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Neurologic deficits are common after surgery for subarachnoid hemorrhage due to a ruptured intracranial aneurysm. In this study, the use of mild intraoperative hypothermia (target body temperature, 33°C) to prevent neurologic deficits after surgery had no protective effect. However, the patients enrolled in this study were at relatively low risk, and it is unclear whether intraoperative hypothermia may have benefits in higher-risk patients. In this study, the use of mild intraoperative hypothermia to prevent neurologic deficits after surgery had no protective effect in patients at relatively low risk. New neurologic deficits are common after intracranial vascular surgery and are due to factors such as brain retraction, vessel occlusion, and intraoperative hemorrhage. Thus, there have been many efforts to protect the brain from such insults. 1 – 6 The use of systemic hypothermia as a protective adjunct in neurosurgery was first reported in 1955 7 but was largely abandoned during the 1970s and 1980s. Interest in this approach was rekindled after the demonstration in the laboratory that the induction of mild hypothermia (a temperature of approximately 33 to 35°C) improved the outcome of ischemic and traumatic insults. 8 – 11 This finding coincided with . . .

Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables. We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90-99), positive predictive value (PPV) 98% (93-100), negative predictive value (NPV) 100% (95-100); intracerebral hemorrhage: SE 100% (97-100), SP 98% (91-100), PPV 98% (94-100), NPV 100% (95-100); other and unspecified intracranial hemorrhage: SE 100% (97-100), SP 96% (90-99), PPV 98% (93-100), NPV 100% (95-100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94-100), SP 66 (57-75), PPV 70% (61-77), NPV 99% (93-100); occlusion of cerebral arteries: SE 100% (97-100), SP 87% (78-93), PPV 91% (84-95), NPV 100% (95-100); acute, but ill-defined, cerebrovascular disease: SE 100% (97-100), SP 78% (69-86), PPV % 83 (75-89), NPV 100% (95-100). Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.

The pharmacokinetics of nimodipine following enteral administration in the early phase after subarachnoid haemorrhage (SAH) has not been described. If a sufficient absorption could be achieved with enterally administered nimodipine, this would be more feasible dosage form and result in a significant reduction in pharmaceutical costs given that the parenteral formulation of nimodipine currently used is tenfold more expensive than the enteral formulation. This was a pilot study in which 17 patients with aneurysmal SAH were randomly assigned to receive nimodipine within 24 h after initial bleeding either as an 60 mg tablet/suspension at 4-h intervals, or as a continuous intravenous infusion of 2 mg/h. Serum nimodipine concentrations were measured during the 4 h following the first dose, and at 24 and 72 h on a validated gas chromatography mass spectrometer (GC-MS). Nimodipine AUC values (expressed in mug min/ml) were lower in the eight SAH patients receiving enteral nimodipine [AUC(0-4) range: 0.13-5.4 (median: 0.32); AUC(24-28) range: 0.16-6.1 (0.71); AUC(72-76) range: 0.47-20.6 (1.9)] than in the nine patients receiving a continuous intravenous infusion of nimodipine [AUC(0-4) range: 2.4-4.9 (3.4), p=0.059; AUC(24-28) range: 4.7-10.3 (7.3), p=0.001; AUC(72-76) range: 3.4-8.6 (6.9), p=0.001]. In three of five good-grade SAH patients receiving nimodipine tablets the AUC values were comparable to those of the intravenous administration, but in two good-grade patients with tablets and in all three poor-grade (Hunt&Hess, grade IV) SAH patients receiving the suspension, the rate and extent of nimodipine absorption was negligible. This pilot study indicates that the rate and extent of nimodipine absorption following enteral administration in some acute SAH patients could be negligible, and this may particularly be the case in patients with a decreased level of consciousness.

Aneurysmal subarachnoid hemorrhage (aSAH) is an heterogeneous disease with variable outcomes, even among patients with similar clinical and radiological severity. Additional research is needed to better stratify aSAH patients. To identify distinct clinical subphenotypes of aSAH, we applied clustering analysis using clinical, radiological, and laboratory data. We conducted a retrospective cohort study of adult patients with aSAH admitted to the ICU between 2010 and 2021. K-means clustering was applied to standardized demographic, clinical, and laboratory variables collected at admission. Principal component analysis was used for dimensionality reduction and visualization. Additionally, we analyzed whether these clusters were associated with serum biomarkers (S100B, HMGB1, and TLR4) in a subset of patients. The study included 511 patients with aSAH. Two distinct subphenotypes were identified: a High-Risk Cluster (n = 301, 58.9 %) characterized by severe systemic complications, and higher mortality, and a Low-Risk Cluster (n = 210, 41.1 %) with less severe symptoms and better outcomes. Serum S100B levels were significantly elevated in the High-Risk Cluster (0.077 [0.056–0.179] vs. 0.055 [0.040–0.079] μg/L, p = 0.008) and showed moderate discriminatory power (AUC = 0.72). Clustering analysis revealed two aSAH subphenotypes associated with DCI, mortality and functional. Integrating early clinical and biomarker data could enhance patient stratification. •Automated clustering identified two distinct subphenotypes in a SAH: High-Risk Cluster and Low-Risk Cluster.•Clustering was based on routinely available clinical, radiological, and biochemical data.•High-Risk cluster showed higher mortality and delayed cerebral ischemia (p = 0.002).•Biomarker (S100B) levels supported biological divergence between identified subphenotypes.•Findings enable early, data-driven risk stratification and personalized management in aSAH.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA is the bulging of a blood vessel caused by a weakening of its wall. This bulge can rupture and, in most cases, cause internal bleeding. In most cases, internal bleeding leads to death or other fatal consequences. Therefore, the development of an automated system for detecting IA is needed to help physicians make more accurate diagnoses. For this reason, we have focused on this problem. In this paper, we propose a 2D Convolutional Neural Network (CNN) based on a network commonly used for data classification in medicine. In addition to our proposed network, we also tested ResNet 50, ResNet 101 and ResNet 152 on a publicly available dataset. In this case, ResNet 152 achieved better results than our proposed network, but our network was significantly smaller and the classifications took significantly less time. Our proposed network achieved an overall accuracy of 98%. This result was achieved on a dataset consisting of 611 images. In addition to the mentioned networks, we also experimented with the VGG network, but it was not suitable for this type of data and achieved only 20%. We compare the results in this work with neural networks that have been verified by the scientific community, and we believe that the results obtained by us can help in the creation of an automated system for the detection of IA.

The objective of the study is to externally validate three primary subarachnoid hemorrhage (pSAH) identification models. We evaluated three models that identify pSAH using recursive partitioning (A), logistic regression (B), and a prevalence-adjusted logistic regression(C), respectively. Blinded chart review and/or linkage to existing registries determined pSAH status. We included all patients aged ≥18 in four participating center registries or whose discharge abstracts contained ≥1 administrative codes of interest between January 1, 2012 and December 31, 2013. A total of 3,262 of 193,190 admissions underwent chart review (n = 2,493) or registry linkage (n = 769). A total of 657 had pSAH confirmed (20·1% sample, 0·34% admissions). The sensitivity, specificity, and positive predictive value (PPV) were as follows: i) model A: 98·3% (97·0–99·2), 53·5% (51·5–55·4), and 34·8% (32·6–37·0); ii) model B (score ≥6): 98·0% (96·6–98·9), 47·4% (45·5–49·4), and 32·0% (30·0–34·1); and iii) model C (score ≥2): 95·7% (93·9–97·2), 85·5% (84·0–86·8), and 62·3 (59·3–65·3), respectively. Model C scores of 0, 1, 2, 3, or 4 had probabilities of 0·5% (0·2–1·5), 1·5% (1·0–2·2), 24·8% (21·0–29·0), 90·0% (86·8–92·0), and 97·8% (88·7–99·6), without significant difference between centers (P = 0·86). The PPV of the International Classification of Diseases code (I60) was 63·0% (95% confidence interval: 60·0–66·0). All three models were highly sensitive for pSAH. Model C could be used to adjust for misclassification bias. •This is the largest multicentre validation of the International Classification of Diseases code for subarachnoid hemorrhage (SAH).•Present alternative methods with wide generalizability for identifying SAH cohorts.•These models provide a fast and cost-effective way to identify patients with SAH.•These models facilitate future research and could impact bedside practice.•Illustrate the limitations of SAH cohorts identified by solitary diagnostic codes.

Abstract BACKGROUND Seizure is a significant complication in patients under acute admission for aneurysmal SAH and could result in poor outcomes. Treatment strategies to optimize management will benefit from methods to better identify at-risk patients. OBJECTIVE To develop and validate a risk score for convulsive seizure during acute admission for SAH. METHODS A risk score was developed in 1500 patients from a single tertiary hospital and externally validated in 852 patients. Candidate predictors were identified by systematic review of the literature and were included in a backward stepwise logistic regression model with in-hospital seizure as a dependent variable. The risk score was assessed for discrimination using the area under the receiver operator characteristics curve (AUC) and for calibration using a goodness-of-fit test. RESULTS The SAFARI score, based on 4 items (age ≥ 60 yr, seizure occurrence before hospitalization, ruptured aneurysm in the anterior circulation, and hydrocephalus requiring cerebrospinal fluid diversion), had AUC = 0.77, 95% confidence interval (CI): 0.73-0.82 in the development cohort. The validation cohort had AUC = 0.65, 95% CI 0.56-0.73. A calibrated increase in the risk of seizure was noted with increasing SAFARI score points. CONCLUSION The SAFARI score is a simple tool that adequately stratified SAH patients according to their risk for seizure using a few readily derived predictor items. It may contribute to a more individualized management of seizure following SAH.

Numerous systems are reported for grading the clinical condition of patients following subarachnoid hemorrhage (SAH). The literature was reviewed for articles pertaining to the grading of such patients, including publications on the Hunt and Hess Scale, Fisher Scale, Glasgow Coma Score (GCS), and World Federation of Neurological Surgeons Scale. This article reviews the advantages and limitations of these scales as well as more recent proposals for other grading systems based on these scales with or without addition of other factors known to be prognostic for outcome after SAH. There remain substantial deficits in the literature regarding grading of patients with SAH. Most grading scales were derived retrospectively, and the intra- and interobserver variability has seldom been assessed. Inclusion of additional factors increases the complexity of the scale, possibly making it less likely to be adopted for routine usage and increasing (only marginally in some cases) the ability to predict prognosis. Until further data are available, it is recommended that publications on patients with SAH report at least the admission GCS as well as factors commonly known to influence prognosis, such as age, pre-existing hypertension, the amount of blood present on admission computed tomography, time of admission after SAH, aneurysm location and size, presence of intracerebral or intraventricular hemorrhage, and blood pressure at admission.

Microdialysis is used in many European neurointensive care units to monitor brain chemistry in patients suffering subarachnoid hemorrhage (SAH) or traumatic brain injury (TBI). We present a consensus agreement achieved at a meeting in Stockholm by a group of experienced users of microdialysis in neurointensive care, defining the use of microdialysis, placement of catheters, unreliable values, chemical markers, and clinical use in SAH and in TBI. As microdialysis is maturing into a clinically useful technique for early detection of cerebral ischemia and secondary brain damage, there is a need to following such definition regarding when and how to use microdialysis after SAH and TBI.

ObjectivesTo develop new nomograms by adding ECG changes (ST depression or tall T wave) and age to three conventional scoring systems, namely, World Federation of Neurosurgical Societies (WFNS) scale, Hunt and Hess (HH) system and Fisher scale, that can predict prognosis in patients with subarachnoid haemorrhage (SAH) using our preliminary research results and to perform external validation of the three new nomograms.DesignRetrospective, observational studySettingEmergency departments (ED) of two university-affiliated tertiary hospital between January 2009 and March 2015.ParticipantsAdult patients with SAH were enrolled. Exclusion criteria were age <19 years, no baseline ECG, cardiac arrest on arrival, traumatic SAH, referral from other hospital and referral to other hospitals from the ED.Primary outcome measuresThe 6 month prognosis was assessed using the Glasgow Outcome Scale (GOS). We defined a poor outcome as a GOS score of 1, 2 or 3.ResultsA total of 202 patients were included for analysis. From the preliminary study, age, ECG changes (ST depression or tall T wave), and three conventional scoring systems were selected to predict prognosis in patients with SAH using multi-variable logistic regression. We developed simplified nomograms using these variables. Discrimination of the developed nomograms including WFNS scale, HH system and Fisher scale was superior to those of WFNS scale, HH system and Fisher scale (0.912 vs 0.813; p<0.001, 0.913 vs 0.826; p<0.001, and 0.885 vs 0.746; p<0.001, respectively). The calibration plots showed excellent agreement. In the external validation, the discrimination of the newly developed nomograms incorporating the three scoring systems was also good, with an area under the receiver-operating characteristic curve value of 0.809, 0.812 and 0.772, respectively.ConclusionsWe developed and externally validated new nomograms using only three independent variables. Our new nomograms were superior to the WFNS scale, HH systems, and Fisher scale in predicting prognosis and are readily available.