An interventional study of Risk-stratified discharge and post-discharge care in Sepsis, sponsored by University of British Columbia. Status unknown at 1 site in Canada. Open to participants aged 0 Days to 59 Months. Per ClinicalTrials.gov, last updated 2023-02-15.
Sponsored by University of British Columbia · Not applicable, Interventional, and Treatment
In Uganda, about 5% of children discharged after hospitalization for a serious infection will die in the weeks after returning home. Doctors and parents are often unaware of this period of vulnerability and are poorly equipped to identify or handle this critical situation. This project builds on past work to develop and evaluate models and technology to predict, before discharge, an individual child's risk of recurrent illness, as well as to provide additional post-discharge support to at-risk children. This study seeks to evaluate the effect of a novel "Smart Discharges" approach on childhood mortality and health seeking behaviour.
PURPOSE:
Our purpose is to conduct an interventional cohort study to evaluate the impact of the Smart Discharges approach to discharge care on pediatric post-discharge mortality.
HYPOTHESIS:
Our Smart Discharges approach will improve post-discharge health seeking and reduce post-discharge mortality.
JUSTIFICATION:
With an improved understanding of risk, and an ability to determine risk at the bedside, a Smart Discharge program will ensure optimized resource allocation, focusing on children most in need of limited resources. Such programs in precision public health can not only save lives and resources, but are much more likely to be scalable in economically strained environments.
OBJECTIVES:
The objective of this study is to determine whether a individualized, risk-based approach to improving pediatric discharges will reduce 6-month post-discharge mortality among children admitted with suspected sepsis
The study has two objectives, each corresponding to a phase:
RESEARCH DESIGN:
This will be a two-phase study: Phase I is a multi-site prospective observational cohort study, while Phase II is a multi-site prospective interventional cohort study. This prospective study will be conducted from March 2017 to January 2024. The study will enroll 5700 children under five years of age (2700 \<6 months of age, 3000 6-60m of age) in Phase I (non-interventional) and an equal number (5700) of children during phase II (interventional phase), for a total of 11,600 children.
STATISTICAL ANALYSIS:
Our prior work has shown that the 6-month post-discharge mortality rate is 5%. Our preliminary work has also suggested that our expected mortality benefit will be between 25% and 30% relative risk reduction. Assuming a relative risk reduction of 22.5%, we would need to enroll 5250 children per arm. We thus will conservatively aim to enroll 5700 per arm to account for losses to follow-up.
All analyses will be conducted using R 4.2.2 (Vienna, Austria; http://www.R-project.org). External model validation will be conducted using the Phase I cohort on the previously developed Smart Discharge Model. The Smart Discharge Model will then be updated to include data from the Phase I cohort. Final prediction models will be developed separately for children \<6m of age and for children 6m - 5 years of age, with an area under the ROC curve analysis used to assess the overall performance of the final models. For the final model in older children (6m - 5y), the risk cut-off will be chosen based on the sensitivity and specificity, ensuring a sensitivity of >80% (initial derived model sensitivity was 82%). The final sensitivity and specificity will be reported, along with positive and negative predictive values (based on the overall mortality rate, and the mortality rates of each site). For the model in younger children, the same approach will be used, but ensuring the sensitivity is at least 85%, due to an expected higher mortality rate among younger children. The separation of ages has been determined to be the optimal approach for these models.
To evaluate the effectiveness of the intervention, a cox-proportional hazards regression on the time to post-discharge mortality will be used, including the year of discharge as a covariate to account for potential trends in mortality unrelated to the intervention. Additional potentially confounding variables will be identified based on a combination of pre-existing and expert knowledge, and univariate analysis of potential confounders on outcomes. A final multivariable model will be used to determine the adjusted effect of the Smart Discharge intervention. Interrupted time series, which use segmented regression modeling to determine the effect of the intervention after controlling for pre- and post-intervention time trends, will also be used to account for potential pre-intervention trends in mortality.
1,903 studies on the registry are indexed under Sepsis; 466 are open to participants now.
This study's planned enrollment of 11,700 is above the median of 105 across 899 interventional studies indexed under Sepsis.
Browse Sepsis studies →University of British Columbia is the lead sponsor of 1,310 studies on the registry; 253 are open to participants now.
Of its 6 completed or terminated interventional studies of FDA-regulated products, 1 (17%) have results posted.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Phase 1: Observational only
Phase 2: Intervention
Behavioral: Risk-stratified discharge and post-discharge care
Interventional intensity is based on predicted risk. Predicted risk based on previously developed prediction algorithms. Low risk: receive discharge education and counselling only; Moderate risk: Discharge education and counselling + 1 post-discharge follow-up referral at day 7; High risk: Discharge education and counselling + 3 post-discharge follow-up referrals (D2, D7, D14); Very high risk: Discharge education and counselling + 3 post-discharge follow-up referrals (D2, D7, D14, D28)
Post-discharge mortality
Rate of all-cause mortality within 6-months post-discharge
Time frame: From discharge until 6 months post-discharge
Post-discharge re-admission
Rate of all-cause re-admissions within 6-months post-discharge.
Time frame: From discharge until 6 months post-discharge
Post-discharge health seeking
proportion of patients who reported attending a post-discharge referral visit within 6 months post-discharge. proportion of patients who reported seeking any care within 6 months post-discharge through self referral.
Time frame: From discharge until 6 months post-discharge
Plan to share: Yes — At each stage of the analysis and data preparation all of the study data will be prepared for public distribution. We will make every effort to prevent re-identification of subjects by coding data that has the potential of being identifiable. For example we will convert all dates into meaningful decimal numbers (date of birth into days since birth and date of recruitment will be reduced to month of recruitment) and all locations will coded into data that is useful but not specific (such as address converted to distance and direction from facility). We will ensure that data elements with small numbers of subjects (less than 10) will be coded or lumped to avoid identification. The study data will be made publically available using a reputable data hosting service (e.g. INDEPTH Data Repository, Dataverse etc.). During the data analysis stage, data lacking patient identifiers will be accessed from REDCap by team members involved in the statistical analysis.
Supporting information: Study protocol, Sap
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University of British Columbia