scholarly journals Prediction of Outcome After Aneurysmal Subarachnoid Hemorrhage

Stroke ◽  
2019 ◽  
Vol 50 (4) ◽  
pp. 837-844 ◽  
Author(s):  
Carlina E. van Donkelaar ◽  
Nicolaas A. Bakker ◽  
Jaqueline Birks ◽  
Nic J.G.M. Veeger ◽  
Jan D.M. Metzemaekers ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Operating Characteristic ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Characteristic Curve ◽  
External Validation ◽  
World Federation ◽  
Final Model ◽  
Fisher Grade ◽  
Temporal Validation ◽  
Grading Scale

Background and Purpose— Early prediction of clinical outcome after aneurysmal subarachnoid hemorrhage (aSAH) is still lacking accuracy. In this observational cohort study, we aimed to develop and validate an accurate bedside prediction model for clinical outcome after aSAH, to aid decision-making at an early stage. Methods— For the development of the prediction model, a prospectively kept single-center cohort of 1215 aSAH patients, admitted between 1998 and 2014, was used. For temporal validation, a prospective cohort of 224 consecutive aSAH patients from the same center, admitted between 2015 and 2017, was used. External validation was performed using the ISAT (International Subarachnoid Aneurysm Trial) database (2143 patients). Primary outcome measure was poor functional outcome 2 months after aSAH, defined as modified Rankin Scale score 4–6. The model was constructed using multivariate regression analyses. Performance of the model was examined in terms of discrimination and calibration. Results— The final model included 4 predictors independently associated with poor outcome after 2 months: age, World Federation of Neurosurgical Societies grade after resuscitation, aneurysm size, and Fisher grade. Temporal validation showed high discrimination (area under the receiver operating characteristic curve, 0.90; 95% CI, 0.85–0.94), external validation showed fair to good discrimination (area under the receiver operating characteristic curve, 0.73; 95% CI, 0.70–0.76). The model showed satisfactory calibration in both validation cohorts. The SAFIRE grading scale was derived from the final model: size of the aneurysm, age, Fisher grade, world federation of neurosurgical societies after resuscitation. Conclusions— The SAFIRE grading scale is an accurate, generalizable, and easily applicable model for early prediction of clinical outcome after aSAH.

scholarly journals Radiodensity of intraventricular hemorrhage associated with aneurysmal subarachnoid hemorrhage may be a negative predictor of outcome

2018 ◽  
Vol 128 (4) ◽  
pp. 1032-1036 ◽  
Author(s):  
Ha Son Nguyen ◽  
Luyuan Li ◽  
Mohit Patel ◽  
Shekar Kurpad ◽  
Wade Mueller
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Clinical Outcome ◽  
Intraventricular Hemorrhage ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Characteristic Curve ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Ventricular System ◽  
Fisher Grade ◽  
Gcs Score

OBJECTIVEThe presence, extent, and distribution of intraventricular hemorrhage (IVH) have been associated with negative outcomes in aneurysmal subarachnoid hemorrhage (SAH). Several qualitative scores (Fisher grade, LeRoux score, and Graeb score) have been established for evaluating SAH and IVH. However, no study has assessed the radiodensity within the ventricular system in aneurysmal SAH patients with IVH. Prior studies have suggested that hemorrhage with a higher radiodensity, as measured by CT Hounsfield units, can cause more irritation to brain parenchyma. Therefore, the authors set out to investigate the relationship between the overall radiodensity of the ventricular system in aneurysmal SAH patients with IVH and their clinical outcome scores.METHODSThe authors reviewed the records of 101 patients who were admitted to their institution with aneurysmal SAH and IVH between January 2011 and July 2015. The following data were collected: age, sex, Glasgow Coma Scale (GCS) score, Hunt and Hess grade, extent of SAH (none, thin, or thick/localized), aneurysm location, and Glasgow Outcome Scale (GOS) score. To evaluate the ventricular radiodensity, the initial head CT scan was loaded into OsiriX MD. The ventricular system was manually selected as the region of interest (ROI) through all pertinent axial slices. After this, an averaged ventricular radiodensity was calculated from the ROI by the software. GOS scores were dichotomized as 1–3 and 4–5 subgroups for analysis.RESULTSOn univariate analysis, younger age, higher GCS score, lower Hunt and Hess grade, and lower ventricular radiodensity significantly correlated with better GOS scores (all p < 0.05). Subsequent multivariate analysis yielded age (OR 0.936, 95% CI 0.895–0.979), GCS score (OR 3.422, 95% CI 1.9–6.164), and ventricular density (OR 0.937, 95% CI 0.878–0.999) as significant independent predictors (p < 0.05). A receiver operating characteristic curve yielded 12.7 HU (area under the curve 0.625, p = 0.032, sensitivity = 0.591, specificity = 0.596) as threshold between GOS scores of 1–3 and 4–5.CONCLUSIONSThis study suggests that the ventricular radiodensity in aneurysmal SAH patients with IVH, along with GCS score and age, may serve as a predictor of clinical outcome.

scholarly journals External validation of the Practical Risk Chart for the prediction of delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage

2017 ◽  
Vol 126 (5) ◽  
pp. 1530-1536 ◽  
Author(s):  
Paul M. Foreman ◽  
Michelle H. Chua ◽  
Mark R. Harrigan ◽  
Winfield S. Fisher ◽  
R. Shane Tubbs ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Cerebral Ischemia ◽  
Operating Characteristic ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Characteristic Curve ◽  
External Validation ◽  
Delayed Cerebral Ischemia ◽  
Model Discrimination ◽  
Operating Characteristic Curve ◽  
Best Fit

OBJECTIVEDelayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH) occurs in approximately 30% of patients. The Practical Risk Chart was developed to predict DCI based on admission characteristics; the authors seek to externally validate and critically appraise this prediction tool.METHODSA prospective cohort of aSAH patients was used to externally validate the previously published Practical Risk Chart. The model consists of 4 variables: clinical condition on admission, amount of cisternal and intraventricular blood on CT, and age. External validity was assessed using logistic regression. Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC).RESULTSIn a cohort of 125 patients with aSAH, the Practical Risk Chart adequately predicted DCI, with an AUC of 0.66 (95% CI 0.55–0.77). Clinical grade on admission and amount of intracranial blood on CT were the strongest predictors of DCI and clinical vasospasm. The best-fit model used a combination of the Hunt and Hess grade and the modified Fisher scale to yield an AUC of 0.76 (95% CI 0.675–0.85) and 0.70 (95% CI 0.602–0.8) for the prediction of DCI and clinical vasospasm, respectively.CONCLUSIONSThe Practical Risk Chart adequately predicts the risk of DCI following aSAH. However, the best-fit model represents a simpler stratification scheme, using only the Hunt and Hess grade and the modified Fisher scale, and produces a comparable AUC.

Is Admission Lipoprotein-Associated Phospholipase A2 a Novel Predictor of Vasospasm and Outcome in Patients With Aneurysmal Subarachnoid Hemorrhage?

Neurosurgery ◽  
2019 ◽  
Vol 86 (1) ◽  
pp. 122-131 ◽  
Author(s):  
Chen-Yu Ding ◽  
Han-Pei Cai ◽  
Hong-Liang Ge ◽  
Liang-Hong Yu ◽  
Yuang-Xiang Lin ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Clinical Outcome ◽  
Phospholipase A2 ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Unfavorable Outcome ◽  
World Federation ◽  
Predictive Values ◽  
Poor Grade ◽  
Fisher Grade

Abstract BACKGROUND The relationships between lipoprotein-associated phospholipase A2 (Lp-PLA2) level, vasospasm, and clinical outcome of patients with aneurysmal subarachnoid hemorrhage (aSAH) are still unclear. OBJECTIVE To identify the associations between admission Lp-PLA2 and vasospasm following subarachnoid hemorrhage and the clinical outcome of aSAH. METHODS A total of 103 aSAH patients who had Lp-PLA2 level obtained within 24 h postbleeding were included. The relationships between Lp-PLA2 level, vasospasm, and clinical outcome were analyzed. RESULTS Vasospasm was observed in 52 patients (50.49%). Patients with vasospasm had significantly higher Lp-PLA2 level than those without (P &lt; .001). Both modified Fisher grade (P = .014) and Lp-PLA2 level (P &lt; .001) were significant predictors associated with vasospasm. The Z test revealed that power of Lp-PLA2 was significantly higher than that of modified Fisher grade in predicting vasospasm (Z = 2.499, P = .012). At 6-mo follow-up, 44 patients (42.72%) had unfavorable outcome and 36 patients (34.95%) died. The World Federation of Neurosurgical Societies (WFNS) grade and Lp-PLA2 level were both significant predictors associated with 6-mo unfavorable outcome and mortality (all P &lt; .001). The predictive values of Lp-PLA2 for unfavorable outcome and mortality at 6-mo tended to be lower than those of the WFNS grade, but the differences were not statistically significant (P = .366 and 0.115, respectively). Poor-grade patients having Lp-PLA2 &gt; 200 μg/L had significantly worse 6-mo survival rate than poor-grade patients having Lp-PLA2 ≤ 200 μg/L (P = .001). CONCLUSION The Lp-PLA2 might be useful as a novel predictor in aSAH patients. A total of 30 poor-grade patients; those with elevated Lp-PLA2 level have higher risk of 6-mo mortality compared to those without.

Three plasma-based microRNAs as potent diagnostic biomarkers for endometrial cancer

2021 ◽  
pp. 1-12
Author(s):  
Xingchen Fan ◽  
Minmin Cao ◽  
Cheng Liu ◽  
Cheng Zhang ◽  
Chunyu Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
External Validation ◽  
Diagnostic Value ◽  
Diagnostic Biomarkers ◽  
Non Invasive ◽  
Polymerase Chain ◽  
Public Datasets ◽  
Plasma Mirnas

BACKGROUND: MicroRNAs (miRNAs), with noticeable stability and unique expression pattern in plasma of patients with various diseases, are powerful non-invasive biomarkers for cancer detection including endometrial cancer (EC). OBJECTIVE: The objective of this study was to identify promising miRNA biomarkers in plasma to assist the clinical screening of EC. METHODS: A total of 93 EC and 79 normal control (NC) plasma samples were analyzed using Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) in this four-stage experiment. The receiver operating characteristic curve (ROC) analysis was conducted to evaluate the diagnostic value. Additionally, the expression features of the identified miRNAs were further explored in tissues and plasma exosomes samples. RESULTS: The expression of miR-142-3p, miR-146a-5p, and miR-151a-5p was significantly overexpressed in the plasma of EC patients compared with NCs. Areas under the ROC curve of the 3-miRNA signature were 0.729, 0.751, and 0.789 for the training, testing, and external validation phases, respectively. The diagnostic performance of the identified signature proved to be stable in the three public datasets and superior to the other miRNA biomarkers in EC diagnosis. Moreover, the expression of miR-151a-5p was significantly elevated in EC plasma exosomes. CONCLUSIONS: A signature consisting of 3 plasma miRNAs was identified and showed potential for the non-invasive diagnosis of EC.

scholarly journals Development and Verification of a Deep Learning Algorithm to Evaluate Small-Bowel Preparation Quality

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1127
Author(s):  
Ji Hyung Nam ◽  
Dong Jun Oh ◽  
Sumin Lee ◽  
Hyun Joo Song ◽  
Yun Jeong Lim
Keyword(s):  
Deep Learning ◽  
Small Bowel ◽  
Scoring System ◽  
Operating Characteristic ◽  
Clinical Evidence ◽  
Learning Algorithm ◽  
Characteristic Curve ◽  
External Validation ◽  
Test Results ◽  
Deep Learning Algorithm

Capsule endoscopy (CE) quality control requires an objective scoring system to evaluate the preparation of the small bowel (SB). We propose a deep learning algorithm to calculate SB cleansing scores and verify the algorithm’s performance. A 5-point scoring system based on clarity of mucosal visualization was used to develop the deep learning algorithm (400,000 frames; 280,000 for training and 120,000 for testing). External validation was performed using additional CE cases (n = 50), and average cleansing scores (1.0 to 5.0) calculated using the algorithm were compared to clinical grades (A to C) assigned by clinicians. Test results obtained using 120,000 frames exhibited 93% accuracy. The separate CE case exhibited substantial agreement between the deep learning algorithm scores and clinicians’ assessments (Cohen’s kappa: 0.672). In the external validation, the cleansing score decreased with worsening clinical grade (scores of 3.9, 3.2, and 2.5 for grades A, B, and C, respectively, p < 0.001). Receiver operating characteristic curve analysis revealed that a cleansing score cut-off of 2.95 indicated clinically adequate preparation. This algorithm provides an objective and automated cleansing score for evaluating SB preparation for CE. The results of this study will serve as clinical evidence supporting the practical use of deep learning algorithms for evaluating SB preparation quality.

Variation of patient characteristics, management, and outcome with timing of surgery for aneurysmal subarachnoid hemorrhage

2011 ◽  
Vol 114 (4) ◽  
pp. 1045-1053 ◽  
Author(s):  
Kelly B. Mahaney ◽  
Michael M. Todd ◽  
James C. Torner
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Management Practices ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Timing Of Surgery ◽  
Early Surgery ◽  
Outcome Variable ◽  
Optimal Time ◽  
World Federation ◽  
Time Interval ◽  
Fisher Grade

ObjectThe past 30 years have seen a shift in the timing of surgery for aneurysmal subarachnoid hemorrhage (SAH). Earlier practices of delayed surgery that were intended to avoid less favorable surgical conditions have been replaced by a trend toward early surgery to minimize the risks associated with rebleeding and vasospasm. Yet, a consensus as to the optimal timing of surgery has not been reached. The authors hypothesized that earlier surgery, performed using contemporary neurosurgical and neuroanesthesia techniques, would be associated with better outcomes when using contemporary management practices, and sought to define the optimal time interval between SAH and surgery.MethodsData collected as part of the Intraoperative Hypothermia for Aneurysm Surgery Trial (IHAST) were analyzed to investigate the relationship between timing of surgery and outcome at 3 months post-SAH. The IHAST enrolled 1001 patients in 30 neurosurgical centers between February 2000 and April 2003. All patients had a radiographically confirmed SAH, were World Federation of Neurosurgical Societies Grades I–III at the time of surgery, and underwent surgical clipping of the presumed culprit aneurysm within 14 days of the date of hemorrhage. Patients were seen at 90-day follow-up visits. The primary outcome variable was a Glasgow Outcome Scale score of 1 (good outcome). Intergroup differences in baseline, intraoperative, and postoperative variables were compared using the Fisher exact tests. Variables reported as means were compared with ANOVA. Multiple logistic regression was used for multivariate analysis, adjusting for covariates. A p value of less than 0.05 was considered to be significant.ResultsPatients who underwent surgery on Days 1 or 2 (early) or Days 7–14 (late) (Day 0 = date of SAH) fared better than patients who underwent surgery on Days 3–6 (intermediate). Specifically, the worst outcomes were observed in patients who underwent surgery on Days 3 and 4. Patients who had hydrocephalus or Fisher Grade 3 or 4 on admission head CT scans had better outcomes with early surgery than with intermediate or late surgery.ConclusionsEarly surgery, in good-grade patients within 48 hours of SAH, is associated with better outcomes than surgery performed in the 3- to 6-day posthemorrhage interval. Surgical treatment for aneurysmal SAH may be more hazardous during the 3- to 6-day interval, but this should be weighed against the risk of rebleeding.

scholarly journals Elevated Baseline C-Reactive Protein as a Predictor of Outcome After Aneurysmal Subarachnoid Hemorrhage

Neurosurgery ◽  
2015 ◽  
Vol 77 (5) ◽  
pp. 786-793 ◽  
Author(s):  
◽  
Carole L. Turner ◽  
Karol Budohoski ◽  
Christopher Smith ◽  
Peter J. Hutchinson ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
White Blood Cells ◽  
Cerebral Injury ◽  
World Federation ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Poor Outcome ◽  
Fisher Grade ◽  
Good Grade

Abstract BACKGROUND: There remains a proportion of patients with unfavorable outcomes after aneurysmal subarachnoid hemorrhage, of particular relevance in those who present with a good clinical grade. A forewarning of those at risk provides an opportunity towards more intensive monitoring, investigation, and prophylactic treatment prior to the clinical manifestation of advancing cerebral injury. OBJECTIVE: To assess whether biochemical markers sampled in the first days after the initial hemorrhage can predict poor outcome. METHODS: All patients recruited to the multicenter Simvastatin in Aneurysmal Hemorrhage Trial (STASH) were included. Baseline biochemical profiles were taken between time of ictus and day 4 post ictus. The t-test compared outcomes, and a backwards stepwise binary logistic regression was used to determine the factors providing independent prediction of an unfavorable outcome. RESULTS: Baseline biochemical data were obtained in approximately 91% of cases from 803 patients. On admission, 73% of patients were good grade (World Federation of Neurological Surgeons grades 1 or 2); however, 84% had a Fisher grade 3 or 4 on computed tomographic scan. For patients presenting with good grade on admission, higher levels of C-reactive protein, glucose, and white blood cells and lower levels of hematocrit, albumin, and hemoglobin were associated with poor outcome at discharge. C-reactive protein was found to be an independent predictor of outcome for patients presenting in good grade. CONCLUSION: Early recording of C-reactive protein may prove useful in detecting those good grade patients who are at greater risk of clinical deterioration and poor outcome.

scholarly journals A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children

2020 ◽  
Vol 31 (6) ◽  
pp. 1348-1357 ◽  
Author(s):  
Ibrahim Sandokji ◽  
Yu Yamamoto ◽  
Aditya Biswas ◽  
Tanima Arora ◽  
Ugochukwu Ugwuowo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
External Validation ◽  
Health Record ◽  
Hospitalized Children ◽  
Operating Characteristic Curve ◽  
Electronic Health

BackgroundTimely prediction of AKI in children can allow for targeted interventions, but the wealth of data in the electronic health record poses unique modeling challenges.MethodsWe retrospectively reviewed the electronic medical records of all children younger than 18 years old who had at least two creatinine values measured during a hospital admission from January 2014 through January 2018. We divided the study population into derivation, and internal and external validation cohorts, and used five feature selection techniques to select 10 of 720 potentially predictive variables from the electronic health records. Model performance was assessed by the area under the receiver operating characteristic curve in the validation cohorts. The primary outcome was development of AKI (per the Kidney Disease Improving Global Outcomes creatinine definition) within a moving 48-hour window. Secondary outcomes included severe AKI (stage 2 or 3), inpatient mortality, and length of stay.ResultsAmong 8473 encounters studied, AKI occurred in 516 (10.2%), 207 (9%), and 27 (2.5%) encounters in the derivation, and internal and external validation cohorts, respectively. The highest-performing model used a machine learning-based genetic algorithm, with an overall receiver operating characteristic curve in the internal validation cohort of 0.76 [95% confidence interval (CI), 0.72 to 0.79] for AKI, 0.79 (95% CI, 0.74 to 0.83) for severe AKI, and 0.81 (95% CI, 0.77 to 0.86) for neonatal AKI. To translate this prediction model into a clinical risk-stratification tool, we identified high- and low-risk threshold points.ConclusionsUsing various machine learning algorithms, we identified and validated a time-updated prediction model of ten readily available electronic health record variables to accurately predict imminent AKI in hospitalized children.

iRNAD: a computational tool for identifying D modification sites in RNA sequence

2019 ◽  
Vol 35 (23) ◽  
pp. 4922-4929 ◽  
Author(s):  
Zhao-Chun Xu ◽  
Peng-Mian Feng ◽  
Hui Yang ◽  
Wang-Ren Qiu ◽  
Wei Chen ◽  
...  
Keyword(s):  
Computational Models ◽  
Operating Characteristic ◽  
Cross Validation ◽  
Characteristic Curve ◽  
Support Vector ◽  
Final Model ◽  
Rna Sequence ◽  
Functional Roles ◽  
Proposed Model ◽  
User Friendly

Abstract Motivation Dihydrouridine (D) is a common RNA post-transcriptional modification found in eukaryotes, bacteria and a few archaea. The modification can promote the conformational flexibility of individual nucleotide bases. And its levels are increased in cancerous tissues. Therefore, it is necessary to detect D in RNA for further understanding its functional roles. Since wet-experimental techniques for the aim are time-consuming and laborious, it is urgent to develop computational models to identify D modification sites in RNA. Results We constructed a predictor, called iRNAD, for identifying D modification sites in RNA sequence. In this predictor, the RNA samples derived from five species were encoded by nucleotide chemical property and nucleotide density. Support vector machine was utilized to perform the classification. The final model could produce the overall accuracy of 96.18% with the area under the receiver operating characteristic curve of 0.9839 in jackknife cross-validation test. Furthermore, we performed a series of validations from several aspects and demonstrated the robustness and reliability of the proposed model. Availability and implementation A user-friendly web-server called iRNAD can be freely accessible at http://lin-group.cn/server/iRNAD, which will provide convenience and guide to users for further studying D modification.

scholarly journals Development and external validation of new nomograms by adding ECG changes (ST depression or tall T wave) and age to conventional scoring systems to improve the predictive capacity in patients with subarachnoid haemorrhage: a retrospective, observational study in Korea

BMJ Open ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. e024007 ◽  
Author(s):  
Ju young Hong ◽  
Je Sung You ◽  
Min Joung Kim ◽  
Hye Sun Lee ◽  
Yoo Seok Park ◽  
...  
Keyword(s):  
Observational Study ◽  
Subarachnoid Haemorrhage ◽  
Characteristic Curve ◽  
External Validation ◽  
Scoring Systems ◽  
Retrospective Observational Study ◽  
World Federation ◽  
Ecg Changes ◽  
T Wave ◽  
St Depression

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.

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