Postoperative Intensive Care Surveillance

NCT ID: NCT02894788

Last Updated: 2016-09-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

2498 participants

Study Classification

OBSERVATIONAL

Study Start Date

2015-03-31

Study Completion Date

2015-09-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

Several score systems were created to stratify perioperative risk and predict mortality. The study rises from the needing of a rapid and simple system to identify the patient worthy of Postoperative Intensive Surveillance. In the first phase Authors retrospectively investigated on patients underwent to elective surgery searching for determining factors (DFs) for postoperative ICU admission. Later, Researchers prospectively studied how DFs could predict the admission in ICU of consecutive patients scheduled for elective surgery during a three-months period and created an index, named PoIS (Post-operative Intensive Surveillance), based on the results of this analysis. Authors used surgical invasiveness (SI), Diabetes Mellitus (DM), Myocardiopathy (MCP), Cerebrovascular Disease (CVD), Body Mass Index (BMI), age, serum creatinine level (sCr), Tiffenau Index (TI) and male sex for the development of the original model. Authors classified SI from G1 (lowest) to G5 (highest).

The results show that the power of prediction of postoperative morbidity of PoIS and POSSUM resulted coincident and better than the American Society of Anesthesiology scoring system.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Post-operative Adhesion(s)

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

CASE_CONTROL

Study Time Perspective

RETROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

ICU

patients postoperatively admitted to ICU

ICU admission

Intervention Type OTHER

no ICU

patients who didn't required ICU admission postoperatively

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

ICU admission

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* elective surgery

Exclusion Criteria

* multiple surgery
* age less than 18
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Istituto Clinico Humanitas

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Responsibility Role SPONSOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Humanitas Research Hospital - Dept. Anesthesia and Intensive Care Unit

Rozzano, Milano, Italy

Site Status

Countries

Review the countries where the study has at least one active or historical site.

Italy

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

PoIS

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.