Evaluation of Degree of Dependency After Stroke.

Evaluation of Degree of Dependency After Stroke: a Challenge for Health and Social Care Planning.

Understanding the risk of dependence and its severity before hospital discharge for stroke is important for health and social care planning as instrument to prioritize people where the assistance is more appropriate in a context o limited resources and avoid the gap across the health care continuum. The goal is to conduct an assessment, which will identify the patient's needs. In doing so, the team, along with family may effectively coordinate, plan and implement any steps necessary to ensure a safe and healthy environment for the patient.

The main study's objective is to asses which factors are associated with outcome of dependence after stroke and propose a suitable instrument for identifying patients in higher risk for needing formal care from health and/or social care providers.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

Study Design It is a prospective, longitudinal, multicenter and community study, with a 2-year follow-up period (from 01.01.2017 to 31.12.2018) of patients who suffered stroke in the Community of Catalonia, Terres De l'Ebre County from the population-based register through specific ICD-9 diagnostic and procedure codes.

Data collection methods Probabilistic sample: all consecutive stroke cases up to reaching the previously calculated sample size. Study will be carried out according the common clinical practice.

Primary outcome: The primary outcome was dependence occurring within the 2-year follow-up after the stroke episode. Assessment of the patients' degree of dependency is essential in determining nursing care needs, planning nursing intervention, helping increase patients' abilities, and creating proper discharge plans. The European Council [12,13] defines dependence as the state in which people, due to causes linked to the lack or loss of physical, psychological, or intellectual autonomy, are in need of assistance and/or significant help to carry out common activities of daily life. In primary care, the nurses in charge are trained of data collection. This situation needs of formal care provided by health or/and social workers, private or public.

Secondary outcomes:

  1. Propose a suitable instrument with predictive power propose for identifying patients in higher risk for needing formal care from health and/or social care providers.
  2. Measure the time elapsed from the hospital discharge to first contact with health primary care services, with social services, application for recognition of dependence degree, and get effective certification.
  3. Know the newly diagnosed cases of dependence after stroke.

Statistical analysis All statistical tests will be performed as intention-to-treat. Prognostic factors' estimates will be adjusted by mixed-effects regression models. Possible confounding or effect-modifying factors will be taken into account. Predictions of dependence risk were based on Cox proportional-hazard regression models. Data analysis information extracted included the adjusted risk estimates and 95% confidence intervals (CI) and all statistical tests were two sided at the 5% significance level.

All potential predictors were considered in a multivariate logistic regression, and a backward step selection procedure was carried out to pick the variables that composed the best model. Subsequently, design of a predictive model of multivariate Cox regression analysis was utilized to define the weight of each of the pathologies in the dependence. To assign the weight according to the hazard ratio (HR) value, we took into account only those with a HR ≥1.2 in the multivariate model approximating the value of HR to the nearest whole number:

  • HR between 1.20 and 1.49 scored a 1.
  • HR between 1.50 and 2.49 was a 2.
  • HR between 2.50 and 3.49 received 3, and so on. The final score for each patient will be made up of the sum of their scores. We will use ROC curves and the AUC to assess the ability of this tool to stratify patients and predict dependence. To ensure internal validity, we will perform a ten-fold cross-validated multivariate regularized logistic regression to predict dependence status based on all other variables. We will plot the receiver operating characteristic (ROC) curves and compute the area under curve (AUC) to assess the prediction power of the models. In a next phase, there will be a prospective study of validation in the cohort of patients with an episode of stroke along 2018 year.

Study Type

Observational

Enrollment (Actual)

230

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Tarragona
      • Tortosa, Tarragona, Spain, 43500
        • Jose Luis Clua-Espuny

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

It is a prospective, longitudinal, multicenter and community study, with a 2-year follow-up period (from 01.01.2017 to 31.12.2018) of patients who suffered stroke in the Community of Catalonia, Terres De l'Ebre County from the population-based register through specific ICD-9 diagnostic and procedure codes.

The study variables were collected while the patients remained in the stroke units (visit 1) and at the follow-up visits at 6 months (visit 2), 12 months (visit 3), 18 months (visit 4) and 24 months (study ending). Predictor variables were considered if they were viewed as commonly measured and available in primary care and had potential evidence of an association with dependence risk.

Description

Inclusion Criteria:

  • Patients who has suffered acute stroke, with residence at the county for last 5 years, at least and registered clinical history in anyone health center of the county, primary care or hospital; and availability of informed consent document.

Exclusion Criteria:

  • No availability or accessibility to enough information to complete the study: clinical report in primary care, hospital or social services.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
patients with Dependence degree
Dependence degree already certificated by Dependence Law: It is calculated by accepting an expected proportion of 40% patients with dependence, with a precision 6.5% and confidence level of 95%, obtaining a N= 200 patients. Assuming a 15% of loses, we estimate we will need N=230 to be followed. This sample size would enable us to construct logistic regression models including simultaneously up to 5 predictive factors to assess the relationship between each of the independent variables and the occurrence of dependency.
The European Council defines dependence as the state in which people, due to causes linked to the lack or loss of physical, psychological, or intellectual autonomy, are in need of assistance and/or significant help to carry out common activities of daily life. In primary care, the nurses in charge are trained of data collection. This situation needs of formal care provided by health or/and social workers, private or public.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Dependence after the stroke episode
Time Frame: 2-year
the records will be checked and the patients were contacted and/or by interviewing the person responsible to provide care.
2-year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Collaborators

Investigators

  • Study Director: JOSE L CLUA-ESPUNY, PhD, IDIAP Jordi Gol
  • Study Director: CONCEPCION CARRATALA-MUNUERA, PhD, Universidad Miguel Hernandez de Elche

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2017

Primary Completion (Actual)

January 1, 2018

Study Completion (Anticipated)

December 31, 2018

Study Registration Dates

First Submitted

February 25, 2018

First Submitted That Met QC Criteria

February 28, 2018

First Posted (Actual)

March 1, 2018

Study Record Updates

Last Update Posted (Actual)

March 1, 2018

Last Update Submitted That Met QC Criteria

February 28, 2018

Last Verified

February 1, 2018

More Information

Terms related to this study

Other Study ID Numbers

  • P17/198 IDIAP Jordi Gol
  • PROJECTE PERIS 2016 (Other Grant/Funding Number: PERIS (2016-2020).)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

The data that support the findings of this study are available from the corresponding author on reasonable request.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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