The current results provide evidence in 5 important domains. First, our findings confirm the published evidence that conventional risk factors for long-term recurrence such as hypertension, diabetes mellitus, and smoking do not confer a risk for stroke over the short term (90 days).1–7,14
Scores based on predictors of the long-term risk such as the Stroke Prognosis Instrument II and the Essen Stroke Risk Score, therefore, offer only limited predictive value in the short term. Second, as also reported previously, etiologic stroke subtype6,7,16,17,29
and prior history of recent TIA/stroke17
are significant clinical predictors of 90-day recurrence risk after ischemic stroke. Nevertheless, the accuracy of predictions based on these predictors alone is modest (AUC = 0.70). Third, predictions by clinical variables can be significantly improved when imaging information is taken into account. The resultant score is called recurrence risk estimator at 90 days, or RRE-90. RRE-90 demonstrates good discrimination (AUC = 0.80) and calibration for predicting 90-day risk of recurrent stroke. Fourth, approximately 50% of recurrent strokes occurring in the first 90 days happen within the first 14 days. The RRE-90 provides good discrimination for predicting 14-day risk of recurrence (AUC = 0.80). Finally, the diagnostic performance of the RRE-90 is maintained after cross-validation and when applied to an independent cohort (AUC = 0.76), suggesting that it has promise when advanced to multicenter validation phase.
Various prior studies have also explored the relationship between imaging characteristics and stroke recurrence. However, while doing this, a significant proportion of such studies either failed to provide any imaging confirmation of recurrent stroke or used much less sensitive imaging methods such as computerized tomography.1,2,16,30
The remaining have chosen not to evaluate multiple imaging features in simultaneous context with each other1,16,17
or assessed a small number of outcome events for the number of independent variables in multivariable analyses.16,17
The current study undertakes a simultaneous assessment of all recognized imaging and clinical features associated with early recurrence. A major strength of the present study is the use of MRI for confirming the adjudication of recurrent stroke. Conventional definitions based on clinical diagnosis of a temporally distinct event often fail to differentiate a recurrent stroke from an event that is caused by progression or local complications (edema, seizures) of index stroke,31
hampering the specificity of diagnoses. Brain imaging allows objective assessment of clinical events as to whether a new event is in fact caused by recurrent infarct, and is routinely used for this in clinical practice. The choice of imaging in the current study was MRI because MRI, in particular DWI, is markedly superior to other imaging techniques in the evaluation of small ischemic lesions as well as in differentiating acute infarcts from chronic lesions.32,33
Although recent evidence suggests that routine use of MRI in acute stroke is justified,33
MRI suffers from limited accessibility and applicability. In order to ensure utility in circumstances in which MRI is not readily accessible, the RRE-90 automatically allows risk predictions using only the available clinical data (model A) yet predictions based on clinical data alone are less optimal than those from clinical and imaging-based model (model B).
Although etiologic stroke subtype is a significant predictor for short-term recurrence risk,6,7,16
this knowledge has thus far not been incorporated explicitly into predictive models. One reason for this is that identification of etiologic stroke subtype requires a comprehensive stroke evaluation and depends on the depth and speed of etiologic stroke investigation, which varies considerably across individual practices.34,35
It is therefore possible that a recurrent stroke may occur before an accurate subtyping is done. The major premise of the current tool is its ability to allow risk stratification with information available to physician immediately after initial stroke evaluation. Baseline imaging features of infarcts provide the prognostic information that relates to the underlying stroke mechanism. For instance, simultaneous infarcts in multiple circulations often indicate an unstable embolic source that is more proximal than carotid arteries. Infarct topography differentiates isolated cortical infarcts caused by small emboli from an unstable source from isolated subcortical or deep lesions caused by local small artery disease. Multiple acute infarcts often specify factors that simultaneously affect more than one artery such as proximal embolism and vasculitides. Other components of the RRE-90 such as recent history of TIA/stroke and multiple infarcts of different ages provide valuable temporal information that there is a continued risk of recurrent events. Because etiologic subtypes represent a combination of heterogeneous conditions with substantial variation in baseline individual risk, the continuity information plays a key role in discriminating whether or not the underlying stroke mechanism is unstable.36,37
Strengths of the present study include large sample size, imaging-based objective definition of outcome events, blind assessment of covariates to the outcome events, and Web-based availability of the final predictive model. Limitations include retrospective design, lack of external validation, incomplete follow-up, and single hospital setting where referral bias can potentially occur. Despite a rigorous derivation process, there were patients with missing follow-up information. This, however, unlikely caused a systematic bias toward selection of a particular risk population because most baseline predictors and distribution of RRE-90 scores were similar in cohorts with or without complete follow-up. Nevertheless, external validation is critical for the generalizability of our results. The number of recurrent events per predictor variable in model B was smaller than recommended,38
suggesting that overfitting might have occurred. Likewise, we cannot exclude the possibility of overfitting during the cross-validation procedure because coefficients were generated using only half of the dataset. Small number of recurrent events might have also caused missing of important differences in model performance in the validation dataset. Because the RRE-90 tool was constructed using only baseline clinical and imaging data, it does not take into account the intensity and choice of preventive stroke treatment. Differences in predictive performance of the algorithm may occur in external settings where timing and type of preventive stroke treatments substantially differ. The use of stringent univariate p
value threshold for eligibility into multivariable models limited our ability to test all potential predictors. Future studies with larger datasets could address whether incorporation of additional risk factors further improve predictions. Finally, the use of a liberal time window to obtain MRI (72 hours) as opposed to earlier time points may have caused more frequent detection of multiple acute infarcts on baseline MRI as a result of accumulation of ischemic lesions over time. Nevertheless, the time epoch analysis that revealed that the diagnostic performance of the model did not significantly change with respect to time from symptom onset to MRI strongly argues against this.
Risk stratification tools like RRE-90 offer utility in improving stroke care and outcome, because such tools have the potential to boost the development of stroke management algorithms that are based on individual patient characteristics. For instance, admission to specialized stroke centers with necessary infrastructure for prompt etiologic investigation and preventive treatment such as early carotid endarterectomy may offer greater benefit in high-risk patients whereas elective evaluation and management may be justified in low-risk patients in settings where resources are limited. Care at specialized centers can also provide an added benefit from the opportunity to administer treatment timely in the event of a recurrent stroke in high-risk patients. Stratification systems like RRE-90 could also serve as a tool for use in clinical trials testing new preventive strategies. Although 90-day recurrence is not a typical outcome measure in stroke prevention trials, there are several preventive treatments applied at the acute setting (anticoagulation, combination antiplatelets, endovascular procedures) with modest benefit but significant risk or cost that necessitate assessment in the short term for a more targeted approach. The RRE-90 tool can provide an excellent opportunity for this if validated externally. Prospective demonstration that the use of RRE-90 improves current practice and research in acute stroke remains to be determined.