Predictors of hospitalization for longer than one day following elective single-level anterior cervical discectomy and fusion: a retrospective case-control database study

Article information

Asian Spine J. 2025;.asj.2024.0321
Publication date (electronic) : 2025 March 4
doi : https://doi.org/10.31616/asj.2024.0321
1Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA
2Department of Neurosurgery, University of South Florida, Lakeland, FL, USA
3Department of Neurological Surgery, University of Wisconsin, Madison, WI, USA
4Department of Neurosurgery, Southern Illinois University, Springfield, IL, USA
5Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
Corresponding Author: Ankit Indravadan Mehta, Department of Neurosurgery, University of Illinois at Chicago, 912 South Wood Street, 451-N, Chicago, IL 60612, USA, Tel: +1-312-355-0510, Fax: +1-312-284-1097, E-mail: ankitm@uic.edu
Received 2024 August 5; Revised 2024 November 3; Accepted 2024 December 18.

Abstract

Study Design

A retrospective case-control study.

Purpose

To understand the risk factors for prolonged hospitalization following anterior cervical discectomy and fusion (ACDF) to reduce postoperative complications and better identify optimal candidates for elective ACDF.

Overview of Literature

Despite the proven safety of ACDF, many patients may experience prolonged postoperative hospitalization.

Methods

Data were collected from the American College of Surgeons National Surgical Quality Improvement Program dataset spanning 2017–2019. The primary outcome of interest was the length of stay (LOS). The study population was divided into two cohorts: those with LOS ≤1 day and those with LOS >1 day. Univariate and multivariate analyses were performed to identify predictors of LOS >1 day. Propensity score matching and group comparisons were used to evaluate pre- and post-discharge complication rates between the cohorts.

Results

A total of 12,906 patients with ACDF were identified in the database and considered eligible for the study. Of these patients, 69.5% had LOS ≤1 day and 30.5% had LOS >1 day. Factors associated with LOS >1 day included age ≥65 years, female sex, non-White race, American Society of Anesthesiologists classification 3, dependent functional status, and operation length of 120–150 minutes and >150 minutes. Patients with LOS >1 day were more likely to undergo intraoperative or postoperative blood transfusions (0.1% vs. 0.7%, p<0.001), unplanned reoperations (0% vs. 1.7%, p<0.001), and develop pneumonia during hospitalization (0% vs. 0.7%, p<0.001). These patients were also more likely to be readmitted (2.7% vs. 4.3%, p<0.001).

Conclusions

Older patients, those with poorer functional status, and those who undergo longer operative times are more likely to experience prolonged postoperative hospitalization. These patients are also at increased risk of complications such as pneumonia, blood transfusions, reoperation, and readmission. Careful patient selection for ACDF is essential to reduce the risk of prolonged hospitalization and associated complications.

Introduction

The aging populations in many countries have led to an increased demand for spine surgery to improve quality of life. Anterior cervical discectomy and fusion (ACDF) is a well-established procedure for managing cervical neck pain [1]. Specifically, ACDF is used to treat radiculopathy caused by nerve root impingement in the cervical spine [2]. It is performed only in cases of ongoing pain that nonsurgical interventions fail to alleviate. The number of ACDF procedures performed in the United States nearly doubled from 2003 to 2013 [3]. Between 2006 and 2013, one study found that ACDF was performed on average 137,000 times per year [4]. However, ACDF is not without risks, and postoperative complications can include hematoma, dysphagia, worsening myelopathy, cerebrospinal fluid leak, recurrent laryngeal nerve palsy, wound infection, Horner’s syndrome, radiculopathy, respiratory insufficiency, esophageal perforation, and instrument failure [5]. Past analyses of the safety of ACDF in the Medicare population have found that the procedure can be performed safely in an outpatient setting [6]. Consequently, ACDF is increasingly shifting toward becoming an outpatient procedure [7].

Despite the proven safety of ACDF, many patients may require hospitalization following the procedure. This can be particularly concerning given the high cost of ACDF, which ranges from US$26,653 to US$129,200 [8]. This high price, combined with the costs associated with hospitalization, can create significant financial burdens for both patients and providers. To minimize the need for hospitalization following ACDF, patient and surgical risk factors must be identified and optimized. Previous studies have found that advanced age, gender, race, insurance status, comorbidities, preoperative opioid use, multiple-level surgery, and preoperative anemia are associated with an extended length of stay (LOS) in the hospital following ACDF [8]. In this study, we utilized the American College of Surgeons National Surgery Quality Improvement Program (ACS-NSQIP) database to examine additional patient and surgical risk factors associated with hospitalization for more than one day following ACDF.

Materials and Methods

Data source

Data were collected from the ACS-NSQIP dataset from 2017 to 2019. The ACS-NSQIP database contains prospectively collected data from over 600 hospitals internationally, detailing surgical patient demographics, procedures, and adverse events within 30 days. This database has been widely used for outcomes research in the spine surgery literature [911]. The ACS-NSQIP data are audited for inter-observer agreement, with an overall disagreement rate of 2.3% [12]. Since the data are de-identified and publicly available, this study is exempt from review by our institutional review board, and patient consent was neither required nor sought. The dataset encodes diagnoses using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10) codes and procedures using the Current Procedural Terminology (CPT) system.

Inclusion and exclusion criteria for cohort selection

Patients were included if they had CPT code 22551 (anterior interbody fusion, with discectomy and decompression; cervical below C2) or 22554 (arthrodesis, anterior interbody technique, including minimal discectomy to prepare interspace [other than for decompression]; cervical below C2).

Individuals were excluded if they (1) were under 18 years of age; (2) underwent a revision procedure; (3) had an American Society of Anesthesiologists (ASA) classification of 4 or higher (since ASA >3 is considered a contraindication to discharge on postoperative day 1); (4) underwent an emergency or non-elective procedure; (5) received a multiple-level procedure, as identified by CPT codes 22552 or 22585; (6) had an ICD-10 or CPT code indicating deformity, infection, malignancy, dislocation, discectomy without fusion, osteotomy, non-anterior procedures, or non-cervical procedures; (7) had the procedure performed by someone other than a neurosurgeon or orthopedic surgeon; (8) received bone morphogenetic protein-2 (since the U.S. Food and Drug Administration issued a warning against its use in the cervical spine in 2008); (9) were hospitalized for more than 30 days (as ACS-NSQIP does not collect information on complications beyond that point); or (10) had missing data regarding discharge date.

Covariates

We collected information regarding patient age, sex, race, height, weight, ASA classification, functional status (independent or dependent), diabetes, smoking (within 1 year), chronic obstructive pulmonary disease (COPD), congestive heart failure, hypertension, corticosteroid use for a chronic condition, hematocrit, sodium, partial thromboplastin time (PTT), international normalized ratio (INR), platelets, leukocytes, surgeon specialty, operation length, and use of a graft (identified using CPT codes 20930, 20931, and 20936–20938).

Age was categorized at the 25th and 75th percentiles for the eligible study population, resulting in age groups of 18–57, 58–65, and >65 years. Anemia was defined as hematocrit below 41% in males and below 36% in females. Platelets were categorized as <150,000/μL or ≥150,000/μL; leukocytes as ≥12,000/μL, <4,000/μL, or in between; albumin as ≥3 g/dL or <3 g/dL; sodium as ≥135 mEq/L or <135 mEq/L; PTT as >40 seconds or ≤40 seconds; and INR as >1.4 or ≤1.4. Height and weight were used to calculate body mass index in kg/m2, and were then categorized into World Health Organization (WHO) class I obesity (30–34.9 kg/m2), WHO class II obesity or above (≥36 kg/m2), and non-obese. Graft type was categorized as allograft or autograft. Categories for operative time were determined by selecting the 30-minute intervals nearest to the 50th and 75th percentiles of the eligible study population (120 and 150 minutes, respectively).

Outcomes

The primary outcome of interest was LOS, defined as the number of calendar days between the day of the operation and the day of discharge. To investigate the patient characteristics associated with LOS >1 day, we divided the study population into cohorts of individuals with LOS ≤1 day and LOS >1 day. The LOS ≤1 cohort includes individuals discharged on the same day as the procedure or after one night of observation.

We were also interested in outcomes and complications within 30 days for each cohort. These included rates of unplanned readmission, reoperation, blood transfusion, wound-related infection (both superficial and deep surgical site infections), deep venous thrombosis (DVT), pulmonary embolism, sepsis, pneumonia, urinary tract infection, myocardial infarction, wound dehiscence, and acute renal failure. To understand which complications were experienced by patients with a longer hospital stay and which potentially precluded discharge, we studied rates of pre-discharge complications. Similarly, we compared rates of complications occurring after discharge to identify delayed complications that may not be immediately recognized or treated in patients discharged early or those who underwent procedures in the ambulatory setting.

Missing data

Missing data in the ACS-NSQIP are typically due to unmeasured laboratory values or missing comorbidity information not recorded by the participating institution. Baseline rates of missing data were assessed for each laboratory value, and those with <40% missing data were imputed using a non-parametric multiple imputation method (missForest), based on a random forest machine learning approach [13]. Variables imputed in this manner include hematocrit, leukocytes, platelets, sodium, and INR.

Statistical analysis

As all covariates were categorical, we first performed unadjusted comparisons between patients with LOS >1 day and LOS ≤1 day using Pearson’s chi-square test. To evaluate predictors of LOS >1, we conducted separate univariate logistic regression analyses for each covariate. Covariates with a p-value <0.20 on univariate analysis and present in >1.0% of the study population were entered into a final multivariate logistic regression model to avoid skewing the results with unrelated predictors. Variables that met these criteria and were incorporated into the model include age, sex, race, ASA classification, functional status, obesity, diabetes, hypertension, COPD, steroid use, anemia, platelets, leukocytes, sodium, operative length, and use of allograft. To determine whether individuals discharged within 1 day were at greater risk for pre- or post-discharge complications, we used a propensity score matching algorithm with a balanced nearest-neighbor approach, incorporating all collected covariates. We compared baseline characteristics in the matched groups using Pearson’s chi-square tests to ensure that differences were mitigated by matching. We also performed forward and backward stepwise logistic regression analysis over all collected covariates, using 30-day readmission as the outcome, to identify risk factors for readmission in patients discharged within 1 day.

An α of 0.05 was determined a priori to represent statistical significance. Due to the large number of independent comparisons, Bonferroni multiple comparisons correction was applied, resulting in an adjusted α=0.002 for the entire study [14]. Bonferroni correction is a statistical method used to correct for the random chance of finding a significant comparison at a given α value when performing numerous independent comparisons. Accordingly, we reported 99.8% confidence intervals (CIs) for all odds ratios (OR). All statistical analysis was performed using R ver. 3.6.3 (R Foundation for Statistical Computing, Vienna, Austria), stepwise logistic regression was performed using the R package MASS, and propensity score matching was performed using MatchIt ver. 3.0.2 (https://cran.r-project.org/package=MatchIt) [15,16].

Results

A total of 36,692 patients who received an ACDF from 2017 to 2019 were identified in the ACS-NSQIP database. After applying all exclusion criteria, 12,906 patients were considered eligible for the study. Of these, 8,972 (69.5%) had a LOS ≤1 day, and 3,934 (30.5%) had LOS >1 day (Fig. 1). A complete listing of baseline patient characteristics and comorbidities for the entire study population, stratified by LOS cohort, is displayed in Table 1.

Fig. 1

Identification and exclusion of patient population. NSQIP, National Surgery Quality Improvement Program; ACDF, anterior cervical discectomy and fusion; ASA, American Society of Anesthesiologists; LOS, length of stay.

Demographics and operative characteristics of the study population

Fig. 2 illustrates the results of the multivariate logistic regression model for LOS. Age 65 years or older (OR, 1.5; 99.8% CI, 1.27–1.77; p<0.001), female sex (OR, 1.57; 99.8% CI, 1.38–1.8; p<0.001), Black race (OR, 1.93; 99.8% CI, 1.58–2.36; p<0.001), other race (OR, 1.74; 99.8% CI, 1.42–2.13; p<0.001), Hispanic ethnicity (OR, 2.02; 99.8% CI, 1.54–2.64; p<0.001), ASA classification 3 (OR, 1.4; 99.8% CI, 1.21–1.61; p<0.001), dependent functional status (OR, 3.25; 99.8% CI, 1.97–5.46; p<0.001), and operation length of 120–150 minutes (OR, 1.95; 99.8% CI, 1.63–2.32; p<0.001) and >150 minutes (OR, 4.59; 99.8% CI, 3.97–5.32; p<0.001) were associated with LOS >1. The model further revealed that receiving an allograft was associated with LOS ≤1 (OR, 0.71; 99.8% CI, 0.62–0.81; p<0.001), which was the only significant predictor of LOS ≤1 among the covariates studied.

Fig. 2

Adjusted analysis of independent predictors for length of stay (LOS) >1 with all-inclusive multivariate logistic regression; bold indicates statistical significance after Bonferroni correction (α=0.002). CI, confidence interval; Ref, reference; ASA, American Society of Anesthesiologists; COPD, chronic obstructive pulmonary disease.

All baseline differences between the study cohorts were completely eliminated by propensity score matching, as all matched groups were similar in all collected characteristics (Supplement 1). In terms of pre-discharge complication rates, patients with LOS >1 were more likely to have undergone intraoperative or postoperative blood transfusions (0.1% versus 0.7%, p<0.001), unplanned reoperations (0% versus 1.7%, p<0.001), and were more likely to develop pneumonia (0% versus 0.7%, p<0.001) while hospitalized (Table 2). Patients with LOS >1 were also more likely to be readmitted (2.7% versus 4.3%, p<0.001).

Comparison of pre- and post-discharge complications within 30 days between matched cohorts

Table 3 displays the results of the stepwise logistic regression model for 30-day unplanned readmission for patients with LOS ≤1. The factors that demonstrated the strongest associations (and were subsequently included in the final regression) were advanced age, female sex, non-White race, ASA classification 3, obesity, diabetes, anemia, and operation length. Of these, ASA classification 3 was the only covariate that reached statistical significance (OR, 1.68; 99.8% CI, 1.03–2.75; p=0.001).

Stepwise logistic regression model for predictors of 30-day unplanned readmission in patients discharged within 1 day

Discussion

This retrospective case-control study assessed perioperative risk factors, complications, and readmissions associated with single-level ACDF. Using the ACS-NSQIP database from 2017 to 2019, we found that preoperative risk factors for LOS >1 included age >65 years, female sex, non-White identity, ASA class 3, and dependent functional status. Intraoperative factors associated with LOS >1 included operative length >120 minutes, while receiving an allograft was associated with LOS ≤1. Pre-discharge complications linked to extended LOS were perioperative blood transfusion, reoperation, and pneumonia, while postoperative complications included readmission. As the volume of ACDFs increases, identifying which patients undergoing single-level ACDF are appropriate for the outpatient setting would help reduce costs and potential complications.

Risk factors for prolonged length of stay

Preoperative factors associated with LOS >1 for single-level ACDF included age >65 years, female sex, non-White identity, ASA class 3, and dependent functional status. Increased age has been associated with extended LOS, readmission, and complications following ACDF in other studies, and was present in our analysis. Older patients tend to have more comorbidities, fewer physiological reserves, and decreased access to personal and social resources [17]. Female sex is a significant marker for prolonged LOS. In a case series of 4,995 patients undergoing transforaminal lumbar interbody fusion, female sex was associated with increased rates of admission [18]. Furthermore, prior reports have found that females had higher utilization of healthcare resources before surgery, although some studies have reported contrasting findings, indicating that this result may require further investigation [18,19]. Non-White race as a factor for LOS >1 may be attributed to decreased socioeconomic status. Existing studies have linked socioeconomic factors, such as insurance status, marital status, and race, to differing surgical outcomes [8,20]. In a case series of 1,896 patients undergoing ACDF, non-White race was significantly associated with increased LOS [8]. A separate case series of 278 patients found non-White race associated with longer LOS and a larger percentage of extended stays [20]. However, the impact of race on surgical outcomes and LOS is controversial, as other studies have found no differences in outcomes [21]. ASA class is a general marker for health and comorbidities, used to evaluate patients before surgery [22]. Higher ASA class has been shown in other spine studies to be associated with extended LOS and worse outcomes [8,23]. Dependent functional status is a significant marker of extended LOS. These patients are typically associated with more medical comorbidities and a diminished ability to perform activities of daily living and instrumental activities of daily living [24]. In one national database study of 17,075 patients undergoing elective cervical spine surgery, dependent functional status was associated with increased mortality and 30-day complications, including sepsis, pulmonary, renal, and cardiac complications [24].

Intraoperative factors associated with LOS >1 included operative length >120 minutes and perioperative blood transfusion. Increased operative length suggests higher case complexity and may be associated with a greater risk of complications and blood loss [25]. Additionally, patients who receive perioperative blood transfusions are often associated with higher estimated blood loss and lower preoperative hemoglobin levels, suggesting more comorbidities [25]. Prior reports have also found that patients undergoing cervical surgery who receive perioperative blood transfusions are at higher risk of extended LOS and perioperative complications [26,27]. However, the use of allografts was significantly associated with decreased LOS. In comparison, autografts require additional incisions in the iliac crest to harvest graft material, which has previously been associated with increased donor site pain and may be relevant in this cohort [8]. Consequently, these patients may have required more robust pain management before discharge.

Any clinical complication requiring inpatient management will extend LOS. However, in this analysis, pre-discharge complications associated with extended LOS included reoperation and pneumonia. Immediate reoperation after the initial surgery may result from life-threatening complications such as hemorrhage or infection [28]. Specifically, in ACDF, esophageal perforation, instrumentation failure, expanding cervical hematoma, and CSF leaks have been previously reported as complications necessitating reoperation [29]. Another complication unique to ACDF is dysphagia and recurrent laryngeal nerve injury due to traction and the proximity of the esophagus and other structures [30]. These patients are more susceptible to aspiration pneumonia due to impaired swallowing, requiring longer inpatient management to treat their complications.

Limitations

As this study utilized a large, retrospective national database, there are limitations. The ACS-NSQIP database variables were not selected specifically to examine risk factors and complications associated with single-level ACDF. As such, many complications associated with ACDF, including dysphagia and pseudarthrosis, are not quantified in the database. These would provide further clarity on the causes of reoperation and extended LOS. Perioperative complications, such as DVT, pulmonary embolism, sepsis, myocardial infarction, and excessive wound drainage, may require further inpatient management after surgery and would be associated with longer LOS. However, these values, particularly for pulmonary embolism, trended towards significance, indicating that this study would benefit from increased power. Additionally, a significant degree of variation in surgeon preferences regarding decisions such as surgical drain placement, direct or indirect decompression, and discharge criteria is not captured in this analysis. Regardless, with rising costs and complications associated with extended LOS, these results may help identify patients who would benefit from surgery in the ambulatory setting.

Conclusions

In this retrospective case-control study utilizing a large national surgical database, we determined that age >65 years, female sex, non-White race, ASA class 3, dependent functional status, and operative length >120 minutes were associated with LOS >1 day. Subsequently, these patients experienced higher rates of perioperative blood transfusion, reoperation, pneumonia, and hospital readmission. The use of an allograft implant was associated with LOS ≤1. Surgeons may consider these risk and protective factors to help select appropriate patients for outpatient ACDF, minimizing the risk of extended LOS.

Key Points

  • Approximately 30% of patients undergoing elective anterior cervical discectomy and fusion (ACDF) experience a length of stay of 1 day or more (LOS >1).

  • Age ≥65 years, female sex, American Society of Anesthesiologists classification 3, dependent functional status, and operation lengths of 120–150 minutes and >150 minutes were associated with LOS >1.

  • Patients with LOS >1 were more likely to undergo intraoperative or postoperative blood transfusions, unplanned reoperations, and to develop pneumonia during hospitalization.

  • Patients with LOS >1 are more likely to be readmitted after discharge.

  • Careful patient selection for ACDF is essential to reduce the risk of prolonged hospitalization and associated complications.

Notes

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Acknowledgments

The American College of Surgeons National Surgical Quality Improvement Program and the hospitals participating in the ACS-NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.

Author Contributions

Conceptualization: NSC. Data curation: DA. Formal analysis: SHJ, JWN, DA. Project administration: AIM. Supervision: NSC, SP, AIM. Writing–original draft: SHJ, JWN, JZN, AG, JP. Writing–review & editing: SHJ, NSC, JWN, SP. Final approval of the manuscript: all authors.

Supplementary Materials

Supplementary materials can be available from https://doi.org/10.31616/asj.2024.0321.

Supplement 1. Baseline characteristics of the propensity-score matched cohorts.

asj-2024-0321-Supplement-1.pdf

References

1. Shen FH, Samartzis D, Khanna N, Goldberg EJ, An HS. Comparison of clinical and radiographic outcome in instrumented anterior cervical discectomy and fusion with or without direct uncovertebral joint decompression. Spine J 2004;4:629–35.
2. Rhee JM, Ju KL. Anterior cervical discectomy and fusion. JBJS Essent Surg Tech 2016;6:e37.
3. Elsamadicy AA, Koo AB, Reeves BC, et al. Octogenarians are independently associated with extended LOS and non-routine discharge after elective ACDF for CSM. Global Spine J 2022;12:1792–803.
4. Saifi C, Cazzulino A, Laratta J, et al. Utilization and economic impact of posterolateral fusion and posterior/transforaminal lumbar interbody fusion surgeries in the United States. Global Spine J 2019;9:185–90.
5. Epstein NE. A review of complication rates for anterior cervical diskectomy and fusion (ACDF). Surg Neurol Int 2019;10:100.
6. Rossi V, Asher A, Peters D, et al. Outpatient anterior cervical discectomy and fusion in the ambulatory surgery center setting: safety assessment for the Medicare population. J Neurosurg Spine 2019;32:360–5.
7. Shenoy K, Adenikinju A, Dweck E, Buckland AJ, Bendo JA. Same-day anterior cervical discectomy and fusion-our protocol and experience: same-day discharge after anterior cervical discectomy and fusion in suitable patients has similarly low readmission rates as admitted patients. Int J Spine Surg 2019;13:479–85.
8. Dial BL, Esposito VR, Danilkowicz R, et al. Factors associated with extended length of stay and 90-day readmission rates following ACDF. Global Spine J 2020;10:252–60.
9. Bhimani AD, Selner AN, Patel JB, et al. Pediatric tethered cord release: an epidemiological and postoperative complication analysis. J Spine Surg 2019;5:337–50.
10. Bhimani AD, Rosinski CL, Patel S, et al. Adult spinal arteriovenous malformations: natural history and a multicenter study of short-term surgical outcomes. World Neurosurg 2019;132:e290–6.
11. Karhade AV, Larsen AM, Cote DJ, Dubois HM, Smith TR. National databases for neurosurgical outcomes research: options, strengths, and limitations. Neurosurgery 2018;83:333–44.
12. American College of Surgeons. User guide for the 2017 ACS NSQIP participant use data file (PUF) Chicago (IL): American College of Surgeons; 2018.
13. Stekhoven DJ, Bühlmann P. MissForest: non-parametric missing value imputation for mixed-type data. Bioinformatics 2012;28:112–8.
14. Armstrong RA. When to use the Bonferroni correction. Ophthalmic Physiol Opt 2014;34:502–8.
15. Venables WN, Ripley BD. Modern applied statistics with S 4th edth ed. New York (NY): Springer; 2002.
16. Ho D, Imai K, King G, Stuart EA. MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw 2011;42:1–28.
17. Di Capua J, Somani S, Kim JS, et al. Elderly age as a risk factor for 30-day postoperative outcomes following elective anterior cervical discectomy and fusion. Global Spine J 2017;7:425–31.
18. Garcia RM, Khanna R, Dahdaleh NS, Cybulski G, Lam S, Smith ZA. Thirty-day readmission risk factors following single-level Transforaminal Lumbar Interbody Fusion (TLIF) for 4992 patients from the ACS-NSQIP database. Global Spine J 2017;7:220–6.
19. Siccoli A, Staartjes VE, de Wispelaere MP, Schroder ML. Gender differences in degenerative spine surgery: do female patients really fare worse? Eur Spine J 2018;27:2427–35.
20. Woodard TK, Cortese BD, Gupta S, Mohanty S, Casper DS, Saifi C. Racial differences in patients undergoing anterior cervical discectomy and fusion: a multi-site study. Clin Spine Surg 2022;35:176–80.
21. Elsamadicy A, Adogwa O, Reiser E, Fatemi P, Cheng J, Bagley C. The effect of patient race on extent of functional improvement after cervical spine surgery. Spine (Phila Pa 1976) 2016;41:822–6.
22. Daabiss M. American Society of Anaesthesiologists physical status classification. Indian J Anaesth 2011;55:111–5.
23. Somani S, Capua JD, Kim JS, et al. ASA classification as a risk stratification tool in adult spinal deformity surgery: a study of 5805 patients. Global Spine J 2017;7:719–26.
24. Minhas SV, Mazmudar AS, Patel AA. Pre-operative functional status as a predictor of morbidity and mortality after elective cervical spine surgery. Bone Joint J 2017;99-B:824–8.
25. Gruskay JA, Fu M, Basques BA, et al. Factors affecting length of stay and complications after elective anterior cervical discectomy and fusion: a study of 2164 patients from the American College of Surgeons National Surgical Quality Improvement Project Database (ACS NSQIP). Clin Spine Surg 2016;29:E34–42.
26. Yuk FJ, Maniya AY, Rasouli JJ, Dessy AM, McCormick PJ, Choudhri TF. Factors affecting length of stay following elective anterior and posterior cervical spine surgery. Cureus 2017;9:e1452.
27. Aoude A, Aldebeyan S, Fortin M, et al. Prevalence and complications of postoperative transfusion for cervical fusion procedures in spine surgery: an analysis of 11,588 patients from the American College of Surgeons National Surgical Quality Improvement Program Database. Asian Spine J 2017;11:880–91.
28. Kim TK, Yoon JR, Choi YN, Park UJ, Kim KR, Kim T. Risk factors of emergency reoperations. Anesth Pain Med (Seoul) 2020;15:233–40.
29. Yee TJ, Swong K, Park P. Complications of anterior cervical spine surgery: a systematic review of the literature. J Spine Surg 2020;6:302–22.
30. Anderson KK, Arnold PM. Oropharyngeal dysphagia after anterior cervical spine surgery: a review. Global Spine J 2013;3:273–86.

Article information Continued

Fig. 1

Identification and exclusion of patient population. NSQIP, National Surgery Quality Improvement Program; ACDF, anterior cervical discectomy and fusion; ASA, American Society of Anesthesiologists; LOS, length of stay.

Fig. 2

Adjusted analysis of independent predictors for length of stay (LOS) >1 with all-inclusive multivariate logistic regression; bold indicates statistical significance after Bonferroni correction (α=0.002). CI, confidence interval; Ref, reference; ASA, American Society of Anesthesiologists; COPD, chronic obstructive pulmonary disease.

Table 1

Demographics and operative characteristics of the study population

Characteristic Total (n=12,906) LOS ≤1 day (n=8,972) LOS >1 day (n=3,934) p-valuea)
Age (yr) <0.001b)
 18–57 6,574 (50.9) 4,819 (53.7) 1,755 (44.6)
 58–65 3,180 (24.6) 2,172 (24.2) 1,008 (25.6)
 >65 3,152 (24.4) 1,981 (22.1) 1,171 (29.8)
Female 6,270 (48.6) 4.197 (46.8) 2,073 (52.69) <0.001b)
Race <0.001b)
 Caucasian 9,488 (73.5) 6,976 (77.8) 2,512 (63.9)
 Black 1,394 (10.8) 783 (8.7) 611 (15.5)
 Hispanic 682 (5.3) 390 (4.3) 292 (7.4)
 Other/not reported 1,342 (10.4) 823 (9.2) 519 (13.2)
ASA classification <0.001b)
 1–2 6,683 (51.8) 5,015 (55.9) 1,668 (42.4)
 3 6,223 (48.2) 3,957 (44.1) 2,266 (57.6)
Obesity <0.001b)
 WHO class I 3,449 (26.7) 2,408 (26.8) 1,041 (26.5)
 WHO class II or III 2,739 (21.2) 1,820 (20.3) 919 (10.2)
Dependent functional status 198 (1.5) 66 (0.7) 132 (1.5) <0.001b)
Diabetes mellitus <0.001b)
 Non-insulin 1,466 (11.4) 937 (10.4) 529 (5.9)
 Insulin 794 (6.2) 465 (11.8) 329 (8.4)
Current smoker 3,127 (24.2) 2,197 (24.5) 930 (23.6) 0.301
Hypertension 6,403 (49.6) 4,247 (47.3) 2,156 (54.8) <0.001b)
Chronic obstructive pulmonary disease 625 (4.8) 382 (4.3) 243 (6.2) <0.001b)
Congestive heart failure 43 (0.3) 24 (0.3) 19 (0.5) 0.051
Chronic steroid use 421 (3.3) 257 (2.9) 164 (4.2) <0.001b)
Anemia 1,977 (15.3) 1,204 (13.4) 773 (19.6) <0.001b)
Leukocytes 0.131
 ≥12,000/μL 380 (2.9) 265 (3.0) 115 (1.3)
 <4,000/uL 296 (2.2) 190 (4.8) 106 (1.2)
Platelets <150,000/μL 473 (3.7) 293 (3.3) 180 (4.6) <0.001b)
Sodium <135 mEq/L 372 (2.9) 226 (2.5) 146 (3.7) <0.001b)
PTT >40 seconds 86 (0.7) 52 (0.6) 34 (0.9) <0.001b)
INR >1.4 38 (0.3) 20 (0.2) 18 (0.5) 0.024
Surgeon specialty 0.094
 Neurosurgery 9,519 (73.8) 6,656 (74.2) 2,863 (72.8)
 Orthopedics 3,387 (26.2) 2,316 (25.8) 1,071 (27.22)
Autograft 2,320 (18.0) 1,621 (18.1) 699 (17.8) 0.684
Allograft 4,525 (35.1) 3,367 (37.5) 1,158 (29.4) <0.001b)
Operative time (min) <0.001b)
 <120 6,120 (47.4) 5,034 (56.1) 1,086 (27.6)
 120–150 2,549 (19.8) 1,787 (19.9) 762 (19.4)
 >150 4,237 (32.8) 2,151 (24.0) 2,086 (53.0)

Values are presented as number (%), unless otherwise stated.

LOS, length of stay; ASA, American Society of Anesthesiologists; PTT, partial thromboplastin time; INR, international normalized ratio.

a)

Statistical tests performed: Pearson’s chi-square test of independence or Welch’s two sample t-test.

b)

Significant after applying Bonferroni correction (α=0.002).

Table 2

Comparison of pre- and post-discharge complications within 30 days between matched cohorts

Outcome Pre-discharge Post-discharge


LOS ≤1 day (n=3,605) Matched LOS >1 day (n=3,605) p-value LOS ≤1 day (n=3,605) Matched LOS >1 day (n=3,605) p-valuea)
Intraoperative durotomy 2 (0.1) 7 (0.2) 0.095 - - -

Intraoperative or postoperative blood transfusion 5 (0.1) 27 (0.7) <0.001b) 0 0 1.000

Unplanned readmission - - - 98 (2.7) 155 (4.3) <0.001b)

Unplanned reoperation 1 (0) 63 (1.7) <0.001b) 28 (0.8) 42 (1.2) 0.093

Deep venous thrombosis 0 6 (0.2) 0.014 7 (0.2) 13 (0.4) 0.179

Pulmonary embolism 0 7 (0.2) 0.008 8 (0.2) 13 (0.4) 0.275

Sepsis 6 (0.2) 15 (0.4) 0.049 0 0 1.000

Pneumonia 0 26 (0.7) <0.001b) 11 (0.3) 12 (0.3) 0.835

Urinary tract infection 2 (0.1) 11 (0.3) 0.012 15 (0.4) 20 (0.6) 0.397

Wound-related infection 6 (0.2) 15 (0.4) 0.049 7 (0.2) 16 (0.4) 0.06

Wound dehiscence 0 3 (0.1) 0.083 0 0 1.000

Myocardial infarction 0 5 (0.1) 0.025 1 (0) 3 (0.1) 0.317

Acute renal failure 0 0 1.000 0 0 1.000

Values are presented as number (%), unless otherwise stated.

LOS, length of stay.

a)

Statistical tests performed: Pearson’s chi-square test of independence.

b)

Significant after applying Bonferroni correction (α=0.002).

Table 3

Stepwise logistic regression model for predictors of 30-day unplanned readmission in patients discharged within 1 day

Factor 30-Day unplanned readmission for patients with LOS ≤1
Crude no. (%)a) OR (99.8% CI) p-value
Age 58–65 yr 52/2,172 (2.4) 1.18 (0.66–2.05) 0.36
Age >65 yr 66/1,981 (3.3) 1.53 (0.88–2.64) 0.016
Female sex 79/4,197 (1.9) 0.81 (0.50–1.28) 0.151
Black 30/783 (3.8) 1.75 (0.88–3.21) 0.007
Hispanic 12/390 (3.1) 1.51 (0.51–3.54) 0.182
Other/unreported race 14/823 (1.7) 0.78 (0.29–1.73) 0.384
ASA classification 3 121/3,957 (3.1) 1.68 (1.03–2.75) 0.001b)
Obesity class II or III 47/2,408 (2.0) 0.67 (0.38–1.14) 0.023
Obesity class II or III 36/1,820 (2.0) 0.62 (0.32–1.14) 0.019
Diabetes, non-insulin 28/937 (3.0) 1.19 (0.58–2.24) 0.431
Diabetes, insulin 23/465 (4.9) 2.01 (0.90–4.07) 0.004
Anemia 44/1,199 (3.7) 1.32 (0.73–2.27) 0.13
Operation time 120–150 min 42/1,787 (2.4) 1.16 (0.63–2.03) 0.437
Operation time >150 min 63/2,151 (2.9) 1.46 (0.87–2.43) 0.021

LOS, length of stay; OR, odds ratio; CI, confidence interval; ASA, American Society of Anesthesiologists.

a)

Readmitted from subgroup/subgroup population (%).

b)

Significant after applying Bonferroni correction (α=0.002).