Evaluating the Predictive Value of Lactate in Patients With Cancer Having Septic Shock

2018 ◽  
Vol 35 (8) ◽  
pp. 789-796
Author(s):  
Lama H. Nazer ◽  
Dalia Rimawi ◽  
Feras I. Hawari
Keyword(s):  
Septic Shock ◽  
Hospital Mortality ◽  
Predictive Validity ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Serum Lactate ◽  
Predictive Values ◽  
Patients With Cancer ◽  
Predict Hospital Mortality

Purpose: Limited studies evaluated the predictive value of serum lactate (LA) in critically ill patients with cancer. The main objective of this study was to evaluate the predictive validity of LA single measurements as well as LA clearance in predicting mortality in patients with cancer having septic shock. The study also aimed to determine the LA measurement over the first 24 hours with the highest predictability for hospital mortality. Materials and Methods: A retrospective cohort study of adult patients with cancer having septic shock and LA measurements during the first 24 hours. Three receiver–operating characteristic (ROC) curves were constructed to evaluate the predictive validity for hospital mortality of LA at baseline, at 6 hours and at 24 hours after identifying septic shock. The ROC with the largest area under the curve was analyzed to determine LA level with the highest predictability for hospital mortality. In addition, the ability of LA normalization (LA <2 mmol/L at 6 hours and at 24 hours) and the degree of LA elimination (>10% and >20% at 24 hours) to predict hospital mortality were evaluated by determining the predictive values for each clearance end point. Results: The study included 401 patients. LA >2.5 mmol/L at 24 hours showed the largest area under the ROC curve to predict hospital mortality (ROC area: 0.648; 95% confidence interval: 0.585-0.711) with a sensitivity of 58.4% and specificity of 62.8%. The LA normalization, LA clearance >10%, and LA clearance >20% were also predictors of hospital mortality, with the highest sensitivity for LA normalization at 6 hours (74%) and LA normalization at 24 hours (73.4%). Conclusion: In patients with cancer having septic shock, LA >2.5 mmol/L at 24 hours of septic shock had the highest predictability for hospital mortality. The LA normalization and clearance were also predictors of hospital mortality. However, all LA end points were not strong predictors.

scholarly journals Precision oncology in AML: validation of the prognostic value of the knowledge bank approach and suggestions for improvement

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Marius Bill ◽  
Krzysztof Mrózek ◽  
Brian Giacopelli ◽  
Jessica Kohlschmidt ◽  
Deedra Nicolet ◽  
...  
Keyword(s):  
Predictive Value ◽  
Prognostic Value ◽  
De Novo ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Precision Oncology ◽  
Predictive Values ◽  
Mutational Status ◽  
Balanced Chromosome Rearrangements ◽  
Group B

AbstractRecently, a novel knowledge bank (KB) approach to predict outcomes of individual patients with acute myeloid leukemia (AML) was developed using unbiased machine learning. To validate its prognostic value, we analyzed 1612 adults with de novo AML treated on Cancer and Leukemia Group B front-line trials who had pretreatment clinical, cytogenetics, and mutation data on 81 leukemia/cancer-associated genes available. We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate the predictive values of the KB algorithm and other risk classifications. The KB algorithm predicted 3-year overall survival (OS) probability in the entire patient cohort (AUCKB = 0.799), and both younger (< 60 years) (AUCKB = 0.747) and older patients (AUCKB = 0.770). The KB algorithm predicted non-remission death (AUCKB = 0.860) well but was less accurate in predicting relapse death (AUCKB = 0.695) and death in first complete remission (AUCKB = 0.603). The KB algorithm’s 3-year OS predictive value was higher than that of the 2017 European LeukemiaNet (ELN) classification (AUC2017ELN = 0.707, p < 0.001) and 2010 ELN classification (AUC2010ELN = 0.721, p < 0.001) but did not differ significantly from that of the 17-gene stemness score (AUC17-gene = 0.732, p = 0.10). Analysis of additional cytogenetic and molecular markers not included in the KB algorithm revealed that taking into account atypical complex karyotype, infrequent recurrent balanced chromosome rearrangements and mutational status of the SAMHD1, AXL and NOTCH1 genes may improve the KB algorithm. We conclude that the KB algorithm has a high predictive value that is higher than those of the 2017 and 2010 ELN classifications. Inclusion of additional genetic features might refine the KB algorithm.

scholarly journals Urine Output Is Associated With In-hospital Mortality in Intensive Care Patients With Septic Shock: A Propensity Score Matching Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Tianyang Hu ◽  
Zhao Qiao ◽  
Ying Mei
Keyword(s):  
Septic Shock ◽  
Risk Factor ◽  
Intensive Care ◽  
Propensity Score ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Scoring System ◽  
Urine Output ◽  
Roc Curves ◽  
Intensive Care Patients

Background: The relationship between urine output (UO) and in-hospital mortality in intensive care patients with septic shock is currently inconclusive.Methods: The baseline data, UO, and in-hospital prognosis of intensive care patients with septic shock were retrieved from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. By drawing receiver operating characteristic (ROC) curves and comparing the areas under the ROC curves (AUC) to determine the predictive value of UO for in-hospital mortality, and by drawing the Kaplan-Meier curves to compare the difference in in-hospital mortality between different groups of UO.Results: Before and after the propensity score matching (PSM) analysis, UO was always a risk factor for in-hospital mortality in patients with septic shock. The AUC of UO was comparable to the Sequential Organ Failure Assessment (SOFA) scoring system, while the AUC of combining UO and SOFA was greater than that of SOFA. The median survival time of the high-UO group (UO &gt; 0.39 ml/kg/h, before PSM; UO &gt; 0.38 ml/kg/h, after PSM) was longer than that of the low-UO group. Compared with the high-UO group, the hazard ratios (HR) of the low-UO group were 2.6857 (before PSM) and 1.7879 (after PSM).Conclusions: UO is an independent risk factor for septic shock. Low levels of UO significantly increase the in-hospital mortality of intensive care patients with septic shock. The predictive value of UO is comparable to the SOFA scoring system, and the combined predictive value of the two surpasses SOFA alone.

scholarly journals Performance of Molecular Breast Imaging as an Adjunct Diagnostic Tool

2019 ◽  
Vol 6 ◽  
pp. 15-19
Author(s):  
Robin B Shermis ◽  
Roberta E Redfern ◽  
John Bazydlo ◽  
Gabriel Naimy ◽  
Haris Kudrolli ◽  
...  
Keyword(s):  
Diagnostic Tool ◽  
Predictive Value ◽  
Breast Imaging ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Performance Measure ◽  
Conventional Imaging ◽  
Predictive Values ◽  
Molecular Breast Imaging ◽  
Invasive Carcinomas

Purpose: The aim was to retrospectively assess the performance of molecular breast imaging (MBI) as an adjunct diagnostic tool when symptoms could not be explained by conventional imaging, or when mammography or ultrasound findings were equivocal. Methods: The analysis was comprised of women who underwent further testing with MBI after diagnostic mammography and/or targeted ultrasound.  Outcome measures included sensitivity, specificity, and positive and negative predictive values. Receiver-operating characteristic (ROC) curve was constructed and analyzed as a performance measure. Results: In 301 women with a complete reference standard, 18 (6.0%) were diagnosed with cancer.  MBI detected cancer in 16 subjects; two interval cancers occurred. 15 of the 16 cancers detected by MBI were invasive. Overall sensitivity of MBI in this sample was 88.9 % (95% CI 65.6 – 98.6), with 97.5% specificity (95% CI 95.0 – 99.0). Positive predictive value (PPV) was 69.6%, while negative predictive value for recall (NPV) was calculated as 99.3%. ROC curves demonstrated excellent performance (area under the curve = 0.933). Conclusions: MBI is a valuable diagnostic tool for further evaluation or to guide management when conventional imaging is incomplete. The majority of tumors in this study were invasive carcinomas with node negative status, important for timely treatment.

Abstract TP155: Predictive Values of Glasgow Coma Scale and National Institutes of Health Stroke Scale Scores in Determining 3-Month Outcomes of Patients With Intracerebral Hemorrhage

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Iryna Lobanova ◽  
Wei Huang ◽  
Adnan I Qureshi
Keyword(s):  
Confidence Interval ◽  
Glasgow Coma Scale ◽  
Intracerebral Hemorrhage ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Roc Curves ◽  
National Institutes Of Health ◽  
Predictive Values ◽  
Coma Scale

Background: Intracerebral hemorrhage (ICH) is associated, with high rates of mortality, and long-term disability. We investigated the predictive values of the Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS) in the prognosis of mortality and functional outcome in patients with ICH. Methods: A total of 1000 patients recruited in a clinical trial with acute were assessed using GCS and NIHSS at admission. Then, the receiver operating characteristic (ROC) curves were established, and the area under the curves of these 2 scoring systems was compared. The primary outcome was death or disability (modified Rankin scale (mRS) score of 4 to 6, on a scale ranging from 0 [no symptoms] to 6 [death]) at 3 months after randomization, as ascertained by an investigator who was unaware of the treatment assignments. Results: The area under the curve of GCS and NIHSS was 0.660 (95% confidence interval: 0.593-0.727) and 0.708 (95% confidence interval: 0.640-0.755), respectively, for predicting disability among survivors. The area under the curve was 0.655 (95% confidence interval: 0.621-0.688) and 0.788 (95% confidence interval: 0.759-0.817), respectively for prediction of 3-months death or disability among all patients with ICH. The GCS predicted 3-month disability among survivors with a sensitivity of 68.7% and a specificity of 57.7%, and the NIHSS predicted 3-month disability with a sensitivity of 74.6% and a specificity of 62.3%. The GCS predicted 3-month death or disability among all patients with a sensitivity of 60.5% and a specificity of 66.5%, and the NIHSS predicted 3-month death or disability with a sensitivity of 80.1% and a specificity of 66.8%. NIHSS (P<0.0001) and GCS (P=0.0002) scores had a statistically significant predictive value for the presence of intracerebral hemorrhage among survivors. Among all patients, NIHSS (P<0.0001) and GCS (P<0.0001) scores also had statistically significant predictive value for identifying patients at risk for death or disability at three months. Conclusions: GCS and NIHSS scales have good predictive values for the prognosis of patients with ICH as regards of mortality and disability. The NIHSS is more accurate than the GCS in predicting death or disability in patients with ICH.

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.

Sepsis and Septic Shock Definitions in Patients With Cancer Admitted in ICU

2019 ◽  
pp. 088506661989493 ◽  
Author(s):  
Neveux Nathan ◽  
Jean-Paul Sculier ◽  
Lieveke Ameye ◽  
Marianne Paesmans ◽  
Grigoriu Bogdan-Dragos ◽  
...  
Keyword(s):  
Septic Shock ◽  
Hospital Mortality ◽  
Sofa Score ◽  
Patients With Cancer ◽  
Failure Assessment ◽  
Predict Hospital Mortality ◽  
Definition Of ◽  
Qsofa Score ◽  
Sepsis And Septic Shock ◽  
Sirs Criteria

Introduction: In 2016, a new definition of sepsis and septic shock was adopted. Some studies based on the general population demonstrated that the Sequential Organ Failure Assessment (SOFA) score is more accurate than the systemic inflammatory response syndrome (SIRS) criteria to predict hospital mortality of infected patients requiring intensive care. Patients and Method: We have analyzed all the records of patients with cancer admitted for a suspected infection between January 1, 2013, and December 31, 2016, in our oncological intensive care unit (ICU). Sequential Organ Failure Assessment score and quick SOFA (qSOFA) score as well as SIRS criteria were calculated. We analyzed the accuracy of each score to predict hospital mortality in the setting of the new and old definitions of septic shock. Results: Our study includes 241 patients with a solid tumor and 112 with a hematological malignancy. The hospital mortality rate is 37% (68% in patients with septic shock according to the new definition and 60% according to old definition) between 2013 and 2016. To predict hospital mortality, the SOFA score has an area under the receiver operating characteristic curve of 0.74 (95% confidence interval [CI], 0.68-0.79), the qSOFA of 0.65 (95% CI, 0.59-0.70), and the SIRS criteria of 0.58 (95% CI, 0.52-0.63). In multivariate analysis, a higher SOFA score or a higher qSOFA score indicates poor prognosis: odds ratio (OR) per 1-point increase by 1.28 (95% CI, 1.18-1.39) and 1.48 (95% CI, 1.04-2.11), respectively. Complete remission is a good prognostic factor for hospital mortality: OR 0.39 (95% CI, 0.22-0.67). Conclusion: The new definition of sepsis and septic shock is applicable in an ICU oncological population with the same reliability as in the general population. The SOFA score is more accurate than qSOFA and SIRS criteria to predict hospital mortality.

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.

Predictive value of thyroxine for prognosis in pediatric septic shock: a prospective observational study

2020 ◽  
Vol 33 (5) ◽  
pp. 653-659
Author(s):  
Jia Song ◽  
Yun Cui ◽  
Chunxia Wang ◽  
Jiaying Dou ◽  
Huijie Miao ◽  
...  
Keyword(s):  
Septic Shock ◽  
Thyroid Hormone ◽  
Observational Study ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Prospective Observational Study ◽  
Threshold Value ◽  
Nonthyroidal Illness ◽  
Hormone Levels ◽  
Thyroid Hormone Levels

AbstractBackgroundThyroid hormone plays an important role in the adaptation of metabolic function to critically ill. The relationship between thyroid hormone levels and the outcomes of septic shock is still unclear. The aim of this study was to assess the predictive value of thyroid hormone for prognosis in pediatric septic shock.MethodsWe performed a prospective observational study in a pediatric intensive care unit (PICU). Patients with septic shock were enrolled from August 2017 to July 2019. Clinical and laboratory indexes were collected, and thyroid hormone levels were measured on PICU admission.ResultsNinety-three patients who fulfilled the inclusion criteria were enrolled in this study. The incidence of nonthyroidal illness syndrome (NTIS) was 87.09% (81/93) in patients with septic shock. Multivariate logistic regression analysis showed that T4 level was independently associated with in-hospital mortality in patients with septic shock (OR: 0.965, 95% CI: 0.937–0.993, p = 0.017). The area under receiver operating characteristic (ROC) curve (AUC) for T4 was 0.762 (95% CI: 0.655–0.869). The cutoff threshold value of 58.71 nmol/L for T4 offered a sensitivity of 61.54% and a specificity of 85.07%, and patients with T4 < 58.71 nmol/L showed high mortality (60.0%). Moreover, T4 levels were negatively associated with the pediatric risk of mortality III scores (PRISM III), lactate (Lac) level in septic shock children.ConclusionsNonthyroidal illness syndrome is common in pediatric septic shock. T4 is an independent predictor for in-hospital mortality, and patients with T4 < 58.71 nmol/L on PICU admission could be with a risk of hospital mortality.

Predictive value of time-variant color-coded multiphase CT angiography (mCTA) regarding clinical outcome of acute ischemic stroke: in comparison with conventional mCTA and CT perfusion

2020 ◽  
pp. 028418512098177
Author(s):  
Yu Lin ◽  
Nannan Kang ◽  
Jianghe Kang ◽  
Shaomao Lv ◽  
Jinan Wang
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Predictive Value ◽  
Ct Perfusion ◽  
Roc Curves ◽  
Multivariate Logistic Regression Model ◽  
Infarct Core ◽  
Predictive Values ◽  
Significant Difference ◽  
Core Volume

Background Color-coded multiphase computed tomography angiography (mCTA) can provide time-variant blood flow information of collateral circulation for acute ischemic stroke (AIS). Purpose To compare the predictive values of color-coded mCTA, conventional mCTA, and CT perfusion (CTP) for the clinical outcomes of patients with AIS. Material and Methods Consecutive patients with anterior circulation AIS were retrospectively reviewed at our center. Baseline collateral scores of color-coded mCTA and conventional mCTA were assessed by a 6-point scale. The reliabilities between junior and senior observers were assessed by weighted Kappa coefficients. Receiver operating characteristic (ROC) curves and multivariate logistic regression model were applied to evaluate the predictive capabilities of color-coded mCTA and conventional mCTA scores, and CTP parameters (hypoperfusion and infarct core volume) for a favorable outcome of AIS. Results A total of 138 patients (including 70 cases of good outcomes) were included in our study. Patients with favorable prognoses were correlated with better collateral circulations on both color-coded and conventional mCTA, and smaller hypoperfusion and infarct core volume (all P < 0.05) on CTP. ROC curves revealed no significant difference between the predictive capability of color-coded and conventional mCTA ( P = 0.427). The predictive value of CTP parameters tended to be inferior to that of color-coded mCTA score (all P < 0.001). Both junior and senior observers had consistently excellent performances (κ = 0.89) when analyzing color-coded mCTA maps. Conclusion Color-coded mCTA provides prognostic information of patients with AIS equivalent to or better than that of conventional mCTA and CTP. Junior radiologists can reach high diagnostic accuracy when interpreting color-coded mCTA images.

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