Literature DB >> 29238634

ASA Classification as a Risk Stratification Tool in Adult Spinal Deformity Surgery: A Study of 5805 Patients.

Sulaiman Somani1, John Di Capua1, Jun S Kim1, Kevin Phan2, Nathan J Lee1, Parth Kothari1, Joung-Heon Kim1, James Dowdell1, Samuel K Cho1.   

Abstract

STUDY
DESIGN: Retrospective analysis of prospectively collected data.
OBJECTIVES: Adult spinal deformity (ASD) surgery is a highly complex procedure that has high complication rates. Risk stratification tools can improve patient management and may lower complication rates and associated costs. The goal of this study was to identify the independent association between American Society of Anesthesiologists (ASA) class and postoperative outcomes following ASD surgery.
METHODS: The 2010-2014 American College of Surgeons National Surgical Quality Improvement Program database was queried using Current Procedural Terminology and International Classification of Diseases, Ninth Revision, codes relevant to ASD surgery. Patients were divided based on their ASA classification. Bivariate and multivariate logistic regression analyses were employed to quantify the increased risk of 30-day postoperative complications for patients with increased ASA scores.
RESULTS: A total of 5805 patients met the inclusion criteria, 2718 (46.8%) of which were ASA class I-II and 3087 (53.2%) were ASA class III-IV. Multivariate logistic regression revealed ASA class to be a significant risk factor for mortality (odds ratio [OR] = 21.0), reoperation within 30 days (OR = 1.6), length of stay ≥5 days (OR = 1.7), overall morbidity (OR = 1.4), wound complications (OR = 1.8), pulmonary complications (OR = 2.3), cardiac complications (OR = 3.7), intra-/postoperative red blood cell transfusion (OR = 1.3), postoperative sepsis (OR = 2.7), and urinary tract infection (OR = 1.6).
CONCLUSIONS: This is the first study evaluating the role of ASA class in ASD surgery with a large patient database. Use of ASA class as a metric for preoperative health was verified and the association of ASA class with postoperative morbidity and mortality in ASD surgery suggests its utility in refining the risk stratification profile and improving preoperative patient counseling for those individuals undergoing ASD surgery.

Entities:  

Keywords:  ASA class; American Society of Anesthesiologists; adult spinal deformity surgery; complications; outcomes; risk stratification

Year:  2017        PMID: 29238634      PMCID: PMC5721995          DOI: 10.1177/2192568217700106

Source DB:  PubMed          Journal:  Global Spine J        ISSN: 2192-5682


Introduction

As the elderly population in the United States continues to rise and is projected to nearly double by 2050,[1] adult spinal deformity (ASD) is becoming increasingly prevalent. The United States Bone and Joint Initiative estimates a total of $75.8 billion in hospital discharge costs related to spinal deformity disorders, with 65% of that cost being derived from scoliosis, spondylolisthesis, and other spondylopathies.[2] Additionally, conservative estimates of complications from ASD surgery tally to $5.4 billion, with complication rates ranging from 13% to 59%.[3] Although there are continued developments in techniques, instrumentation, and anesthesia in the realm of ASD surgery,[3,4] the increasing emphasis on cost containment and restructuring of compensation schemes have prioritized the utility of potential risk stratification tools to predict complications and improve perioperative planning and management. The American Society of Anesthesiologists (ASA) Physical Status classification system was originally developed as a variable for statistical tabulations.[5] The original goal of the ASA class system was to assess overall preoperative physical status of the patient and not surgical risk per se because it does not include the impact of surgery on the patient’s outcomes. However, since then, multiple studies have demonstrated and emphasized its potential as a useful proxy for judging patients’ operative risk and as a predictor for postoperative complications, particularly in spinal surgeries.[6-13] Because the score is assigned preoperatively based on the patient’s preoperative health, ASA classifications have the potential to be an accessible tool for surgeons to gauge patient risk for postoperative complications. Prior literature exploring the utility of preoperative factors, especially ASA class, in ASD surgery has conflicting results (Table 1). Schwab et al conducted a multicenter, retrospective study of ASD patients and found no significant differences in ASA class between the cohorts with complications and without complications.[14] However, Tang et al identified ASA class to be an independent risk factor for major complications in ASD surgery, while Pateder et al also found an association between a higher ASA class ranking and patient mortality. This study seeks to help resolve these conflicts from previous works by investigating the capability of ASA class to predict adverse postoperative events using the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database.
Table 1.

Prior Literature Overview for ASA Class Utility in ASD Surgery.

AuthorsYearData SourceSample SizeASA Class AnalyzedMajor Findings
Pateder et al[17] 2008Single-center, chart review361YesASA + for short-term mortality
Schwab et al[14] 2012Multicenter, chart review953 (150 used)YesASA not correlated with postoperative complications
Tang et al[7] ,a 2014Single-center, chart review236YesASA + for major postoperative complications (OR = 2.21)
Smith et al[16] 2016Multicenter, prospective291NoComorbidities, age, and obesity associated with complications
Manoharan et al[28] 2016Multicenter, database747NoPreoperative risk factors associated with 30-day readmissions
This study2016Multicenter, database5822YesASA + for postoperative morbidity

Abbreviations: ASA, American Society for Anesthesiologists; ASD, adult spinal deformity; OR, odds ratio.

aEvaluated for lumbar scoliosis surgery only.

Prior Literature Overview for ASA Class Utility in ASD Surgery. Abbreviations: ASA, American Society for Anesthesiologists; ASD, adult spinal deformity; OR, odds ratio. aEvaluated for lumbar scoliosis surgery only.

Materials and Methods

This was a retrospective study of prospectively collected data in the 2010-2014 ACS-NSQIP database. NSQIP is a large national database with risk-adjusted 30-day postoperative morbidity and mortality outcomes. More than 500 hospitals that vary in size, socioeconomic location, and academic affiliation contributed data to the 2010-2014 ACS-NSQIP database.[15] NSQIP data is collected prospectively by dedicated clinical abstractors at each institution on more than 150 demographic, preoperative, intraoperative, and 30-day postoperative variables. These on-site surgical clinical reviewers stringently maintain the fidelity of the NSQIP database, and they conduct ongoing internal auditing processes to analyze interrater reliability and to ensure accuracy of data collection.

Inclusion Criteria

The NSQIP database from 2010 to 2014 was used in this study. Adult patients (≥18 years) undergoing spinal fusion for deformity were identified based on Current Procedural Terminology (CPT) codes 22 800, 22 802, 22 804, 22 808, 22 810, 22 812, 22 818, and 22 819. CPT codes 22 843, 22 844, 22 846, or 22 847 were also included to capture long, multilevel fusion constructs. Patients with CPT codes 22 842 and 22 845 were included if they had an ICD-9 (International Classification of Diseases, Ninth Revision) diagnosis for spinal deformity (including 737.1, 737.2, 737.3, 737.4, 737.8, and 737.9). Cases with missing preoperative data; emergency cases; patients with a wound class of 2, 3, or 4; an open wound on their body; current sepsis; current pneumonia; prior surgeries within 30 days; cases requiring cardiopulmonary resuscitation prior to surgery; any patients undergoing a nonelective procedure; or cases with diagnoses of cervical spine, trauma or injury to spine, or neoplasm of spine were excluded in order to reduce the risk of confounding variables.

Variable Definition

Patient demographic variables included sex, age (≥65 years old), and race (white, black, Hispanic, and other). Other race included American Indian, Alaska Native, Asian, Native Hawaiian, Pacific Islander, or unknown/not reported. Preoperative variables included operation year, obesity (body mass index ≥30 kg/m2), diabetes (non–insulin-dependent diabetes mellitus or insulin-dependent diabetes mellitus), current smoking (within 1 year of surgery), dyspnea (≤30 days prior to surgery), functional status prior to surgery (independent or dependent/partially dependent ≤30 days prior to surgery), pulmonary comorbidity (ventilator dependent ≤48 hours prior to surgery or history of chronic obstructive pulmonary disease ≤30 days prior to surgery), cardiac comorbidity (use of hypertensive medication or history of chronic heart failure ≤30 days prior to surgery), renal comorbidity (acute renal failure ≤24 hours prior to surgery or dialysis treatment ≤2 weeks prior to surgery), steroid use for chronic condition (≤30 days prior to surgery), ≥10% loss of body weight (in the last 6 months), bleeding disorder (chronic, active condition), and preoperative transfusion of ≥1 unit of whole/packed red blood cells (RBCs; ≤72 hours prior to surgery). Intraoperative variables included fusion length (long fusion is ≥4 levels during an anterior approach and ≥7 levels during a posterior approach), surgical approach (posterior, anterior, or combined), bone graft, fusion to pelvis, osteotomy, operative time (≥4 hours), and total relative value units. Thirty-day postoperative outcome variables include mortality, any postoperative complication, length of stay (LOS; ≥5 days), wound complication (superficial or deep surgical site infection, organ space infection, or wound dehiscence), pulmonary complication (pneumonia, unplanned reintubation, or duration of ventilator-assisted respiration ≥48 hours), venous thromboembolism (pulmonary embolism or deep vein thrombosis), renal complication (progressive renal insufficiency or acute renal failure), urinary tract infection (UTI), peripheral nerve injury, cardiac complication (cardiac arrest requiring cardiopulmonary resuscitation or myocardial infarction), intra-/postoperative transfusion, sepsis, central nervous system complication (cerebrovascular accident or coma), reoperation (related to initial procedure), and unplanned readmission (related to initial procedure). ACS-NSQIP provides further information on variable characteristics.[16] Patients were split up into 4 cohorts according to their assigned ASA classification score of 1, 2, 3, and 4. Exclusion criteria discussed above removed any instances of ASA classes 5 or 6 and so was not considered.

Statistical Analysis

Bivariate analyses were performed on patient demographic, preoperative, intraoperative, and postoperative characteristics using Pearson’s χ2 test. Fischer’s exact test was used where appropriate. Multivariable logistic regression analysis, with stepwise entry and removal criteria set to a significance level of .05, was performed to identify postoperative outcomes with which the higher ASA classes were associated. The c-statistic, which is the area under the receiver operating characteristic curve, was also retrieved from the predictors of postoperative outcomes models and determined the accuracy of this model. The area under this curve measures the ability of the model to correctly classify those with the complication and those without. SAS Studio Version 3.4 (SAS Institute Inc, Cary, NC) was used for all statistical analysis.

Results

Study Population

A total of 5803 patients met the inclusion criteria for the study, of which 155 (2.7%) patients were ASA class I, 2561 (44.1%) patients were ASA class II, 2927 (50.4%) patients were ASA class III, and 160 (2.8%) patients were ASA class IV (Table 2). Patients with ASA class IV were more likely to be male, ≥65 years of age, black, obese, diabetic, dyspneic, partially or totally functionally dependent, pulmonary comorbid, cardiac comorbid, renal comorbid, smokers, use steroids, have recent weight loss, bleeding disorder, longer operation times, osteotomy, fusion to pelvis, longer fusion lengths, and posterior surgical approach.
Table 2.

Patient Demographics, Comorbidities, and Intraoperative Variables (N = 5803).a

ASA Class IASA Class IIASA Class IIIASA Class IV
Categoryn%N%n%n% P Value
Sex
 Female8756.1%154760.4%171958.7%7043.8% .0006
 Male6843.9%101439.6%120841.3%9056.3%
Age ≥65 years1711.0%78230.5%142348.6%9358.1% <.0001
Race
 White12379.4%209381.7%237481.1%12175.6% .0458
 Other1912.3%2017.8%2036.9%95.6%
 Hispanic53.2%933.6%1103.8%116.9%
 Black85.2%1746.8%2408.2%1911.9%
Obese2818.1%91935.9%142148.5%7144.4% <.0001
Diabetes42.6%1616.3%62721.4%5836.3% <.0001
Dyspnea10.6%863.4%2338.0%2616.3% <.0001
Partially or totally functionally dependent00.0%602.3%1776.0%2716.9% <.0001
Pulmonary comorbidity00.0%532.1%2117.2%2918.1% <.0001
Cardiac comorbidity74.5%108142.2%195666.8%11873.8% <.0001
Renal comorbidity00.0%20.1%140.5%95.6% <.0001
Smoke2415.5%52320.4%62121.2%3823.8%.2801
Steroid use10.6%481.9%1465.0%2415.0% <.0001
Recent weight loss00.0%00.0%100.3%10.6% .0350
Bleeding disorder21.3%140.5%481.6%63.8% .0001
Preoperative RBC transfusion00.0%30.1%100.3%00.0%.4290
Operation time quartile
 Q1 (≤154 minutes)3824.5%77430.2%61020.8%2918.1% <.0001
 Q2 (≤235 minutes)4831.0%64525.2%73725.2%3320.6%
 Q3 (≤346 minutes)3120.0%60723.7%75525.8%4930.6%
 Q4 (>346 minutes)3824.5%53520.9%82528.2%4930.6%
Operation year
 2010127.7%2208.6%2217.6%148.8% .0005
 2011149.0%1465.7%1856.3%159.4%
 2012127.7%1787.0%2187.4%1610.0%
 20135233.5%95737.4%104135.6%6339.4%
 20146541.9%106041.4%126243.1%5232.5%
Osteotomy1711.0%32512.7%47416.2%2113.1% .0016
Fusion to pelvis10.6%1656.4%30510.4%116.9% <.0001
Fusion length
 Long8353.5%152259.4%193166.0%12376.9% <.0001
 Short7246.5%103940.6%99634.0%3723.1%
Surgical approach
 Posterior8554.8%127249.7%182762.4%10766.9% <.0001
 Anterior6541.9%117746.0%100934.5%4628.8%
 Combined53.2%1124.4%913.1%74.4%

Abbreviations: ASA, American Society for Anesthesiologists; RBC, red blood cell.

aBolded values indicate statistical significance.

Patient Demographics, Comorbidities, and Intraoperative Variables (N = 5803).a Abbreviations: ASA, American Society for Anesthesiologists; RBC, red blood cell. aBolded values indicate statistical significance.

Unadjusted Analysis

There were statistically significant differences in 30-day unadjusted morbidities and mortality between the 4 ASA cohorts (Table 3). Patients in the ASA IV cohort, compared to the ASA I cohort, experienced a higher rate of mortality (3.8% vs 0.0%), any complication (51.9% vs 17.4%), LOS ≥5 days (55.0% vs 20.6%), wound complication (4.4% vs 0.6%, P = .0005), pulmonary complication (11.9% vs 0.6%), UTI (3.1% vs 0.6%, P = .0095), cardiac complication (4.4% vs 0.0%), intra-/postoperative RBC transfusion (41.3% vs 15.5%), sepsis (6.3% vs 0.0%), reoperation (9.6% vs 0.7%), and unplanned readmission (12.3% vs 3.5%). All P values are <.0001 unless otherwise stated.
Table 3.

Unadjusted Outcomes (N = 5803).a

ASA Class IASA Class IIASA Class IIIASA Class IV
Categoryn%n%n%n% P Value
Mortality00.0%10.0%230.8%63.8% <.0001
Any complication2717.4%63524.8%107636.8%8351.9% <.0001
LOS ≥5 days3220.6%54221.2%101334.6%8855.0% <.0001
Wound complication10.6%401.6%943.2%74.4% .0005
Pulmonary complication10.6%371.4%993.4%1911.9% <.0001
Venous thromboembolism21.3%431.7%531.8%74.4%.1682
Renal complication10.6%160.6%401.4%10.6%.0891
Urinary tract infection10.6%371.4%802.7%53.1% .0095
Peripheral nerve injury00.0%00.0%50.2%10.6%.0806
Cardiac complication00.0%60.2%260.9%74.4% <.0001
Intra-/postoperative RBC transfusion2415.5%55721.7%92831.7%6641.3% <.0001
Sepsis00.0%230.9%692.4%106.3% <.0001
CNS complication00.0%50.2%60.2%10.6%.7909
Reoperation (related to initial procedure)10.7%692.9%1344.9%149.6% <.0001
Unplanned readmission (related to initial procedure)53.5%984.2%2117.8%1812.3% <.0001

Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell; CNS, central nervous system.

aBolded values indicate statistical significance.

Unadjusted Outcomes (N = 5803).a Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell; CNS, central nervous system. aBolded values indicate statistical significance.

Subgroup Analysis Between ASA Class II and III

A bivariate subgroup analysis was performed between ASA class II and ASA class III (Table 4). Patients in the ASA class III cohort were more likely to be ≥65 years of age, obese, diabetic, dyspneic, partially or totally functionally dependent, pulmonary comorbid, cardiac comorbid, renal comorbid, use steroids, have recent weight loss, bleeding disorder, operation time ≥4 hours, osteotomy, fusion to pelvis, longer fusion lengths, and posterior surgical approaches.
Table 4.

Subgroup Bivariate Analysis Between ASA II and ASA III Patients for Patient Characteristics (N = 5488).a

ASA Class IIASA Class III
Categoryn%n% P
Sex
 Female154760.4%171958.7%.2067
 Male101439.6%120841.3%
Age ≥65 years78230.5%142348.6% <.0001
Race
 White209381.7%237481.1%.1546
 Other2017.8%2036.9%
 Hispanic933.6%1103.8%
 Black1746.8%2408.2%
Obese91935.9%142148.5% <.0001
Diabetes1616.3%62721.4% <.0001
Dyspnea863.4%2338.0% <.0001
Partially or totally dependent functional status602.3%1776.0% <.0001
Pulmonary comorbidity532.1%2117.2% <.0001
Cardiac comorbidity108142.2%195666.8% <.0001
Renal comorbidity20.1%140.5% .0061
Smoke52320.4%62121.2%.4697
Steroid use481.9%1465.0% <.0001
Recent weight loss00.0%100.3% .0031
Bleeding disorder140.5%481.6% .0001
Preoperative RBC transfusion30.1%100.3%.0879
Operation time ≥4 hours109242.6%153452.4% <.0001
Operation year
 20102208.6%2217.6%.2526
 20111465.7%1856.3%
 20121787.0%2187.4%
 201395737.4%104135.6%
 2014106041.4%126243.1%
Osteotomy32512.7%47416.2% .0002
Fusion to pelvis1656.4%30510.4% <.0001
Fusion length
 Long152259.4%193166.0% <.0001
 Short103940.6%99634.0%
Surgical approach
 Posterior127249.7%182762.4% <.0001
 Anterior117746.0%100934.5%
 Combined1124.4%913.1%

Abbreviations: ASA, American Society for Anesthesiologists; RBC, red blood cell.

aBolded values indicate statistical significance.

Subgroup Bivariate Analysis Between ASA II and ASA III Patients for Patient Characteristics (N = 5488).a Abbreviations: ASA, American Society for Anesthesiologists; RBC, red blood cell. aBolded values indicate statistical significance. There were statistically significant differences in 30-day unadjusted morbidities and mortality between the ASA II and ASA III cohorts (Table 5). ASA III patients experienced a higher rate of mortality (0.8% vs 0.0%), any complication (36.8% vs 24.8%), LOS ≥5 days (34.6% vs 21.2%), wound complication (3.2% vs 1.6%, P = .0001), pulmonary complication (3.4% vs 1.6%), renal complication (1.4% vs 0.6%), UTI (2.7% vs 1.4%, P = .0010), peripheral nerve injury (0.2% vs 0.0%, P = .0364), cardiac complication (0.9% vs 0.2%, P = .0015), intra-/postoperative RBC transfusion (31.7% vs 21.7%), sepsis (2.4% vs 0.9%), reoperation (4.9% vs 2.9%, P = .0003), and unplanned readmission (7.8% vs 4.2%). All P are <.0001 unless otherwise stated.
Table 5.

Subgroup Bivariate Analysis Between ASA II and ASA III Patients for 30-Day Outcomes (N = 5488).a

ASA Class IIASA Class III
Categoryn%n% P Value
Mortality10.0%230.8% <.0001
Any complication63524.8%107636.8% <.0001
LOS ≥5 days54221.2%101334.6% <.0001
Wound complication401.6%943.2% .0001
Pulmonary complication371.4%993.4% <.0001
Venous thromboembolism431.7%531.8%.7104
Renal complication160.6%401.4% .0064
Urinary tract infection371.4%802.7% .0010
Peripheral nerve injury00.0%50.2% .0364
Cardiac complication60.2%260.9% .0015
Intra-/postoperative RBC transfusion55721.7%92831.7% <.0001
Sepsis230.9%692.4% <.0001
CNS complication50.2%60.2%.9358
Reoperation (related to initial procedure)692.9%1344.9% .0003
Unplanned readmission (related to initial procedure)984.2%2117.8% <.0001

Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell; CNS, central nervous system.

aBolded values indicate statistical significance.

Subgroup Bivariate Analysis Between ASA II and ASA III Patients for 30-Day Outcomes (N = 5488).a Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell; CNS, central nervous system. aBolded values indicate statistical significance.

Multivariate Analysis

Multivariate logistic regression analysis (Table 6) revealed ASA classes II, III, and IV, compared to ASA class I, to be a significant, independent risk factor for several acute complications. Patients experienced an increased risk of any complication (ASA class III: odds ratio [OR] = 1.89, confidence interval [CI] = 1.19-3.01, P = .0070; ASA class IV: OR = 3.58, CI = 2.00-6.39; c-statistic = 0.7973), LOS ≥5 days (ASA class IV: OR = 3.34, CI = 1.91-5.84; c-statistic = 0.7706), pulmonary complication (ASA class IV: OR = 8.81, CI = 1.14-68.33, P = .0373; c-statistic = 0.7733), intra-/postoperative RBC transfusion (ASA class III: OR = 1.69, CI = 1.04-2.76, P = .0349; ASA class IV: OR = 2.52, CI = 1.37-4.62, P = .0029; c-statistic = 0.8104), and reoperation (ASA class IV: OR = 11.03, CI = 1.42-85.61, P = .0217; c-statistic = 0.6544). P values are <.0001 unless otherwise stated.
Table 6.

Multivariate Logistic Regression Results for ASA Class as a Risk Factor for Adverse Outcomes Following Elective ASD Surgery.a

OutcomeASA ClassOdds RatioLower Confidence LimitUpper Confidence Limit P Value c-statistic
Any complicationASA class II vs ASA class I1.360.862.16.19340.7973
ASA class III vs ASA class I1.891.193.01 .0070
ASA class IV vs ASA class I3.582.006.39 <.0001
LOS ≥5 daysASA class II vs ASA class I0.930.601.45.76220.7706
ASA class III vs ASA class I1.540.992.38.0545
ASA class IV vs ASA class I3.341.915.84 <.0001
Pulmonary complicationASA class II vs ASA class I1.780.2413.11.57330.7733
ASA class III vs ASA class I3.180.4423.23.2536
ASA class IV vs ASA class I8.811.1468.33 .0373
Intra-/postoperative RBC transfusionASA class II vs ASA class I1.320.812.15.27260.8104
ASA class III vs ASA class I1.691.042.76 .0349
ASA class IV vs ASA class I2.521.374.62 .0029
Reoperation (related to initial procedure)ASA class II vs ASA class I3.970.5528.83.17260.6544
ASA class III vs ASA class I5.910.8242.66.0784
ASA class IV vs ASA class I11.031.4285.61 .0217

Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell.

aBolded values indicate statistical significance.

Multivariate Logistic Regression Results for ASA Class as a Risk Factor for Adverse Outcomes Following Elective ASD Surgery.a Abbreviations: ASA, American Society for Anesthesiologists; LOS, length of stay; RBC, red blood cell. aBolded values indicate statistical significance.

Discussion

This study explored the role of patient ASA class assignment in improving risk stratification for patients undergoing elective ASD surgery. Higher ASA class assignment was found to be significantly and independently associated with the many acute postoperative outcomes such as any complication, LOS ≥5 days, pulmonary complications, intra-/postoperative RBC transfusion, and reoperation (related to initial procedure). The bivariate analysis (Table 2) in this study was most useful in illustrating the differences in characteristics of patients between the low and high ASA class cohorts. In patient demographics, old age had a significant correlation with higher ASA. Although ASA class assignment is not dependent on this variable, it may instead function as a confounder. Stratification by age revealed that the incidence of pulmonary and cardiac comorbidities, two leading drivers of higher ASA class assignment, increased with older age in this study’s patient population. This may explain the difference seen in age between these ASA class cohorts. Bivariate analysis also revealed that patients with a higher comorbidity burden was correlated with higher ASA scores. Since ASA class is dependent on physical status, which is dependent on patient preoperative health, this observed result agrees with ASA class assignment guidelines, as well as other previous literature in spinal surgeries.[6-13] Interestingly, the prevalence of smoking in the higher ASA class cohort was not significantly different than that of the lower ASA class. ASA guidelines register current smokers automatically into ASA class II, but there is no concrete information on how the degree of smoking, aside from conferred illnesses that more relate to a patient’s current disease states, plays a role in ASA class assignment. Because NSQIP registers patient smoking as binary and fails to capture the degree of smoking, these 2 factors may have led to this result. Most important, on multivariate analysis, increasing ASA class was identified as an independent risk factor for many postoperative complications. Pateder et al echoed these results in their study, which identified the bivariate association between ASA class and mortality.[17] Smith et al conducted a prospective, multicenter, 2-year follow-up of patients following ASD surgery and found that higher, perioperative (<6 weeks from operation) complication rates (ie, overall morbidity) are associated with patients who have greater preoperative comorbidities.[18] Mannion et al used the Eurospine Spine Tango Registry to create a cohort of patients undergoing spine surgery for degenerative lumbar disorders and found ASA class to be an independent risk factor of surgical and general complication incidence in patients undergoing any spine surgery.[19] Preoperative patient comorbidities have been shown to increase complication rates in spinal surgery.[18,19] Similarly, ASA class is an effective surrogate for patient preoperative comorbidities, and therefore, advanced ASA class acts as a risk factor for postoperative adverse events. This is in line with other studies that have shown ASA class to correlate with and increased incidence of postoperative complications following spine surgery.[6,7,9,12,20] All of the postoperative adverse events where ASA class was identified as a risk factor generally had modest c-statistic values (Table 6). For example, in other spinal surgeries, ASA class has been implicated as a risk factor for wound complications.[10,13] This may be justified by the fact that ASA class encapsulates diabetes and obesity, both of which have been associated with a greater risk of surgical site infections as a result of tissue hypoperfusion and subsequently impaired immunological function.[21] Finally, ASA class is a proxy for patients’ preoperative health and encapsulates multiple comorbidities that are known to be risk factors for cardiac complications,[22] pulmonary complications,[23] postoperative sepsis,[22,24] UTI,[24] and intra-/postoperative transfusion.[25] A greater incidence of these complications can lead to prolonged length of hospital stay. The key findings from this study were different than the conclusions from Schwab et al,[14] which may have stemmed from differences in study design. Schwab et al divided their patient population into a complication cohort and control cohort. The complication cohort was collected by a nonrandom, retrospective consecutive sampling method, and the control cohort was randomly selected from a time-matched sample. The advantage of using this method, as Schwab et al did, is that the optimization algorithm for multivariate logistic regression will be less likely to generate a model with low sensitivity and specificity (ie, low c-statistic). However, this study ensures that this advantage is mirrored by taking into account c-indices when looking at multivariate regression model accuracies. The differences between this study and Schwab’s, then, stem from the different sampling procedures used. Given that nonrandom sampling has a greater risk of creating a sample that may not be the best representation of the true population,[26] NSQIP, given its much larger data size, is more likely to represent this true ASD population, helping bolster the reliability of outcomes in this study. However, there are several limitations that must be addressed in this work. Because the NSQIP database classifies cases based on CPT codes, differences between procedural techniques cannot be accounted for in this study. The NSQIP database does not delineate patients by ICD-9 codes, which presents an inherent limitation of the database. We attempted to control for variables that we considered surrogates for case complexity such as operative duration, presence or absence of an osteotomy, pelvic fixation, surgical approach, long fusion lengths, and total relative value units in our multivariate regression analysis. Furthermore, NSQIP offers a large patient size but may overrepresent academic US medical centers. Additionally, long-term complications, radiological outcomes, and other spine-specific variables are not captured in the NSQIP database, which only evaluates complications up to 30 days postoperatively, leading to a potential underestimation of risk. Finally, interrater reliability of ASA class are not perfect, even though ASA class assignment has been known to achieve 98% reliability (±1 class) across different anesthesiologists.[27] Despite these limitations, this is the first study evaluating the role of ASA class in ASD surgery with a large patient database. ASA class can intuitively be appreciated as a tool in patient risk stratification since it inherently captures a large spectrum of patient comorbidities. In this study, this notion was verified, with higher ASA class assignments showing significant and independent correlation with any complications, LOS ≥5 days, pulmonary complications, intra-/postoperative RBC transfusions, and reoperation. These results suggest the utility of ASA class in refining the risk stratification profile and improving preoperative patient counseling for those individuals undergoing ASD surgery.
  25 in total

1.  Risk factors for major peri-operative complications in adult spinal deformity surgery: a multi-center review of 953 consecutive patients.

Authors:  Frank J Schwab; Nicola Hawkinson; Virginie Lafage; Justin S Smith; Robert Hart; Gregory Mundis; Douglas C Burton; Breton Line; Behrooz Akbarnia; Oheneba Boachie-Adjei; Richard Hostin; Christopher I Shaffrey; Vincent Arlet; Kirkham Wood; Munish Gupta; Shay Bess; Praveen V Mummaneni
Journal:  Eur Spine J       Date:  2012-05-17       Impact factor: 3.134

2.  Short-term mortality and its association with independent risk factors in adult spinal deformity surgery.

Authors:  Dhruv B Pateder; Ricardo A Gonzales; Khaled M Kebaish; David B Cohen; Jen-Yi Chang; John P Kostuik
Journal:  Spine (Phila Pa 1976)       Date:  2008-05-15       Impact factor: 3.468

3.  Risk factors for immediate postoperative complications and mortality following spine surgery: a study of 3475 patients from the National Surgical Quality Improvement Program.

Authors:  Andrew J Schoenfeld; Leah M Ochoa; Julia O Bader; Philip J Belmont
Journal:  J Bone Joint Surg Am       Date:  2011-09-07       Impact factor: 5.284

4.  Missing data in the American College of Surgeons National Surgical Quality Improvement Program are not missing at random: implications and potential impact on quality assessments.

Authors:  Barton H Hamilton; Clifford Y Ko; Karen Richards; Bruce Lee Hall
Journal:  J Am Coll Surg       Date:  2010-02       Impact factor: 6.113

5.  Adult spine deformity.

Authors:  Christopher R Good; Joshua D Auerbach; Patrick T O'Leary; Thomas C Schuler
Journal:  Curr Rev Musculoskelet Med       Date:  2011-12

Review 6.  The obese surgical patient: a susceptible host for infection.

Authors:  Daniel A Anaya; E Patchen Dellinger
Journal:  Surg Infect (Larchmt)       Date:  2006-10       Impact factor: 2.150

7.  ASA grade and Charlson Comorbidity Index of spinal surgery patients: correlation with complications and societal costs.

Authors:  Robert G Whitmore; James H Stephen; Coleen Vernick; Peter G Campbell; Sanjay Yadla; George M Ghobrial; Mitchell G Maltenfort; John K Ratliff
Journal:  Spine J       Date:  2013-04-17       Impact factor: 4.166

8.  Risk factors for surgical site infection following orthopaedic spinal operations.

Authors:  Margaret A Olsen; Jeffrey J Nepple; K Daniel Riew; Lawrence G Lenke; Keith H Bridwell; Jennie Mayfield; Victoria J Fraser
Journal:  J Bone Joint Surg Am       Date:  2008-01       Impact factor: 5.284

9.  Risk factors for postoperative spinal wound infections after spinal decompression and fusion surgeries.

Authors:  Anand Veeravagu; Chirag G Patil; Shivanand P Lad; Maxwell Boakye
Journal:  Spine (Phila Pa 1976)       Date:  2009-08-01       Impact factor: 3.468

10.  Risk factors for pulmonary complications after spine surgery.

Authors:  Felix Imposti; Amy Cizik; Richard Bransford; Carlo Bellabarba; Michael J Lee
Journal:  Evid Based Spine Care J       Date:  2010-08
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  18 in total

1.  Higher American Society of Anesthesiologists Classification Does Not Limit Safety or Improvement Following Minimally Invasive Transforaminal Lumbar Interbody Fusion.

Authors:  Conor P Lynch; Elliot D K Cha; Cara E Geoghegan; Caroline N Jadczak; Shruthi Mohan; Kern Singh
Journal:  Neurospine       Date:  2022-01-02

2.  Is the Centers for Medicare and Medicaid Services Hierarchical Condition Category Risk Adjustment Model Satisfactory for Quantifying Risk After Spine Surgery?

Authors:  Andrew K Chan; Shane Shahrestani; Alexander M Ballatori; Katie O Orrico; Geoffrey T Manley; Phiroz E Tarapore; Michael Huang; Sanjay S Dhall; Dean Chou; Praveen V Mummaneni; Anthony M DiGiorgio
Journal:  Neurosurgery       Date:  2022-05-16       Impact factor: 5.315

3.  External validation of the adult spinal deformity (ASD) frailty index (ASD-FI).

Authors:  Emily K Miller; Alba Vila-Casademunt; Brian J Neuman; Daniel M Sciubba; Khaled M Kebaish; Justin S Smith; Ahmet Alanay; Emre R Acaroglu; Frank Kleinstück; Ibrahim Obeid; Francisco Javier Sánchez Pérez-Grueso; Leah Y Carreon; Frank J Schwab; Shay Bess; Justin K Scheer; Virginie Lafage; Christopher I Shaffrey; Ferran Pellisé; Christopher P Ames
Journal:  Eur Spine J       Date:  2018-03-30       Impact factor: 3.134

4.  Prophylactic muscle flap reconstruction after complex spine surgery for degenerative disease: case series and institutional protocol.

Authors:  Nikhil Adapa; Nikhil Jain; Allison Capek; Rajiv Chandawarkar; Safdar N Khan; Yazeed M Gussous; Elizabeth Yu
Journal:  J Spine Surg       Date:  2018-09

5.  Who benefits more in osteoporotic fractures: Pedicle screw instrumentation or kyphoplasty for American Society of Anesthesiologists II/III patients?

Authors:  Tjark Tassemeier; Marcel Haversath; Moritz Schutzbach; Marcus Jäger
Journal:  J Craniovertebr Junction Spine       Date:  2018 Oct-Dec

6.  Sepsis and septic shock after craniotomy: Predicting a significant patient safety and quality outcome measure.

Authors:  Jingwen Zhang; Yan Icy Li; Thomas A Pieters; James Towner; Kevin Z Li; Mohammed A Al-Dhahir; Faith Childers; Yan Michael Li
Journal:  PLoS One       Date:  2020-09-17       Impact factor: 3.240

7.  Incidence and risk factors predicting deep venous thrombosis of lower extremity following spinal fractures.

Authors:  Jiangtao Ma; Pei Du; Jin Qin; Yali Zhou; Ningxi Liang; Jinglve Hu; Yingze Zhang; Yanbin Zhu
Journal:  Sci Rep       Date:  2021-01-28       Impact factor: 4.379

8.  Midterm outcome after posterior stabilization of unstable Midthoracic spine fractures in the elderly.

Authors:  U J Spiegl; P-L Hölbing; J-S Jarvers; N V D Höh; P Pieroh; G Osterhoff; C-E Heyde
Journal:  BMC Musculoskelet Disord       Date:  2021-02-15       Impact factor: 2.362

9.  Trends in Ambulatory Laminectomy in the USA and Key Factors Associated with Successful Same-Day Discharge: A Retrospective Cohort Study.

Authors:  Ellen M Soffin; James D Beckman; Jonathan C Beathe; Federico P Girardi; Gregory A Liguori; Jiabin Liu
Journal:  HSS J       Date:  2019-08-19

10.  Spinal Surgery in Patients Aged 80 Years and Older: Risk Stratification Using the Modified Frailty Index.

Authors:  Barry Kweh; Hui Lee; Terence Tan; Tom O'Donohoe; Joseph Mathew; Mark Fitzgerald; Dashiell Gantner; Tony Kambourakis; Kim Tew; Martin Hunn; Jeffrey Rosenfeld; Jin Tee
Journal:  Global Spine J       Date:  2020-03-30
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