A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage

Zhuang, Dongzhou; Ren, Zhihui; Sheng, Jiangtao; Zheng, Zenan; Peng, Hui; Ou, Xiao-qing; Zhang, Yuan; Tian, Lu; Wang, Shousen; Li, Kangsheng; Chen, W

doi:10.1002/acn3.51789

Cited by 6 publications

(4 citation statements)

References 57 publications

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“…These previous findings are consistent with our results. The preoperative WFNS grade and H&H grade have been employed as predictive factors in previous models for predicting individual outcomes in aSAH patients, yielding favorable results [ 20 , 23 , 28 ].…”

Section: Discussionmentioning

confidence: 99%

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Textbook Outcomes Among Patients with Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment

Liu,

Tan,

Wei

et al. 2024

Neurol Ther

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Introduction The case fatality rate among patients with aneurysmal subarachnoid hemorrhage (aSAH) has decreased progressively, with numerous patients subjected to contemporary paradigms that minimize the use of agonizing therapeutic processes. The concept of the “Textbook Outcome” (TO), a composite outcome that highlights numerous favorable outcomes, was developed in the context of gastrointestinal tumor surgeries and expeditiously extended across diverse surgical spheres. The aim of this study was to explore the factors hindering the achievement of optimal prognoses in postinterventional aSAH patients, employ textbook outcomes, and establish predictive models. Methods We conducted a retrospective review of data from 1270 aSAH patients who received endovascular treatment between 2012 and 2018. We delineated an exemplary TO within the aSAH domain, characterized by favorable clinical results, minimal complications, and the absence of retreatments. This TO-oriented approach is explained within the manuscript. Results The findings revealed that preoperative intraventricular hemorrhage (IVH), preoperative Hunt and Hess grade (H&H) ≥ 3, World Federation of Neurosurgical Societies (WFNS) grade ≥ 3, the presence of blebs on the aneurysm, aneurysms situated at branching sites, and non-stent-assisted endovascular intervention were the strongest risk factors for not achieving textbook outcomes (non-“Textbook Outcome” [N-TO]). Decision curve analysis and calibration analyses revealed strong concordance between the predictions of the N-TO nomogram model and the actual observations. Conclusions Treatment Outcomes hold significant practical value in clinical studies of aSAH patients receiving endovascular treatment. The likelihood of N-TOs was predicted by IVH, H&H grade ≥ 3, WFNS grade ≥ 2, presence o f bleb on the aneurysm, and aneurysms located at branching sites.

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Section: Discussionmentioning

confidence: 99%

“…Nomograms are considered a reliable instrument for personalized risk assessment. Clinically, the Nutritional Risk Screening 2002 (NRS-2002) tool has been harnessed to predict the prognosis of aSAH and the outcomes of various surgeries, thus demonstrating its ability to predict aSAH accurately [ 18 – 20 ].…”

Section: Introductionmentioning

confidence: 99%

Textbook Outcomes Among Patients with Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment

Liu,

Tan,

Wei

et al. 2024

Neurol Ther

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“…Several predictive models have been developed to estimate the prognosis of SAH patients ( 18 – 20 ). However, the predictive models for short-term mortality in patients with SAH requiring mechanical ventilation are rarely reported.…”

Section: Discussionmentioning

confidence: 99%

“…Model A included variables that were easily available at admission or within 24 h, including GCS and SAPS II, and other parameters associated with poor prognosis, rebleeding, and Moreover, more effort is needed to improve the model and make it more accurate and practical. Several predictive models have been developed to estimate the prognosis of SAH patients (18)(19)(20). However, the predictive models for short-term mortality in patients with SAH requiring mechanical ventilation are rarely reported.…”

Section: Discussionmentioning

confidence: 99%

A nomogram for the prediction of short-term mortality in patients with aneurysmal subarachnoid hemorrhage requiring mechanical ventilation: a post-hoc analysis

Mei,

Shen,

Liu

2024

Front. Neurol.

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BackgroundAneurysmal subarachnoid hemorrhage (aSAH) is a devastating stroke subtype with high morbidity and mortality. Although several studies have developed a prediction model in aSAH to predict individual outcomes, few have addressed short-term mortality in patients requiring mechanical ventilation. The study aimed to construct a user-friendly nomogram to provide a simple, precise, and personalized prediction of 30-day mortality in patients with aSAH requiring mechanical ventilation.MethodsWe conducted a post-hoc analysis based on a retrospective study in a French university hospital intensive care unit (ICU). All patients with aSAH requiring mechanical ventilation from January 2010 to December 2015 were included. Demographic and clinical variables were collected to develop a nomogram for predicting 30-day mortality. The least absolute shrinkage and selection operator (LASSO) regression method was performed to identify predictors, and multivariate logistic regression was used to establish a nomogram. The discriminative ability, calibration, and clinical practicability of the nomogram to predict short-term mortality were tested using the area under the curve (AUC), calibration plot, and decision curve analysis (DCA).ResultsAdmission GCS, SAPS II, rebleeding, early brain injury (EBI), and external ventricular drain (EVD) were significantly associated with 30-day mortality in patients with aSAH requiring mechanical ventilation. Model A incorporated four clinical factors available in the early stages of the aSAH: GCS, SAPS II, rebleeding, and EBI. Then, the prediction model B with the five predictors was developed and presented in a nomogram. The predictive nomogram yielded an AUC of 0.795 [95% CI, 0.731–0.858], and in the internal validation with bootstrapping, the AUC was 0.780. The predictive model was well-calibrated, and decision curve analysis further confirmed the clinical usefulness of the nomogram.ConclusionWe have developed two models and constructed a nomogram that included five clinical characteristics to predict 30-day mortality in patients with aSAH requiring mechanical ventilation, which may aid clinical decision-making.

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A dynamic nomogram for predicting intraoperative brain bulge during decompressive craniectomy in patients with traumatic brain injury: a retrospective study

Zhuang,

Li,

Xie

et al. 2023

International Journal of Surgery

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Objective: The aim of this paper is to investigate the risk factors associated with intraoperative brain bulge (IOBB), especially the computed tomography (CT) value of the diseased lateral transverse sinus, and to develop a reliable predictive model to alert neurosurgeons to the possibility of IOBB. Methods: A retrospective analysis was performed on 937 patients undergoing traumatic decompressive craniectomy. A total of 644 patients from Fuzong Clinical Medical College of Fujian Medical University were included in the development cohort, and 293 patients from the First Affiliated Hospital of Shantou University Medical College were included in the external validation cohort. Univariate and multifactorial logistic regression analyses identified independent risk factors associated with IOBB. The logistic regression models consisted of independent risk factors, and receiver operating characteristic curves, calibration, and decision curve analyses were used to assess the performance of the models. Various machine learning models were used to compare with the logistic regression model and analyze the importance of the factors, which were eventually jointly developed into a dynamic nomogram for predicting IOBB and published online in the form of a simple calculator. Results: IOBB occurred in 93/644 (14.4%) patients in the developmental cohort and 47/293 (16.0%) in the validation cohort. Univariate and multifactorial regression analyses showed that age, subdural hematoma, contralateral fracture, brain contusion, and CT value of the diseased lateral transverse sinus were associated with IOBB. A logistic regression model (full model) consisting of the above risk factors had excellent predictive power in both the development cohort [area under the curve (AUC)=0.930] and the validation cohort (AUC=0.913). Among the four machine learning models, the AdaBoost model showed the best predictive value (AUC=0.998). Factors in the AdaBoost model were ranked by importance and combined with the full model to create a dynamic nomogram for clinical application, which was published online as a practical and easy-to-use calculator. Conclusions: The CT value of the diseased lateral transverse is an independent risk factor and a reliable predictor of IOBB. The online dynamic nomogram formed by combining logistic regression analysis models and machine learning models can more accurately predict the possibility of IOBBs in patients undergoing traumatic decompressive craniectomy.

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A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage

Cited by 6 publications

References 57 publications

Textbook Outcomes Among Patients with Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment

Textbook Outcomes Among Patients with Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment

A nomogram for the prediction of short-term mortality in patients with aneurysmal subarachnoid hemorrhage requiring mechanical ventilation: a post-hoc analysis

A dynamic nomogram for predicting intraoperative brain bulge during decompressive craniectomy in patients with traumatic brain injury: a retrospective study

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