Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-25T08:54:56.589Z Has data issue: false hasContentIssue false
  • English
  • Français

Prediction tool for high risk of surgical site infection in spinal surgery

Published online by Cambridge University Press:  24 April 2020

Takanori Namba ,
Masaki Ueno ,
Gen Inoue ,
Takayuki Imura ,
Wataru Saito ,
Toshiyuki Nakazawa ,
Masayuki Miyagi ,
Eiki Shirasawa ,
Osamu Takahashi  and
Masashi Takaso
Takanori Namba
Affiliation:
Department of Orthopaedic Surgery, Sagamidai Hospital, Kanagawa, Japan
Masaki Ueno*
Affiliation:
Department of Orthopaedic Surgery, Machida Keisen Hospital, Tokyo, Japan
Gen Inoue
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Takayuki Imura
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Wataru Saito
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Toshiyuki Nakazawa
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Masayuki Miyagi
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Eiki Shirasawa
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
Osamu Takahashi
Affiliation:
Department of General Internal Medicine, St. Luke’s International Hospital, Tokyo, Japan
Masashi Takaso
Affiliation:
Department of Orthopaedic Surgery, Kitasato University School of Medicine, Kanagawa, Japan
*
Author for correspondence: Masaki Ueno, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

The incidence of surgical site infection (SSI) is higher in spinal surgeries than in general orthopedic operations. In this study, we aimed to develop a scoring system with reduced health care costs for detecting spinal surgery patients at high risk for SSI.

Design:

Retrospective cohort study.

Patients:

In total, 824 patients who underwent spinal surgery at 2 university hospitals from September 2005 to May 2011.

Methods:

We reviewed the medical records of 824 patients, and we examined 19 risk factors to identify high-risk patients. After narrowing down the variables by univariate analysis, multiple logistic analysis was performed for factors with P values <.2, using SSI as a dependent variable. Only factors that showed P values <.05 were included in the final models, and each factor was scored based on the β coefficient values obtained. The clinical prediction rules were thereby prepared.

Results:

“Emergency operation,” “blood loss >400 mL,” “presence of diabetes,” “presence of skin disease,” and “total serum albumin value <3.2 g/dL” were detected by multivariable modeling and were incorporated into the risk scores. Applying these 5 independent predictive factors, we were able to predict the infection incidence after spinal surgery.

Conclusions:

Our present study could aid physicians in making decisions regarding prevention strategies in patients undergoing spinal surgery. Stratification of risks employing this scoring system will facilitate the identification of patients most likely to benefit from complex, time-consuming and expensive infection prevention strategies, thereby possibly reducing healthcare costs.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 41 , Issue 7 , July 2020 , pp. 799 - 804
Check for updates
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

de Lissovoy, G, Fraeman, K, Hutchins, V, Murphy, D, Song, D, Vaughn, BB. Surgical site infection: incidence and impact on hospital utilization and treatment costs. Am J Infect Control 2009;37:387–397.CrossRefGoogle ScholarPubMed
Rosenthal, NA, Heinrich, KH, Chung, J, Yu, H. Cost and hospital resource utilization of Staphylococcus aureus infection post elective posterior instrumented spinal fusion surgeries in US hospitals: a retrospective cohort study. Spine (Phila Pa 1976) 2019;44:637–646.CrossRefGoogle Scholar
Weinstein, MA, McCabe, JP, Cammisa, FP Jr. Postoperative spinal wound infection: a review of 2,391 consecutive index procedures. J Spinal Disord 2000;13:422–436.CrossRefGoogle ScholarPubMed
Sponseller, PD, LaPorte, DM, Hungerford, MW, Eck, K, Bridwell, KH, Lenke, LG. Deep wound infections after neuromuscular scoliosis surgery: a multicenter study of risk factors and treatment outcomes. Spine (Phila Pa 1976) 2000;25:2461–2466.CrossRefGoogle ScholarPubMed
Davne, SH, Myers, DL. Complications of lumbar spinal fusion with transpedicular instrumentation. Spine (Phila Pa 1976) 1992;17 suppl 6:S184–S189.CrossRefGoogle ScholarPubMed
Chang, FY, Chang, MC, Wang, ST, Yu, WK, Liu, CL, Chen, TH. Can povidone-iodine solution be used safely in a spinal surgery? Eur Spine J 2006;15:1005–1014.CrossRefGoogle Scholar
De Luna, V, Mancini, F, De Maio, F, Bernardi, G, Ippolito, E, Caterini, R. Intraoperative disinfection by pulse irrigation with povidone-iodine solution in spine surgery. Adv Orthop 2017;2017:7218918.CrossRefGoogle ScholarPubMed
Tokyo: practical guideline for management of MRSA infection [in Japanese]. The Japanese Association for Infectious Diseases website. http://www.kansensho.or.jp/uploads/files/guidelines/guideline_mrsa_2014.pdf. Published 2014. Accessed May 31, 2019.Google Scholar
Japanese Society of Chemotherapy and Japan Society for Surgical Infection. Advisory Committee of Japanese Clinical Practice Guidelines for antimicrobial prophylaxis in surgery [in Japanese]. Tokyo: The Societies; 2016.Google Scholar
Evaniew, N, Khan, M, Drew, B, Peterson, D, Bhandari, M, Ghert, M. Intrawound vancomycin to prevent infections after spine surgery: a systematic review and meta-analysis. Eur Spine J 2015;24:533–542.CrossRefGoogle ScholarPubMed
Chiang, HY, Herwaldt, LA, Blevins, AE, Cho, E, Schweizer, ML. Effectiveness of local vancomycin powder to decrease surgical site infections: a meta-analysis. Spine J 2014;14:397–407.CrossRefGoogle ScholarPubMed
The Japanese Orthopaedic Association. Clinical practice guideline on the prevention of postoperative infection of osteosrthrotomy, 2015 [in Japanese]. Tokyo: Nankodo; 2015.Google Scholar
Torres, K, Sampathkumar, P. Predictors of methicillin-resistant Staphylococcus aureus colonization at hospital admission. Am J Infect Control 2013;41:1043–1047.CrossRefGoogle ScholarPubMed
Wakatake, H, Fujitani, S, Kodama, T, et al. Positive clinical risk factors predict a high rate of methicillin-resistant Staphylococcus aureus colonization in emergency department patients. Am J Infect Control 2012;40:988–991.CrossRefGoogle ScholarPubMed
Steyerberg, EW, Harrell, FE Jr, Borsboom, GJ, et al. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol 2001;54:774–781.CrossRefGoogle ScholarPubMed
Core Team, R. R: a language and environment for statistical computing. R Foundation for Statistical Computing website. https://www.R-project.org/. Published 2019. Accessed February 26, 2020.Google Scholar
Chen, SH, Lee, CH, Huang, KC, Hsieh, PH, Tsai, SY. Postoperative wound infection after posterior spinal instrumentation: analysis of long-term treatment outcomes. Eur Spine J 2015;24:561–570.CrossRefGoogle ScholarPubMed
Kuhns, BD, Lubelski, D, Alvin, MD, et al. Cost and quality of life outcome analysis of postoperative infections after subaxial dorsal cervical fusions. J Neurosurg Spine 2015;22:381–386.CrossRefGoogle ScholarPubMed
Calderone, RR, Garland, DE, Capen, DA, Oster, H. Cost of medical care for postoperative spinal infections. Orthop Clin North Am 1996;27:171–182.Google ScholarPubMed
Johnston, DH, Fairclough, JA, Brown, EM, Morris, R. Rate of bacterial recolonization of the skin after preparation: four methods compared. Br J Surg 1987;74:64.CrossRefGoogle ScholarPubMed
Ritter, MA, Campbell, ED. Retrospective evaluation of an iodophor-incorporated antimicrobial plastic adhesive wound drape. Clin Orthop Relat Res 1988;228:307–308.Google Scholar
Ueno, M, Saito, W, Yamagata, M, et al. Triclosan-coated sutures reduce wound infections after spinal surgery: a retrospective, nonrandomized, clinical study. Spine J 2015;15:933–938.CrossRefGoogle ScholarPubMed
Wang, ZX, Jiang, CP, Cao, Y, Ding, YT. Systematic review and meta-analysis of triclosan-coated sutures for the prevention of surgical-site infection. Br J Surg 2013;100:465–473.CrossRefGoogle ScholarPubMed
Global guidelines on the prevention of surgical site infection. World Health Organization. website. http://www.who.int/gpsc/ssi-guidelines/en/. Published 2016. Accessed May 30, 2019.Google Scholar
Berríos-Torres, SI, Umscheid, CA, Bratzler, DW, et al. Healthcare Infection Control Practices Advisory Committee. Centers for Disease Control and Prevention Guideline for the Prevention of Surgical Site Infection, 2017. JAMA Surg 2017;152:784–791.Google ScholarPubMed
Yamada, K, Abe, H, Higashikawa, A, et al. Evidence-based care bundles for preventing surgical site infections in spinal instrumentation surgery. Spine (Phila Pa 1976) 2018;43:1765–1773.CrossRefGoogle ScholarPubMed
Mangram, AJ, Horan, TC, Pearson, ML, Silver, LC, Jarvis, WR. Guideline for prevention of surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infect Control Hosp Epidemiol 1999;20:250–278.CrossRefGoogle ScholarPubMed
Bratzler, DW, Houck, PM; Surgical Infection Prevention Guideline Writers Workgroup. Antimicrobial prophylaxis for surgery: an advisory statement from the National Surgical Infection Prevention Project. Am J Surg 2005;189:395–404.CrossRefGoogle ScholarPubMed
Ban, KA, Minei, JP, Laronga, C, et al. American College of Surgeons and Surgical Infection Society: surgical site infection guidelines, 2016 update. J Am Coll Surg 2017;224:59–74.CrossRefGoogle Scholar
Berbari, EF, Osman, DR, Lahr, B, et al. The Mayo prosthetic joint infection risk score: implication for surgical site infection reporting and risk stratification. Infect Control Hosp Epidemiol 2012;33:774–781.CrossRefGoogle ScholarPubMed
Wasson, JH, Sox, HC, Neff, RK, Goldman, L. Clinical prediction rules. Applications and methodological standards. N Engl J Med 1985;313:793–799.CrossRefGoogle ScholarPubMed
McGinn, T, Jervis, R, Wisnivesky, J, Keitz, S, Wyer, PC; Evidence-Based Medicine Teaching Tips Working Group. Tips for teachers of evidence-based medicine: clinical prediction rules (CPRs) and estimating pretest probability. J Gen Intern Med 2008;23:1261–1268.CrossRefGoogle Scholar
Wells, PS, Hirsh, J, Anderson, DR, et al. Accuracy of clinical assessment of deep-vein thrombosis. Lancet 1995;345:1326–1330. Erratum in: Lancet 1995;346:516.CrossRefGoogle ScholarPubMed
Wells, PS, Ginsberg, JS, Anderson, DR, et al. Use of a clinical model for safe management of patients with suspected pulmonary embolism. Ann Intern Med 1998;129:997–1005.CrossRefGoogle ScholarPubMed
Wells, PS, Anderson, DR, Rodger, M, et al. Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer. Thromb Haemost 2000;83:416–420.Google ScholarPubMed