Incidence and Risk Factors for Clostridium Difficile-Associated Diarrhea Following Revision Total Hip Arthroplasty

Abstract

Clostridium difficile-associated diarrhea (CDAD) is a well-known cause of complications and increased hospital cost following surgery. As CDAD rates continue to be adopted as a quality metric by institutions, it is important to detect high-risk patients prior to surgery, including revision total hip arthroplasty (rTHA). This study was performed to identify the incidence and risk factors of CDAD within 30 days of rTHA. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) was accessed from 2015 to 2016 to identify rTHA procedures. Overall, 4,178 patients were included. Preoperative and perioperative variables were analyzed as potential risk factors for the development of CDAD. To compare categorical variables, Chi-square and Fisher's exact tests were used, while t-tests were used to detect differences in continuous variables. Independent risk factors for CDAD were identified using stepwise logistic regression. The rate of CDAD was found to be 0.5% (20/4,178) within 30 days of rTHA. Preoperative functional dependence (odds ratio [OR] = 3.34; p = 0.035) and dyspnea (OR = 3.80; p = 0.019), were statistically significant risk factors for the development of CDAD after rTHA. Septic revision was not a significant risk factor for CDAD (OR = 2.50; p = 0.082). The incidence of CDAD after rTHA in the United States is approximately 0.5%. Independent risk factors for CDAD include preoperative functional dependence and dyspnea. High-risk patients must be identified prior to surgery and antibiotic selection for other infections should be managed judiciously.

Keywords

Clostridium difficile - incidence - risk factors - revision - total hip arthroplasty

• References

• 1 CDC Frequently asked questions about Clostridium difficile for healthcare providers. Available at: http://processcleaningsolutions.com/pdf/Preview_of_cdc.pdf . Accessed March 29, 2019
• 2 Bouza E. Consequences of Clostridium difficile infection: understanding the healthcare burden. Clin Microbiol Infect 2012; 18 (Suppl. 06) 5-12
• 3 Lessa FC, Mu Y, Bamberg WM. , et al. Burden of Clostridium difficile infection in the United States. N Engl J Med 2015; 372 (09) 825-834
• 4 Bouza E, Muñoz P, Alonso R. Clinical manifestations, treatment and control of infections caused by Clostridium difficile. Clin Microbiol Infect 2005; 11 (Suppl. 04) 57-64
• 5 Jenkins PJ, Teoh K, Simpson PM, Dave J, Simpson AHWR, Breusch S. Clostridium difficile in patients undergoing primary hip and knee replacement. J Bone Joint Surg Br 2010; 92 (07) 994-998
• 6 Bovonratwet P, Bohl DD, Malpani R, Nam D, Della Valle CJ, Grauer JN. Incidence, risk factors, and impact of Clostridium difficile colitis following primary total hip and knee arthroplasty. J Arthroplasty 2018; 33 (01) 205-210.e1
• 7 Kurd MF, Pulido L, Joshi A, Purtill JJ, Parvizi J. Clostridium difficile infection after total joint arthroplasty: who is at risk?. J Arthroplasty 2008; 23 (06) 839-842
• 8 Tokarski AT, Karam JA, Zmistowski B, Deirmengian CA, Deirmengian GK. Clostridium difficile is common in patients with postoperative diarrhea after hip and knee arthroplasty. J Arthroplasty 2014; 29 (06) 1110-1113
• 9 Maltenfort MG, Rasouli MR, Morrison TA, Parvizi J. Clostridium difficile colitis in patients undergoing lower-extremity arthroplasty: rare infection with major impact. Clin Orthop Relat Res 2013; 471 (10) 3178-3185
• 10 Delanois RE, George NE, Etcheson JI, Gwam CU, Mistry JB, Mont MA. Risk factors and costs associated with clostridium difficile colitis in patients with prosthetic joint infection undergoing revision total hip arthroplasty. J Arthroplasty 2018; 33 (05) 1534-1538
• 11 NSQIP. American College of Surgeons National Surgical Quality Improvement Program. Available at: https://www.facs.org/quality-programs/acs-nsqip . Accessed August 11, 2016
• 12 ACS-NSQIP User guide for the 2016 ACS NSQIP participant use data file (PUF) 2017 . Available at: https://www.facs.org/~/media/files/quality%20programs/nsqip%20peds/peds_nsqip_puf_userguide_2016.ashx . Accessed March 29, 2019
• 13 Osman F, Saleh F, Jackson TD, Corrigan MA, Cil T. Increased postoperative complications in bilateral mastectomy patients compared to unilateral mastectomy: an analysis of the NSQIP database. Ann Surg Oncol 2013; 20 (10) 3212-3217
• 14 Khuri SF. The NSQIP: a new frontier in surgery. Surgery 2005; 138 (05) 837-843
• 15 Hamilton BH, Ko CY, Richards K, Hall BL. 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. J Am Coll Surg 2010; 210 (02) 125-139.e2
• 16 R Core Team. R: a language and environment for statistical computing 2015 . Available from: https://cran.r-project.org/doc/manuals/fullrefman.pdf . Accessed March 29, 2019
• 17 Piccinin MA, Sayeed Z, Kozlowski R, Bobba V, Knesek D, Frush T. Bundle Payment for Musculoskeletal Care: Current Evidence (Part 1). Orthop Clin North Am 2018; 49 (02) 135-146
• 18 Cohen ME, Dimick JB, Bilimoria KY, Ko CY, Richards K, Hall BL. Risk adjustment in the American College of Surgeons National Surgical Quality Improvement Program: a comparison of logistic versus hierarchical modeling. J Am Coll Surg 2009; 209 (06) 687-693
• 19 Cohen ME, Ko CY, Bilimoria KY. , et al. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg 2013; 217 (02) 336-46.e1
• 20 Lawson EH, Louie R, Zingmond DS. , et al. A comparison of clinical registry versus administrative claims data for reporting of 30-day surgical complications. Ann Surg 2012; 256 (06) 973-981
• 21 Scott WK, Macera CA, Cornman CB, Sharpe PA. Functional health status as a predictor of mortality in men and women over 65. J Clin Epidemiol 1997; 50 (03) 291-296