| Titre : | The Co-Seasonality of Pneumonia and Influenza With Clostridium difficile Infection in the United States, 1993-2008 (2013) |
| Auteurs : | Kevin-A BROWN ; Dalla Lana School of Public Health, University of Toronto (Toronto ON, Canada) ; Nick DANEMAN ; Paul ARORA ; Rahim MOINEDDIN ; David-N FISMAN |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 178, n° 1, Juillet 2013) |
| Pagination : | 118-125 |
| Langues: | Anglais |
| Mots-clés : | Pneumonie ; Diarrhée ; Infection ; Variation saisonnière ; Grippe ; Homme ; Saison ; Epidémiologie ; Virose ; Bactérie ; Amérique ; Amérique du Nord |
| Résumé : | [BDSP. Notice produite par INIST-CNRS o88s9R0x. Diffusion soumise à autorisation]. Seasonal variations in the incidence of pneumonia and influenza are associated with nosocomial Clostridium difficile infection (CDI) incidence, but the reasons why remain unclear. Our objective was to consider the impact of pneumonia and influenza timing and severity on CDI incidence. We conducted a retrospective cohort study using the US National Hospital Discharge Survey sample. Hospitalized patients with a diagnosis of CDI or pneumonia and influenza between 1993 and 2008 were identified from the National Hospital Discharge Survey data set. Poisson regression models of monthly CDI incidence were used to measure 1) the time lag between the annual pneumonia and influenza prevalence peak and the annual CDI incidence peak and 2) the lagged effect of pneumonia and influenza prevalence on CDI incidence. CDI was identified in 18,465 discharges (8.52 per 1,000 discharges). Peak pneumonia prevalence preceded peak CDI incidence by 9.14 weeks (95% confidence interval : 4.61,13.67). A 1% increase in pneumonia prevalence was associated with a cumulative effect of 11.3% over a 6-month lag period (relative risk=1.113,95% confidence interval : 1.073,1.153). Future research could seek to understand which mediating pathways, including changes in broad-spectrum antibiotic prescribing and hospital crowding, are most responsible for the associated changes in incidence. |
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