A Predictive Model to Identify High Risk of Cardiac Arrest or In-Hospital Mortality among Patients with Suspected Acute Coronary Syndromes: An IMMEDIATE Trial Sub-study.
Ray, Madhab.
2014
-
Abstract: Background:
Intravenous glucose insulin potassium (GIK) solution has been shown to have a protective
role in preventing myocardial damage from ischemic insult in laboratory animals. Its
effectiveness in human subjects has long been debated and clinical studies have produced
divergent results. The recently completed IMMEDIATE Trial showed benefit of GIK in the
composite outcome of ca... read morerdiac arrest or in-hospital mortality in patients with suspected
acute coronary syndrome (ACS). To aid the identification of patients most likely to
experience this benefit, this ancillary analysis of the IMMEDIATE Trial was performed to
develop a predictive model that could facilitate recognition of these high-risk patients
for prioritization for GIK therapy. Methods: Multivariable logistic regression was used
to develop a predictive model for the composite endpoint cardiac arrest or in-hospital
mortality using patients of the control arm of the IMMEDIATE Trial, i.e., patients not
treated with GIK. Tertiles of predicted risk categories then were created for all
patients in the trial (treated and not treated) using the developed predictive model and
risk categories were tested for interactions with GIK on the outcome. Results: Four
variables were significantly associated with the study endpoint: advanced age, low
systolic blood pressure, ST elevation in the presenting electrocardiogram (ECG), and
duration of symptoms from the onset. The model developed using these variables predicted
cardiac arrest or death with good performance, corresponding to a C statistic of 0.75.
Calibration of the predictive instrument for observed and predicted rates of cardiac
arrest or in-hospital mortality was very good. No significant interaction on the odds
ratio scale with GIK was identified for any candidate variables or the predicted risk
categories in the study population. However, based on constant odds ratio (OR) across
the risk categories there was an absolute risk reduction of 8.6% with GIK in high-risk
tertile with the corresponding number needed to treat (NNT) of 12 to prevent one cardiac
arrest or in-hospital mortality. The corresponding figures for the low-risk tertile were
0.8% and 125 respectively. Thus there appears to be a pronounced benefit of GIK in the
high-risk group compared to the low-risk group when absolute risk reduction was used to
measure the effect of treatment with GIK compared to placebo. Conclusions: A
multivariable predictive model was developed that identifies patients at high risk of
cardiac arrest or death. When classified by the predictive model, the greatest benefit
of GIK is demonstrated in the high-risk
tertile.
Thesis (M.S.)--Tufts University, 2014.
Submitted to the Dept. of Clinical & Translational Science.
Advisor: Harry Selker.
Committee: Robin Ruthazer, Joni Beshansky, and David Kent.
Keyword: Health sciences.read less - ID:
- 0v838b682
- Component ID:
- tufts:20518
- To Cite:
- DCA Citation Guide EndNote
