Joint hypothesis testing of the area under the receiver operating characteristic curve and the Youden index

Evaluating joint confidence region of hypervolume under ROC manifold and generalized Youden index

In biomarker evaluation/diagnostic studies, the hypervolume under the receiver operating characteristic manifold (HUM K $$ {\mathrm{HUM}}_K $$ ) and the generalized Youden index (J K $$ {J}_K $$ ) are the most popular measures for assessing classification accuracy under multiple classes. WhileHUM K $$ {\mathrm{HUM}}_K $$ is frequently used to evaluate the overall accuracy,J K $$ {J}_K $$ provides direct measure of accuracy at the optimal cut-points. Simultaneous evaluation ofHUM K $$ {\mathrm{HUM}}_K $$ andJ K $$ {J}_K $$ provides a comprehensive picture about the classification accuracy of the biomarker/diagnostic test under consideration. This article studies both parametric and non-parametric approaches for estimating the confidence region ofHUM K $$ {\mathrm{HUM}}_K $$ andJ K $$ {J}_K $$ for a single biomarker. The performances of the proposed methods are investigated by an extensive simulation study and are applied to a real data set from the Alzheimer's Disease Neuroimaging Initiative.

Correlation between TMJ Space Alteration and Disc Displacement: A Retrospective CBCT and MRI Study

This study aims to determine if a large anterior and reduced posterior/superior joint space is highly predictable for disc displacement. From patients with temporomandibular disorders symptoms, fifty-two experimental joints and fourteen control joints were included. The cone beam computed tomography (CBCT) images were used to calculate posterior-to-anterior (P-A) and superior-to-anterior (S-A) joint space ratios, while disc position was determined using magnetic resonance imaging (MRI). One-way analysis of covariance test and receiver operating characteristics analysis were carried out. The results showed that among the 52 experimental joints, 45 were diagnosed as disc displacement and 7 as normal disc positions (N). All 14 control joints showed normal disc positions. The P-A ratio was 1.46 ± 0.21, 0.99 ± 0.23, and 0.86 ± 0.30 in the control, N, and DD groups, respectively (p < 0.001). The S-A ratio was 1.80 ± 0.27, 1.44 ± 0.33, and 1.08 ± 0.35 in the control, N, and DD groups, respectively (p < 0.001). When an altered P-A ratio and/or S-A ratio are observed on the CBCT, the diagnosis of disc displacement is quite predictable with high sensitivity and specificity.

Psychometric Testing and Validation of the Italian Version of the Helsinki Chronic Pain Index (I-HCPI) in Dogs with Pain Related to Osteoarthritis

Pain assessment is of paramount importance for properly managing dogs with osteoarthritis (OA) pain. The aim of the present study was to develop and psychometrically validate the Italian version of the Helsinki Chronic Pain Index (I-HCPI). Owners of OA painful (n = 87) and healthy dogs (n = 40) were administered the I-HCPI once or twice after an eight-week meloxicam treatment. Sixty-nine owners of healthy and OA dogs also completed the Italian version of the Canine Brief Pain Inventory (I-CBPI). Pain on palpation on a 0-4 scale was assessed on all recruited dogs. Construct validity was tested both with hypothesis testing and principal component analysis, confirming the I-HCPI accurately measured chronic pain. Good convergent and criterion validity were shown through correlations with I-CBPI subscores and distribution among pain on palpation scores (p < 0.0001). The significant difference between the pre- and post-treatment I-HCPI scores (p < 0.0001) and Cohen's effect size (2.27) indicated excellent responsiveness. The I-HCPI was shown to be reliable through communalities (range 0.47-0.90) and Cronbach α (≥0.95). Discriminative ability and cut-off point, as tested through Receiver Operating Characteristic analysis, showed excellent diagnostic accuracy with a threshold value of 11 (specificity 0.98 and sensitivity 0.94). The I-HCPI was confirmed to be a valid, sensitive, reliable, and accurate tool to discriminate between dogs with and without pain.

Predictive value of ELWI combined with sRAGE/esRAGE levels in the prognosis of critically ill patients with acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is a life-threatening condition. Accurate judgement of the disease progression is essential for controlling the condition in ARDS patients. We investigated whether changes in the level of serum sRAGE/esRAGE could predict the 28-day mortality of ICU patients with ARDS. A total of 83 ARDS patients in the ICU of the Second Affiliated Hospital of Nantong University from January 2021 to June 2022 were consecutively enrolled in this study. Demographic data, primary diagnosis and comorbidities were obtained. Multiple scoring systems, real-time monitoring systems, and biological indicators were determined within 6 h of admission. The clinical parameters for survival status of the ARDS patients were identified by multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was employed to verify the accuracy of the prognosis of the related parameters. The admission level of sRAGE was significantly higher in the nonsurvival group than in the survival group (p < 0.05), whereas the serum esRAGE level showed the opposite trend. Multivariate logistic regression analysis showed that sRAGE (AUC 0.673, p < 0.05), esRAGE (AUC 0.704, p < 0.05), and ELWI (extravascular lung water index) (AUC 0.717, p < 0.05) were independent risk factors for the prognosis of ARDS. Model B (ELWI + esRAGE) could not be built as a valid linear regression model (ELWI, p = 0.079 > 0.05). Model C (esRAGE + sRAGE) was proven to have no significance because it had a predictive value similar to that of the serum levels of esRAGE (Z = 0.993, p = 0.351) or sRAGE (Z = 1.116, p = 0.265) alone. Subsequently, Model D (sRAGE + esRAGE + ELWI) showed the best 28-day mortality predictive value with a cut-off value of 0.426 (AUC 0.841; p < 0.001), and Model A (sRAGE + ELWI) had a cut-off value of 0.401 (AUC 0.820; p < 0.001), followed by sRAGE (AUC 0.704, p = 0.004), esRAGE (AUC 0.717, p = 0.002), and ELWI (AUC 0.637, p = 0.028). In addition, there was no statistically significant difference between Model A and Model D (Z = 0.966, p = 0.334). The admission level of sRAGE was higher in the nonsurvival group, while the serum esRAGE level showed the opposite trend. Model A and Model D could be used as reliable combined prediction models for predicting the 28-day mortality of ARDS patients.

A Novel Approach for Prediction of Lung Disease Using Chest X-ray Images Based on DenseNet and MobileNet

Covid19 corona virus has caused widespread disruption across the world, in terms of the health, economy, and society problems. X-ray images of the chest can be helpful in making an accurate diagnosis because the corona virus typically first manifests its symptoms in patients' lungs. In this study, a classification method based on deep learning is proposed as a means of identifying lung disease from chest X-ray images. In the proposed study, the detection of covid19 corona virus disease from chest X-ray images was made with MobileNet and Densenet models, which are deep learning methods. Several different use cases can be built with the help of MobileNet model and case modelling approach is utilized to achieve 96% accuracy and an Area Under Curve (AUC) value of 94%. According to the result, the proposed method may be able to more accurately identify the signs of an impurity from dataset of chest X-ray images. This research also compares various performance parameters such as precision, recall and F1-Score.

Maximum bilateral bite strength and RMS EMG for the diagnosis of myogenic TMD

Aim: The study aimed to evaluate the accuracy of the maximum bilateral molar bite force and the Root Mean Square (RMS) Electromyography (EMG) index of the masticatory muscles in the maximum bilateral molar bite (MMBMax) of women with myogenic Temporomandibular Disorder (TMD) and asymptomatic. Methods: This is a cross-sectional study, composed of 86 women allocated to the TMD Group (n=43) and Control Group (n=43) diagnosis through the Diagnostic Criteria for Temporomandibular Disorders. The maximum bilateral molar bite force was evaluated using a bite dynamometer and the RMS EMG index of the masticatory muscles (anterior temporalis, masseter) during 5 seconds of the MMBMax task. Student t-test was used for data comparison between accuracy of the bite force and RMS EMG of masticatory muscles during the MMBMax. Results: The maximum bilateral molar bite force showed high accuracy (AUC=0.99) for the diagnosis of women with myogenic TMD and asymptomatic women, and the RMS EMG index evaluated during the MMBMax showed a moderate level of accuracy for all masticatory muscles (AUC=0.70 to 0.75). Conclusion: The bilateral bite dynamometer with a surface EMG during bilateral bite can be used to diagnose TMD in young women.

Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina

Over the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluate the relationship between the incidence of begomovirus and weather before and during the crop cycle. Soybean and bean fields from north-western (NW) Argentina were monitored between 2001 and 2018 and classified as moderate (≤50%) or severe (>50%) according to the begomovirus incidence. Bean golden mosaic virus (BGMV) and soybean blistering mosaic virus (SbBMV) were the predominant begomovirus in bean and soybean crops, respectively. Nearly 200 bio-meteorological variables were constructed by summarizing climatic variables in 10-day periods from July to November of each crop year. The studied variables included temperature, precipitation, relative humidity, wind (speed and direction), pressure, cloudiness, and visibility. For bean, high maximum winter temperatures, low spring humidity, and precipitation 10 days before planting correlated with severe incidence. In soybeans, high temperatures in late winter and in the pre-sowing period, and low spring precipitations were found to be good predictors of high incidence of begomovirus. The results suggest that temperature and pre-sowing precipitations can be used to predict the incidence status [predictive accuracy: 80% (bean) and 75% (soybean)]. Thus, these variables can be incorporated in early warning systems for crop management decision-making to reduce the virus impact on bean and soybean crops.

Validity of a combination of periodontal pathogens and salivary biomarkers as predictors of periodontitis

OBJECTIVE

Chronic periodontitis is caused by multiple risk factors. To predict chronic periodontitis in older people, we evaluated the association between a combination of major periodontal pathogens and salivary biomarkers and the presence of periodontitis.

METHODS

Stimulated saliva samples were collected to analyze the prevalence of Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, and Prevotella intermedia, as well as four biomarkers: interleukin (IL)-1β, IL-6, tumor necrosis factor-α (TNF-α), and prostaglandin E2 (PGE2). A total of 201 Japanese patients were recruited. Oral examinations ware performed to determine chronic periodontitis as measured by Community Periodontal Index. The sociodemographic and behavioral characteristics were also obtained, and the parameters were adjusted as potential confounders to employ statistical models.

RESULTS

The odds ratio (OR) for the presence of P. gingivalis and the third tertile level of IL-1β as compared with the absence of P. gingivalis and the lowest tertile of IL-1β was highest in individuals with periodontitis (OR = 13.98; 95% confidence interval [CI] 3.87-50.52) with the best level (0.79) of area under the curve (AUC) based on the receiver operating characteristic curve. The OR for the presence of P. gingivalis and the third tertile of PGE2 was 7.76 (CI 1.89-31.91) with an AUC of 0.78. The coexistence of more than two periodontal bacteria and the third tertile of PGE2 was also strongly associated with chronic periodontitis (OR = 9.23, 95% CI 2.38-35.79) with an AUC of 0.76.

CONCLUSIONS

The combined information of the presence of P. gingivalis in stimulated saliva, and higher levels of salivary IL-1β may play a vital role in the detection and prediction of chronic periodontitis in older adults.

Can really plasma interleukin-6 predict postoperative delirium among patients undergoing open repair surgery of acute type A aortic dissection?

The letter to the editor was written in response to “Plasma interleukin-6 is a potential predictive biomarker for postoperative delirium (POD) among acute type a aortic dissection patients treated with open surgical repair”, which is recently published by Lv et al. (J Cardiothorac Surg 16(1):146, 2021). In this article, Lv et al. conclude that plasma IL-6 is a potential biomarker for prediction of POD. However, we note several issues in this study that would have made interpretation of their results questionable. Our main concerns include the use of a short POD assessment time, no providing the data of analgesics and sedatives used in the ICU, application of incorrect statistical methods when assessing predictive ability of plasma IL-6 for the development of POD, and incorrect interpretation for the area under the receiver operating characteristic curve. We believe that addressing these issues will improve the transparency of this study and help the interpretation of findings.

Joint inference about the AUC and Youden index for paired biomarkers

It is common to compare biomarkers' diagnostic or prognostic performance using some summary ROC measures such as the area under the ROC curve (AUC) or the Youden index. We propose to compare two paired biomarkers using both the AUC and the Youden index since the two indices describe different aspects of the ROC curve. This comparison can be made by estimating the joint confidence region (an elliptical area) of the differences of the paired AUCs and the Youden indices. Furthermore, for deciding if one marker is better than the other in terms of both the A U C and the Youden index (J), we can test H 0 : A U C a ≤ A U C b or J a ≤ J b against H a : A U C a > A U C b and J a > J b using the paired differences. The construction of such a joint hypothesis is an example of the multivariate order-restricted hypotheses. For such a hypothesis, we propose and compare three testing procedures: (1) the intersection-union test ( I U T ); (2) the conditional test; and (3) the joint test. The performance of the proposed inference methods was evaluated and compared through simulations. The simulation results demonstrate that the proposed joint confidence region maintains the desired confidence level, and all three tests maintain the type I error under the null. Furthermore, among the three proposed testing methods, the conditional test is the preferred approach with markedly larger power consistently than the other two competing methods.

Determining association between blood glucose variability and postoperative delirium in acute aortic dissection patients: methodological issues

The letter to the editor made several comments regarding possible methodological issues in the recent article by Lin et al. determining the association between blood glucose variability and postoperative delirium in patients undergoing acute aortic dissection surgery with cardiopulmonary bypass, which is published in Journal of Cardiothoracic Surgery. 2021; 16(1):82. Our concerns included the lack of some important perioperative factors associated with postoperative delirium, the process of establishing multivariate model and the method of using the receiver operating characteristic curve analysis to assess the predictive performance of the standard deviation of blood glucose for the development of POD. We would like to invite the authors to comment on these and believe that clarifying these issues would improve the transparency of this study and interpretation of findings.

Adrenomedullin Is a Diagnostic and Prognostic Biomarker for Acute Intracerebral Hemorrhage

Hemorrhagic stroke remains an important health challenge. Adrenomedullin (AM) is a vasoactive peptide with an important role in cardiovascular diseases, including stroke. Serum AM and nitrate-nitrite and S-nitroso compounds (NOx) levels were measured and compared between healthy volunteers (n = 50) and acute hemorrhagic stroke patients (n = 64). Blood samples were taken at admission (d0), 24 h later (d1), and after 7 days or at the time of hospital discharge (d7). Neurological severity (NIHSS) and functional prognosis (mRankin) were measured as clinical outcomes. AM levels were higher in stroke patients at all times when compared with healthy controls (p < 0.0001). A receiving operating characteristic curve analysis identified that AM levels at admission > 69.0 pg/mL had a great value as a diagnostic biomarker (area under the curve = 0.89, sensitivity = 80.0%, specificity = 100%). Furthermore, patients with a favorable outcome (NIHSS ≤ 3; mRankin ≤ 2) experienced an increase in AM levels from d0 to d1, and a decrease from d1 to d7, whereas patients with unfavorable outcome had no significant changes over time. NOx levels were lower in patients at d0 (p = 0.04) and d1 (p < 0.001) than in healthy controls. In conclusion, AM levels may constitute a new diagnostic and prognostic biomarker for this disease, and identify AM as a positive mediator for hemorrhagic stroke resolution.