Clinical, laboratory, and radiographic predictors of the occurrence of seizures following aneurysmal subarachnoid hemorrhage

2013 ◽  
Vol 119 (2) ◽  
pp. 347-352 ◽  
Author(s):  
George M. Ibrahim ◽  
Aria Fallah ◽  
R. Loch Macdonald
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Roc Curve ◽  
Subdural Hematoma ◽  
Clinical Laboratory ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Univariate Analysis ◽  
Aneurysm Rupture ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Clot Burden

Object At present, the administration of prophylactic antiepileptic medication following aneurysmal subarachnoid hemorrhage (SAH) is controversial, and the practice is heterogeneous. Here, the authors sought to inform clinical decision making by identifying factors associated with the occurrence of seizures following aneurysm rupture. Methods Exploratory analysis was performed on 413 patients enrolled in CONSCIOUS-1 (Clazosentan to Overcome Neurological Ischemia and Infarction Occurring after Subarachnoid Hemorrhage), a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. The association among clinical, laboratory, and radiographic covariates and the occurrence of seizures following SAH were determined. Covariates with a significance level of p < 0.20 on univariate analysis were entered into a multivariate logistic regression model. Receiver operating characteristic (ROC) curve analysis was used to define optimal predictive thresholds. Results Of the 413 patients enrolled in the study, 57 (13.8%) had at least 1 seizure following SAH. On univariate analysis, a World Federation of Neurosurgical Societies grade of IV–V, a greater subarachnoid clot burden, and the presence of midline shift and subdural hematomas were associated with seizure activity. On multivariate analysis, only a subarachnoid clot burden (OR 2.76, 95% CI 1.39–5.49) and subdural hematoma (OR 5.67, 95% CI 1.56–20.57) were associated with seizures following SAH. Using ROC curve analysis, the optimal predictive cutoff for subarachnoid clot burden was determined to be 21 (of a possible 30) on the Hijdra scale (area under the curve 0.63). Conclusions A greater subarachnoid clot burden and subdural hematoma are associated with the occurrence of seizures after aneurysm rupture. These findings may help to identify patients at greatest risk for seizures and guide informed decisions regarding the prescription of prophylactic anticonvulsive therapy. Clinical trial registration no.: NCT00111085 (ClinicalTrials.gov).

scholarly journals Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaohua Ban ◽  
Xinping Shen ◽  
Huijun Hu ◽  
Rong Zhang ◽  
Chuanmiao Xie ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Roc Curve ◽  
Multinomial Logistic Regression ◽  
Univariate Analysis ◽  
Ct Imaging ◽  
Squamous Cell Carcinomas ◽  
Curve Analysis ◽  
Imaging Features ◽  
Roc Curve Analysis ◽  
Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

scholarly journals Management of Patients Presenting with Acute Subdural Hematoma due to Ruptured Intracranial Aneurysm

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
Serge Marbacher ◽  
Ottavio Tomasi ◽  
Javier Fandino
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Subdural Hematoma ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Mass Effect ◽  
Aneurysm Rupture ◽  
Treatment Modalities ◽  
Acute Subdural Hematoma ◽  
Rare Presentation ◽  
Ruptured Intracranial Aneurysm ◽  
Threatening Condition

Acute subdural hematoma is a rare presentation of ruptured aneurysms. The rarity of the disease makes it difficult to establish reliable clinical guidelines. Many patients present comatose and differential diagnosis is complicated due to aneurysm rupture results in or mimics traumatic brain injury. Fast decision-making is required to treat this life-threatening condition. Determining initial diagnostic studies, as well as making treatment decisions, can be complicated by rapid deterioration of the patient, and the mixture of symptoms due to the subarachnoid hemorrhage or mass effect of the hematoma. This paper reviews initial clinical and radiological findings, diagnostic approaches, treatment modalities, and outcome of patients presenting with aneurysmal subarachnoid hemorrhage complicated by acute subdural hematoma. Clinical strategies used by several authors over the past 20 years are discussed and summarized in a proposed treatment flowchart.

scholarly journals P.093 Hemoglobin values, fluctuations from baseline, and transfusion as predictors of outcome following aneurysmal subarachnoid hemorrhage

2018 ◽  
Vol 45 (s2) ◽  
pp. S41-S41
Author(s):  
ME Eagles ◽  
MK Tso ◽  
RL Macdonald
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Roc Curve ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Youden Index ◽  
Predictors Of Outcome ◽  
Roc Curve Analysis ◽  
Transfusion Threshold ◽  
Poor Outcome

Background: Anemia following aneurysmal subarachnoid hemorrhage (aSAH) has been associated with poor outcome, but complications from transfusion have limited aggressive management of anemic patients. This study examined the relationship between hemoglobin levels, transfusion and outcome following aSAH. Methods: We performed a post-hoc analysis of the CONSCIOUS-1 trial. Poor outcome was defined as a 3-month modified Rankin Scale > 2. Minimum hemoglobin levels were evaluated as predictors of outcome using logistic regression analysis, ROC curve analysis, and LOWESS curves. Propensity score matching was used to assess the effect of transfusion on poor outcome in patients with minimum hemoglobin levels between 70-90 and 80-100 g/L. Results: Lower minimum hemoglobin levels were associated with poor outcome on both univariate (p<0.001) and multivariate (p=0.012) analysis. Area under the ROC curve for minimum hemoglobin was 0.673. Youden index analysis found a minimum hemoglobin threshold of 91.5 g/L maximally predictive for good functional outcome. Propensity score matching showed a trend towards poor outcome in transfused patients with minimum hemoglobin levels between 70-90 and 80-100 g/L (p=0.052 and 0.09). Conclusions: This work suggests that decreasing hemoglobin is an independent predictor of poor outcome following aSAH. However, there was a trend towards poor outcome in transfused patients. The optimal transfusion threshold should be evaluated by prospective trials.

Risk Stratification in COVID-19 Pneumonia – Determining the Role of Lung Ultrasound

2021 ◽  
Author(s):  
Valeria Tombini ◽  
Mirko Di Capua ◽  
Nicolò Capsoni ◽  
Andrea Lazzati ◽  
Marta Bergamaschi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Roc Curve ◽  
Primary Outcome ◽  
Clinical Laboratory ◽  
Curve Analysis ◽  
Secondary Outcome ◽  
Roc Curve Analysis ◽  
Additional Tool ◽  
Factors Associated ◽  
Independent Risk Factors

AbstractLUS patterns of COVID-19 pneumonia have been described and shown to be characteristic. The aim of the study was to predict the prognosis of patients with COVID-19 pneumonia, using a score based on LUS findings. Materials and Methods An observational, retrospective study was conducted on patients admitted to Niguarda hospital with a diagnosis of COVID-19 pneumonia during the period of a month, from March 2nd to April 3rd 2020. Demographics, clinical, laboratory, and radiological findings were collected. LUS was performed in all patients. The chest was divided into 12 areas. The LUS report was drafted using a score from 0 to 3 with 0 corresponding to A pattern, 1 corresponding to well separated vertical artifacts (B lines), 2 corresponding to white lung and small consolidations, 3 corresponding to wide consolidations. The total score results from the sum of the scores for each area. The primary outcome was endotracheal intubation, no active further management, or death. The secondary outcome was discharge from the emergency room (ER). Results 255 patients were enrolled. 93.7 % had a positive LUS. ETI was performed in 43 patients, and 24 received a DNI order. The general mortality rate was 15.7 %. Male sex (OR 3.04, p = 0.014), cardiovascular disease and hypertension (OR 2.75, p = 0.006), P/F (OR 0.99, p < 0.001) and an LUS score > 20 (OR 2.52, p = 0.046) were independent risk factors associated with the primary outcome. Receiver operating characteristic (ROC) curve analysis for an LUS score > 20 was performed with an AUC of 0.837. Independent risk factors associated with the secondary outcome were age (OR 0.96, p = 0.073), BMI (OR 0.87, p = 0,13), P/F (OR 1.03, p < 0.001), and LUS score < 10 (OR 20.9, p = 0.006). ROC curve analysis was performed using an LUS score < 10 with an AUC 0.967. Conclusion The extent of lung abnormalities evaluated by LUS score is a predictor of a worse outcome, ETI, or death. Moreover, the LUS score could be an additional tool for the safe discharge of patient from the ER.

Enlarged Basal Ganglia Perivascular Spaces are Associated with Pulsatile Components of Blood Pressure

2018 ◽  
Vol 79 (1-2) ◽  
pp. 86-89 ◽  
Author(s):  
Oscar H. Del Brutto ◽  
Robertino M. Mera ◽  
Keyword(s):  
Blood Pressure ◽  
Basal Ganglia ◽  
Roc Curve ◽  
Diastolic Pressure ◽  
Univariate Analysis ◽  
Systolic Pressure ◽  
Area Under The Curve ◽  
Curve Analysis ◽  
Perivascular Spaces ◽  
Roc Curve Analysis

Background/Aims: Pathogenetic mechanisms involved in enlargement of basal ganglia perivascular spaces (BG-PVSs) are controversial. Here, we assessed whether pulsatile or steady components of blood pressure (BP) are associated with enlarged BG-PVS. Methods: We evaluated the association between BG-PVS and pulsatile and steady components of BP in Atahualpa residents aged ≥60 years, by the use of regression models and receiver operator characteristics (ROC) curve analysis, after taking into account the effect of demographics, cardiovascular risk factors, and other signatures of cerebral small vessel disease (SVD). Results: Of 437 candidates, 363 (83%) were included. MRI showed >10 enlarged BG-PVS in 103 (28%) subjects. In univariate analysis, the association between enlarged BG-PVS and systolic pressure (SP) and pulse pressure (PP) were highly significant, while the association with diastolic pressure (DP) was not. ROC curve analysis showed a higher area under the curve for PP than for DP (p < 0.05). The area under the curve for SP was also higher than that of DP, but not significantly better due to overlapping 95% CI. Conclusion: Enlarged BG-PVS are associated with pulsatile components of BP, although some of the effect is taken away by the strong interaction between BG-PVS and other signatures of SVD.

Acute heart failure: predicting early in-hospital outcomes

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Santos ◽  
S Paula ◽  
I Almeida ◽  
H Santos ◽  
H Miranda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Acute Heart Failure ◽  
Roc Curve ◽  
Real Life ◽  
Study Data ◽  
Curve Analysis ◽  
Older Age ◽  
Invasive Ventilation ◽  
Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p &lt; 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p &lt; 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p &lt; 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

scholarly journals Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuichiro Shimoyama ◽  
Osamu Umegaki ◽  
Noriko Kadono ◽  
Toshiaki Minami
Keyword(s):  
Multivariate Analysis ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Prognostic Nutritional Index ◽  
Early Mortality ◽  
Curve Analysis ◽  
Rank Test ◽  
Roc Curve Analysis ◽  
Log Rank Test ◽  
Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

scholarly journals Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiajia Liu ◽  
Xiaoyi Tian ◽  
Yan Wang ◽  
Xixiong Kang ◽  
Wenqi Song
Keyword(s):  
T Lymphocyte ◽  
Roc Curve ◽  
Cytotoxic T Lymphocyte ◽  
Tumor Grade ◽  
Curve Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Low Grade ◽  
High Grade ◽  
Healthy Individuals ◽  
Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

scholarly journals Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

2019 ◽  
Vol 11 ◽  
pp. 1759720X1988555 ◽  
Author(s):  
Wanlong Wu ◽  
Jun Ma ◽  
Yuhong Zhou ◽  
Chao Tang ◽  
Feng Zhao ◽  
...  
Keyword(s):  
Emergency Department ◽  
Prediction Model ◽  
Risk Score ◽  
Roc Curve ◽  
Curve Analysis ◽  
Multivariable Logistic Regression Analysis ◽  
Invasive Infection ◽  
Roc Curve Analysis ◽  
All Cause Mortality ◽  
Qsofa Score

Background: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. Methods: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. Results: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections ( n = 108). Conclusions: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.

scholarly journals Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

2014 ◽  
Vol 5 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Balkishan Sharma ◽  
Ravikant Jain
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Traditional Method ◽  
Statistical Technique ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296      

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