A new score to predict Clostridioides difficile infection in medical patients: a sub-analysis of the FADOI-PRACTICE study
Tóm tắt
Medical divisions are at high risk of Clostridioides difficile infection (CDI) due to patients’ frailty and complexity. This sub-analysis of the FADOI-PRACTICE study included patients presenting with diarrhea either at admission or during hospitalization. CDI diagnosis was confirmed when both enzyme immunoassay and A and B toxin detection were found positive. The aim of this sub-analysis was the identification of a new score to predict CDI in hospitalized, medical patients. Five hundred and seventy-two patients with diarrhea were considered. More than half of patients was female, 40% on antibiotics in the previous 4 weeks and 60% on proton pump inhibitors (PPIs). CDI diagnosis occurred in 103 patients (18%). Patients diagnosed with CDI were older, more frequently of female sex, recently hospitalized and bed-ridden, and treated with antibiotics and PPIs. Through a backward stepwise logistic regression model, age > 65 years, female sex, recent hospitalization, recent antibiotic therapy, active cancer, prolonged hospital stay (> 12 days), hypoalbuminemia (albumin < 3 g/dL), and leukocytosis (white blood cells > 9 × 10^9/L) were found to independently predict CDI occurrence. These variables contributed to building a clinical prognostic score with a good sensitivity and a modest specificity for a value > 3 (79% and 58%, respectively; AUC 0.75, 95% CI 0.71–0.79, p < 0.001), that identified low-risk (score ≤ 3; 42.5%) and high-risk (score > 3; 57.5%) patients. Although some classical risk factors were confirmed to increase CDI occurrence, the changing landscape of CDI epidemiology suggests a reappraisal of common risk factors and the development of novel risk scores based on local epidemiology.
Tài liệu tham khảo
Surawicz CM (2013) Infection: treating recurrent C. difficile infection-the challenge continues. Nat Rev Gastroenterol Hepatol 10:10–11
Bauer MP, Notermans DW, van Benthem BH, Brazier JS, Wilcox MH, Rupnik M et al (2011) Clostridium difficile infection in Europe: a hospital-based survey. Lancet 377:63–73
Smits WK, Lyras D, Lacy DB, Wilcox MH, Kuijper EJ (2016) Clostridium difficile infection. Nat Rev Dis Primers 2:16020
Henrich TJ, Krakower D, Bitton A, Yokoe DS (2009) Clinical risk factors for severe Clostridium difficile-associated disease. Emerg Infect Dis 15:415–422
Kee VR (2012) Clostridium difficile infection in older adults: a review and update on its management. Am J Geriatr Pharmacother 10:14–24
Potter VA, Aravinthan A (2012) Identifying patients at risk of severe Clostridium difficile-associated disease. Br J Hosp Med (Lond) 73:265–270
Cioni G, Viale P, Frasson S, Cipollini F, Menichetti F, Petrosillo N et al (2016) Epidemiology and outcome of Clostridium difficile infections in patients hospitalized in internal medicine: findings from the nationwide FADOI-PRACTICE study. BMC Infect Dis 16:656
Abou Chakra CN, McGeer A, Labbe AC, Simor AE, Gold WL, Muller MP et al (2015) Factors associated with complications of clostridium difficile infection in a multicenter prospective cohort. Clin Infect Dis 61:1781–1788
Davies K, Lawrence J, Berry C, Davis G, Yu H, Cai B et al (2020) Risk factors for primary clostridium difficile infection; results from the observational study of risk factors for Clostridium difficile infection in hospitalized patients with infective diarrhea (ORCHID). Front Public Health 8:293
Mellace L, Consonni D, Jacchetti G, Del Medico M, Colombo R, Velati M et al (2013) Epidemiology of Clostridium difficile-associated disease in internal medicine wards in northern Italy. Intern Emerg Med 8:717–723
Carrabba M, Zarantonello M, Formica S, Mellace L, Castaldi S, Cappellini MD et al (2012) Pneumonia and Clostridium difficile infection: hospital acquired infection in a non-ICU department. Eur Respir J 40:P2469
Bagdasarian N, Rao K, Malani PN (2015) Diagnosis and treatment of Clostridium difficile in adults: a systematic review. JAMA 313:398–408
Polage CR, Solnick JV, Cohen SH (2012) Nosocomial diarrhea: evaluation and treatment of causes other than Clostridium difficile. Clin Infect Dis 55:982–989
Sansone S, Aschbacher R, Staffler M, Bombonato M, Girardi F, Larcher C et al (2009) Nosocomial diarrhoea in adult medical patients: the role of Clostridium difficile in a North Italian acute care teaching hospital. J Prev Med Hyg 50:117–120
Aukes L, Fireman B, Lewis E, Timbol J, Hansen J, Yu H et al (2021) A risk score to predict Clostridioides difficile Infection. Open Forum Infect Dis 8:ofa052
Baggs J, Yousey-Hindes K, Ashley ED, Meek J, Dumyati G, Cohen J et al (2015) Identification of population at risk for future Clostridium difficile infection following hospital discharge to be targeted for vaccine trials. Vaccine 33:6241–6249
Bozarth S, Broome S, Hester W, Pirkle S, Williams C, Mannepalli S (2017) Clostridium difficile: can an admission assessment predict high risk patients? Am J Infect Control 45:S96
Kuntz JL, Johnson ES, Raebel MA, Platt RW, Petrik AF, Yang X et al (2015) Predicting the risk of Clostridium difficile infection following an outpatient visit: development and external validation of a pragmatic, prognostic risk score. Clin Microbiol Infect 21:256–262
Kuntz JL, Smith DH, Petrik AF, Yang X, Thorp ML, Barton T et al (2016) Predicting the risk of Clostridium difficile infection upon admission: a score to identify patients for antimicrobial stewardship efforts. Perm J 20:20–25
Marley C, El Hahi Y, Ferreira G, Woods L, Ramirez VA (2019) Evaluation of a risk score to predict future Clostridium difficile disease using UK primary care and hospital data in clinical practice research Datalink. Hum Vaccin Immunother 15:2475–2481
Miller MA, Louie T, Mullane K, Weiss K, Lentnek A, Golan Y et al (2013) Derivation and validation of a simple clinical bedside score (ATLAS) for Clostridium difficile infection which predicts response to therapy. BMC Infect Dis 13:148
Tabak YP, Johannes RS, Sun X, Nunez CM, McDonald LC (2015) Predicting the risk for hospital-onset Clostridium difficile infection (HO-CDI) at the time of inpatient admission: HO-CDI risk score. Infect Control Hosp Epidemiol 36:695–701
van Werkhoven CH, van der Tempel J, Jajou R, Thijsen SF, Diepersloot RJ, Bonten MJ et al (2015) Identification of patients at high risk for Clostridium difficile infection: development and validation of a risk prediction model in hospitalized patients treated with antibiotics. Clin Microbiol Infect 21(786):e1-8
Collins GS, Reitsma JB, Altman DG, Moons KG (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement. BMC Med 13:1
Lewis SJ, Heaton KW (1997) Stool form scale as a useful guide to intestinal transit time. Scand J Gastroenterol 32:920–924
Ena J, Afonso-Carrillo RG, Bou-Collado M, Galian-Nicolas V, Reyes-Jara MD, Martinez-Peinado C et al (2019) Epidemiology of severe acute diarrhea in patients requiring hospital admission. J Emerg Med 57:290–298
Nusrat S, Bashir MH, Nusrat S, Iqbal T, Zhao D (2015) Epidemiological facts and inpatient burden of diarrhea in resource rich countries: an analysis of time trends in United States: 2326. Off J Am Coll Gastroenterol ACG 110:S967
Corinaldesi R, Stanghellini V, Barbara G, Tomassetti P, De Giorgio R (2012) Clinical approach to diarrhea. Intern Emerg Med 7(Suppl 3):S255–S262
Guh AY, Kutty PK (2018) Clostridioides difficile Infection. Ann Intern Med 169:ITC49–ITC64
Marra AR, Perencevich EN, Nelson RE, Samore M, Khader K, Chiang HY et al (2020) Incidence and outcomes associated with clostridium difficile infections: a systematic review and meta-analysis. JAMA Netw Open 3:e1917597