Negative Predictive Value Npv Research Articles

Validation of the Arabic version of the sleep apnea scale of the sleep disorders questionnaire SDQ-SA

BackgroundObstructive sleep apnea (OSA) is a widespread syndrome characterized by breathing cessation or reduction. It has a wide range of significant symptoms, such as snoring and fatigue. This study aimed to assess the validity of the Arabic version of the Sleep Disorders Questionnaire-Sleep Apnea Scale (SDQ-SA) as a screening tool in Arabic-speaking countries.MethodsThis study was conducted at a sleep disorders clinic at Damascus University’s hospitals from June 2023 to September 2023. Patients aged 18 to 75 who spoke Arabic were included, while those under 18 or over 75, with incomplete questionnaires, previous OSA diagnoses, or certain chronic diseases and sedative drug use were excluded. The questionnaire was translated into the Arabic language by two bilingual researchers. It was then given to around 15 patients to ensure clarity of the questions. The questionnaire was readministered to 30 participants to ensure reliability. After analyzing the results of the Arabic version of the SDQ-SA, we administered Polysomnography (PSG) type III tests to validate our results. Data analysis was conducted using Microsoft Excel and IBM SPSS version 22.ResultsThe study included 103 participants, with an average age of 56.55 years. The SDQ-SA identified 85 (82.5%) participants as being at high risk for having OSA. Among those classified as high risk, 39 (45.9%) had severe OSA, 34 (40%) had moderate OSA, 8 (9.4%) had mild OSA, and 4 (4.7%) had no OSA based on the apnea–hypopnea index (AHI) calculated by the PSG. On the other hand, 18 (17.5%) participants were classified as low risk for OSA, 3 (16.7%) had severe OSA, 3 (16.7%) had moderate OSA, 7 (38.9%) had mild OSA, and 5 (27.8%) had no OSA based on the AHI calculated by the PSG. For AHI ≥ 5, the sensitivity and specificity for men were 0.87 and 0.6, respectively, and for women, they were 0.84 and 0.5, respectively.ConclusionOur study showed that the Arabic version of the SDQ-SA questionnaire had good sensitivity and negative predictive value NPV, especially for patients with moderate to severe OSA. We recommend that physicians use this questionnaire and other similar questionnaires more frequently to identify and treat this underrecognized disease properly.

Evaluation of post-chemotherapy residual seminomatous masses by 18F-fluorodeoxyglucose PET/CT using tumor-to-liver ratio - conundrum or solution?

Assessment of diagnostic accuracy of FDG-PET/CT in the detection of viable disease in post-chemotherapy seminomatous residual masses using visual interpretation, SUVmax, and T/L ratio. This is a retrospective study assessing the post-chemotherapy seminomatous residual masses of size >3 cm. The PET/CT scan findings were interpreted visually for presence of residual disease which were validated from histopathology reports or imaging follow-up for a maximum of 3 years. SUVmax and T/L ratios were also determined for all the residual lesions. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value NPV were calculated and compared for all three parameters along with ROC analysis to obtain an optimal cutoff value for SUVmax and T/L ratio, respectively. Sample size was 49. Out of these 49 patients, 8 had validation of PET results with histopathology. Rest was validated with imaging follow-up. FDG-PET was positive in 30 patients and negative in 19 patients by visual interpretation. The sensitivity, specificity, PPV, and NPV by this method were 100%, 62.5%, 73%, and 100%, respectively. The SUVmax and T/L ratios were also calculated for these lesions. The cutoff for these two variables was 4.56 and 1.21, respectively. The sensitivity, specificity, PPV, and NPV at these cutoffs were 76%, 87.5%, 86%, 77.7%, and 92%, 87.5%, 88%, 91%, respectively. FDG-PET has a favorable diagnostic value in predicting viable disease in post-chemotherapy seminomatous residual masses and using T/L ratio cutoff of 1.21 will increase the specificity of the test.

A Neonatal Sequential Organ Failure Assessment Score as a Predictor of Mortality in Neonates with Late-Onset Sepsis

Background Late onset neonatal sepsis (LOS) is an important problem in neonatal intensive care units (NICUs).The occurrence of multi-organ dysfunction can result in mortality in neonates with LOS. Many scores are being developed to predict mortality in neonates with LOS. Aim Our aim was to test the validity of neonatal sequential organ failure assessment score (nSOFA) to identify NICU patients at a high risk of mortality among those with LOS dependent on routinely collected data . Patients and Methods This prospective observational study was conducted on neonates with late onset sepsis. Full history taking and complete clinical examination was undertaken. Complete blood count (CBC) including total leukocytic count (TLC), C- reactive protein (CRP) and blood culture were withdrawn from included neonates. nSOFA score was calculated for all included neonates using data from patients records. nSOFA score is a noval objective score that detect organ dysfunction in neonates with late onset sepsis, and used to identify the risk of mortality using data from patients records. Results The obtained results showed that, neonates who did not survive had significantly higher CRP and TLC significantly lower platelet count than those who survived. Also, neonates who did not survive had significantly higher median nSOFA score than survivors. In the current study, the sensitivity of nSOFA score on presentation to predict mortality in LOS neonates was 84.21% and its specificity was 80.39% with area under the curve (AUC) was 0.890%.Also positive predictive value PPV was 61.5% and negative predictive value NPV was 93.2%. Conclusion The nSOFA can be useful in predicting mortality in neonates with LOS. Further studies are needed to assess its utility in different gestational age groups.

Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks

To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool. A retrospective data set including 2000 de-identified images from intensive care unit patients was split into 1488 for training and 512 for testing. AI was developed to automatically identify the ETT, trachea, and carina using semantically embedded neural networks that combine a declarative knowledge base with deep neural networks. To check the ETT tip placement, a "safe zone" was computed as the region inside the trachea and 3-7 cm above the carina. Two AI outputs were evaluated: (1) ETT overlay, (2) ETT misplacement alert messages. Clinically relevant performance metrics were compared against prespecified thresholds of >85% overlay accuracy and positive predictive value (PPV) > 30% and negative predictive value NPV > 95% for alerts to move into clinical validation. An ETT was present in 285 of 512 test cases. The AI detected 95% (271/285) of ETTs, 233 (86%) of these with accurate tip localization. The system (correctly) did not generate an ETT overlay in 221/227 CXRs where the tube was absent for an overall overlay accuracy of 89% (454/512). The alert messages indicating that either the ETT was misplaced or not detected had a PPV of 83% (265/320) and NPV of 98% (188/192). The chest X-ray AI met prespecified performance thresholds to move into clinical validation.

Ankle Magnetic Resonance Imaging in Juvenile Idiopathic Arthritis Versus Non-Juvenile Idiopathic Arthritis Patients with Arthralgia.

This retrospective case–control study aimed to evaluate whether Magnetic Resonance Imaging (MRI) enables differentiation of ankle arthritis in Juvenile Idiopathic Afrthritis JIA from ankle arthralgia of unknown aetiology in patients clinically suspected of JIA. Forty-four children, at ages 5–16, who underwent MRI of the ankle from January 2016 to March 2021 for clinically suspected active ankle arthritis in the course of JIA were included. MRI findings in both groups—patients with the final diagnosis of JIA and without final diagnosis of JIA—were compared and scored. The sum of the scores of 22 ankle lesions in an individual patient (active, destructive and developmental), so-called the MRI summarized score, was calculated and tested in terms of the most optimal diagnosis of JIA. Interobserver agreement was calculated. Inflammatory features were seen on MRI in 38 out of all the included patients (86%). The most common lesions in both groups were effusion in the tibio-talar joint (68% in JIA and 64% in the arthralgia group) and effusion in subtalar joint (64% in JIA vs. 59% in the arthralgia group). In general, more lesions were identified in the JIA group than in non-JIA. However, only tenosynovitis was significantly more common in the JIA vs. non-JIA group (p = 0.031). The MRI summarized score did not allow for discrimination between ankle arthritis in JIA from non-JIA patients; the best levels of sensitivity (32%), specificity (91%), positive predictive value PPV (78%) and negative predictive value NPV (57%) were achieved only at the cut-off point of 10.

A deep learning approach for predicting severity of COVID-19 patients using a parsimonious set of laboratory markers

SummaryThe SARS-CoV-2 virus has caused tremendous healthcare burden worldwide. Our focus was to develop a practical and easy-to-deploy system to predict the severe manifestation of disease in patients with COVID-19 with an aim to assist clinicians in triage and treatment decisions. Our proposed predictive algorithm is a trained artificial intelligence-based network using 8,427 COVID-19 patient records from four healthcare systems. The model provides a severity risk score along with likelihoods of various clinical outcomes, namely ventilator use and mortality. The trained model using patient age and nine laboratory markers has the prediction accuracy with an area under the curve (AUC) of 0.78, 95% CI: 0.77–0.82, and the negative predictive value NPV of 0.86, 95% CI: 0.84–0.88 for the need to use a ventilator and has an accuracy with AUC of 0.85, 95% CI: 0.84–0.86, and the NPV of 0.94, 95% CI: 0.92–0.96 for predicting in-hospital 30-day mortality.

Diagnostic performance of a colorimetric RT -LAMP for the identification of SARS-CoV-2: A multicenter prospective clinical evaluation in sub-Saharan Africa.

BackgroundManagement and control of the COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus SARS-CoV-2 is critically dependent on quick and reliable identification of the virus in clinical specimens. Detection of viral RNA by a colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a simple, reliable and cost-effective assay, deployable in resource-limited settings (RLS). Our objective was to evaluate the intrinsic and extrinsic performances of RT-LAMP in RLS.MethodsThis is a multicenter prospective observational study of diagnostic accuracy, conducted from October 2020 to February 2021 in four African Countries: Cameroon, Ethiopia, Kenya and Nigeria; and in Italy. We enroled 1657 individuals who were either COVID-19 suspect cases, or asymptomatic and presented for screening. RNA extracted from pharyngeal swabs was tested in parallel by a colorimetric RT-LAMP and by a standard real time polymerase chain reaction (RT-PCR).FindingsThe sensitivity and specificity of index RT LAMP compared to standard RT-PCR on 1657 prospective specimens from infected individuals was determined. For a subset of 1292 specimens, which underwent exactly the same procedures in different countries, we obtained very high specificity (98%) and positive predictive value (PPV = 99%), while the sensitivity was 87%, with a negative predictive value NPV = 70%, Stratification of RT-PCR data showed superior sensitivity achieved with an RT-PCR cycle threshold (Ct) below 35 (97%), which decreased to 60% above 35.InterpretationIn this field trial, RT-LAMP appears to be a reliable assay, comparable to RT-PCR, particularly with medium-high viral loads (Ct < 35). Hence, RT-LAMP can be deployed in RLS for timely management and prevention of COVID-19, without compromising the quality of output.FundingBill & Melinda Gates Foundation [Grant No. INV-022,816].

A Deep Learning Approach for Predicting Severity of COVID-19 Patients Using a Parsimonious Set of Laboratory Markers

Background: SARS-CoV-2 virus has caused tremendous burden on both patients and providers across the globe. Our focus is to develop a practical and easy to deploy system to predict the severe manifestation of disease in COVID-19 patients with an aim to assist clinicians in triage and treatment decisions.Methods: We used multiple cohorts from 14,172 COVID-19 patients with captured clinical outcomes from four healthcare systems across the globe. Our proposed predictive algorithm is a trained artificial intelligence-based network using 8,427 patient records. We focused on building a parsimonious model with the fewest possible number of input parameters to facilitate clinical deployment. The model provides a severity risk score along with likelihoods of various clinical outcomes, namely ventilator use, end organ damage, and mortality.Findings: Model computed severity risk scores using nine laboratory markers taken from 4,293 patients at the initial presentation and the age have the prediction accuracy with the area under the curve (AUC) of 0 · 77 95% CI: 0·76-0·78, and the negative predictive value NPV of 0·87 95% CI: 0·85-0·87 for the need to use a ventilator. Similarly, the model has an accuracy with AUC of 0·83 95% CI: 0·82-0·84, and the NPV of 0·93 95% CI: 0·92-0·94 for predicting in-hospital 30-day mortality.Interpretations: Our deep learning model has a promising predictive performance in using various laboratory markers taken from patients admitted due to COVID-19 at the initial encounter to directly inform clinical and resource management and allocations, respectively.Funding: Provided through research and collaboration grants from Siemens Healthineers, Laboratory Diagnostics, Tarrytown, New York, USA.Declaration of Interests: VS, DC, JS, ER, RM, SV, DC, and AK are employees of Siemens Healthcare, USA. All other authors have nothing to declare. Ethics Approval Statement: This study was approved by the ethics committees at Hospital University of La Paz, Emory University Hospital, and Houston Methodist Hospital.

Tongue strength, dysphagia questionnaire, pharyngeal secretions and FEES findings in dysphagia management in amyotrophic lateral sclerosis

ObjectiveDysphagia is common in Amyotrophic lateral sclerosis (ALS). ALS shows significant phenotypic variability. It is characterized by progressive weakness and/or spasticity of muscles. Dysphagia symptoms vary. Aspiration is often silent and cognitive dysfunction is common. The purpose of the study was to evaluate tongue strength measurements, dysphagia questionnaire, the presence of pharyngeal secretions, and FEES findings in dysphagia management in ALS. MethodsTwenty-five patients completed the Eating Assessment Tool-10 (EAT-10), had their Maximum Isometric Tongue Pressure (MITP), and endurance measured and underwent Flexible Endoscopic Evaluation of Swallowing (FEES) providing 31 examinations. ResultsOut of 25 patients, 76% were self-reported as dysphagic (EAT-10≥3) with a mean EAT-10 at 14.95 (±7.96). ALS patients had significantly decreased tongue strength (mean MITPanterior: 31.69 ± 17.32kPa). Comparing examinations of dysphagic and non-dysphagic status the mean MITPa of non-dysphagic was significantly greater (52.33 ± 10.97 kPa versus 20.6 ± 12.67 kPa), p<0.001. FEES detected aspiration in 10 out of 31 examinations [Penetration Aspiration Scale(PAS) ≥6]. Aspirator status examinations showed statistically significantly worse cough (p = 0.001), tongue strength (p = 0.001) and endurance (p = 0.003), pharyngeal secretions (p<0.001), velopharyngeal sufficiency (p = 0.006), pharyngeal squeeze (p = 0.009), vocal cords’ movements (p = 0.001), pharyngeal pooling (p<0.001), EAT-10 (p = 0.001) and bulbar subscale of ALS Functioning Rating Scale-Revised (b-ALSFRS-R) scores (p = 0.014) compared to non-aspirator status. Correlation analysis indicated that the feeding status had strong statistically significant correlations with the EAT-10 score (rho = −0.816), anterior tongue strength (rho = 0.735), secretions (rho = −0.811), pharyngeal pooling (rho = −0.712) and PAS (rho = −0.676) at FEES, and b-ALSFRS-R score (rho = 0.791), all p<0.001. The EAT-10 had strong statistically significant correlations with the MITPa (r = −0.794, p<0.001), secretions (rho = 0.668, p<0.001), and b-ALSFRS-R score (rho = -0.766, p = 0.001). The FEES findings had strong statistically significant correlations with the anterior tongue strength (pooling: rho = −0.784), and secretions (PAS: rho = 0.723; pooling: rho = 0.671), all p<0.001. For the questionnaire, tongue strength and pharyngeal secretions, ROC analysis assessed cut-off points and discriminating ability to predict aspiration status (Area Under the Curve: 0.838; 0.845 and 0.93, respectively). EAT-10 with a cut-off at 8 was able to predict aspirator status with a sensitivity of 100% and a specificity of 42.9% (negative predictive value-NPV = 100%). A cut-off value of 22KPa for the MITPa discriminated aspirator status (sensitivity = 80%, specificity = 89.5%, NPV = 89.5%). The quantity of secretions observed upon endoscopy with a cut-off value at 1 was able to predict aspirator status (sensitivity = 90%, specificity = 80%, NPV = 94.1%). ConclusionReduced tongue strength, questionnaire-reported symptoms, pharyngeal secretions, and FESS findings can guide identification of patients with ALS at risk of inefficient and unsafe swallowing.

Mo1635 CLASSIFICATION OF NUCLEAR MORPHOLOGY OF EC FINDINGS IN COLORECTAL ENDOCYTOSCOPY

Endocytoscopy (EC) is a next-generation endoscopy that allows diagnostic imaging at 520× magnification. In the EC classifications, lesions diagnosed as EC3a vary extensively from adenoma to carcinomas with massive submucosal invasion (SM-m), including some lesions that are unsuitable for endoscopic treatment. Therefore, to improve the accuracy of assessing the depth of invasion based on the EC classification, we investigated the presence or absence of 2 factors; high degree of nuclear enlargement (HNE) and multilayered nuclei (MNs), that are indicators of SM-m. Between May 2005 and August 2018, we retrospectively examined 866 lesions diagnosed as EC2 or EC3, according to the EC classification. We subclassified EC 3a into 2 grades (low or high grade) and defined low grade as not recognizing both HNE and MNs, and high grade as for any of the two factors. We examined the diagnostic accuracy of SM-m based on this EC3a subclassification. In addition, we compared the diagnostic ability of EC for SM-m with that of other modalities; narrow-band imaging (NBI) and pit pattern. The sensitivity, specificity, positive predictive value (PPV), negative predictive value NPV), accuracy, and positive likelihood ratio for the diagnostic accuracy of the EC3a subclassification were 89.3%, 91.2%, 80.6%, 92.3%, 90.6%, and 10.1, respectively (P < 0.001). Diagnostic performance for predicting SM-m or worse among EC, NBI and pit pattern is as follows: The sensitivity, specificity, PPV, NPV, and accuracy about EC were 95.1%, 96.5%, 94.9%, 96.7%, 96.0% respectively. On the other hand, those of NBI were 65.0%, 98.7%, 97.0%, 80.7%, 85.1%, and pit pattern were 88.8%, 96.0%, 93.7%, 92.7%, 93.1%, respectively. The sensitivity, specificity, NPV, and accuracy of EC were significantly higher than those of NBI .(P < 0.05) . Futhermore, the sensitivity, NPV, and accuracy of EC were significantly higher than those of pit pattern. (P < 0.05) From the EC findings, the presence of HNE, and MNs are important risk factors for SM-m or worse outcomes. Furthermore, the EC3a subclassification taking account of these findings could be effective for the diagnosis of SM-m or worse.

RULE OF RUSH PROTOCOL IN MANAGEMENT OF SHOCKED PATIENTS

SESSION TITLE: Wednesday Abstract Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/23/2019 09:45 AM - 10:45 AM PURPOSE: Background: Clinical assessment and classification of shock is extremely difficult to conduct on critically ill patients. Rapid Ultrasound in Shock (RUSH) is an easily learned and quickly performed shock ultrasound protocol, it allows for rapid evaluation of reversible causes of shock and improves accurate diagnosis in undifferentiated hypotension. Objectives: To evaluated the accuracy of early RUSH protocol performed by chest physicians to predict type of shock and its guide of resuscitation in critically ill patients. METHODS: Study was conducted on 68 patients with shock state in RICU and evaluated for the cause of shock by performing early RUSH protocol for patients. Patients received all needed standard therapeutic and diagnostic interventions without delay and were followed to document their final clinical diagnosis. The agreement between the initial impression provided by RUSH and the final diagnosis was investigated by calculating the Kappa index. Sensitivity, Specificity, positive predictive value PPV and negative predictive value NPV of RUSH for diagnosis of each case. RESULTS: We performed RUSH examination on 68 shocked patients. 39 were males (58%) and 29 were females (41%), with mean age 58 years. Kappa index was 0.85 (P= 0.0001), reflecting acceptable general agreement between initial impression and final diagnosis. For hypovolemic, cardiogenic and obstructive shock, the protocol had an NPV above 97%, but it had low sensitivity. For shock with distributive or mixed etiology, RUSH showed a PPV of {97% & 100%} respectively, with high sensitivity. The agreement of protocol for final diagnosis was highest in distributive and obstructive shock followed by cardiogenic and hypovolemic shock [(94% & 93%), P < 0.001 & (84% & 73%), P < 0.001,] respectively. CONCLUSIONS: We highlight the role of integrating focused ultrasound techniques, such as the RUSH examination, in the physician resuscitation pathways to diagnose shock etiology, augment their clinical evaluation and guide resuscitation CLINICAL IMPLICATIONS: Early identification of causes of shock in critically ill patients allow good clinical evaluation and guide resuscitation and help physician to used correct treatment. DISCLOSURES: no disclosure on file for Esrra Abdei-All; no disclosure on file for Gamal Agamy; no disclosure on file for AzzA Ahmad; No relevant relationships by Hamdy Mohammadien, source=Web Response

The Clinical Value of DWI and T2WI MRI in the Detection of Transitional Zone Prostatic Cancer

Background: The prostate cancer is one of the commonest non-cutaneous cancers detected among elderly men. The difficulty in interpretation of the transitional zone prostate MRI arises mainly from the presence of benign prostatic hyperplasia (BPH) nodules in the transitional zone. Objective: The objective of this study is to evaluate the clinical efficacy of DWI in combination with T2WI for the detection of transitional zone prostate cancer, compared with T2WI alone. Patients and methods: A total of 58 patients with clinical suspicion of prostatic cancer were evaluated by 1.5 T MRI. Two diagnostic protocols were designed, protocol A consists of only data obtained from T2WI, protocol B consists of T2WI and DWI. The likelihood of the presence of prostate cancer in transitional and central zone was assigned using a 5 point scale after evaluating the entire prostate in each reading session, scales of 5, 4, and 3 were considered positive results and scales 1 and 2 were considered negative results. Results: Transitional zone prostate cancer was identified histopathologically in 23/58 patients. MRI diagnostic performance: In protocol A, the sensitivity is 56.5%, specificity is 62.9% and accuracy is 60.3%. Positive predictive value PPV is 50% while negative predictive value NPV is 68.8%. In protocol B, the sensitivity is 91.3%, specificity is 80% and accuracy is 84.5%. Positive predictive value is 75% while negative predictive value is 93.3%. Diagnostic protocol B has a significantly better sensitivity and specificity than protocol A (p˂0.05). According to ROC curve analysis, the cut point of protocol A scale is 2, so protocol A scale (≥ 2) is predictive for the diagnosis of malignant lesions (AUC=67.5%). The cut point of protocol B scale is 4, so protocol B scale (≥ 4) is predictive for the diagnosis of malignant lesions (AUC=87.3%). The cut off ADC value is 0.99 × 10-3 mm2/sec, so ADC value (<0.99 × 10-3mm2/ sec) is predictive for the diagnosis of malignant lesions with 91.3% sensitivity, 76% specificity, and 83.3% accuracy. Conclusion: Combination of DWI (ultra-high b value) with T2WI significantly increases the diagnostic accuracy of transitional zone prostatic cancer and scale ≥ 4 is associated with high proportion of malignancy.

Detection of high density lipoprotein cholesterol using feed forward artificialneural network.

The high-density lipoprotein-cholesterol (HDL) is well known as the “good cholesterol”, since it removes harmful “bad cholesterol” out of blood. Low HDL levels increase the risk for cardiovascular diseases. This paper presents a solution for detection of low HDL level by using artificial neural network (ANN). The big dataset with 1517 persons is used for ANN training, validation and testing. Our solution achieves positive predictive value PPV=0.6782 and negative predictive value NPV=0.7066, which means that it is suitable both for positive and negative low HDL level detection.

Correlation between Platelet Count vs Spleen Bipolar Diameter Ratio and Esophageal Varices in Liver Cirrhosis

Background: Esophageal variceal bleeding is a potentially fatal complication in patients with liver cirrhosis and portal hypertension. In cirrhotic patients, endoscopic screening for esophageal varices (EV)is currently recommended at the time of diagnosis. The present study intends to find out correlation between platelet countspleen bipolar diameter ratio and esophageal varices in liver cirrhosis and prospectively validate its use for the noninvasive diagnosis of EV.Methods: This observational study was done at theDepartment of Gastrointestinal Hepatobiliary and Pancreatic Disorder, BIRDEM General Hospital, Dhaka, during the period of November, 2013 to October, 2014. A total 64 patients with cirrhosis of liver were included. Complete blood count, liver function tests, ultrasonographyof whole abdomenand endoscopy of upper gastro-intestinal tract (GIT)were done in all patients. Statistical analysis was done with SPSS version 16.Results: Among 64 study population EV were detected in 54 patients (84.4%). The platelet count/ spleen bipolar diameter ratio was significantly higher without EV compared with those with EV(1570 ± 493) and (688 ± 227), respectively; (p&lt;0.001).Patients with EV had lower platelet counts (86799.84 ±27389.99/mm3, p&lt;0.001), higher bipolar spleen diameters (127.94±15.14 mm, p&lt;0.001) and lower platelet count/ spleen bipolar diameter ratios (688.79 ±227.13, p&lt;0.001). In this analysis, by applying (ROC)curve the platelet count-spleen bipolar diameter ratio at a cut-of 908.5 maintained high sensitivity (100 %), Robust negative predictive value NPV (100%),specificity (55.6%) and PPV (85.4%), with an overall diagnostic accuracy of 87.50% for the prediction of EV.With advancing Child-Pugh (C-P) class the percentage of patients with varices increased, 33.3% in C-P class A, 85.7% in C-P class B and 91.6% in C-P class C. The presence of EVcorrelated significantly with the severity of liver cirrhosis (p = 0.03) as measured by Child-Pugh score.Conclusion: The identification of non-endoscopic, noninvasive methods that can accurately predict esophageal varicesin cirrhosis of liver has been addressed in several recent studies. This study was yet another attempt to achieve this goal. Predicting the presence of EV by noninvasive means would restrict the performance of endoscopy and reducing the number of unpleasant screening endoscopiesBirdem Med J 2018; 8(2): 159-166

Prediction of seizure outcome improved by fast ripples detected in low-noise intraoperative corticogram.

Fast ripples (FR, 250-500Hz) in the intraoperative corticogram have recently been proposed as specific predictors of surgical outcome in epilepsy patients. However, online FR detection is restricted by their low signal-to-noise ratio. Here we propose the integration of low-noise EEG with unsupervised FR detection. Pre- and post-resection ECoG (N=9 patients) was simultaneously recorded by a commercial device (CD) and by a custom-made low-noise amplifier (LNA). FR were analyzed by an automated detector previously validated on visual markings in a different dataset. Across all recordings, in the FR band the background noise was lower in LNA than in CD (p<0.001). FR rates were higher in LNA than CD recordings (0.9±1.4 vs 0.4±0.9, p<0.001). Comparison between FR rates in post-resection ECoG and surgery outcome resulted in positive predictive value PPV=100% in CD and LNA, and negative predictive value NPV=38% in CD and NPV=50% for LNA. Prediction accuracy was 44% for CD and 67% for LNA. Prediction of seizure outcome was improved by the optimal integration of low-noise EEG and unsupervised FR detection. Accurate, automated and fast FR rating is essential for consideration of FR in the intraoperative setting.

Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome.

High frequency oscillations (HFOs) and in particular fast ripples (FRs) in the post-resection electrocorticogram (ECoG) have recently been shown to be highly specific predictors of outcome of epilepsy surgery. FR visual marking is time consuming and prone to observer bias. We validate here a fully automatic HFO detector against seizure outcome. Pre-resection ECoG dataset (N=14 patients) with visually marked HFOs were used to optimize the detector's parameters in the time-frequency domain. The optimized detector was then applied on a larger post-resection ECoG dataset (N=54) and the output was compared with visual markings and seizure outcome. The analysis was conducted separately for ripples (80-250Hz) and FRs (250-500Hz). Channel-wise comparison showed a high association between automatic detection and visual marking (p<0.001 for both FRs and ripples). Automatically detected FRs were predictive of clinical outcome with positive predictive value PPV=100% and negative predictive value NPV=62%, while for ripples PPV=43% and NPV=100%. Our automatic and fully unsupervised detection of HFO events matched the expert observer's performance in both event selection and outcome prediction. The detector provides a standardized definition of clinically relevant HFOs, which may spread its use in clinical application.

Abstract O.32: An Improved Point-of-care Differentiation Of Kawasaki Disease From Other Febrile Illnesses

Background: Kawasaki disease (KD) shares many clinical features with other pediatric febrile illnesses (FC). Clinical confusion can lead to a missed or delayed diagnosis that increases the risk of coronary artery damage. In the present study, we improved our previous KD diagnostic algorithm for point-of-care diagnosis. Methods and Results: We reviewed clinical records of 534 acute KD and 318 FC patients (development dataset) and subsequent 268 acute KD and 161 FC patients (validation dataset). KD subjects met the American Heart Association definition. Using clinical data and lab test results, we integrated our previously developed linear discriminant analysis (LDA)-based clinical model with a newly developed decision tree-based algorithm to improve KD diagnosis. To train the decision trees, sub cohorts were constructed based upon the 5 KD classic criteria. Our 1 st clinical model (LDA) stratified the subjects into FC (FC diagnosis, negative predictive value NPV &gt;=95%), undecided (88/802 KD, 167/479 FC), and KD (KD diagnosis, positive predictive value PPV &gt;=95%) subgroups. The subsequent 2 nd clinical model (decision trees) further classified the undecided group into FC, undecided, and KD subgroups, resulting in a much-improved algorithm with only 59/479 FC (Specificity&gt;76%) and 26/802 KD (Sensitivity&gt;95%) undetermined. Conclusions: Our computer-based algorithm that incorporates only clinical findings and readily available clinical laboratory data now has sufficient sensitivity and specificity in distinguishing acute KD from FC patients that a multicenter, prospective clinical trial is warranted to test the performance of the diagnostic algorithm against the gold standard of expert clinical opinion.

Utility of Kynurenic Acid for Non-Invasive Detection of Metastatic Spread to Lymph Nodes in Non-Small Cell Lung Cancer

Background: Kynurenic acid (KYNA) is a side-stream product of the kynurenine metabolic pathway that plays a controversial role in malignancies either enabling escape of malignant cells from immune surveillance or exerting antiproliferative effect on cancer cells, and is associated with differences in invasiveness related to metastatic spread to lymph nodes in lung cancer. Nodal involvement is a significant negative prognostic factor usually considered a contraindication for primary surgical resection.Objective: To assess potential value of circulating KYNA for non-invasive identification of patients with metastatic lymph nodes (N+) in non-small cell lung cancer (NSCLC).Methods: KYNA level in venous blood serum was determined with use of high performance liquid chromatography (HPLC) in 312 subjects including 230 patients with NSCLC and 32 healthy controls.Results: Circulating KYNA level in NSCLC patients was higher than in controls (93.6±61.9pmol/ml vs. 31.4±16.6pmol/ml; p=2.2•10-15) and positively correlated with N (R=0.326; p=2•10-6) but not with T or M stage (p>0.05). In N+ patients it was higher than in N0 patients (137.7±51.8pmol/ml vs. 71.9±41.7pmol/ml; p=4.8•10-16). KYNA effectively discriminated N+ from N0 patients at a cut-off value 82.3 pmol/ml with sensitivity 94.7% (95%CI 87.1-98.5%), specificity 80.5% (95%CI 73.4-86.5%), negative predictive value NPV=96.8%, PPV=70.5% and area under the ROC curve AUC=0.900 (95%CI 0.854-0.935; p=0.0001).Discussion and Conclusion: Circulating KYNA level measurement offers reliable non-invasive discrimination between N0 and N+ patients in NSCLC. Robust discriminatory characteristics of KYNA assay predestines it for clinical use as an adjunct facilitating selection of candidates for primary surgical resection.

AB0547 Bone mineral density (bmd) assessment in patients with symptoms suggestive of spondyloarthritis: an accurate tool for diagnosis

BackgroundSeveral diseases can mimick spondyloarthritis (SpA) symptoms. Patients may be overdiagnosed in the presence of HLA B27. Patients with spondyloarthritis (SpA) have an increased risk of osteoporosis which can be...

FRI0471 A comparative analysis of erosion repair in rheumatoid arthritis (RA) patients by magnetic resonance imaging (MRI) and hr-pqct

BackgroundThe detection of bone erosions is fundamental both for monitoring of disease activity and therapy decisions in rheumatoid arthritis (RA). Recently, it could be shown by high-resolution peripheral quantitative computed...