METHODS: ALS patients were prospectively recruited. Muscle fasciculation (≥2 over 30-seconds, examined in biceps brachii-brachialis (BB), brachioradialis, tibialis anterior and vastus medialis) and nerve cross-sectional area (CSA) (median, ulnar, tibial, fibular nerve) were evaluated through NMUS. Ultrasound parameters were correlated with clinical data, including revised ALS Functional Rating Scale (ALSFRS-R) progression at one year. A predictive model was constructed to differentiate fast progressors (ALSFRS-R decline ≥ 1/month) from non-fast progressors.
RESULTS: 40 ALS patients were recruited. Three parameters emerged as strong predictors of fast progressors: (i) ALSFRS-R slope at time of NMUS (p = 0.041), (ii) BB fasciculation count (p = 0.027) and (iii) proximal to distal median nerve CSA ratio
METHODS: The NFS was calculated and LSM obtained for consecutive adult NAFLD patients scheduled for liver biopsy. The accuracy of predicting advanced fibrosis using either modality and in combination were assessed. An algorithm combining the NFS and LSM was developed from a training cohort and subsequently tested in a validation cohort.
RESULTS: There were 101 and 46 patients in the training and validation cohort, respectively. In the training cohort, the percentages of misclassifications using the NFS alone, LSM alone, LSM alone (with grey zone), both tests for all patients and a 2-step approach using LSM only for patients with indeterminate and high NFS were 5.0, 28.7, 2.0, 2.0 and 4.0 %, respectively. The percentages of patients requiring liver biopsy were 30.7, 0, 36.6, 36.6 and 18.8 %, respectively. In the validation cohort, the percentages of misclassifications were 8.7, 28.3, 2.2, 2.2 and 8.7 %, respectively. The percentages of patients requiring liver biopsy were 28.3, 0, 41.3, 43.5 and 19.6 %, respectively.
CONCLUSIONS: The novel 2-step approach further reduced the number of patients requiring a liver biopsy whilst maintaining the accuracy to predict advanced fibrosis. The combination of NFS and LSM for all patients provided no apparent advantage over using either of the tests alone.
METHODS: The POCT was used to test 170 serum specimens collected through measles surveillance or vaccination programmes in Ethiopia, Malaysia and the Russian Federation: 69 were positive for measles immunoglobulin M (IgM) antibodies, 74 were positive for rubella IgM antibodies and 7 were positive for both. Also tested were 282 oral fluid specimens from the measles, mumps and rubella (MMR) surveillance programme of the United Kingdom of Great Britain and Northern Ireland. The Microimmune measles IgM capture enzyme immunoassay was the gold standard for comparison. A panel of 24 oral fluids was used to investigate if measles virus haemagglutinin (H) and nucleocapsid (N) genes could be amplified by polymerase chain reaction directly from used POCT strips.
FINDINGS: With serum POCT showed a sensitivity and specificity of 90.8% (69/76) and 93.6% (88/94), respectively; with oral fluids, sensitivity and specificity were 90.0% (63/70) and 96.2% (200/208), respectively. Both H and N genes were reliably detected in POCT strips and the N genes could be sequenced for genotyping. Measles virus genes could be recovered from POCT strips after storage for 5 weeks at 20-25 °C.
CONCLUSION: The POCT has the sensitivity and specificity required of a field-based test for measles diagnosis. However, its role in global measles control programmes requires further evaluation.
METHODS: In this retrospective cohort study, all consecutive patients were aged 18 years and over and undergoing non-cardiac thoracic surgery at a tertiary-care university hospital. Respiratory complications included bronchospasm, atelectasis, pneumonia, respiratory failure, and adult respiratory distress syndrome within 30 days of surgery or before discharge.
RESULTS: A total of 1488 patients were included over a 7-year period, and 15.8% (235 of 1488 patients) developed respiratory complications. The significant predictors of respiratory complications were chronic obstructive pulmonary disease, American Society of Anesthesiologist physical status ≥ 3, right-sided surgery, duration of surgery longer than 180 min, preoperative arterial oxygen saturation on room air
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
STUDY DESIGN: Diagnostic cross-sectional study.
METHODS: This study included consecutive CRS patients without prior sinus surgery. Computed tomography (CT) scans of the paranasal sinuses were blindly assessed and allergy status was confirmed by serum or skin testing. Individual sinus cavities were defined as either centrally limited or diffuse disease. The radiological pattern that may predict allergy was determined, and its diagnostic accuracy was calculated.
RESULTS: One hundred twelve patients diagnosed to have CRS, representing 224 sides, were assessed (age 46.31 ± 13.57 years, 38.39% female, 41.07% asthma, Lund-Mackay CT score 15.88 ± 4.35, 56.25% atopic). The radiological pattern defined by centrally limited changes in all of the paranasal sinuses was associated with allergy status (73.53% vs. 53.16%, P = .03). This predicted atopy with 90.82% specificity, 73.53% positive predictive value, likelihood positive ratios of 2.16, and diagnostic odds ratio of 4.59.
CONCLUSIONS: A central radiological pattern of mucosal disease is associated with inhalant allergen sensitization. This group may represent a CCAD subgroup of patients with mainly allergic etiology.
LEVEL OF EVIDENCE: 3b Laryngoscope, 128:2015-2021, 2018.
METHOD: In this work, resting-state EEG-derived features were utilized as input data to the proposed feature selection and classification method. The aim was to perform automatic classification of AUD patients and healthy controls. The validation of the proposed method involved real-EEG data acquired from 30 AUD patients and 30 age-matched healthy controls. The resting-state EEG-derived features such as synchronization likelihood (SL) were computed involving 19 scalp locations resulted into 513 features. Furthermore, the features were rank-ordered to select the most discriminant features involving a rank-based feature selection method according to a criterion, i.e., receiver operating characteristics (ROC). Consequently, a reduced set of most discriminant features was identified and utilized further during classification of AUD patients and healthy controls. In this study, three different classification models such as Support Vector Machine (SVM), Naïve Bayesian (NB), and Logistic Regression (LR) were used.
RESULTS: The study resulted into SVM classification accuracy=98%, sensitivity=99.9%, specificity=95%, and f-measure=0.97; LR classification accuracy=91.7%, sensitivity=86.66%, specificity=96.6%, and f-measure=0.90; NB classification accuracy=93.6%, sensitivity=100%, specificity=87.9%, and f-measure=0.95.
CONCLUSION: The SL features could be utilized as objective markers to screen the AUD patients and healthy controls.