Combined serum amylase and lipase determinations for diagnosis of suspected acute pancreatitis

1993 ◽  
Vol 39 (12) ◽  
pp. 2495-2499 ◽  
Author(s):  
J P Corsetti ◽  
C Cox ◽  
T J Schulz ◽  
D A Arvan
Keyword(s):  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Test Performance ◽  
Serum Amylase ◽  
Discriminant Functions ◽  
Clinical Implementation ◽  
Sensitivity Specificity ◽  
Bivariate Approach

Abstract Serum amylase and lipase measurements are often used to diagnose acute pancreatitis. This study addresses the question of whether it is advantageous to order serum amylase and lipase tests simultaneously. We evaluated performance of the two tests separately and in combination through a retrospective study of patients for whom both amylase and lipase determinations were ordered. Initial analysis of test performance was conducted with a uniformly applied criterion based on determination of optimal sensitivity-specificity pairs. Individual tests and combinations of tests, including the "AND" and "OR" rules and discriminant functions, were examined. Only the discriminant approach demonstrated better performance than the lipase test alone. This finding was subsequently confirmed by logistic regression analysis. We conclude that ordering both tests simultaneously can be advantageous in diagnosing acute pancreatitis when a bivariate approach is used; however, this must be weighed against the difficulties associated with clinical implementation of such approaches.

DECISION MAKING BY VARIABLE CONTRIBUTION IN DISCRIMINANT, LOGIT, AND REGRESSION ANALYSES

2004 ◽  
Vol 03 (02) ◽  
pp. 265-279 ◽  
Author(s):  
STAN LIPOVETSKY ◽  
MICHAEL CONKLIN
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Statistical Models ◽  
Regression Analyses ◽  
Discriminant Functions ◽  
Multivariate Statistical ◽  
Linear Discriminant ◽  
Variable Contribution ◽  
Linear Aggregate

Comparative contribution of predictors in multivariate statistical models is widely used for decision making on the importance of the variables for the aims of analysis and prediction. However, the analysis can be made difficult because of the predictors' multicollinearity that distorts estimates for coefficients in the linear aggregate. To solve the problem of the robust evaluation of the predictors' contribution, we apply the Shapley Value regression analysis that provides consistent results in the presence of multicollinearity both for regression and discriminant functions. We also show how the linear discriminant function can be constructed as a multiple regression, and how the logistic regression can be approximated by linear regression that helps to obtain the variables contribution in the linear aggregate.

scholarly journals Compositional and drug-resistance profiling of pathogens in patients with severe acute pancreatitis: a retrospective study

2020 ◽  
Author(s):  
Ning Fan ◽  
Yong Hu ◽  
Hong Shen ◽  
Shengjie Liu ◽  
Guang Zhao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Bacterial Infection ◽  
Drug Resistant ◽  
Bacterial Strains ◽  
Unconditional Logistic Regression ◽  
Gram Positive ◽  
Gram Negative

Abstract Background: Infection is one of the important causes of death in patients with severe acute pancreatitis (SAP) , but the bacterial spectrum and antibiotic resistance are constantly changing. Making good use of antibiotics and controlling multi-drug-resistant (MDR) bacterial infections are of vital importance in improving the cure rate of SAP. We conducted a retrospective study in the hope of providing references for antibiotic selection and control of drug-resistant bacteria. Methods: Retrospective analysis was performed on the data of patients hospitalized in our hospital due to acute pancreatitis (AP) in the past 5 years. General data were classified and statistically analyzed. Subsequently, the bacterial spectrum characteristics and the data related to drug-resistant bacterial infection of 569 AP patients were analyzed. Finally, unconditional logistic regression analysis was conducted to analyze the risk factors of MDR infection. Results: A total of 398 patients were enrolled in this study and the hospitalization data and associated results were analyzed. A total of 461 strains of pathogenic bacteria were detected, including 223 (48.4%) gram-negative bacterial strains, 190 (41.2%) gram-positive bacterial strains and 48 (10.4%) fungal strains. The detection rates of resistance in gram-negative and gram-positive bacterial strains were 48.0% (107/223) and 25.3% (48/190), respectively. There were significant differences between the MDR group and the non-MDR group for the factors of precautionary antibiotic use, kinds of antibiotics used, receipt of carbapenem, tracheal intubation, hemofiltration and number of hospitalization days in the intensive care unit. Unconditional logistic regression revealed 2 risk factors for MDR bacterial infection. Conclusions: Our results illustrate that gram-negative bacteria were the most common pathogens in SAP infection, and the proportion of gram-positive bacteria increased notably. The rate of antibiotic resistance was higher than previously reported. Unconditional logistic regression analysis showed that using more types of antibiotics and the number of hospitalization days in the ICU were the risk factors associated with MDR bacterial infection.

scholarly journals “A Four-Leaf Clover” Sign for Rapid Identification of Coagulase-Negative Staphylococci by Gram Staining From Positive Blood Culture: A Cross-Sectional Study

2020 ◽  
Author(s):  
Takahiro Matsuo ◽  
Kuniyoshi Hayashi ◽  
Aki Sakurai ◽  
Masumi Suzuki Shimizu ◽  
Masaya Morimoto ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Blood Culture ◽  
Positive Predictive Value ◽  
Positive Blood Culture ◽  
Predictive Value ◽  
Blood Cultures ◽  
Coagulase Negative Staphylococci ◽  
Gram Staining ◽  
Sensitivity Specificity

Abstract Background: Coagulase-negative staphylococci (CoNS) are one of the most common contaminant microorganisms isolated from blood cultures. Few studies exploring the use of Gram staining to distinguish between Staphylococcus aureus (SA) and CoNS have been reported. Here, this study aimed to explore whether morphological features of Gram staining could identify SA or CoNS.Methods: This study was conducted at St. Luke’s International Hospital from November 2016 to September 2017. The positive blood cultures for which the Gram staining showed gram-positive cocci (GPC) in clusters were included in our study. The direct smear of Gram staining obtained from positive blood culture bottles were examined within 24 hours of positivity. We have identified and characterized the following two signs: “four-leaf clover (FLC)” if 4 GPC gathered like a planar four-leaf clover and “grapes” if the GPC gathered like grapes in a three-dimensional form. The number of fields with FLC and grapes signs in 10 fields per slide with ×1,000 power was counted, and the results in a total of 20 fields with ×1,000 power were combined. We performed a logistic regression analysis to assess whether these signs could serve as factors distinguishing between SA and CoNS. The predictive ability of these signs was evaluated based on the sensitivity, specificity, positive predictive value, and negative predictive value for CoNS via receiver operating curve analysis.Results: In total, 106 blood cultures for which Gram staining showed GPC in clusters were examined; 46 (43%) were SA, and 60 (57%) were CoNS samples. The result of multivariate logistic regression analysis showed that the FLC sign was a statistically significant marker of CoNS with an odds ratio of 1.31 (95 % confidential interval (CI): 1.07–1.61, p<0.05). In aerobic bottles, sensitivity, specificity, positive predictive value, and negative predictive value for CoNS were 0.67, 0.91, 0.92, and 0.65, respectively, and the value of area under the curve was 0.79 (95% CI: 0.67–0.91).Conclusions: To our knowledge, this is the first study to show that the FLC could be a rapid and useful indicator to identify CoNS in aerobic bottles. Thus, the presence of FLC sings could help clinicians to suspect the possibility of CoNS before the final identification by cultures.

scholarly journals Elastography for the Diagnosis of High-Suspicion Thyroid Nodules Based on the 2015 American Thyroid Association Guidelines: A Multicenter Study

2020 ◽  
Author(s):  
Hairu Li ◽  
Yulan Peng ◽  
Yan Wang ◽  
Hong Ai ◽  
Xiaodong Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Reference Method ◽  
Final Analysis ◽  
American Thyroid Association ◽  
Diagnostic Efficiency ◽  
Sensitivity Specificity

Abstract Background: An accurate diagnosis for high-suspicion nodules based on the 2015 American Thyroid Association (ATA) guidelines would reduce unnecessary invasive examinations. Elastography is a useful tool for discriminating benign and malignant thyroid nodules. The aim of this study is to investigate the diagnostic efficiency of elastography for high-suspicion thyroid nodules based on the 2015 ATA guidelines in the Chinese population.Methods: Thyroid nodules with high-suspicion characteristics based on the 2015 ATA guidelines were subjected to conventional ultrasound (US) and ultrasound strain elastography (USE) examinations at 12 hospitals from 4 geographic regions across China. Cytology/histology of thyroid nodules was used as a reference method. Receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic performance of the elasticity score (ES) and strain ratio (SR). Logistic regression analysis was used to determine the predictors of malignancy.Results: Overall, a total of 1445 thyroid nodules (834 malignant, 611 benign) from 12 centers were included in the final analysis. The areas under the curve of the ES and SR were 0.828 and 0.732, respectively. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the ES were 92.4%, 60.7%, 79.0%, 76.3% and 85.5%, respectively, and those of the SR were 81.1%, 50.1%, 68.9%, 65.9% and 67.9%, respectively. The combination of the Thyroid Imaging Reporting and Data System (TI-RADS) and ES led to a significant increase in the sensitivity and NPV (97.1% and 91.9%, respectively) compared with the TI-RADS alone. Logistic regression analysis showed that microcalcifications (OR=5.290), taller than wide (OR=12.710), irregular margins (OR=10.117), extrathyroidal extension (ETE; OR=6.412), the ES (OR=3.741) and the SR (OR=1.083) were independent predictors of malignant thyroid nodules. The sensitivity, specificity, accuracy, PPV and NPV of the ES were all superior in nodules ≥1 cm than in those <1 cm (95.0% vs 90.4%, 68.8% vs 56.8%, 85.9% vs 74.4%, 85.2% vs 69.9%, and 87.8% vs 84.2%, respectively).Conclusions: Elastography combined with the ES is a valuable tool for the assessment of high-suspicion thyroid nodules based on the 2015 ATA guidelines, especially in nodules ≥1 cm.

scholarly journals Elastography for the Diagnosis of High-Suspicion Thyroid Nodules Based on the 2015 American Thyroid Association Guidelines: A Multicenter Study

2020 ◽  
Author(s):  
Hairu Li ◽  
Yulan Peng ◽  
Yan Wang ◽  
Hong Ai ◽  
Xiaodong Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Reference Method ◽  
Final Analysis ◽  
American Thyroid Association ◽  
Diagnostic Efficiency ◽  
Sensitivity Specificity

Abstract Background: An accurate diagnosis for high-suspicion nodules based on the 2015 American Thyroid Association (ATA) guidelines would reduce unnecessary invasive examinations. Elastography is a useful tool for discriminating benign and malignant thyroid nodules.Aims: To investigate the diagnostic efficiency of elastography for high-suspicion thyroid nodules based on the 2015 ATA guidelines in the Chinese population.Materials and Methods: Thyroid nodules with high-suspicion characteristics based on the 2015 ATA guidelines were subjected to conventional ultrasound (US) and ultrasound strain elastography (USE) examinations at 12 hospitals from 4 geographic regions across China. Cytology/histology of thyroid nodules was used as a reference method. Receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic performance of the elasticity score (ES) and strain ratio (SR). Logistic regression analysis was used to determine the predictors of malignancy.Results: Overall, a total of 1445 thyroid nodules (834 malignant, 611 benign) from 12 centers were included in the final analysis. The areas under the curve of the ES and SR were 0.828 and 0.732, respectively. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the ES were 92.4%, 60.7%, 79.0%, 76.3% and 85.5%, respectively, and those of the SR were 81.1%, 50.1%, 68.9%, 65.9% and 67.9%, respectively. The combination of the Thyroid Imaging Reporting and Data System (TI-RADS) and ES led to a significant increase in the sensitivity and NPV (97.1% and 91.9%, respectively) compared with the TI-RADS alone. Logistic regression analysis showed that microcalcifications (OR=5.290), taller than wide (OR=12.710), irregular margins (OR=10.117), extrathyroidal extension (ETE; OR=6.412), the ES (OR=3.741) and the SR (OR=1.083) were independent predictors of malignant thyroid nodules. The sensitivity, specificity, accuracy, PPV and NPV of the ES were all superior in nodules ≥1 cm than in those <1 cm (95.0% vs 90.4%, 68.8% vs 56.8%, 85.9% vs 74.4%, 85.2% vs 69.9%, and 87.8% vs 84.2%, respectively).Conclusions: Elastography combined with the ES is a valuable tool for the assessment of high-suspicion thyroid nodules based on the 2015 ATA guidelines, especially in nodules ≥1 cm.

scholarly journals Nomogram for Predicting Persistent Organ Failure with Acute Pancreatitis in Pregnancy

2022 ◽  
Author(s):  
Chengcheng Sheng ◽  
Zongxu Xu ◽  
Jun Wang
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Organ Failure ◽  
Multivariate Logistic Regression Analysis ◽  
Concordance Index ◽  
Multivariate Logistic Regression ◽  
Independent Risk Factors ◽  
In Pregnancy

Abstract Background: Acute pancreatitis in pregnancy (APIP) with persistent organ failure (POF) poses a high risk of death for mother and fetus. This study sought to create a nomogram model for early prediction of POF with APIP patients.Methods: We conducted a cross-sectional study on APIP patients with organ failure (OF) between January 2012 and March 2021 in a university hospital. 131 patients were collected. Their clinical courses and pregnancy outcomes were obtained. Risk factors for POF were identified by univariate and multivariate logistic regression analysis. Prediction models with POF were built and nomogram was plotted. The performance of the nomogram was evaluated by using a bootstrapped-concordance index and calibration plots.Results: Hypertriglyceridemia was the most common etiology in this group of APIP patients, which accounted for 50% of transient organ failure (TOF) and 72.3% of POF. All in-hospital maternal death was in the POF group (P<0.05), which also had a significantly higher perinatal mortality rate than the TOF group (P<0.05). Univariate and multivariate logistic regression analysis determined that lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were independent risk factors for predicting POF in APIP. A nomogram for POF was created by using the four indicators. The area under the curve was 0.875 (95% confidence interval 0.80–0.95). The nomogram had a bootstrapped-concordance index of 0.85 and was well-calibrated.Conclusions: Hypertriglyceridemia was the leading cause of organ failure-related APIP. Lactate dehydrogenase, triglycerides, serum creatinine, and procalcitonin were the independent risk factors of POF in APIP. Our nomogram model showed an effective prediction of POF with the four indicators in APIP patients.

Determination of amylase activity in serum by using a wheat germ inhibitor with the Du Pont aca.

1986 ◽  
Vol 32 (8) ◽  
pp. 1539-1541 ◽  
Author(s):  
D A Lacher ◽  
M B Harize
Keyword(s):  
Acute Pancreatitis ◽  
Wheat Germ ◽  
Serum Amylase ◽  
Amylase Activity ◽  
Reference Interval ◽  
Pancreatic Amylase ◽  
Wheat Germ Extract ◽  
Rapid Procedure ◽  
Assay Conditions

Abstract A rapid procedure for determining salivary- and pancreatic-type amylase (EC 3.2.1.1) in serum by incorporating a wheat germ inhibitor (from Triticum aestivum) was developed for the Du Pont aca IV analyzer. Under optimal assay conditions, activities of salivary and pancreatic amylase were inhibited by 93% and 19%, respectively. The 95% central reference interval for the percentage of inhibition of serum amylase was 38-84%. Patients with acute pancreatitis showed less than 26% inhibition of amylase after addition of the wheat germ extract, reflecting the prevalence of pancreatic-type amylase in this disorder.

scholarly journals Diabetes and Younger Age Are Vital and Independent Risk Factors for Acute Pancreatitis in Patients with Severe Hypertriglyceridemia

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Qiang Li ◽  
Chaoqun Hou ◽  
Yunpeng Peng ◽  
Xiaole Zhu ◽  
Chenyuan Shi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Severe Hypertriglyceridemia ◽  
Younger Age ◽  
History Of ◽  
Independent Risk Factors

Background. The incidence of hypertriglyceridemia-induced acute pancreatitis (HIAP) is increasing worldwide, and now it is the third leading cause of acute pancreatitis in the United States. But, there are only 5% of patients with severe hypertriglyceridemia (>1000 mg/dl) which might generate acute pancreatitis. In order to explore which part of the patients is easy to develop into pancreatitis, a case-control study was performed by us to consider which patient population tend to develop acute pancreatitis in patients with severe hypertriglyceridemia. To perform a retrospective case-control study, we identified severe hypertriglyceridemia patients without AP (HNAP) and with HIAP with a fasting triglyceride level of >1000 mg/dl from The First Affiliated Hospital of Nanjing Medical University during January 1, 2014, to December 31, 2016. Baseline patient characteristics, comorbidities, and risk factors were recorded and evaluated by the univariate and multivariate logistic regression analysis for HIAP and HNAP patients. A total of 124 patients with severe hypertriglyceridemia were included in this study; of which, 62 patients were in the HIAP group and 62 were in the HNAP group. Univariate logistic regression analysis showed that there was no gender difference in both groups; however, there were more younger patients in the HIAP group than in the HNAP group (P value < 0.001), and the HIAP group had low level of high-density lipoprotein compared to the HNAP group (P<0.05). Meanwhile, the presence of pancreatitis was associated with higher level of glycemia and a history of diabetes (P<0.05). Multivariate logistic regression analysis indicated that a history of diabetes and younger age were independent risk factors for acute pancreatitis in patients with severe hypertriglyceridemia. Uncontrolled diabetes and younger age are potential risk factors in patients with severe hypertriglyceridemia to develop acute pancreatitis.

Determination of the factors affecting pre-service teachers’ technological self-efficacy beliefs by logistic regression analysis

2021 ◽  
Vol 9 (2) ◽  
pp. 481-488
Author(s):  
Nurcan Tekin ◽  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Personal Computer ◽  
Self Efficacy ◽  
Material Design ◽  
Efficacy Beliefs ◽  
Instructional Technologies ◽  
Factors Affecting

Technology transfer to classes has become very important for teachers, regardless of their field. The purpose of this study is to determine how pre-service teachers with high and low level of technological self-efficacy beliefs are predicted by the independent variables. These variables are attitude towards technology, attitude towards instructional technologies and material design course, having a personal computer. The study sample of this relational study consisted of 193 pre-service teachers. As data collection tools, Technological Self-Efficacy Belief Scale, Attitude towards Technology Scale, Attitude towards Instructional Technologies Scale, and a questionnaire developed by researchers were administered. Logistic regression analysis, which is used when the dependent variable is categorical, was employed in data analysis. According to analysis results, the variables of having a personal computer (Wald = 4.23, df = 1, p < 0.05), attitude towards technology (Wald = 13.66, df = 1, p < 0.01) and attitude towards instructional technologies and material design course (Wald = 6.17, df = 1, p < 0.01) had a significant effect on pre-service teachers’ technological self-efficacy beliefs. Particularly, the variable of having a personal computer significantly increased pre-service teachers’ technological self-efficacy beliefs by 20%. In this context, various recommendations were offered to the researchers, institutions and instructors.

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