Preoperative Risk Stratification of Follicular-patterned Thyroid Lesions on Core Needle Biopsy by Histologic Subtyping and RAS Variant-specific Immunohistochemistry.

Follicular-patterned lesions often have indeterminate results (diagnostic category III or IV) by core needle biopsy (CNB) and fine needle aspiration (FNA). However, CNB diagnoses follicular neoplasm (category IV) more frequently than FNA. Therefore, we aimed to develop a risk stratification system for CNB samples with category III/IV using immunohistochemistry (IHC). The specificity of the RAS Q61R antibody was validated on 58 thyroid nodules with six different types of RAS genetic variants and 40 cases of RAS wild-type. We then applied IHC analysis of RAS Q61R to 207 CNB samples with category III/IV in which all patients underwent surgical resection. RAS Q61R IHC had 98% sensitivity and 98% specificity for detecting the RAS p.Q16R variant. In an independent dataset, the positive rate of RAS Q61R was significantly higher in NIFTP (48%) and malignancies (45%) than in benign tumors (19%). The risk of NIFTP/malignancy was highest in the group with nuclear atypia and RAS Q61R expression (86%) and lowest in the group without both parameters (32%). The high-risk group with either nuclear atypia or RAS Q61R had 67.3% sensitivity, 73.4% specificity, 75.2% positive predictive value, and 65.1% negative predictive value for identifying NIFTP/malignancy. We conclude that RAS Q61R IHC can be a rule-in diagnostic test for NIFTP/malignancy in CNB category III/IV results. Combining of the histologic parameter (nuclear atypia) with RAS Q61R IHC results can further stratify CNB category III/IV into a high-risk group, which is sufficient for a surgical referral, and a low-risk group sufficient for observation.

Upper airway angle and glottic height: a prospective cohort to evaluate two new features for airway prediction.

BACKGROUND: Predicting difficult direct laryngoscopies remains challenging and improvements are needed in preoperative airway assessment. We conceived two new tests (the upper airway angle and the glottic height) and assessed their association with difficult direct laryngoscopies as well as their predictive performance. METHODS: A prospective cohort was conducted with 211 patients undergoing general anesthesia for surgical procedures. We assessed the association between difficult laryngoscopies and modified Mallampati Test (MMT), Upper Lip Bite Test (ULBT), Mandibular Length (ML), Neck Circumference (NC), Mouth Opening (MO), Sternomental Distance (SMD), Thyromental Distance (TMD), Upper Airway Angle (UAA), and Glottic Height (GH). We also estimated their predictive values. RESULTS: Difficult laryngoscopy was presented by 12 patients (5.7%). Six tests were significantly associated with difficult laryngoscopies and their area under the ROC curve, and 95% CIs were as follows: UAA = 88.82 (81.86-95.78); GH = 86.43 (72.67-100); ML = 83.75 (72.77-94.74); NC = 79.17 (64.98-93.36); MO = 65.58 (45.13-86.02); and MMT = 77.89 (68.37-87.41). CONCLUSION: We have found two new features (the UAA and the GH) to be significantly associated with the occurrence of difficult direct laryngoscopies. They also presented the best predictive performance amongst the nine evaluated tests in our cohort of patients. We cannot ensure, however, these tests to be superior to other regularly used bedside tests based on our estimated 95% CIs.

Upper airway angle and glottic height: a prospective cohort to evaluate two new features for airway prediction

Abstract Background: Predicting difficult direct laryngoscopies remains challenging and improvements are needed in preoperative airway assessment. We conceived two new tests (the upper airway angle and the glottic height) and assessed their association with difficult direct laryngoscopies as well as their predictive performance. Methods: A prospective cohort was conducted with 211 patients undergoing general anesthesia for surgical procedures. We assessed the association between difficult laryngoscopies and modified Mallampati Test (MMT), Upper Lip Bite Test (ULBT), Mandibular Length (ML), Neck Circumference (NC), Mouth Opening (MO), Sternomental Distance (SMD), Thyromental Distance (TMD), Upper Airway Angle (UAA), and Glottic Height (GH). We also estimated their predictive values. Results: Difficult laryngoscopy was presented by 12 patients (5.7%). Six tests were significantly associated with difficult laryngoscopies and their area under the ROC curve, and 95% CIs were as follows: UAA = 88.82 (81.86-95.78); GH = 86.43 (72.67-100); ML = 83.75 (72.77-94.74); NC = 79.17 (64.98-93.36); MO = 65.58 (45.13-86.02); and MMT = 77.89 (68.37-87.41). Conclusion: We have found two new features (the UAA and the GH) to be significantly associated with the occurrence of difficult direct laryngoscopies. They also presented the best predictive performance amongst the nine evaluated tests in our cohort of patients. We cannot ensure, however, these tests to be superior to other regularly used bedside tests based on our estimated 95% CIs.

Which hematological markers have predictive value as early indicators of severe COVID-19 cases in the emergency department?

Background/aim: Coronavirus 2019 disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic infectious disease that causes morbidity and mortality. As a result of high mortality rate among the severe COVID-19 patients, the early detection of the disease stage and early effective interventions are very important in reducing mortality. Hence, it is important to differentiate severe and nonsevere cases from each other. To date, there are no proven diagnostic or prognostic parameters that can be used in this manner. Due to the expensive and not easily accessible tests that are performed for COVID-19, researchers are investigating some parameters that can be easily used. In some recent studies, hematological parameters have been evaluated to see if they can be used as predictive parameters. Materials and methods: In the current study, almost all hematological parameters were used, including the neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio, mean platelet volume to lymphocyte ratio, mean platelet volume to platelet ratio, plateletcrit, and D-dimer/fibrinogen ratio, neutrophil/lymphocyte/platelet scoring system, and systemic immune-inflammation index. A total of 750 patients, who were admitted to Ankara City Hospital due to COVID-19, were evaluated in this study. The patients were classified into 2 groups according to their diagnosis (confirmed or probable) and into 2 groups according to the stage of the disease (nonsevere or severe). Results: The values of the combinations of inflammatory markers and other hematological parameters in all of the patients with severe COVID-19 were calculated, and the predicted values of these parameters were compared. According to results of the study, nearly all of the hematological parameters could be used as potential diagnostic biomarkers for subsequent analysis, because the area under the curve (AUC) was higher than 0.50, especially for the DFR and NLR, which had the highest AUC among the parameters. Conclusion: Our findings indicate that, the parameters those enhanced from complete blood count, which is a simple laboratory test, can help to identify and classify COVID-19 patients into non-severe to severe groups.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone App.

PURPOSE: We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. METHODS: Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. RESULTS: A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. CONCLUSIONS: External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone A / 대한배뇨장애요실금학회지

PURPOSE: We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. METHODS: Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. RESULTS: A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. CONCLUSIONS: External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

A proposal for a new scoring system to predict difficult ventilation through a supraglottic airway.

BACKGROUND: The aim of this study was to propose and validate a new clinical score to predict difficult ventilation through a supraglottic airway device. METHODS: The score was proposed from our previously reported derivation data, and we prospectively validated the score in 5532 patients from November 2013 to April 2014. Predictive accuracy of the score was compared by the area under the receiver operating characteristic (ROC) curve (AUC). We assigned point values to each of the identified four risk factors: male, age >45 yr, short thyromental distance, and limited neck movement, their sum composing the score. The score ranged between 0 and 7 points. The optimal predictive level of the score was determined using ROC curve analysis. RESULTS: The AUC of the score was 0.75 (95% CI 0.66 to 0.84) in the validation data set, and was similar to that in the derivation data set (0.80; 95% CI 0.75 to 0.86). In derivation and validation data sets, the incidence of low risk categories (scores 0-3) was 0.42% vs 0.32% and of high risk categories (scores 4-7) was 3% vs 1.7% respectively. A score 4 or greater is associated with a six to seven fold increased risk of difficult ventilation through a supraglottic airway device. CONCLUSIONS: The new score for prediction of difficult ventilation through a supraglottic airway device is easy to perform and reliable, and could help anaesthetists plan for difficult airway management.