MAEDICA – a Journal of Clinical Medicine 2015; 10(2): 97-100
Mædica - a Journal of Clinical Medicine O RGINAL
PAPERS
Clostridium Difficile Associated Disease: Burden of and Predictors for in Hospital Fatal Outcome. Results of a Hospital-Based Study, Bucharest, Romania Niculae ION-NEDELCUa; Petre Iacob CALISTRUb; Emanoil CEAUSUa a
“Dr. Victor Babes” Infectious and Tropical Diseases Hospital, Bucharest, Romania b “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania
ABSTRACT In the last 15 years Clostridium difficile infection became a typical new emergent threat worldwide. Our aim was to describe the risk factors associated with fatal outcome of Clostridium difficile associated disease (CDAD) cases treated in 2012 in “Dr Victor Babes” Infectious and Tropical Diseases Hospital, a 450 beds teaching clinic from Bucharest, Romania. Methods: Retrospective cohort study - the case records of hospitalized patients in the year 2012, presenting with diarrhea and that tested positive for C difficile through toxin A and B assays were reviewed. Data collected through chart review of CDAD were demographic and clinical. A Charlson comorbidities index score was allocated to each case. An EpiInfo data base was fed with demo and clinical data – software’s facilities were used for univariate analysis (Chi square) and also for logistic regression. Results: In study were included all 326 hospitalization episodes with a discharge diagnosis of CDAD in 2012. Overall, 30 of the 326 CDAD patients (9.2%) versus 289 of the 18636 non-CDAD patients (1.55%) died during their hospital stay, resulting in a relative risk of pre-discharge death of 5.93 (4.148.50) for CDAD patients, a CDAD attributable risk of death of 7.65 per 100 patients and a CDAD attributable fraction of 83.15 % (70.1-86%). Unconditional logistic regression retained as fatal outcome predictors the following: (a) a Charlson comorbidity index score >3: (OR: 3.03; CI 95%: 1.21-7.54), (b) ICU stay: (OR: 15.81; CI 95%: 4.4755.89) and (c) age >64 years: (OR: 2.95; CI 95%: 1.15-7.69). Conclusions: Our findings add to the understanding of Clostridium difficile fatal outcome and they have implications for prevention and therapy - the case fatality of 9.2% underlines the importance of the increased efforts in CDAD prevention. Keywords: Clostridium difficile associated disease; predictors for fatal outcome
Address for correspondence: Niculae Ion-Nedelcu, “Dr Victor Babes” Infectious and Tropical Diseases Hospital, Mihai Bravu Avenue, No 281, 3rd District, 030303, Bucharest, Romania E-mail: [email protected] Article received on the 30th of July 2013. Article accepted on the 21st of June 2015.
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
97
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE INTRODUCTION
I
n the last 15 years Clostridium difficile infection became a typical new emergent threat worldwide – for instance number of cases of Clostridium difficile infection that were reported in 2005 in acute care hospitals in the United States (84 per 100,000) were nearly three times the 1996 rate (31 per 100,000) (1). Of even greater concern are increases in severe or fatal infection (2-4). Mortality rates from Clostridium difficile disease in the United States increased from 5.7 per million populations in 1999 to 23.7 per million in 2004 (5). In England, Clostridium difficile infection was listed as the primary cause of death for 499 patients in 1999, a number that rose to 1998 in 2005 and to 3393 in 2006 (6). However specific data on the effect of Clostridium difficile associated disease (CDAD) on the patient’s risk of death or overall hospital mortality are scarce and predictors of outcome are inadequately understood. AIM
T
o describe the burden of and risk factors associated with fatal outcome of CDAD cases treated in 2012 in “Dr Victor Babes” infectious and tropical hospital, a 450 beds teaching clinic from Bucharest, Romania. METHODS
A
retrospective cohort study was carried out. The case records of hospitalized patients in the year 2012, cases presenting with diarrhea and that tested positive for Clostridium difficile through toxin A and B assays were reviewed. Data collected through chart review of CDAD were demographic: (age, gender, place of resi-
Death prevalence Risk Factors
dence) and clinical (comorbidities, lengths of hospitalization, ICU stay, recurrence status and outcome)). A Charlson comorbidities index score (7,8) was allocated to each case. Continuous variable (length of stay and Charlson score) have been converted in categorical ones based on the cut-off represented by the value calculated for 75% percentiles of respective series. Seniors were empirically defined as patients aged over 64 years. An EpiInfo (EpiInfo, version 3.4.2 CDC Atlanta, GA, USA) data base was fed with demographic and clinical data – software’s facilities were used for performing univariate analysis (Chi square test) and also for binary logistic regression. The burden of CDAD associated deaths (relative risk, attributable risk and attributable fraction) was estimated by comparing with pre discharge lethality in non-CDAD cases. RESULTS
I
n study were included all 326 hospitalization episodes with a discharge diagnosis of CDAD in 2012. Overall, 30 of the 326 CDAD patients (9.2%) versus 289 of the 18636 non-CDAD patients (1.55%) died during their hospital stay, resulting in a relative risk of pre-discharge risk of death of 5.93 (4.14-8.50) for CDAD patients, a CDAD attributable risk of death of 7.65 per 100 patients and a CDAD attributable fraction of 83.15 % (70.1-86%). Univariate analysis (Table 1) identified as risk factors significantly associated (p3 [Relative Risk (RR): 2.68; 95% Confidence Interval (CI 95%): 1.35-5.31], (b) age >64 years (RR: 2.77;
Univariate analysis’ results
Risk factor Risk factor Relative Risk p value Present Absent (CI95%) 0.0045 Charlson score > 3 19.1 % 7.1 % 2.68 (1.35-5.31) Residence in Bucharest 10.4 % 7.2 % 1.45 (0.69-3.07) 0.3239 0.0098 Aged > 64 years 13.0 % 4.7 % 2.77 (1.22-6.26) Male gender 10.3 % 8.4 % 1.26 (0.64-2.51) 0.5063 0.0000 Stay in ICU* 43.3 % 5.7 % 7.55 (4.07-13.98) Hospitalization > 15 days 13.8 % 7.7 % 1.78 (0.89-3.58) 0.1052 0.0017 Nosocomial case 19.7 % 6.8 % 2.90 (1.47-5.69) Recurrent case 8.0 % 9.4 % 0.85 (0.31-2.33) 0.7492 TABLE 1. CDAD associated fatal outcome - risk factors’ assessment through univariate analysis performed in “Dr. Victor Babes” Infectious and Tropical Diseases Hospital, Bucharest, 2012. * ICU = Intensive Care Unit
98
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE Risk factors assessed as predictors of CDAD death
Unconditional Logistic Regression Results Odds Ratios (CI95%)
Z statistic
p value
Charlson score >3 (Yes/No) 3.03 (1.21-7.54) 2.3768 0.0175 Stay in ICU (Yes/No) 15.81 (4.47-55.89) 4.2856 0.0000 Aged >64 years (Yes/No) 2.95 (1.15-7.69) 2.2488 0.0245 Nosocomial case (Yes/No) 0.67 (0.19-2.34) -0.6300 0.5887* CONSTANT *** -7.9477 0.0000 TABLE 2. Predictors of CDAD associated fatal outcome found by unconditional logistic regression performed in “Dr. Victor Babes” Infectious and Tropical Diseases Hospital – Bucharest, 2012. * Invalidated as independent predictor of CDAD pre-discharge fatal outcome.
CI 95%: 1.22-6.26), (c) ICU stay (RR:7.55; CI 95%: 4.07-13.98), and (d) nosocomial CDAD (RR: 2.90; CI 95%: 1.147-5.69) Unconditional logistic regression (Table 2) retained as risk factors independently associated (p3 (OR: 3.03;CI 95%: 1.21-7.54], (b) ICU stay (OR: 15.81; CI 95%: 4.47-55.89), and (c) age >64 years (OR: 2.95; CI 95%: 1.15-7.69). DISCUSSIONS
6
%-38% mortality in patients with CDAD has been described (9). Mortality rates similar with our data (9.2%) were reported recently world round (10,11). We found that the higher age is a predictor of pre-discharge CDAD associated death (see Table nr 2); our data are externally validated by many authors who recently explored the relationship between age and fatal outcome in CDAD patients (9, 12-15). Also we found that comorbidities represent an independent risk factors for CDAD pre-discharge fatal outcome (see Table nr 2) – other authors, including those who used Charlson score index as an metric for comorbidities influence, confirmed this finding giving to our data a higher reproducibility profile (3,12,1518). Finally we calculated a higher CDAD fatality odd (see Table 2: 15.81) for patients with an ICU stay history; the same association was reported by Ramirez-Rosales et al in Mexico (9).
The significance of this finding is special; for prevention purpose the ICU stay seems to be a key issue being the unique potentially modifiable variable from the three CDAD mortality predictors documented in this study. Logically and practically prevention of Clostridium difficile spores transmission in the health facilities and mainly in ICU appears to be the key strategy to alter the CDAD morbidity and consequently the mortality. On this end the published guidelines (19, 20) must be integrated in facility’s current practices, compliance with these practices (i.e. hand hygiene, contact precautions, antimicrobial stewardship, etc.) carefully monitorized and in time feedback provided to clinicians. CONCLUSIONS
O
ur findings add to the understanding of Clostridium difficile fatal outcome and have implications for prevention and therapy – the case fatality of 9.2% underscore the importance of increased efforts in CDAD prevention, in particular for patients with underlying diseases, old and/or treated in ICU. LIMITS
O
ur findings are limited to hospitalized patients and may not be applicable to patients with community-associated Clostridium difficile infections (21). Conflict of interests: none declared. Financial support: none declared.
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
99
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE
REFERENCES 1.
2.
3.
4.
5.
6.
7.
Kelly CP, LaMont JT – Clostridium difficile – More difficult than ever. N Eng J Med 2008;359:1932-1940. Pepin J, Valiquette L, Alary ME, et al. – Clostridium difficile-associated diarrhea in a region of Quebec from 1991 to 2003: a changing pattern of disease severity. CMAJ 2004;171: 466-72. Loo VG, Poirier L, Miller MA, et al. – A predominantly clonal multi-institutional outbreak of Clostridium difficile-associated diarrhea with high morbidity and mortality. N Engl J Med 2006; 353: 2442-9. Muto CA, Pokrywka M, Shutt K, et al. – A large outbreak of Clostridium difficile-associated disease with an unexpected proportion of deaths and colectomies at a teaching hospital following increased fluoroquinolone use. Infect Control Hosp Epidemiol 2005;26:273-80. Redelings MD, Sorvillo F, Masdcola L – Increase in Clostridium difficile-related mortality rates, United States, 1999-2004. Emerg Infect Dis 2007;13:1417-1419. United Kingdom national statistics. Nexport, United Kingdom Office for National Statistics, UK Statistic Authority. http://www.statistics.gov. uk Charlson ME, Pompei P, Ales KL, et al. – A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis 1987;40:373-383.
100
Maedica
8.
9.
10.
11.
12.
13.
14.
15.
Deyo R, Chekin DC, Ciol MA – Adapting a clinical comorbidity index for use with ICD-CM administrative databases. J Clin Epidemiol 1992;45:613-619 Ramirez-Rosales A, Cantu-Llanos E – Intrahospital mortality in patients with Clostridium difficile-associated diarrhea infection. Rev Gastroenterol Mex. 2012;77:60-65. Dudukgian H, Sie E, Gonzales-Ruiz C, et al. – C difficile colitis – predictors of fatal outcome. J Gastrointest Surg. 2010;14:315-322. Wenisch JM, Schmid D, Kuo KW, et al. – Hospital-acquired Clostridium difficile infection: determinants for severe disease. Eur J Clin Microbiol Infect Dis 2012;18:1923-1930. Halim HA, Peterson GM, Friesen WT, et al. – Case-controlled review of Clostridium difficile-associated diarrhea in southern Tasmania. J Clin Pharm Ther 1997;22:391-397. Karas JA, Enoch DA, Allyu SH – A review of mortality due to Clostridium difficile infection. J Infect 2010;61:1-8. Morrison RH, Hall NS, Said M, et al. – Risk factors associated with complications and mortality in patients with Clostridium difficile infections. Clin Infect Dis 2011;53:1173-1178. Rodriguez-Pardo D, Almirante B, Bartolome RM, et al. – Epidemiology of Clostridium difficile Infection and Risk Factors for Unfavorable Clinical Outcomes: Results of a Hospital-based
A Journal of Clinical Medicine, Volume 10 No.2 2015
16.
17.
18.
19.
20.
21.
Study in Barcelona, Spain. J Clin Microbiol 2013;51:1465-1473. Kyne L, Merry C, O’Connell B, et al. – Factors associated with prolonged symptoms and severe disease due to Clostridium difficile. Age Ageing 1999;28:107-112. Welfare MR, Lalayiannis LC, Martin KE, et al. – Co-morbidities as predictors of mortality in Clostridium difficile infection and derivation of the ARC predictive score. J Hosp Infect 2011;79:359-363. Wenisch JM, Schmid D, Tucek G, et al. – A prospective cohort study on hospital mortality due to Clostridium difficile infection. Infection 2012;40:479484. Dubberke ER, Gerding DN, Classen D, et al. – Strategies to prevent Clostridium difficile infections in acute care hospitals. Infect Control Hosp Epidemiol 2008;20 (Suppl 1): S81-S92 Cohen SN, Gerding DN, Johnson S, et al. – Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by society of healthcare epidemiology of America (SHEA) and the infectious diseases society of America (IDSA). Infect Control Hosp Epidemiol 2010;31:434-455. CDC Severe Clostridium difficile- associated disease in populations previously at low risk-four states, 2005. MMWR Morb Mortal Wkly Rep 2005;54:1201-1205.
Mædica - a Journal of Clinical Medicine O RGINAL
PAPERS
Clostridium Difficile Associated Disease: Burden of and Predictors for in Hospital Fatal Outcome. Results of a Hospital-Based Study, Bucharest, Romania Niculae ION-NEDELCUa; Petre Iacob CALISTRUb; Emanoil CEAUSUa a
“Dr. Victor Babes” Infectious and Tropical Diseases Hospital, Bucharest, Romania b “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania
ABSTRACT In the last 15 years Clostridium difficile infection became a typical new emergent threat worldwide. Our aim was to describe the risk factors associated with fatal outcome of Clostridium difficile associated disease (CDAD) cases treated in 2012 in “Dr Victor Babes” Infectious and Tropical Diseases Hospital, a 450 beds teaching clinic from Bucharest, Romania. Methods: Retrospective cohort study - the case records of hospitalized patients in the year 2012, presenting with diarrhea and that tested positive for C difficile through toxin A and B assays were reviewed. Data collected through chart review of CDAD were demographic and clinical. A Charlson comorbidities index score was allocated to each case. An EpiInfo data base was fed with demo and clinical data – software’s facilities were used for univariate analysis (Chi square) and also for logistic regression. Results: In study were included all 326 hospitalization episodes with a discharge diagnosis of CDAD in 2012. Overall, 30 of the 326 CDAD patients (9.2%) versus 289 of the 18636 non-CDAD patients (1.55%) died during their hospital stay, resulting in a relative risk of pre-discharge death of 5.93 (4.148.50) for CDAD patients, a CDAD attributable risk of death of 7.65 per 100 patients and a CDAD attributable fraction of 83.15 % (70.1-86%). Unconditional logistic regression retained as fatal outcome predictors the following: (a) a Charlson comorbidity index score >3: (OR: 3.03; CI 95%: 1.21-7.54), (b) ICU stay: (OR: 15.81; CI 95%: 4.4755.89) and (c) age >64 years: (OR: 2.95; CI 95%: 1.15-7.69). Conclusions: Our findings add to the understanding of Clostridium difficile fatal outcome and they have implications for prevention and therapy - the case fatality of 9.2% underlines the importance of the increased efforts in CDAD prevention. Keywords: Clostridium difficile associated disease; predictors for fatal outcome
Address for correspondence: Niculae Ion-Nedelcu, “Dr Victor Babes” Infectious and Tropical Diseases Hospital, Mihai Bravu Avenue, No 281, 3rd District, 030303, Bucharest, Romania E-mail: [email protected] Article received on the 30th of July 2013. Article accepted on the 21st of June 2015.
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
97
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE INTRODUCTION
I
n the last 15 years Clostridium difficile infection became a typical new emergent threat worldwide – for instance number of cases of Clostridium difficile infection that were reported in 2005 in acute care hospitals in the United States (84 per 100,000) were nearly three times the 1996 rate (31 per 100,000) (1). Of even greater concern are increases in severe or fatal infection (2-4). Mortality rates from Clostridium difficile disease in the United States increased from 5.7 per million populations in 1999 to 23.7 per million in 2004 (5). In England, Clostridium difficile infection was listed as the primary cause of death for 499 patients in 1999, a number that rose to 1998 in 2005 and to 3393 in 2006 (6). However specific data on the effect of Clostridium difficile associated disease (CDAD) on the patient’s risk of death or overall hospital mortality are scarce and predictors of outcome are inadequately understood. AIM
T
o describe the burden of and risk factors associated with fatal outcome of CDAD cases treated in 2012 in “Dr Victor Babes” infectious and tropical hospital, a 450 beds teaching clinic from Bucharest, Romania. METHODS
A
retrospective cohort study was carried out. The case records of hospitalized patients in the year 2012, cases presenting with diarrhea and that tested positive for Clostridium difficile through toxin A and B assays were reviewed. Data collected through chart review of CDAD were demographic: (age, gender, place of resi-
Death prevalence Risk Factors
dence) and clinical (comorbidities, lengths of hospitalization, ICU stay, recurrence status and outcome)). A Charlson comorbidities index score (7,8) was allocated to each case. Continuous variable (length of stay and Charlson score) have been converted in categorical ones based on the cut-off represented by the value calculated for 75% percentiles of respective series. Seniors were empirically defined as patients aged over 64 years. An EpiInfo (EpiInfo, version 3.4.2 CDC Atlanta, GA, USA) data base was fed with demographic and clinical data – software’s facilities were used for performing univariate analysis (Chi square test) and also for binary logistic regression. The burden of CDAD associated deaths (relative risk, attributable risk and attributable fraction) was estimated by comparing with pre discharge lethality in non-CDAD cases. RESULTS
I
n study were included all 326 hospitalization episodes with a discharge diagnosis of CDAD in 2012. Overall, 30 of the 326 CDAD patients (9.2%) versus 289 of the 18636 non-CDAD patients (1.55%) died during their hospital stay, resulting in a relative risk of pre-discharge risk of death of 5.93 (4.14-8.50) for CDAD patients, a CDAD attributable risk of death of 7.65 per 100 patients and a CDAD attributable fraction of 83.15 % (70.1-86%). Univariate analysis (Table 1) identified as risk factors significantly associated (p3 [Relative Risk (RR): 2.68; 95% Confidence Interval (CI 95%): 1.35-5.31], (b) age >64 years (RR: 2.77;
Univariate analysis’ results
Risk factor Risk factor Relative Risk p value Present Absent (CI95%) 0.0045 Charlson score > 3 19.1 % 7.1 % 2.68 (1.35-5.31) Residence in Bucharest 10.4 % 7.2 % 1.45 (0.69-3.07) 0.3239 0.0098 Aged > 64 years 13.0 % 4.7 % 2.77 (1.22-6.26) Male gender 10.3 % 8.4 % 1.26 (0.64-2.51) 0.5063 0.0000 Stay in ICU* 43.3 % 5.7 % 7.55 (4.07-13.98) Hospitalization > 15 days 13.8 % 7.7 % 1.78 (0.89-3.58) 0.1052 0.0017 Nosocomial case 19.7 % 6.8 % 2.90 (1.47-5.69) Recurrent case 8.0 % 9.4 % 0.85 (0.31-2.33) 0.7492 TABLE 1. CDAD associated fatal outcome - risk factors’ assessment through univariate analysis performed in “Dr. Victor Babes” Infectious and Tropical Diseases Hospital, Bucharest, 2012. * ICU = Intensive Care Unit
98
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE Risk factors assessed as predictors of CDAD death
Unconditional Logistic Regression Results Odds Ratios (CI95%)
Z statistic
p value
Charlson score >3 (Yes/No) 3.03 (1.21-7.54) 2.3768 0.0175 Stay in ICU (Yes/No) 15.81 (4.47-55.89) 4.2856 0.0000 Aged >64 years (Yes/No) 2.95 (1.15-7.69) 2.2488 0.0245 Nosocomial case (Yes/No) 0.67 (0.19-2.34) -0.6300 0.5887* CONSTANT *** -7.9477 0.0000 TABLE 2. Predictors of CDAD associated fatal outcome found by unconditional logistic regression performed in “Dr. Victor Babes” Infectious and Tropical Diseases Hospital – Bucharest, 2012. * Invalidated as independent predictor of CDAD pre-discharge fatal outcome.
CI 95%: 1.22-6.26), (c) ICU stay (RR:7.55; CI 95%: 4.07-13.98), and (d) nosocomial CDAD (RR: 2.90; CI 95%: 1.147-5.69) Unconditional logistic regression (Table 2) retained as risk factors independently associated (p3 (OR: 3.03;CI 95%: 1.21-7.54], (b) ICU stay (OR: 15.81; CI 95%: 4.47-55.89), and (c) age >64 years (OR: 2.95; CI 95%: 1.15-7.69). DISCUSSIONS
6
%-38% mortality in patients with CDAD has been described (9). Mortality rates similar with our data (9.2%) were reported recently world round (10,11). We found that the higher age is a predictor of pre-discharge CDAD associated death (see Table nr 2); our data are externally validated by many authors who recently explored the relationship between age and fatal outcome in CDAD patients (9, 12-15). Also we found that comorbidities represent an independent risk factors for CDAD pre-discharge fatal outcome (see Table nr 2) – other authors, including those who used Charlson score index as an metric for comorbidities influence, confirmed this finding giving to our data a higher reproducibility profile (3,12,1518). Finally we calculated a higher CDAD fatality odd (see Table 2: 15.81) for patients with an ICU stay history; the same association was reported by Ramirez-Rosales et al in Mexico (9).
The significance of this finding is special; for prevention purpose the ICU stay seems to be a key issue being the unique potentially modifiable variable from the three CDAD mortality predictors documented in this study. Logically and practically prevention of Clostridium difficile spores transmission in the health facilities and mainly in ICU appears to be the key strategy to alter the CDAD morbidity and consequently the mortality. On this end the published guidelines (19, 20) must be integrated in facility’s current practices, compliance with these practices (i.e. hand hygiene, contact precautions, antimicrobial stewardship, etc.) carefully monitorized and in time feedback provided to clinicians. CONCLUSIONS
O
ur findings add to the understanding of Clostridium difficile fatal outcome and have implications for prevention and therapy – the case fatality of 9.2% underscore the importance of increased efforts in CDAD prevention, in particular for patients with underlying diseases, old and/or treated in ICU. LIMITS
O
ur findings are limited to hospitalized patients and may not be applicable to patients with community-associated Clostridium difficile infections (21). Conflict of interests: none declared. Financial support: none declared.
Maedica
A Journal of Clinical Medicine, Volume 10 No.2 2015
99
CLOSTRIDIUM DIFFICILE ASSOCIATED DISEASE
REFERENCES 1.
2.
3.
4.
5.
6.
7.
Kelly CP, LaMont JT – Clostridium difficile – More difficult than ever. N Eng J Med 2008;359:1932-1940. Pepin J, Valiquette L, Alary ME, et al. – Clostridium difficile-associated diarrhea in a region of Quebec from 1991 to 2003: a changing pattern of disease severity. CMAJ 2004;171: 466-72. Loo VG, Poirier L, Miller MA, et al. – A predominantly clonal multi-institutional outbreak of Clostridium difficile-associated diarrhea with high morbidity and mortality. N Engl J Med 2006; 353: 2442-9. Muto CA, Pokrywka M, Shutt K, et al. – A large outbreak of Clostridium difficile-associated disease with an unexpected proportion of deaths and colectomies at a teaching hospital following increased fluoroquinolone use. Infect Control Hosp Epidemiol 2005;26:273-80. Redelings MD, Sorvillo F, Masdcola L – Increase in Clostridium difficile-related mortality rates, United States, 1999-2004. Emerg Infect Dis 2007;13:1417-1419. United Kingdom national statistics. Nexport, United Kingdom Office for National Statistics, UK Statistic Authority. http://www.statistics.gov. uk Charlson ME, Pompei P, Ales KL, et al. – A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis 1987;40:373-383.
100
Maedica
8.
9.
10.
11.
12.
13.
14.
15.
Deyo R, Chekin DC, Ciol MA – Adapting a clinical comorbidity index for use with ICD-CM administrative databases. J Clin Epidemiol 1992;45:613-619 Ramirez-Rosales A, Cantu-Llanos E – Intrahospital mortality in patients with Clostridium difficile-associated diarrhea infection. Rev Gastroenterol Mex. 2012;77:60-65. Dudukgian H, Sie E, Gonzales-Ruiz C, et al. – C difficile colitis – predictors of fatal outcome. J Gastrointest Surg. 2010;14:315-322. Wenisch JM, Schmid D, Kuo KW, et al. – Hospital-acquired Clostridium difficile infection: determinants for severe disease. Eur J Clin Microbiol Infect Dis 2012;18:1923-1930. Halim HA, Peterson GM, Friesen WT, et al. – Case-controlled review of Clostridium difficile-associated diarrhea in southern Tasmania. J Clin Pharm Ther 1997;22:391-397. Karas JA, Enoch DA, Allyu SH – A review of mortality due to Clostridium difficile infection. J Infect 2010;61:1-8. Morrison RH, Hall NS, Said M, et al. – Risk factors associated with complications and mortality in patients with Clostridium difficile infections. Clin Infect Dis 2011;53:1173-1178. Rodriguez-Pardo D, Almirante B, Bartolome RM, et al. – Epidemiology of Clostridium difficile Infection and Risk Factors for Unfavorable Clinical Outcomes: Results of a Hospital-based
A Journal of Clinical Medicine, Volume 10 No.2 2015
16.
17.
18.
19.
20.
21.
Study in Barcelona, Spain. J Clin Microbiol 2013;51:1465-1473. Kyne L, Merry C, O’Connell B, et al. – Factors associated with prolonged symptoms and severe disease due to Clostridium difficile. Age Ageing 1999;28:107-112. Welfare MR, Lalayiannis LC, Martin KE, et al. – Co-morbidities as predictors of mortality in Clostridium difficile infection and derivation of the ARC predictive score. J Hosp Infect 2011;79:359-363. Wenisch JM, Schmid D, Tucek G, et al. – A prospective cohort study on hospital mortality due to Clostridium difficile infection. Infection 2012;40:479484. Dubberke ER, Gerding DN, Classen D, et al. – Strategies to prevent Clostridium difficile infections in acute care hospitals. Infect Control Hosp Epidemiol 2008;20 (Suppl 1): S81-S92 Cohen SN, Gerding DN, Johnson S, et al. – Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by society of healthcare epidemiology of America (SHEA) and the infectious diseases society of America (IDSA). Infect Control Hosp Epidemiol 2010;31:434-455. CDC Severe Clostridium difficile- associated disease in populations previously at low risk-four states, 2005. MMWR Morb Mortal Wkly Rep 2005;54:1201-1205.
