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The Seasonal Variability in Surgical Site Infections and the Association With Warmer Weather: A Population-Based Investigation

Published online by Cambridge University Press:  16 May 2017

Chris A. Anthony
Affiliation:
Department of Orthopaedic Surgery and Rehabilitation, University of Iowa Hospitals and Clinics, Iowa City, Iowa
Ryan A. Peterson
Affiliation:
Department of Biostatistics, University of Iowa, Iowa City, Iowa
Linnea A. Polgreen
Affiliation:
Department of Pharmacy Practice and Science, University of Iowa, Iowa City, Iowa
Daniel K. Sewell
Affiliation:
Department of Biostatistics, University of Iowa, Iowa City, Iowa
Philip M. Polgreen*
Affiliation:
Departments of Internal Medicine and Epidemiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa University of Iowa Health Ventures’ Signal Center for Health Innovation, Iowa City, Iowa
*
Address correspondence to Philip M. Polgreen, MD, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, IA 52242 ([email protected]).

Abstract

OBJECTIVE

To determine whether the seasonality of surgical site infections (SSIs) can be explained by changes in temperature.

DESIGN

Retrospective cohort analysis.

SETTING

The National Inpatient Sample database.

PATIENTS

All hospital discharges with a primary diagnosis of SSI from 1998 to 2011 were considered cases. Discharges with a primary or secondary diagnoses of specific surgeries commonly associated with SSIs from the previous and current month served as our “at risk” cohort.

METHODS

We modeled the national monthly count of SSI cases both nationally and stratified by region, sex, age, and type of institution. We used data from the National Climatic Data Center to estimate the monthly average temperatures for all hospital locations. We modeled the odds of having a primary diagnosis of SSI as a function of demographics, payer, location, patient severity, admission month, year, and the average temperature in the month of admission.

RESULTS

SSI incidence is highly seasonal, with the highest SSI incidence in August and the lowest in January. During the study period, there were 26.5% more cases in August than in January (95% CI, 23.3–29.7). Controlling for demographic and hospital-level characteristics, the odds of a primary SSI admission increased by roughly 2.1% per 2.8°C (5°F) increase in the average monthly temperature. Specifically, the highest temperature group, >32.2°C (>90°F), was associated with an increase in the odds of an SSI admission of 28.9% (95% CI, 20.2–38.3) compared to temperatures <4.4°C (<40°F).

CONCLUSIONS

At population level, SSI risk is highly seasonal and is associated with warmer weather.

Infect Control Hosp Epidemiol 2017;38:809–816

Type
Original Articles
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

REFERENCES

1. Procedure-associated module: surgical site infection (SSI) event. Centers for Disease Control and Prevention website. http://www.cdc.gov/nhsn/pdfs/pscmanual/9pscssicurrent.pdf. Published 2016. Accessed October 15, 2016.Google Scholar
2. Anderson, DJ, Podgorny, K, Berrios-Torres, SI, et al. Strategies to prevent surgical site infections in acute care hospitals: 2014 update. Infect Control Hosp Epidemiol 2014;35(Suppl 2):S66S88.Google Scholar
3. Magill, SS, Hellinger, W, Cohen, J, et al. Prevalence of healthcare-associated infections in acute care hospitals in Jacksonville, Florida. Infect Control Hosp Epidemiol 2012;33:283291.CrossRefGoogle ScholarPubMed
4. Sandy-Hodgetts, K, Leslie, GD, Lewin, G, Hendrie, D, Carville, K. Surgical wound dehiscence in an Australian community nursing service: time and cost to healing. J Wound Care 2016;25:377383.CrossRefGoogle Scholar
5. 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;37:387397.CrossRefGoogle ScholarPubMed
6. Dohmen, PM. Antibiotic resistance in common pathogens reinforces the need to minimise surgical site infections. J Hosp Infect 2008;70(Suppl 2):1520.Google Scholar
7. Leaper, DJ, van Goor, H, Reilly, J, et al. Surgical site infection—a European perspective of incidence and economic burden. Int Wound J 2004;1:247273.Google Scholar
8. Kirkland, KB, Briggs, JP, Trivette, SL, Wilkinson, WE, Sexton, DJ. The impact of surgical-site infections in the 1990s: attributable mortality, excess length of hospitalization, and extra costs. Infect Control Hosp Epidemiol 1999;20:725730.Google Scholar
9. Astagneau, P, Rioux, C, Golliot, F, Brucker, G. Morbidity and mortality associated with surgical site infections: results from the 1997–1999 INCISO surveillance. J Hosp Infect 2001;48:267274.CrossRefGoogle ScholarPubMed
10. Ramkumar, PN, Chu, CT, Harris, JD, et al. Causes and rates of unplanned readmissions after elective primary total joint arthroplasty: a systematic review and meta-analysis. Am J Orthoped (Belle Mead, NJ) 2015;44:397405.Google Scholar
11. Whitehouse, JD, Friedman, ND, Kirkland, KB, Richardson, WJ, Sexton, DJ. The impact of surgical-site infections following orthopedic surgery at a community hospital and a university hospital: adverse quality of life, excess length of stay, and extra cost. Infect Control Hosp Epidemiol 2002;23:183189.CrossRefGoogle Scholar
12. Durkin, MJ, Dicks, KV, Baker, AW, et al. Seasonal variation of common surgical site infections: does season matter? Infect Control Hosp Epidemiol 2015;36:10111016.Google Scholar
13. Beitsch, P, Balch, C. Operative morbidity and risk factor assessment in melanoma patients undergoing inguinal lymph node dissection. Am J Surg 1992;164:462466.Google Scholar
14. Harrop, JS, Styliaras, JC, Ooi, YC, Radcliff, KE, Vaccaro, AR, Wu, C. Contributing factors to surgical site infections. J Am Acad Orthopaed Surg 2012;20:94101.Google Scholar
15. Lilienfeld, DE, Vlahov, D, Tenney, JH, McLaughlin, JS. Obesity anddiabetes as risk factors for postoperative wound infections after cardiac surgery. Am J Infect Control 1988;16:36.Google Scholar
16. Nystrom, PO, Jonstam, A, Hojer, H, Ling, L. Incisional infection after colorectal surgery in obese patients. Acta chirurgica Scand 1987;153:225227.Google Scholar
17. Mishriki, SF, Law, DJ, Jeffery, PJ. Factors affecting the incidence of postoperative wound infection. J Hosp Infect 1990;16:223230.Google Scholar
18. Casey, J, Flinn, WR, Yao, JS, Fahey, V, Pawlowski, J, Bergan, JJ. Correlation of immune and nutritional status with wound complications in patients undergoing vascular operations. Surgery 1983;93:822827.Google Scholar
19. Meyer, E, Weitzel-Kage, D, Sohr, D, Gastmeier, P. Impact of department volume on surgical site infections following arthroscopy, knee replacement or hip replacement. BMJ Qual Safety 2011;20:10691074.CrossRefGoogle ScholarPubMed
20. Muilwijk, J, van den Hof, S, Wille, JC. Associations between surgical site infection risk and hospital operation volume and surgeon operation volume among hospitals in the Dutch nosocomial infection surveillance network. Infect Control Hosp Epidemiol 2007;28:557563.CrossRefGoogle ScholarPubMed
21. Hughes, JM, Culver, DH, White, JW, et al. Nosocomial infection surveillance, 1980–1982. MMWR CDC Surveil Sum 1983;32:1ss16ss.Google Scholar
22. Durkin, MJ, Dicks, KV, Baker, AW, et al. Postoperative infection in spine surgery: does the month matter? J Neurosurg Spine 2015;23:128134.CrossRefGoogle ScholarPubMed
23. Kane, P, Chen, C, Post, Z, Radcliff, K, Orozco, F, Ong, A. Seasonality of infection rates after total joint arthroplasty. Orthopedics 2014;37:e182e186.Google Scholar
24. Sagi, HC, Cooper, S, Donahue, D, Marberry, S, Steverson, B. Seasonal variations in posttraumatic wound infections after open extremity fractures. J Trauma Acute Care Surg 2015;79:10731078.Google Scholar
25. Kahle, D, Wickham, H. ggmap: Spatial Visualization with ggplot2 [computer program]. R Journal 2013;5:144161.Google Scholar
26. Kuhn, M. caret: Classification and Regression Training [computer program]. R package, version 6.0-76. https://CRAN.R-project.org/package=caret. Published 2016. Accessed September 1, 2016.Google Scholar
27. A. Elixhauser, CS, Harris, DR, et al. Comorbidity measures for use with administrative data. Med Care 1998;366:827.Google Scholar
28. Fisman, DN. Seasonality of infectious diseases. Ann Rev Public Health 2007;28:127143.Google Scholar
29. Polgreen, PM, Yang, M, Bohnett, LC, Cavanaugh, JE. A time-series analysis of Clostridium difficile and its seasonal association with influenza. Infect Control Hosp Epidemiol 2010;31:382387.Google Scholar
30. Reil, M, Hensgens, MP, Kuijper, EJ, et al. Seasonality of Clostridium difficile infections in southern Germany. Epidemiol Infect 2012;140:17871793.CrossRefGoogle ScholarPubMed
31. Brown, KA, Daneman, N, Arora, P, Moineddin, R, Fisman, DN. The co-seasonality of pneumonia and influenza with Clostridium difficile infection in the United States, 1993–2008. Am J Epidemiol 2013;178:118125.Google Scholar
32. Schwab, F, Gastmeier, P, Meyer, E. The warmer the weather, the more gram-negative bacteria-impact of temperature on clinical isolates in intensive care units. PloS One 2014;9:e91105.Google Scholar
33. Al-Hasan, MN, Lahr, BD, Eckel-Passow, JE, Baddour, LM. Seasonal variation in Escherichia coli bloodstream infection: a population-based study. Clin Microbiol Infect 2009;15:947950.CrossRefGoogle ScholarPubMed
34. Anderson, JE. Seasonality of symptomatic bacterial urinary infections in women. J Epidemiol Commun Health 1983;37:286290.CrossRefGoogle ScholarPubMed
35. Simmering, JE, Tang, F, Cavanaugh, JE, Polgreen, LA, Polgreen, PM. The increase in hospitalizations for urinary tract infections and the associated costs in the United States, 1998–2011. Open Forum Infect Dis 2017;4:ofw281.CrossRefGoogle ScholarPubMed
36. Peterson, RA, Polgreen, LA, Cavanaugh, JE, Polgreen, PM. Increasing incidence, cost, and seasonality in patients hospitalized for cellulitis. Open Forum Infectious Diseases 2017;4:ofx008.Google Scholar
37. Gruskay, J, Smith, J, Kepler, CK, et al. The seasonality of postoperative infection in spine surgery. J Neurosurg Spine 2013;18:5762.CrossRefGoogle ScholarPubMed
38. Mermel, LA, Machan, JT, Parenteau, S. Seasonality of MRSA infections. PLoS One 2011;6:e17925.Google Scholar
39. Wang, X, Towers, S, Panchanathan, S, Chowell, G. A population based study of seasonality of skin and soft tissue infections: implications for the spread of CA-MRSA. PloS One 2013;8:e60872.Google Scholar
40. Leekha, S, Diekema, DJ, Perencevich, EN. Seasonality of staphylococcal infections. Clin Microbiol Infect 2012;18:927933.Google Scholar
41. McBride, ME, Duncan, WC, Knox, JM. The environment and the microbial ecology of human skin. Appl Environ Microbiol 1977;33:603608.Google Scholar
42. Young, JQ, Ranji, SR, Wachter, RM, Lee, CM, Niehaus, B, Auerbach, AD. “July effect”: impact of the academic year-end changeover on patient outcomes: a systematic review. Ann Intern Med 2011;155:309315.Google Scholar
43. Stevenson, KB, Khan, Y, Dickman, J, et al. Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care-associated infections. Am J Infect Control 2008;36:155164.CrossRefGoogle ScholarPubMed
44. Goto, M, Ohl, ME, Schweizer, ML, Perencevich, EN. Accuracy of administrative code data for the surveillance of healthcare-associated infections: a systematic review and meta-analysis. Clin Infect Dis 2014;58:688696.Google Scholar
45. Baker, AW, Dicks, KV, Durkin, MJ, et al. Epidemiology of surgical site infection in a community hospital network. Infect Control Hosp Epidemiol 2016;37:519526.Google Scholar
46. Healthcare-associated Infections (HAI) Progress Report. Centers for Disease Control and Prevention website. https://www.cdc.gov/hai/surveillance/progress-report/. Published 2016. Accessed February 27, 2017.Google Scholar