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Impact of Comorbid Disease on Length of Hospitalization in Spine Fusion Patients: An HCUP-US-NIS Study

Article Information

Zachary Sanford, Andrew Broda, Elizabeth Keller, Justin Turcotte*, Chad Patton

Anne Arundel Medical Center Orthopedics, Annapolis, MD, United States

*Corresponding Author: Justin Turcotte, Anne Arundel Medical Center, 2000 Medical Parkway, Suite 101 Annapolis, MD 21401, United States

Received: 25 November 2019; Accepted: 07 December 2019; Published: 16 December 2019

Citation:

Zachary Sanford, Andrew Broda, Elizabeth Keller, Justin Turcotte, Chad Patton. Impact of Comorbid Disease on Length of Hospitalization in Spine Fusion Patients: An HCUP-US-NIS Study. Journal of Spine Research and Surgery 1 (2019): 048-059.

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Abstract

Introduction: The following is a study of the impact of comorbid conditions on hospital length of stay following spinal fusion.

Methods: Surgeries were identified from the 2016 Healthcare Cost and Utilization Project National Inpatient Sample (HCUP-US-NIS) by Medicare Severity Diagnosis Related Group (MS-DRG) codes and subdivided for analysis by fusion location and procedure approach. Length of stay was evaluated in relation to comorbid disease status, fusion location, and surgical technique. Comorbidities of interest included hypothyroidism, diabetes mellitus, hypertension, hyperlipidemia, anxiety, obesity, chronic obstructive pulmonary disease, osteoarthritis, rheumatoid arthritis, major depression, coronary atherosclerosis, arrhythmia, congestive heart failure, osteoporosis, stroke, and transient ischemic attack. Patients hospitalized longer than two months were excluded from this analysis.

Results: 185,216 patients undergoing an inpatient spinal fusion were identified (Cervical 32,753, Cervicothoracic 2,633, Thoracic 2,817, Thoracolumbar 4,761, Lumbar 32,316, Lumbosacral 17,326). Each comorbid disease was found to significantly increase the length of hospital stay for at least one procedure location (p<.05), with transient ischemic attack (8.5 days in cervicothoracic cases), arrhythmia (5.4 days in thoracic cases), and chronic heart failure (4.8 days in cervicothoracic cases) associated with substantially increased duration of hospitalization. Chronic heart failure (β 2.85, SE 0.11, p <.001), stroke (β 3.05, SE 0.08, p <.001), and osteoarthritis (β 2.12, SE 0.41, p <.001) demonstrated strong positive association with increases in length of peroperative hospitalization.

 Conclusion: Preoperative comorbidities contribute variably to the length of post-spinal fusion hospital stay. With increasing trends towards predictive modeling in healthcare outcomes these conditions represent important factors for consideration in surgical planning.

Keywords

Spinal Fusion; Hospitalization; Comorbidity

Spinal Fusion articles, Hospitalization articles, Comorbidity articles

Article Details

1. Introduction

Spinal surgery represents a growing proportion of total surgical cases performed globally, the majority of which occur within the United States [1]. As the prevalence of spine-related pathologies continue to increase, addressing the burdens placed on the healthcare system as a result of this expanding surgical case volume will require better understanding of the modifiable cost drivers of spine care. Among spinal surgeries, fusion procedures are the most frequently performed and have more than doubled in number since the late 1990s [2-5]. Mean length of hospital stay (LOS) following fusion procedures is reported between 3-7 days, with an average hospitalization of approximately 3-4 days [6-8]. Still, spinal fusion represents the procedure with greatest aggregate hospital costs incurred across all inpatient surgeries, according to previous reports by the Healthcare Cost and Utilization Project (HCUP) [5]. LOS reduction initiatives for spinal fusion may yield substantial benefits to healthcare delivery networks. A multitude of comorbidities have been shown to impact LOS to varying degrees for patients undergoing spinal fusion [6, 9, 10]. Understanding which of these factors contributes most to prolonged hospitalization is important for optimizing patient care and determining appropriate hospital resource allocation. The following presents retrospective review of the 2016 Healthcare Cost and Utilization Project National Inpatient Sample (HCUP-US-NIS) database examines the relationship between various comorbid conditions and duration of postoperative hospital LOS in spine fusion patients.

2. Materials and Methods

2.1 Healthcare cost and utilization project national inpatient sample (HCUP-US-NIS)

This study is a retrospective cohort analysis of secondary data (level 3 evidence). Patients were identified from the 2016 HCUP-US-NIS, the largest publicly available all-payer inpatient health care database in the United States [11]. The NIS provides national estimates of hospital inpatient stays including 46 states and the District of Colombia across 4,575 hospitals and 7,135,090 patients approximating more than 35 million hospitalizations nationally. Data encompasses a full calendar year of hospitalizations representing more than 97 percent of the United States’ population and serves as an estimate of a 20% stratified sample of discharges from community hospitals excluding rehabilitation and long-term acute care facilities. Billing data are compiled from patients with coverage provided by Medicare, Medicaid, private insurance, and the uninsured. Patient information is encoded as International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) diagnosis, procedures, and external cause of morbidity codes beginning October 1, 2015. Confidentiality is ensured with safeguards to protect the privacy of individual patients, physicians, and hospitals. Data include patient demographic characteristics, hospital characteristics, expected payment source, total charges, discharge status, length of hospital stay, and severity as well as comorbidity measures.

2.2 Inclusion criteria

Patients undergoing spinal procedures were identified by Medicare Severity Diagnosis Related Group (MS-DRG) codes 028, 029, 030, 453, 454, 455, 459, 460, 471, 472, and 473 (Table 1). A subsequent filter was applied using ICD-10-PCS codes, from which patients were included if the ICD-10-PCS code description contained the string search term “fusion.” Patients who remained in the hospital longer than two months were excluded from this study in an attempt to minimize outlier effects. The subsequent cohort was stratified by ICD-10-PCS codes and spinal fusion region including cervical (C), cervicothoracic (CT), thoracic (T), thoracolumbar (TL), lumbar (L), and lumbosacral (LS) in addition to the directionality of procedure approach either as anterior (A), combined anterior / posterior (A/P), or posterior (P).

MS-DRG #

MS-DRG Description

028

Spinal procedures with major complications or comorbidities

029

Spinal procedures with complications or comorbidities or spinal neurostimulators

030

Spinal procedures without complications or comorbidities / major complications or comorbidities

453

Combined anterior/posterior spinal fusion with major complications or comorbidities

454

Combined anterior/posterior spinal fusion with complications or comorbidities

455

Combined anterior/posterior spinal fusion without complications or comorbidities / major complications or comorbidities

459

Spinal fusion except cervical with major complications or comorbidities

460

Spinal fusion except cervical without major complications or comorbidities

471

Cervical spinal fusion with major complications or comorbidities

472

Cervical spinal fusion with complications or comorbidities

473

Cervical spinal fusion without complications or comorbidities / major complications or comorbidities 

Table 1: Medicare Severity Diagnosis Related Group (MS-DRG) codes relating to spinal fusions that were used for inclusion criteria in this study.

2.3 Comorbidity

Presence of preoperative comorbid disease was queried by ICD-10-CM codes for hypothyroidism, diabetes mellitus, hypertension, hyperlipidemia, anxiety, obesity, chronic obstructive pulmonary disease, major depression, coronary atherosclerosis, arrhythmia, chronic heart failure, osteoporosis, and nicotine dependence (Table 2). Length of hospitalization was calculated and compared based on the presence or absence of these comorbidities.

Hypertension

53,397

Major depression

15,937

I10 – Essential (primary) hypertension

48,464

f32 – Major depressive disorder, single episode

15,374

I11 – Hypertensive heart disease

542

f33 – Major depressive disorder, recurrent

563

I12 – Hypertensive chronic kidney disease

4,047

Nicotine dependence

14,879

I13 – Hypertensive heart and chronic kidney disease

251

f17 – Nicotine dependence

14,879

I15 – Secondary hypertension

55

Hypothyroidism

11,777

I16 – Hypertensive crisis

38

e01 – Iodine-deficiency related thyroid disorders and allied conditions

6

Hyperlipidemia

34,870

e02 – Subclinical iodine-deficiency hypothyroidism

5

E78 – Disorders of lipoprotein metabolism and other lipidemias

34,870

e03 – Other hypothyroidism

11,766

Diabetes mellitus

22,034

Coronary atherosclerosis,

9,589

E08 – Diabetes mellitus due to underlying condition

7

i251 – Atherosclerotic heart disease of native coronary artery

9,589

E09 – Drug or chemical induced diabetes mellitus

74

Chronic Obstructive Pulmonary Disease

8,076

E10 – Type 1 diabetes mellitus

557

j44 – Other chronic obstructive pulmonary disease

8,076

E11 – Type 2 diabetes mellitus

21,355

Osteoporosis

3,805

E13 – Other specified diabetes mellitus

41

m80 – Osteoporosis with current pathological fracture

216

Obesity

17,686

m81 – Osteoporosis without current pathological fracture

3,589

E66 – Overweight and obesity

17,686

Chronic heart failure

2,448

Anxiety

16,215

i50 – Heart failure

2,448

F41 – Other anxiety disorders

16,215

Arrhythmia

831

   

i49 – Other cardiac arrhythmias

831

Table 2:  ICD-10-CM codes used for identification of preoperative comorbid disease and associated frequencies observed among the study dataset.

2.4 Statistical analysis

Statistical analysis was performed using MATLAB version 9.3.0.713579 (R2017b), The Mathworks, Inc. (Natick, Massachusetts). Statistical significance was defined as p <.05 with a confidence interval (CI) of 95%. Two sample two-tailed Student’s T-Tests were used to compare observed increases in length of hospitalization by the presence of each comorbidity. Comparison groups were separated from fusion location (C, CT, T, TL, L, LS) and procedure approach (A, A/P, P). A multiple linear regression was performed to determine the predictive relationship between comorbidities and LOS.

3. Results

Significant increases in LOS by comorbidity were observed for hypothyroidism (C,TL,L,LS), diabetes mellitus (C,T,TL,L,LS), hypertension (C,CT,T,TL,L,LS), hyperlipidemia (C,T,TL,L,LS), anxiety (TL,L,LS), obesity (C,TL,L,LS), chronic obstructive pulmonary disease (C,CT,T,TL,LS), osteoarthritis (C,L,LS), rheumatoid arthritis (CT), major depression (C,TL,L,LS), coronary atherosclerosis (C,CT,T,TL,L,LS), arrhythmia (C,CT,T,TL,L,LS), congestive heart failure (C,CT,T,TL,L,LS), osteoporosis (C,TL,L,LS), stroke (C,CT,T,TL,L,LS), and transient ischemic attack (C,CT). A more granular analysis of the two most common procedures, cervical and lumbar fusion, follows.

3.1 Cervical spinal fusion

32,753 patients were identified who underwent cervical spinal fusion procedures. Fusion patients with concomitant chronic heart failure experienced an average additional 3-6 days of hospitalization depending on the surgical approach (82 – 150 hours, p < .001) compared to patients without a diagnosis of CHF. Other significant predictors of increased length of stay included arrhythmia (+2 days, 38 – 46 hours, p < .001 – .029), diabetes (+1 day, 16 – 26 hours, p < .001), coronary atherosclerosis (+1 day, 20 – 27 hours, p < .001  – .004), and hypertension (+1 day, 12 – 24 hours, p < .001). These increases were observed for all surgical approaches. A 0.75 day increase in LOS was observed for COPD excluding combined A/P approach (14 – 21 hours, p <.001 – .005). Minimal differences were observed by the surgical approach with the presence of osteoporosis (9 – 17 hours, p < .001 – .002), hyperlipidemia (6 – 7 hours, p < .001), hypothyroidism (4 hours, p = .013), obesity (4 hours, p < .001 – .019), depression (3 hours, p =  .026 – .033), and nicotine dependence (3 – 4 hours, p < .001 – .005). No statistically significant differences were observed for anxiety across any surgical approach.

3.2 Lumbar spinal fusion

32,316 patients were identified who underwent lumbar spinal fusion procedures. Fusion patients with concomitant chronic heart failure experienced an average additional 2-3 days of hospitalization across all approaches (54 – 69 hours, p <. 001) compared to patients without a diagnosis of CHF. Other significant predictors of increased length of stay across all approaches included arrhythmia (+0.5 – 2.5 days, 13 – 62 hours, p < .001 – .018) and osteoporosis (+0.5 – 1 days, 17 – 25 hours, p < .001 – .006). Minimal differences were observed by surgical approach with the presence of COPD (11 – 17 hours, p < .001), coronary atherosclerosis (10 – 14 hours, p < .001), depression (6 – 18 hours, p < .001), diabetes (9 – 11 hours, p < .001 – .045), obesity (6 – 10 hours, p < .001), anxiety (4 – 15 hours, p < .001 – .015); hypertension (6 – 8 hours, p < .001); hypothyroidism (4 – 7 hours, p <.001 – .028), and hyperlipidemia (2 – 3 hours, p <.001 – .009). No statistically significant differences were observed for nicotine dependence.

3.3 Regression

Multiple linear regression across the entire sample highlighted 11 comorbidities associated with significantly increased LOS following spinal fusion (Table 3). Chronic heart failure (β 2.85, SE 0.11, p < .001) demonstrated a strong positive association with increases in length of perioperative hospitalization while weak positive associations were also observed between arrhythmia (β 1.39, SE 0.14, p < .001) and osteoporosis (β 1.00, SE 0.06, p < .001).

Risk Factor

ß

SE

p

Chronic heart failure

3.05

0.08

<.001

Arrhythmia

1.39

0.14

<.001

Osteoporosis

1.00

0.06

<.001

Chronic Obstructive Pulmonary Disease

0.44

0.05

<.001

Coronary Atherosclerosis

0.34

0.04

<.001

Hypertension

0.33

0.03

<.001

Diabetes Mellitus

0.32

0.03

<.001

Anxiety

0.18

0.04

<.001

Obesity

0.14

0.03

<.001

Major Depression

0.13

0.04

<.001

Hypothyroidism

0.09

0.04

.023

Nicotine Dependence

-0.10

0.04

.004

Hyperlipidemia

-0.21

0.03

<.001

Table 3: Linear regression demonstrating impact of comorbid disease on length of hospital stay for spinal fusion surgery. † Indicates statistical significance (p< .05).

4. Discussion

Previous studies have examined the relationship between comorbidity and length of postoperative hospital stay among spinal fusion patients. Of the thirteen comorbid diseases included in this analysis, chronic heart failure and arrhythmia were found to be both positively associated with increased LOS by regression and responsible for substantial increases in observed duration of additional hospitalization post-surgery. Chronic heart failure demonstrated anywhere between 3-9 additional days of hospital stay in comorbid fusion patients compared to disease-free counterparts, while arrhythmia accounted for 1-15 additional days of hospitalization. These findings are consistent with reports that suggest chronic heart failure is a significant risk factor for postoperative complications, increasing risks for morbidity and mortality in spine surgery by 1.6 and 5.6 fold, respectively [12-14]. Chronic heart failure has also been identified as an independent risk factor of post-spinal fusion admissions to the intensive care unit, possibly explaining the prolonged course of hospital stay observed across the NIS database [15]. Similarly, the potential impact of cardiac arrhythmia on prolonged LOS following spine surgery has been anecdotally discussed, but a direct linkage has not been formally established [16, 17]. Additional findings that lacked positive association in regression but were still associated with increased hospital LOS included diabetes, coronary atherosclerosis, hypertension, and COPD, all accounting for approximately 1-2 additional days of hospitalization. The impact of diabetes has been repeatedly reported to adversely impact spine surgical outcomes [18, 19]. Diabetics undergoing spinal fusion are at increased risk of discharge to non-home facilities such as skilled nursing or rehabilitation units which sometimes present delays in discharge and could explain observed increases in LOS [20]. Atherosclerosis and hypertension have also been linked to poor surgical outcomes following fusion, and similarly have been reported to increase likelihood of patient discharge to non-home facilities as in diabetes [21-25]. Additionally, COPD has been shown to prolong hospitalization of spine surgery patients, however this is often linked to the risk of developing postoperative pneumonia [26, 27]. Judicious efforts by the surgeon should be taken to minimize this risk when possible. Of note, anxiety, depression, and nicotine dependence accounted for little to no additional length of stay following fusion observed in this study. Nicotine has been well-studied in rabbit models, showing negative effects on fusion outcomes with increased rates of nonunion, poor revascularization, and postoperative stiffness [28-30]. Analysis of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database across 2005 – 2014 was unable to identify increased odds of single or major postoperative complication in current smokers independent of pack-years consumed, although ever-smoker status did increase the risk of incurring single major postoperative adverse events [31]. More detailed analyses of post-fusion bone revascularization mirror the animal model data, with inferior outcomes and delayed rates of revascularization observed in smokers [32]. Meaningful interpretations of these data in the contexts of patient satisfaction domains have proven challenging, with literature reporting conflicting findings. One study from Denmark identified smoking as associated with increased risk of nonunion but was unable to identify functional deficits among patients by the Dallas Pain Questionnaire [33]. This is in contrast to analyses of the Swedish Spine Register which show that while patients report postoperative satisfaction independent of smoking status, the degree to which smokers were satisfied was less so than nonsmokers two years following lumbar spinal surgery [34]. Consensus appears to suggest that while patients are satisfied following spinal surgery regardless of smoking status, smoking serves as an independent risk factor for diminished subjective gains among spine surgery patients [35, 36].

Depression and anxiety are less well-understood in the context of spine surgery as studies primarily focus on the risks for postoperative delirium and short-term quality of life improvements [37-39]. Although the prevalence of psychiatric disorders is widely understood to be increased among patients with complaints of chronic neck and back pain, these analyses group depression alongside other psychiatric diagnoses such as schizophrenia and dementia and are difficult to interpret in the contexts of anxiety or depression alone [40]. By some estimates depression has been found to positively associate with shortened postoperative LOS in spine fusion patients however this was not observed in our analysis [41]. It is possible surgeons are underestimating the role of these comorbidities in postoperative recovery and should be subject to further investigation.  Management of medical comorbidities may benefit from cooperative partnership between primary care physicians and operating surgeons. Programs such as the Perioperative Enhancement Team (POET) formed at Duke University School of Medicine have successfully enhanced perioperative care coordination [42]. The POET program has performed preoperative risk stratification while reducing risk and optimizing care for the patient. Targeted clinics have been implemented for preoperative management of anemia, diabetes, nutrition optimization, pain, and elderly patients. Similar constructs could be undertaken by spine surgeons working in conjunction with primary care providers and pre-anesthesia testing centers. The recent efforts by the Global Spine Care Initiative, for example, have taken early steps towards implementing international interprofessional attempts at delivering spine care to developing and underserved populations around the globe [43]. The opportunity exists for orthopaedic spine and neurosurgeons to take substantive leadership roles in such organizations and help deliver valuable evidence-based care.

Limitations

The findings presented rely on data from information available through the HCUP-US-NIS database and necessarily rely on the integrity of their database. As this is a broadly available collection of inpatient hospitalizations, not specifically indicative of spine patient populations, cases may be underreported that are more prevalent in specialty spine surgery centers. Although cervical, lumbar, and lumbosacral spine fusion cohorts demonstrate the robust sample size, cervicothoracic, thoracic, and thoracolumbar regions are comparatively few in number. The result may be artificially distorted differences between data for patients with and without comorbidity of interest. However, as this database presents a large sample for study, we are confident that any inherent biases have been mitigated to the greatest extent possible.

5. Conclusion

Comorbid diseases play a significant role in prolonging postoperative hospitalization among spine fusion patients. This analysis presents a study of specific interplay between comorbidity, directionality of surgical approach, and region of the spine undergoing surgical fusion. Thorough understanding of the extent to which these factors interrelate may assist surgeons in preparing patients more effectively during the preoperative phase through enhanced medical optimization prior to surgery. Continued study as to additional factors that could impact patient length of stay following spinal fusion including additional comorbidities, patient demographic variables, and socioeconomic data may provide additional insights to further enhance these findings.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Author Contribution

All authors satisfy the criteria set forth by the ICMJE in the Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly work in Medical Journals.

References

  1. Weinstein JN, Lurie JD, Olson PR, Bronner KK, Fisher ES. United States' trends and regional variations in lumbar spine surgery: 1992-2003. Spine (Phila Pa 1976) 31 (2006): 2707-2714.
  2. Kepler CK, Vaccaro AR, Hilibrand AS, Anderson DG, Rihn JA, Albert TJ, et al. National trends in the use of fusion techniques to treat degenerative spondylolisthesis. Spine (Phila Pa 1976) 39 (2014): 1584-1589.
  3. Thirukumaran CP, Raudenbush B, Li Y, Molinari R, Rubery P, Mesfin A. National Trends in the Surgical Management of Adult Lumbar Isthmic Spondylolisthesis: 1998 to 2011. Spine (Phila Pa 1976) 41 (2016): 490-501.
  4. Salzmann SN, Derman PB, Lampe LP, Kueper J, Pan TJ, Yang J, et al. Cervical Spinal Fusion: 16-Year Trends in Epidemiology, Indications, and In-Hospital Outcomes by Surgical Approach. World Neurosurg 113 (2018): e280-e295.
  5. Weiss AJ, Elixhauser A, Andrews RM. Characteristics of Operating Room Procedures in U.S. Hospitals, 2011: Statistical Brief #170. In: Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville (MD) (2006).
  6. Gruskay JA, Fu M, Bohl DD, Webb ML, Grauer JN. Factors affecting length of stay after elective posterior lumbar spine surgery: a multivariate analysis. Spine J 15 (2015): 1188-1195.
  7. Bradywood A, Farrokhi F, Williams B, Kowalczyk M, Blackmore CC. Reduction of Inpatient Hospital Length of Stay in Lumbar Fusion Patients With Implementation of an Evidence-Based Clinical Care Pathway. Spine (Phila Pa 1976) 42 (2017): 169-176.
  8. Shields LB, Clark L, Glassman SD, Shields CB. Decreasing hospital length of stay following lumbar fusion utilizing multidisciplinary committee meetings involving surgeons and other caretakers. Surg Neurol Int 8 (2017): 5.
  9. Adogwa O, Lilly DT, Khalid S, Desai SA, Vuong VD, Davison MA, et al. Extended Length of Stay After Lumbar Spine Surgery: Sick Patients, Postoperative Complications, or Practice Style Differences Among Hospitals and Physicians? World Neurosurg 123 (2019): e734-e739.
  10. Berry JG, Glotzbecker M, Rodean J, Leahy I, Hall M, Ferrari L. Comorbidities and Complications of Spinal Fusion for Scoliosis. Pediatrics 139 (2017).
  11. Stulberg JJ, Haut ER. Practical Guide to Surgical Data Sets: Healthcare Cost and Utilization Project National Inpatient Sample (NIS). JAMA Surg 153 (2018): 586-587.
  12. Worley N, Marascalchi B, Jalai CM, Yang S, Diebo B, Vira S, et al. Predictors of inpatient morbidity and mortality in adult spinal deformity surgery. Eur Spine J 25 (2016): 819-827.
  13. Jain A, Hassanzadeh H, Puvanesarajah V, Klineberg EO, Sciubba DM, Kelly MP, et al. Incidence of perioperative medical complications and mortality among elderly patients undergoing surgery for spinal deformity: analysis of 3519 patients. J Neurosurg Spine 27 (2017): 534-539.
  14. Passias PG, Diebo BG, Marascalchi BJ, Jalai CM, Horn SR, Zhou PL, et al. A novel index for quantifying the risk of early complications for patients undergoing cervical spine surgeries. J Neurosurg Spine 27 (2017): 501-507.
  15. Kay HF, Chotai S, Wick JB, Stonko DP, McGirt MJ, Devin CJ. Preoperative and surgical factors associated with postoperative intensive care unit admission following operative treatment for degenerative lumbar spine disease. Eur Spine J 25 (2016): 843-849.
  16. Staartjes VE, Schillevoort SA, Blum PG, van Tintelen JP, Kok WE, Schroder ML. Cardiac Arrest During Spine Surgery in the Prone Position: Case Report and Review of the Literature. World Neurosurg 115 (2018): 460-467.
  17. Chowdhury T, Schaller B. The negative chronotropic effect during lumbar spine surgery: A systemic review and aggregation of an emerging model of spinal cardiac reflex. Medicine (Baltimore) 96 (2017): e5436.
  18. Armaghani SJ, Archer KR, Rolfe R, Demaio DN, Devin CJ. Diabetes Is Related to Worse Patient-Reported Outcomes at Two Years Following Spine Surgery. J Bone Joint Surg Am 98 (2016): 15-22.
  19. Javier Z Guzman, Branko Skovrlj, John Shin, Andrew C Hecht, Sheeraz A Qureshi, James C Iatridis, et al. The impact of diabetes mellitus on patients undergoing degenerative cervical spine surgery. Spine (Phila Pa 1976) 39 (2014): 1656-1665.
  20. Murphy ME, Maloney PR, McCutcheon BA, Rinaldo L, Shepherd D, Kerezoudis P, et al. Predictors of Discharge to a Nonhome Facility in Patients Undergoing Lumbar Decompression Without Fusion for Degenerative Spine Disease. Neurosurgery 81 (2017): 638-649.
  21. Lee DY, Lee SH, Jang JS. Risk factors for perioperative cardiac complications after lumbar fusion surgery. Neurol Med Chir (Tokyo) 47 (2007): 495-500.
  22. Sakaura H, Miwa T, Yamashita T, Kuroda Y, Ohwada T. Lifestyle-Related Diseases Affect Surgical Outcomes after Posterior Lumbar Interbody Fusion. Global Spine J 6 (2016): 2-6.
  23. Gum JL, Carreon LY, Stimac JD, Glassman SD. Predictors of Oswestry Disability Index worsening after lumbar fusion. Orthopedics 36 (2013): 478-483.
  24. Lovecchio F, Hsu WK, Smith TR, Cybulski G, Kim B, Kim JY. Predictors of thirty-day readmission after anterior cervical fusion. Spine (Phila Pa 1976) 39 (2014): 127-133.
  25. Sultan Aldebeyan, Ahmed Aoude, Maryse Fortin, Anas Nooh, Peter Jarzem, Jean Ouellet, et al. Predictors of Discharge Destination After Lumbar Spine Fusion Surgery. Spine (Phila Pa 1976) 41 (2016): 1535-1541.
  26. Elsamadicy AA, Sergesketter AR, Kemeny H, Adogwa O, Tarnasky A, Charalambous L, et al. Impact of Chronic Obstructive Pulmonary Disease on Postoperative Complication Rates, Ambulation, and Length of Hospital Stay After Elective Spinal Fusion (>/=3 Levels) in Elderly Spine Deformity Patients. World Neurosurg 116 (2018): e1122-e1128.
  27. Sami Walid M, Zaytseva NV. The impact of chronic obstructive pulmonary disease and obesity on length of stay and cost of spine surgery. Indian J Ortho 44 (2010): 424-427.
  28. Daffner SD, Waugh S, Norman TL, Mukherjee N, France JC. Effect of serum nicotine level on posterior spinal fusion in an in vivo rabbit model. Spine J 15 (2015): 1402-1408.
  29. Silcox DH, Daftari T, Boden SD, Schimandle JH, Hutton WC, Whitesides TE. The effect of nicotine on spinal fusion. Spine (Phila Pa 1976) 20 (1995): 1549-1553.
  30. Wing KJ, Fisher CG, O'Connell JX, Wing PC. Stopping nicotine exposure before surgery. The effect on spinal fusion in a rabbit model. Spine (Phila Pa 1976) 25 (2000): 30-34.
  31. Purvis TE, Rodriguez HJ, Ahmed AK, Boone C, De la Garza-Ramos R, Elder BD, et al. Impact of smoking on postoperative complications after anterior cervical discectomy and fusion. J Clin Neurosci 38 (2017): 106-110.
  32. Daftari TK, Whitesides TE Jr, Heller JG, Goodrich AC, McCarey BE, Hutton WC. Nicotine on the revascularization of bone graft. An experimental study in rabbits. Spine (Phila Pa 1976) 19 (1994): 904-911.
  33. Andersen T, Christensen FB, Laursen M, Hoy K, Hansen ES, Bunger C. Smoking as a predictor of negative outcome in lumbar spinal fusion. Spine (Phila Pa 1976) 26 (2001): 2623-2628.
  34. Sanden B, Forsth P, Michaelsson K. Smokers show less improvement than nonsmokers two years after surgery for lumbar spinal stenosis: a study of 4555 patients from the Swedish spine register. Spine (Phila Pa 1976) 36 (2011): 1059-1064.
  35. Paulsen RT, Bouknaitir JB, Fruensgaard S, Carreon L, Andersen M. Prognostic Factors for Satisfaction After Decompression Surgery for Lumbar Spinal Stenosis. Neurosurgery 82 (2018): 645-651.
  36. Sigmundsson FG, Jonsson B, Stromqvist B. Determinants of patient satisfaction after surgery for central spinal stenosis without concomitant spondylolisthesis: a register study of 5100 patients. Eur Spine J 26 (2017): 473-480.
  37. Alvin MD, Miller JA, Sundar S, Lockwood M, Lubelski D, Nowacki AS, et al. The impact of preoperative depression on quality of life outcomes after posterior cervical fusion. Spine J 15 (2015): 79-85.
  38. Elsamadicy AA, Adogwa O, Lydon E, Sergesketter A, Kaakati R, Mehta AI, et al. Depression as an independent predictor of postoperative delirium in spine deformity patients undergoing elective spine surgery. J Neurosurg Spine 27 (2017): 209-214.
  39. Fineberg SJ, Nandyala SV, Marquez-Lara A, Oglesby M, Patel AA, Singh K. Incidence and risk factors for postoperative delirium after lumbar spine surgery. Spine (Phila Pa 1976) 38 (2013): 1790-1796.
  40. Demyttenaere K, Bruffaerts R, Lee S, Posada-Villa J, Kovess V, Angermeyer MC,, et al. Mental disorders among persons with chronic back or neck pain: results from the World Mental Health Surveys. Pain 129 (2007): 332-342.
  41. Menendez ME, Neuhaus V, Bot AG, Ring D, Cha TD. Psychiatric disorders and major spine surgery: epidemiology and perioperative outcomes. Spine (Phila Pa 1976) 39 (2014): E111-E122.
  42. Aronson S, Westover J, Guinn N, Setji T, Wischmeyer P, Gulur P, et al. A Perioperative Medicine Model for Population Health: An Integrated Approach for an Evolving Clinical Science. Anesth Analg 126 (2018): 682-690.
  43. Kopansky-Giles D, Johnson CD, Haldeman S, Chou R, Côté P, Green BN, et al. The Global Spine Care Initiative: resources to implement a spine care program. Eur Spine J 27 (2018): 915-924.

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