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Correlates of Postoperative Pain and Intravenous Patient-Controlled Analgesia Use in Younger and Older Surgical Patients

Lucia Gagliese PhD, Lynn R. Gauthier MA, Alison K. Macpherson PhD, Melissa Jovellanos MSc, Vincent W. S. Chan MD
DOI: http://dx.doi.org/10.1111/j.1526-4637.2008.00426.x 299-314 First published online: 1 April 2008

ABSTRACT

Objective. Age-related patterns in postoperative pain are unclear with reports of no age differences and less pain with age. The objective of this study was to identify correlates of pain and intravenous patient-controlled analgesia (IV PCA) morphine use in younger and older patients.

Design. 24 hours after surgery, patients completed measures of pain intensity and pain qualities. Surgical factors, IV PCA morphine intake, anticholinergic load, polypharmacy, physical status, previous chronic and postoperative pain, and PCA experience were measured.

Setting. Two academic general hospitals.

Patients. Two hundred forty-six general surgery patients ranging in age from 18 to 82 years old.

Results. In older patients, higher pain scores were associated with female gender and previous experience of postoperative PCA. In younger patients, higher pain scores were associated with female gender, previous surgery without PCA, and greater morphine intake. Lower pain was associated with being male, and no previous surgical experience in older patients, and lower morphine intake in younger patients. Morphine intake was higher in patients who were younger, had better physical status, higher anticholinergic load, and experience with PCA. Among younger patients, increased morphine use also was associated with surgical procedure and duration. Higher pain scores were more strongly associated with morphine use among younger than older patients.

Conclusions. The correlates of postoperative pain and morphine use may differ with age, and the same factor may have different effects across age groups. Research is needed into the mechanisms of these age-specific profiles.

  • Postoperative Pain
  • Aging
  • Elderly
  • McGill Pain Questionnaire
  • Patient-Controlled Analgesia
  • Pain History

Introduction

Despite increasing research and clinical attention, many adult surgical patients continue to experience moderate to severe pain [1]. This can have serious consequences including respiratory, immune, and cardiac dysfunction [2], delirium [3], and the development of chronic postsurgical pain [4]. Each of these may be more dire for older patients [5]. As the population ages and surgical and anesthetic protocols become safer, the number of older people undergoing surgery will grow [6]. In order to provide effective pain control across the adult lifespan, it is important to identify correlates of postoperative pain that may vary with age.

The mechanisms of acute postoperative pain are not well understood. While there is a strong relationship with extent of surgical trauma, patients who undergo the same procedure exhibit significant variability in pain. The most consistently identified correlates of pain intensity 24 hours following surgery include surgical procedure, female gender, and preoperative pain [7–9].

Age-related patterns in postoperative pain remain unclear. Several studies have found that older patients report lower pain intensity and obtain lower McGill Pain Questionnaire (MPQ) scores than younger patients [7,10–13], while others have not found age differences [9,14–17]. While these discrepant results may be related to cross-study methodological variability, it is also possible that they reflect the influence of unmeasured age-related factors. For instance, comorbid conditions, polypharmacy, and previous pain experience may be more relevant for one age group than the other. To date, studies examining the relationship between these factors and postoperative pain in younger and older patients are not available.

Age-related patterns in postoperative analgesic requirements are more consistent. Older adults self-administer less morphine via intravenous patient-controlled analgesia (IV PCA) than younger adults [12,14,18–23]. In this modality, postoperative patients are connected to a PCA pump, programmed to deliver an IV dose of morphine when a button is pressed. As a result, patients manage their analgesic use within dosing parameters set to minimize the risk of adverse effects and overdose [24]. Age differences in IV PCA morphine use may be related to changes in metabolism and clearance of morphine with age [25,26]. Although biopsychosocial and surgical variables associated with IV PCA use have been identified [18,24,27–29], the consistency of these associations in patients of different ages has not been reported.

Older patients are more likely than younger patients to have impaired physical status [30,31]. The most commonly used preoperative index of physical status is the American Society of Anesthesiologists (ASA) Class [32]. ASA I is assigned to surgical patients without systemic disease or physical impairment. ASA II refers to patients with mild, usually managed, systemic disease with minimal physical impairment. ASA III denotes significant illness that interferes with normal activity, and ASA IV refers to patients with severe, life-threatening conditions. More intense postoperative pain has been associated with both higher [8] and lower [33] ASA status. IV PCA opioid use may be higher among ASA I or II patients than ASA III or IV [19]. Older general surgery patients are more likely than younger patients to receive higher ASA scores [14].

Advancing age and impaired physical status are associated with polypharmacy, or use of multiple medications, in both community [34] and surgical populations [35]. Up to 50% of patients may be taking medicine unrelated to the surgical indication at the time of admission [35]. Polypharmacy increases the risk of drug interactions and poor surgical outcomes [35,36]. Interestingly, the number of medications taken by surgical patients appears to be high even among younger patients. For instance, Davis and Heavner [36] reported that approximately 20% of surgical patients under 60 years old were taking six or more prescription drugs. As such, polypharmacy may also be a potential risk factor for younger patients.

Adverse outcomes have been associated specifically with the use of drugs having anticholinergic properties. Among community-dwelling older people, anticholinergic load has been related to impaired cognitive and physical function, increased risk of falls, and reduced performance of activities of daily living [37,38]. While younger people may also experience anticholinergic side effects [39], the role of these drugs in daily function and surgical outcome has not been well established. Among hospitalized elderly patients, anticholinergic load is an important factor in the development of delirium [40,41].

Older patients may have more lifetime experience with surgery [14] and pain [42] than younger people. This may impact on both current pain levels and analgesic use as a result of processes such as adaptation, response shifts, and neuroplasticity. Previous pain and injury have been associated with altered threshold and tolerance for experimentally applied pain [43,44]. Interestingly, Bachiocco et al. [45] found that current postoperative pain was associated with previous medical but not surgical pain. These studies have not considered the role of advancing age that may be associated with response shifts due to changing health status, expectations of normal aging, and increased lifetime pain [46,47]. Postoperative pain within the context of ongoing chronic pain is extremely complex, and these patients may have unique pain control needs [48,49]. Therefore, in order to assess the role of chronic pain history, patients who reported ongoing pain of at least 3 months duration at some point in the past but who had been pain-free for at least 6 months prior to surgery were enrolled.

The relationship of physical status, polypharmacy, anticholinergic load, and pain experience to postoperative pain and analgesic requirements among cognitively intact, younger, and older surgical patients has not been reported. The objective of the present study was to determine demographic, surgical, and biomedical correlates of postoperative pain and IV PCA morphine intake in a sample of younger (<60 years old) and older (≥60 years old) patients matched for gender and surgical procedure. These data would not only be heuristic for the study of pain and analgesia across age groups; but also would contribute to the clinical identification of younger and older at-risk patients.

Methods

Subjects

Two hundred and forty-six patients were drawn from a larger consecutive sample (N = 504) of patients receiving IV PCA morphine following general surgery at the Toronto General and Mount Sinai Hospitals in Toronto, Ontario. For the larger sample, patients were excluded if they were cognitively impaired, unable to read and speak English sufficiently to complete questionnaires and provide informed consent, had more than one surgical incision site, received epidural or regional analgesia, weighed more than 100 kg, were ASA IV, reported or had documented in their charts chronic pain within the 6 months prior to surgery, or had chronic opioid use or substance abuse. Patients were divided into younger (<60 years old) and older (≥60 years old) age groups and matched on gender and surgical procedure. Characteristics of this matched sample have been reported previously [13]. The sample size was chosen to ensure adequate numbers of older patients and sufficient power for detailed psychometric analyses of the MPQ (to be reported separately).

Variables and Measures

The MPQ [50] is a self-report measure of the multidimensional qualities of pain. It is comprised of 78 pain adjectives grouped into 20 categories. Adjectives in each group are presented in ascending order of intensity. Patients selected those words that most closely reflected their feelings and sensations of pain at rest at the time of testing. The rank values of the words chosen were summed to obtain a total pain rating index score (MPQ). The MPQ has been validated for younger and older patients with pain [12,51,52].

The numeric rating scale (NRS) is a self-report measure of pain intensity made up of a line marked with the numbers 0 to 10 where 0 is “no pain” and 10 is “worst pain imaginable.” Patients circled the number that best represented their current pain intensity at rest. The NRS is widely used and is valid and reliable in both younger and older surgical patients [13,53].

The anticholinergic drug scale (ADS) [54] is an index of anticholinergic burden that is appropriate for clinical use. The anticholinergic activity of individual drugs is rated using the following scale: 0 (no anticholinergic properties), 1 (potentially anticholinergic), 2 (anticholinergic adverse events have been noted), and 3 (marked anticholinergic activity; see Carnahan et al. [55] for a complete listing of drugs). The total ADS score is the sum of all maintenance, preoperative, intraoperative, and postoperative medications. ADS scores have been associated with serum anticholinergic activity in elderly women, an indication of criterion validity [55]. ADS scores were derived and verified by two researchers (Lynn R. Gauthier and Melissa Jovellanos) to enhance reliability.

Procedures

Prior to surgery, the Acute Pain Service evaluated all patients in order to develop a postoperative pain control plan. Patients were ineligible for IV PCA morphine if they were cognitively impaired, had drug dependence, either historically or currently, or were unable to understand the instructions for PCA use. All patients had surgery under general anesthesia with perioperative care according to the hospitals' standard of care guidelines. In the post-anesthetic care unit, they were connected to a PCA pump (Abbott Life Care Infuser, Chicago, IL) set to deliver a 1.0–2.0-mg IV bolus dose of morphine with a 5–7-minute lock out, a 40 mg morphine maximum dose in any 4-hour period, and no continuous background infusion.

At 24 ± 2 hours postoperatively, clinical staff were asked to identify patients who met the eligibility criteria. These patients were approached, told about the study, and written informed consent was obtained. Cognitive status was assessed by screening for orientation to time, place, and person using items from the Mini-Mental State Exam [56]. This subset of items has been shown to be an effective, brief, bedside screen for delirium [57]. Any patient who was not fully oriented was withdrawn from the study. Patients were interviewed regarding their medical and pain history. They were asked about previous surgeries and the use of PCA (either IV or epidural). The research assistant then administered several pain measures, including the MPQ and NRS (for further details see [13]). For each scale, patients rated their current pain at rest. Order of scale completion was counterbalanced to minimize order effects.

Additional demographic, medical, and surgical information was extracted from the medical chart. The PCA machine recorded all patient requests for analgesia (total demand), amount of morphine administered (mg), and number of successful patient demands. To obtain a value for unmet demands, the total number of successful patient demands was subtracted from the patients' total demand. Cumulative morphine intake was derived by summing hourly morphine intake over 24 hours.

Patients were categorized based on both experience of surgery and PCA. Three groups were formed: patients who reported no previous surgeries; previous surgery without PCA (surgery – PCA); and previous surgery with PCA postoperatively (surgery + PCA). The Research Ethics Boards of the University Health Network, Mount Sinai Hospital, and York University approved the study protocol.

Data Analyses

Fourteen candidate correlates of NRS and MPQ scores and morphine intake were examined separately in the younger (<60 years old) and older (≥60 years old) groups: demographic (age in years, gender, education, ethnicity); biomedical (ASA class, body mass index [BMI], history of chronic pain, ADS score, polypharmacy, surgical experience ± PCA); and surgical variables (procedure, blood loss in milliliters, and duration in minutes). Frequencies, proportions, means, and standard deviations were calculated for these variables, as appropriate, to characterize the younger and older patients. Education level, ethnicity, and surgical procedure were each collapsed to generate more stable distributions. Similar descriptive statistics were calculated for the outcome variables NRS, MPQ, and morphine use.

Age differences were tested using chi-square (χ2) tests for categorical variables and independent samples t-tests for continuous variables. Multiple dichotomous variables for all categorical variables were created. Several steps were taken to calculate dose/demand ratio: 1) total morphine intake (mg) over 24 hours was converted to a successful demand variable by dividing total intake (mg) by bolus dose (mg); and 2) successful demands were divided by total demands. To determine unmet demand/demand ratio, total unmet demands were divided by total demand. Independent samples t-tests were used to assess age group differences in the ratios.

Several steps were taken to identify correlates of the outcome variables. First, bivariate tests of association were calculated for the total sample between the candidate and outcome variables to determine which should be retained for entry into the final multivariate models. Those that reached significance at or below 0.25 were considered for inclusion [58]. Backward multivariate linear regression was then used to identify significant correlates of NRS, MPQ, and IV PCA morphine intake separately for each age group. Criteria for removal of independent variables from each model was P ≥ 0.15. R2 values were examined to determine the variance explained by each model. The power for each final backward linear regression model (probability that R2 will be significantly different from zero) was calculated using the steps provided by Cohen et al. [59]. Power for the MPQ model in older patients was >0.90. The power for all other regression models was >0.99.

Once the correlates retained in the final regression models were identified in each age group, the interaction of these correlates with age on each outcome (NRS, MPQ, and IV PCA morphine use) was assessed. A series of factorial anovas was carried out, with age and the correlate as the between subjects' factors and the outcome as the dependent variable. For correlates that were continuous variables, a median split (based on the median value of the full sample) was performed to separate patients into higher and lower groups. This strategy resulted in 26 comparisons (NRS: three correlates × two age groups; MPQ: four correlates × two age groups; morphine intake: seven correlates × two age groups). This may have been associated with an elevated probability of Type 1 error. However, it was decided not to adopt a more conservative level of significance in order to maximize the hypothesis-generating potential of the analyses. All data were analyzed using SPSS version 15.0 for Windows (SPSS Inc., Chicago, IL).

Results

Patient Characteristics

Five hundred fifty-one patients gave consent to participate in the study. Forty-seven (8.5%) were subsequently excluded when further investigation revealed they had not met the inclusion/exclusion criteria. The most common reasons were multiple incision sites (N = 10) more than 26 hours since the end of surgery (N = 10), and linguistic barriers (N = 6). Only one patient was withdrawn due to disorientation to place and time. This patient was oriented to person only. That is, he could not accurately state the time or his location but was able to give his name. Patients who were withdrawn did not differ from those who completed the study. The study was completed by 504 patients with average age of 52.7 ± 14.9 years (range: 18–86 years).

Two age groups, matched on surgical procedure and gender, were formed from only those who were able to complete all of the pain measures included in the original study [13] (N = 373). For a detailed analysis of differences between this subset of patients and those who were unable to complete the pain measures, please see Gagliese et al. [13], but briefly, the patients who made errors were older than those who did not [13]. The lower age cutoff for the older group was 60 years. This cutoff was chosen to maximize the number of older patients and is consistent with other studies of postoperative pain and aging [12]. Because there were fewer older than younger patients, each older patient was matched to one younger patient. When more than one younger patient met the matching criteria, the patient was chosen randomly.

Characteristics of the matched age groups are shown in Table 1. The average age of the 246 patients was 54.85 ± 16.09 years (range 18–82 years). The age groups did not differ on education, with most completing at least high school (89%). The majority of patients were white (85%), with a larger proportion of white patients in the older than the younger group (P ≤ 0.04).

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Table 1

Demographic, surgical, biomedical, pain, and PCA use variables for younger and older patients

Younger (N = 123)Older (N = 123)P
Demographic variables
  Age42.00 ± 12.3267.75 ± 5.72
  Sex (% female)60 (48.8)60 (48.8)
  Ethnicity (% Caucasian)99 (80.4)110 (91.7)0.04
  Education level0.10
   Elementary school5 (4.1)18 (15.0)
   High school57 (46.7)47 (39.2)
   College/University52 (42.3)49 (39.8)
   Graduate/professional8 (6.6)6 (5.0)
   Missing1 (0.8)3 (2.4)
Surgical variables
  Procedure
   Gynecological/urological77 (62.6)77 (62.6)
   Gastrointestinal26 (21.1)26 (21.1)
   Orthopedic20 (16.3)20 (16.3)
  Blood loss (mL)619.49 ± 725.00726.16 ± 883.000.31
  Surgical duration (minute)208.46 ± 81.69198.39 ± 69.520.31
Biomedical variables
  BMI26.0 ± 5.827.2 ± 4.80.07
  ASA class0.001
   ASA I45 (36.6)12 (9.8)
   ASA II59 (48.0)81 (65.9)
   ASA III13 (10.6)25 (20.3)
  History of chronic pain36 (29.3)36 (29.3)1.00
  ADS score4.66 ± 2.164.65 ± 2.300.98
  Polypharmacy1.61 ± 1.803.28 ± 2.530.001
  Previous experience0.07
   No previous surgical or PCA use experience22 (17.9)11 (8.9)
  Previous surgical experience only75 (61.0)90 (73.2)
  Previous surgical and PCA use experience26 (21.1)22 (17.9)
Pain variables
  NRS3.75 ± 2.003.33 ± 2.220.13
  MPQ-total16.49 ± 12.7111.63 ± 10.060.001
IV PCA use
  Morphine intake (mg)58.90 ± 38.7138.23 ± 24.890.007
1.68 ± 0.30*1.49 ± 0.31*0.001
  • * Log scale.

  • BMI = body mass index; ASA = American Society of Anesthesiology; ADS = anticholinergic drug scale; PCA = patient-controlled analgesia; IV PCA = intravenous patient-controlled analgesia; NRS = numeric rating scale; MPQ = McGill Pain Questionnaire.

  • Data are mean ± SD or N (%).

As expected, a greater proportion of older than younger patients were classified as ASA II or III, indicating poorer physical status (P ≤ 0.001). Older patients were taking twice as many medications as younger patients (P ≤ 0.001). Nonetheless, ADS scores did not differ between the age groups, most likely due to the influence of perioperative drug administration. ADS and polypharmacy scores were moderately correlated (r = 0.34, P ≤ 0.01) suggesting that these scales measure slightly overlapping but different constructs.

Approximately 30% of the patients in each age group reported ongoing pain of at least 3 months' duration at a previous time in their lives. Most of the patients in both age groups had previous surgical experience, with older people slightly more likely than younger people to have had previous surgery (82% of younger vs 91% of older patients; P ≤ 0.04). This difference was eliminated when patients were classified based on previous PCA experience.

The age groups did not differ on any of the surgical variables suggesting the matching procedure was successful. Consistent with acute pain management guidelines [60], the PCA machines were programmed to give a smaller dose of morphine per demand to older (1.06 ± 0.18 mg) than younger (1.16 ± 0.35 mg) patients (P ≤ 0.004).

Correlates of Pain Intensity

As reported previously [13], there were no age differences in pain intensity (see Table 1). Table 2 shows the results of the multivariate linear regression models for NRS for younger and older patients. Variables considered for inclusion in this model based on P ≤ 0.25 were age (r = −0.17, P ≤ 0.007), sex (P ≤ 0.001), ASA I (P ≤ 0.25), ADS score (r = 0.16, P ≤ 0.012), polypharmacy (r = 0.14, P ≤ 0.024), history of chronic pain (P ≤ 0.002), previous surgery ± PCA (P ≤ 0.104), surgical procedure (P ≤ 0.004), and morphine intake (r = 0.33, P ≤ 0.001).

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Table 2

Multivariate backward linear regression analysis of pain intensity (NRS) in younger and older patients

Younger (N = 123)Older (N = 123)
Crude Beta*SE (P≤)BetaSE (P≤)Crude Beta*SE (P≤)BetaSE (P≤)
Age−0.060.01 (0.001)−0.030.02 (0.047)0.070.04 (0.061)0.060.04 (0.090)
Female sex1.090.35 (0.002)0.870.34 (0.011)1.040.39 (0.009)0.760.39 (0.055)
Previous surgical experience without PCA−0.460.45 (0.315)1.000.66 (0.131)
Previous surgical and PCA experience−0.270.44 (0.550)−0.720.40 (0.076)1.360.51 (0.008)1.990.77 (0.011)
Gastrointestinal surgery§0.710.51 (0.166)0.710.48 (0.144)
IV PCA morphine intake (mg)2.620.57 (0.001)1.950.62 (0.002)1.810.64 (0.005)1.690.63 (0.008)
R2 = 0.26, F(4) = 9.92, P ≤ 0.001R2 = 0.20, F(6) = 4.82, P ≤ 0.001
  • * Unadjusted beta;

  • unstandardized beta;

  • reference group is no previous surgical or PCA experience;

  • § reference group is orthopedic surgery.

  • NRS = numeric rating scale; SE = standard error; PCA = patient-controlled analgesia; IV PCA = intravenous patient-controlled analgesia.

In younger patients, crude analyses revealed that younger age, female sex, and morphine intake were significantly associated with NRS. Although not statistically significant, previous surgery + PCA was also associated with NRS. In the final multivariate model, younger age, female sex, and morphine intake remained significant. Previous surgery + PCA was retained but was nonsignificant. This model was significant (P ≤ 0.001) and accounted for 26% of the variance in pain intensity for younger patients (R2 = 0.26).

For older surgical patients, crude analyses showed that female sex, previous surgery + PCA, and morphine intake were significantly associated with NRS. Age, previous surgery − PCA, and gastrointestinal surgery were correlated with NRS, but these associations were nonsignificant. In the multivariate analysis, only previous surgery + PCA and morphine intake remained statistically significant. Although not statistically significant, age, female sex, previous surgery − PCA, and gastrointestinal surgery were retained in the model. This model was significant (P ≤ 0.001) and accounted for 20% of the variance in pain intensity for older patients (R2 = 0.20).

The only significant interaction between age group and sex, morphine intake, surgical experience, and procedure was found for previous surgical experience (Table 3). Specifically, in the younger group, the highest NRS scores were obtained by those who had previous surgery − PCA, whereas those who did not have surgical experience and who had surgery + PCA obtained similar pain scores. By contrast, in the older group, previous surgical experience was associated with higher pain scores that were highest in those who had had PCA previously. Older people without surgical experience reported the lowest NRS scores. There was a trend toward significance for the interaction of morphine consumption and age group (P ≤ 0.10). This suggested that younger patients who used more morphine reported higher NRS scores than younger patients who used less morphine. In addition, younger patients who used less morphine had lower pain scores than older patients. Finally, women reported higher NRS scores than men.

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Table 3

The main and interaction effects of age and correlates on pain intensity (NRS)

Younger (N = 123) (Mean ± SD)Older (N = 123) (Mean ± SD)Total (N = 246) (Mean ± SD)Main Effect PInteraction Effect P
Sex
  Females4.34 ± 1.943.87 ± 2.394.09 ± 2.190.00010.93
  Males3.25 ± 1.932.83 ± 1.933.04 ± 1.94
Previous surgical and/or PCA experience
  Group 1*3.36 ± 2.222.09 ± 1.642.94 ± 2.110.040.03
  Group 23.93 ± 1.943.21 ± 2.103.54 ± 2.05
  Group 33.54 ± 2.004.45 ± 2.563.96 ± 2.30
IV PCA morphine intake
  ≤40.8 mg2.76 ± 1.583.05 ± 2.142.94 ± 1.940.00010.11
  >40.8 mg4.36 ± 2.013.78 ± 2.354.14 ± 2.15
  • * No previous surgical or PCA experience;

  • previous surgical experience without PCA;

  • previous surgical and PCA experience.

  • NRS = numeric rating scale; PCA = patient-controlled analgesia; IV PCA = intravenous patient-controlled analgesia.

Correlates of Pain Quality

Older patients had significantly lower MPQ scores than younger patients. Multivariate linear regression models for younger and older patients are shown in Table 4. Variables considered for inclusion in this model based on P ≤ 0.25 were age (r = −0.27, P ≤ 0.001), sex (P ≤ 0.002), BMI (r = 0.16, P ≤ 0.014), ASA I (P ≤ 0.164), ADS score (r = 0.18, P ≤ 0.005), history of chronic pain (P ≤ 0.005), previous surgery ± PCA (P ≤ 0.004), surgical procedure (P ≤ 0.001), blood loss (r = −0.11, P ≤ 0.105), and morphine intake (r = 0.33, P ≤ 0.001).

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Table 4

Multivariate backward linear regression analysis of pain quality scores (MPQ) in younger and older patients

Younger (N = 123)Older (N = 123)
Crude Beta*SE (P≤)BetaSE (P≤)Crude Beta*SE (P≤)BetaSE (P≤)
Age−0.250.09 (0.007)−0.160.10 (0.103)
BMI0.510.19 (0.009)0.770.18 (0.001)
Previous surgical and PCA experience5.532.77 (0.048)8.622.51 (0.001)
Gynecological/Urological surgery§−4.951.85 (0.009)−4.551.95 (0.021)
IV PCA morphine intake (mg)14.823.67 (0.001)11.183.81 (0.004)7.252.91 (0.014)6.942.93 (0.020)
R2 = 0.31, F(4) = 11.83, P ≤ 0.001R2 = 0.10, F(2) = 6.23, P ≤ 0.003
  • * Unadjusted beta;

  • unstandardized beta;

  • reference group is no previous surgical or PCA experience;

  • § reference group is orthopedic surgery.

  • MPQ = McGill Pain Questionnaire; SE = standard error; BMI = body mass index; PCA = patient-controlled analgesia; IV PCA = intravenous patient-controlled analgesia.

In younger patients, crude analyses indicated that age, BMI, previous surgery + PCA, and morphine intake were significantly correlated with MPQ scores. Once entered into the multivariate model, BMI, previous surgery + PCA, and morphine intake remained significant. Age was retained, but it was nonsignificant. This model was significant (P ≤ 0.001) and accounted for 31% of the variance in MPQ scores (R2 = 0.31).

For older patients, crude analyses revealed that only gynecological/urological surgery and morphine intake were significantly associated with MPQ scores. Both of these variables were retained in the multivariate analysis. This model was significant (P ≤ 0.003) and accounted for 10% of the variance in MPQ scores (R2 = 0.10).

None of the interactions between age group and the correlates retained in the models (BMI, previous surgical experience, morphine intake, and surgical procedure) was significant (Table 5). There were main effects of surgical procedure, BMI, and morphine use. MPQ scores were higher among orthopedic surgery patients than both gynecological/urological and gastrointestinal surgery groups. Those with higher BMI had greater MPQ scores than those with lower BMI. Similarly, those who used more morphine had higher MPQ scores than those who used less.

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Table 5

Main and interaction effects of age and correlates on pain quality (MPQ)

Younger (N = 123) (Mean ± SD)Older (N = 123) (Mean ± SD)Total (N = 246) (Mean ± SD)Main Effect PInteraction Effect P
BMI
  ≤26.113.90 ± 9.7910.80 ± 8.5012.56 ± 9.340.020.22
  >26.119.10 ± 14.6612.41 ± 11.2415.25 ± 13.17
Previous surgical and/or PCA experience
  Group 1*10.95 ± 8.759.91 ± 8.0310.61 ± 8.400.0050.56
  Group 216.60 ± 12.1410.72 ± 9.3613.41 ± 11.01
  Group 320.85 ± 15.5116.18 ± 12.5718.71 ± 14.29
Surgical procedure
  Gynecological/urological14.58 ± 12.069.85 ± 8.7312.21 ± 10.760.00010.78
  Gastrointestinal16.64 ± 11.6212.96 ± 9.7314.88 ± 10.80
  Orthopedic23.75 ±14.3616.81 ± 13.1120.20 ± 14.01
IV PCA morphine intake
  ≤40.8 mg10.87 ± 9.449.47 ± 6.9710.01 ± 8.000.00010.26
  >40.8 mg19.85 ± 13.2715.17 ± 13.1418.06 ± 13.36
  • * No previous surgical or PCA experience;

  • previous surgical experience only;

  • previous surgical and PCA experience.

  • MPQ = MPQ = McGill Pain Questionnaire; BMI = body mass index; IV PCA = intravenous patient-controlled analgesia; PCA = patient-controlled analgesia.

Correlates of Cumulative IV PCA Morphine Intake

The distribution of the morphine intake variable was skewed and a log transformation was performed. Older patients used significantly less morphine than younger patients (P ≤ 0.001). There were no age differences in achieving a successful dose. Specifically, the dose/demand ratio (younger: 0.80 ± 0.31, older: 0.85 ± 0.36; P > 0.62) and the unmet demand/demand ratio (younger: 0.30 ± 0.23, older: 0.29 ± 0.3; P > 0.27) were similar in each group.

Table 6 shows the multivariate linear regression models for morphine intake for younger and older patients. All beta coefficients have been exponentiated. Variables that were considered for inclusion based on P ≤ 0.25 were age (r = −0.45, P ≤ 0.001), sex (P ≤ 0.24), ASA II (P ≤ 0.13), ASA III (P ≤ 0.13), ADS (r = 0.22, P ≤ 0.001), history of chronic pain (P ≤ 0.03), previous surgery ± PCA (P ≤ 0.06), surgical procedure (P ≤ 0.001), surgical duration (r = 0.12, P ≤ 0.06), NRS (r = 0.33, P ≤ 0.001), and MPQ (r = 0.33, P ≤ 0.001).

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Table 6

Multivariate backward linear regression analysis of IV PCA morphine intake (mg) in younger and older patients

Younger (N = 123)Older (N = 123)
Crude Beta*SE (P≤)BetaSE (P≤)Crude Beta*SE (P≤)BetaSE (P≤)
Age−0.971.22 (0.001)−0.981.00 (0.001)−0.971.01 (0.02)−0.961.01 (0.001)
ASA II1.441.14 (0.008)1.921.20 (0.001)
ASA III−0.861.18 (0.380)1.471.24 (0.080)
ADS1.121.03 (0.001)1.071.02 (0.004)1.041.03 (0.20)1.051.02 (0.057)
Previous surgical and PCA experience§1.341.18 (0.09)1.351.17 (0.065)
Gynecological/urological surgery−0.561.13 (0.001)−0.651.10 (0.001)
Surgical duration (minutes)1.001.00 (0.04)1.001.00 (0.001)
NRS1.081.03 (0.005)1.071.03 (0.016)
MPQ1.021.00 (0.001)1.011.00 (0.09)
R2 = 0.47, F(5) = 19.81, P ≤ 0.001R2 = 0.26, F(6) = 6.33, P ≤ 0.001
  • * Unadjusted beta;

  • unstandardized beta (all beta coefficients and standard errors in table have been exponentiated);

  • reference group is ASA I;

  • § reference group is no previous surgical or PCA experience;

  • reference group is orthopedic surgery.

  • IV PCA = intravenous patient-controlled analgesia; SE = standard error; ASA = American Society of Anesthesiology; PCA = patient-controlled analgesia; ADS = anticholinergic drug scale; NRS = numeric rating scale; MPQ = McGill Pain Questionnaire.

In younger patients, crude analyses revealed that age and gynecological/urological surgery were significantly inversely associated with morphine intake. ADS, surgical duration, and MPQ were significantly positively associated with morphine intake. Once entered into the multivariate model, age, ADS, gynecological/urological surgery, and surgical duration remained significant. MPQ remained in the model but was no longer significant. The model is significant (P ≤ 0.001) and accounts for 47% of the variance in morphine intake (R2 = 0.47).

For older patients, crude analyses revealed that age was significantly inversely correlated with morphine intake. ASA II and NRS scores were significantly positively associated with morphine intake. Although not statistically significant, ASA III, ADS, and previous surgery + PCA were associated with morphine intake. Once entered into the multivariate model, age, ASA II and NRS remained significant. ASA III, ADS, and previous surgery + PCA were retained in the model but were nonsignificant. The multivariate model is significant (P ≤ 0.001) and accounts for 26% of the variance in morphine intake (R2 = 0.26).

anovas were conducted with age group and the significant correlates (ADS, surgical procedure, surgical duration, MPQ, ASA status, NRS, and previous surgical experience) as between subject factors and IV PCA morphine intake as the dependent variable. There was a significant interaction between age group and surgical procedure (Table 7). Among older patients, orthopedic surgery was associated with the highest morphine intake whereas, among younger patients, gastrointestinal surgery was associated with the highest morphine intake. In both age groups, gynecological/urological surgeries were associated with the lowest morphine use. Among younger patients there was a large difference in the amount of morphine used by those undergoing gastrointestinal and gynecological/urological surgery (approximately 40 mg, a difference of 46%). On the other hand, older people undergoing orthopedic versus gynecological/urological surgery did not use substantially different amounts of morphine (approximately 13 mg, a difference of 27%). There was a significant interaction between MPQ and age group, and the NRS by age group interaction approached significance. For both pain variables, among younger patients there was a large difference in the amount of morphine used by those with higher versus lower pain scores (approximately 22 mg, a difference of 31–32%). However, older people with higher and lower pain scores did not use substantially different amounts of morphine (approximately 2–6 mg, a 5–10% difference). There was a main effect of ASA class. ASA II patients used more morphine than ASA I or III patients. There was also a significant main effect for ADS. Patients with higher ADS scores used more morphine.

View this table:
Table 7

Main and interaction effects of age and correlates on IV PCA morphine intake (mg)

Younger (N = 123) (Mean ± SD)Older (N = 123) (Mean ± SD)Total (N = 246) (Mean ± SD)Main Effect PInteraction Effect P
ASA class
  ASA I55.99 ± 36.7123.10 ± 13.8348.94 ± 35.740.060.39
  ASA II63.78 ± 43.0841.18 ± 22.8750.67 ± 34.63
  ASA III48.94 ± 23.7937.72 ± 33.8741.46 ± 30.99
ADS score
  ≤449.11 ± 38.6235.51 ± 23.4942.08 ± 32.300.0040.12
  >467.47 ± 36.9940.91 ± 26.1054.51 ± 34.67
Previous surgical and/or PCA experience
  Group 1*51.47 ± 30.6533.48 ± 18.9845.28 ± 28.240.030.89
  Group 256.63 ± 35.9336.66 ± 23.5545.72 ± 31.34
  Group 371.87 ± 49.8047.42 ± 31.3560.70 ± 43.71
Surgical procedure
  Gynecological/urological46.66 ± 28.0635.02 ± 19.1140.88 ± 24.660.0010.05
  Gastrointestinal86.62 ± 45.5240.09 ± 25.7163.36 ± 43.47
  Orthopedic75.59 ± 45.6048.01 ± 38.1661.11 ± 43.60
Surgical duration (minutes)
  ≤19055.70 ± 38.3239.49 ± 21.4847.53 ± 31.920.540.19
  >19063.77 ± 38.5636.56 ± 27.1250.40 ± 35.98
NRS
  ≤347.76 ± 35.5135.69 ± 23.5741.16 ± 32.180.0010.06
  >369.32 ± 35.2441.73 ± 26.4256.87 ± 34.33
MPQ
  ≤1046.05 ± 35.5137.45 ± 27.9241.11 ± 31.520.0040.01
  >1068.39 ± 38.4639.36 ± 20.5956.06 ± 35.09
  • * No previous surgical or PCA experience;

  • previous surgical experience only;

  • previous surgical and PCA experience.

  • IV PCA = intravenous patient-controlled analgesia; ASA = American Society of Anesthesiology; ADS = anticholinergic drug scale; PCA = patient-controlled analgesia; NRS = numeric rating scale; MPQ = McGill Pain Questionnaire.

Discussion

As the number of older surgical patients grows, it will become increasingly important to understand age-related patterns in postoperative pain and analgesia [6]. Older surgical patients may differ from younger patients in many ways, including physical status, medication use and previous pain experiences. The objective of the present study was to identify the correlates of pain intensity and quality and IV PCA morphine use separately in younger and older patients. We found both commonalities and differences between the age groups. In addition, we found that some variables interacted with age.

Characteristics of Younger and Older Surgical Patients

As expected, the older patients in our sample were more likely than younger people to have impaired physical status. This is consistent with data from both community and surgical samples [14,30]. Older patients also were using more medications than younger patients. On average, they were taking approximately three medications, which is somewhat lower than other studies [36]. This may be due to the exclusion of patients with severe illnesses or ongoing chronic pain. Although we expected older people to have higher anticholinergic drug burden, there were no age differences on this variable. This may be due to the perioperative administration of anticholinergic drugs across age groups that may have obscured any presurgical differences. It is also possible that excluding patients with acute cognitive impairment, which has been associated with higher anticholinergic burden [40,41] further diminished differences between the age groups.

Although we expected older people to have more experience with chronic pain, there was no difference between the age groups. This may be due to recall biases. That is, people may have had difficulty remembering chronic pain that had been resolved for at least 6 months prior to surgery, although this seems unlikely. More likely, exclusion of patients with ongoing pain may have resulted in a unique sample. Many patients report ongoing preoperative pain, often directly related to the indication for surgery [7,11]. In addition, comorbid conditions not related to the surgical procedure may be painful. Therefore, while we excluded those with ongoing chronic pain due to the pain management challenges presented by this group [48,49], this may have resulted in a sample with less lifetime pain than would be the case in general.

Consistent with the literature [14], older patients were more likely than younger patients to have had previous surgery. This difference was small and was no longer evident when previous PCA was considered. Research has shown that, regardless of age, patients have significant concerns about PCA, in particular equipment malfunction and accidental overdose [14]. It is possible that patients with previous PCA experience, approximately 20% of our sample, may have differed from those using PCA for the first time.

Taken together, it appears that the age groups were similar but with several important differences. Compared with younger patients, older surgical patients were coping with poorer health, taking more medications, and were more likely to have had surgery in the past. How these older patients differ from those who become confused or are ineligible for PCA and how this, in turn, impacts on pain, analgesic requirements, and recovery remain to be documented.

Correlates of Postoperative Pain in Younger and Older Surgical Patients

Similar to some previous studies [9,14–17], pain intensity did not differ between the age groups. However, several other studies have suggested that younger age is associated with greater postoperative pain [7,10,11]. The results of the current study suggest that some of these discrepancies may be due to the role of factors that may differentially impact on pain across age groups. In both age groups, age, gender, morphine consumption, and previous surgical experience were important correlates. However, the direction of some of the associations differed across age groups.

Older patients obtained lower MPQ scores than younger patients. Similar findings have been reported previously [12,13,52,61]. There is evidence that this is not due to increased difficulty completing the MPQ with age, age differences in pain language, or the psychometric properties of the scale [13,52,61]. The present results suggest that age-related correlates of MPQ scores may be important. Given that measures of pain intensity (NRS) and pain qualities (MPQ) assess related but different aspects of pain [51], it is not surprising that their predictors differed. These findings support the importance of using both types of measures to assess pain.

The only correlate of MPQ scores that was important for both age groups was morphine intake. Increased MPQ scores were associated with increased morphine use. There were also some unique correlates identified in the regression analysis. For younger patients, higher BMI and previous surgical and PCA experience were associated with increased MPQ scores. For older patients, surgical procedure was a unique correlate; gynecological/urological surgery was associated with lower MPQ scores. Collapsing across age groups, orthopedic surgery was associated with higher MPQ scores than gynecological/urological or gastrointestinal surgery. This is consistent with the literature [33] and supports the importance of matching for surgical procedure across age groups. Interestingly, the regression models explained more variance in the younger than the older group. This suggests that other variables not included in the present analyses also may be important correlates of MPQ scores in older people.

Gender was an important correlate of pain intensity in both age groups, with higher pain intensity associated with being female. Gender-related patterns in postoperative pain have been reported previously, with studies suggesting that women report more pain than men [16,62]. The mechanisms for a relationship between sex and postoperative pain intensity are undoubtedly multidimensional and include the influence of neurobiological (e.g., gonadal hormones), psychological (e.g., emotional reactions) and cognitive (e.g., meaning of pain) factors [63]. Age and gender interactions in pain remain unclear [64], and there was no evidence for any significant interaction on either pain measure. However, gender-related patterns in pain may be particularly relevant for the elderly as women predominate in the oldest age groups [65].

Previous surgical experience played an important role in postoperative pain. On the MPQ, previous experience was retained in the regression model only for younger patients, but factorial analysis showed that it was important in both age groups. Specifically, those without previous surgical experience reported the lowest MPQ scores while those with both surgical and PCA experience reported the highest MPQ scores. On the NRS, previous surgical experience interacted with age. In both age groups, those who did not have surgical experience reported the lowest NRS. In the younger group, the pain intensity reported by each experience group was very similar (and all within one point). By contrast, there was far more spread in the NRS scores reported by older people within each experience group (over two points, a difference that has clinical relevance [66]). For this age group, similar to the MPQ, the lowest scores were obtained by those without surgical experience, intermediate scores were obtained by those with only surgical experience, and the highest scores were obtained by those with both surgical and PCA experience. These findings are consistent with literature indicating a relationship between past and present pain [8,43,45,67]. This relationship may reflect response shifts, adaptation processes, and neuroplastic changes in the central nervous system [43,68,69]. Wilder-Smith et al. [67] demonstrated that preoperative pain could induce central neuroplastic changes, involving both inhibitory and facilitative mechanisms. It is postulated that in patients with previous experiences of pain, facilitated central nervous system nociceptive processing may increase vulnerability to more intense postoperative pain [67].

The interpretation of the role of previous PCA experience is not immediately apparent. It is possible that these patients were more willing to make demands due to learning and reduced concerns about the apparatus. It also is possible that previous opioid use led to increased pain sensitivity and tolerance [70,71], although the impact of such effects in our sample remains highly speculative. Unfortunately, we do not have data regarding the interval of time between the previous and current PCA use, or the exact surgeries or analgesics that patients had previously. Importantly, the persistence of acute opioid-induced changes in pain sensitivity and tolerance, and the impact of age on these effects, have not been documented in postsurgical patients. Nonetheless, the current findings suggest that the role of previous surgical experiences on subsequent pain and opioid use is complex. At the least, it is modified by modality of analgesic delivery and patient age.

Correlates of PCA in Younger and Older Surgical Patients

Consistent with previous studies [14,15,18,20], older patients used less morphine than younger patients. We previously showed that this was not due to age differences in psychosocial factors including self-efficacy or willingness to use the PCA machine [14]. Given the comparable NRS and the lower MPQ scores with age, the difference in morphine use does not reflect inadequate analgesia or difficulties using the PCA machine. Older and younger patients received 80% or more of their requests for analgesia, which is higher than previously reported [72], and there were no differences in the dose/demand ratios and unmet demand/demand ratios. These results extend our previous findings [14] and further support the acceptability and feasibility of IV PCA for older patients. Specifically, they showed that older and younger people are using the apparatus similarly. Nonetheless, the interactions of age group with pain scores and surgical procedure suggest that the age differences in IV PCA use are not solely due to differences in morphine sensitivity, metabolism, and clearance [25,26].

In both age groups, higher anticholinergic load was associated with greater morphine use. To date, anticholinergic drug load has been neglected in the study of postoperative pain and opioid consumption. However, it is easy to imagine that these drugs may increase opioid requirements. The cholinergic system is important in pain inhibition and regulation directly and through facilitation of opioid analgesia [73,74]. Anticholinergic drugs may interfere with these endogeneous pain modulatory systems, leading to greater opioid requirements. With advancing age, there is a general decline in the cholinergic system [75]. The effects of anticholinergic drugs on pain behaviors, nociception, and opioid analgesia in animals of different ages have not been reported. Nonetheless, our data suggest that anticholinergic drugs are associated with increased opioid requirements. More research, including serum assays of anticholinergic activity and opioid metabolites and their interactions is needed to begin to elucidate this issue.

There was only limited evidence that physical status was associated with pain or analgesic requirements. In both age groups, patients with better physical status used more morphine than those with poorer physical status. This is consistent with Tsui et al. [19] and extends this finding to different age groups. The inconsistency with Chung et al. [33] is likely due to differences in surgical populations across studies. The interpretation of this finding is not clear. ASA status, although extensively used to classify surgical patients, is a crude measure of physical status. Future studies should use more comprehensive measures of health status, impairment, and comorbidities in order to clarify these findings.

An especially intriguing finding was the interaction between age group and pain scores on IV PCA morphine self-administration. In younger people, those with higher pain scores consumed substantially more morphine than those with lower pain scores. Similar findings have been reported previously [18,22], but the mechanism for this relationship remains to be examined. Importantly, the relationship between IV PCA morphine use and pain was not the same among older patients. Morphine use differed very little between older patients with higher and lower pain scores, and was similar to that of younger people with lower levels of pain. There are several possible reasons for these age-related findings. It may reflect the elderly's increased sensitivity to opioid drugs [25]. It is possible that an increase by a few milligrams will have comparable analgesic effects from the approximately 20 mg increase seen among younger people. This is consistent with research showing that older patients require smaller doses of opioids to attain analgesia comparable to that reported by younger patients [76,77]. Older patients are also more sensitive to the adverse effects of morphine [25]. Therefore, if patients using IV PCA strive to balance analgesia with side effects [24], older patients may have a smaller window of dosing within which to achieve this balance, potentially limiting the amount they can increase. Importantly, if replicated, this interaction suggests that age differences in morphine use are not due solely to changes in the pharmacological properties of these drugs. Rather, the relationship may be influenced by pain intensity such that younger patients with more severe pain may be at highest risk for inadequate postoperative pain control.

Another factor that may mediate the age–IV PCA morphine consumption relationship is surgical procedure. Those undergoing gynecological/urological procedures used the least amount of opioid in each age group. However, older patients undergoing orthopedic procedures and younger patients undergoing gastrointestinal procedures used the most opioid in each group. Interestingly, the range of morphine use was much larger for the younger than the older patients. This may reflect the heightened sensitivity of older people to opioid drugs that preclude large ranges in usage. In addition, it is important to note that the younger gynecological/urological patients used approximately the same amount of opioid as the older orthopedic patients, and only 7–12 mg more, on average, than the older gastrointestinal and gynecological/urological patients, respectively. This interaction suggests that the well-known age-related decline in IV PCA morphine use may also be related to surgical procedure and that younger patients undergoing orthopedic and gastrointestinal surgery may be a greater risk for increased postoperative opioid requirements. Longitudinal studies are needed to examine these interactions further and to identify the unique characteristics of younger patients who report more severe pain, including biological, psychological, and surgical parameters. Identification of at-risk patients early in the course of postoperative recovery would contribute to the development of pain management protocols tailored to the special needs of patients with different risk profiles, including age and surgical procedure. Our results suggest that younger patients, especially those undergoing orthopedic and gastrointestinal surgery, may be most likely to require such interventions.

Conclusions and Future Directions

Taken together, these results suggest that there may be age-related differences in patients who are most likely to report more intense pain 24 hours after surgery. Among older patients, women and those who have had previous postoperative PCA may report higher pain intensity. Among younger patients, women, those with previous surgical but not PCA experience, and those who self-administer more morphine may report higher pain intensity. Lower pain is associated with being male regardless of age, not having previous surgical experience for older patients, and lower opioid intake for younger patients. Similarly, IV PCA morphine use may be higher in patients who are younger, have better physical status, are taking more drugs with anticholinergic effects, and have had previous experience with postoperative PCA. Among younger patients, increased morphine use may also be associated with surgical procedure and duration. These results, especially the interactions, suggest that age-related patterns in pain and opioid requirements are multidetermined and that the same factor may have different effects across age groups. Because these factors often have not been considered in studies of age differences in postoperative pain, it is likely that they may have contributed to the inconsistent results in the literature.

Several limitations must be considered in the interpretation of these results. First, only patients eligible for IV PCA, who did not have ongoing chronic pain, and who were not confused were included. As such, conclusions are limited to this segment of the surgical population. It would be interesting to extend these results to the more frail elderly, including those with chronic pain and cognitive impairment. Postoperative pain at rest was measured at only one time point. This is not a comprehensive assessment and limits our ability to determine causal or predictive relationships. However, 24 hours is a common assessment interval in postoperative pain and aging studies, making our study comparable to those already available. Nonetheless, the data may be relevant only to that one time point and applicability to other postoperative time intervals remains to be determined. A further limitation arises from the data analyses undertaken. Multiple comparisons were tested, and it was decided not to use a conservative level of significance in order to maximize the hypothesis generating potential of this analysis, a goal that has been met. As a result, the possibility of Type 1 error cannot be ruled out. Nonetheless, the power for the regression analyses was excellent. Future studies are needed to determine the stability of our findings.

Despite these limitations, this study provides important new information regarding age-related patterns in postoperative pain. It is the first to assess correlates of analgesic use and postoperative pain, using both a measure of pain intensity and quality, separately in matched age groups. It is the first to consider the role of age-related factors, such as polypharmacy and anticholinergic drug load, and the first to examine the relationship of previous PCA experience to pain and analgesic use in younger and older patients. Several important age-related factors have been identified. Future studies should aim to identify the trajectory of postoperative pain in different age groups and the important correlates and predictors of pain at rest and with movement over time. Importantly, future work should focus on further elaborating the relationship between age and opioid use. These prospective studies should include a broader range of psychosocial variables, biological, and behavioral responses to tissue injury and surgical trauma, and serum assays of opioid metabolites and anticholinergic activity. These data would be invaluable to our understanding of pain and aging and to our efforts to provide effective postoperative pain control across the lifespan.

Acknowledgments

The authors are grateful to the members of the Acute Pain Service, University Health Network and to Denise Hosey, Timothy Salomons, and Danielle Cautadella who assisted with data collection. This work was supported by a University of Toronto Faculty of Medicine Dean's Fund Grant, a Canadian Institutes for Health Research Operating Grant and a New Investigator Award to L.G.

References

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