UMIN-CTR Clinical Trial

Public title

Does the scoring patient complexity with COMPRI predict the length of hospital stay? A multicenter study in Japan

Acronym

Does the scoring patient complexity with COMPRI predict the length of hospital stay? A multicenter study in Japan

Scientific Title

Does the scoring patient complexity with COMPRI predict the length of hospital stay? A multicenter study in Japan

Scientific Title:Acronym

Does the scoring patient complexity with COMPRI predict the length of hospital stay? A multicenter study in Japan

Region

Japan

Condition

Not applicable

Classification by specialty

Medicine in general

Adult

Classification by malignancy

Others

Genomic information

NO

Narrative objectives1

We evaluate the complexity using COMPRI for newly hospitalized patients in five comprehensive internal department wards in the prefecture and analyze the relationship between score and hospitalization period. We also analyze factors contributing to hospitalization retrospectively and clarify the relationship with COMPRI score.

Basic objectives2

Others

Basic objectives -Others

Case-control study

Trial characteristics_1

Confirmatory

Trial characteristics_2

Developmental phase

Primary outcomes

length of hospital stay

Key secondary outcomes

Study type

Observational

Basic design

Randomization

Randomization unit

Blinding

Control

Stratification

Dynamic allocation

Institution consideration

Blocking

Concealment

No. of arms

Purpose of intervention

Type of intervention

Interventions/Control_1

Interventions/Control_2

Interventions/Control_3

Interventions/Control_4

Interventions/Control_5

Interventions/Control_6

Interventions/Control_7

Interventions/Control_8

Interventions/Control_9

Interventions/Control_10

Age-lower limit

20

years-old

<=

Age-upper limit

Not applicable

Gender

Male and Female

Key inclusion criteria

We recruit cases admitted to general department of five facilities in Chiba prefecture.

Key exclusion criteria

We exclude patients who have been hospitalized or rehospitalized for other departments.

Target sample size

150

Name of lead principal investigator

1st name	Daiki
Middle name
Last name	Yokokawa

Organization

Chiba University Hospital

Division name

Department of General Medicine

Zip code

260-8677

Address

1-8-1, Inohana, Chuo-ku, Chiba city, Chiba pref., Japan

TEL

0432227171

Email

dyokokawa6@gmail.com

Name of contact person

1st name	Daiki
Middle name
Last name	Yokokawa

Organization

Chiba University Hospital

Division name

Department of General Medicine

Zip code

260-8677

Address

1-8-1, Inohana, Chuo-ku, Chiba city, Chiba pref., Japan

TEL

0432227171

Homepage URL

Email

dyokokawa6@gmail.com

Institute

Chiba University

Institute

Department

Personal name

Organization

Japan Primary Care Association

Organization

Division

Category of Funding Organization

Other

Nationality of Funding Organization

Co-sponsor

Name of secondary funder(s)

Organization

Chiba University Hospital

Address

1-8-1, Inohana, Chuo-ku, Chiba city, Chiba pref., Japan

Tel

0432227171

Email

0432227171

Secondary IDs

NO

Study ID_1

Org. issuing International ID_1

Study ID_2

Org. issuing International ID_2

IND to MHLW

Institutions

Date of disclosure of the study information

2018

Year

05

Month

31

Day

URL releasing protocol

https://bmjopen.bmj.com/content/12/4/e051891

Publication of results

Unpublished

URL related to results and publications

https://bmjopen.bmj.com/content/12/4/e051891

Number of participants that the trial has enrolled

33

Results

The 17 patients allocated to the long-term hospitalisation group (hospitalised >=14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses.
A logistic regression model (COMPRI >=6) showed better predictive accuracy compared with a multiple logistic regression model (5-fold cross-validation, AUC of 0.87 vs 0.78). The OR of a patient with a COMPRI of >=6 joining the long-term hospitalisation group was 4.25(1.43-12.63).

Results date posted

2022

Year

05

Month

17

Day

Results Delayed

Results Delay Reason

Date of the first journal publication of results

Baseline Characteristics

From November 2017 to December 2019, we recruited newly hospitalised patients from three general internal medicine wards in Chiba Prefecture, Japan. We included hospitals in different cities that have general medicine outpatient and ward facilities and that agreed to participate in the study. There were no age criteria for participants. We excluded any patients who were being re-hospitalised after being discharged less than 2 weeks previously. Participants with missing data were also excluded.

Participant flow

The patients' COMPRI scores were measured at the time of their hospital admission. COMPRI score measurements require subjective assessment by both a physician and a nurse. In this study, when physicians determined that a patient required hospitalisation, they input this information on the form, and the nurses who were in charge of outpatients then provided scores for the patient. Patients, or their family members, were also interviewed at the time of admission to obtain further details regarding the patients' medical history.

For each patient, age, sex, co-existence of physical illnesses, co-existence of psychiatric illnesses, the responding physician's years of experience (hereafter, 'physician experience') and whether the hospitalisation site was a tertiary care hospital were recorded. The physical illnesses considered included chronic lung disease, diabetes, heart disease, hypertension, rheumatic disease, neurological disorders, malignant tumours and disabilities.　Meanwhile, the psychiatric illnesses considered included delirium, dementia, depression, anxiety disorders, schizophrenia, drug/alcohol use disorders and other psychiatric illnesses. LOS was defined as the number of days from the date of admission to either the date of discharge or transfer; for patients who died, their date of death was considered to represent their date of discharge.

Adverse events

No adverse events were identified.

Outcome measures

The primary outcome was LOS. Generally, LOS varies depending on the primary disease and, as a result, there is no clear standard, even in Japan, regarding the cut-off point for prolonged LOS. However, multiple studies have set an LOS of more than 14 days as a cut-off. Our study also followed this standard and allocated patients with an LOS of 14 days or more to a 'long-term hospitalisation group' and patients with an LOS of fewer than 14 days to a 'short-term hospitalisation group.' We then compared the two groups in regard to COMPRI score, age and physician experience (using the Mann-Whitney U test), sex, co-existence of physical illnesses and co-existence of psychiatric illnesses (using chi-2 test/Fisher's exact test).

Sample size estimates were conducted with reference to previous studies. To perform the Mann-Whitney U test for the primary outcome of LOS, the CI was set at 95%, the detectability at 0.8, the median COMPRI score of the long-term hospitalisation group at 9.5, the median score value of the short-term hospitalisation group at 6.0 and the SD at 4.0. Meanwhile, a target sample size of 24 patients was assumed.

Next, two prediction models were designed. Model A was a logistic regression model based only on the COMPRI score, and model B was a multiple logistic regression model that featured age, sex, co-existence of physical illnesses, co-existence of mental illnesses and physician experience as explanatory variables. These prediction models were used to conduct an ROC-AUC accuracy comparison based on stratified K-fold cross-validation. When identifying the constituent patients for the two groups, cut-offs for each variable were determined based on the ROC analyses, and these were set as explanatory variables when creating the variables for model B. Age older than 75 years (which is a defining characteristic of the target patients of Japan's late-stage older adult healthcare system) was set as the explanatory variable.

All statistical analyses were conducted using Python (3.6.8) and scikit-learn (0.22.1), which is a module for machine learning in Python. For all analyses, the significance level was set at <5%.

Plan to share IPD

IPD sharing Plan description

Recruitment status

Completed

Date of protocol fixation

2017

Year

05

Month

01

Day

Date of IRB

2017

Year

10

Month

16

Day

Anticipated trial start date

2017

Year

10

Month

01

Day

Last follow-up date

2019

Year

03

Month

31

Day

Date of closure to data entry

Date trial data considered complete

2020

Year

11

Month

20

Day

Date analysis concluded

Other related information

1. Background
COMPRI is a measure of patient complexity and was developed to evaluate and screen the complexity required for treatment planning of inpatients. Validity concerning usefulness in Japan is insufficient and none has been made as a multicenter collaborative research.
2. Purpose
COMPRI evaluates the complexity of newly hospitalized patients in five comprehensive internal department wards in the prefecture and analyzes the relationship between the scores and hospitalization period. We also analyze factors contributing to hospitalization retrospectively and clarify the relationship with COMPRI score.
3. Research design and observation period
Measure the COMPRI score of the inpatient. As a case-control study after discharge, we analyze the relationship between COMPRI score and extension of hospitalization period, and COMPRI and other factors with 14 days of hospitalization cutoff.
4. Setting
We recruit cases admitted to general department of five facilities in Chiba prefecture. We excluded cases that were rehospitalized or hospitalized for other departments. From the previous study, 150 cases was recruited(r = 0.3, alpha 0.01 (two-sided, event occurrence: non occurrence = 1: 2, explanatory variable 5).
5. Interventions or factors
Factors include COMPRI total score (cutoff is 7points), age (cutoff is 65 years old), presence or absence of coexistence of chronic disease, psychiatric disorders, social worker intervention.
6. Main outcome indicator
The hospitalization period at the general internal ward is taken as the main outcome.
7. Statistical analysis method
Perform ROC analysis and Pearson product moment correlation coefficient test for total score and hospital stay using SPSS. We also analyze the relation to the hospitalization period for explanatory variables by multiple logistic regression analysis.

Registered date

2018

Year

05

Month

25

Day

Last modified on

2022

Year

05

Month

17

Day

Link to view the page

Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000037308