Perfect Sensitivity Research Articles

Influence of pentoxifylline on gene expression of PAG1/ miR-1206/ SNHG14 in ischemic heart disease

The regulation by immune checkpoint is able to prevent excessive tissue damage caused by ischemia reperfusion (I/R); therefore, the study aims to investigate the behavior of phosphoprotein associated with glycosphingolipid-enriched microdomains 1 (PAG1) mRNA, miR-1206 and small nucleolar RNA host gene 14 (SNHG14) during I/R and intake of pentoxifylline (PTX) as a protective drug. The relative expression level of PAG1/miR-1206/SNHG14 was determined by qRT-PCR. Cardiac tissue levels of cytotoxic T-lymphocyte associated antigen 4 (CTLA4) and PAG1 protein expression were determined by ELISA technique. The regulatory T cells achieved by the flow cytometry. The results found that the relative expression of SNHG14 was significantly upregulated in I/R, but suppressed in PTX treated groups with enhancement of the relative expression level of miR-1206. The gene and protein expression of PAG1 were downregulated with effective doses of PTX. The results showed that (30 and 40 mg/kg bwt) PTX dose suppressed the CTLA4 development significantly. The mean of the regulatory T cell in PTX protective groups is significantly reduced at (p < 0.001) in a comparison with I/R group. Spearman's correlation analysis revealed a significant negative correlation between SNHG14 and miR-1206, but a significant positive correlation between SNHG14 and PAG1 in I/R heart tissue. The results indicated that miR-1206 and SNHG14 can be used as biomarkers with perfect sensitivity and specificity. Using PTX reduced cardiac tissue damage. SNHG14 and miR-1206 can be used as a diagnostic tool in I/R.

New cut-score to improve performance of the Memory Validity Profile (MVP) in heterogenous clinical populations

ABSTRACT The Memory Validity Profile (MVP) is a standalone performance validity test developed specifically for use with children. Prior research has demonstrated the MVP’s strength in its ease of administration to children with a wide range of intellectual abilities. However, it has been found to lack sensitivity in detecting noncredible performance in select clinical populations using published cutoffs. The current study examines the MVP’s performance in a diagnostically heterogeneous clinical sample and proposes a new cutoff for optimization of sensitivity and specificity. Archival clinical data were examined from 96 participants referred for a comprehensive neuropsychological evaluation (ages 6–18). Receiver operating characteristic analysis was used to assess the discriminative ability of MVP in detecting cases of noncredible performance defined as failures on both the Test of Memory Malingering and Reliable Digit Span. Using published cutoffs, the MVP demonstrated perfect specificity (100%) but suboptimal sensitivity (33.3%). Receiver operating characteristic analysis revealed strong discrimination using MVP Total score (AUC = 0.891 (p < 0.001)) and a MVP Total cut-score of ≤30 resulted in optimal sensitivity (89%) and specificity (63%). Our findings provide additional evidence that published MVP cutoffs may be too lenient to adequately capture instances of noncredible performance and indicate an MVP Total score cutoff of ≤30 may be more appropriate for use with heterogeneous clinical populations.

Diagnostic challenges in gastric adenocarcinoma: a case report

Occam’s razor dictates that the simplest diagnosis is usually the correct one. In ascites of unknown origin, the top differentials must include cirrhosis, malignancy and cardiac failure. Investigations such as ascitic fluid cytology and computed tomography can help identify the underlying pathology, however, these investigations do not have perfect specificity and sensitivity. Thus, “normal” investigations cannot be used to completely dismiss important differentials. In a middle-aged patient with no evidence of cirrhosis or cardiac failure, Occam’s razor suggests that a surgeon thoroughly consider and definitively exclude an occult malignancy prior to removing it from the list of differentials.

Development of a Real-time System for Detecting Driver"s Cognitive Load using Multi-Layer Artificial Neural Network on ECG Signals

Objective: This study developed a real-time system to detect driver"s cognitive load using a multi-layer artificial neural network (MANN) based on electrocardiography (ECG) signals. The real-time system was aimed at classifying driver"s status into either normal or overload.Background: Driving with cognitive load is considered as one of significant factors for traffic accidents. Thus, an early detection of this risky status while driving is needed to prevent vehicle accidents.Method: The ECG signals of this study were measured from 22 participants who performed simulator-based driving experiment under two different conditions (1: normal driving, 2: overload driving (driving while doing a two-back task or an arithmetic task)). A real-time detection system was developed using MANN on the ECG signals and its effectiveness was evaluated for two new participants who drove under the two driving conditions.Results: The MANN model used for the real-time detection system showed perfect accuracy (100%), sensitivity (100%), and specificity (100%) for both of the training and testing data sets. In addition, the proposed real-time detection system successfully detected the change of participant"s status with a reasonable time delay (mean = 4.5 seconds).Conclusion: This study demonstrated that the ECG signals can be used as a biometric measure for the detection of the driver"s cognitive status in real-time.Application: The proposed detection system would be useful for the development of an intelligent vehicle that can provide timely interventions and/or warnings at the early onset of cognitive overload.

Intraoperative Neuromonitoring in Patients with Intradural Extramedullary Spinal Cord Tumor: A Single-Center Case Series

Intradural extramedullary spinal cord tumors (ID-EMSCT) make up 40% of all spinal neoplasms. Resection of these tumors is mostly conducted using intraoperative neuromonitoring (IONM). However, the literature shows heterogenous data on its added value for ID-EMSCT. The aim of this study is to define sensitivity and specificity of IONM in ID-EMSCT resection and to study possible correlations between preoperative, intraoperative, and postoperative variables and neurologic outcomes after ID-EMSCT resection. Data of patients undergoing ID-EMSCT surgeries with IONM from January 2012 until July 2019 were examined. Using neurologic status 6 weeks and 1 year postoperatively, sensitivity and specificity for IONM were calculated. IONM test results and neurologic outcomes were paired to preoperative, intraoperative, and postoperative parameters. Data of 78 patients were analyzed. 6 weeks postoperatively, 14.10% of patients had worse neurologic status, decreasing to 9.84% 1 year postoperatively. Multimodal IONM showed a sensitivity of 0.73 (95% confidence interval [CI], 0.39-0.94) and a specificity of 0.78 (95% CI, 0.66-0.87) after 6 weeks, and a sensitivity of 1.00 (95% CI, 0.54-1.00) and a specificity of 0.71 (95% CI, 0.57-0.82) after 1 year. IONM yielded high to perfect sensitivity and high specificity. However, IONM signals did not always determine the extent of resection, and false-positive results did not always result in incomplete tumor resections, because of surgeons overruling IONM. Therefore, IONM cannot fully replace clinical judgment and other perioperative information.

Discriminating complicated from uncomplicated appendicitis by ultrasound imaging, computed tomography or magnetic resonance imaging: systematic review and meta-analysis of diagnostic accuracy

BackgroundDiscriminating complicated from uncomplicated appendicitis is crucial. Patients with suspected complicated appendicitis are best treated by emergency surgery, whereas those with uncomplicated appendicitis may be treated with antibiotics alone. This study aimed to obtain summary estimates of the accuracy of ultrasound imaging, CT and MRI in discriminating complicated from uncomplicated appendicitisMethodsA systematic literature review was conducted by an electronic search in PubMed, Embase and the Cochrane Library for studies describing the diagnostic accuracy of complicated versus uncomplicated appendicitis. Studies were included if the population comprised adults, and surgery or pathology was used as a reference standard. Risk of bias and applicability were assessed with QUADAS-2. Bivariable logitnormal random-effect models were used to estimate mean sensitivity and specificity.ResultsTwo studies reporting on ultrasound imaging, 11 studies on CT, one on MRI, and one on ultrasonography with conditional CT were included. Summary estimates for sensitivity and specificity in detecting complicated appendicitis could be calculated only for CT, because of lack of data for the other imaging modalities. For CT, mean sensitivity was 78 (95 per cent c.i. 64 to 88) per cent, and mean specificity was 91 (85 to 99) per cent. At a median prevalence of 25 per cent, the positive predictive value of CT for complicated appendicitis would be 74 per cent and its negative predictive value 93 per cent.ConclusionUltrasound imaging, CT and MRI have limitations in discriminating between complicated and uncomplicated appendicitis. Although CT has far from perfect sensitivity, its negative predictive value for complicated appendicitis is high.

Whole-genome sequencing of clinical Clostridioides difficile isolates reveals molecular epidemiology and discrepancies with conventional laboratory diagnostic testing

The high clinical burden of Clostridioides difficile infections merits rapid and sensitive identification of affected individuals. However, effective diagnosis remains challenging. Current best practice guidelines recommend molecular and/or direct toxin detection-based screening for symptomatic individuals, but previous work has called into question the concordance and performance of extant clinical assays. To better correlate the genomic and phenotypic properties of clinical C.difficile isolates with laboratory testing outcomes in both C.difficile-infected patients and asymptomatic carriers. Whole-genome sequencing of clinical C.difficile isolates collected from an inpatient population at a single healthcare institution was performed, enabling examination of their molecular epidemiology and toxigenic gene content. Genomic findings were compared with clinical testing outcomes, identifying multiple diagnostic discrepancies. Toxigenic culture, considered a 'reference standard', provided perfect sensitivity and specificity in predicting toxigenic gene content, whereas reduced performance was observed for Simplexa C.difficile Direct Assay (100% specificity, 88% sensitivity), Gene Xpert CD/Epi Assay (86% specificity, 83% sensitivity), and Quick Check Complete Tox A/B (100% specificity, 30% sensitivity). Genomic analysis additionally revealed variability in toxin gene sequences among C.difficile strains, phylogenomic equivalency between isolates from affected patients and carriers, and patient carriage with uncommon environmentally derived C.difficile lineages, as well as presenting opportunities for tracing pathogen transmission events. These results highlight the variable performance of clinical stool-based testing approaches as well as the potential diagnostic utility of whole-genome sequencing as an alternative to conventional testing algorithms.

Identification and evaluation of Polygonatum kingianum with different growth ages based on data fusion strategy

Polysaccharide, the main component of Polygonatum kingianum, has been proven to have many pharmacological effects, such as antioxidant, anti-aging and anti-bacteria. The accumulation of polysaccharides was greatly influenced by the growth age of P. kingianum. Therefore, a fast and low-cost chemometric method is needed to identify the growth age. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) and ultraviolet visible (UV-Vis) spectroscopy of P. kingianum with four growth ages (80 samples) were collected and analyzed by chemometric methods. The correlation between 13 agronomic traits and polysaccharide accumulation was discussed. A data fusion strategy was used to identify the growth age of P. kingianum by extracting the latent variables (LVs) and principal components (PCs) of the spectra. The results founded that the polysaccharide content showed a negative correlation the fibrous root number, leaf length, leaf width, stem diameter and fresh weight on the ground part. The ATR-FTIR and UV-Vis spectra in P. kingianum with different growth ages were similar. The regions of 1750–1500 cm−1, 1000–750 cm−1 and 200–250 nm, 330–360 nm are important variables for discriminating four growth ages of P. kingianum. The classification effect of data fusion models was better than that of single spectra models with 100% accuracy as well as perfect sensitivity and specificity. Hierarchical cluster analysis shown that the samples were divided into two categories: one 5-year-old and the other 2, 3 and 4-year-old. In summary, the polysaccharide content in 4-year-old P. kingianum by seed reproduction was the highest. Data fusion of ATR-FTIR and UV-Vis spectra combined with PLS-DA models could be used to accurately distinguish P. kingianum in different growth ages, which was valuable for the identification and evaluation of other medicinal and edible homologous plants. Meanwhile, it also provides a theoretical basis for the harvesting age and cultivation conditions of P. kingianum.

Imaging strategies for patients with suspicion of uncomplicated colic pain: diagnostic accuracy and management assessment.

Compare different imaging scenarios in the diagnosis of uncomplicated renal colic due to urolithiasis (URCU). A total of 206 prospectively included patients had been admitted with suspected URCU and had undergone abdominal plain film (APF), US and unenhanced CT after clinical STONE score evaluation. CT was the reference standard. We assessed sensitivity (Se), specificity (Spe) and Youden index for colic pain diagnosis, percentage of patients managed by urologic treatment with stone identified, percentage of alternative diagnoses (AD) and exposure to radiation, according to single imaging approaches, strategies driven by patient characteristics and conditional imaging strategies after APF and US. One hundred (48.5%) patients had a final diagnosis of URCU and 19 underwent urologic treatment. The conditional strategy, i.e. CT in patients who had no stone identified at US, had a perfect sensitivity and specificity. This enabled diagnosis of all stones requiring urology management while decreasing the number of CT exams by 22%. The strategy whereby CT was used when there was neither direct or indirect APF + US finding of colic pain nor alternative diagnoses in patients with a STONE score ≥ 10 had a sensitivity of 0.95 and a specificity of 0.99, identified 84% of stones managed by urologic treatment and decreased the number of CT examinations by 76%. In patients with clinical findings consistent with URCU, the use of ultrasound as first-line imaging modality, with CT restricted to patients with negative US and a STONE score ≥ 10, led to a sensitivity and specificity of above 95%, identified 84% of stones requiring urological management and reduced the number of CT scans needed by fourfold. • For diagnosis, the use of APF + US as first-line imaging, with CT restricted to patients with both a normal APF + US and a STONE score ≥ 10, provides both a sensitivity and specificity superior or equal to 95% and reduces the number of CT scans necessary by fourfold. • For management, the use of APF + US as first-line imaging, with CT restricted to patients with both a normal APF + US and a STONE score ≥ 10, maintains a 84% stone identification rate in urology-treated patients.

Author response: Prospective validation of the PML risk biomarker l -selectin and influence of natalizumab extended intervals

On behalf of all authors, we would like to thank Mr. Tugemann for his interest in our article.1 It is correct that acute progressive multifocal leukoencephalopathy (PML) can, in some circumstances, lead to high(er) CD62L values. However, as the study was conducted prospectively and, more importantly, alongside treatment, we reported all results of samples shipped to us back to the treating physicians. At the time of measurement and reporting, we were not aware of the patients' disease state. Because this is the situation to be expected in postmarketing settings, we chose to report all measured values, even if the samples turned out to be less than 6 months before PML diagnosis. Although the exclusion of these samples would indeed have led to a perfect sensitivity with the threshold of 36.05, we believed that it would not accurately reflect the real-world situation. Similarly, we chose not to focus on other PML risk stratification factors such as previous immune suppression or anti-JC virus antibody serostatus because we could not rely on having this information for all samples shipped to us. We, therefore, decided to report on the feasibility of measuring one biomarker rather than presenting a holistic approach for risk stratification using all available markers, which was addressed before.2 As supported by this study, CD62L was proven to be a useful biomarker for PML risk stratification also in the real-world setting but could also help with monitoring immunologic changes because of natalizumab-extended interval dosing. Owing to its initial detection in a retrospective cohort, the validated methodology3 still requires a mandatory freeze/thaw cycle, thereby limiting its widespread use. However, we would be more than happy if methodological improvements could be achieved here.

Machine Learning and Clinical Prediction Rules: A Perfect Match?

* Abbreviations: EHR — : electronic health record PCA — : principal component analysis The field of machine learning involves the study of algorithms that can be used to discover mathematical functions for classification and prediction. Increasing computational power and larger data sets have allowed for the detection of complex, multidimensional associations not discoverable with traditional statistical modeling techniques, such as logistic regression. In this issue of Pediatrics , Ramgopal et al1 apply a mix of traditional statistical techniques and machine learning to the vexing problem of the young infant (≤60 days) with fever. Several clinical decision rules have been developed to help the clinician decide which patients are at low risk of bacterial infection and can forego lumbar puncture and/or hospital admission. The authors used a public use data set from the Pediatric Emergency Care Applied Research Network (PECARN) study of young infants with fever and tested several different models to attempt to improve on PECARN’s own decision rule.2 The authors were indeed able to improve on the PECARN decision rule, achieving an improvement in specificity from 60% to 75% without a loss of almost perfect sensitivity. They were able to accomplish this despite a small data set by machine learning standards, with only 138 patients with bacterial infection. The most successful model was a random forest … Address correspondence to James M. Chamberlain, MD, Division of Emergency Medicine, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC 20010. E-mail: jchamber{at}childrensnational.org

Real-Time Automatic Seizure Detection Using Ordinary Kriging Method in an Edge-IoMT Computing Paradigm

Epilepsy is one of the leading neurological diseases in the world, affecting approximately 70 million of the world’s population and often results in early mortality if not properly managed. The primary purpose of seizure detection is to reduce threat to life in the event of a seizure crisis. Previous efforts in the literature concentrate mostly on performance based on accuracy and other similar metrics. However, there is a short time lapse between the onset of a seizure attack and a potential injury that could claim the life of the patient. Therefore, there is the need for a more time-sensitive seizure detection model. We hereby propose a real-time seizure detection model in an edge computing paradigm using the ordinary kriging method, relying on the premise that the brain can be modeled as a three-dimensional spatial object, similar to a geographical panorama where kriging excels. Fractal dimensional features were extracted from patients’ electroencephalogram (EEG) signals and then classified using the proposed ordinary kriging model. The proposed model achieves a training accuracy of 99.4% and a perfect sensitivity, specificity, precision and testing accuracy. Hardware implementation in an edge computing environment results in a mean detection latency of 0.85 s. To the best of the authors’ knowledge, this is the first work that uses the kriging method for early detection of seizure.

Reaction-based highly selective and sensitive monomer/polymer probes with Schiff base groups for the detection of Hg2+ and Fe3+ ions.

It is urgent and important to detect heavy metals in environments. In this work, novel reaction-based fluorescent probes were obtained by Schiff base reaction. The probes with Schiff base moiety (-C=N-) undergo irreversible hydrolysis in the presence of Hg2+ and Fe3+. They exhibit perfect high selectivity and sensitivity to Hg2+and Fe3+ ions. Upon the addition of Hg2+and Fe3+, fluorescence intensity of the probes increased notably. And the color of the probe changes from brown to bright green under UV light, which can realize "naked eye" detection. In addition, Schiff base group was introduced into polyurethane chain through condensation polymerization reaction. As expected, the fluorescent polyurethane probe (P2) maintained the detection performance of its original small molecules (BSD). Even more P2 showed a more sensitive detection effect than BSD, and the detection limits of P2 for Hg2+ and Fe3+ reach 0.19μM and 0.21μM, respectively. It indicates that Reaction-based probes could be a useful tool for the detection of Hg2+ and Fe3+.

Development of a novel nomogram incorporating platelet-to-lymphocyte ratio for the prediction of lymph node involvement in prostate carcinoma

ObjectiveThe available nomograms used to predict lymph node involvement (LNI) are not comprehensive. We sought to derive a novel nomogram incorporating the platelet to lymphocyte ratio (PLR) to predict LNI and compare its performance to validated preoperative risk nomograms in a cohort of men undergoing robotic-assisted radical prostatectomy at our institution. MethodsOur electronic health record was queried for patients who underwent robotic-assisted radical prostatectomy with bilateral pelvic lymphadenectomy between 2013 and 2019. A bootstrapped multivariate logistic regression model was constructed for the predictors of LNI while adjusting for other covariates. Then, we used the derived logistic regression formula to estimate each patient's risk (%) for LNI. Individualized risks were also calculated using the following verified nomograms: Briganti-2012, Cagiannos, Godoy, and Memorial Sloan Kettering Cancer Center. Subsequently, we plotted the risks for our nomogram and the 4 verified nomograms into receiver operating characteristics curves. We reported the area under the curve (AUC) for each of the 5 nomograms and the corresponding 95% confidence interval (CI). ResultsThe cohort included 173 patients, of which 13.9% demonstrated LNI. LNI was associated with higher preoperative prostate-specific antigen (PSA) ≥ 10 [odds ratio [OR] = 4.89; 95% confidence interval [CI] (1.42–16.83)], higher grade (WHO group ≥ 3)[19.21; (2.23–195.25)], and higher percentage of positive biopsy cores (≥60%) [3.38, (1.04–11.00)]. With every 30-unit increase in PLR the risk of LNI increased by 47%. The nomogram derived from our data had the highest AUC [(AUC 0.877; 95% CI (0.806–0.947)]. The Memorial Sloan Kettering Cancer Center and Briganti 2012 displayed almost congruent ability [0.836; 95% CI (0.758–0.915)] and [0.827; (0.752–0.902)] to identify patients with positive nodes in our cohort with perfect sensitivity and negative predictive value. ConclusionThe nomogram incorporating PLR demonstrated 94.7% sensitivity to predict LNI and avoided pelvic lymphadenectomy in half of the patients at a cut-off between 6.5% and 8.5%. A prospective study with a larger sample is needed to validate our findings.

Targeted Informatics for Optimal Detection, Characterization, and Quantification of FLT3 Internal Tandem Duplications Across Multiple Next-Generation Sequencing Platforms

Assessment of internal tandem duplications in FLT3 (FLT3-ITDs) and their allelic ratio (AR) is recommended by clinical guidelines for diagnostic workup of acute myeloid leukemia and traditionally performed through capillary electrophoresis (CE). Although significant progress has been made integrating FLT3-ITD detection within contemporary next-generation sequencing (NGS) panels, AR estimation is not routinely part of clinical NGS practice because of inherent biases and challenges. In this study, data from multiple NGS platforms—anchored multiplex PCR (AMP), amplicon [TruSeq Custom Amplicon (TSCA)], and hybrid-capture—were analyzed through a custom algorithm, including platform-specific measures of AR. Sensitivity and specificity of NGS for FLT3-ITD status relative to CE were 100% (42/42) and 99.4% (1076/1083), respectively, by AMP on an unselected cohort and 98.1% (53/54) and 100% (48/48), respectively, by TSCA on a selected cohort. Primer analysis identified criteria for ITDs to escape detection by TSCA, estimated to occur in approximately 9% of unselected ITDs. Allelic fractions under AMP or TSCA were highly correlated to CE, with linear regression slopes near 1 for ITDs not duplicating primers, and systematically underestimated for ITDs duplicating a primer. Bias was alleviated in AMP through simple adjustments. This article provides an approach for targeted computational FLT3-ITD analysis for NGS data from multiple platforms; AMP was found capable of near perfect sensitivity and specificity with relatively accurate estimates of ARs.

Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening.

A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a “second opinion” for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

The round window sign: a sensitive sign to detect perilymphatic fistulae on delayed postcontrast 3D-FLAIR sequence.

The aim of this study is to assess the diagnostic performance of a new MR sign, named the round window sign (RWS), to diagnose perilymphatic fistula (PLF) in a population of patients with chronic cochleo-vestibular symptoms, classified as definite or probable Menière's disease (MD). A total of 164 patients (mean age 52 ± 35years) with chronic cochleo-vestibular symptoms underwent MRI, between 4 and 5h after intravenous gadoteric acid injection (Dotarem®, 0.1mmol/kg). MRI exploration was carried out on a 3-T Achieva® TX scanner. We analyzed the presence of the RWS, defined as a nodular FLAIR high signal in the round window (RW) and the presence of associated saccular hydrops. When this RWS was present, a temporal bone CT scan was performed and the RW was analyzed. Of the 164 patients with definite MD (85 patients) or probable MD (79 patients), we found the RWS in 18 (11%), and 17/18 were classified into the group of probable MD. All these 18 patients showed other MR sequences considered as normal, including heavily weighted T2 imaging. Among these 18 patients, the temporal bone CT examination presented a filling of the RW in 13 patients (72%) and no filling of the RW in 5 patients (28%). Seven patients were surgically managed confirming in vivo the PLF diagnosis. The RWS was associated with the presence of a saccular hydrops in 4 cases. Delayed postcontrast 3D-FLAIR may reveal perilymphatic fistulae in patients with probable Menière's disease using the round window sign. • MRI with delayed acquisition can detect perilymphatic fistulae with perfect sensitivity, based on the presence of the round window sign. • This visual sign is only visible on a 3D-FLAIR sequence. • 3D-FLAIR sequence with delayed acquisition is more sensitive than temporal bone CT scan examination in detecting PLF.

Reader response: RCVS2 score and diagnostic approach for reversible cerebral vasoconstriction syndrome.

We read with interest the article by Rocha et al.,1 who developed a new diagnostic tool to distinguish reversible cerebral vasoconstriction syndrome (RCVS) from other intracranial arteriopathies. The RCVS2 score performed perfect specificity and sensitivity for the differential diagnosis between RCVS and non-RCVS arteriopathy at admission. However, there were some issues, which should be raised. First, as a retrospective study, there was a limited sample size in a stroke center (30 RCVS vs 80 non-RCVS). Prospective studies with larger samples from multiple centers in the other sites of the United States or the other countries are urgently needed to confirm. Second, besides the objective 3 variables of RCVS2 score (carotid artery involvement, sex, and subarachnoid hemorrhage), both the thunderclap headache and vasoconstrictive trigger were derived from the patients' subjective complaints and lack of golden standard to assess, which may lead to higher false positivity. Third, using the data from a published cohort,2 this study only validated to distinguish RCVS from primary angiitis of the CNS, not including all the non-RCVS arteriopathies just as mentioned in the derivation cohort, such as moyamoya disease, intracranial atherosclerosis, secondary vasculitis, and radiation-induced arteriopathy. As a quite novel tool for accurate differential diagnosis of RCVS and non-RCVS, more available clinical variables, imaging features (such as vascular wall imaging3 and transcranial color-coded sonography4), and other biomarkers are warranted to confirm such findings.

SAT-422 Evaluation of the Siemens Thyroid Stimulating Immunoglobulin (TSI) Assay for Diagnosis and Prognosis of Graves’ Disease

Background: Hyperthyroidism due to Graves’ disease (GD) is an autoimmune condition caused by thyroid stimulating hormone receptor (TSHR) autoantibodies. Autoantibodies to the TSHR can stimulate or block thyroid hormone production, therefore testing specifically for stimulating antibodies would be beneficial for diagnosis of GD. Objectives: The primary objective of the first phase of this trial is to assess the diagnostic capability of the Siemens Thyroid Stimulating Immunoglobulin (TSI) immunoassay in diagnosing GD and to compare it with the Roche TSH Receptor Antibody (TRAb) assay. Design and Methods: Two hundred patients with suspected GD are being enrolled in this single-center multiphase prospective cohort study. Consenting patients undergo biochemical testing including thyroid stimulating hormone (TSH), free T3 (FT3) and T4 (FT4), TRAb and TSI measurements. GD diagnosis was confirmed by endocrinologists that were blinded to TSI results. Results: To date, 85 patients were included in the analysis, of which 66 were diagnosed with GD. For the primary analysis, all patients taking anti-thyroid drugs (ATD) at time of sample collection (n=14) were removed. The respective sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for TSI was 98, 84, 94 and 94%, which were comparable to those generated by TRAb (98, 95, 95, and 98%). In patients with clinical findings of GD (ie. orbitopathy or goiter, n=33), both the TSI and TRAb assays had identical sensitivity and specificity at 96% and 80% respectively. In patients without orbitopathy or goiter (n=38), the TSI assay had perfect sensitivity and excellent specificity of 100% and 86% respectively (TRAb had 100% sensitivity and specificity). Sensitivity, specificity, NPV, and PPV were slightly lower for both TSI and TRAb in patients treated with ATDs compared to patients without treatment (TSI: 85, 84, 62, 95%; TRAb: 91, 95, 75, 98%). Of ten patients with GD and false negative TSI results, nine were on ATDs. Of this subset, four patients had discordant results between TSI (negative) and TRAb (positive). Notably, one of these patients had normalization of their FT3 and FT4 on the day of sample collection. Discussion and Conclusion: Based on our preliminary results, TSI is an excellent marker for diagnosing GD, particularly in untreated GD patients. The performance of the TSI assay has been comparable to the TRAb assay and correlates well with clinical findings. Discordant false negative results were only seen in patients on ATD. One potential explanation is that the TSI assay is detecting a decrease in stimulating autoantibodies when there is normalization of FT3 and FT4. Importantly, all discordant samples will be tested by a TSI bioassay to confirm diagnosis. Further patient enrollment is occurring, and prognostic assessment of these assays will soon be possible.

Interval-censored data with misclassification: a Bayesian approach

Survival data involving silent events are often subject to interval censoring (the event is known to occur within a time interval) and classification errors if a test with no perfect sensitivity and specificity is applied. Considering the nature of this data plays an important role in estimating the time distribution until the occurrence of the event. In this context, we incorporate validation subsets into the parametric proportional hazard model, and show that this additional data, combined with Bayesian inference, compensate the lack of knowledge about test sensitivity and specificity improving the parameter estimates. The proposed model is evaluated through simulation studies, and Bayesian analysis is conducted within a Gibbs sampling procedure. The posterior estimates obtained under validation subset models present lower bias and standard deviation compared to the scenario with no validation subset or the model that assumes perfect sensitivity and specificity. Finally, we illustrate the usefulness of the new methodology with an analysis of real data about HIV acquisition in female sex workers that have been discussed in the literature.