Predictive Nomogram for Unfavorable Outcome of Spontaneous Intracerebral Hemorrhage

The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage

Background and objectives

Recently, some literature has proposed new indicators such as rate-pressure product, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, etc. However, there has been no literature that has utilized these new indicators to establish a predictive model for assessing the risk of mortality in patients within 24 h on admission. Therefore, this study aims to build a predictive model that can rapidly assess the likelihood of mortality in patients within 24 h of admission.

Methods

The datasets used in this study are available from the corresponding author upon reasonable request. Patients were randomly assigned to the training or validation cohort based on a ratio of 7:3, which was implemented as internal validations for the final predictive models. In the training set, least absolute shrinkage and selection operator (LASSO) regression was employed to select predictive factors, followed by both univariate and subsequent multivariate analysis. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve.

Results

A total of 428 patients were included in our research. The final model included 4 independent predictors (Glasgow Coma Scale, hematoma volume, rate-pressure product, c-reactive protein) and was developed as a simple-to-use nomogram. The training set and internal validation set model's C-index are 0.933 and 0.954, demonstrating moderate predictive ability with regard to risks of mortality. Compared to ICH score (AUC: 0.910 and 0.925), the net reclassification index (NRI) is 0.298 (CI = -0.105 to 0.701, p: 0.147) and integrated discrimination improvement (IDI) is 0.089 (CI = -0.049 to 0.228, p: 0.209). Our model is equally excellent as the classic ICH score model.

Conclusion

We developed a model with four independent risk factors to predict the mortality of ICH patients. Our predictive model is effective in assessing the risk of mortality in patients within 24 h on admission, which might be worth considering in clinical settings after further external validation.

Development and validation of a risk nomogram to estimate risk of hyponatremia after spinal cord injury: A retrospective single-center study

OBJECTIVE

This study aimed to establish a nomogram-based assessment for predicting the risk of hyponatremia after spinal cord injury (SCI).

DESIGN

The study is a retrospective single-center study.

PARTICIPANTS

SCI patients hospitalized in the First Affiliated Hospital of Guangxi Medical University.

SETTING

The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.

METHODS

We performed a retrospective clinical study to collect SCI patients hospitalized in the First Affiliated Hospital of Guangxi Medical University from 2016 to 2020. Based on their clinical scores, the SCI patients were grouped as either hyponatremic or non-hyponatremic, SCI patients in 2016-2019 were identified as the training set, and patients in 2020 were identified as the test set. A nomogram was generated, the calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to validate the model.

RESULTS

A total of 895 SCI patients were retrieved. After excluding patients with incomplete data, 883 patients were finally included in this study and used to construct the nomograms. The indicators used in the nomogram included sex, completeness of SCI, pneumonia, urinary tract infection, fever, constipation, white blood cell (WBC), albumin and serum Ca2+. These indices were determined by the least absolute shrinkage and selection operator (LASSO) regression analysis. The C-index of the model was 0.81, the area under the curve (AUC) of the training set was 0.82(Cl:0.79-0.85), and the validation set was 0.79(Cl:0.73-0.85).

CONCLUSIONS

Nomogram has good predictive ability, sex, completeness of SCI, pneumonia, urinary tract infection, fever, constipation, WBC, albumin and serum Ca2+ were predictors of hyponatremia after SCI.

Prediction Model for Unfavorable Outcome in Spontaneous Intracerebral Hemorrhage Based on Machine Learning

OBJECTIVE

The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML).

METHODS

Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR).

RESULTS

We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables.

CONCLUSION

The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

Significance of serum sestrin2 as a biomarker of severity and functional outcome in acute intracerebral hemorrhage: a prospective observational longitudinal study

BACKGROUND

Sestrin2 is a highly conserved stress-inducible protein with neuroprotective properties. Herein, we investigated the prognostic significance of serum sestrin2 in human intracerebral hemorrhage (ICH).

METHODS

In this prospective observational longitudinal study, we enrolled 126 patients with supratentorial ICH as cases together with 126 healthy individuals as controls. Severity indicators were National Institutes of Health Stroke Scale (NIHSS) and hematoma volume. Prognostic parameters were early neurologic deterioration (END) and post-stroke 6-month poor prognosis [modified Rankin Scale (mRS) scores of 3-6]. Multivariate analysis was performed to assess relations of serum sestrin2 levels to severity and prognosis.

RESULTS

Patients had statistically significantly higher serum sestrin2 levels than controls. Serum sestrin2 levels of patients were independently correlated with NIHSS scores and hematoma volume, as well as were substantially elevated in order of mRS scores from 0 to 6. Serum sestrin2 was identified as an independent predictor of END and poor prognosis. Based on the receiver operating characteristic curve, serum sestrin2 had a similar predictive ability for END and poor prognosis, as compared to NIHSS scores and hematoma volume. Prediction models of END and poor prognosis, in which serum sestrin2, NIHSS scores and hematoma volume were integrated, were visually described via nomogram, were reliable and stable under calibration curve and were of clinical benefit using decision curve analysis. Also, prediction model of poor prognosis showed dramatically higher discriminatory efficiency than any of NIHSS scores, hematoma volume and serum sestrin2.

CONCLUSION

Serum sestrin2 levels, which are obviously increased following acute ICH, are independently related to illness severity and poor clinical outcomes, substantializing serum sestrin2 as a clinically valuable prognostic biomarker of ICH.

Comparative outcome of endovascular embolization with microsurgery in managing acute spontaneous cerebral hemorrhage in pediatric patients, an institutional experience

OBJECTIVES

A few previous studies have reported the role of embolization with curative intent in the treatment of the early phase of a spontaneous cerebral hemorrhage in pediatric patients, and its efficacy needs to be compared with surgery at the same time risk factors for hemorrhage following early embolization in such patients need to be evaluated.

METHODS

From a pool of 80 pediatric (< 18 years) who had undergone treatment for ruptured AVM with hemorrhage at our center between July 2018 and July 2022, we identified 36 patients with spontaneous bleeding due to AVM. Out of which, 20 were treated solely by embolization (group 1), while the remaining patients were treated surgically (with and without adjuvant embolization) (group 2).

RESULT

Spetzler-Martin's grading of the lesion suggested seven lesions < 3 and 13 lesions ≥ 3 in the embolization group. Similarly, seven lesions were < 3 and nine ≥ 3 Spetzler-Martin grade in the surgery group. Incomplete embolization was associated with hemorrhage in two patients treated with curative intent and four patients treated with embolization as adjuvant in the surgery group (p = 0.01). On follow-up, 18 patients in the embolization group and 12 in the surgery group had Glasgow outcome scores ≥ 4 (p = 0.273).

CONCLUSION

In the pediatric age group, incomplete embolization is the significant risk factor for hemorrhage in AVMs treated after a hemorrhagic stroke. Embolization with curative intent is as effective as surgery in treating such lesions as adjuvant embolization with careful patient selection.