Abstract
Background
Resilience and depression may influence opioid consumption in patients undergoing primary hip and knee arthroplasty (TJA); however, data evaluating these relationships are limited.
Methods
We retrospectively identified 119 patients undergoing TJA who completed preoperative questionnaires to measure resilience (Brief Resilience Scale) and depression (PHQ-9) from 2017 to 2018 at a single institution. Patients were stratified into high, normal, and low resilience groups as well as no, mild, and major depression groups. Opioid use was recorded in morphine milligram equivalents (MMEs). Nonparametric statistical testing was performed with significance level at P < 0.05.
Results
Higher levels of resilience correlated with less postoperative inpatient opioid use (P = 0.003). Patients with high resilience were less likely to use preoperative opioids compared to those with low resilience (OR = 6.08, 95% CI [1.230.5]). There was no difference in postoperative outpatient opioid prescriptions between resilience groups. Lower levels of depression correlated with less postoperative inpatient opioid use, though this did not reach statistical significance (P = 0.058). Additionally, there was no significant difference in preoperative opioid use or postoperative outpatient opioid prescriptions between depression groups.
Conclusion
Patients with higher levels of resilience are less likely to use opioids before TJA and utilize lower amounts of opioids while inpatient following surgery. Depression correlated with higher postoperative inpatient opioid use; however, the present findings regarding this relationship are inconclusive. Resilience is a psychological trait that may impact opioid use in patients undergoing TJA and should be viewed as a modifiable risk factor.
Level of Evidence: III
Keywords: resilience, opioid, total joint arthroplasty
Introduction
Patients undergoing total joint arthroplasty (TJA) have high rates of opioid consumption pre- and postoperatively. Approximately 40% of patients undergoing TJA fill an opioid prescription in the 3 months preceding surgery.1,2 Over 60% of patients fill an opioid prescription within the first month after surgery; 18-25% of patients continue to fill opioid prescriptions at 3 months postoperatively, and approximately 15% will fill an opioid prescription at 1 year following TJA.1,2
Multiple risk factors for persistent opioid consumption following TJA have been identified, including younger age, female sex, preoperative opioid use, and mental health disorders including depression and anxiety.1-5 Additionally, preoperative opioid use has been linked to greater postoperative inpatient opioid use.6 Presence of more than one of these characteristics may result in a synergistic effect begetting significant increases in duration and quantity of opioid consumption following TJA.7 Recently, the influence of psychologic traits, such as a resilience, on pain perception following orthopedic surgery has been examined.8,9 Helmhorst et al.8 went as far as proclaiming resilience to be “the ultimate analgesic after musculoskeletal surgery.” However, data regarding the influence of resilience on opioid consumption after TJA is limited.
The purpose of the present study to investigate the potential relationship between resilience, depression, and duration and quantity of opioid consumption in patients undergoing elective primary TJA.
Methods
Institutional Review Board approval was obtained. A retrospective chart review of patients who underwent elective primary total hip arthroplasty (THA) or total knee arthroplasty (TKA) by one of three fellowship-trained arthroplasty surgeons from January 1, 2018 to December 31, 2018 was performed. Patients were identified using Current Procedural Terminology (CPT) codes 27447 and 27130. Inclusion criteria were patients ≥18 years of age undergoing primary THA or TKA, completion of preoperative questionnaires including the Brief Resilience Scale (BRS) and Patient Health Questionnaire-9 (PHQ-9) that were administered from June through August of 2017, and a minimum follow-up of 3 months. Exclusion criteria were patients who underwent revision or reoperations within 90 days as well as chronic opioid users (defined as those with at least six consecutive months of preoperative opioid usage or who had seen a chronic pain specialist) due to potential factors unrelated to hip or knee pain possibly influencing opioid usage.
Opioid use was recorded in morphine milligram equivalents (MMEs), which were calculated using an opioid equianalgesic chart.10 Opioid consumption was identified at five time points: preoperative, perioperative, intraoperative, inpatient postoperative, and outpatient postoperative. Preoperative was defined as within three months before surgery. Perioperative was defined as the time from admission to incision. Intraoperative was defined as the time from incision to leaving the operating room. Inpatient postoperative was defined as the time from leaving the operating room to hospital discharge. Outpatient postoperative was defined as the time from hospital discharge to three months following surgery.
Prolonged preoperative opioid consumption was defined as at least six continuous months of opioid use at any time before surgery. Number of patient call-ins pertaining to pain management or opioid refills were recorded, as were length of hospital stay (in hours) and type of anesthesia.
Study Instruments
Instruments administered to patients included the BRS to measure resilience and the PHQ-9 to measure depression. BRS (Figure 1) is a six-item questionnaire that has demonstrated positive correlation with social support and optimism, negative correlation with self-blame and pessimism, and successful internal consistency and test-retest reliability. The score ranges from 1.00-5.00 and can be stratified into three groups: low resilience (1.002.99), normal resilience (3.00-4.30), and high resilience (4.31-5.00).11,12 PHQ-9 scale (Figure 2) has been proven as a reliable and valid measure of both diagnosing and assessing the severity of depression symptoms. The score ranges from 0-27 and can be stratified into three groups: no depression (0-4), mild depression (5-9), and major depression (10-27).13,14
Figure 1.
Brief Resilience Scale
Figure 2.
Patient Health Questionnaire-9
Study Cohort
Included in the time period were 119 total patients, 58 TKA patients and 61 THA patients. Demographics including age, sex, race, and body mass index (BMI) were recorded. Charlson Comorbidity Index (CCI) was also calculated for each patient (Table 1 and Table 2). Preoperatively, high resilience was identified in 36% of patients, normal resilience in 56%, and low resilience in 8%. Major depression was identified in 18% of patients and mild depression in 17%.
Table 1.
Demographics for Patients by Resilience Groups
| High resilience (n = 43) | Normal resilience (n = 67) | Low resilience (n = 9) | P-value | |
|---|---|---|---|---|
| Age (median, IQR) | 65 (54-72) | 65 (55-69) | 61 (60-63) | 0.583 |
| Gender (% female) | 39.5% | 56.7% | 55.5% | 0.211 |
| Race (% Caucasian) | 97.6% | 97.0% | 77.7% | 0.056 |
| BMI (median, IQR) | 32.30 (27.93- 37.54) | 32.17 (28.46- 37.15) | 32.93 (25.1234.37) | 0.819 |
| CCI (median, IQR) | 0 (0-2) | 1 (0-2) | 1 (1-4) | 0.126 |
| Preop opioid use (% yes) | 11.6% | 19.4% | 44.4% | 0.059 |
| Prolonged opioid use (% yes) | 23.2% | 23.8% | 33.3% | 0.806 |
SD, standard deviation; BMI, body mass index; CCI, Charlson comorbidity index.
Table 2.
Demographics for Patients by Depression Groups
| No depression (n=77) | Mild depression (n = 20) | Major depression (n = 22) | P-value | |
|---|---|---|---|---|
| Age median, IQR) | 66 (58-71) | 59.5 (51.5-69) | 62 (52-65) | 0.074 |
| Gender (% female) | 49.3% | 55.0% | 50.0% | 0.929 |
| Race (% Caucasian) | 97.4% | 100.0% | 86.3% | 0.094 |
| BMI (median, IQR) | 31.63 (28.28- 35.26) | 30.26 (26.23- 37.39) | 34.14 (31.8240.12) | 0.109 |
| CCI (median, IQR) | 0 (0-2) | 1 (0-2.5) | 0.5 (0-2) | 0.330 |
| Preop opioid use (% yes) | 18.1% | 15.0% | 22.7% | 0.834 |
| Prolonged opioid use (% yes) | 20.7% | 30.0% | 31.8% | 0.428 |
IQR, interquartile range; BMI, body mass index; CCI, Charlson comorbidity index.
Statistical Analysis
We used the Spearman’s rank-order correlation test to evaluate correlations between BRS, PHQ-9, and opioid MME’s. The Wilcoxon sum rank test and Kruskal-Wallis test were used to compare continuous scores between different groups. Chi-square statistics and the Fischer exact test were used to compare categorical variables. All statistical analysis was done by SAS 9.4 (SAS Institute Inc., Cary, NC, USA) with significant level at P < 0.05.
Results
Patients with high resilience were significantly less likely to use preoperative opioids within 3 months of surgery compared to those with low resilience (OR = 6.08, 95% CI [1.21-30.47]) (Table 3). Further, patients with low resilience tended to have higher rates of opioid use relative to those with normal resilience, who had higher rates than those with high resilience; this closely reached significance (44.4% vs. 19.4% vs. 11.6%, respectively, P = 0.059). There was no significant difference in rates of prolonged preoperative opioid use between patients in high resilience, normal resilience, and low resilience groups (23.2% vs. 23.8% vs. 33.3%, P = 0.806) (Table 1).
Table 3.
Perioperative Inpatient and Postoperative Opioid Use by Resilience Groups
| High resilience (n = 43) | Normal resilience (n = 67) | Low resilience (n = 9) | P-value | |
|---|---|---|---|---|
| Periop opioid (% yes) | 39.5% | 49.2% | 44.4% | 0.601 |
| Intraop opioid (% yes) | 60.4% | 62.6% | 55.5% | 0.908 |
| Anesthesia type (%) | 0.586 | |||
| General | 23.2% | 26.8% | 11.1% | |
| Regional Converted to General | 9.3% | 4.4% | 11.1% | |
| Regional | 25.5% | 26.8% | 44.4% | |
| Regional + Monitored | 41.8% | 41.7% | 33.3% | |
| Postop inpatient, MME/h (median, IQR) | 2.12 (0.93- 3.40) | 2.91 (1.87- 3.78) | 3.11 (2.583.85) | 0.053 |
| High vs. Normal | .051 | |||
| High vs. Low | .035 | |||
| Normal vs. Low | .430 | |||
| Length of stay, hours (median, IQR) | 27 (24-47) | 26 (24-47) | 28 (21-47) | 0.956 |
| Initial postop prescription, MME (median, IQR) | 500 (480-500) | 500 (500-500) | 500 (320-500) | 0.402 |
| Total postop refill, MME (median, IQR) | 0 (0-300) | 0 (0-200) | 300 (0-600) | 0.158 |
| Number of call-ins (median, IQR) | 0 (0-1) | 0 (0-1) | 1 (0-2) | 0.319 |
MME/h, morphine milligram equivalent/hour; MME, morphine milligram equivalent; IQR, interquartile range.
The percentages of patients who received opioids in the perioperative (39.5% high resilience, 49.2% normal resilience, 44.4% low resilience, P = 0.601) and intra-operative (60.4% high, 62.6% normal, 55.5% low, P = 0.908) periods were not significantly different between resilience groups (Table 3). During the inpatient postoperative period, patients with high resilience consumed significantly fewer opioids than patients with low resilience (2.12 MME/h vs. 3.11 MME/h, P = 0.035) (Table 3). Similarly, higher preoperative BRS scores strongly correlated with decreased inpatient opioid use (r = -.026, P = 0.003) (Table 5).
Table 5.
Correlations between Resilience, Depression, and Postoperative Opioid Use
| Variable | Correlation (Spearman) | P-value | |
|---|---|---|---|
| BRS vs. | |||
| Postop inpatient, MME/h | -0.26 | 0.003 | |
| Initial postop prescription in MME | -0.07 | 0.427 | |
| Total postop refill in MME | -0.06 | 0.480 | |
| PHQ-9 vs. | |||
| Postop inpatient, MME/h | +0.17 | 0.058 | |
| Initial postop prescription in MME | -0.02 | 0.826 | |
| Total postop refill in MME | -0.08 | 0.372 | |
BRS, brief resilience scale; MME/h, morphine milligram equivalent/hour; MME, morphine milligram equivalent ; PHQ-9, patient health questionnaire-9.
No significant differences existed between resilience groups for median postoperative outpatient opioid MME’s for either initial prescriptions (500 high resilience, 500 normal resilience, 500 low resilience, P = 0.402) or total refills (0 high, 0 normal, 300 low, P = 0.158). Also, length of stay (P = 0.956), number of call-ins (P = 0.319), and anesthesia type (P = 0.586) did not significantly differ between groups (Table 3).
When comparing patients by depression symptoms, major, mild, and no depression groups did not demonstrate significantly different preoperative, perioperative, or intraoperative opioid consumption (Tables 2, 4). Lower preoperative PHQ9-9 correlated with less postoperative inpatient opioid use (r = +.17, P = 0.058) (Table 5). No significant differences existed between depression groups for initial postoperative prescription MME (P = 0.972), postoperative outpatient refill MME (P = 0.289), length of stay (P = 0.870), number of call-ins (P = 0.946), or anesthesia type (P = 0.899) (Table 4).
Table 4.
Perioperative Inpatient and Postoperative Opioid Use by Depression Groups
| No depression (n=77) | Mild depression (n = 20) | Major depression (n = 22) | P-value | |
|---|---|---|---|---|
| Periop opioid (% yes) | 41.5% | 45.0% | 59.0% | 0.366 |
| Intraop opioid (% yes) | 59.7% | 50.0% | 77.2% | 0.807 |
| Anesthesia type (%) | 0.899 | |||
| General | 22.0% | 20.0% | 36.3% | |
| Regional Converted to General | 6.4% | 5.0% | 9.0% | |
| Regional | 27.2% | 35.0% | 22.7% | |
| Regional + Monitored | 44.1% | 40.0% | 31.8% | |
| Postop inpatient, MME/h (median, IQR) | 2.58 (1.44- 3.57) | 3.02 (1.95- 4.03) | 3.16 (1.91- 3.57) | 0.418 |
| Length of stay, hours (median, IQR) | 26 (24-42) | 26.5 (24- 51.5) | 25 (21-70) | 0.870 |
| Initial postop prescription, MME (median, IQR) | 500 (500- 500) | 500 (500- 500) | 500 (500- 500) | 0.972 |
| Total postop refill, MME (median, IQR) | 0 (0-300) | 0 (0-262.5) | 0 (0-0) | 0.289 |
| Number of call-ins (median, IQR) | 0 (0-1) | 0 (0-1) | 0 (0-1) | 0.946 |
MME/h, morphine milligram equivalent/hour; MME, morphine milligram equivalent; IQR, interquartile range.
Discussion
Primary total hip and knee arthroplasty are common elective orthopedic procedures with high opioid usage. Therefore, it is imperative to identify risk factors associated with increased opioid consumption in order to prevent abuse, addiction, and overdose. Data evaluating the effects of mental health disorders, such as depression, and psychological traits, such as resilience, are limited.
We found that resilience contributes to both pre- and postoperative opioid use in patients undergoing TJA. Patients with low resilience were six times more likely to use opioids in the months leading up to surgery compared to those with high resilience. Additionally, higher baseline resilience scores correlated with decreased inpatient opioid use after surgery (P = 0.003). These trends align with literature that shows that preoperative opioid use is a risk factor for higher postoperative inpatient opioid use.6 While we did not find that patients with major or mild depression significantly used more opioids than those without depression, the presence of more depressive symptoms correlated with more postoperative inpatient use (P = 0.058). Though this did not reach statistical significance, it may have with a greater sample size and still demonstrates a clinically important point that depression may affect opioid usage.
Current literature proves that preoperative opioid consumption before TJAs negatively impacts outcomes. Studies have shown that patients who use opioids before surgery have worse postoperative pain and function as well as higher rates of nonhome discharge, 30-day readmission, and periprosthetic joint infections. Additionally, preoperative opioid users are more likely to have prolonged postoperative opioid use and require TJA revision surgery.15-19 Postoperative opioid use has proven similarly detrimental. Adverse effects from postoperative inpatient opioids lead to increased complications, longer length of stay, and higher rates of nonhome discharge.20 Therefore, the present study proves valuable since findings showed that patients with lower resilience are more likely to use preoperative opioids and have greater postoperative opioid consumption.
This study has several limitations. First, as a retrospective study, it depends on accurate documentation of medical records, which may not be fully reliable. Second, this study could only analyze opioid prescriptions prescribed by providers at our institution, so patients may have had others from outside institutions not included. Further, analyzing prescriptions filled may not be the most accurate way to measure opioid consumption since patients don’t necessarily utilize their prescriptions. Finally, the sample size was limited, and future studies with larger patient populations from multiple institutions would provide more concrete, generalizable results.
In conclusion, the present study demonstrates that psychological traits, such as resilience, and possibly mental health disorders, such as depression, may influence opioid consumption in patients undergoing total joint arthroplasty. Patients with higher resilience utilize fewer opioids before and after surgery, which may result in improved outcomes following surgery. Furthermore, patients who scored higher on the depression scale trended toward higher opioid use while inpatient after surgery; however, our study lacked enough power to definitively conclude the presence or absence of a relationship between depression and opioid usage. Though some work has expressed that resilience can be improved,21-22 future studies are still needed to understand potential interventions for improving resilience prior to elective TJA in order to minimize patient opioid use and optimize patient outcomes.
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