Clostridioides difficile infections (CDIs) are caused by a bacterium called clostridioides difficile which is and are often contracted and transmitted in healthcare settings.
CDIs place a significant burden on healthcare facilities and has been shown to substantially increase hospital costs, hospital length of stay, and can cause death. Although CDI is mostly associated with old age, there is still difficulty in predicting which patients are at a higher risk of acquiring it and in turn should be targeted for intervention.
This study aims to determine which patient groups are at a higher chance of getting CDI by calculating the number of cases in different age groups, exploring presence of additional diseases and, the likelihood of subsequent hospitalisation and death.
We shall do this by looking at all patients with a reported CDI diagnosis and classifying them based on whether they developed CDI outside of the hospital (community acquired) or in the hospital (hospital acquired) and whether it was primary or recurrent (repeat) infection. The general CDI population and each group will be described on their characteristics, health care resource use and selected risk factors. A further step will be a comparison of the patients with CDI with patients without CDI in terms of their chance of dying and developing complications.
We should be able to provide an in-depth look into CDIs in England, which will allow changes in health policy and treatment patterns, especially targeting patients with risk factors and those who consume a lot of resources in the NHS.
There has been a dramatic increase in the incidence of CDI in many countries including the UK in recent years despite guidelines such as restricting the use of certain antibiotics aimed at stemming this increase. With current advancements in vaccine research, there is hope that CDI can be prevented in the most at risk groups which would in turn reduce the morbidity, mortality and health care costs associated with them. However, there is limited understanding of the most at risk groups which would affect the potential of targeted preventive methods such as vaccines if they are to be made available on the NHS. There is also a limited availability of knowledge on the prevalence of CDI based on where it is acquired I.e. in the community or hospital and recurrence.
This study aims to differentiate between community and hospital acquired infections by calculating prevalence based on point of acquiring the infection. This will be done by creating two cohorts from the general CDI population by defining community and hospital acquired infections using NHS definitions translated into ICD-10 and OPCS-4 codes.
We shall describe the two cohorts in terms of patient demographic characteristics, prevalence of comorbidities and selected risk factors. Health care resource usage for each cohort will be calculated and reported for inpatient admissions, outpatient, A&E attendances, and primary care appointments. Demographics and health care resource usage for recurrent CDI will be calculated and presented. Outcomes will be described as total, means, medians, percentage or rates as appropriate.
Adjusted and unadjusted odds ratios along with 95% confidence intervals will be calculated for mortality, hospital admission, subsequent CDI morbidity and destination on discharge on comparing each cohort to matched controls. We shall adjust for age, sex and any other risk factors that we may identify as having an effect on the dependent variables.
Prevalence of CDI; Prevalence of recurrence; Prevalence of co-morbidities in the cohort (IBD, CKD, DM, CA); Demographics (Mean and median age on inclusion, age distribution by decade, percent males, deprivation, mean and median follow-up, total and mean admitted time, prevalence of CKD within the cohort, prevalence of Heart Failure within the cohort, prevalence of COPD within the cohort); Healthcare resource outcomes (prescriptions issued in primary care, procedures in secondary care, total appointments and cost in primary care, outpatient appointments, A&E attendances, inpatient admissions, inpatient length of stay, inpatient HRG tariffs, prior hospitalisation); Clinical outcomes(mortality, destination after discharge, severity of the CDI)
Adrian Paul J. Rabe - Chief Investigator - Health iQ Ltd ( UK ) t/a CorEvitas
Adrian Paul J. Rabe - Corresponding Applicant - Health iQ Ltd ( UK ) t/a CorEvitas
Gulsah Akin Unal - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Gulum Alamgir - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
James Tilbury - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Jay Were - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
Gulsah Akin Unal - Collaborator - Health iQ Ltd ( UK ) t/a CorEvitas
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation