A nomogram to predict early hematoma expansion of hypertensive cerebral hemorrhage

CT radiomics combined with clinical and radiological factors predict hematoma expansion in hypertensive intracerebral hemorrhage

OBJECTIVES

This study aimed to establish a hematoma expansion (HE) prediction model for hypertensive intracerebral hemorrhage (HICH) patients by combining CT radiomics, clinical information, and conventional imaging signs.

METHODS

A retrospective continuous collection of HICH patients from three medical centers was divided into a training set (n = 555), a validation set (n = 239), and a test set (n = 77). Extract radiomics features from baseline CT plain scan images and combine them with clinical information and conventional imaging signs to construct radiomics models, clinical imaging sign models, and hybrid models, respectively. The models will be evaluated using the area under the curve (AUC), clinical decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI).

RESULTS

In the training, validation, and testing sets, the radiomics model predicts an AUC of HE of 0.885, 0.827, and 0.894, respectively, while the clinical imaging sign model predicts an AUC of HE of 0.759, 0.725, and 0.765, respectively. Glasgow coma scale score at admission, first CT hematoma volume, irregular hematoma shape, and radiomics score were used to construct a hybrid model, with AUCs of 0.901, 0.838, and 0.917, respectively. The DCA shows that the hybrid model had the highest net profit rate. Compared with the radiomics model and the clinical imaging sign model, the hybrid model showed an increase in NRI and IDI.

CONCLUSION

The hybrid model based on CT radiomics combined with clinical and radiological factors can effectively individualize the evaluation of the risk of HE in patients with HICH.

CLINICAL RELEVANCE STATEMENT

CT radiomics combined with clinical information and conventional imaging signs can identify HICH patients with a high risk of HE and provide a basis for clinical-targeted treatment.

KEY POINTS

HE is an important prognostic factor in patients with HICH. The hybrid model predicted HE with training, validation, and test AUCs of 0.901, 0.838, and 0.917, respectively. This model provides a tool for a personalized clinical assessment of early HE risk.

Prognostic value of nomogram model based on clinical risk factors and CT radiohistological features in hypertensive intracerebral hemorrhage

Objective

To construct a nomogram model based on clinical risk factors and CT radiohistological features to predict the prognosis of hypertensive intracerebral hemorrhage (HICH).

Methods

A total of 148 patients with HICH from April 2022 to July 2024 were retrospectively selected as the research subjects. According to the modified Rankin scale at the time of discharge, they were divided into good group (Rankin scale score 0-2) and bad group (Rankin scale score 3-6). To compare the clinical data and the changes of CT radiographic characteristics in patients with different prognosis. Relevant factors affecting the prognosis were analyzed, and nomogram model was established based on the influencing factors. The fitting degree, prediction efficiency and clinical net benefit of the nomogram model were evaluated by calibration curve, ROC curve and clinical decision curve (DCA).

Results

Compared with the good group, the hematoma volume in the poor group was significantly increased, the serum thromboxane 2(TXB2) and lysophosphatidic acid receptor 1(LPAR1) levels were significantly increased, and the energy balance related protein (Adropin) level was significantly decreased. The proportions of irregular shape, promiscuous sign, midline displacement, island sign and uneven density were all significantly increased (p < 0.05). In Logistic multivariate analysis, hematoma volume, Adropin, TXB2, LPAR1 and CT radiological features were all independent factors influencing the poor prognosis of HICH (p < 0.05). A nomogram prediction model was established based on the influencing factors. The calibration curve showed that the C-index was 0.820 (95% CI: 0.799-0.861), the goodness of fit test χ2 = 5.479, and p = 0.391 > 0.05, indicating a high degree of fitting. The ROC curve showed that the AUC was 0.896 (95% CI: 0.817-0.923), indicating that this model had high prediction ability. The DCA curve shows that the net benefit of the nomogram model is higher when the threshold probability is 0.1-0.9.

Conclusion

The nomogram prediction model established based on hematoma volume, Adropin, TXB2, LPAR1 and other clinical risk factors as well as CT radiographic characteristics has high accuracy and prediction value in the diagnosis of poor prognosis in patients with HICH.

Intracerebral hemorrhage complicated by alcohol use disorder in young males in Chongqing China: Characteristics and long-term outcome

BACKGROUND

The characteristics of patients with intracerebral hemorrhage (ICH) complicated by alcohol use disorders (AUD) are not well understood. Investigating the clinical characteristics and prognosis of this subgroup (AUD-ICH) is necessary.

METHODS

This study involved young males with ICH who were admitted to our hospital between January 2013 and March 2022. Based on drinking patterns, the included cases were divided into three groups: AUD, occasional drinking, and non-drinking. We compared the clinical characteristics and prognosis of patients in the three groups. The effect of AUD on hematoma expansion and long-term dysfunction was explored by developing regression models. The potential mediating role of hematoma density heterogeneity within the relationship between AUD and hematoma expansion was examined through mediation analysis.

RESULTS

This study included 222 cases of male patients with ICH, with a mean age of 54.16. AUD patients had a higher risk of hematoma expansion and dysfunction compared to occasional drinkers (odds ratio [OR] 2.966, p=0.028 for hematoma expansion; hazard ratio [HR] 2.620, p=0.006 for dysfunction) and non-drinkers (OR 3.505, p=0.011 for hematoma expansion; HR 2.795, P=0.003 for dysfunction). The mediation analysis showed that the indirect effect through hematoma density heterogeneity on the relationship between AUD and hematoma expansion was significant, with a mediated proportion of 19.3%.

CONCLUSIONS

AUD was an independent risk factor for hematoma expansion and long-term dysfunction in young male patients with ICH. Hematoma density heterogeneity partially mediated the relationship between AUD and hematoma expansion.

Development and validation of a prognostic nomogram based on the hub genes of patients with hypertensive intracerebral hemorrhage

OBJECTIVE

Hypertensive intracerebral hemorrhage (HICH) is frequently associated with high disability, high mortality, and poor prognosis. The present study aimed to identify genes associated with HICH to construct prognostic models to improve accuracy in predicting HICH prognosis.

METHODS

Hub genes were identified by screening out differentially expressed genes from data in the Gene Expression Omnibus database and conducting weighted gene co-expression network analysis. 68 patients with HICH were recruited and categorized based on prognosis. The univariate logistic, least absolute shrinkage and selection operator, and multivariate logistic regression models were then established based on clinical data and the identified hub genes. A prognostic model was constructed based on the nomogram score. The model was validated using receiver operating characteristic curve, C-index, calibration plots, and decision curve analysis. It was also compared to a prognostic model constructed based on clinical data alone. The prognostic value of the nomogram score was assessed in different subgroups.

RESULTS

Three hub genes: pro-platelet basic protein (PPBP), PDZ and LIM domain protein 1 (PDLIM1), and metalloproteinase 1 (TIMP1) were identified as significantly correlated to adverse outcomes in HICH. These hub genes, in combination with the clinical data, were used to construct a nomogram score system, which exhibited strong predictive power, excellent consistency between actual outcomes and predictions, and a higher net clinical benefit. HICH patients with high scores presented significantly worse outcome. Importantly, the developed nomogram score system was superior to the use of clinicopathological features in predicting HICH prognosis. The nomogram score system exhibited adequate predictive performance in different subgroups as well.

CONCLUSION

The nomogram score system based on PPBP, PDLIM1, and TIMP1 genes, along with clinical data, exhibited superior performance in predicting adverse outcome in HICH patients. This system could, therefore, be useful for guiding clinical decisions and providing valuable insight for designing individualized treatments for HICH patients.

Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis

PURPOSE

Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, radiomics has been gradually introduced into the early identification of hematoma enlargement. Though, radiomics has limited predictive accuracy due to variations in procedures. Therefore, we conducted a systematic review and meta-analysis to explore the value of radiomics in the early detection of HE in patients with cerebral hemorrhage.

METHODS

Eligible studies were systematically searched in PubMed, Embase, Cochrane and Web of Science from inception to April 8, 2024. English articles are considered eligible. The radiomics quality scoring (RQS) tool was used to evaluate included studies.

RESULTS

A total of 34 studies were identified with sample sizes ranging from 108 to 3016. Eleven types of models were involved, and the types of modeling contained mainly clinical, radiomic, and radiomic plus clinical features. The radiomics models seem to have better performance (0.77 and 0.73 C-index in the training cohort and validation cohort, respectively) than the clinical models (0.69 C-index in the training cohort and 0.70 C-index in the validation cohort) in discriminating HE. However, the C-index was the highest for the combined model in both the training (0.82) and validation (0.79) cohorts.

CONCLUSIONS

Machine learning based on radiomic plus clinical features has the best predictive performance for HE, followed by machine learning based on radiomic features, and can be used as a potential tool to assist clinicians in early judgment.

Efficacy of Neuroendoscopy Surgery Combined With Postoperative Lokomat Rehabilitation Training in Patients With Hypertensive Intracerebral Hemorrhage

OBJECTIVE

To explore the effects of neuroendoscopy surgery combined with postoperative Lokomat rehabilitation training on patients with hypertensive cerebral hemorrhage.

METHODS

A total of 88 patients with hypertensive cerebral hemorrhage who underwent surgical treatment in our hospital were retrospectively analyzed. They were divided into a study group and a conventional group with 44 patients in each group. The patients in the 2 groups were compared regarding operation-related conditions, hospital stay, preoperative and postoperative functional status scores, and postoperative complications.

RESULTS

The operation time, intraoperative blood loss, hospital stays, and hematoma clearance rate of the study group were significantly better than those of the conventional group (P<0.001). Regarding scores of related functional status, there was no significant difference between the 2 groups before operation (P>0.05). The different scores of the study group were significantly better than those of the conventional group 1 month after the operation (P<0.05). Regarding complications, the study group also has significant advantages, with only one case of rebleeding.

CONCLUSION

Compared to the traditional approach of small bone window craniotomy followed by postoperative Lokomat rehabilitation training, the combination of neuroendoscopy surgery and Lokomat training proves to be more efficient. This approach can effectively reduce the operating time and hospital stay of patients with hypertensive intracerebral hemorrhage, minimize intraoperative blood loss, improve the hematoma clearance rate, and lower the incidence of postoperative complications.

Systematic Evaluation of Hematoma Expansion Models in Spontaneous Intracerebral Hemorrhage: A Meta-Analysis and Meta-Regression Approach

INTRODUCTION

Accurate prediction of hematoma expansion (HE) in spontaneous intracerebral hemorrhage (sICH) is crucial for tailoring patient-specific treatments and improving outcomes. Recent advancements have yielded numerous HE risk factors and predictive models. This study aims to evaluate the characteristics and efficacy of existing HE prediction models, offering insights for performance enhancement.

METHODS

A comprehensive search was conducted in PubMed for observational studies and randomized controlled trials focusing on HE prediction, written in English. The prediction models were categorized based on their incorporated features and modeling methodology. Rigorous quality and bias assessments were performed. A meta-analysis of studies reporting C-statistics was executed to assess and compare the performance of current HE prediction models. Meta-regression was utilized to explore heterogeneity sources.

RESULTS

From 358 initial records, 22 studies were deemed eligible, encompassing traditional models, hematoma imaging feature models, and models based on artificial intelligence or radiomics. Meta-analysis of 11 studies, involving 12,087 sICH patients, revealed an aggregated C-statistic of 0.74 (95% CI: 0.69-0.78) across seven HE prediction models. Eight characteristics related to development cohorts were identified as key factors contributing to performance variability among these models.

CONCLUSION

The findings indicate that the current predictive capacity for HE risk remains suboptimal. Enhanced accuracy in HE prediction is vital for effectively targeting patient populations most likely to benefit from tailored treatment strategies.

Research advances in predicting the expansion of hypertensive intracerebral hemorrhage based on CT images: an overview

Hematoma expansion (HE) is an important risk factor for death or poor prognosis in patients with hypertensive intracerebral hemorrhage (HICH). Accurately predicting the risk of HE in patients with HICH is of great clinical significance for timely intervention and improving patient prognosis. Many imaging signs reported in literatures showed the important clinical value for predicting HE. In recent years, the development of radiomics and artificial intelligence has provided new methods for HE prediction with high accuracy. Therefore, this article reviews the latest research progress in CT imaging, radiomics, and artificial intelligence of HE, in order to help identify high-risk patients for HE in clinical practice.

Signature and function of plasma exosome-derived circular RNAs in patients with hypertensive intracerebral hemorrhage

Intracerebral hemorrhage (ICH) is one of the major causes of death and disability, and hypertensive ICH (HICH) is the most common type of ICH. Currently, the outcomes of HICH patients remain poor after treatment, and early prognosis prediction of HICH is important. However, there are limited effective clinical treatments and biomarkers for HICH patients. Although circRNA has been widely studied in diseases, the role of plasma exosomal circRNAs in HICH remains unknown. The present study was conducted to investigate the characteristics and function of plasma exosomal circRNAs in six HICH patients using circRNA microarray and bioinformatics analysis. The results showed that there were 499 differentially expressed exosomal circRNAs between the HICH patients and control subjects. According to GO annotation and KEGG pathway analyses, the targets regulated by differentially expressed exosomal circRNAs were tightly related to the development of HICH via nerve/neuronal growth, neuroinflammation and endothelial homeostasis. And the differentially expressed exosomal circRNAs could mainly bind to four RNA-binding proteins (EIF4A3, FMRP, AGO2 and HUR). Moreover, of differentially expressed exosomal circRNAs, hsa_circ_00054843, hsa_circ_0010493 and hsa_circ_00090516 were significantly associated with bleeding volume and Glasgow Coma Scale score of the subjects. Our findings firstly revealed that the plasma exosomal circRNAs are significantly involved in the progression of HICH, and could be potent biomarkers for HICH. This provides the basis for further research to pinpoint the best biomarkers and illustrate the mechanism of exosomal circRNAs in HICH.

Relationship between changes in neurological deficit severity and adverse cardiac events in elderly patients with hypertensive intracerebral hemorrhage: a retrospective cohort study

OBJECTIVE

To explore the relationship between changes in neurological deficit severity and the occurrence of adverse cardiac events in elderly patients with hypertensive intracerebral hemorrhage.

METHODS

Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of NIHSS scores for adverse cardiac events.

RESULTS

There were significant differences between the two groups. Multivariate logistic regression analysis showed that advanced age, high NIHSS score, large intracerebral hemorrhage volume, and high CK level were independent risk factors for adverse cardiac events in elderly patients with hypertensive intracerebral hemorrhage (p < 0.05). The NIHSS scores of both groups gradually increased after admission, peaking at 48 h after admission. In Group A, this elevation persisted until 72 h after admission, while in Group B, there was a significant decrease at 72 h after admission (p < 0.05). From admission to 7 days after admission, the NIHSS scores in Group A were higher than those in Group B (p < 0.05). The area under the curve (AUC) of the NIHSS scores at 48 h after admission was 0.776, with sensitivity and specificity of 80.9% and 84.5%, respectively, which were higher than those of other indicators (p < 0.05).

CONCLUSION

The occurrence of adverse cardiac events in elderly patients with hypertensive intracerebral hemorrhage is influenced by multiple factors, and as the NIHSS score increases, the risk of such events gradually increases. Clinicians should pay attention to monitoring NIHSS scores after admission, as they have value in predicting adverse cardiac events in elderly patients with hypertensive intracerebral hemorrhage.

Optimal cut-off values of haematoma volume for predicting haematoma expansion at different intracerebral haemorrhage locations

BACKGROUND

Haematoma expansion (HE) is a frequent manifestation of acute intracerebral haemorrhage (ICH) and is associated with early disease progression and poor functional status. Approximately 30 % of patients with ICH experience substantial HE within the first few hours of onset.

OBJECTIVES

This study aimed to investigate the relationship between HE and initial volume at different locations in patients with ICH.

METHODS

We investigated consecutive patients with ICH admitted to the emergency room at Xiangyang No. 1 People's Hospital between January 2018 and June 2022. Haematoma volume was calculated using a three-dimensional slicer platform. Prediction models were assessed using a logistic regression model. The Youden index was used to assess the haematoma volume cut-off values for predicting HE.

RESULTS

This study included 306 patients: 161 had basal ganglia ICH, 41 lobar ICH, and 104 thalamic ICH. The area under the ROC curve (AUC) for the thalamic ICH score in predicting intraventricular haemorrhage (IVH) expansion ≥ 1 mL or delayed IVH expansion was 0.786, and the best cut-off value was 7.05 mL (specificity, 85.3 %; sensitivity, 62.8 %; and accuracy, 76.0 %). The AUC for the thalamic ICH and lobar ICH scores in predicting haematoma or IVH expansion were 0.756 and 0.653, respectively; the best cut-offs were 7.05 mL for the thalamus (specificity, 84.8 %; sensitivity, 60.0 %; and accuracy, 74.0 %) and 31.89 mL in the lobar area (specificity, 81.8 %; sensitivity, 52.3 %; and accuracy, 68.3 %).

CONCLUSIONS

Initial ICH volume predicted haematoma or IVH expansion at different locations. Moreover, it can assist clinicians in determining whether patients are suitable for future surgical interventions or other procedures.

Radiomics Outperforms Clinical and Radiologic Signs in Predicting Spontaneous Basal Ganglia Hematoma Expansion: A Pilot Study

Prediction of the hematoma expansion (HE) of spontaneous basal ganglia hematoma (SBH) from the first non-contrast CT can result in better management, which has the potential of improving outcomes. This study has been designed to compare the performance of "Radiomics analysis," "radiology signs," and "clinical-laboratory data" for this task. We retrospectively reviewed the electronic medical records for clinical, demographic, and laboratory data in patients with SBH. CT images were reviewed for the presence of radiologic signs, including black-hole, blend, swirl, satellite, and island signs. Radiomic features from the SBH on the first brain CT were extracted, and the most predictive features were selected. Different machine learning models were developed based on clinical, laboratory, and radiology signs and selected Radiomic features to predict hematoma expansion (HE). The dataset used for this analysis included 116 patients with SBH. Among different models and different thresholds to define hematoma expansion (10%, 20%, 25%, 33%, 40%, and 50% volume enlargement thresholds), the Random Forest based on 10 selected Radiomic features achieved the best performance (for 25% hematoma enlargement) with an area under the curve (AUC) of 0.9 on the training dataset and 0.89 on the test dataset. The models based on clinical-laboratory and radiology signs had low performance (AUCs about 0.5-0.6).

Analysis of the Therapeutic Effect and Prognostic Factors of 126 Patients With Hypertensive Cerebral Hemorrhage Treated by Soft-Channel Minimally Invasive Puncture and Drainage

Background

Surgery is the main method for the clinical treatment of hypertensive cerebral hemorrhage. Traditional craniotomy faces the disadvantages of the long operation time, easy to cause secondary injury to patients during the operation, and prone to infection after the operation, which is not conducive to the rehabilitation of patients. At present, it is urgent to find a surgical scheme, which can clear hematoma in time, protect brain tissue, and effectively reduce surgical trauma in the clinic.

Materials and Methods

The case database of our hospital was consulted, and the clinical data of patients with hypertensive intracerebral hemorrhage (HICH) treated with soft channel minimally invasive puncture and drainage from February 2018 to October 2021 were retrospectively analyzed. Patients were evaluated for efficacy, and the changes in serum C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), homocysteine (Hcy), endothelin (ET), and vasopressin (AVP) levels before surgery, 3 days after surgery, and 7 days after surgery were analyzed. Clinical data were collected and Logistic regression was used to analyze the prognostic factors.

Results

Finally, according to the inclusion and exclusion criteria, 126 patients were selected as the research object. Among them, there were 24 cases (19.05%) of recovery, 47 cases (37.30%) of markedly effective, 34 cases (26.98%) of effective, 11 cases (8.73%) of ineffective, and 10 cases (7.94%) of death. The total effective rate was 83.33%. The hematoma was basically removed in 116 cases (92.06%). The average evacuation time of hematoma was (7.82 ± 1.63) days. Post-operative intracranial infection occurred in 2 cases (1.59%) and post-operative rebleeding occurred in 5 cases (3.97%). The average hospital stay was (34.16 ± 16.59) days. Serum CRP, TNF-α, IL-6, Hcy, ET, and AVP levels of all patients on the third and seventh days after surgery were lower than those before surgery, and those on the seventh day after surgery were lower than those on the third day after surgery (p < 0.05). The differences in pre-operative Glasgow Coma Scale (GCS) score, bleeding volume, ventricular rupture, complicated cerebral hernia, and attack time to surgery between the good prognosis group and the bad prognosis group were statistically significant (p < 0.05). Pre-operative GCS score, bleeding volume, ventricular rupture, complicated cerebral hernia, and onset time to surgery were all independent factors that affect the prognosis of patients (p < 0.05).

Conclusion

Soft-channel minimally invasive puncture and drainage treatment of HICH has a significant effect, which is conducive to the complete removal of hematoma, reducing hospitalization time, while adjusting the balance and stability of various cytokines, and improving patient prognosis. Pre-operative GCS score, bleeding volume, rupture into the ventricle, complicated cerebral hernia, and time from onset to operation are all independent factors that affect the prognosis of patients.

Short-term effect and long-term prognosis of neuroendoscopic minimally invasive surgery for hypertensive intracerebral hemorrhage. World J Clin Cases 2021;9:8358-8365. [PMID: 34754845 PMCID: PMC8554417 DOI: 10.12998/wjcc.v9.i28.8358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Hypertensive intracerebral hemorrhage is a common critical disease of the nervous system, comprising one fifth of all acute cerebrovascular diseases and has a high disability and mortality rate. It severely affects the patients’ quality of life.

AIM

To analyze the short-term effect and long-term prognosis of neuroendoscopic minimally invasive surgery for hypertensive intracerebral hemorrhage.

METHODS

From March 2018 to May 2020, 118 patients with hypertensive intracerebral hemorrhage were enrolled in our study and divided into a control group and observation group according to the surgical plan. The control group used a hard-channel minimally invasive puncture and drainage procedure. The observation group underwent minimally invasive neuroendoscopic surgery. The changes in the levels of serum P substances (SP), inflammatory factors [tumor necrosis factor-α, interleukin-6 (IL-6), IL-10], and the National Hospital Stroke Scale (NIHSS) and Barthel index scores were recorded. Surgery related indicators and prognosis were compared between the two groups.

RESULTS

The operation time (105.26 ± 28.35) of the observation group was min longer than that of the control group, and the volume of intraoperative bleeding was 45.36 ± 10.17 mL more than that of the control group. The hematoma clearance rates were 88.58% ± 4.69% and 94.47% ± 4.02% higher than those of the control group at 48 h and 72 h, respectively. Good prognosis rate (86.44%) was higher in the observation group than in the control group, and complication rate (5.08%) was not significantly different from that of the control group (P > 0.05).The SP level and Barthel index score of the two groups increased (P < 0.05) and the inflammatory factors and NIHSS score decreased (P < 0.05). The cytokine levels, NIHSS score, and Barthel index score were better in the observation group than in the control group (P < 0.05).

CONCLUSION

Neuroendoscopic minimally invasive surgery is more complicated than hard channel minimally invasive puncture drainage in the treatment of hypertensive intracerebral hemorrhage; however, hematoma clearance is more thorough, and the short-term effect and long-term prognosis are better than hard channel minimally invasive puncture drainage.