One of the least-appreciated aspects of pain is how it changes over time.  Pain fluctuations can provide surprising insight into the physiological processes that maintain chronic pain. Understanding such processes are key in identifying the interventions that are most likely to help alleviate a person’s pain.

To appreciate the many implications of pain fluctuations over time, there are a handful of pain features that come into play.  One must consider whether pain is constant or intermittent, its degree of variability, whether it is provoked by stimuli/activity or occurs spontaneously, and even the amount of time spent without pain.

Provocation:

Fortunately for pain scientists, pain is the slowest sensory perception we have. Acute nociceptive pain usually begins and ends with the application and removal of a noxious stimulus. However, many nociceptors are sluggish unmyelinated C-fibers that take their sweet time transmitting the nociceptive signal that become heat pain. For example, C-fibers mediate the slow, burning pain that hits a few seconds after you eat a jalapeño and continues to build in delightful waves of heat. Other types of pain may be triggered by an activity, like muscle spasms that kick in after a few minutes of carrying a writhing toddler. Therefore the timing between a triggering event and the onset of pain is a critical piece of information for understanding its underpinnings.

Although chronic pain frequently includes periods of “spontaneous” (unprovoked) pain,  there are often reliable physical triggers that intensify or change the ongoing pain. Notably, careful questioning may reveal different patterns in the quality, time course, and treatment response of spontaneous versus provoked pain, which is suggestive of independent physiological processes at play. Only two chronic pain conditions feature pain that is primarily provoked: use-dependent osteoarthritis pain and pressure hypersensitivity in some with vulvodynia.

Patients have described a staggering range of pain triggers to me, including unique types of sensory input (static versus moving pressure), activity (or lack thereof), weight bearing, sexual activity, stress, digestion, and much more. I find that pain “triggers” are invaluable because they allow you to conduct naturalistic experiments with chronic pain. Waking up with back pain that gradually lessens with within the hour tells you about the impact of mobility on pain. In “functional” pain conditions, pain may ebb and flow as the bladder fills and empties, and in some people voiding may relieve pain or it may rapidly intensify it. Gary Bennett has noted that natural physiological processes could be considered adequate pain “triggers,” which questions our use of the word “spontaneous” in describing chronic pain.

How does pain fluctuate? Pain may slowly increase as the day progresses. Perhaps it occurs in discrete exacerbations (“flares”) over the course of hours, days, or weeks. Perhaps there is a baseline rumbling of pain with seemingly random surges in intensity that seem to have no relationship with readily identifiable triggers.

CPPS_fractal_phoneratig

Take a look at the far left panel. These are the daily pain ratings of research study participants with chronic pelvic pain. Three times per day, they were asked to rate their pain from 0 (no pain) to 10 (worst pain imaginable) on their smartphones. For each person, all pain ratings were lined up in chronological order (pain rating vector) and plotted across time. The resulting line graph represents the fluctuating pain intensity over weeks to months. What was first noticeable to me was the dramatic variation in the shapes of these lines. Even though these individuals all presented with a common pain diagnosis, their pain was almost certainly NOT the same.

Why is this important? Consider the idea of central sensitization. Convincing data suggests it needs to be “re-kindled” to be maintained over long periods of time (it doesn’t  flip on like a light switch, and it doesn’t persist indefinitely unless there is more nociceptive input).  So I would be comfortable speculating that spinal cord central sensitization is NOT playing a role in the pain of those who report stable pain intensity levels. If we were to directly extrapolate from the pain literature, the best candidates for spinally mediated CS are the individuals reporting regular pain flares of moderate intensity. That is an ideal learning signal. With that said, I can’t rule out CS in the others with highly variable pain ratings.

In the middle panel, the fractal dimensions of these factors are plotted across multiple periods of time (the sampling rate).  If a person’s pain were perfectly stable all the time we would see a horizontal line; therefore we also see that even the fractal nature of this pain varies across stretches of time. The dotted horizontal line (y intercept=1.5) is the mathematical threshold for D: participants whose pain ratings have D>1.5 exhibit fractal natures. Fractals are self-similar at multiple levels, and this type of ingrained consistency in pain perception suggests either a pain stimulus that occurs with unnerving regularity, OR a stable cycle of aberrant physiological variability that could only emerge from a reorganized nervous system. I would hypothesize that those individuals would be the most treatment resistant.

On the bottom right panel, the smartphone pain intensity ratings are plotted for an individual who responded to an experimental drug that acts in the central nervous system. Notice that pain is reduced, not fully alleviated. These data suggest that the centrally acting drug addressed mechanisms that were only responsible for 50% of pain, and another culprit continues to generate pain. Two possibilities remain: (1) a second central mechanism continues to maintain this pain or (2) there is continuing peripheral nociceptive input that has not been affected by the centrally acting drug.  I suspect that peripheral, spinal, and brain mechanisms play ongoing roles in chronic pain maintenance, to varying degrees, across time. This hypothesis would account for the incremental drop in mean pain in this particular patient.

1 Comment

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