Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage

Mader, Marius Marc-Daniel; Piffko, Andras; Dengler, Nora; Ricklefs, Franz; Dührsen, Lasse; Schmidt, Nils Ole; Regelsberger, Jan; Westphal, Manfred; Wolf, Stefan; Czorlich, Patrick

doi:10.1038/s41598-020-61513-1

Cited by 20 publications

(21 citation statements)

References 30 publications

(33 reference statements)

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“…Similarly, previously described parameters predicting the mortality and outcome in SAH patients were examined such as age, WFNS score, pupil status, and rebleed (14)(15)(16). All these factors reported in the literature, as well as aneurysm location, were also shown to be predictive in our analysis.…”

Section: Discussionmentioning

confidence: 63%

Aneurysm Location Affects Clinical Course and Mortality in Patients With Subarachnoid Hemorrhage

et al. 2022

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ObjectiveThe influence of preexisting factors on the clinical course of patients with subarachnoid hemorrhage (SAH), such as patient age, arterial hypertension, and aneurysm characteristics, is still a matter of debate. However, the specific impact of the exact aneurysm location has not received adequate attention. Therefore, the aim of this study was to investigate the influence of aneurysm location as a preexisting factor on the clinical course and mortality.MethodsThe data of consecutive patients with aneurysmal SAH who were treated from October 2010 to July 2020 were retrospectively analyzed. We distinguished four aneurysm locations: the anterior complex, internal carotid artery (ICA), middle cerebral artery (MCA), and posterior circulation. Logistic regression analysis and receiver operating characteristics were used to investigate the influence of aneurysm location on the occurrence of acute hydrocephalus, Delayed Cerebral Ischemia (DCI), neurological outcome, and in-hospital mortality. Neurological outcome was assessed 3 months after discharge using the Glasgow Outcome Scale.ResultsA total of 603 patients were included in this study. Patients with MCA aneurysms were 2.52 times less likely to develop acute hydrocephalus compared to patients with anterior complex aneurysms (p = 0.001). Delayed cerebral ischemia occurred most frequently in patients with an anterior complex aneurysm and least frequently in MCA aneurysms (p = 0.014). In ICA aneurysms, mortality was 2.56-fold higher than in patients with aneurysms of the anterior complex (p = 0.006). An additional ROC analysis showed a good prediction for in-hospital mortality when taking the aneurysm's location into account [AUC.855 (CI.817 −0.893)].ConclusionsThe aneurysm's location proved to be a significant predictor of acute hydrocephalus, DCI, and in-hospital mortality, demonstrating the impact of this preexisting biological factor on the course of SAH.

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Section: Discussionmentioning

confidence: 63%

Aneurysm Location Affects Clinical Course and Mortality in Patients With Subarachnoid Hemorrhage

et al. 2022

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“…Cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI) remain common and severe complications after aneurysmal subarachnoid hemorrhage (SAH) and are jointly responsible for the high morbidity and mortality, which is still above 20% in recent publications (1)(2)(3). About 30% of all patients develop DCI in the course of SAH (4).…”

Section: Introductionmentioning

confidence: 99%

Safety and Clinical Effects of Switching From Intravenous to Oral Nimodipine Administration in Aneurysmal Subarachnoid Hemorrhage

Göttsche¹,

Schweingruber²,

Groth³

et al. 2021

Front. Neurol.

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Objective: Several guidelines recommend oral administration of nimodipine as vasospasm prophylaxis after aneurysmal subarachnoid hemorrhage (SAH). However, in clinical practice, the drug is administered orally and intravenously (i.v.), depending on clinical conditions and local treatment regimens. We have therefore investigated the safety and clinical effects of switching from i.v. to oral nimodipine therapy.Methods: Patients with aneurysmal SAH between January 2014 and April 2018 and initial i.v. nimodipine therapy, which was subsequently switched to oral administration, were included in this retrospective study. Transcranial Doppler sonography (TCD) of the vessels of the anterior circulation was performed daily. The occurrence of vasospasm and infarction during the overall course of the treatment was recorded. Statistical level of significance was set to p < 0.05.Results: A total of 133 patients (mean age 55.8 years, 65% female) initially received nimodipine i.v. after aneurysmal SAH, which was subsequently switched to oral administration after a mean of 12 days. There were no significant increases in mean flow velocities on TCD after the switch from i.v. to oral nimodipine administration regarding the anterior cerebral artery. For the middle cerebral artery, an increase from 62.36 to 71.78 cm/sec could only be detected in the subgroup of patients with infarction. There was no clustering of complicating events such as new-onset vasospasm or infarction during or after the switch.Conclusions: Our results do not point to any safety concerns when switching nimodipine from initial i.v. to oral administration. Switching was neither associated with clinically relevant increases in TCD velocities nor other relevant adverse events.

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“…The majority of previously established aSAH outcome prediction models are based on neurological deficits on admission and radiographic features, such as thickness of subarachnoid blood clots and the presence of IVH or ICH. However, more recent evidence suggests that other factors play a role in precise outcome prediction, such as patient age, pupil status, and aneurysm size and location [21,29]. The inclusion of a high number of variables is one of the main strengths of ML approaches.…”

Section: Discussionmentioning

confidence: 99%

Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores

et al. 2021

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Reliable prediction of outcomes of aneurysmal subarachnoid hemorrhage (aSAH) based on factors available at patient admission may support responsible allocation of resources as well as treatment decisions. Radiographic and clinical scoring systems may help clinicians estimate disease severity, but their predictive value is limited, especially in devising treatment strategies. In this study, we aimed to examine whether a machine learning (ML) approach using variables available on admission may improve outcome prediction in aSAH compared to established scoring systems. Combined clinical and radiographic features as well as standard scores (Hunt & Hess, WFNS, BNI, Fisher, and VASOGRADE) available on patient admission were analyzed using a consecutive single-center database of patients that presented with aSAH (n = 388). Different ML models (seven algorithms including three types of traditional generalized linear models, as well as a tree bosting algorithm, a support vector machine classifier (SVMC), a Naive Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net) were trained for single features, scores, and combined features with a random split into training and test sets (4:1 ratio), ten-fold cross-validation, and 50 shuffles. For combined features, feature importance was calculated. There was no difference in performance between traditional and other ML applications using traditional clinico-radiographic features. Also, no relevant difference was identified between a combined set of clinico-radiological features available on admission (highest AUC 0.78, tree boosting) and the best performing clinical score GCS (highest AUC 0.76, tree boosting). GCS and age were the most important variables for the feature combination. In this cohort of patients with aSAH, the performance of functional outcome prediction by machine learning techniques was comparable to traditional methods and established clinical scores. Future work is necessary to examine input variables other than traditional clinico-radiographic features and to evaluate whether a higher performance for outcome prediction in aSAH can be achieved.

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Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage

Cited by 20 publications

References 30 publications

Aneurysm Location Affects Clinical Course and Mortality in Patients With Subarachnoid Hemorrhage

Aneurysm Location Affects Clinical Course and Mortality in Patients With Subarachnoid Hemorrhage

Safety and Clinical Effects of Switching From Intravenous to Oral Nimodipine Administration in Aneurysmal Subarachnoid Hemorrhage

Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores

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