A nomogram to predict the probability of mortality after first-ever acute manifestations of cerebral small vessel disease

Background and purpose: Symptomatic lacunar stroke (LS) and deep intracerebral hemorrhage (dICH) represent the acute manifestations of type 1 cerebral small vessel disease (cSVD). Recently, two studies showed that the risk factor profile of dICH differs from that associated with LS in subjects with biologically plausible cSVD; however, the prognostic predictors after acute manifestations are currently lacking. We aimed to develop a nomogram for individualized prediction of the mortality probability in a cohort of patients with a first-ever acute manifestation of biologically plausible cSVD.

Methods: We conducted a retrospective analysis of data collected from consecutive patients with acute symptomatic non-embolic LS or primary dICH. The outcome measure was 3-month mortality. Based on multivariate logistic model, the nomogram was generated.

Results: Of the 288 patients who entered into the study for biologically plausible cSVD, 131 (45%) experienced a LS and 157 (55%) a dICH. After multivariate logistic regression, 5 variables remained predictors of mortality to compose the nomogram: dICH (OR:11.36; p=0.001), severe presentation (OR:8.08; p<0.001), age (OR:1.08; p=0.001), glucose (OR:1.23; p=0.003) and creatinine (OR:1.01; p=0.024) at admission were predictors of mortality. The discriminative performance of nomogram assessed by using the area under the receiver operating characteristic curve (AUC-ROC) was 0.898. The model was internally validated by using bootstrap (1000 samples) with AUC-ROC of 0.895 and cross-validation (deleted-d method repeated 1000 times) with AUC-ROC of 0.895.

Conclusions: We developed the first nomogram for prediction of the mortality probability in a cohort of patients with a first-ever acute manifestation of biologically plausible cSVD.