Predicting outcomes in organophosphate poisoning based on APACHE II and modified APACHE II scores

2007 ◽  
Vol 26 (7) ◽  
pp. 573-578 ◽  
Author(s):  
N. Eizadi-Mood ◽  
M. Saghaei ◽  
M. Jabalameli
Keyword(s):  
Confidence Interval ◽  
Prognostic Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Emergency Situation ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Organophosphate Poisoning ◽  
Biochemical Tests ◽  
Operating Characteristic Curve

The aim of this study was to evaluate the scores of the Acute Physiology and Chronic Health Evaluation (APACHE) II and a modified APACHE II system (MAS), without parameters of biochemical tests; and to find prognostic value of individual elements of the APACHE II and MAS in predicting outcomes in organophosphate (OP) poisoning. Data were collected from 131 patients. The median (25th—75th percentiles) of APACHE II score for survivors without intubation were found to be lower than those of non survivors or survivors with intubation and ventilation, [4 (1—7); versus 17.5 (7.8—29), and 13.5 (7.8—16.3)]. Logistic regression analysis identified white blood cell (WBC), potassium, Glasgow coma scale (GCS), age and sodium in APACHE II; GCS and mean arterial pressure in MAS system as prognostically valuable. There was no statistically significance difference between APACHE II and MAS scores in terms of area under Receiver Operating Characteristic Curve [(0.902, 95% confidence interval: (0.837—0.947) for APACHE II), and (0.892, 95% confidence interval: (0.826—0.940) for MAS); P = 0.74) to predict need for intubation. It is concluded usage of MAS facilitates the prognostication of the OP poisoned patients due to simplicity, less time-consuming and effectiveness in an emergency situation. Human & Experimental Toxicology (2007) 26: 573—578.

Protein Carbonyl, But Not Malondialdehyde, Is Associated With ICU Mortality in Patients With Septic Shock

2017 ◽  
Vol 34 (8) ◽  
pp. 669-673 ◽  
Author(s):  
Nara Aline Costa ◽  
Ana Lucia Gut ◽  
Paula Schmidt Azevedo ◽  
Ana Angelica Henrique Fernandes ◽  
Bertha Furlan Polegato ◽  
...  
Keyword(s):  
Septic Shock ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Protein Carbonyl ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Icu Mortality ◽  
Logistic Regression Models ◽  
The Mean

Background:The objective of our study was to evaluate the association of serum malondialdehyde (MDA) and protein carbonyl concentration with intensive care unit (ICU) mortality in patients with septic shock.Methods:We prospectively evaluated 175 patients aged over 18 years with septic shock upon ICU admission. However, 16 patients were excluded. Thus, 159 patients were enrolled in the study. In addition, we evaluated 16 control patients. At the time of the patients’ enrollment, demographic information was recorded. Blood samples were taken within the first 24 hours of the patient’s admission to determine serum MDA and protein carbonyl concentrations.Results:The mean age was 67.3 ± 15.9 years, 44% were males, and the ICU mortality rate was 67.9%. Median MDA concentration was 1.53 (0.83-2.22) µmol/L, and median protein carbonyl concentration was 24.0 (12.7-32.8) nmol/mL. Patients who died during ICU stay had higher protein carbonyl concentration. However, there was no difference in MDA levels between these patients. Receiver operating characteristic curve analysis showed that higher levels of protein carbonyl were associated with ICU mortality (area under the curve: 0.955; 95% confidence interval [CI]: 0.918-0.992; P < .001) at the cutoff of >22.83 nmol/mL (sensibility: 80.4% and specificity: 98.1%). In the logistic regression models, protein carbonyl concentrations (odds ratio [OR]: 1.424; 95% CI: 1.268-1.600; P < .001), but not MDA concentrations (OR: 1.087; 95% CI: 0.805-1.467; P = .59), were associated with ICU mortality when adjusted for age, gender, and Acute Physiology and Chronic Health Evaluation (APACHE) II score; and when adjusted by APACHE II score, lactate, and urea; protein carbonyl concentrations (OR: 1.394; 95% CI: 1.242-1.564; P < .001); and MDA (OR: 1.054; 95% CI: 0.776-1.432; P = .73).Conclusion:In conclusion, protein carbonyl, but not MDA, concentration is associated with ICU mortality in patients with septic shock.

scholarly journals Enhanced neoplasia detection in chronic ulcerative colitis: the ENDCaP-C diagnostic accuracy study

2021 ◽  
Vol 8 (1) ◽  
pp. 1-88
Author(s):  
Ashish Awasthi ◽  
Jamie Barbour ◽  
Andrew Beggs ◽  
Pradeep Bhandari ◽  
Daniel Blakeway ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Confidence Interval ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Chronic Ulcerative Colitis ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Added Value ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Background Chronic ulcerative colitis is a large bowel inflammatory condition associated with increased colorectal cancer risk over time, resulting in 1000 colectomies per year in the UK. Despite intensive colonoscopic surveillance, 50% of cases progress to invasive cancer before detection. Detecting early (precancer) molecular changes by analysing biopsies from routine colonoscopy should increase neoplasia detection. Objectives To establish a deoxyribonucleic acid (DNA) marker panel associated with early neoplastic changes in ulcerative colitis patients. To develop the DNA methylation test for high-throughput analysis within the NHS. To prospectively evaluate the test within the existing colonoscopy surveillance programme. Design Module 1 analysed 569 stored biopsies from neoplastic and non-neoplastic sites/patients using pyrosequencing for 11 genes that were previously reported to have altered promoter methylation associated with colitis-associated neoplasia. Classifiers were constructed to predict neoplasia based on gene combinations. Module 2 translated analysis to a NHS laboratory, assessing next-generation sequencing to increase speed and reduce cost. Module 3 applied the molecular classifiers within a prospective diagnostic accuracy study, in the existing ulcerative colitis surveillance programme. Comparisons were made between baseline and reference colonoscopies undertaken in a stratified patient sample 6–12 months later. Setting Thirty-one UK hospitals. Participants Patients with chronic ulcerative colitis, either for at least 10 years and extensive disease, or with primary sclerosing cholangitis. Interventions An optimised DNA methylation classifier tested on routine mucosal biopsies taken during colonoscopy. Main outcome Identifying ulcerative colitis patients with neoplasia. Results Module 1 selected five genes with specificity for neoplasia. The optimism-adjusted area under the receiver operating characteristic curve for neoplasia was 0.83 (95% confidence interval 0.79 to 0.88). Precancerous neoplasia showed a higher area under the receiver operating characteristic curve of 0.88 (95% confidence interval 0.84 to 0.92). Background mucosa had poorer discrimination (optimism-adjusted area under the receiver operating characteristic curve was 0.68, 95% confidence interval 0.62 to 0.73). Module 2 was unable to develop a robust next-generation sequencing assay because of the low amplification rates across all genes. In module 3, 818 patients underwent a baseline colonoscopy. The methylation assay (testing non-neoplastic mucosa) was compared with pathology assessments for neoplasia and showed a diagnostic odds ratio of 2.37 (95% confidence interval 1.46 to 3.82; p = 0.0002). The probability of dysplasia increased from 11.1% before testing to 17.7% after testing (95% confidence interval 13.0% to 23.2%), with a positive methylation result suggesting added value in neoplasia detection. To determine added value above colonoscopy alone, a second (reference) colonoscopy was performed in 193 patients without neoplasia. Although the test showed an increased number of patients with neoplasia associated with primary methylation changes, this failed to reach statistical significance (diagnostic odds ratio 3.93; 95% confidence interval 0.82 to 24.75; p = 0.09). Limitations Since the inception of ENDCaP-C, technology has advanced to allow whole-genome or methylome testing to be performed. Conclusions Methylation testing for chronic ulcerative colitis patients cannot be recommended based on this study. However, following up this cohort will reveal further neoplastic changes, indicating whether or not this test may be identifying a population at risk of future neoplasia and informing future surveillance programmes. Trial registration Current Controlled Trials ISRCTN81826545. Funding This project was funded by the Efficacy and Mechanism Evaluation programme, a Medical Research Council and National Institute for Health Research (NIHR) partnership, and will be published in full in Efficacy and Mechanism Evaluation; Vol. 8, No. 1. See the NIHR Journals Library website for further project information.

scholarly journals Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Sophie Lemmens ◽  
Toon Van Craenendonck ◽  
Jan Van Eijgen ◽  
Lies De Groef ◽  
Rose Bruffaerts ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Confidence Interval ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Retinal Imaging ◽  
Classification Model ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Introduction The eye offers potential for the diagnosis of Alzheimer’s disease (AD) with retinal imaging techniques being explored to quantify amyloid accumulation and aspects of neurodegeneration. To assess these changes, this proof-of-concept study combined hyperspectral imaging and optical coherence tomography to build a classification model to differentiate between AD patients and controls. Methods In a memory clinic setting, patients with a diagnosis of clinically probable AD (n = 10) or biomarker-proven AD (n = 7) and controls (n = 22) underwent non-invasive retinal imaging with an easy-to-use hyperspectral snapshot camera that collects information from 16 spectral bands (460–620 nm, 10-nm bandwidth) in one capture. The individuals were also imaged using optical coherence tomography for assessing retinal nerve fiber layer thickness (RNFL). Dedicated image preprocessing analysis was followed by machine learning to discriminate between both groups. Results Hyperspectral data and retinal nerve fiber layer thickness data were used in a linear discriminant classification model to discriminate between AD patients and controls. Nested leave-one-out cross-validation resulted in a fair accuracy, providing an area under the receiver operating characteristic curve of 0.74 (95% confidence interval [0.60–0.89]). Inner loop results showed that the inclusion of the RNFL features resulted in an improvement of the area under the receiver operating characteristic curve: for the most informative region assessed, the average area under the receiver operating characteristic curve was 0.70 (95% confidence interval [0.55, 0.86]) and 0.79 (95% confidence interval [0.65, 0.93]), respectively. The robust statistics used in this study reduces the risk of overfitting and partly compensates for the limited sample size. Conclusions This study in a memory-clinic-based cohort supports the potential of hyperspectral imaging and suggests an added value of combining retinal imaging modalities. Standardization and longitudinal data on fully amyloid-phenotyped cohorts are required to elucidate the relationship between retinal structure and cognitive function and to evaluate the robustness of the classification model.

scholarly journals Potential Metabolite Markers of Multiple Myeloma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3163-3163
Author(s):  
Jiliang Xia ◽  
Jingyu Zhang ◽  
Xuan Wu ◽  
ShiLian Chen ◽  
Jingchao Lin ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Confidence Interval ◽  
Peripheral Blood ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Petroselinic Acid ◽  
Characteristic Curve ◽  
Training Set ◽  
Operating Characteristic Curve ◽  
Testing Set

Abstract E-mail: [email protected] Background: Metabolism reprogramming is one of ten features in cancer. It is well known that metabolites in tumor microenvironment contribute to the survival and proliferation of cancer cells. Currently, a lack of detailed information about the metabolites profiling in bone marrow microenvironment limits us to understand the roles of metabolites associated with multiple myeloma(MM) and its diagnosis and treatment. Here we report a serum untargeted metabolomics study of MM patients, together with healthy donors(HD), with the aim of discovering metabolite markers associated with MM. Materials and Methods: Gas chromatography-time-of-flight mass spectrometry (GC-TOFMS)-based metabolomics was used to analyze 140 serum subjects, including 81 bone marrow subjects(22 HD, 59 MM patients) and 59 peripheral blood subjects(27 HD, 32 MM patients). The bone marrow subjects were divided into training set(11 HD, 32 MM patients) and testing set(11 HD, 27 MM patients). SIMCA-14.1 software package was used to visualize the metabolite alterations between MM patient and HD through Principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA). Both the T-test and the receiver operating characteristic curve(ROC) analysis were performed by SPSS software. Metabolites in serum with higher fold change(FC) and variable importance in the projection(VIP) value(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) were considered as biomarker candidates. Results: A total of 117 and 123 metabolites were annotated from the detected spectral features in bone marrow serum subjects derived from training set and testing set, respectively. Based on multivariate statistical analysis(PCA and OPLS-DA) and univariate statistical analysis(T-test), a panel of 6 and 10 metabolites were identified as differential metabolites(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) between MM patients and HD in training set and testing set, respectively, among of which 5 metabolites were found significantly altered in both sets. Creatinine and glycine were significantly elevated in MM patients compared with HD, while fatty acid consists of palmitic acid, petroselinic acid and stearic acida were found decreased in MM patients compared with HD. ROC analysis of these 5 metabolites resulted in an area under the receiver operating characteristic curve (AUC) of 0.922(95% confidence interval=0.748-1) in the training set and 0.923(95% confidence interval=0.853-1) in the testing set. Furthermore, the diagnostic potential of the metabolite signatures was assessed in peripheral blood subjects. Consistent with bone marrow subjects, metabolite signatures were significantly changed(VIP > 1.5, P < 0.05 and FC > 1.5, P < 0.05, FDR < 0.05) in peripheral blood subjects derived from MM patients compared with HD. The AUC of this metabolites signatures was 0.901(95% confidence interval=0.748-1) in peripheral blood subjects, implying that this panel of metabolites could be of potential clinical significance for the diagnosis of MM. Conclusion: We conclude that a panel of 5 metabolites, including creatinine, glycine, palmitic acid, petroselinic acid and stearic acid, in serum has great potential in discriminating MM patient from HD. This metabolite signatures provides a novel and promising molecular diagnostic approach for the detection of MM. Disclosures No relevant conflicts of interest to declare.

scholarly journals Prognostic Accuracy of a Novel Prognostic Score Using a Combination of PCT, DDi, and Lactate Biomarkers in Patients With Sepsis: A Retrospective Cohort Study

2021 ◽  
Author(s):  
Yansong miao ◽  
LiFeng Xing
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Prognostic Score ◽  
Laboratory Data ◽  
Apache Ii ◽  
Cutoff Points ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background A combination of multiple biomarkers will be more accurate in predicting the mortality of sepsis patients. Herein, we aimed to assess the ability to predict adverse outcomes of a novel scoring system using the combination of PCT, DDi, and lactate (PDLS) in patients with sepsis from the emergency department (ED) of a hospital. Methods The patients’ baseline characteristics, main laboratory data and outcome were collected from the patient's electronic medical record. A receiver operating characteristic curve (ROC) analysis determine the optimal cutoff points for biomarkers PCT, DDi and lactate and establish a PDLS system based on their cutoff points. ROC was used to compare the accuracy of PDLS to Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE) II scores in predicting short-term mortality in patients with sepsis. Results The analysis cohort included 1001 patients. 117 sepsis patients died in 28 days. An increase in PDLS was associated with higher mortality and adverse events including MV, VD, AICU, and CRRT. PDLS was an independent predictor of 28-day mortality, MV, VD, AICU, and CRRT. The Area Under the Receiver Operating Characteristic curve (AUROC) of PDLS (0.96; Cl=0.94-0.98) was significantly higher than that of SOFA (0.84; Cl=0.80-0.89) and APACHE II (0.84; Cl=0.79-0.88). Conclusion PDLS is an independent prognostic predictor of adverse clinical outcomes for sepsis patients and was superior to other prognostic scores, including SOFA and APACHE II.

Performance of the simplified acute physiology score III in acute organophosphate poisoning: A retrospective observational study

2017 ◽  
Vol 37 (3) ◽  
pp. 221-228 ◽  
Author(s):  
DH Lee ◽  
BK Lee
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Case Fatality ◽  
Simplified Acute Physiology Score ◽  
Acute Physiology Score ◽  
Apache Ii ◽  
Organophosphate Poisoning ◽  
Hospital Case ◽  
Saps Ii ◽  
Standardized Mortality Ratios

The performances of acute physiology and chronic health evaluation (APACHE) II and simplified acute physiology score (SAPS) II have previously been evaluated in acute organophosphate poisoning. We aimed to compare the performance of the SAPS III with those of the APACHE II and SAPS II, as well as to identify the best tool for predicting case fatality using the standardized mortality ratios (SMRs) in acute organophosphate poisoning. A retrospective analysis of organophosphate poisoning was conducted. The APACHE II, SAPS II, and SAPS III were calculated within 24 h of admission. Discrimination was evaluated by calculating the area under the receiver operating characteristic curve (AUROC). The SMRs were calculated as 95% confidence intervals (CIs). In total, 100 cases of organophosphate poisoning were included. The in-hospital case fatality was 19%. The median scores of the APACHE II, SAPS II, and SAPS III were 20.0 (10.0–27.0), 41.0 (28.0–54.8), and 53.0 (36.3–68.8), respectively. The AUROCs were not significantly different among the APACHE II (0.815; 95% CI, 0.712–0.919), SAPS II (0.820; 95% CI, 0.719–0.912), and SAPS III (0.850; 95% CI, 0.763–0.936). Based on these scores and in-hospital case fatality, the SMRs for the APACHE II, SAPS II, and SAPS III were 1.01 (95% CI, 0.50–2.72), 1.01 (95% CI, 0.54 -2.78), and 0.98 (95% CI, 0.33–1.99), respectively. The SAPS III provided a good discrimination and satisfactory calibration in acute organophosphate poisoning. It was therefore a useful tool in predicting case fatality in acute organophosphate poisoning, similar to the APACHE II and SAPS II.

Diagnostic usefulness of differential time to positivity in neutropenic cancer patients with suspected catheter-related candidemia

2019 ◽  
Vol 58 (1) ◽  
pp. 137-140
Author(s):  
Kyeong Min Jo ◽  
Sungim Choi ◽  
Kyung Hwa Jung ◽  
Jung Wan Park ◽  
Ji Hyun Yun ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Cancer Patients ◽  
Diagnostic Performance ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Optimal Cutoff ◽  
Cutoff Value ◽  
Time To Positivity ◽  
Diagnostic Usefulness ◽  
Operating Characteristic Curve

Abstract Methods for distinguishing catheter-related candidemia (CRC) from non-CRC before catheter removal remain limited. We thus evaluated the diagnostic performance of differential time to positivity (DTP) to diagnose CRC in neutropenic cancer patients with suspected CRC. Of the 35 patients enrolled, 15 (43%) with CRC (six definite and nine probable) and 17 (49%) with non-CRC were finally analyzed. Based on the receiver operating characteristic curve, the optimal cutoff value of DTP for diagnosing CRC was ≥1.45 hours with the sensitivity 80% (95% confidence interval [CI], 51–95) and specificity 100% (95% CI, 80–100), respectively.

scholarly journals Could IL-6 predict the clinical severity of COVID-19?

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Guzin Aykal ◽  
Hatice Esen ◽  
Derya Seyman ◽  
Tuğba Çalışkan
Keyword(s):  
Intensive Care Unit ◽  
Prognostic Value ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Clinical Severity ◽  
Longitudinal Analyses ◽  
Significant Difference ◽  
Severe Group ◽  
Operating Characteristic Curve ◽  
Excessive Inflammatory Response

Abstract Objectives An excessive inflammatory response to SARS-CoV-2 is thought to be a major cause of disease severity in COVID-19. The aim herein was to determine the prognostic value of IL-6, and demonstrate the comparison between IL-6 and related parameters in COVID-19. Methods Data were collected from 115 COVID-19 patients. Results The median age was 46.04 years in the mild group, 56.42 years in the moderate group, and 62.92 years in the severe group (p=0.001). There was a significant difference in the hospitalized clinic to intensive care unit ratio among the patients (p<0.001). The IL-6 values were significantly higher in the severe group than those in the mild (p=0.04) and moderate groups (p=0.043). The area under the receiver operating characteristic curve for IL-6, as predictor of severe clinical condition, was 0.864 (95% CI 0.765–0.963 p=0.000). The longitudinal analyses showed that the severe group presented with significantly increased IL-6 levels during hospitalization. Conclusions IL‐6 seemed to be a guide in the early diagnosis of severe COVID-19 and an ideal marker for monitoring negative outcome.

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