Impact of recurrent Clostridium difficile infection: hospitalization and patient quality of life

Objectives: Data quantifying outcomes of recurrent Clostridium difficile infection (rCDI) are lacking. We sought to determine the UK hospital resource use and health-related quality of life (HrQoL) associated with rCDI hospitalisations. Patients and methods: A non-interventional study in 6 UK acute hospitals collected retrospective clinical and resource use data from medical records of 64 adults hospitalised for rCDI and 64 matched inpatient controls with a first episode only (f)CDI. Patients were observed from the index event (date rCDI/fCDI confirmed) for 28-days (or death, if sooner); UK-specific reference costs were applied. HrQoL was assessed prospectively in a separate cohort of 30 patients hospitalised with CDI, who completed the EQ-5D-3L questionnaire during their illness. Results: The median total management cost (post-index) was £7,539 and £6,294 for rCDI and fCDI, respectively (cost difference, p=0.075); median length of stay (LOS) was 21 days and 15.5 days, respectively (p=0.269). The median cost difference between matched rCDI and fCDI cases was £689 (IQR=£-1,873-£3,954). Subgroup analysis demonstrated the highest median costs (£8,542/patient) in severe rCDI cases. CDI management costs were driven primarily by hospital LOS, which accounted for >85% of costs in both groups. Mean EQ-5D index values were 46% lower in CDI patients compared with UK population values (0.42 and 0.78, respectively); EQ-VAS scores were 38% lower (47.82 and 77.3, respectively). Conclusions: CDI has considerable impact on patients and healthcare resources. This multicentre study provides a contemporaneous estimate of the real-world UK costs associated with rCDI management, which are substantial and comparable to fCDI costs

Panel Discussion

Each speaker presents for 15 minutes followed by comments from the entire panel for another 15 minutes

NmeCas9 is an intrinsically high-fidelity genome-editing platform

Abstract Background The development of CRISPR genome editing has transformed biomedical research. Most applications reported thus far rely upon the Cas9 protein from Streptococcus pyogenes SF370 (SpyCas9). With many RNA guides, wildtype SpyCas9 can induce significant levels of unintended mutations at near-cognate sites, necessitating substantial efforts toward the development of strategies to minimize off-target activity. Although the genome-editing potential of thousands of other Cas9 orthologs remains largely untapped, it is not known how many will require similarly extensive engineering to achieve single-site accuracy within large genomes. In addition to its off-targeting propensity, SpyCas9 is encoded by a relatively large open reading frame, limiting its utility in applications that require size-restricted delivery strategies such as adeno-associated virus vectors. In contrast, some genome-editing-validated Cas9 orthologs are considerably smaller and therefore better suited for viral delivery. Results Here we show that wildtype NmeCas9, when programmed with guide sequences of the natural length of 24 nucleotides, exhibits a nearly complete absence of unintended editing in human cells, even when targeting sites that are prone to off-target activity with wildtype SpyCas9. We also validate at least six variant protospacer adjacent motifs (PAMs), in addition to the preferred consensus PAM (5′-N4GATT-3′), for NmeCas9 genome editing in human cells. Conclusions Our results show that NmeCas9 is a naturally high-fidelity genome-editing enzyme and suggest that additional Cas9 orthologs may prove to exhibit similarly high accuracy, even without extensive engineering

Investigating Risky Choices Over Losses Using Experimental Data

We conduct a battery of experiments in which agents make choices from several pairs of all-loss-lotteries. Using these choices, we estimate a representation of individual preferences over lotteries. We find statistically and economically significant departures from expected utility maximization for many subjects. We also estimate a preference representation based on summary statistics for behavior in the population of subjects, and again find departures from expected utility maximization. Our results suggest that public policies based on an expected utility approach could significantly underestimate preferences and willingness to pay for risk reduction. Copyright Springer Science + Business Media, Inc. 2005risky decision-making, loss domain, experiments,