Abstract TP325: Lack of Early Improvement Predicts Poor Clinical Outcome Following Acute Intracerebral Hemorrhage

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Vignan Yogendrakumar ◽  
Eric E Smith ◽  
Andrew M Demchuk ◽  
RIchard I Aviv ◽  
David Rodriguez-Luna ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Predictive Values ◽  
Early Improvement ◽  
Poor Outcome ◽  
Using Data ◽  
Definition Of ◽  
Sensitivity Specificity ◽  
The Cost

Background: Early Neurological Worsening (ENW) is common after ICH, and predicts poor outcome. However, there is limited data as to what degree of ENW best relates to outcome. We used two ICH cohorts to refine and validate a definition of ENW that best predicted 90-day outcomes. Methods: We generated receiver operating characteristic (ROC) curves for the association between 24-hour NIHSS change and ICH outcomes using data from the VISTA collaboration. Primary outcome was poor outcome at 90 days (mRS 4-6); secondary outcomes were other mRS cutpoints (mRS 2-6, 3-6, 5-6, 6). We tested the commonly used NIHSS≥4 definition and in addition employed Youden’s J Index to select optimal cutpoints and calculated sensitivity, specificity, and predictive values. Independent predictors of poor outcome were determined via multivariable logistic regression. Definitions were validated in the prospectively collected PREDICT-ICH cohort. Results: Using 552 patients from the VISTA cohort, ROC curves of 24hr NIHSS change had an area under the curve of 0.75. NIHSS change of ≥0 at 24hrs was seen in 46.4%. Youden’s method showed an optimum cutoff at -0.5. Based on this, ENW defined as >0 (Sens 43%, Spec 91%, PPV 83%, aOR 7.13 [CI:4.05-12.55]), ≥0 (Sens 65%, Spec 73%, PPV 70%, aOR 5.05 [CI:3.25-7.85]), or ≥-1 (Sens 78%, Spec 59%, PPV 65%, aOR 6.04 [CI:3.75-9.71]) all accurately predicted poor outcome. PPV increased with higher NIHSS cutoffs, but at the cost of lower sensitivities. Regression confirmed that all definitions independently predicted outcome at all mRS cutpoints. ENW definitions reproduced well in the validation cohort of 275 patients. Conclusion: All NIHSS cut-offs for ENW predict clinical outcome, regardless of outcome definition. In particular, lack of clinical improvement at 24 hours (i.e. NIHSS is the same or higher) robustly predicted poor outcome, but may not be sufficiently reliable to determine clinical management.

scholarly journals Associations and prognostic accuracy of electrolyte imbalances in predicting poor COVID-19 outcome: a systematic review and meta-analysis of 28 observational studies

2021 ◽  
Author(s):  
Harris Jun Jie Muhammad Danial Song ◽  
Alys Zhi Qin Chia ◽  
Benjamin Kye Jyn Tan ◽  
Chong Boon Teo ◽  
Horng Ruey Chua ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Observational Studies ◽  
Inflammatory Marker ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Cochrane Library ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Poor Outcome ◽  
Prognostic Accuracy

BACKGROUND: Serum electrolyte imbalances are highly prevalent in COVID-19 patients. However, their associations with COVID-19 outcomes are inconsistent, and of unknown prognostic value. OBJECTIVES: To systematically clarify the associations and prognostic accuracy of electrolyte imbalances (sodium, calcium, potassium, magnesium, chloride and phosphate) in predicting poor COVID-19 clinical outcome. METHODS: PubMed, Embase and Cochrane Library were searched. Odds of poor clinical outcome (a composite of mortality, intensive-care unit (ICU) admission, need for respiratory support and acute respiratory distress syndrome) were pooled using mixed-effects models. The associated prognostic sensitivity, positive and negative likelihood ratios (LR+, LR-) and predictive values (PPV, NPV; assuming 25% pre-test probability), and area under the curve (AUC) were computed. RESULTS: We included 28 observational studies from 953 records with low to moderate risk-of-bias. Hyponatremia (OR=2.08, 95%CI=1.48-2.94, I2=93%, N=8), hypernatremia (OR=4.32, 95%CI=3.17-5.88, I2=45%, N=7) and hypocalcemia (OR=3.31, 95%CI=2.24-4.88, I2=25%, N=6) were associated with poor COVID-19 outcome. These associations remained significant on adjustment for covariates such as demographics and comorbidities. Hypernatremia was 97% specific in predicting poor outcome (LR+ 4.0, PPV=55%, AUC=0.80) despite no differences in CRP and IL-6 levels between hypernatremic and normonatremic patients. Hypocalcemia was 76% sensitive in predicting poor outcome (LR- 0.44, NPV=87%, AUC=0.71). Overall quality of evidence ranged from very low to moderate. CONCLUSION: Hyponatremia, hypernatremia and hypocalcemia are associated with poor COVID-19 clinical outcome. Hypernatremia is 97% specific for a poor outcome and the association is independent of inflammatory marker levels. Further studies should evaluate if correcting these imbalances help improve clinical outcome.

scholarly journals El dilema del vigilante. Valoración de pruebas diagnósticas.

2018 ◽  
Vol 10 (8) ◽  
pp. 4
Author(s):  
Manuel Molina
Keyword(s):  
Diagnostic Tests ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Significant Parameter ◽  
Quantitative Results ◽  
Sensitivity Specificity

Existen una serie de parámetros que caracterizan las pruebas diagnósticas, como son la sensibilidad, la especificidad, los valores predictivos y los cocientes de probabilidad. Solo estos últimos nos permiten el cálculo de la probabilidad del paciente de presentar la enfermedad, con independencia de la prevalencia en la población. Para caracterizar las pruebas con resultado cuantitativo se utilizan las curvas ROC, cuyo parámetro más significativo es el área bajo la curva. ABSTRACT There are a series of parameters that characterize the diagnostic tests, such as sensitivity, specificity, predictive values and likelihood ratios. Only the latter allow us to calculate the patient's probability of presenting the disease, regardless of the prevalence in the population. To characterize the tests with quantitative results, the ROC curves are used, whose most significant parameter is the area under the curve.

scholarly journals Evaluation of PORT/PSI and SOFA scores in predicting in-hospital mortality of patients with COVID-19

2021 ◽  
Vol 1 ◽  
pp. e1196
Author(s):  
José M. Alanís-Naranjo ◽  
Salvador Hernández-Sandoval ◽  
Víctor M. Anguiano-Álvarez ◽  
Eduardo F. Hammeken-Larrondo ◽  
Gabriela Olguín-Contreras ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Sofa Score ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Prognostic Scores ◽  
Limited Information ◽  
Good Tool ◽  
Predictive Values ◽  
Study Population ◽  
Sensitivity Specificity

Introduction: There is limited information analyzing the utility of different prognostic scores in predicting in-hospital mortality among patients with COVID-19. This study aimed to evaluate the performance of PORT/PSI and SOFA scores in predicting the in-hospital mortality of patients with COVID-19. Material and methods: This was an observational, analytical, and retrospective study that included consecutive patients hospitalized for COVID-19 from April 1, 2020, to May 31, 2020. The study population was characterized, and ROC analysis was performed and used to calculate the area under the curve of PORT/PSI and SOFA scores as well as the sensitivity, specificity, and predictive values. Results: A total of 151 patients were included, with a median age of 52 years (IQR 45-64); 69.5% were men, with a median BMI of 29.3 kg/m2 (IQR 25.5-34.7). Of the total, 102 patients died during hospitalization (67.5%). The areas under the ROC curves for predicting in-hospital mortality were 0.74 (95% CI 0.67-0.81) for the SOFA score and 0.85 (95% CI 0.78-0.90) for the PORT/PSI score. When compared, the PORT/PSI score predicted mortality significantly better than the SOFA score (p: 0.01). Conclusions: The PORT/PSI score is a good tool to predict in-hospital mortality in patients with COVID-19.

scholarly journals Establishment and Characterization of an Empirical Biomarker SS/PV-ROC Plot Using Results of the UBC® Rapid Test in Bladder Cancer

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 729 ◽  
Author(s):  
Peter Oehr ◽  
Thorsten Ecke
Keyword(s):  
Bladder Cancer ◽  
Roc Curve ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Rapid Test ◽  
Roc Curves ◽  
Threshold Value ◽  
Control Group ◽  
Predictive Values ◽  
Sensitivity Specificity

Background: This investigation included both a study of potential non-invasive diagnostic approaches for the bladder cancer biomarker UBC® Rapid Test and a study including comparative methods about sensitivity–specificity characteristic (SS-ROC) and predictive receiver operating characteristic (PV-ROC) curves that used bladder cancer as a useful example. Methods: The study included 289 urine samples from patients with tumors of the urinary bladder, patients with non-evidence of disease (NED) and healthy controls. The UBC® Rapid Test is a qualitative point of care assay. Using a photometric reader, quantitative data can also be obtained. Data for pairs of sensitivity/specificity as well as positive/negative predictive values were created by variation of threshold values for the whole patient cohort, as well as for the tumor-free control group. Based on these data, sensitivity–specificity and predictive value threshold distribution curves were constructed and transformed into SS-ROC and PV-ROC curves, which were included in a single SS/PV-ROC plot. Results: The curves revealed TPP-asymmetric improper curves which cross the diagonal from above. Evaluation of the PV-ROC curve showed that two or more distinct positive predictive values (PPV) can correspond to the same value of a negative predictive value (NPV) and vice versa, indicating a complexity in PV-ROC curves which did not exist in SS-ROC curves. In contrast to the SS-ROC curve, the PV-ROC curve had neither an area under the curve (AUC) nor a range from 0% to 100%. Sensitivity of the qualitative assay was 58.5% and specificity 88.2%, PPV was 75.6% and NPV 77.3%, at a threshold value of approximately 12.5 µg/L. Conclusions: The SS/PV-ROC plot is a new diagnostic approach which can be used for direct judgement of gain and loss of predictive values, sensitivity and specificity according to varied threshold value changes, enabling characterization, comparison and evaluation of qualitative and quantitative bioassays.

Evaluation of the clot burden score (cbs) for acute ischemic stroke (ais) in intent-to-treat patients.

2019 ◽  
Vol 1 (1) ◽  
pp. 11-15 ◽  
Author(s):  
Sarah Yaziz ◽  
Ahmad Sobri Muda ◽  
Wan Asyraf Wan Zaidi ◽  
Nik Azuan Nik Ismail
Keyword(s):  
Ischemic Stroke ◽  
Clinical Outcome ◽  
Acute Ischemic Stroke ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Rank Correlation ◽  
Treatment Decision ◽  
Roc Curves ◽  
Significant Negative Correlation ◽  
Clot Burden

Background : The clot burden score (CBS) is a scoring system used in acute ischemic stroke (AIS) to predict patient outcome and guide treatment decision. However, CBS is not routinely practiced in many institutions. This study aimed to investigate the feasibility of CBS as a relevant predictor of good clinical outcome in AIS cases. Methods:  A retrospective data collection and review of AIS patients in a teaching hospital was done from June 2010 until June 2015. Patients were selected following the inclusion and exclusion criteria. These patients were followed up after 90 days of discharge. The Modified Rankin scale (mRS) was used to assess their outcome (functional status). Linear regression Spearman Rank correlation was performed between the CBS and mRS. The quality performance of the correlations was evaluated using Receiver operating characteristic (ROC) curves. Results: A total of 89 patients with AIS were analysed, 67.4% (n=60) male and 32.6% (n=29) female. Twenty-nine (29) patients (33.7%) had a CBS ?6, 6 patients (6.7%) had CBS <6, while 53 patients (59.6%) were deemed clot free. Ninety (90) days post insult, clinical assessment showed that 57 (67.6%) patients were functionally independent, 27 (30.3%) patients functionally dependent, and 5 (5.6%) patients were deceased. Data analysis reported a significant negative correlation (r= -0.611, p<0.001). ROC curves analysis showed an area under the curve of 0.81 at the cut-off point of 6.5. This showed that a CBS of more than 6 predicted a good mRS clinical outcome in AIS patients; with sensitivity of 98.2%, specificity of 53.1%, positive predictive value (PPV) of 76%, and negative predictive value (NPV) of 21%. Conclusion: CBS is a useful additional variable for the management of AIS cases, and should be incorporated into the routine radiological reporting for acute ischemic stroke (AIS) cases.

Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS

2020 ◽  
Vol 163 (6) ◽  
pp. 1156-1165
Author(s):  
Juan Xiao ◽  
Qiang Xiao ◽  
Wei Cong ◽  
Ting Li ◽  
Shouluan Ding ◽  
...  
Keyword(s):  
Thyroid Nodules ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Study ◽  
Diagnostic Efficiency ◽  
Training Set ◽  
Multivariable Logistic Regression Model ◽  
Predictive Values ◽  
Validation Set ◽  
Sensitivity Specificity

Objective To develop an easy-to-use nomogram for discrimination of malignant thyroid nodules and to compare diagnostic efficiency with the Kwak and American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). Study Design Retrospective diagnostic study. Setting The Second Hospital of Shandong University. Subjects and Methods From March 2017 to April 2019, 792 patients with 1940 thyroid nodules were included into the training set; from May 2019 to December 2019, 174 patients with 389 nodules were included into the validation set. Multivariable logistic regression model was used to develop a nomogram for discriminating malignant nodules. To compare the diagnostic performance of the nomogram with the Kwak and ACR TI-RADS, the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values were calculated. Results The nomogram consisted of 7 factors: composition, orientation, echogenicity, border, margin, extrathyroidal extension, and calcification. In the training set, for all nodules, the area under the curve (AUC) for the nomogram was 0.844, which was higher than the Kwak TI-RADS (0.826, P = .008) and the ACR TI-RADS (0.810, P < .001). For the 822 nodules >1 cm, the AUC of the nomogram was 0.891, which was higher than the Kwak TI-RADS (0.852, P < .001) and the ACR TI-RADS (0.853, P < .001). In the validation set, the AUC of the nomogram was also higher than the Kwak and ACR TI-RADS ( P < .05), each in the whole series and separately for nodules >1 or ≤1 cm. Conclusions When compared with the Kwak and ACR TI-RADS, the nomogram had a better performance in discriminating malignant thyroid nodules.

scholarly journals Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting

Diagnostics ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 109 ◽  
Author(s):  
Ukweh ◽  
Ugbem ◽  
Okeke ◽  
Ekpo
Keyword(s):  
Predictive Value ◽  
Performance Metrics ◽  
Area Under The Curve ◽  
Youden Index ◽  
Likelihood Ratios ◽  
Diagnostic Efficacy ◽  
Predictive Values ◽  
Resource Setting ◽  
Post Test ◽  
Sensitivity Specificity

Background: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. Materials and Methods: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th–22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. Results: In total, 6520 fetuses of women aged 15–46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68–84.6), 99.5 (95% CI: 99.3–99.7), and 88.3 (95% CI: 83.7–92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7–79.0), negative predictive value, 99.6 (95% CI: 99.5–99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37–2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7–221.4) and 0.23 (95% CI: 0.16–0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65–79). Conclusion: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

scholarly journals Identification of the most specific markers to differentiate primary pulmonary carcinoma from metastatic gastrointestinal carcinoma to the lung

2022 ◽  
Vol 17 (1) ◽  
Author(s):  
Bachar Alabdullah ◽  
Amir Hadji-Ashrafy
Keyword(s):  
Gastrointestinal Tract ◽  
Predictive Value ◽  
Regression Models ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Multivariate Models ◽  
Gastrointestinal Carcinoma ◽  
Lung Tumours ◽  
Napsin A ◽  
Sensitivity Specificity

Abstract Background A number of biomarkers have the potential of differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract, however, a standardised panel for that purpose does not exist yet. We aimed to identify the smallest panel that is most sensitive and specific at differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract. Methods A total of 170 samples were collected, including 140 primary and 30 non-primary lung tumours and staining for CK7, Napsin-A, TTF1, CK20, CDX2, and SATB2 was performed via tissue microarray. The data was then analysed using univariate regression models and a combination of multivariate regression models and Receiver Operating Characteristic (ROC) curves. Results Univariate regression models confirmed the 6 biomarkers’ ability to independently predict the primary outcome (p < 0.001). Multivariate models of 2-biomarker combinations identified 11 combinations with statistically significant odds ratios (ORs) (p < 0.05), of which TTF1/CDX2 had the highest area under the curve (AUC) (0.983, 0.960–1.000 95% CI). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75.7, 100, 100, and 37.5% respectively. Multivariate models of 3-biomarker combinations identified 4 combinations with statistically significant ORs (p < 0.05), of which CK7/CK20/SATB2 had the highest AUC (0.965, 0.930–1.000 95% CI). The sensitivity, specificity, PPV, and NPV were 85.1, 100, 100, and 41.7% respectively. Multivariate models of 4-biomarker combinations did not identify any combinations with statistically significant ORs (p < 0.05). Conclusions The analysis identified the combination of CK7/CK20/SATB2 to be the smallest panel with the highest sensitivity (85.1%) and specificity (100%) for predicting tumour origin with an ROC AUC of 0.965 (p < 0.001; SE: 0.018, 0.930–1.000 95% CI).

Abstract P533: Incidence and Outcomes of Thrombectomy Rescue Therapies in Acute Basilar Artery Occlusions

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Ronda Lun ◽  
Greg B Walker ◽  
David Weisenburger-Lile ◽  
Bertrand Lapergue ◽  
Adrien Guenego ◽  
...  
Keyword(s):  
Primary Outcome ◽  
Secondary Analysis ◽  
Hematoma Expansion ◽  
Primary Analysis ◽  
Predictive Values ◽  
Previous Definition ◽  
Secondary Analyses ◽  
Revised Definitions ◽  
Definition Of ◽  
Sensitivity Specificity

Background: Hematoma expansion (HE) is an important therapeutic target in intracerebral hemorrhage. Recently proposed HE definitions have not been validated, and no previous definition has accounted for withdrawal of care (WOC). Objective: To compare conventional and revised definitions of hematoma expansion (HE), while accounting for WOC. Methods: We analyzed data from the ATACH-2 trial, comparing revised definitions of HE incorporating intraventricular hemorrhage (IVH) expansion to the conventional definition of “≥6 mL or ≥33%”. The primary outcome was modified Rankin Scale of 4-6 at 90-days. We calculated the incidence, sensitivity, specificity, positive and negative predictive values, and c- statistic for all definitions of HE. Definitions were compared using non-parametric methods. Secondary analyses were performed after removing patients who experienced WOC. Results: Primary analysis included 948 patients. Using the conventional definition, the sensitivity was 37.1% and specificity was 83.2% for the primary outcome. Sensitivity improved with all three revised definitions (53.3%, 48.7%, and 45.3%, respectively), with minimal change to specificity (78.4%, 80.5%, and 81.0%, respectively). The greatest improvement was seen with the definition “≥6 mL or ≥33% or any IVH”, with increased c -statistic from 60.2% to 65.9% (p < 0.001). Secondary analysis excluded 46 participants who experienced WOC. The revised definitions outperformed the conventional definition in this population as well, with the greatest improvement in c -statistic using “≥6 mL or ≥33% or any IVH” (58.1% vs 64.1%, p < 0.001). Conclusions: HE definitions incorporating intraventricular expansion outperformed conventional definitions for predicting poor outcome, even after accounting for care limitations.

Image evaluation and breast density categories as a function of mammary positioning in full-field digital mammography

2019 ◽  
Vol 61 (7) ◽  
pp. 868-874
Author(s):  
Irene Tomoko Nakano ◽  
Gabriel Lucca de Oliveira Salvador ◽  
Hugo Reuters Schelin ◽  
Valeriy Denyak ◽  
Helen Jamil Khoury ◽  
...  
Keyword(s):  
Breast Density ◽  
Area Under The Curve ◽  
Quality Criteria ◽  
Roc Curves ◽  
Full Field ◽  
European Guidelines ◽  
Full Field Digital Mammography ◽  
Definition Of ◽  
The Individual ◽  
The Right

Background Appropriate mammary positioning is an important factor in optimizing image quality in mammography (MMG). Purpose To study the correlation of quality criteria and breast density classification proposed by the American College of Radiology (ACR) and European Guidelines and its influence to achieve a proper positioning, therefore an adequate MMG. Material and methods A total of 128 routine MMG examinations were reviewed for the definition of breast composition parenchyma and assessment of several quality criteria proposed by the ACR and European Guidelines to achieve an adequate MMG. Adequate MMG was defined as a difference between the posterior nipple line (PNL), difference of the mediolateral oblique (MLO) and craniocaudal (CC) incidences > 1 cm. The quality criteria were analyzed as a function of correlation coefficient in order to evaluate the individual impact of each factor and analysis of variance (ANOVA) for all criteria. Receiver operating characteristic (ROC) curves were plotted to evaluate the performance of the criteria on each type of parenchyma. Results Negative correlation of fatty breasts and visibility of the mammary angle, a greater number of skin folds and PNL > 1 cm (r < 0). Dense MMG presented less visibility of the lateral tissue compared with other categories. Area under the curve of ROC analysis revealed values of 53.1% and 54.7% for the right and left breasts, respectively. Conclusion Several factors influenced in the MMG process, but we find that breast parenchyma has a substantial role in affecting these criteria and therefore a correct position for diagnosis, which could compromise MMG diagnostic performance.

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