The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12617001362381
Ethics application status
Approved
Date submitted
20/09/2017
Date registered
27/09/2017
Date last updated
27/09/2017
Type of registration
Prospectively registered

Titles & IDs
Public title
Early and late predictors of hospital readmissions and whether nutrition status helps predict hospital readmissions
Scientific title
Predictors of very early and late readmissions in medical patients and whether Malnutrition universal screening tool (MUST) score can predict hospital readmissions
Secondary ID [1] 292941 0
None
Universal Trial Number (UTN)
U1111-1202-4512
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Hospital readmissions 304828 0
Malnutrition 304829 0
Readmission prediction tools 304830 0
Medical inpatients 304831 0
Condition category
Condition code
Diet and Nutrition 304130 304130 0 0
Other diet and nutrition disorders
Public Health 304131 304131 0 0
Epidemiology

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
A retrospective observational study looking into predictors of hospital readmissions within six months of discharge in medical patients and whether nutrition status predicts hospital readmissions
Intervention code [1] 299174 0
Diagnosis / Prognosis
Intervention code [2] 299175 0
Early Detection / Screening
Comparator / control treatment
No control group
Control group
Uncontrolled

Outcomes
Primary outcome [1] 303451 0
This is an exploratory outcome to predict factors which can predict hospital readmissions.
Timepoint [1] 303451 0
Within seven days, thirty days and six months following hospital discharge.
Secondary outcome [1] 338955 0
Whether nutrition status, as determined by Malnutrition Universal Screening Tool (MUST) score, at time of admission improves prediction power of existing readmission prediction tools.
Timepoint [1] 338955 0
Within seven days, thirty days and six months of hospital discharge.

Eligibility
Key inclusion criteria
All medical inpatients admitted between 1st January 2016 to 31 st December 2016
Minimum age
18 Years
Maximum age
No limit
Gender
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
Surgical and Gynaecology patients and patients less than 18 years of age.

Study design
Purpose
Screening
Duration
Longitudinal
Selection
Defined population
Timing
Retrospective
Statistical methods / analysis
The variables will be assessed for normality using skewness and kurtosis test. Data will be presented as mean (SD) or median (IQR). Categorical variables will be expressed as frequency and percent and compared using Pearson’s x2 or Fisher’s exact test as appropriate.
Univariate logistic regression will be used to assess the association between nutritional status and unplanned readmission within 7 days, 30 days and 180 days post-discharge. Multivariate logistic regression analysis will be used to test the relationship between readmissions and nutrition status at different time points and will be adjusted for other variables-age, gender, Charlson index, principal diagnosis at presentation, number of medications at admission, length of hospital stay, number of medical emergency response team calls during index admission and total number of hours spent in intensive care unit (ICU). Variance inflation factor and tolerance values will be used to detect collinearity between variables included in the model. A link test will be used to confirm that the linear approach to model the outcome is correct. Model fit will be assessed using the Hosmer-Lemeshow goodness-of–fit test. Kaplan Meier survival curve will be plotted from time of discharge to the first endpoint (readmission) and Log rank test will be utilized used to compare survival proportions in the nourished and malnourished groups. A two-sided p<0.05 will be considered to indicate statistical significance. All analysis will be performed using STATA version 15.0 (StataCorp, College Station, Texas, USA).

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
SA
Recruitment hospital [1] 9083 0
Flinders Medical Centre - Bedford Park
Recruitment hospital [2] 9084 0
The Royal Adelaide Hospital - Adelaide
Recruitment postcode(s) [1] 17577 0
5000 - Adelaide
Recruitment postcode(s) [2] 17576 0
5042 - Bedford Park

Funding & Sponsors
Funding source category [1] 297567 0
Hospital
Name [1] 297567 0
Flinders Medical Centre
Address [1] 297567 0
Flinders Drive
Bedford Park
South Australia 5042
Country [1] 297567 0
Australia
Primary sponsor type
Hospital
Name
Flinders Medical Centre
Address
Flinders Drive
Bedford Park
South Australia 5042
Country
Australia
Secondary sponsor category [1] 296581 0
None
Name [1] 296581 0
Address [1] 296581 0
Country [1] 296581 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 298662 0
Southern Adelaide Clinical Human Research Ethics Committee
Ethics committee address [1] 298662 0
Flinders Medical Centre
Room 6A219
Flinders Drive
Bedford Park
South Australia 5042
Ethics committee country [1] 298662 0
Australia
Date submitted for ethics approval [1] 298662 0
Approval date [1] 298662 0
04/09/2017
Ethics approval number [1] 298662 0
216.17

Summary
Brief summary
Hospital readmissions are common and are risky for the patients and imposes additional financial burden on already constrained health care resources. Although numerous readmission predictor tools have been developed their ability to accurately identify patients at high risk of unplanned readmissions is only modest. Experts believe that this could be due to unknown variables, which needs to be identified. Majority of studies predicting hospital readmissions have so far been carried out in United States and only limited studies are available in Australia. Moreover, these studies are centred on 30-day readmission rate, as this is a commonly used benchmark to reimburse hospitals in US. The present study aims to study predictors, which can influence very early and late readmissions in medical inpatients and whether nutrition status as determined by Malnutrition universal screening tool (MUST) can be used as a predictor of hospital readmissions.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 77810 0
Dr Yogesh Sharma
Address 77810 0
Level 6
General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park
South Australia 5042
Country 77810 0
Australia
Phone 77810 0
+61882046694
Fax 77810 0
Email 77810 0
Yogesh.Sharma@sa.gov.au
Contact person for public queries
Name 77811 0
Dr Yogesh Sharma
Address 77811 0
Level 6
General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park
South Australia 5042
Country 77811 0
Australia
Phone 77811 0
+61882046694
Fax 77811 0
Email 77811 0
Yogesh.Sharma@sa.gov.au
Contact person for scientific queries
Name 77812 0
Dr Yogesh Sharma
Address 77812 0
Level 6
General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park
South Australia 5042
Country 77812 0
Australia
Phone 77812 0
+61882046694
Fax 77812 0
Email 77812 0
Yogesh.Sharma@sa.gov.au

No information has been provided regarding IPD availability
Summary results
No Results