pain recovery following surgery. Genetic predictive capacity, especially following high chronic pain risk surgeries such as amputation, thoracotomy, and mastectomy would be of significant value in identifying, stratifying, and treating patients in need of more intensive resources.

Several candidate gene polymorphisms have been linked to pain susceptibility. Notable examples include catechol-O-methyltransferase (COMT) that modifies adrenergic tone and the SCN9A gene that codes for the alpha-subunit of a voltage-gated sodium channel (Nav1.7). SCN9A mutations have been noted in both gain of function disorders such as erythromelalgia and paroxysmal extreme pain disorder as well as loss of function conditions such as congenital insensitivity to pain. Although the implications of the SCN9A gene mutations are dramatic when present, clinical therapeutics developed from candidate gene polymorphisms (SNPs) have remained limited.

In addition to candidate gene analyses, genome-wide association studies (GWAS) have been used to improve the study of the associations between disease and common variants. This approach has led to insight for diseases such as cancer and diabetes, however, GWAS findings generally only account for a fraction of the population attributable risk of complex heritable traits and risk-predictive abilities across the wide spectrum of surgical diseases and procedures remain limited.

The technique of polygenic risk scoring is now being utilized in other medical arenas and is currently being investigated in an effort to strengthen genetic risk predictive tools. These polygenic methodologies, based upon a composite index of intermediate phenotypes and gene polymorphisms, may provide significant advantages in the identification of genetic risk factors and predictive tools for the development of chronic postsurgical pain.

Biomarkers of Risk: Cytokine Profiling

Research increasingly supports the important role of the immune system and cytokine dysregulation in the development and amplification of various chronic pain states. For instance, tumor necrosis factor (TNF) and interleukin-2 (IL-2) are found to be significantly elevated in patients with neuropathic pain conditions such as Complex Regional Pain Syndrome (CRPS). The association between a proinflammatory cytokine state and chronic pain is additionally noted in studies of traumatic injury and osteoarthritis. The growing body of knowledge around cytokine dysregulation and specific disease states played an important role in the development of disease-modifying therapies in conditions such as ankylosing spondylitis, painful neuropathy, and arthritis, and will be critical for novel therapeutic approaches in chronic pain. The important influence of inflammatory cytokines in chronic pain is further supported by research that shows improvements in proinflammatory cytokine profiles that mirror the improvements in depression and fatigue with successful treatment and that demonstrate associations between catastrophizing and pain severity in traumatically injured individuals. Research into these unique biomarkers will continue to elucidate mechanisms and facilitate the development of future risk–predictive tools and tailored therapeutics.

Optimization

Pain outcome assessment and eventually prediction are only one part of the overall story. The next step in truly affecting outcomes is the optimization of modifiable factors related to pain in patients prior to undergoing surgery. It has been established that many economic and health-care utilization outcomes such as increased length of stay, readmissions, hospital costs, and decreased return to work are associated with preoperative opioid use. Related to health outcomes, one high-powered study additionally found that chronic preoperative opioid users were significantly more likely to undergo early total knee arthroplasty revision.

On a patient level, other studies have shown that preoperative opioid use is associated with increased postoperative pain (both short and long term), increased postoperative opioid requirements (both short and long term), higher incidence of complications, and decreased range of motion. One study by Menendez et al. additionally demonstrated that preoperative opioid dependence is significantly associated with increased morbidity and even mortality. With preoperative opioids often leading to higher operative opioid use, there are additional potential comorbidities such as acute tolerance, hyperalgesia, and increased risks of chronic postsurgical pain.

Because of these risks, there is a growing interest in preoperative optimization involving opioid weaning to improve both patient and surgical outcomes along with economic and health-care utilization in these patients. Nguyen et al. showed that patients with a 50% reduction in oral morphine equivalent prior to primary knee or hip arthroplasty had greater improvements to their postoperative WOMAC, SF12 Physical Component, and UCLA activity scores compared with those who did not wean. These patients also had similar and equivalent changes in WOMAC, SF12 Physical Component, SF12 Mental Component, and UCLA activity scores to patients who were opioid naive, suggesting that opioid weaning can be as beneficial as never being exposed to opioids in the first place.

Summary and Recommendations

Optimization of pain outcomes following surgery must take into account multiple factors including the patient’s psychological phenotype, opioid/medication use, and functional status. The development of easily incorporated multidimensional risk predictive tools with germane functional outcome goals will be a critical step to identify and mobilize necessary resources for higher risk patients. As shown in Table 41.3 , we recommend preoperative pain risk assessment and opioid prediction using PCS and MAPS. For those patients at high risk, we recommend delay in surgery until pain psychology assessment and intervention is completed, along with potential opioid weaning. Low-risk patients may continue to surgery as scheduled. Postoperatively, we recommend assessment using BPI and NRS with objective functionality metrics in all patients. In the future, we believe that phenotypic cluster analysis, cytokine profiling, and polygenic risk scoring will play an important role in the prediction of patients at high risk of prolonged recovery; concrete tools are currently in development. Ultimately, utilization of these optimization techniques within the context of a patient-centered system of care will allow the maturation of personalized perioperative pain interventions and improved outcomes.

Table 41.3

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related

Related posts:

Perioperative Cardiac Risk Assessment in Noncardiac Surgery Perioperative Management of Valvular Heart Disease Carotid and Intracranial Surgery Preservation of Fetal Viability During Noncardiac Surgery Major Abdominal Surgery Transitions From Hospital to Home

Stay updated, free articles. Join our Telegram channel

Join