Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
A nomogram to predict the probability of mortality after first-ever acute manifestations of cerebral small vessel disease. |
| Συγγραφείς: |
Cappellari, Manuel1 manuel.cappellari@aovr.veneto.it, Zivelonghi, Cecilia1, Turcato, Gianni2, Forlivesi, Stefano1, Micheletti, Nicola1, Tomelleri, Giampaolo1, Bovi, Paolo1, Bonetti, Bruno1 |
| Πηγή: |
Journal of the Neurological Sciences. Feb2018, Vol. 385, p92-95. 4p. |
| Θεματικοί όροι: |
*Nomography (Mathematics), *Mortality -- Mathematical models, *Cerebral small vessel diseases, *Creatinine, *Glucose |
| Περίληψη: |
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. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: |
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