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The incubation period for Clostridioides difficile infection (CDI) is generally considered to be less than 1 week, but some recent studies suggest that prolonged carriage prior to disease onset may be common.
Objective:
To estimate the incubation period for patients developing CDI after initial negative cultures.
Methods:
In 3 tertiary care medical centers, we conducted a cohort study to identify hospitalized patients and long-term care facility residents with negative initial cultures for C. difficile followed by a diagnosis of CDI with or without prior detection of carriage. Cases were classified as healthcare facility-onset, community-onset, healthcare facility-associated, or community-associated and were further classified as probable, possible, or unlikely CDI. A parametric accelerated failure time model was used to estimate the distribution of the incubation period.
Results:
Of 4,179 patients with negative enrollment cultures and no prior CDI diagnosis within 56 days, 107 (2.6%) were diagnosed as having CDI, including 19 (17.8%) with and 88 (82.2%) without prior detection of carriage. When the data were censored to only include participants with negative cultures collected within 14 days, the estimated median incubation period was 6 days with 25% and 75% of estimated incubation periods occurring within 3 and 12 days, respectively. The observed estimated incubation period did not differ significantly for patients classified as probable, possible, or unlikely CDI.
Conclusion:
Our findings are consistent with the previous studies that suggested the incubation period for CDI is typically less than 1 week and is less than 2 weeks in most cases.
We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.