The National Early Warning Score: Preceding Dynamics in the Score for Those Who Suffer an In-hospital Cardiac Arrest
To this date no clinical evaluation reports of the dynamics in the National Early Warning Score (NEWS) for those patients who suffer an in-hospital cardiac arrest, IHCA, exists. This process needs to be investigated in order to optimize the future care of these patients.
Research Questions H1: Patients that suffer an IHCA has had higher NEWS in the preceding 24 hours from the event compared to those who did not suffer an IHCA.
H2: The dynamics in the NEWS, differs between the patients that suffer an IHCA and those who do not in the preceding 24 hours from the event.
調査の概要
詳細な説明
Power:
A sample size of 300 patients in the control group and 150 patients in the group that suffered from an IHCA would generate a power estimate of 80 percent if the difference in the median is one point on the NEWS with a standard deviate of three points.
Analysis of the Research Data:
Categorical and nonparametric data will be presented in median (25-75 percentiles).
A hypothesis testing will be performed where the documented NEWS will be categorized into low-, medium- and high-risk and divided into different timespans. The timespans will be 0-6 h, 6-12 h, 12-18 and 18-24 h preceding the IHCA. In case of multiple NEWS measurements within each timespan, the worst NEWS measurement will be chosen. Each timespan during the 24 hours will not be treated as repeated measures and will be tested by the Chi square test. This test is chosen because the data is categorical. Another hypothesis test where all the NEWS measurements will be included and each documented NEWS on the same patient will be treated as repeated measures. A binary logistic regression analysis will be performed using Generalized Estimating Equations (GEE) and modelled to fit.
In order to select the covariates that is to be included in the regression analysis a non-parametric test including all the parameters in the NEWS will be executed. The level of significance for this test will be set to p=0.2 2. Collinearity within the NEWS parameters that is to be included in the regression analysis will be tested. The level of collinearity that is accepted will be <+0,6 and >-0,6. A binomial logistic regression analysis will be executed with the selected parameters in the NEWS The outcome of the regression analysis will be presented as odds ratio (OR).
研究の種類
入学 (実際)
連絡先と場所
研究場所
-
-
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Kristianstad、スウェーデン
- Region Skåne
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-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
All patients ≥18 years of age admitted to the hospitals during a period of 12 months will be reviewed for eligibility
Exclusion Criteria:
-
研究計画
研究はどのように設計されていますか?
デザインの詳細
コホートと介入
グループ/コホート |
介入・治療 |
---|---|
Cases
150 patients that suffered an in-hospital cardiac arrest in a hospital ward.
|
NEWS
|
Controls
300 patients that did not suffer an in-hospital cardiac arrest but was treated in a hospital ward.
|
NEWS
|
この研究は何を測定していますか?
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
---|---|---|
Dynamics in the National Early Warning Score (NEWS) in the 24 hours preceding an in-hospital cardiac arrest.
時間枠:24 hours preceding an in-hospital cardiac arrest
|
All documented National Early Warning Scores (NEWS) on eligible patients admitted to a hospital ward will be collected.
The NEWS will be divided into different timespans in the 24 hours preceding the in-hospital cardiac arrest.
A control group of patients will also have their NEWS collected.
The NEWS of the control group and the cases will then be entered into the hypothesis testing.
The aim is to find some dynamics in the NEWS that separates the patients that suffers an in-hospital cardiac arrest from those who do not in the 24 hours preceding the event.
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24 hours preceding an in-hospital cardiac arrest
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協力者と研究者
スポンサー
捜査官
- 主任研究者:Karin Samuelson, Ass Professor、Region Skåne
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- RegionSkaneKrYHVOAnIVAMS2
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
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