Mutation analysis of the GLA gene in Chinese patients with intracerebral hemorrhage

Prevalence of Fabry disease and GLA variants in young patients with acute stroke: The challenge to widen the screening. The Fabry-Stroke Italian Registry

BACKGROUND

Fabry disease (FD) is a treatable X-linked lysosomal storage disorder caused by GLA gene variants leading to alpha-galactosidase A deficiency. FD is a rare cause of stroke, and it is still controversial whether in stroke patients FD should be searched from the beginning or at the end of the diagnostic workup (in cryptogenic strokes).

METHODS

Fabry-Stroke Italian Registry is a prospective, multicentric screening involving 33 stroke units. FD was sought by measuring α-galactosidase A activity (males) and by genetic tests (males with reduced enzyme activity and females) in patients aged 18-60 years hospitalized for TIA, ischemic stroke, or intracerebral hemorrhage. We diagnosed FD in patients with 1) already known pathogenic GLA variants; 2) novel GLA variants if additional clinical, laboratory, or family-derived criteria were present.

RESULTS

Out of 1906 patients, we found a GLA variant in 15 (0.79%; 95%CI 0.44-1.29) with a certain FD diagnosis in 3 (0.16%; 95%CI 0.03-0.46) patients, none of whom had hemorrhage. We identified 1 novel pathogenic GLA variant. Ischemic stroke etiologies in carriers of GLA variants were: cardioaortic embolism (33%), small artery occlusion (27%), other causes (20%), and undetermined (20%). Mild severity, recurrence, previous TIA, acroparesthesias, hearing loss, and small artery occlusion were predictors of GLA variant.

CONCLUSION

In this large multicenter cohort the frequency of FD and GLA variants was consistent with previous reports. Limiting the screening for GLA variants to patients with cryptogenic stroke may miss up to 80% of diagnoses. Some easily recognizable clinical features could help select patients for FD screening.

Development and validation of a nomogram to predict the 30-day mortality risk of patients with intracerebral hemorrhage

Background

Intracerebral hemorrhage (ICH) is a stroke syndrome with an unfavorable prognosis. Currently, there is no comprehensive clinical indicator for mortality prediction of ICH patients. The purpose of our study was to construct and evaluate a nomogram for predicting the 30-day mortality risk of ICH patients.

Methods

ICH patients were extracted from the MIMIC-III database according to the ICD-9 code and randomly divided into training and verification cohorts. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression were applied to determine independent risk factors. These risk factors were used to construct a nomogram model for predicting the 30-day mortality risk of ICH patients. The nomogram was verified by the area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA).

Results

A total of 890 ICH patients were included in the study. Logistic regression analysis revealed that age (OR = 1.05, P < 0.001), Glasgow Coma Scale score (OR = 0.91, P < 0.001), creatinine (OR = 1.30, P < 0.001), white blood cell count (OR = 1.10, P < 0.001), temperature (OR = 1.73, P < 0.001), glucose (OR = 1.01, P < 0.001), urine output (OR = 1.00, P = 0.020), and bleeding volume (OR = 1.02, P < 0.001) were independent risk factors for 30-day mortality of ICH patients. The calibration curve indicated that the nomogram was well calibrated. When predicting the 30-day mortality risk, the nomogram exhibited good discrimination in the training and validation cohorts (C-index: 0.782 and 0.778, respectively). The AUCs were 0.778, 0.733, and 0.728 for the nomogram, Simplified Acute Physiology Score II (SAPSII), and Oxford Acute Severity of Illness Score (OASIS), respectively, in the validation cohort. The IDI and NRI calculations and DCA analysis revealed that the nomogram model had a greater net benefit than the SAPSII and OASIS scoring systems.

Conclusion

This study identified independent risk factors for 30-day mortality of ICH patients and constructed a predictive nomogram model, which may help to improve the prognosis of ICH patients.