LHI imposes a substantial burden on both patients and their family members due to its high mortality. Identifying potential risk factors for in-hospital mortality at an early stage is essential for both patients and clinicians. In our study, the mortality of patients with LHI is 29.6%, which is comparatively low1. Several factors contribute to this lower mortality rate. First, decompressive hemicraniectomy was performed in some of our patients, leading to a reduction in mortality7. Second, the participants in our study were elderly, with an average age of 75.67 years. Elderly patients may exhibit brain atrophy, which allows for more space for brain swelling.
Previous study has reported that MBE, pulmonary infection, and hypoalbuminemia are independently associated with a 3-month unfavorable outcome in patients with right-sided large hemisphere infarction (RLHI)8. Additionally, admission NIHSS > 20 and mechanical ventilation within 48 hours of admission were independently associated with a poor outcome in very elderly patients with LHI which received medical management only9. In our study, we found that MLS, ventilation, NLR, NIHSS, collateral score and involve of non-ischemic territory could predict the in-hospital mortality in LHI patients (Fig. 1).
We have identified that MLS is a crucial independent factor associated with poor outcome in LHI patients. MLS typically indicates the presence of malignant brain edema (MBE), a significant contributor to early mortality. MBE can lead to irreversible tissue damage, inadequate cerebral blow flow, an impaired blood-brain barrier (BBB), elevated intracranial pressure and brain herniation10. Li et al.8 reported that MBE is linked to unfavorable outcome in patients with RLHI independently. Thus, early detection of brain edema is imperative.
In a previous study6 focused on predicting the risk of MCE after acute LHI involving the anterior circulation, eight independent predictors were identified, including GCS score, NIHSS score, ASPECTS, monocyte count, WBC count, HbA1c level, history of hypertension, as well as a history of hypertension and atrial fibrillation. While this study shed light on the predictive mechanisms of LHI progression to MCE, it did not delve into the exploration of risk prediction mechanisms for in-hospital mortality in patients who did not undergo DHC. To manage elevated intracranial pressure resulting from cerebral edema, hyperosmolar agents such as hypertonic saline and mannitol are commonly employed. However, these therapies require an intact BBB to exert their osmotic effects and may not be effective at the site of edema11. DHC has been advocated as an effective treatment to reduce MBE-related mortality, but its criteria are stringent. For instance, very elderly patients may not be candidates for this procedure9. The GAMES-RP trial12 demonstrated that glibenclamide, when compared to a placebo, significantly reduce mortality at 30 days, although no distinction in mortality rates was observed12 between days 7 and 90. Therefore, early detection and treatment of brain edema are vital steps to reduce the mortality rates among patients suffering from large-scale cerebral infarctions in the future.
In our study, we also found that mechanical ventilation was another independent predictor for mortality, consistent with previous researches13, 14 which highlighted that a high mortality rate among patients requiring artificial ventilation. Zhang et al.15 demonstrated that mechanical ventilation represented an independent risk factor for in-hospital mortality in acute stroke patients13. On one hand, patients with LHI usually require mechanical ventilation due to severe brain damage, swallowing dysfunction, and impaired consciousness. On the other hand, serious complications such as pneumonia and sepsis may result in respiratory failure, necessitating mechanical ventilations. According to the most recent finding, the outcome is worse for those who need mechanical ventilation on the day of stroke diagnosis compared to those who require it after diagnosis14. Although the exact mechanism remains unclear, it appears that mechanical ventilation is the underlying factor contributing to this discrepancy. This is attributed to the fact that mechanical ventilation augments the susceptibility to lung infections, ventilator-associated pulmonary injuries, respiratory failure, and additional complications, all of which can substantially heighten the risk of mortality16.
In the last few years, inflammation has emerged as a pivotal factor in predicting the prognosis of cerebral infarction. In our study, we identified that the NLR was associated with poor outcome of patients with LHI, consistent with previous study that NLR was the highly potential predictor of clinical outcomes17, additionally, the study also suggested that NLR can be an indicator of brain edema and death in individuals suffering from a large-scale cerebral infarction. Ji et al.18 also reported that NLR had the exceptional predictive ability for in-hospital mortality following acute myocardial infarction, it appears that inflammatory factors can infiltrate ischemia-damaged tissues, including myocardial and brain tissues, and exert their effects. Prior study17 postulated that cerebral edema might constitute a crucial mechanism linking systemic inflammation to secondary brain injury and stroke morbidity, a hypothesis with which we concur. Stroke initiates an early disruption of the blood-brain barrier (BBB), permitting the infiltration of peripheral immune cells into injured tissues19. Inflammations in infarcted regions would rapidly coalesces within a few hours, then occluding the microvascular network, reducing the microvessel blood flow, and exacerbating tissue damage20. By triggering local inflammation, this process may worsen the existing endothelial damage, thus resulting in further brain injury due to cerebral edema. An experiment revealed that when a vessel is blocked, neutrophils quickly accumulate in the downstream microcirculation veins. This phenomenon, known as downstream microvascular thromboinflammation (DMT), is intensified by neutrophil activation21. A recent MRI study22 in mice has lent credibility to the idea that DMT could potentially exacerbate ischemic damage and disrupt the BBB, thereby potentially leading to hemorrhagic transformation. Both studies had suggested that specific substances released by inflammatory cells, such as oxygen species, proteases, cytokines and chemokines could increase the neuronal death. Boisseua et al.23 found that Neutrophil count predicts poor outcomes after endovascular therapy. Cui et al.24 also demonstrated that early peripheral neutrophil count after stroke correlates with infarct size and the fatal outcome of LHI patients. Thus, the control of inflammatory cell aggregation and the subsequent inflammatory reactions is imperative in reducing brain edema, preventing bleeding transformation, and decreasing mortality in patients with LHI.
The NIHSS score is a valuable tool for diagnosing and treating clinical cerebral infarction. It assesses the degree of functional impairment in patients with cerebral infarction, including aspects like speech, consciousness, and limb activity. Generally, a higher the score indicates a more severe condition. Previous investigations have shown that NIHSS scores can be utilized to predict the onset of brain edema25. It has been observed that a high NIHSS score is associated with an unfavorable clinical outcome8. Consistent with previous studies, our research reveals a correlation between the NIHSS score and mortality. Therefore, healthcare professionals should pay particular attention to patients with higher NIHSS scores.
The Collateral Score (CS) and infarctions involving Non-MCA Perfusion Territories have both demonstrated associations with the mortality of LHI patients. Jo et al.25 demonstrated that CS was independently associated with malignant brain edema. Other research26 had similarly found that poor collateral status independently predicts malignant infarction in patients receiving endovascular therapy. In a study conducted by Elijovich et al.27, a favorable collateral status was associated with smaller infarct volumes and improved clinical outcomes in patients who underwent endovascular recanalization. Collateral circulation represents an existing vascular pathway that can supply blood to target tissue in the event of blockages in the primary vascular channels28. Consequently, collateral flow is an effective technique for augmenting blood supply to protect the neurons in ischemic areas. When collateral flow is insufficient, irreversible neuronal damage can occur in a matter of minutes29. The provision of collateral circulation is integral to the development of cerebral ischemia, albeit challenging to measure due to its intricate and narrow pathways30. The CS serves as a fundamental yet reliable method for evaluating collateral supply and its correlation with smaller infarct volumes. Non-middle cerebral artery infarction usually implies the involvement of other blood vessels, such as the anterior or posterior cerebral artery regions. A previous study31 had established that anterior cerebral artery involvement is an independent predictor for malignant cerebral edema in LHI patients. Payabvash et al.32 similarly demonstrated that anterior extension of LHI, which involves the ACA territory and ACA-MCA border zone, independently predicts poor functional outcomes in LHI patients. When the ACA territory is affected in LHI patients, it likely indicates a larger infarction or an occlusion closer to the internal carotid artery, which is often accompanied by reduced hemispheric collateral flow and the presence of edematous brain tissue33. Nevertheless, alternative perspectives have been presented in some articles. Kürten et al.34 suggested that patients with infarctions extending beyond the MCA territory have similar likelihoods of positive outcomes as those with solely MCA infarction. Further research is needed on these topics.
Nomogram is a widely popularized visual tool for Logistic regression models in recent years, enabling a clear and concise risk prediction for binary classification tasks. Sun's article had previously conducted a similar study and discovered that age, NLR, and MLS are the risk factors for mortality, which aligns with our findings5. However, our study offers three distinct advantages in comparison to the prior research. Firstly, our research has a larger sample size and a more comprehensive population representation than the previous investigation. The earlier study had a sample size of 158 participants, ranging in age from 53 to 71 years. In contrast, our study encompassed 314 individuals, aged between 32 and 104 years. Secondly, our research has identified a broader range of predictive factors that can be easily accessed from routine clinical practice, thus enhancing their practical utility. Previous research has highlighted the challenges in obtaining predictive factors, such as such as the requirement for logarithmic values in the case of NLR. Moreover, in contrast to prior research, this study utilized a variant of the random forest-based artificial intelligence method known as Boruta for variable selection. Unlike the conventional approach employed in the study mentioned above, which involved a sequential process of univariate regression followed by multivariate regression, our method accounts for interactions between variables, resulting in more robust outcomes.
While we have made every effort to mitigate potential constraints, our study still exhibits certain limitations. Firstly, the study is a single center sample study. Secondly, it’s important to note that our prediction tool is merely validated internally, despite the model we developed achieved a high performance. In the future, research efforts should prioritize the investigation of subgroups and their clinical implications.
In conclusion, our research demonstrated that MLS, ventilation, NLR, NIHSS, collateral score and non-ischemic territory are reliable indicators for predicting in-hospital mortality in LHI patients. Our prediction model can serve as a useful tool for clinicians in guiding appropriate treatment strategies for patients with ischemic stroke.