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Original Study

Preoperative Depression and Anxiety Impact on Inpatient Surgery Outcomes

A Prospective Cohort Study

Geoffrion, Roxana MD*; Koenig, Nicole A. BA*; Zheng, Meimuzi MSc*; Sinclair, Nicholas BSc*; Brotto, Lori A. PhD*; Lee, Terry PhD; Larouche, Maryse MD MPH

Author Information
doi: 10.1097/AS9.0000000000000049
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INTRODUCTION

Depressive disorders have persistently ranged in the top 3 global causes of nonfatal disease burden (measured in years lived with disability)1 and have been named a World Health Organization priority.2 Disability is defined as health loss associated with a single given health state.1 Psychiatric disorders cause higher disability, yet are undertreated compared with physical disorders in high-, middle-, and low-income countries.3 Among mental and substance use disorders, depression and anxiety account for 40.5% and 14.6% of disability-adjusted life years, respectively.4 Psychological stress in patients is associated with a chronic inflammatory response that can impair or delay normal postsurgical healing.5 In addition, depression and immune inflammatory activation may share common genetic predispositions.6 Certain genetic characteristics regulating immune function may also be associated with reduced responsiveness to antidepressants.6 After surgery, normal immune function is required for tissue repair and prevention of infections. Despite available treatment strategies for mood disorders, mental health optimization is infrequently addressed before major surgery. Some surgeons do not consider their patients’ depressive symptoms in operative planning,7 and yet psychological distress is a significant predictor for postoperative pain in many surgical specialties.8 Moreover, depression has been associated with increased analgesic use,9 length of stay,10 early readmission,11 and higher complication rates12 in various surgical disciplines. Depression and anxiety have been well studied in cardiac surgery, where they significantly increase postoperative mortality.13 Adult women have a greater burden from psychiatric disorders than men,4 yet the impact of sex on postsurgical outcomes is unclear and conflicting in various studies.8

We hypothesized that depression and anxiety increase adverse surgical outcomes and postoperative pain. We aimed to quantify the association of preoperative depression and anxiety symptoms on postoperative complications, length of stay, readmission, and pain, and to explore sex differences and sex-specific coping mechanisms in patients undergoing major surgery.

METHODS

We conducted a prospective cohort study of depression and anxiety symptoms in patients undergoing major surgery at a university hospital. Major surgery was defined as a need for postoperative inpatient admission. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for this study.14 Institutional review board approval was obtained. We included all adult patients who presented to preoperative assessment clinics one day before or same day as their surgery (February 2015 to January 2020). We excluded patients who were unable to complete English language questionnaires. Patients were recruited at baseline before surgery, written informed consent was obtained and demographic data collected including age, sex, body mass index, ethnicity, level of education, smoking, alcohol use, recreational drug use, exercise and activity levels, changes in sleep patterns, and a coping mechanism questionnaire consisting of questions about support at home after surgery, trust in the surgical team, expectations of surgical results, satisfaction with preoperative educational materials received, additional sources of information sought, anticipation of surgical pain, and self-reported pain tolerance. Patients also completed validated questionnaires including the Beck Depression Inventory (BDI-II),15,16 the Beck Anxiety Inventory (BAI),17 the Pain Catastrophizing Scale,18 and the Brief Pain Inventory Short Form (BPI).19 Depression and anxiety questionnaires asked about symptoms in the weeks before questionnaire administration, with the anxiety questionnaire asking participants to exclude feelings the day of questionnaire completion to mitigate stress of upcoming surgery. Following the planned surgery, we collected demographic, intraoperative, and postoperative data from hospital charts up to 30 days postoperatively. Intraoperative data included American Society of Anesthesiologists (ASA) physical status classification20 and type of surgery (specialty). Postoperative data included Visual Analog Scale (VAS)21 for pain, narcotic use up to 72 hours, postoperative complications, length of hospital stay, and readmissions. Narcotic use was quantified using morphine milligram equivalents (MME).22 Adverse events for each patient were categorized using the modified Clavien-Dindo surgical complication grading scale.23,24

Our primary analysis was to determine the association of preoperative depression and anxiety with postoperative complications, length of stay, and readmission in males versus females. Our primary outcome measure was a composite of Clavien-Dindo score >0, extended length of stay (ELOS, >90th percentile of specialty-specific LOS) and early readmission (up to 30 days postoperatively). Secondary analyses explored the association between primary outcome and patient demographics/coping mechanisms, impact of depression and anxiety on early postoperative pain, sex differences, and correlations between depression/anxiety and patient demographics, coping mechanisms and pain catastrophizing. Participants were analyzed by sex; if they indicated “other” under the sex category, they were excluded from comparative analyses of males versus females. Although there are notable gender effects on mood, we specifically asked participants to report their identified sex, as male, female, or other. As such, we refer to sex differences and use these terms throughout this article.

Based on the BDI percentiles reported in Roelofs,25 we hypothesized that the distribution of BDI in preoperative patients can be approximated by a Gamma distribution with shape and scale parameters being 2 and 3, respectively. Assuming the primary outcome rate is 40% for patients with BDI score of 6 (ie, mean score of the assumed Gamma distribution), the sample size required to detect an odds ratio of 2 (per 10 unit of BDI increase) with 80% power at the 5% significance level would be 398 for each sex group. To account for a potential loss to follow up of 10%, a sample size of 442 was planned for each sex group (male and female participants, respectively).

Comparisons of preoperative and postoperative variables between sexes and groups defined by selected patient variables were made by Chi-square test, Fisher exact test, ANOVA, or Kruskal-Wallis test as appropriate. Comparison of MME between sexes was based on quantile regression adjusted for patient’s weight. The relationship between preoperative BDI-II/BAI scores and the primary outcome within each sex group was assessed univariately using the Cochran-Armitage trend test. Logistic regression analysis adjusted for clinically relevant confounders including age, ASA, and surgical specialty (type of surgery) was also performed for each sex group separately. Upon examination of the data, the association between BDI-II/BAI scores and the primary outcome was nonlinear, and thus, BDI-II/BAI was considered as categorical variables in the regression analysis and adjacent categories were combined if their observed primary outcome rates were similar. Comparisons of primary outcome rate across levels of ordinal or categorical patient variables were based on the Cochran-Armitage trend test or Chi-square test as appropriate. Logistic regression analysis adjusted for the same confounders as in the primary analysis was also performed. Spearman correlation (rho) was used to assess the association between pairs of variables. No adjustment was made to the P value to account for comparisons of multiple secondary outcomes. All analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC).

RESULTS

Demographics

Preoperative

In total, 1061 preoperative patients were recruited and 942 (455 males, 486 females, and 1 other) had preoperative BDI-II/BAI scores and surgical and postoperative data available. The baseline median BDI-II score was 6.3 (interquartile range [IQR] 3–11) and 9.3% of patients had moderate or severe depression; median BAI score was 6 (IQR 2–11) and 7.4% of patients had moderate or severe anxiety. Females were more likely than males to be moderately or severely depressed (11% vs 7%, P = 0.036) and moderately or severely anxious (9% vs 6%, P = 0.034).

Patients’ mean age was 62.9 years (range 20.2–96.2) and most described their ethnicity as Canadian (69.6%). Some demographic characteristics were significantly different between men and women (Table 1). Most did not require any assistance with basic daily activities preoperatively (91.5%). Over half of patients reported exercising lightly >4× per week (57.2%), but less than half for moderately strenuously >1× per week (37.7%). Recent moderate-severe changes in their sleeping patterns were noted by 16.6% of patients. Similar proportions in both males and females reported no recent change in sleeping pattern (38% vs 39%), but more males reported getting more sleep than usual when compared to females (27% vs 18%, P = 0.003). Most (79.8%) described having quite a bit or a lot of support at home for recovering after surgery, with no difference between males and females. Male patients placed significantly more trust in their surgical team compared with females (complete trust: 71% vs 58%, P < 0.001). Both sexes thought surgeries for their condition would most likely be successful (89%) and were quite satisfied or very satisfied with the amount of medical information received (95%). Females were more likely than males to consult the Internet for additional surgical information (57% vs 50%, respectively, P = 0.036). Significantly more females anticipated early postoperative pain to be moderate or severe (75% vs 66%, P < 0.001). The sexes had similar reported pain tolerance, but females had higher pain catastrophizing total scores and in each subscale of rumination, magnification, and helplessness (P < 0.001). Females also had higher baseline pain score on the BPI (median 1.3 vs 0.5, IQR 0–3.3 and 0–2.3, respectively, P = 0.001).

TABLE 1. - Patient Characteristics
Variable All (n = 942) Male (n = 455) Female (n = 486) P
Body mass index, mean (SD), kg/m2 27.2 (5.8) 27.4 (5.0) 27.0 (6.4) 0.003
 Missing, n 49 22 27
Age, mean (SD), y 62.9 (15.0) 65.9 (13.4) 60.0 (16.0) <0.001
 Missing, n 34 15 19
Ethnicity, n (%)*
 Canadian 654 (69.6) 324 (71.7) 329 (67.7) 0.185
 European origins 243 (25.9) 130 (28.8) 113 (23.3) 0.054
 Asian 101 (10.8) 34 (7.5) 67 (13.8) 0.002
 Aboriginal/North American Indian 21 (2.2) 11 (2.4) 10 (2.1) 0.697
 Other 54 (5.8) 23 (5.1) 31 (6.4) 0.397
Cancer as indication for surgery, n (%) 161 (17.1) 88 (19.3) 73 (15.0) 0.079
Highest level of education, n (%) 0.017
 Unknown 1 1 0
 8th grade or less 52 (5.5) 32 (7.0) 20 (4.1)
 High School 275 (29.2) 135 (29.7) 139 (28.6)
 College/University 480 (51.0) 212 (46.7) 268 (55.1)
 Postgraduate 134 (14.2) 75 (16.5) 59 (12.1)
Exercise lightly, n (%) 0.484
 Unknown 17 11 6
 Once a month or less 54 (5.8) 30 (6.8) 24 (5.0)
 Few times each month 111 (12.0) 55 (12.4) 55 (11.5)
 2–3 times each week 231 (25.0) 115 (25.9) 116 (24.2)
 4 times or more each week 529 (57.2) 244 (55.0) 285 (59.4)
Exercise moderately to strenuously, n (%) 0.833
 Unknown 61 29 32
 Once a month or less 375 (42.6) 177 (41.5) 198 (43.6)
 Few times each month 174 (19.8) 84 (19.7) 89 (19.6)
 2–3 times each week 209 (23.7) 101 (23.7) 108 (23.8)
 4 times or more each week 123 (14.0) 64 (15.0) 59 (13.0)
Smoked cigarettes in the last year, n (%) 86/930 (9.2) 44/447 (9.8) 42/482 (8.7) 0.553
Any use of alcohol, n (%) 475/929 (51.1) 264/447 (59.1) 211/481 (43.9) <0.001
Any use of recreational drugs, n (%) 100/927 (10.8) 69/443 (15.6) 31/483 (6.4) <0.001
*Multiple categories can be selected for each patient. Data were missing for 3 patients.

Intraoperative

Ten different surgical specialties were represented (Table 2). Females had significantly fewer reported comorbidities and lower ASA category (P < 0.001).

TABLE 2. - Intraoperative and Postoperative Characteristics
Variable All (n = 942) Male (n = 455) Female (n = 486) P
Surgical specialty, n (%) <0.001
 Cardiac 305 (32.4) 215 (47.3) 89 (18.3)
 Colorectal 117 (12.4) 67 (14.7) 50 (10.3)
 ENT 15 (1.6) 6 (1.3) 9 (1.9)
 General 134 (14.2) 67 (14.7) 67 (13.8)
 Gynecology 99 (10.5) 0 (0.0) 99 (20.4)
 Orthopedic 2 (0.2) 1 (0.2) 1 (0.2)
 Plastic 1 (0.1) 1 (0.2) 0 (0.0)
 Urogynecology 135 (14.3) 0 (0.0) 135 (27.8)
 Urology 99 (10.5) 70 (15.4) 29 (6.0)
 Vascular 35 (3.7) 28 (6.2) 7 (1.4)
Comorbidities score, median (IQR) 1.0 (0.0, 2.0) 1.0 (0.0, 3.0) 0.0 (0.0, 2.0) <0.001
 Missing, n 31 12 19
ASA physical status, n (%) <0.001
 1 76 (8.2) 10 (2.3) 66 (13.7)
 2 290 (31.4) 81 (18.4) 209 (43.5)
 3 237 (25.7) 128 (29.0) 109 (22.7)
 4 320 (34.7) 222 (50.3) 97 (20.2)
Clavien-Dindo classification, n <0.001
 0 589 (64.0) 249 (56.0) 340 (71.6)
 1 160 (17.4) 82 (18.4) 78 (16.4)
 2 112 (12.2) 74 (16.6) 37 (7.8)
 3 45 (4.9) 30 (6.7) 15 (3.2)
 4 13 (1.4) 8 (1.8) 5 (1.1)
 5 2 (0.2) 2 (0.4) 0 (0.0)
Clavien-Dindo > 0, n (%) 332/921 (36.0) 196/445 (44.0) 135/475 (28.4) <0.001
Length of stay, median (IQR), d 2.9 (1.2, 5.1) 3.9 (1.9, 6.0) 2.0 (1.1, 4.1) <0.001
 Missing, n 23 12 11
ELOS, n (%) 68/919 (7.4) 28/443 (6.3) 40/475 (8.4) 0.225
Early readmission to hospital, n (%) 91/918 (9.9) 48/441 (10.9) 43/476 (9.0) 0.349
Primary outcome (postoperative complication, ELOS or early readmission), n (%) 412/915 (45.0) 231/440 (52.5) 180/474 (38.0) <0.001
ASA indicates American Society of Anesthesiologists; ENT, ear nose and throat; IQR, interquartile range.

Postoperative

Males had more postoperative complications (Clavien-Dindo score > 0, P < 0.001) and longer median length of stay (P < 0.001), but similar proportion with ELOS (P = 0.23) or early postoperative readmission to hospital when compared with females (P = 0.35) (Table 3). Postoperatively, females reported more severe pain at 48 to 72 hours (mean VAS: 2.5 vs 2.1, P = 0.045) but not in the first 48 hours (2.8 vs 2.6, P = 0.46). No difference in MME was observed by sex in any time increment after adjusting for patients’ weight.

TABLE 3. - Association Between BDI-II and BAI and the Primary Outcome (Rate of Postoperative Complications, ELOS, and/or Hospital Readmission)
BDI-II BAI
Male Female Male Female
Variable Odds Ratio (95% CI) P Odds Ratio (95% CI) P Odds Ratio (95% CI) P Odds Ratio (95% CI) P
BDI-II
 1–19 vs 0 0.87 (0.41, 1.83) 0.707 2.57 (1.04, 6.37) 0.041
 >19 vs 0 2.29 (0.56, 9.35) 0.247 4.48 (1.48, 13.56) 0.008
 >19 vs 1–19 2.65 (0.77, 9.15) 0.124 1.74 (0.86, 3.53) 0.124
BAI: ≤6 vs >6 1.40 (0.92, 2.14) 0.119 1.54 (1.02, 2.32) 0.038
ASA (per category increase) 1.74 (1.15, 2.63) 0.009 1.32 (0.95, 1.82) 0.095 1.79 (1.19, 2.69) 0.005 1.37 (0.99, 1.89) 0.056
Age (per 5 y decrease) 1.07 (0.98, 1.16) 0.124 1.11 (1.03, 1.19) 0.005 1.05 (0.97, 1.15) 0.216 1.10 (1.03, 1.19) 0.008
Surgical specialty
 General 1 (Reference) 1 (Reference) 1 (Reference) 1 (Reference)
 Cardiac 0.91 (0.41, 1.98) 0.807 2.38 (1.03, 5.53) 0.044 0.85 (0.39, 1.84) 0.675 2.43 (1.05, 5.65) 0.038
 Colorectal 0.88 (0.42, 1.85) 0.733 1.00 (0.45, 2.22) 0.991 1.01 (0.49, 2.11) 0.974 1.15 (0.52, 2.55) 0.731
 Gynecology 0.88 (0.42, 1.81) 0.719 0.93 (0.45, 1.92) 0.848
 Urogynecology 0.98 (0.49, 1.99) 0.961 1.14 (0.56, 2.32) 0.708
 Urology 0.56 (0.26, 1.18) 0.128 1.08 (0.40, 2.91) 0.886 0.75 (0.36, 1.57) 0.447 1.04 (0.38, 2.87) 0.943
 Vascular 0.49 (0.17, 1.37) 0.173 1.43 (0.24, 8.54) 0.694 0.67 (0.24, 1.88) 0.452 1.08 (0.18, 6.28) 0.935
 Other 0.37 (0.06, 2.11) 0.263 0.54 (0.11, 2.67) 0.454 0.42 (0.08, 2.37) 0.328 0.60 (0.12, 2.94) 0.528
ASA indicates American Society of Anesthesiologists.

Primary Analysis

Increasing BDI-II scores was significantly associated with more postoperative complications, ELOS, and/or hospital readmission in female patients (unadjusted P = 0.002 [Fig. 1] and adjusted P ≤ 0.041 when compared with BDI-II = 0 [Table 3]) but not in males (unadjusted P = 0.615 and adjusted P > 0.124). Increasing BAI scores was also significantly associated with more postoperative complications, ELOS, and/or hospital readmission in females (unadjusted P = 0.048 and adjusted P = 0.038) but not in males (unadjusted P = 0.092 and adjusted P = 0.12) (Fig. 1 and Table 3).

F1
FIGURE 1.:
Primary outcome: rate of postoperative complications, ELOS, and/or hospital readmission by preoperative BDI-II/BAI scores for males and females.

Secondary Analyses

Infrequent light exercise (unadjusted P = 0.007 and adjusted P = 0.047) and sleep disturbance (unadjusted P = 0.014 and adjusted P = 0.022) were associated with worsening of the primary outcome in females, but not in males. Other coping mechanisms did not influence the primary outcome (Table A1).

Both BDI-II and BAI showed moderate positive correlations with preoperative pain catastrophizing (rumination, magnification, and helplessness) and with pain interference on daily activities (Spearman rho: 0.4–0.5) for both sexes, but not with postoperative pain or opioid requirements (Spearman rho ≤ 0.23). Preoperatively, for both sexes, depressive symptoms were significantly associated with levels of exercise and assistance for basic daily activities; overall sentiments about success of surgery; and anticipation of pain (Table A2). The level of exercise and anticipation/tolerance of pain were significantly associated with BAI in males, but not in females.

Anticipation of higher pain severity was associated with significantly greater VAS and MME scores in all time increments, as well as with more complications and longer length of stay for both sexes (P < 0.05 for all; Table A3). In both sexes, those with lower subjective pain tolerance reported significantly higher VAS in the first 24 hours postoperatively, with similar length of stay. There were no significant correlations between preoperative pain catastrophizing, or BPI scores and postoperative VAS, MME, or length of stay (Spearman rho ≤ 0.3).

There were no significant correlations between exercise or sleep and VAS or MME scores (Spearman rho < 0.3). Trust in the surgical team was not consistently associated with pain across all time intervals in both sexes (Table A4). Trust did not affect opioid consumption. Anticipated success of surgery was significantly associated with less pain yet similar MME use for both sexes. Satisfaction with the amount of surgical information was associated with less pain in males and females at 24 to 48 hours and less opioid consumption in females in the same time interval.

DISCUSSION

Our study described the association of preoperative depression and anxiety symptoms with postsurgical outcomes, and how these differed by sex of participants. We showed both depression and anxiety were associated with postoperative complications, length of stay, and readmission in female patients. Greater preoperative perceptions of pain were correlated with higher subjective pain, greater opioid use, more complications and longer length of stay postoperatively. There was also an overall difference by sex, independent of outcomes, with females reporting more surgical pain than males at 48 to 72 hours, with similar opioid consumption for pain control. Exercise and sleep were significant predictors of successful surgical outcomes in females.

A systematic review and meta-analysis including data from 236,595 patients undergoing cardiac surgery showed perioperative depression and anxiety may be associated with increased postoperative mortality.13 Emotional distress has shown a multifactorial association with coronary artery disease, explained by factors such as tendency to sedentary behaviors and poor adherence to preventative measures such as diet and exercise. The association between depression and greater risk of postoperative complications has been demonstrated in other surgical specialties as well.26 In cancer patients in particular, depression is common and may be a consequence of their particular diagnosis. However, tumor growth and progression of disease can be affected by inadequate immune responses and treatment of depression may be of benefit. For example, in a population of women undergoing surgery for breast cancer, individual psychotherapy and pharmacologic management resulted in a significant difference in disease-free survival 1 year postoperatively when compared with a control group.27 Prior studies from various surgical fields have shown associations of depression and anxiety with ELOS.10,11,28,29

It is difficult to tease out cause and effect relationships given the confounding effect of pain around the time of surgery. In accordance with the sleep and pain diathesis model, in a group of women with chronic pain from fibromyalgia, more disrupted sleep was associated with higher psychological and physical disability, and this was mediated by pain.30 Preoperatively, females in our cohort had more pain, more mood symptoms and reported less sleep than males. However, unlike participants in the Hamilton study, our participants were not recruited from a chronic pain clinic and preoperative pain scores were low. Sex differences in pain perception may have a basis in the immune system; research shows different sex hormone-mediated immune reactivities before and following injury,31 and surgery is a type of injury. Both infrequent exercise and poor sleep were associated with worse surgical outcomes in our patient population. There is a medium effect between sleep deprivation and pain perception, as demonstrated via meta-analysis.32 Acute sleep deprivation lowers pain thresholds.33 Exercise and sleep are related, with exercise showing clear benefits on sleep for patients with depressive symptoms and sleep disorders.34 Exercise and mental health optimization are among strategies suggested as part of a larger package of preoperative conditioning to facilitate return to baseline activities of daily living.35,36 In women, aerobic and anaerobic exercise can be an option to reduce negative mood.37

Mood and anxiety influence pain perceptions independent of sleep quality.38 Although higher depression and anxiety scores were correlated with preoperative pain catastrophizing and interference from pain, we did not show an association with postoperative pain or opioid consumption. Studies from different surgical fields seem contradictory: in patients undergoing abdominal surgery, for example, moderate to intense acute postoperative pain was associated with high-trait anxiety and depressive mood,39 whereas adult spine surgery did not show this association.40 A systematic review of predictive factors for postoperative pain8 showed preexisting pain, anxiety, younger age, and type of surgery to be the most significant predictors. Our baseline pain intensity score was low and our patient population was older. It is possible that depression and anxiety, in the absence of pre-existing chronic pain, contribute to pain perceptions (such as catastrophizing about pain) rather than actual pain once the surgery is completed. On the other hand, higher anticipated pain and lower subjective pain threshold did predict higher postoperative pain and higher postoperative opioid consumption for both male and female participants in our study. This is consistent with studies of objective preoperative pain threshold measurement as a predictor of postoperative pain.41,42

Another predictor of pain and opioid consumption in females was patients’ satisfaction with the amount of information received about their surgery. An educational workshop on pelvic floor health interventions improved women’s knowledge, symptoms, and quality of life scores evaluated three months later.43 A Cochrane review of the effect of preoperative education in orthopedic hip or knee replacements concluded that it may have benefits for patients with depression or anxiety.44 In an era of opioid misuse, tailored patient education in the context of surgical interventions may lead to less pain and safer behaviors. Interestingly, although females in our study reported more pain at 48 to 72 hours, they did not receive more opioids than males at any time point. There are significant biases reported in the literature regarding pain management in men versus women. For example, women’s pain reports are taken less seriously (which may have resulted in prescribing of fewer opioids) and their medication is less effective for pain control than treatments prescribed to men (which may have resulted in female patients asking for fewer opioids or perhaps more nonprescription anti-inflammatories, for example).45

A strength of our study is that this represents one of the largest prospective cohort investigations of mental health in both sexes recruited from various surgical specialties. Another strength is our use of validated brief questionnaires that can be used in the clinical setting. The results from our study can be used to build individualized mental health optimization tools in vulnerable patients prior to surgery.

Limitations include patient selection bias. Depressed or anxious patients may have declined participation in our study before their upcoming surgery more often than other patients. Additionally, as we did not collect a treatment history, we may have also included patients with well controlled symptoms of depression and anxiety. This may explain the lower than expected incidence of clinical depression and anxiety in our patient population, which can limit our power to detect the relationship between depression, anxiety and patient characteristics or outcomes. On the other hand, although we tried to capture symptoms of the weeks before hospital admission, the patients who did elect to answer our questionnaires may have had heightened mood symptoms due to the imminent stress of surgery. Our study was likely underpowered to show significance in the male population. It could be that depression and anxiety are less prominent in males versus females undergoing surgery. On the other hand, our screening questionnaires may be sex-biased, thus resulting in an under-diagnosis of mood disorders in male participants. Psychological research shows that males and females experience depression differently: although men and women report similar severity of depression on the BDI, they endorse different symptoms within the questionnaire; men are also more likely to conceal symptoms.46 Research needs to focus on male-specific symptom clusters when assessing men for depression.46 Perhaps, our study tools were not sensitive enough to capture these subtle diagnostic nuances. Additionally, we did not examine the effect of self-identified gender, a socioculturally driven sex identification31 in our patients and our baseline measure only asked about sex, namely male versus female. Gender does play a role in the experience of pain, for example.31 Future research should ask participants to identify both their birth assigned sex, and their identified gender, which may include trans- and nonbinary identities, to better understand how we might optimize mental health prior to surgery in a more precise manner. Another limitation of our study is the inclusion of a great variety of patient surgeries, even within the same specialty category. This is associated with variation in length of stay and introduces variability in outcomes such as pain and pain perceptions. Surgery-specific anticipated versus actual length of stay was not available at our hospital. We hope the number of included patients ensured enough representation for many different surgical procedures within specialties. Given the limited sample size of different subgroups, we did not have sufficient statistical power to conduct subgroup analyses (such as by comorbidity, for example). Our current findings will hopefully encourage further research with mental health of particular subgroups.

In summary, our study showed preoperative depression, anxiety, and coping mechanisms were associated with adverse surgical outcomes and postoperative pain in a sex-specific way, with female patients significantly more impacted than males. It highlighted the importance of holistic preoperative medical care, patient education, and the emergence of sleep and exercise as novel therapeutic targets to potentially optimize outcomes for patients undergoing major surgery.

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APPENDIX

TABLE A1. - Association Between Primary Outcome and Selected Preoperative Variables
Male Female
Variable Primary Outcome Rate P * aOR (95% CI) P  Primary Outcome Rate P * aOR (95% CI) P 
Exercise lightly, n (%) 0.249 0.007
 Once a month or less 13/28 (46.4) 0.74 (0.32, 1.69) 0.470 14/23 (60.9) 2.59 (1.01, 6.61) 0.047
 Few times each month 27/53 (50.9) 0.89 (0.47, 1.71) 0.734 25/53 (47.2) 1.58 (0.83, 3.03) 0.165
 2–3 times each week 51/109 (46.8) 0.70 (0.43, 1.14) 0.150 42/114 (36.8) 1.14 (0.70, 1.84) 0.594
 4+ times each week 132/239 (55.2) 1 (Reference) 96/278 (34.5) 1 (Reference)
Exercise moderately to strenuously, n (%) 0.686 0.296
 Once a month or less 86/169 (50.9) 0.83 (0.44, 1.56) 0.558 79/193 (40.9) 0.93 (0.49, 1.77) 0.826
 Few times each month 40/81 (49.4) 0.81 (0.40, 1.64) 0.551 35/89 (39.3) 0.92 (0.44, 1.90) 0.821
 2–3 times each week 59/101 (58.4) 1.31 (0.67, 2.59) 0.432 30/106 (28.3) 0.63 (0.31, 1.30) 0.215
 4+ times each week 30/61 (49.2) 1 (Reference) 23/55 (41.8) 1 (Reference)
Change in sleeping pattern, n (%) 0.642 0.014
 No change 80/161 (49.7) 1 (Reference) 53/172 (30.8) 1 (Reference)
 More sleep than usual 58/109 (53.2) 1.04 (0.62, 1.75) 0.882 40/81 (49.4) 1.98 (1.10, 3.56) 0.022
 Less sleep than usual 84/153 (54.9) 1.21 (0.75, 1.95) 0.440 79/198 (39.9) 1.25 (0.79, 1.98) 0.347
Support at home after your surgery, n (%) 0.597 0.507
 No support 15/25 (60.0) 1.30 (0.52, 3.21) 0.575 5/20 (25.0) 0.47 (0.13, 1.73) 0.257
 Little support 30/61 (49.2) 0.85 (0.46, 1.57) 0.595 33/79 (41.8) 1.54 (0.87, 2.72) 0.139
 Quite a bit of support 60/127 (47.2) 0.78 (0.49, 1.24) 0.295 69/164 (42.1) 1.36 (0.86, 2.15) 0.182
 A lot of support 122/219 (55.7) 1 (Reference) 70/207 (33.8) 1 (Reference)
Trust in surgical team, n (%) 0.767 0.201
 Some trust 2/7 (28.6) 0.14 (0.01, 3.73) 0.242 11/24 (45.8) 1.85 (0.73, 4.71) 0.198
 A lot of trust 65/115 (56.5) 1.16 (0.73, 1.85) 0.528 71/175 (40.6) 1.32 (0.87, 2.01) 0.195
 Complete trust 159/310 (51.3) 1 (Reference) 97/271 (35.8) 1 (Reference)
Surgery for your condition, n (%) 0.668 0.603
 Perhaps be successful 25/45 (55.6) 1.11 (0.56, 2.19) 0.766 20/49 (40.8) 1.25 (0.65, 2.39) 0.509
 Most likely be successful 203/389 (52.2) 1 (Reference) 154/416 (37.0) 1 (Reference)
Amount of information received, n (%) 0.064 0.191
 Somewhat satisfied 8/20 (40.0) 0.51 (0.18, 1.45) 0.205 14/22 (63.6) 2.40 (0.90, 6.39) 0.080
 Quite satisfied 57/120 (47.5) 0.69 (0.44, 1.09) 0.109 54/149 (36.2) 0.99 (0.64, 1.53) 0.951
 Very satisfied 164/295 (55.6) 1 (Reference) 110/296 (37.2) 1 (Reference)
*A P value was based on the Cochran-Armitage trend test or Chi-square test as appropriate.
†A P value was based on logistic regression adjusted for age, ASA, and surgical specialty.
ASA indicates American Society of Anesthesiologists.

TABLE A2. - Median BDI-II and BAI Score by Patient Demographics and Coping Mechanisms
Male Female
BDI-II BAI BDI-II BAI
Variable Median (IQR) P Median (IQR) P Median (IQR) P Median (IQR) P
Exercise lightly <0.001 <0.001 0.001 0.756
 Once a month or less 9.5 (6.1, 15.0) 11.3 (4.0, 18.4) 6.7 (3.6, 11.0) 7.5 (1.5, 14.5)
 Few times each month 8.0 (4.2, 13.0) 7.0 (4.0, 12.0) 10.0 (6.0, 16.0) 7.0 (5.0, 10.0)
 2–3 times each week 5.9 (3.0, 10.0) 4.5 (1.1, 8.0) 8.0 (4.0, 14.0) 7.0 (3.0, 12.0)
 4 times or more each week 6.0 (3.0, 10.0) 4.0 (1.0, 8.4) 6.0 (3.0, 10.0) 6.0 (3.0, 12.2)
Exercise moderately to strenuously <0.001 <0.001 0.001 0.134
 Once a month or less 8.0 (5.0, 13.0) 6.0 (3.0, 13.0) 8.0 (4.0, 13.0) 7.0 (3.2, 13.0)
 Few times each month 6.0 (3.0, 10.8) 4.0 (2.0, 7.0) 7.0 (4.0, 10.0) 7.0 (3.0, 13.0)
 2–3 times each week 4.0 (2.0, 7.4) 3.0 (1.0, 7.0) 5.0 (2.0, 9.0) 5.0 (2.0, 10.5)
 4 times or more each week 5.0 (1.5, 9.2) 4.0 (1.0, 8.6) 6.2 (2.1, 10.0) 6.2 (3.5, 10.5)
Level of assistance required with basic daily activities <0.001 <0.001 0.002 <0.001
 None 6.0 (3.0, 10.0) 4.0 (1.0, 8.5) 6.3 (3.0, 11.0) 6.0 (3.0, 12.0)
 Some 13.8 (8.0, 18.4) 13.0 (7.0, 22.0) 11.5 (7.0, 16.6) 12.6 (8.4, 18.5)
 A lot/totally dependent on another person 8.1 (5.5, 14.5) 11.6 (6.0, 13.0) 11.6 (1.6, 14.3) 8.0 (1.0, 13.3)
Trust in surgical team 0.055 0.092 0.308 0.223
 Some trust - - 9.0 (5.7, 14.0) 8.7 (5.5, 13.8)
 A lot of trust 8.0 (3.0, 13.0) 5.3 (2.0, 12.0) 7.0 (4.0, 12.0) 7.0 (3.0, 13.5)
 Complete trust 6.0 (3.0, 10.0) 4.0 (1.0, 8.5) 6.3 (3.0, 11.6) 6.0 (3.0, 11.1)
Surgery for your condition <0.001 0.005 <0.001 0.006
 Perhaps be successful 9.0 (6.0, 15.0) 8.0 (3.0, 16.0) 10.0 (7.0, 16.0) 9.2 (4.0, 17.0)
 Most likely be successful 6.0 (3.0, 10.0) 5.0 (1.0, 9.0) 6.0 (3.0, 11.0) 6.0 (3.0, 11.5)
Pain anticipate in the first few days after surgery <0.001 <0.001 <0.001 0.117
 No pain 6.2 (3.6, 8.0) 3.5 (1.0, 8.2) - -
 Mild pain 5.0 (2.0, 8.0) 3.0 (0.0, 7.0) 5.3 (3.0, 9.0) 7.0 (3.0, 11.0)
 Moderate pain 6.3 (3.0, 12.0) 5.0 (2.0, 10.0) 7.0 (3.0, 12.0) 6.5 (3.0, 12.0)
 Severe pain 9.0 (5.0, 16.0) 9.0 (3.0, 19.0) 9.0 (5.0, 16.5) 7.4 (4.0, 16.0)
Pain tolerance 0.003 0.038 0.140 0.232
 Low 9.5 (5.0, 14.2) 6.0 (3.0, 13.0) 9.0 (4.9, 13.0) 7.0 (4.0, 14.0)
 Average 6.0 (3.2, 11.0) 5.0 (2.0, 10.0) 7.0 (3.0, 12.0) 7.0 (3.0, 12.0)
 High 5.0 (2.2, 9.0) 4.0 (1.0, 8.0) 6.0 (3.0, 10.8) 5.0 (3.0, 12.2)
A P value was based on the Kruskal-Wallis test.
For subgroups with less than 10 patients, they were not included in the comparison and their medians were not shown in the table.
IQR indicates interquartile range.

TABLE A3. - Association Between VAS/MME and Anticipation/Tolerance of Pain
Male
Pain Anticipate in the First Few Days After Surgery Pain Tolerance
Variable No Pain Mild Pain Moderate Pain Severe Pain P No/Low Average High P
VAS first 24 h, mean (SD) 1.3 (1.8) 1.8 (2.0) 2.8 (2.0) 3.6 (2.0) <0.001 3.5 (2.2) 2.4 (2.1) 2.6 (2.0) 0.012
 N 22 100 197 49 42 219 113
VAS 24–48 h, mean (SD) 1.6 (1.7) 1.8 (1.8) 2.8 (2.0) 3.3 (1.7) <0.001 2.9 (2.2) 2.5 (1.9) 2.6 (2.0) 0.526
 N 11 62 178 43 38 167 94
VAS 48–72 h, mean (SD) 0.6 (0.9) 1.5 (1.6) 2.2 (2.0) 2.5 (2.1) 0.021 2.1 (1.9) 1.8 (1.7) 2.5 (2.2) 0.076
 N 7 42 127 35 27 122 65
MME first 24 h, median (IQR) 0.0 (0.0, 12.5) 4.0 (0.0, 24.8) 10.0 (0.0, 34.4) 34.4 (6.5, 72.0) <0.001 9.8 (0.0, 55.2) 8.1 (0.0, 34.4) 8.0 (0.0, 39.5) 0.661
 N 29 121 239 55 51 259 141
MME 24–48 h, median (IQR) 0.0 (0.0, 0.0) 0.0 (0.0, 16.0) 4.0 (0.0, 24.0) 24.0 (0.0, 48.0) <0.001 5.3 (0.0, 33.0) 0.0 (0.0, 24.0) 6.3 (0.0, 24.0) 0.465
 N 21 92 221 51 46 226 118
MME 48–72 h, median (IQR) 0.0 (0.0, 16.0) 0.0 (0.0, 8.0) 0.0 (0.0, 16.0) 8.0 (0.0, 36.0) 0.006 8.0 (0.0, 26.0) 0.0 (0.0, 11.3) 0.0 (0.0, 24.0) 0.014
 N 13 63 185 49 37 177 100
Length of stay, median (IQR), d 1.4 (1.0, 3.9) 2.1 (1.0, 5.0) 4.1 (2.3, 6.0) 5.5 (4.0, 7.8) <0.001 4.7 (2.2, 7.9) 3.9 (1.8, 5.8) 3.9 (1.9, 5.8) 0.127
 N 28 119 234 52 48 253 138
Clavien-Dindo > 0, n (%) 8 (28.6) 45 (37.8) 108 (46.0) 31 (58.5) 0.024 29 (59.2) 100 (39.4) 66 (47.8) 0.022
Female
Pain anticipate in the First Few Days After Surgery Pain Tolerance
Variable No Pain Mild Pain Moderate Pain Severe Pain P No/Low Average High P
VAS first 24 h, mean (SD) 1.4 (2.6) 1.8 (1.8) 3.1 (2.2) 3.2 (2.1) <0.001 3.5 (2.3) 2.7 (2.1) 2.8 (2.3) 0.037
 N 5 90 230 75 58 221 126
VAS 24–48 h, mean (SD) 0.9 (1.2) 1.8 (2.1) 2.8 (2.3) 3.6 (2.5) <0.001 3.4 (2.2) 2.7 (2.4) 2.6 (2.3) 0.216
 N 2 56 168 57 41 150 94
VAS 48–72 h, mean (SD) 0.0 (0.0) 1.5 (1.7) 2.8 (2.3) 2.9 (2.0) 0.005 2.5 (1.9) 2.6 (2.2) 2.5 (2.3) 0.985
 N 2 30 93 42 25 89 54
MME first 24 h, median (IQR) 0.0 (0.0, 0.0) 1.6 (0.0, 13.0) 12.0 (0.0, 29.4) 15.6 (0.0, 30.8) <0.001 14.5 (4.0, 30.4) 8.0 (0.0, 27.2) 8.1 (0.0, 27.3) 0.121
 N 9 109 272 86 65 264 153
MME 24–48 h, median (IQR) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.0 (0.0, 16.0) 8.0 (0.0, 28.0) <0.001 0.0 (0.0, 16.0) 0.0 (0.0, 12.0) 0.0 (0.0, 15.2) 0.516
 N 5 83 225 74 53 215 122
MME 48–72 h, median (IQR) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.0 (0.0, 15.0) 0.0 (0.0, 24.0) 0.022 0.0 (0.0, 20.0) 0.0 (0.0, 9.0) 0.0 (0.0, 14.4) 0.812
 N 2 44 134 59 36 130 75
Length of stay, median (IQR), d 1.0 (1.0, 1.6) 1.9 (1.0, 3.1) 2.0 (1.1, 4.0) 3.8 (1.9, 6.0) <0.001 2.1 (1.2, 4.5) 2.0 (1.1, 4.1) 2.0 (1.1, 4.1) 0.856
 N 8 105 268 85 64 256 151
Clavien-Dindo > 0, n (%) 3 (37.5) 24 (22.9) 68 (25.3) 36 (42.9) 0.008 21 (32.8) 75 (29.4) 37 (24.3) 0.373
IQR indicates interquartile range.

TABLE A4. - Association Between VAS/MME and Coping Mechanism
Male
Trust In Surgical Team Surgery for Your Condition Amount of Information Received
Variable Some Trust A Lot of Trust Complete Trust P Perhaps Be Successful Most Likely Be Successful P Somewhat Satisfied Quite Satisfied Very Satisfied P
VAS first 24 h, mean (SD) 2.2 (2.5) 2.9 (2.1) 2.5 (2.0) 0.301 2.9 (2.3) 2.6 (2.0) 0.284 2.9 (2.1) 2.8 (2.2) 2.5 (2.0) 0.366
 N 7 95 267 40 332 16 103 254
VAS 24–48 h, mean (SD) 3.6 (2.6) 2.9 (1.9) 2.5 (1.9) 0.112 3.7 (2.1) 2.5 (1.9) 0.002 3.7 (2.7) 2.9 (1.9) 2.4 (1.9) 0.018
 N 6 75 215 30 267 14 72 212
VAS 48–72 h, mean (SD) 3.4 (4.1) 2.6 (1.9) 1.9 (1.8) 0.041 2.9 (2.5) 2.0 (1.8) 0.014 2.8 (2.5) 2.5 (2.0) 1.9 (1.8) 0.070
 N 3 59 151 26 187 12 50 152
MME first 24 h, median (IQR) 0.0 (0.0, 34.0) 6.5 (0.0, 33.6) 8.1 (0.0, 38.4) 0.653 13.7 (0.8, 37.2) 8.1 (0.0, 37.0) 0.458 14.4 (0.0, 24.8) 6.4 (0.0, 30.5) 10.1 (0.0, 40.0) 0.315
 N 7 119 321 46 403 21 123 304
MME 24–48 h, median (IQR) 0.0 (0.0, 48.0) 0.0 (0.0, 18.4) 4.0 (0.0, 27.2) 0.305 0.0 (0.0, 39.0) 2.0 (0.0, 24.0) 0.511 0.0 (0.0, 40.0) 0.0 (0.0, 24.0) 2.0 (0.0, 24.0) 0.816
 N 7 100 280 39 350 19 103 267
MME 48–72 h, median (IQR) 20.0 (0.0, 40.0) 0.0 (0.0, 24.0) 0.0 (0.0, 14.5) 0.143 0.0 (0.0, 40.0) 0.0 (0.0, 16.0) 0.207 4.5 (0.0, 48.0) 0.0 (0.0, 32.0) 0.0 (0.0, 12.0) 0.115
 N 5 80 227 33 281 15 78 221
Length of stay, median (IQR), d 3.5 (1.9, 4.2) 3.9 (1.3, 6.2) 3.9 (1.9, 5.9) 0.966 4.2 (1.8, 7.3) 3.9 (1.9, 5.8) 0.268 3.7 (2.2, 8.0) 3.8 (1.1, 5.8) 4.0 (2.0, 6.0) 0.266
 N 7 116 312 45 392 20 122 296
Clavien-Dindo > 0, n (%) 2 (28.6) 55 (47.0) 135 (43.1) 0.546 23 (51.1) 172 (43.7) 0.340 8 (40.0) 48 (39.7) 140 (46.8) 0.375
Female
Trust in Surgical Team Surgery for Your Condition Amount of Information Received
Variable Some Trust A Lot of Trust Complete Trust P Perhaps Be Successful Most Likely e Successful P Somewhat Satisfied Quite Satisfied Very Satisfied P
VAS first 24 h 3.7 (2.1) 3.1 (2.3) 2.6 (2.1) 0.016 3.5 (2.6) 2.7 (2.2) 0.029 4.1 (2.2) 2.8 (2.2) 2.8 (2.2) 0.118
 N 18 150 236 41 363 13 131 258
VAS 24–48 h 3.0 (2.6) 2.9 (2.5) 2.7 (2.2) 0.715 3.7 (2.7) 2.6 (2.3) 0.013 4.6 (3.0) 2.8 (2.3) 2.6 (2.2) 0.010
 N 17 113 155 33 250 14 80 190
VAS 48–72 h 1.1 (1.9) 2.7 (2.3) 2.5 (2.0) 0.168 3.5 (2.4) 2.4 (2.1) 0.048 2.4 (2.6) 2.7 (2.2) 2.5 (2.1) 0.803
 N 7 75 85 18 145 13 50 104
MME first 24 h 12.9 (6.6, 26.5) 10.1 (0.0, 29.5) 8.1 (0.0, 27.2) 0.379 9.0 (0.0, 32.0) 9.2 (0.0, 27.6) 0.463 13.4 (0.0, 48.2) 11.6 (0.0, 28.7) 8.0 (0.0, 27.0) 0.424
 N 24 180 278 51 426 22 152 305
MME 24–48 h 0.0 (0.0, 24.0) 0.0 (0.0, 8.8) 0.0 (0.0, 15.6) 0.745 0.0 (0.0, 34.4) 0.0 (0.0, 12.0) 0.158 32.5 (0.0, 50.7) 0.0 (0.0, 8.0) 0.0 (0.0, 15.2) 0.007
 N 20 149 220 41 344 16 123 249
MME 48–72 h 0.0 (0.0, 0.0) 0.0 (0.0, 10.0) 0.0 (0.0, 15.5) 0.361 0.0 (0.0, 28.0) 0.0 (0.0, 12.8) 0.975 9.5 (0.0, 52.0) 0.0 (0.0, 12.0) 0.0 (0.0, 12.8) 0.095
 N 9 103 128 27 209 14 69 156
Length of stay (d) 1.9 (1.1, 3.1) 2.3 (1.2, 4.1) 1.9 (1.1, 4.1) 0.086 2.0 (1.1, 3.1) 2.0 (1.1, 4.1) 0.737 3.2 (1.0, 6.2) 2.0 (1.1, 3.3) 2.0 (1.1, 4.1) 0.323
 N 24 174 273 50 416 22 148 298
Clavien-Dindo > 0, n (%) 8 (33.3) 53 (30.5) 73 (26.7) 0.601 13 (26.5) 117 (28.1) 0.822 12 (54.5) 41 (27.7) 81 (27.2) 0.022
IQR indicates interquartile range.

Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.