Complicated intra-abdominal infections in a worldwide context: an observational prospective study (CIAOW Study).

Despite advances in diagnosis, surgery, and antimicrobial therapy, mortality rates associated with complicated intra-abdominal infections remain exceedingly high. The World Society of Emergency Surgery (WSES) has designed the CIAOW study in order to describe the clinical, microbiological, and management-related profiles of both community- and healthcare-acquired complicated intra-abdominal infections in a worldwide context. The CIAOW study (Complicated Intra-Abdominal infection Observational Worldwide Study) is a multicenter observational study currently underway in 57 medical institutions worldwide. The study includes patients undergoing surgery or interventional drainage to address complicated intra-abdominal infections. This preliminary report includes all data from almost the first two months of the six-month study period. Patients who met inclusion criteria with either community-acquired or healthcare-associated complicated intra-abdominal infections (IAIs) were included in the study. 702 patients with a mean age of 49.2 years (range 18-98) were enrolled in the study. 272 patients (38.7%) were women and 430 (62.3%) were men. Among these patients, 615 (87.6%) were affected by community-acquired IAIs while the remaining 87 (12.4%) suffered from healthcare-associated infections. Generalized peritonitis was observed in 304 patients (43.3%), whereas localized peritonitis or abscesses was registered in 398 (57.7%) patients.The overall mortality rate was 10.1% (71/702). The final results of the CIAOW Study will be published following the conclusion of the study period in March 2013.

Complicated intra-abdominal infections worldwide: the definitive data of the CIAOW Study.

The CIAOW study (Complicated intra-abdominal infections worldwide observational study) is a multicenter observational study underwent in 68 medical institutions worldwide during a six-month study period (October 2012-March 2013). The study included patients older than 18 years undergoing surgery or interventional drainage to address complicated intra-abdominal infections (IAIs). 1898 patients with a mean age of 51.6 years (range 18-99) were enrolled in the study. 777 patients (41%) were women and 1,121 (59%) were men. Among these patients, 1,645 (86.7%) were affected by community-acquired IAIs while the remaining 253 (13.3%) suffered from healthcare-associated infections. Intraperitoneal specimens were collected from 1,190 (62.7%) of the enrolled patients. 827 patients (43.6%) were affected by generalized peritonitis while 1071 (56.4%) suffered from localized peritonitis or abscesses. The overall mortality rate was 10.5% (199/1898). According to stepwise multivariate analysis (PR = 0.005 and PE = 0.001), several criteria were found to be independent variables predictive of mortality, including patient age (OR = 1.1; 95%CI = 1.0-1.1; p < 0.0001), the presence of small bowel perforation (OR = 2.8; 95%CI = 1.5-5.3; p < 0.0001), a delayed initial intervention (a delay exceeding 24 hours) (OR = 1.8; 95%CI = 1.5-3.7; p < 0.0001), ICU admission (OR = 5.9; 95%CI = 3.6-9.5; p < 0.0001) and patient immunosuppression (OR = 3.8; 95%CI = 2.1-6.7; p < 0.0001).

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.