Research Article | Open Access
The Influence of Psychiatric Comorbidity on Inpatient Outcomes following Distal Humerus Fractures
Background. The influence of psychiatric comorbidity on outcomes following inpatient management of upper extremity fractures is poorly understood. Methods. The National Hospital Discharge Survey was queried to identify patients admitted to US hospitals with distal humerus fractures between 1990 and 2007. Patients were subdivided into 5 groups: depression, anxiety, schizophrenia, dementia, and no psychiatric comorbidity. Multivariable logistic regression analysis identified independent risk factors for adverse events, requirement of blood transfusion, and discharge to another inpatient facility. Results. A cohort representative of 526,185 patients was identified as having a distal humerus fracture. Depression, anxiety, and dementia were independently associated with higher odds of in-hospital adverse events (). Depression was associated with higher odds of inpatient blood transfusion (). Depression, schizophrenia, and dementia were associated with higher odds of nonroutine discharge to another inpatient facility (). Patients with a diagnosis of schizophrenia had a mean of 12 () more days of care than patients with no psychiatric comorbidity. Discussion. Patients with comorbid psychiatric illness who are admitted to hospitals with distal humerus fractures are at increased risk of inpatient adverse events and posthospitalization care.
Psychiatric comorbidity is associated with longer hospital stays, higher risk of suboptimal outcomes, and increased resource utilization among patients undergoing inpatient surgery [1–7]. Major depressive disorder and anxiety are the most common psychiatric diagnoses [1–5]. Schizophrenia is less common, with an estimated prevalence of one percent , but is associated with significant cognitive impairment . Dementia is present in approximately six percent of the population over 60 years of age . The rate of elderly individuals with psychiatric disorders is projected to double by 2030 .
In orthopaedics, psychiatric comorbidity has been associated with worse long-term outcomes (i.e., pain and disability) following total knee arthroplasty , major spine surgery , and orthopaedic trauma . Psychiatric comorbidity with concurrent antipsychotic and antidepressant use are known risk factors for extremity fractures [14–16], postulated to be a result of decreased bone mineral density. While prior research in lower extremity fractures has demonstrated longer hospital stays, more in-hospital adverse events, and lower rates of discharge to home among patients with psychiatric comorbidity , there is a paucity of data on the influence of psychiatric illness on acute, inpatient outcomes among patients admitted with upper extremity fractures. This study sought to evaluate the influence of psychiatric illness on length of stay, mortality, in-hospital adverse events, requirement for blood transfusion, and nonroutine discharge to another inpatient facility among patients admitted with distal humerus fractures. Knowledge of the effects of psychiatric illness on inpatient outcomes may be used for planning and resource allocation for orthopaedic patients with psychiatric illness.
2. Materials and Methods
2.1. Data Source
The National Hospital Discharge Survey (NHDS) database, developed by the National Center for Health Statistics , was used to evaluate the influence of psychiatric comorbidity on outcomes following distal humerus fractures. The NHDS is a publically available survey providing demographic and medical data for inpatients discharged from nonfederal, short-stay hospitals in the United States . It is the principal database used by the US government for monitoring hospital use and is thought to be the most comprehensive of all inpatient surgical databases in use . The survey, which began in 1965 and has been collected annually since then, uses International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes  for classifying medical diagnoses and procedures. Using a stratified, multistage probability design, the NHDS collects demographic information (age, gender, and race), expected source of payment (insurance status), medical information of up to seven discharge diagnoses and up to four procedures, length of care, hospital size, US region, and inpatient outcomes including discharge destination . The NHDS uses a complex three-stage probability design to ensure an unbiased national sampling of inpatient records including inflation by reciprocals of the probabilities of sample selection and adjustment for no response and population weighting ratio adjustments . Because the NHDS is a publically available database with no patient identifying information, this study did not require approval by the institutional review board.
2.2. Study Population
Using ICD-9-CM codes, we identified all patients admitted in the United States with a distal humerus fracture between 1990 and 2007. Discharges with a diagnosis code (ICD-9-CM) of closed fracture of lower end of humerus (812.4x) or open fracture of lower end of humerus (812.5x) were identified using previously described techniques . Patients managed surgically with open reduction and internal fixation (ORIF) or closed reduction and internal fixation (CRIF) were identified using ICD-9 procedure codes 79.3x and 79.1x, respectively. To analyze their influence on inpatient outcomes, psychiatric comorbidities were divided into four groups: depression (ICD-9-CM 296.2, 296.3, 296.5, 296.9, 300.4, 301.12, 309.0, and 311.x), anxiety (ICD-9-CM 300.0x, 309.24, and 309.28), schizophrenia (ICD-9-CM 295.x), and dementia (ICD-9-CM 290.x). After obtaining our study population, demographic variables were collected including age, sex, primary diagnosis, type of fracture, prevalence of comorbidities, length of stay, and discharge destination. The complication screening package  was used to determine the incidence of complications and the variable of adverse event was created based on the variables: shock (998.0), bleeding (998.1), acute postoperative infection (998.5), acute postoperative anemia (285.1), acute renal failure (584), acute myocardial infarction (410), pulmonary embolism (415.1), induced mental disorder (293), pneumonia (480–486), pulmonary insufficiency (518.5), deep venous thrombosis (453.4), intubation (96.xx), and transfusion of blood (99.x).
We assumed a normal distribution of the data because of the large sample size. Differences between categorical variables were compared using the Pearson chi-square test and the independent-samples -tests were used to compare differences between continuous variables. To analyze whether depression, anxiety, schizophrenia, or dementia were independent predictors of a negative in-hospital outcome (adverse events, requirement for blood transfusion, or discharge to inpatient facility), all variables present in at least 2% of the population  were included in a multivariable binary logistic regression model; for in-hospital adverse events, a 1% cutoff was used due to their lower rates of occurrence, as previously described . The dichotomous variables were (1) presence of adverse events, (2) need for blood transfusion, and (3) discharge to inpatient facility. The multivariable regression model allowed us to control for potential confounders and isolate the effect of psychiatric illness on inpatient outcomes. Notably, the cooccurrence of psychiatric comorbidity was rare with depression and anxiety in 33 patients (0.00%), depression and schizophrenia in 46 patients (0.01%), and no cooccurrence of other psychiatric comorbidities. Covariates accounted for in the regression model included gender, age, region of the country, and preexisting comorbidities (anemia, obesity, diabetes mellitus, hypertension, congestive heart failure, coronary artery disease, atrial fibrillation, prior myocardial infarction, osteoporosis, connective tissue disease, thyroid disease, and chronic obstructive pulmonary disease). Odds ratios and confidence intervals were calculated to assess the association between psychiatric comorbidities and inpatient outcomes. To correct for multiple comparisons, a value of <0.001 was used to define statistical significance, as previously described . All data were analyzed using the statistical package for social sciences [SPSS] software version 20 (Chicago, IL, USA).
A cohort representative of 526,185 discharges with a diagnosis of distal humerus fracture, between 1990 and 2007, was retrieved from the NHDS database. The prevalence of depression was 1.27%, anxiety was 0.42%, schizophrenia was 0.2%, and dementia was 0.36%. The mean age of the cohort was 30.3 years (95% CI, 27.6 to 33.0 years) while those with psychiatric illness were significantly older () (Table 1). Females comprised 50.2% of the total cohort, 67.5% of patients with depression and greater than 80% of patients with either dementia or anxiety (Table 1). The most common diagnosis was closed supracondylar humerus fracture (ICD-9-CM 812.41), followed by closed fracture of unspecified part of humerus (812.4), and closed fracture of lateral condyle of humerus (812.42). Length of hospital stay was significantly longer for patients with schizophrenia (16.12 days) compared with nonpsychiatric patients (3.96; ) (Table 1). In-hospital mortality was lower in patients with depression (), but not statistically significantly different between patients with anxiety, dementia, or schizophrenia and no psychiatric comorbidity (Table 1).
The prevalence of comorbidities and adverse events with bivariate analyses are listed in Tables 2 and 3, respectively. Hypertensive disease was the most common comorbidity at 9.28% followed by diabetes mellitus at 4.75%. Psychiatric comorbidity was associated with a higher rate of inpatient adverse events (depression, 23.27%, anxiety, 7.21%, and dementia, 24.81%) compared with no psychiatric comorbidity (6.23%) (Tables 1 and 3). For patients with depression and dementia, the most common adverse event was pneumonia at 10.99% and 23.43%, respectively. Multivariable logistic regression analysis showed dementia (OR 5.024, range: 4.522 to 5.583, ), depression (OR 4.742, range: 4.476 to 5.024, ), and those treated with ORIF (OR 1.499, range: 1.466 to 1.533, ) to be independently associated with higher odds of inpatient adverse events, whereas there was a lower odds ratio of adverse event among those treated with CRIF (OR 0.115, range: 0.110 to 0.121, ) (model fit: for omnibus test of model coefficients: = 4746, , Nagelkerke = 0.0663; Table 4).
Omnibus , .|
Among the total cohort, 2.1% of patients experienced acute postoperative anemia. In multivariable logistic regression analysis, patients with depression (OR 5.334, range: 4.834 to 5.886, ) and those treated with ORIF (OR 2.75, range: 2.618 to 2.884, ) had significantly higher odds of blood transfusion, while patients with schizophrenia (OR 0.033, range: 0.002 to 0.525, ), dementia (OR 0.452, range: 0.256 to 0.797, ), and those treated with CRIF (OR 0.146, range: 0.133 to 0.161, ) had a lower odds ratio of requiring blood transfusion (model fit: omnibus test of model coefficients: = 4746, , Nagelkerke = 0.2062; Table 5).
Omnibus , . |
Patients with comorbid mental illness experienced a higher rate of discharge to inpatient short- or long-term facility (depression, 38.9%, schizophrenia, 44.6%, and dementia, 69.3%) compared with patients who had no psychiatric comorbidity (9.5%). In multivariable regression analysis, dementia (OR 20.609, range: 18.674 to 22.745, ), schizophrenia (OR 7.232, range: 6.708 to 8.163, ), and depression (OR 5.909, range: 5.621 to 6.212, ) were independently associated with nonroutine discharge to another inpatient facility, while patients treated surgically with ORIF (OR 0.785, range: 0.771 to 0.800, ) or CRIF (OR 0.197, range: 0.190 to 0.203, ) had a lower odds ratio of nonroutine discharge (model fit: omnibus test of model coefficients: = 4717, , Nagelkerke = 0.482; Table 6).
Omnibus , . |
Psychiatric comorbidity is a common cause of disability, a known contributor to poor quality of life and increased healthcare resource utilization [25–27]. Previously, groups have demonstrated poor long-term outcomes after orthopaedic surgery for patients with psychiatric illness . However, reports are conflicting on whether psychiatric comorbidities affect inpatient outcomes in patients with musculoskeletal injuries, as some studies have demonstrated decreased rates of major in-hospital complications and mortality . The influence of psychiatric comorbidities on lower extremity fractures has previously been investigated . In this study, we used nationally representative data collected over a 17-year period to evaluate the effect of psychiatric comorbidity on inpatient adverse events, requirement for blood transfusion, and discharge status for patients admitted with distal humerus fractures.
The findings of this study demonstrate that, in patients admitted with distal humerus fractures, diagnoses of depression and dementia are associated with higher odds of in-hospital adverse events. This finding is consistent with previous studies conducted by Hu et al. , Bot et al. , and Beresnevait et al.  who found increased complication rates among patients with psychiatric illness who are undergoing surgery. Of note, our study demonstrated a decreased risk of adverse events for patients with schizophrenia, which is contradictory to previous findings . One reason for this discrepancy could be the small sample size of only 1,007 patients. Another reason could be due to the limited coding available in the database. The NHDS only allows for 7 diagnosis codes per weighted case, which may limit the amount of comorbidities and adverse events listed.
This study found depression to be associated with increased odds of requirement for blood transfusion in patients with distal humerus fractures. A possible explanation for this finding is that medications used for the treatment of depression, such as selective serotonin reuptake inhibitors, inhibit platelet activity and could result in increased bleeding [29, 30]. It is also possible that symptoms of depression, such as fatigue, may mimic symptoms of anemia leading to a higher rate of transfusion. Paradoxically, patients with anxiety had increased rates of postoperative anemia but lower rates of blood transfusion. In our study, patients with anxiety had the shortest hospital stay at 2.49 days, which may have limited their treatment options and could explain their decreased rate of transfusion despite increased rates of anemia.
This study demonstrated an increased risk for nonroutine discharge to another inpatient facility for patients with depression, schizophrenia, and dementia after hospitalization with a distal humerus fracture. In addition, in-hospital days of care were significantly greater for patients with depression and schizophrenia. These findings correlate with prior studies showing psychiatric illnesses, in patients with orthopaedic conditions, are independent risk factors for increased healthcare resource utilization [25–27].
Interestingly, mortality rates were lower among patients with depression. This finding is in line with studies by previous groups and has been postulated to be due to increased attention from health care professionals due to heightened fear and awareness of pain and symptoms by these patients . While the mechanism of fracture is unknown due to limitations of the database, our results demonstrate that patients with no comorbid psychiatric diagnoses were significantly younger. It is possible this cohort sustained a distal humerus fracture from a high-energy mechanism, possibly as part of a polytrauma, which may explain the higher morbidity.
The use of the NHDS database for this study allowed for a national analysis of a large number of patients over a 17-year period. However, despite the benefits of using a large, national database , this type of data collection poses several limitations . Diagnosis codes and procedure codes were collected to compose all parts of the statistical analysis. Misclassification of ICD-9-CM codes poses an intrinsic source of error. However, misclassifications are likely distributed evenly among groups, preventing them from affecting our statistical analysis . Additionally, the database only allows for seven diagnosis codes and four procedure codes per entry. As a result, the prevalence of comorbid conditions and adverse events may be underreported, as the prevalences found in this study are lower than other national estimates of depression, anxiety, and dementia [35–37]. This is similar to multiple prior administrative database studies [17, 25]. Another potential cause of the lower prevalence may be that patients with distal humerus fractures who have psychiatric comorbidities may not be admitted to the hospital and are selected to receive conservative treatment from initial presentation. It is also possible that the lower numbers among patients with distal humerus fractures and psychiatric comorbidities may be due to inequities in access to care, or they may be neglected and not present to the hospital or they may choose not to receive treatment at all. Regardless of the cause, because all cases undergo the same data collection process, potential underreporting should be equally distributed. Another limitation is that the database only provides inpatient data, so complications that arise after discharge are not obtainable. What is more, the large sample size may have resulted in the identification of statistically significant differences that may not be clinically relevant. Additionally, calculation of odds ratios by binomial logistic regression has been shown to result in an overestimate of effect when the outcome occurs in greater than 10 percent of the cohort  and thus should be interpreted as a trend instead of an absolute effect size. Finally, the influence of treatment status among patients with psychiatric illness is unknown, as medications are not listed in the database. Therefore, it is impossible to discern whether treatment of psychiatric illness influences outcomes in patients admitted with distal humerus fractures.
In conclusion, this study utilized the NHDS to analyze US national data over a 17-year period and showed that psychiatric illness poses an increased risk of in-hospital adverse events, requirement for blood transfusion, and nonroutine discharge to an inpatient facility for patients admitted with distal humerus fractures. These findings may aid healthcare providers in appropriately allocating resources to orthopaedic patients with psychiatric illness.
This study was conducted using the National Hospital Discharge Survey, a publically available database conducted by the Centers for Disease Control and Prevention, in which all data are deidentified and available for public use. As a result, this study was exempt from approval by the institutional review board.
The authors report no financial, consultant, institutional, or other relationships that may lead to bias or competing interests.
- J. de Miguel-Díez, P. Carrasco-Garrido, J. Rejas-Gutierrez et al., “The influence of heart disease on characteristics, quality of life, use of health resources, and costs of COPD in primary care settings,” BMC Cardiovascular Disorders, vol. 10, article 8, 2010.
- C. Enger, L. Weatherby, R. F. Reynolds, D. B. Glasser, and A. M. Walker, “Serious cardiovascular events and mortality among patients with schizophrenia,” The Journal of Nervous and Mental Disease, vol. 192, no. 1, pp. 19–27, 2004.
- L. J. Graven and J. Grant, “The impact of social support on depressive symptoms in individuals with heart failure,” The Journal of Cardiovascular Nursing, vol. 28, no. 5, pp. 429–443, 2013.
- A. H. Jakobsen, L. Foldager, G. Parker, and P. Munk-Jørgensen, “Quantifying links between acute myocardial infarction and depression, anxiety and schizophrenia using case register databases,” Journal of Affective Disorders, vol. 109, no. 1-2, pp. 177–181, 2008.
- C. B. Nemeroff and P. J. Goldschmidt-Clermont, “Heartache and heartbreak-the link between depression and cardiovascular disease,” Nature Reviews Cardiology, vol. 9, no. 9, pp. 526–539, 2012.
- B. Ruo, J. S. Rumsfeld, M. A. Hlatky, H. Liu, W. S. Browner, and M. A. Whooley, “Depressive symptoms and health-related quality of life: the Heart and Soul study,” The Journal of the American Medical Association, vol. 290, no. 2, pp. 215–221, 2003.
- M. Beresnevait, R. Benetis, G. J. Taylor, K. Jurnien, Š. Kinduris, and V. Barauskien, “Depression predicts perioperative outcomes following coronary artery bypass graft surgery,” Scandinavian Cardiovascular Journal, vol. 44, no. 5, pp. 289–294, 2010.
- J. Perälä, J. Suvisaari, S. I. Saarni et al., “Lifetime prevalence of psychotic and bipolar I disorders in a general population,” Archives of General Psychiatry, vol. 64, no. 1, pp. 19–28, 2007.
- H. Kitchen, D. Rofail, L. Heron, and P. Sacco, “Cognitive impairment associated with schizophrenia: a review of the humanistic burden,” Advances in Therapy, vol. 29, no. 2, pp. 148–162, 2012.
- C. F. Reynolds III, P. Cuijpers, V. Patel et al., “Early intervention to reduce the global health and economic burden of major depression in older adults,” Annual Review of Public Health, vol. 33, pp. 123–135, 2012.
- D. A. Fisher, B. Dierckman, M. R. Watts, and K. Davis, “Looks good but feels bad: factors that contribute to poor results after total knee arthroplasty,” The Journal of Arthroplasty, vol. 22, no. 6, supplement 2, pp. 39–42, 2007.
- C. L. Seebach, M. Kirkhart, J. M. Lating et al., “Examining the role of positive and negative affect in recovery from spine surgery,” Pain, vol. 153, no. 3, pp. 518–525, 2012.
- R. J. Crichlow, P. L. Andres, S. M. Morrison, S. M. Haley, and M. S. Vrahas, “Depression in orthopaedic trauma patients: prevalence and severity,” Journal of Bone and Joint Surgery A, vol. 88, no. 9, pp. 1927–1933, 2006.
- G. Cizza, S. Primma, M. Coyle, L. Gourgiotis, and G. Csako, “Depression and osteoporosis: a research synthesis with meta-analysis,” Hormone and Metabolic Research, vol. 42, no. 7, pp. 467–482, 2010.
- T. Kishimoto, M. De Hert, H. E. Carlson, P. Manu, and C. U. Correll, “Osteoporosis and fracture risk in people with schizophrenia,” Current Opinion in Psychiatry, vol. 25, no. 5, pp. 415–429, 2012.
- Y. Zhao, L. Shen, and H.-F. Ji, “Alzheimer's disease and risk of hip fracture: a meta-analysis study,” The Scientific World Journal, vol. 2012, Article ID 872173, 5 pages, 2012.
- M. E. Menendez, V. Neuhaus, A. G. J. Bot, M. S. Vrahas, and D. Ring, “Do psychiatric comorbidities influence inpatient death, adverse events, and discharge after lower extremity fractures?” Clinical Orthopaedics and Related Research, vol. 471, no. 10, pp. 3336–3348, 2013.
- Centers for Disease Control and Prevention, National Hospital Discharge Survey, August 2013–June 2014, http://www.cdc.gov/nchs/nhds.htm.
- C. Dennison and R. Pokras, “Design and operation of the national hospital discharge survey: 1988 redesign,” Vital and Health Statistics, no. 39, pp. 1–42, 2000.
- CDC/National Center for Health Statistics, International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), 2013, http://www.cdc.gov/nchs/icd/icd9cm.htm.
- S. G. Memtsoudis, A. González Della Valle, M. C. Besculides, L. Gaber, and T. P. Sculco, “In-hospital complications and mortality of unilateral, bilateral, and revision TKA: based on an estimate of 4,159,661 discharges,” Clinical Orthopaedics and Related Research, vol. 466, no. 11, pp. 2617–2627, 2008.
- O. Stundner, M. Kirksey, Y. L. Chiu et al., “Demographics and perioperative outcome in patients with depression and anxiety undergoing total joint arthroplasty: a population-based study,” Psychosomatics, vol. 54, no. 2, pp. 149–157, 2013.
- L. I. Iezzoni, J. Daley, T. Heeren et al., “Using administrative data to screen hospitals for high complication rates,” Inquiry, vol. 31, no. 1, pp. 40–55, 1994.
- S. Lemeshow, D. Teres, J. Klar, J. S. Avrunin, S. H. Gehlbach, and J. Rapoport, “Mortality probability models (MPM II) based on an international cohort of intensive care unit patients,” JAMA, vol. 270, no. 20, pp. 2478–2486, 1993.
- A. G. J. Bot, M. E. Menendez, V. Neuhaus, and D. Ring, “The influence of psychiatric comorbidity on perioperative outcomes after shoulder arthroplasty,” Journal of Shoulder and Elbow Surgery, vol. 23, no. 4, pp. 519–527, 2014.
- M. M. Vissers, J. B. Bussmann, J. A. N. Verhaar, J. J. V. Busschbach, S. M. A. Bierma-Zeinstra, and M. Reijman, “Psychological factors affecting the outcome of total hip and knee arthroplasty: a systematic review,” Seminars in Arthritis and Rheumatism, vol. 41, no. 4, pp. 576–588, 2012.
- M. S. Walid and J. S. Robinson Jr., “Economic impact of comorbidities in spine surgery,” Journal of Neurosurgery: Spine, vol. 14, no. 3, pp. 318–321, 2011.
- C. J. Hu, C. C. Liao, C. C. Chang, C. H. Wu, and T. L. Chen, “Postoperative adverse outcomes in surgical patients with dementia: a retrospective cohort study,” World Journal of Surgery, vol. 36, no. 9, pp. 2051–2058, 2012.
- A. Dietrich-Muszalska, J. Rabe-Jablonska, P. Nowak, and B. Kontek, “The first- and second-generation antipsychotic drugs affect ADP-induced platelet aggregation,” World Journal of Biological Psychiatry, vol. 11, no. 2, pp. 268–275, 2010.
- A. Flöck, A. Zobel, G. Bauriedel et al., “Antiplatelet effects of antidepressant treatment: a randomized comparison between escitalopram and nortriptyline,” Thrombosis Research, vol. 126, no. 2, pp. e83–e87, 2010.
- J. I. Escobar, M. Gara, H. Waitzkin, R. C. Silver, A. Holman, and W. Compton, “Dsm-IV hypochondriasis in primary care,” General Hospital Psychiatry, vol. 20, no. 3, pp. 155–159, 1998.
- D. D. Bohl, B. A. Basques, N. S. Golinvaux, M. R. Baumgaertner, and J. N. Grauer, “Nationwide inpatient sample and national surgical quality improvement program give different results in hip fracture studies,” Clinical Orthopaedics and Related Research, vol. 472, no. 6, pp. 1672–1680, 2014.
- S. G. Memtsoudis, “Limitations associated with the analysis of data from administrative databases,” Anesthesiology, vol. 111, no. 2, article 449, 2009.
- V. L. Tseng, F. Yu, F. Lum, and A. L. Coleman, “Risk of fractures following cataract surgery in medicare beneficiaries,” The Journal of the American Medical Association, vol. 308, no. 5, pp. 493–501, 2012.
- R. C. Kessler, W. T. Chiu, O. Demler, K. R. Merikangas, and E. E. Walters, “Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication,” Archives of General Psychiatry, vol. 62, no. 6, pp. 617–627, 2005.
- R. C. Kessler, S. Aguilar-Gaxiola, J. Alonso et al., “The global burden of mental disorders: an update from the WHO World Mental Health (WMH) surveys,” Epidemiologia e Psichiatria Sociale, vol. 18, no. 1, pp. 23–33, 2009.
- C. P. Ferri, M. Prince, C. Brayne et al., “Global prevalence of dementia: a Delphi consensus study,” The Lancet, vol. 366, no. 9503, pp. 2112–2117, 2005.
- M. E. Menendez, V. Neuhaus, A. G. J. Bot, D. Ring, and T. D. Cha, “Psychiatric disorders and major spine surgery: epidemiology and perioperative outcomes,” Spine, vol. 39, no. 2, pp. E111–E122, 2014.
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