To our knowledge, the present study is to establish a nomogram model to predict 6-month prognosis in younger adults with ICH. In this cohort, age, hematoma volume, blood glucose, infratentorial lesion, haemoglobin and the NIHSS score were significant prognostic factors in the univariate logistic regression analysis and were confirmed as independent risk factors for functional prognosis. Based on those predicting parameters, we constructed a nomogram model for evaluation. We incorporated several common clinical factors and an easily overlooked blood indicator haemoglobin into our model. The performance of the present nomogram was strictly assessed and internally validated, and its net benefit was also explored by DCA and the CIC compared with other prognostic scores commonly used in clinical practice. In addition, our study demonstrates that the clinical applicability of this nomogram is feasible for ICH in younger adults.Estimating haemoglobin levels is part of standard blood analysis. Establishing a link between haemoglobin levels and the undesirable prognosis of stroke at no extra cost or the need for additional tests suggests this could be a widely-implemented clinical screening tool.
Haemoglobin level is part of the automated analysis of blood cells at no additional cost, establishing an important link with the undesirable prognosis of stroke [19]. In recent years, several studies have found a positive correlation between anaemia and higher mortality in stroke patients [12, 20]. In 2018, a meta-analysis identified seven cohort studies with 7,328 ICH patients, including 1,546 patients with anaemia, revealing that anaemia was associated with an increased risk of poor outcome in patients with ICH (OR = 2.29 for 3-month outcome, 95% CI 1.16 to 4.51; OR = 3.42 for 12-month outcome, 95% CI 0.50 to 23.23) [12]. Another recent study that reported a large meta-analysis of pooled data from the ATACH-2, FAST, and ERICH studies also found that higher admission Hb levels were associated with better outcomes [20]. It has been posited that such a result may have occurred because these patients had a haematologic disorder that causes the hematoma and, eventually, a poor prognosis [21]. Lower erythrocyte counts may result in less efficient radial transport of platelets towards the vessel wall, preventing the platelet endothelial interaction that is vital to haemostasis initiation. In addition, erythrocytes themselves may be implicated in haemostasis through their adhesion to the injured vessel wall in addition to their interaction with platelets and fibrinogen, leading to blood clot contraction [22]. David J. Roh et al. also suggested that hyperacute transfusion of pRBCs can be considered in preventing the early occurrence of HE to improve outcomes. However, the timing of red blood cell transfusions still needs more research to be clarified [21].
Previous studies have suggested that hyperglycaemia is associated with mortality in ICH patients [23, 24]. A meta-analysis of 16 studies reinforced this view: high blood glucose was significantly associated with poor functional outcome in ICH patients [25]. Previous animal studies identified an evident association between hyperglycaemia and perihematomal neuronal apoptosis in rat models [26]. In ICH models, hematoma with high blood glucose was found to lead to neurological injury and decreased autophagy [27]. High blood glucose can increase superoxide production in ICH induced by tissue plasminogen activator [28].
A 2013 study showed that age could affect the prognosis of intracerebral hemorrhage in younger people, and the INTERACT-2 study also showed that age is a strong predictor of a poor prognosis for intracerebral hemorrhage, consistent with the results of this study [11, 10]. The reason for this may be that younger people are in better physical condition than elderly people. Their vascular atherosclerosis is mild, and they can establish collateral circulation in a short period of time so that angioedema is relatively mild, neurological deficits are milder, and younger patients have a strong sense of health care and actively carry out secondary prevention [29].
The GCS and NIHSS scores are commonly used stroke scales, with GCS scores assessing a patient's state of consciousness and NIHSS scores assessing both the patient’s state of consciousness and neurological deficits. A 2003 study found that the NIHSS score was superior to the GCS score in predicting the prognosis of patients with intracerebral hemorrhage. This is consistent with the results of the univariate analysis of this study that the NIHSS score and GCS score affected the prognosis at the time of univariate analysis, while the NIHSS score was independent of the influencing factors in the multivariate regression analysis [30].
Using such 6 variables, a nomogram combining haemoglobin with acceptable discrimination (C-index = 0.791) and calibration was established for predicting an unfavourable outcome, and it seems to possess more power efficiency than currently utilized prognostic tools. The decision curve suggested that, when the probability ranged from 20 to 40%, the net benefits of the nomogram were higher than those of the ICH-score and ICH-FOS. Moreover, the outcome was verified by a clinical impact curve.
In this study, our nomogram is novel and shows certain advantages. First, we integrated and internally validated a new nomogram model that combines clinical scores and laboratory data. The nomogram can be employed to predict early functional prognosis with high accuracy (AUC 0.791). Second, DCA and CIC were used to creatively evaluate the clinical performance of the new model. Finally, haemoglobin levels at admission may be an easily overlooked prognostic risk factor for negative outcomes after ICH. Our novel nomogram model may provide a promising and convenient tool to predict the early functional prognosis in younger adults with ICH. Prospective, multicentre studies are needed to validate these findings.
However, this study has limitations. First, it was a retrospective study in a single centre and not a randomized controlled trial (RCT). As a result, selection bias caused by single-centre data may have resulted in lack of broad representation of results. The accuracy of clinical valuation may have been attenuated by its retrospective nature. External validations in other institutions are warranted. Moreover, our model covered many types of clinical data variables, but the lack of detailed neuroimaging and therapeutic data may have led to an unavoidable systemic bias that weakens the discriminative performance of the nomogram. Finally, we collected a limited number of cases and had a 30% loss-of-follow-up rate, which may have affected the credibility of the results. Despite these limitations, we made a first attempt to establish and validate a nomogram model to predict a 6-month functional prognosis in younger ICH patients.