External validation of clinical prediction rules for complications and mortality following Clostridioides difficile infection
Autoři:
Catherine Beauregard-Paultre aff001; Claire Nour Abou Chakra aff001; Allison McGeer aff002; Annie-Claude Labbé aff003; Andrew E. Simor aff004; Wayne Gold aff005; Matthew P. Muller aff006; Jeff Powis aff007; Kevin Katz aff008; Suzanne M. Cadarette aff009; Jacques Pépin aff001; Louis Valiquette aff001
Působiště autorů:
Department of Microbiology and Infectious Disease, Université de Sherbrooke, Sherbrooke, Québec, Canada
aff001; Mount Sinai Hospital, Toronto, Ontario, Canada
aff002; Division of Infectious Disease and Microbiology, CIUSSS de l’Est-de-l’Ile-de-Montréal, Montréal, Québec, Canada
aff003; Microbiology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
aff004; Toronto General Hospital, Toronto, Ontario, Canada
aff005; St.Michael’s Hospital, Toronto, Ontario, Canada
aff006; Michael Garron Hospital, Toronto, Ontario, Canada
aff007; Department of Infection Control, North York General Hospital, Toronto, Ontario, Canada
aff008; Leslie Dan Faculty of Pharmacy and Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
aff009; Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
aff010
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0226672
Souhrn
Background
Several clinical prediction rules (CPRs) for complications and mortality of Clostridioides difficile infection (CDI) have been developed but only a few have gone through external validation, and none is widely recommended in clinical practice.
Methods
CPRs were identified through a systematic review. We included studies that predicted severe or complicated CDI (cCDI) and mortality, reported at least an internal validation step, and for which data were available with minimal modifications. Data from a multicenter prospective cohort of 1380 adults with confirmed CDI were used for external validation. In this cohort, cCDI occurred in 8% of the patients and 30-day all-cause mortality occurred in 12%. The performance of each tool was assessed using individual outcomes, with the same cut-offs and standard parameters.
Results
Seven CPRs were assessed. Three predictive scores for cCDI showed low sensitivity (25–61%) and positive predictive value (PPV; 9–31%), but moderate specificity (54–90%) and negative predictive value (NPV; 82–95%). One model [using age, white blood cell count (WBC), narcotic use, antacids use, and creatinine ratio > 1.5× the normal level as covariates] showed a probability of 25% of cCDI at the optimal cut-off point with 36% sensitivity and 84% specificity. Two scores for mortality had low sensitivity (4–55%) and PPV (25–31%), and moderate specificity (71–78%) and NPV (87–92%). One predictive model for 30-day all-cause mortality [Charlson comorbidity index, WBC, blood urea nitrogen (BUN), diagnosis in ICU, and delirium] showed an AUC-ROC of 0.74. All other CPRs showed lower AUC values (0.63–0.69). Errors in calibration ranged from 12%- 27%.
Conclusions
Included CPRs showed moderate performance for clinical use in a large validation cohort with a majority of patients infected with ribotype 027 strains and a low rate of cCDI and mortality. These data show that better CPRs need to be developed and validated.
Klíčová slova:
Clostridium difficile – Death rates – Systematic reviews – Inpatients – Creatinine – Intensive care units – Colectomy
Zdroje
1. McFarland LV, Ozen M, Dinleyici EC, Goh S. Comparison of pediatric and adult antibiotic-associated diarrhea and Clostridium difficile infections. World J Gastroenterol. 2016;22(11):3078–104. doi: 10.3748/wjg.v22.i11.3078 27003987
2. Abou Chakra CN, Pepin J, Sirard S, Valiquette L. Risk factors for recurrence, complications and mortality in Clostridium difficile infection: a systematic review. PLoS One. 2014;9(6):e98400. doi: 10.1371/journal.pone.0098400 24897375
3. Gao T, He B, Pan Y, Deng Q, Sun H, Liu X, et al. Association of Clostridium difficile infection in hospital mortality: A systematic review and meta-analysis. Am J Infect Control. 2015;43(12):1316–20. doi: 10.1016/j.ajic.2015.04.209 26654234
4. Pepin J, Valiquette L, Alary ME, Villemure P, Pelletier A, Forget K, et al. Clostridium difficile-associated diarrhea in a region of Quebec from 1991 to 2003: a changing pattern of disease severity. CMAJ. 2004;171(5):466–72. doi: 10.1503/cmaj.1041104 15337727
5. Loo VG, Poirier L, Miller MA, Oughton M, Libman MD, Michaud S, et al. A predominantly clonal multi-institutional outbreak of Clostridium difficile-associated diarrhea with high morbidity and mortality. N Engl J Med. 2005;353(23):2442–9. doi: 10.1056/NEJMoa051639 16322602
6. Redelings MD, Sorvillo F, Mascola L. Increase in Clostridium difficile-related mortality rates, United States, 1999–2004. Emerg Infect Dis. 2007;13(9):1417–9. doi: 10.3201/eid1309.061116 18252127
7. Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating: Springer; 2009.
8. McGinn T. Putting Meaning into Meaningful Use: A Roadmap to Successful Integration of Evidence at the Point of Care. JMIR. 2016;4(2):e16.
9. Abou Chakra CN, Pepin J, Valiquette L. Prediction tools for unfavourable outcomes in Clostridium difficile infection: a systematic review. PLoS One. 2012;7(1):e30258. doi: 10.1371/journal.pone.0030258 22291926
10. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535. doi: 10.1136/bmj.b2535 19622551
11. Abou Chakra CN, McGeer A, Labbe AC, Simor AE, Gold WL, Muller M, et al. Factors associated with Complications of Clostridium difficile Infection in a Multicenter Prospective Cohort. Clin Infect Dis. 2015;61(12):1781–8. doi: 10.1093/cid/civ749 26338788
12. Crowson CS, Atkinson EJ, Therneau TM. Assessing calibration of prognostic risk scores. Stat Methods Med Res. 2016;25(4):1692–706. doi: 10.1177/0962280213497434 23907781
13. Rubin MS, Bodenstein LE, Kent KC. Severe Clostridium difficile colitis. Dis Colon Rectum. 1995;38(4):350–4. doi: 10.1007/bf02054220 7720439
14. Velazquez-Gomez I, Rocha-Rodriguez R, Toro DH, Gutierrez-Nuñez JJ, Gonzalez G, Saavedra S. A Severity Score Index for Clostridium difficile Infection. Infect Dis Clin Pract. 2008;16(6):376–8.
15. Welfare MR, Lalayiannis LC, Martin KE, Corbett S, Marshall B, Sarma JB. Co-morbidities as predictors of mortality in Clostridium difficile infection and derivation of the ARC predictive score. J Hosp Infect. 2011;79(4):359–63. doi: 10.1016/j.jhin.2011.08.015 22047977
16. Bhangu S, Bhangu A, Nightingale P, Michael A. Mortality and risk stratification in patients with Clostridium difficile-associated diarrhoea. Colorectal Dis. 2010;12(3):241–6. doi: 10.1111/j.1463-1318.2009.01832.x 19508548
17. Li BY, Oh J, Young VB, Rao K, Wiens J. Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection. Open Forum Infect Dis. 2019.
18. Reigadas E, Alcala L, Valerio M, Marin M, Martin A, Bouza E. Toxin B PCR cycle threshold as a predictor of poor outcome of Clostridium difficile infection: a derivation and validation cohort study. J Antimicrob Chemoth 2016;71(5):1380–5.
19. Lungulescu OA, Cao W, Gatskevich E, Tlhabano L, Stratidis JG. CSI: a severity index for Clostridium difficile infection at the time of admission. J Hosp Infect. 2011;79(2):151–4. doi: 10.1016/j.jhin.2011.04.017 21849220
20. Cozar A, Ramos-Martinez A, Merino E, Martinez-Garcia C, Shaw E, Marrodan T, et al. High delayed mortality after the first episode of Clostridium difficile infection. Anaerobe. 2019;57:93–8. doi: 10.1016/j.anaerobe.2019.04.004 30959165
21. Bloomfield MG, Carmichael AJ, Gkrania-Klotsas E. Mortality in Clostridium difficile infection: a prospective analysis of risk predictors. Eur J Gastroenterol Hepatol 2013;25(6):700–5. doi: 10.1097/MEG.0b013e32835ed64d 23442414
22. Zilberberg MD, Shorr AF, Micek ST, Doherty JA, Kollef MH. Clostridium difficile-associated disease and mortality among the elderly critically ill. Critical care medicine. 2009;37(9):2583–9. doi: 10.1097/CCM.0b013e3181ab8388 19623053
23. Kulaylat AS, Kassam Z, Hollenbeak CS, Stewart DB, Sr. A Surgical Clostridium-Associated Risk of Death Score Predicts Mortality After Colectomy for Clostridium difficile. Dis Colon Rectum. 2017;60(12):1285–90. doi: 10.1097/DCR.0000000000000920 29112564
24. Drew RJ, Boyle B. RUWA scoring system: a novel predictive tool for the identification of patients at high risk for complications from Clostridium difficile infection. J HospInfect. 2009;71(1):93–4.
25. Na X, Martin AJ, Sethi S, Kyne L, Garey KW, Flores SW, et al. A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection. PLoS One. 2015;10(4):e0123405. doi: 10.1371/journal.pone.0123405 25906284
26. Hensgens MP, Dekkers OM, Goorhuis A, LeCessie S, Kuijper EJ. Predicting a complicated course of Clostridium difficile infection at the bedside. Clin Microbiol Infect 2014;20(5):O301–8. doi: 10.1111/1469-0691.12391 24188103
27. Van der Wilden GM, Chang Y, Cropano C, Subramanian M, Schipper IB, Yeh DD, et al. Fulminant Clostridium difficile colitis: prospective development of a risk scoring system. J Trauma Acute Care Surg. 2014;76(2):424–30. doi: 10.1097/TA.0000000000000105 24458048
28. Butt E, Foster JA, Keedwell E, Bell JE, Titball RW, Bhangu A, et al. Derivation and validation of a simple, accurate and robust prediction rule for risk of mortality in patients with Clostridium difficile infection. BMC Infect Dis. 2013;13(1):316.
29. Kassam Z, Cribb Fabersunne C, Smith MB, Alm EJ, Kaplan GG, Nguyen GC, et al. Clostridium difficile associated risk of death score (CARDS): a novel severity score to predict mortality among hospitalised patients with C. difficile infection. Aliment Pharmacol Ther. 2016;5(10):13546.
30. Shivashankar R, Khanna S, Kammer PP, Harmsen WS, Zinsmeister AR, Baddour LM, et al. Clinical factors associated with development of severe-complicated Clostridium difficile infection. Clin Gastroenterol Hepatol. 2013;11(11):1466–71. doi: 10.1016/j.cgh.2013.04.050 23702192
31. Archbald-Pannone LR, McMurry TL, Guerrant RL, Warren CA. Delirium and other clinical factors with Clostridium difficile infection that predict mortality in hospitalized patients. Am J Infect Control. 2015;43(7):690–3. doi: 10.1016/j.ajic.2015.03.017 25920706
32. Neelon VJ, Champagne MT, Carlson JR, Funk SG. The NEECHAM Confusion Scale: construction, validation, and clinical testing. Nurs Res. 1996;45(6):324–30. doi: 10.1097/00006199-199611000-00002 8941300
33. van Beurden YH, Hensgens MPM, Dekkers OM, Le Cessie S, Mulder CJJ, Vandenbroucke-Grauls C. External Validation of Three Prediction Tools for Patients at Risk of a Complicated Course of Clostridium difficile Infection: Disappointing in an Outbreak Setting. Infect Control Hosp Epidemiol. 2017;38(8):897–905. doi: 10.1017/ice.2017.89 28592343
34. Garneau JR, Abou Chakra CN, Fortier LC, Labbe AC, Simor AE, Gold W, et al. Multilocus Variable-Number Tandem-Repeat Analysis of Clostridioides difficile Clusters in Ribotype 027 Isolates and Lack of Association with Clinical Outcomes. JCM 2019;57(5):pii: e01724–18.
35. Steyerberg EW, Moons KG, van der Windt DA, Hayden JA, Perel P, Schroter S, et al. Prognosis Research Strategy (PROGRESS) 3: prognostic model research. PLoS Med. 2013;10(2):e1001381. doi: 10.1371/journal.pmed.1001381 23393430
36. Hayden JA, van der Windt DA, Cartwright JL, Cote P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med. 2013;158(4):280–6. doi: 10.7326/0003-4819-158-4-201302190-00009 23420236
37. Fujitani S, George WL, Murthy AR. Comparison of clinical severity score indices for Clostridium difficile infection. Infect Control Hosp Epidemiol. 2011;32(3):220–8. doi: 10.1086/658336 21460506
38. Gomez-Simmonds A, Kubin CJ, Furuya EY. Comparison of 3 severity criteria for Clostridium difficile infection. Infect Control Hosp Epidemiol. 2014;35(2):196–9. doi: 10.1086/674851 24442086
39. Hernandez-Rocha C, Tejos Sufan R, Plaza-Garrido A, Barra-Carrasco J, Aguero Luengo C, Inostroza Levy G, et al. Performance of prognostic index in severe Clostridium difficile-associated infection: retrospective analysis in a university hospital. Rev Chilena Infectol. 2014;31(6):659–65. doi: 10.4067/S0716-10182014000600003 25679920
40. McDonald LC, Gerding DN, Johnson S, Bakken JS, Carroll KC, Coffin SE, et al. Clinical Practice Guidelines for Clostridium difficile Infection in Adults and Children: 2017 Update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA). Clin Infect Dis. 2018;66(7):987–94. 29562266
41. Bauer MP, Hensgens MP, Miller MA, Gerding DN, Wilcox MH, Dale AP, et al. Renal failure and leukocytosis are predictors of a complicated course of Clostridium difficile infection if measured on day of diagnosis. Clin Infect Dis. 2012;55 Suppl 2:S149–53.
42. Miller MA, Louie T, Mullane K, Weiss K, Lentnek A, Golan Y, et al. Derivation and validation of a simple clinical bedside score (ATLAS) for Clostridium difficile infection which predicts response to therapy. BMC Infect Dis. 2013;13:148. doi: 10.1186/1471-2334-13-148 23530807
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts