Evaluate the factors associated with postoperative ICU admission in patients undergoing surgical management of degenerative lumbar spine disease.
Patients undergoing surgery for degenerative lumbar spine disease were enrolled into a prospective registry over a 2-year period. Preoperative variables (age, gender, ASA grade, ODI %, CAD, HTN, MI, CHF, DM, BMI, depression, anxiety) and surgical variables (instrumentation, arthrodesis, estimated blood loss, length of surgery) were collected prospectively. Postoperative ICU admission details were retrospectively determined from the electronic medical record. Student’s t test (continuous variables) and Chi-square test (categorical variables) were used to determine the association of each preoperative and surgical variable with ICU admission.
808 Patients (273 laminectomy, 535 laminectomy and fusion) were evaluated. Forty-one (5.1 %) patients were found to have postoperative ICU admissions. Reasons for admission included blood loss (12.2 %), cardiac (29.3 %), respiratory (19.5 %), neurologic (31.7 %), and other (7.3 %). For preoperative variables, female gender (P < 0.001), history of CAD (P = 0.003), history of MI (P = 0.008), history of CHF (P = 0.001), age (P = 0.025), and ASA grade (P = 0.008) were significantly associated with ICU admission. For surgical variables, estimated blood loss (P < 0.001) and length of surgery (P < 0.001) were significantly associated with ICU admission.
Age, female gender, ASA grade, cardiac comorbidities, intraoperative blood loss, and length of surgery were associated with increased risk of postoperative ICU admission. Knowledge of these factors can aid surgeons in patient selection and preoperative discussion with patients about potential need for unexpected admission to the ICU.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
NHE Fact Sheet (2014) http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NHE-Fact-Sheet.html. Accessed 11 March 2015
Pastores S, Dakwar J, Halpern NA (2012) Costs of critical care medicine. Crit Care Clin 28(1):1–10
Halpern N, Pastores S (2010) Critical care medicine in the United States 2000–2005: an analysis of bed numbers, occupancy rates, payer mix, and costs. Crit Care Med 38(1):65–71
Coopersmith C, Wunsch H, Fink M et al (2012) A comparison of critical care research funding and the financial burden of critical illness in the United States. Crit Care Med 40(4):1072–1079
Halpern N (2009) Can the costs of critical care be controlled? Curr Opin Crit Care 15(6):591–596
Patient Protection and Affordable Care Act (2010) In: Congress US (ed) 111–148
Delisle D (2013) Big things come in bundled packages: implications of bundled payment systems in health care reimbursement reform. Am J Med Qual 28(4):339–344
Froimson M, Rana A, White RJ et al (2013) Bundled payments for care improvement initiative: the next evolution of payment formulations: AAHKS Bundled Payment Task Force. J Arthroplast 28(8 suppl):157–165
Bushnell B (2015) Bundled payments in orthopedic surgery. Orthopedics 38(2):128–135
Schutzer S (2015) Bundled payment programs: how to get started: assessing readiness and bringing the stakeholders to the table. J Arthroplast 30(3):343–345
Hamilton M, Cecconi M, Rhodes A (2011) A systematic review and meta-analysis on the use of preemptive hemodynamic intervention to improve postoperative outcomes in moderate and high-risk surgical patients. Anesth Analg 112(6):1392–1402
Ghaferi A, Birkmeyer J, Dimick J (2009) Variation in hospital mortality associated with inpatient surgery. N Engl J Med 361:1368–1375
Chang C, Jiang C (1997) Evaluation of critical postoperative situations in orthopedic patients. J Formos Med Assoc 96(12):990–995
AbdelSalam H, Restrepo C, Tarity T, Sangster W, Parvizi J (2012) Predictors of intensive care unit admission after total joint arthroplasty. J Arthroplast 27(5):720–725
Kamath A, McAuliffe C, Gutsche J et al (2013) Intensive care monitoring after total joint replacement. Bone Joint J 11(Suppl A(95-B)):74–76
Pinheiro L, Santoro I, Perfeito J, Izbicki M, Ramos R, Faresin S (2015) Preoperative predictive factors for intensive care unit admission after pulmonary resection. J Bras Pneumol 41(1):31–38
Sudarshan M, Feldman L, St Louis E et al (2015) Predictors of mortality and morbidity for acute care surgery patients. J Surg Res 193(2):868–873
Helling T, Martin L, Martin M, Mitchell M (2014) Failure events in transition of care for surgical patients. J Am Coll Surg 218(4):723–731
Weinstein J, Lurie J, Olson P, Bronner K, Fisher E (2006) United States’ trends and regional variations in lumbar spine surgery: 1992–2003. Spine (Phila Pa 1976) 31:2707–2714
Deyo R, Mirza S, Bartin B, Kreuter W, Goodman D, Jarvik J (2010) Trends, major medical complications, and charges associated with surgery for lumbar spinal stenosis in older adults. JAMA 303:1259–1265
Menke H, Klein A, John KD et al (1993) Predictive value of ASA classification for the assessment of the perioperative risk. Int Surg 78(3):266–270
Wolters U, Wolf T, Stützer H et al (1996) ASA classification and perioperative variables as predictors of postoperative outcome. Br J Anaesth 77(2):217–222
Garcia AE, Bonnaig JV, Yoneda ZT et al (2012) Patient variables which may predict length of stay and hospital costs in elderly patients with hip fracture. J Orthop Trauma 26(11):620–623
Joshi Y, Ali M, Pradhan N et al (2012) Correlation between ASA grade, BMI, and length of stay of patients undergoing primary hip and knee arthroplasty. Does ‘cherry picking’ by the ITC affect NHS hospitals? J Bone Joint Surg Br 94-B no(SUPP IV):9
Fairbank JC, Couper J, Davies JB, O’Brien JP (1980) The Oswestry low back pain disability questionnaire. Physiotherapy 66:271–273
Fairbank JC, Pynsent PB (2000) The Oswestry disability index. Spine 25:2940–2952 ; discussion 2952
McAlinden NM, Oei TP (2006) Validation of the quality of life inventory for patients with anxiety and depression. Compr Psychiatry 47:307–314
Zung WW, Richards CB, Short MJ (1965) Self-rating depression scale in an outpatient clinic. Further validation of the SDS. Arch Gen Psychiatry 13:508–515
Thurber S, Snow M, Honts CR (2002) The Zung Self-Rating Depression Scale: convergent validity and diagnostic discrimination. Assessment 9:401–405
Donaldson MB, Learman K, Wright A et al (2011) Factor structure and concurrent/convergent validity of the modified somatic perception questionnaire and pain beliefs instrument. J Manipulative Physiol Ther 34(1):30–36
Deyo RA, Walsh NE, Schoenfeld LS, Ramamurthy S (1989) Studies of the modified somatic perceptions Questionnaire (MSPQ) in patients with back pain: Psychometric and predictive properties. Spine (Phila Pa 1976) 14(5):507–510
Rhodes A, Moreno RP, Metnitz B et al (2011) Epidemiology and outcome following post-surgical admission to critical care. Intensive Care Med 37(9):1466–1472
Bos MM, Bakhshi-Raiez F, Dekker JW et al (2013) Outcomes of intensive care unit admissions after elective cancer surgery. Eur J Surg Oncol 39(6):584–592
Haynes SR, Lawler PG (1995) An assessment of the consistency of ASA physical status classification allocation. Anaesthesia 50(3):195–199
Owens WD, Felts JA, Spitznagel EL (1978) ASA physical status classification: a study of consistency of ratings. Anaesthesia 49(4):239–243
Sobol JB, Gershengorn HB, Wunsch H, Li G (2013) The surgical Apgar score is strongly associated with intensive care unit admission after high-risk intraabdominal surgery. Anesth Analg 117(2):438–446
Conflict of interest
About this article
Cite this article
Kay, H.F., Chotai, S., Wick, J.B. et al. Preoperative and surgical factors associated with postoperative intensive care unit admission following operative treatment for degenerative lumbar spine disease. Eur Spine J 25, 843–849 (2016). https://doi.org/10.1007/s00586-015-4175-8