Article

The Effect of Hospital-Acquired Clostridium difficile Infection on In-Hospital Mortality

Clinical Quality and Performance Management, Ottawa Hospital, Ottawa, Ontario, Canada.
Archives of internal medicine (Impact Factor: 17.33). 11/2010; 170(20):1804-10. DOI: 10.1001/archinternmed.2010.405
Source: PubMed

ABSTRACT

The effects of hospital-acquired Clostridium difficile infection (CDI) on patient outcomes are incompletely understood. We conducted this study to determine the independent impact of hospital-acquired CDI on in-hospital mortality after adjusting for the time-varying nature of CDI and baseline mortality risk at hospital admission.
This retrospective observational study used data from the Ottawa Hospital (Ottawa, Ontario, Canada) data warehouse. Inpatient admissions with a start date after July 1, 2002, and a discharge date before March 31, 2009, were included. Stratified analyses and a Cox multivariate proportional hazards regression model were used to determine if hospital-acquired CDI was associated with time to in-hospital death.
A total of 136 877 admissions were included. Hospital-acquired CDI was identified in 1393 admissions (overall risk per admission, 1.02%; 95% confidence interval [CI], 0.97%-1.06%). The risk of hospital-acquired CDI significantly increased as the baseline mortality risk increased: from 0.2% to 2.6% in the lowest to highest deciles of baseline risk. Hospital-acquired CDI significantly increased the absolute risk of in-hospital death across all deciles of baseline risk (pooled absolute increase, 11%; 95% CI, 9%-13%). Cox regression analysis revealed an average 3-fold increase in the hazard of death associated with hospital-acquired CDI (95% CI, 2.4-3.7); this hazard ratio decreased with increasing baseline mortality risk.
Hospital-acquired CDI was independently associated with an increased risk of in-hospital death. Across all baseline risk strata, for every 10 patients acquiring the infection, 1 person died.

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    • "In the literature, C. difficile infections are associated with high mortality risks of around 10% in the first 30 days [3,4]. In our study, the CDI-related mortality was also 10%, and 12% of the CDI patients experienced a complicated course within 30 days after diagnosis. "
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    ABSTRACT: Clostridium difficile infections (CDIs) are a common cause of antibiotic-associated diarrhoea and associated with CDI-related mortality in c. 10%. To date, there is no prediction model in use that guides clinicians to identify patients at high risk for complicated CDI. From 2006 to 2009, nine Dutch hospitals included hospitalized CDI patients in a prospective cohort. Potential predictors of a complicated course (ICU admission, colectomy or death due to CDI) were evaluated in uni- and multivariate logistic regression. A score was constructed that was internally validated by bootstrapping. Furthermore, a pilot external validation was performed. Twelve per cent of 395 CDI patients had a complicated course within 30 days after diagnosis. Age (≥85 years, OR 4.96; 50-84 years, 1.83), admission due to diarrhoea (OR 3.27), diagnosis at the ICU department (OR 7.03), recent abdominal surgery (OR 0.23) and hypotension (OR 3.25) were independent predictors of a complicated course. These variables were used to construct a prediction model. A score subsequently classified patients into high risk (39% with a complicated course), intermediate (16%), low (5%) or virtually no risk of experiencing a complicated course. The score performed well after internal validation (AUC 0.78) and a pilot external validation among 139 patients showed similar good performance (AUC 0.73). We present an easy-to-use, clinically useful risk score that is capable of categorizing CDI patients according to their outcome. Because classification is available at diagnosis, it could have major implications for treatment choice.
    Full-text · Article · Sep 2013 · Clinical Microbiology and Infection
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    • "We are testing our approach in a Clinical Intelligence scenario dedicated to the surveillance for, and research on Hospital-Acquired Infections (HAI). To this end, we are prototyping a SADI-based infrastructure for semantic querying of a relational database used by The Ottawa Hospital (TOH) and containing an extract from the large TOH datawarehouse accumulating data from the most important IT systems of the hospital (see, e.g., [21,22]). Our infrastructure consists of an ontology defining concepts suitable for reasoning about Hospital-Acquired Infections, and a number of SADI services drawing data from the DB, as well as several general purpose services dealing with information about drugs, diseases and infectious agents. "
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    ABSTRACT: Background Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas. Results A possible solution is semantic querying where the user formulates queries in terms of domain ontologies that are much easier to navigate and comprehend than data schemas. In this article, we are exploring the possibility of using SADI Semantic Web services for semantic querying of clinical data. We have developed a prototype of a semantic querying infrastructure for the surveillance of, and research on, hospital-acquired infections. Conclusions Our results suggest that SADI can support ad-hoc, self-service, semantic queries of relational data in a Clinical Intelligence context. The use of SADI compares favourably with approaches based on declarative semantic mappings from data schemas to ontologies, such as query rewriting and RDFizing by materialisation, because it can easily cope with situations when (i) some computation is required to turn relational data into RDF or OWL, e.g., to implement temporal reasoning, or (ii) integration with external data sources is necessary.
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    • "The two numbers that are shown in the n columns reflect the number of patients that died on the total number of patients that lived within the community boundaries (numerator/denominator). In another recent study, the independent impact of hospital acquired CDI on in-hospital mortality was investigated, after adjusting for the time-varying nature of CDI and baseline mortality risk at hospital [27]. On average, patients with CDI had a 3-fold increased risk of death. "
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    ABSTRACT: Clostridium difficile infection (CDI) due to polymerase chain reaction (PCR) ribotype 027 (type 027) has been described worldwide. In some countries, an increase was reported of toxin A-negative PCR ribotype 017 (type 017). We encountered an outbreak due to these 2 types occurring simultaneously in a 980-bed teaching hospital in the Netherlands. In a case-control study from May 2005 through January 2007, we investigated general and type-specific risk factors as well as outcome parameters for CDI due to type 027 or 017. Clonal dissemination was investigated by multilocus variable number of tandem repeat analysis (MLVA). We identified 168 CDI patients: 57 (34%) with type 017, 46 (27%) with type 027, and 65 (39%) with 1 of 36 different other types. As controls, we included 77 non-CDI diarrheal patients and 162 patients without diarrhea. Risk factors for CDI were nasogastric intubation, recent hospitalization, and use of cephalosporins and clindamycin. Type-specific risk factors were older age for both types 017 and 027, use of clindamycin and immunosuppressive agents for type 017, and use of fluoroquinolones for type 027. At day 30 of follow-up, the overall mortality among patients with types 017, 027, other types, non-CDI diarrheal patients, and nondiarrheal patients was 23%, 26%, 3%, 2%, and 6%, respectively. MLVA showed persistent clonal dissemination of types 017 and 027, despite appropriate infection control measures. Patients with CDI have type-specific risk factors and mortality rates, with prolonged clonal spread of type 027 or 017.
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