Anesth Analg 2004;99:477-481
© 2004 International Anesthesia Research Society
doi: 10.1213/01.ANE.0000132696.15310.DD
PAIN MEDICINE
An Analysis of the Relationship Between Activity and Pain in Chronic and Acute Low Back Pain
John J. Liszka-Hackzell, MD PhD*, and
David P. Martin, MD PhD
*Department of Anesthesiology, University of Arizona, Tucson; and
Department of Anesthesiology, Mayo Clinic College of Medicine, Rochester, Minnesota
Address correspondence and reprint requests to John J. Liszka-Hackzell, MD, PhD, Assistant Professor of Anesthesiology, University of Arizona, Department of Anesthesiology, 1501 N. Campbell Ave., Tucson, AZ 85724. Address e-mail to hackzell{at}u.arizona.edu
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Abstract
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We studied the temporal relationship between pain and activity in patients with acute or chronic low back pain. We studied 15 patients with acute low back pain and 15 patients with chronic low back pain over 3 wk. The activity levels were collected automatically using a wrist accelerometer and were sampled every minute. The pain levels were recorded at least every 90 min using a pocket-sized electronic diary. The time series from each patient were then analyzed using the cross-correlation function at various time offsets. We found that during the first 7 days of acute low back pain, there was a significant (P < 0.01) degree of cross-correlation between activity and pain. On average, pain followed activity by approximately 30 min. As these patients improved and reported less pain, the relationship between activity and pain disappeared. There was no such relationship at any point among the patients with chronic low back pain.
IMPLICATIONS: We studied 15 patients with acute low back pain and 15 patients with chronic low back pain and found that there is a relationship between activity and pain in the patients with acute low back pain but not in the patients with chronic low back pain.
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Introduction
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Patients with low back pain are a significant concern for both health care professionals and employers (1). Low back pain is second only to the common cold as a cause of lost workdays among those under age 45. Patients and health care providers tend to believe that there is a relationship between activity and pain. Pain that is worse with motion or activity is often termed mechanical pain. It seems reasonable to assume that increases in activity may cause increases in pain and that this causal relationship would be an established fact. However, this has not been demonstrated in a convincing manner.
Most patients with acute low back pain improve quickly with conservative management; however, some patients experience a relapse or recurrence within a year (2). It is possible that patients with acute low back pain demonstrate a more consistent association between activity and pain. No study has proven such a relationship or compared patients with acute versus chronic low back pain. The objective of this study was to test the hypothesis that activity correlates with acute pain but not chronic pain.
Linton (3) analyzed the relationship between activity and pain in patients with chronic back pain. The results showed that patients reported an association between activity and pain, and patients with more pain tended to make lower ratings of their ability to participate in daily activities. No significant correlation was found between pain and actual activity levels. In that study, pain levels were only recorded twice a day, and activity was recorded on a daily basis using a checklist of different activities that the patients might have participated in during that particular day. The patients were observed between 1 and 3 wk.
Geisser et al. (4) used a time series analysis approach to show significant group relationships between physical activity and pain and self-report of stress and pain, but there was no relationship between electromyographic activity and pain in a group of patients with chronic low back pain. They were also able to find a lagged relationship between physical activity and pain. Further analysis at the individual level indicated stronger relationships between many of the variables. The study was limited to patients with chronic low back pain, and the patients were monitored for only 3 days. The pain and activity levels were recorded by hand and manually entered into a pocket-sized notebook.
There are many challenges to measuring pain and activity in a reliable way (5). Patient-provided information is subject to forgetting and bias. Concurrent (ecological) collection of symptom data requires active patient input and optimal compliance. Several recent technological advances make ecological collection of pain and activity time series more feasible. In this study, we introduce the use of an electronic pain diary used in conjunction with an electronic activity meter. It has not been firmly established that an electronic pain diary reduces the amount of bias, but electronic recording likely minimizes prompting bias because it does not provide tangible feedback of previous entries as can be seen with paper diaries. Furthermore, electronic diaries reduce the amount of recall bias because they decrease the number of pain measurements that patients forget to record (6).
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Methods
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The protocol was reviewed and approved by our IRB. Our goal was to study 15 patients with acute low back pain from both the Urgent Care Center and Emergency Department. Another 15 patients with chronic low back pain (>6 mo) were studied from the Spine Center. The patients were between the ages of 18 and 75 yr, they were all English speaking, able to consent, and able to use the electronic diary (Table 1). Chronic low back pain was defined as a history of low back pain for at least 6 mo. Patients with acute low back pain were enrolled if their pain had an acute onset, they had no previous episode of acute back pain within the last year, and no history of surgery to the spine. All of the patients with acute low back pain had their symptoms <2 wk when they were enrolled in the study. The patients with acute back pain were treated conservatively, whereas the patients with chronic back pain remained on their current medications.
The patients were interviewed by a nurse coordinator to confirm eligibility and to obtain consent. During the initial meeting, the data collection procedure was explained. Each patient was asked to monitor his or her pain and activity levels continuously for 3 wk. Pain levels were recorded between 8 AM and 10 PM using an electronic diary.
The Electronic Symptom Diary is a pager-sized device developed at Mayo Clinic (Rochester, MN) for collecting symptoms from patients over time (Fig. 1). Patients were instructed to quantify their pain using a numerical rating scale and enter the value by pressing one of the buttons labeled from 0 to 10, where 0 is no pain and 10 is the worst possible pain. Their entry was stored in the device along with the corresponding date and time.
Patients were prompted by the diary every 90 min to enter the scheduled measurements, and they could also enter additional measurements at any time. They were encouraged to enter additional measurements as often as they wanted, emphasizing the importance of recording symptoms at their peak and lowest level, as well as intermediate values. At the end of the session, the data were downloaded for analysis.
Activity levels were monitored using an AW-64 Actiwatch (Mini-Mitter Inc, Sunriver, OR). The Actiwatch passively measures activity (7,8). Patients were asked to wear it continuously on their nondominant arm for the duration of the study. The activity was sampled as accumulated counts every minute.
The patients were contacted by telephone on the 2nd and 10th day of the study to provide an opportunity for further patient education regarding the study and study equipment. At the end of the 3-wk data collection, the patients were again telephoned and asked to return the equipment via prepaid mail. Once the patients had returned the diaries and activity watches, the data were recovered and analyzed.
The time series were checked to assure that both pain and activity data were complete. Only the data collected between 8 AM and 10 PM each day were used for further analysis. It is possible to obtain activity level data during the night because the activity monitor records data without active patient input. However, obtaining pain level data requires active patient input and would likely not be possible to obtain during the night. Incomplete time series were discarded. If the activity level time series for a certain day was incomplete, the corresponding pain level time series was also discarded and vice versa. Any patient who had not collected at least 14 complete time series (14 days) was dropped from the study.
The activity level time series were sampled every 1 min. The pain level time series were sampled on average every 90 min. To further analyze the two time series, they had to be converted so that they would appear as if they had both been sampled at the same intervals. In the activity level time series, every tenth measurement was kept, and a new activity level time series was created. This new activity level time series seemed as if it was sampled every 10 min (Fig. 2). The original pain level time series was interpolated using cubic splines (9–12) to seem as if it would have been sampled every 10 min (Fig. 2). Cubic splines are mathematical aids used to draw smooth curves through a set of points. The new time series now had equal length and sampling intervals and consisted of 84 measurements corresponding to each interval between 8 AM and 10 PM.
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Figure 2. An example of the two time series (activity, top; pain, bottom) from a patient with chronic low back pain (left) and a patient with acute low back pain (right). The scale on the x-axis is time (h). The scale of the y-axis is activity counts (activity) and pain levels (0–10). The two time series on the left show no cross-correlation, whereas the two time series on the right give a cross-correlation coefficient of 0.42 at a time lag of 0.
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The next step in the data analysis was to examine the time series for immediate and offset relationships using the cross-correlation function (13–15). We used the SPSS 7.5 software package (15) (SPSS, Chicago, IL) for this analysis. The first and last seven pairs of the time series (8 AM to 10 PM) from each patient were analyzed for cross-correlation with offset relationships of up to ±60 min. The null hypothesis was tested by a single sample t-test against an expected cross-correlation of zero. The level of significance for cross-correlation was set at a projected value of P < 0.01. The analysis of the cross-correlation between the various time series was performed using SPSS 7.5. This software package was also used for the t-tests.
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Results
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The average age of the patients with acute back pain was 46 ± 10.6 yr and 51 ± 10.2 yr for the patients with chronic back pain. The patients with acute back pain consisted of nine men and six women, whereas the patients with chronic back pain were eight men and seven women. Of the 41 patients who were initially enrolled, 30 patients completed the study (acute back pain, 15 of 22; chronic back pain, 15 of 19). The number of complete time series (activity and pain) was on average 16 of 21 in the patients with acute back pain and 18 of 21 in the patients with chronic back pain. The main reason why patients did not complete the study was that it caused inconvenience by requiring too much time and patient effort. Patients found using the electronic diary daily over 3 wk to be demanding at times because it requires active patient input. The activity monitor was considered easier to use because it is a passive device.
The pain levels remained unchanged during the first and last seven time series in the patients with chronic back pain. We found a significant (P < 0.01) decrease in pain levels in patients with acute back pain when comparing the mean pain levels for each individual patient for the first and last seven time series using a paired sample t-test. The pattern of activity levels indicated that they remained unchanged in patients with chronic back pain, whereas they went up for patients with acute low back pain.
Most of the patients with acute low back pain showed significant cross-correlation during the first seven time series (Table 2). None of the patients with chronic low back pain showed significant cross-correlation at any time during the first or last seven time series obtained during the 3-wk study period.
Significant cross-correlation was obtained at various time offsets between 0 and +60 min. A time offset of 0 means that an increase in activity was immediately followed by an increase in pain levels. A time lag of +60 min indicates that an increase in activity is followed by an increase in pain levels after 60 min. None of the patients with acute back pain showed a significant cross-correlation during the last seven time series.
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Discussion
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Our study compared pain and activity using new data collection methods in patients with both acute and chronic back pain. Pain is inherently subjective, and its measurement may be difficult. In this study, we used an electronic diary to collect the pain levels. The electronic diary has several advantages. It prompts the patients to enter measurements at preselected intervals. It also reduces the risk that previous measurements will affect subsequent measurements because they are stored in electronic format and will not be available to the patient once they have been entered. The compact size and easy-to-use interface facilitates patient compliance.
Activity was collected using an automatic computerized activity monitor (Actiwatch). This device continually records activity (nondominant arm). It does not require active patient input. Studies have indicated (16) that the activity monitor does not necessarily have to be placed on the nondominant arm as long as the same site is used consistently throughout the study. These types of data collection differed from other studies because we recorded data more often and with devices that facilitated patient compliance. Also, this study investigated patients with both acute and chronic back pain. Assessing pain more frequently increases the reliability and validity of the measurements (17).
We made the assumption that an interpolation of the pain level time series would reflect the change in pain levels outside the collected measurements. Collection of pain levels requires the patient to manually enter a measurement into the electronic diary when prompted. During preliminary studies, we found that prompting the patients more often than every 90 min over 3 weeks would negatively affect compliance with the electronic diary. A spline is a piecewise kth degree polynomial that is smoothly connected at each data point. From clinical experience, we feel that an interpolation with cubic splines most accurately reflects this process. Cubic splines have been used for interpolation in a variety of applications (11,12). Patients were allowed to enter pain level measurements in addition to the scheduled ones. However, additional measurements only contributed an additional 10%–20% for each measurement period and patient. In the patients with acute low back pain, any additional pain levels entered outside the scheduled measurements may not have been accurately reflected by interpolation with cubic splines. However, because the number of additional measurements was small and inconsistent, cubic splines may still have been an appropriate interpolation technique.
We were able to obtain significant cross-correlations for most of the patients with acute low back pain during the first seven days. In many of these patients, an increase in activity was followed by an increase in pain. In some of the patients with acute back pain, there was an immediate relationship between activity and pain. After seven days, it was not possible to show a significant cross-correlation in any of the patients with acute low back pain. As these patients had improvement of their pain levels, it is likely that the initial relationship disappeared.
In 5 of the 15 patients with acute low back pain, we were unable to show a significant relationship. These patients all had a quick recovery or had low and rapidly declining pain levels already at the beginning of the data collection period. Because we have investigated cross-correlation during the first seven and last seven days and then performed a t-test over the seven measurement periods, it seems that high enough cross-correlation coefficients were not obtained to provide significance in these cases. Demographic data (age and sex) among the patients with acute back pain do not seem to be related to the presence or absence of significant cross-correlation. With the limited number of patients, we can only explain this by individual differences. Interpatient variability could result from underlying pathology, differing neurophysiology of pain (sensitization or windup), or differing psychosocial or cultural factors that affect expression of pain.
Other studies (18–20) suggest that restricting activity during an episode of acute back pain does not improve outcome. Our findings could thus indicate that good pain control with oral analgesics may be beneficial to improve pain control and facilitate early activity because there seems to be a relationship between activity and pain. The patients with chronic low back pain did not show any relationship between activity and pain at any point. Patients with chronic back pain often assume that activity and pain may be linked. This study may indicate that restricting activity does not contribute to improved pain control and that behavioral approaches may be of benefit.
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Acknowledgments
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Supported, in part, by a grant from Mayo Foundation, Rochester, MN.
The authors thank Diane Maxson, RN, Greg Wilson, and Laurie Meade, RN, for their help in recruiting patients and collecting data.
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References
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Accepted for publication March 5, 2004.
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Abstract
Introduction
