Journal
BMC NEUROLOGY
Volume 23, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s12883-022-03039-9
Keywords
Nomogram; Haemoglobin; Intracerebral hemorrhage; Prognosis
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This study aimed to construct a valuable prognostic nomogram model incorporating hemoglobin levels for adult patients with intracerebral hemorrhage (ICH). Independent prognostic factors were identified and a new nomogram model was developed and validated. The model showed high accuracy in predicting early functional prognosis.
Objective Intracerebral hemorrhage (ICH) is the second most common subtype of stroke, with high mortality and morbidity. At present, there are no effective 6-month prognostic markers, particularly for younger patients. The aim of this research was to construct a new valuable prognostic nomogram model incorporating haemoglobin levels for adult patients with ICH.Methods Patients aged between 18 and 50 presenting with intracerebral haemorrhage at the Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology between January 1st 2012 and December 31st 2018 were included in this retrospective study. Independent factors of prognosis were identified by univariate and multivariate logistic regression analyses, and a new nomogram model was constructed and validated. The clinical value of the nomogram model was subsequently explored utilizing decision curve analysis and clinical impact curves.Results In total, 565 patients were enrolled in this study, 117 (20.7%) of whom developed an unfavourable prognosis. Infratentorial lesion (adjusted odds ratio [aOR]= 3.708, 95% confidence interval [CI], 1.490-9.227; P = 0.005) was the most significant unfavourable outcome. Age ([aOR] = 1.054; 95% CI, 1.014-1.096; P = 0.008), hematoma volume (aOR= 1.014, 95% CI, 1.002-1.027; P = 0.024), haemoglobin (aOR= 0.981, 95% CI, 0.969-0.993; P = 0.002), blood glucose (aOR = 1.135, 95% CI, 1.037-1.241; P = 0.005) and NIHSS (aOR = 1.105, 95% CI, 1.069-1.141; P < 0.001) were independent risk factors. Based on these 6 factors, the nomogram can be employed to predict early functional prognosis with high accuracy (AUC 0.791). Decision curve analysis and clinical impact curves showed an increased net benefit for utilizing the nomogram.Conclusion The haemoglobin level at admission may be an easily overlooked factor in clinical work. This new nomogram model could be a promising and convenient tool to predict the early functional prognosis of adults with ICH. More prospective multicentre studies are needed to validate these findings.
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