ANZCTR - Registration

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Trial registered on ANZCTR

Registration number

ACTRN12620000177954

Ethics application status

Approved

Date submitted

11/01/2020

Date registered

17/02/2020

Date last updated

17/02/2020

Date data sharing statement initially provided

17/02/2020

Type of registration

Retrospectively registered

Titles & IDs

Public title

The costs of anaemia after major surgery

Scientific title

The impact of preoperative anaemia on hospital costs following major abdominal surgery

Secondary ID [1]

None

Universal Trial Number (UTN)

U111-1246-3429

Trial acronym

Linked study record

Health condition

Health condition(s) or problem(s) studied:

Anaemia

Major abdominal surgery

Condition category

Condition code

Blood

Anaemia

Surgery

Surgical techniques

Anaesthesiology

Anaesthetics

Intervention/exposure

Study type

Observational

Patient registry

False

Target follow-up duration

Target follow-up type

Description of intervention(s) / exposure

Outcome data from the financial costing records of patients undergoing major abdominal surgery at Austin Health will be collected for the time periods between July 2010 and June 2018. To more clearly appreciate the financial burden associated with preoperative anaemia, we will select four types of subspecialty surgeries, each of which being associated with significant morbidity. These surgeries will include:
• pancreaticoduodenectomy
• major colonic resection
• major rectal resections
• liver resection surgery

We will collect elective and emergent data from the above 4 surgeries using procedural ICD-10 codes
32003-01 Right hemicolectomy with anastomosis
32005-03 Laparoscopic extended right hemicolectomy with anastomosis
32003-03 Laparoscopic right hemicolectomy with anastomosis
32005-01 Extended right hemicolectomy with anastomosis
32004-01 Extended right hemicolectomy with formation of stoma
32000-03 Laparoscopic right hemicolectomy with formation of stoma
32004-03 Laparoscopic extended right hemicolectomy with formation of stoma
32000-01 Right hemicolectomy with formation of stoma
32006-00 Left hemicolectomy with anastomosis
32006-02 Laparoscopic left hemicolectomy with anastomosis
32006-03 Laparoscopic left hemicolectomy with formation of stoma
32006-01 Left hemicolectomy with formation of stoma
32009-00 Total colectomy with ileostomy
32012-01 Laparoscopic total colectomy with ileorectal anastomosis
32009-01 Laparoscopic total colectomy with ileostomy
32012-00 Total colectomy with ileorectal anastomosis
32004-02 Laparoscopic subtotal colectomy with formation of stoma
32005-02 Laparoscopic subtotal colectomy with anastomosis
32005-00 Subtotal colectomy with anastomosis
32004-00 Subtotal colectomy with formation of stoma
32000-02 Laparoscopic limited excision of large intestine with formation of stoma
32003-00 Limited excision of large intestine with anastomosis
32003-02 Laparoscopic limited excision of large intestine with anastomosis
32000-00 Limited excision of large intestine with formation of stoma
30414-00 Excision of lesion of liver
30415-00 Segmental resection of liver
30418-00 Lobectomy of liver
30421-00 Trisegmental resection of liver
30584-00: Pancreaticoduodenectomy with formation of stoma
32024-00 High anterior resection of rectum
32025-00 Low anterior resection of rectum
32026-00 Ultra low anterior resection of rectum
32028-00 Ultra low anterior resection of rectum with hand sutured coloanal anastomosis
32030-00 Rectosigmoidectomy with formation of stoma
32030-01 Laparoscopic rectosigmoidectomy with formation of stoma
32039-00 Abdominoperineal proctectomy
32047-00 Perineal proctectomy
32051-00 Total proctocolectomy with ileo-anal anastomosis
32051-01 Total proctocolectomy with ileo-anal anastomosis and formation of temporary ileostomy
32112-00 Perineal rectosigmoidectomy
92208-00 Anterior resection of rectum, level unspecified

Patients records will reviewed for up for 30 days following discharge from the index admission.

Intervention code [1]

Not applicable

Comparator / control treatment

No control group. Comparisons between the groups are not being made. This study is looking at the relationship between anaemia and major abdominal surgery

Control group

Uncontrolled

Outcomes

Primary outcome [1]

The primary outcome will be hospital costs of patients who have preoperative anaemia. This will be determined from the hospital medical records

Timepoint [1]

Costs will be calculated from day of surgery to hospital discharge. Readmission costs will be considered within 30 days of discharge from the index admission.
Data will be collected from the patients' hospital medical records.

Primary outcome [2]

The primary outcome will be hospital costs of patients who do not have preoperative anaemia. This will be determined from the hospital medical records

Timepoint [2]

Costs will be calculated from day of surgery to hospital discharge. Readmission costs will be considered within 30 days of discharge from the index admission.

Secondary outcome [1]

The development of postoperative complications. Data will be collected from the patients' hospital medical records.

Timepoint [1]

These will be collected from day of surgery to hospital discharge. Data will be collected from the patients' hospital medical records.

Secondary outcome [2]

The severity of complications as graded by the Clavien Dindo classification. Data will be collected from the patients' hospital medical records.

Timepoint [2]

These will be collected from day of surgery to hospital discharge.

Secondary outcome [3]

Requirement of allogenic red blood cell (RBC) transfusion and number of RBC transfused. Data will be collected from the patients' hospital medical records.

Timepoint [3]

These will be collected from day of surgery to hospital discharge.

Secondary outcome [4]

Number of patients with a postoperative ICU admission. Data will be collected from the patients' hospital medical records.

Timepoint [4]

These will be collected from completion of surgery to hospital discharge.

Secondary outcome [5]

Length of hospital stay. Data will be collected from the patients' hospital medical records.

Timepoint [5]

These will be collected from completion of surgery to hospital discharge.

Secondary outcome [6]

Readmission within 30 days after discharge. Data will be collected from the patients' hospital medical records.

Timepoint [6]

These will be collected from completion of surgery to within 30 days after hospital discharge.

Secondary outcome [7]

Costs incurred during readmission. Data will be collected from databases from the hospital's Business Intelligence Unit.

Timepoint [7]

These will be collected from the date of readmission to hospital until the date of hospital discharge.

Eligibility

Key inclusion criteria

1. Adult patients (>18 years of age) undergoing one of four types of major abdominal surgeries at Austin Health: Colon resections, Rectal resections, Pancreaticodoudenectomy and Liver resections. Both emergent and elective patients will be included.
2. We will only include patients who underwent surgery of greater than two hours duration and who required at least one overnight hospital stay.

Minimum age

18 Years

Maximum age

No limit

Sex

Both males and females

Can healthy volunteers participate?

Key exclusion criteria

Pregnancy

Study design

Purpose

Natural history

Duration

Longitudinal

Selection

Defined population

Timing

Retrospective

Statistical methods / analysis

For statistical analysis, we will use IBM SPSS Statistics for Windows (version 23.0, IBM Corp., Armonk, NY, 2015) and R software 3.5.2 (R Development Core Team, Vienna, Austria, 2018). All collected data will be coded with numerical values, and names of variables will be encrypted to blind the variables’ characteristics to the statistician. Data will be presented as mean ± standard deviation, median (1st ~ 3rd quartiles), or the number of cases (percentile) for descriptive statistics. Estimated values will be described with 95% confidence intervals. Statistical results will be presented with P-values and corresponding effect sizes. Any P-value below 0.05 will considered as statistically significant, based on the null hypothesis significance testing. The number of effects will evaluated with the estimated effect sizes.

We anticipate data from ~1300 patients to be collected.

Prior to statistical analysis, normality will assessed for continuous variables using the Shapiro-Wilk test, a visual check of the normal Q-Q plot, and frequency histograms. For skewed distributions, transformation using logarithmic or exponential scales will be applied, and normality will be re-evaluated using the normal Q-Q plot. If normality is violated post-transformation, non-parametric statistical methods will be applied for that variable. Extreme values will be managed by applying standard statistical methods and then compared to the original values from the data source. If any extreme value cannot be reconciled by interrogating the clinical notes and context of the value, they will be replaced with the Winsorization method.

Variables with a missing rate of greater than 5% will be identified and evaluated to determine whether the missing values occurred at random. In such cases, imputation will be applied using the univariate imputation method of classification and regression trees, using the “mice package”. Maximal iteration will be set at 250, and the number of multiple imputations will be determined appropriately. We will assess the imputed values with an over-imputation diagnostic plot. For the missing analysis of categorical data, the multiple correspondence analysis will be applied with “missMDA package” in the “R” system. Otherwise, statistical analysis will performed as a complete case analysis. Parametric statistical methods will be used only for the continuous, numerical variables that satisfied the normality assumption; otherwise, non-parametric methods will be applied. For parametric, statistical purposes, the homogeneity of variance assumption will be evaluated if required.

For crude estimation of relationship between [Hb]c and hospital costs, curve estimation based on the least square method will be evaluated for linear, quadratic, and cubic models. According to the curve-fit results and physiologically accepted criteria, we will divided [Hb]c into 4 categories; <9.0 g/dL, 9.0 - 13.0 g/dL, 13.0 - 15.0 g/dL, and >15.0 g/dL.

To evaluate the relationship between hospital costs and the patient’s status, correlation analysis and multiple log-linear regression analysis will be used. A stepwise selection method will be applied to determine the relevant regression coefficient for this modelling. For regression, all categorical variables with more than three levels will be transformed into dummy variables. Residuals will be evaluated with the Durbin-Watson statistic test and standardised residual plots, including all partial plots. The variance inflation factor (VIF) will be used to assess collinearity, and Pearson product-moment correlation analysis will be used to evaluate the independency between selected variables. A constant will be included during estimation, in order to compensate for the unknown effect. To enhance the robustness of estimates, bootstrapping will applied to the final regression model, with 1000 samples and the simple sampling method.

To evaluate the effects of [Hb]c on the variables directly related to hospital costs, multivariate general linear modelling will be used. With Pearson’s correlation analysis, the assumption of independence will be validated, and the multivariate normal distribution assumption will be tested using the “mshapiro.test” function in the “mvnormtest package”, in the R system. The Box test will also used for testing homogeneity of covariance matrices. Data for multivariate, general linear modelling will be trimmed using propensity score matching. This will be performed in order to adjust for other variables that may be indicative of patient status, given that they could affect the value of variables directly related to hospital costs. For propensity score matching, the nearest neighbor matching without the caliper method will be applied. Variables selected in the multiple linear regression model will be used for estimating the propensity score. Matched quality will be assessed using standardized differences with a criteria of 0.1, a propensity score distribution graph, and standardized differences density plot check.

Recruitment

Recruitment status

Recruiting

Date of first participant enrolment

Anticipated

Actual

30/01/2020

Date of last participant enrolment

Anticipated

22/02/2020

Actual

Date of last data collection

Anticipated

21/03/2020

Actual

Sample size

Target

1300

Accrual to date

800

Final

Recruitment in Australia

Recruitment state(s)

VIC

Recruitment hospital [1]

Austin Health - Austin Hospital - Heidelberg

Recruitment postcode(s) [1]

3084 - Heidelberg

Funding & Sponsors

Funding source category [1]

Hospital

Name [1]

Austin Health

Address [1]

Department of Anaesthesia, Austin Health, 145 Studley Road, Heidelberg VIC, 3084

Country [1]

Australia

Primary sponsor type

Hospital

Name

Austin Health

Address

Department of Anaesthesia, Austin Health, 145 Studley Road, Heidelberg VIC, 3084

Country

Australia

Secondary sponsor category [1]

None

Name [1]

Address [1]

Country [1]

Ethics approval

Ethics application status

Approved

Ethics committee name [1]

Austin Health Human Research Ethics Committee

Ethics committee address [1]

Level 8, Harold Stokes Building, 145 Studley Road, Heidelberg, Victoria, 3084

Ethics committee country [1]

Australia

Date submitted for ethics approval [1]

13/01/2020

Approval date [1]

20/01/2020

Ethics approval number [1]

Audit/20/Austin/04

Summary

Brief summary

Preoperative anaemia is independently associated with an increased risk of postoperative morbidity and mortality and greater health care expenditure. The purpose of this study is to determine the costs associated with preoperative anaemia in patients undergoing major abdominal surgery.

Who is it for?
Eligible patients will include adult patients who underwent colonic, rectal, pancreatic or liver resections at the Austin Hospital between July 2010 and June 2018. All data will be retrospectively collected.

Study details:
Costs from the entire inpatients hospital admission will be collected from Austin Health's Business Unit. We will evaluate the association of preoperative haemoglobin levels and hospital costs.

It is hoped that this study will:
1) Quantify the costs implicated by anaemia and the impact of anaemia on pharmacological costs, medical costs, operative costs, intensive care unit costs and ward costs.

2) Quantify the impact of anaemia on costs within the following patient cohorts:
a. Emergency and elective procedures
b. Laparoscopic, open and combined procedures
c. Malignant and non-malignant diagnoses

3) Identify key patient and perioperative variables associated with increased costs and adverse patient outcomes to ascertain areas for improvement allowing the development of evidence-based guidelines with the ultimate goal of improving patient outcomes and efficiency of our health services.

Trial website

Trial related presentations / publications

Public notes

Contacts

Principal investigator

Name

A/Prof Laurence Weinberg

Address

Department of Anaesthesia, Austin Health, 145 Studley Road, Heidelberg, VIC 3084

Country

Australia

Phone

+61 3 94965000

Fax

+61 3 94596421

[email protected]

Contact person for public queries

Name

A/Prof Laurence Weinberg

Address

Department of Anaesthesia, Austin Health, 145 Studley Road, Heidelberg, VIC 3084

Country

Australia

Phone

+61 3 94965000

Fax

+61 3 94596421

[email protected]

Contact person for scientific queries

Name

A/Prof Laurence Weinberg

Address

Department of Anaesthesia, Austin Health, 145 Studley Road, Heidelberg, VIC 3084

Country

Australia

Phone

+61 3 94965000

Fax

+61 3 94596421

[email protected]

Data sharing statement

Will individual participant data (IPD) for this trial be available (including data dictionaries)?

No/undecided IPD sharing reason/comment

As this is an observational study, patients have not provided informed consent for their data to be shared.

What supporting documents are/will be available?

Doc. No.	Type	Citation	Link	Email	Other Details	Attachment
6381	Statistical analysis plan			[email protected]		379040-(Uploaded-11-01-2020-14-54-08)-Study-related document.pdf
6829	Ethical approval			[email protected]		379040-(Uploaded-09-02-2020-19-54-58)-Study-related document.pdf

Results publications and other study-related documents

Documents added manually

No documents have been uploaded by study researchers.

Documents added automatically

Source	Title	Year of Publication	DOI
Embase	Associations between preoperative anaemia and hospital costs following major abdominal surgery: Cohort study.	2021	https://dx.doi.org/10.1093/bjsopen/zraa070

N.B. These documents automatically identified may not have been verified by the study sponsor.

Trial Review

Documents added manually

Documents added automatically