An artificial intelligence algorithm for the classification of sphenoid sinus pneumatisation on sinus computed tomography scans.

BACKGROUND: Classifying sphenoid pneumatisation is an important but often overlooked task in reporting sinus CT scans. Artificial intelligence (AI) and one of its key methods, convolutional neural networks (CNNs), can create algorithms that can learn from data without being programmed with explicit rules and have shown utility in radiological image classification. OBJECTIVE: To determine if a trained CNN can accurately classify sphenoid sinus pneumatisation on CT sinus imaging. METHODS: Sagittal slices through the natural ostium of the sphenoid sinus were extracted from retrospectively collected bone-window CT scans of the paranasal sinuses for consecutive patients over 6 years. Two blinded Otolaryngology residents reviewed each image and classified the sphenoid sinus pneumatisation as either conchal, presellar or sellar. An AI algorithm was developed using the Microsoft Azure Custom Vision deep learning platform to classify the pattern of pneumatisation. RESULTS: Seven hundred eighty images from 400 patients were used to train the algorithm, which was then tested on a further 118 images from 62 patients. The algorithm achieved an accuracy of 93.2% (95% confidence interval [CI] 87.1-97.0), 87.3% (95% CI 79.9-92.7) and 85.6% (95% CI 78.0-91.4) in correctly identifying conchal, presellar and sellar sphenoid pneumatisation, respectively. The overall weighted accuracy of the CNN was 85.9%. CONCLUSION: The CNN described demonstrated a moderately accurate classification of sphenoid pneumatisation subtypes on CT scans. The use of CNN-based assistive tools may enable surgeons to achieve safer operative planning through routine automated reporting allowing greater resources to be directed towards the identification of pathology.

A Computer Vision Algorithm to Classify Pneumatization of the Mastoid Process on Temporal Bone Computed Tomography Scans.

BACKGROUND: Pneumatization of the mastoid process is variable and of significance to the operative surgeon. Surgical approaches to the temporal bone require an understanding of pneumatization and its implications for surgical access. This study aims to determine the feasibility of using deep learning convolutional neural network algorithms to classify pneumatization of the mastoid process. METHODS: De-identified petrous temporal bone images were acquired from a tertiary hospital radiology picture archiving and communication system. A binary classification mode in the pretrained convolutional neural network was used to investigate the utility of convolutional neural networks in temporal bone imaging. False positive and negative images were reanalyzed by the investigators and qualitatively assessed to consider reasons for inaccuracy. RESULTS: The overall accuracy of the model was 0.954. At a probability threshold of 65%, the sensitivity of the model was 0.860 (95% CI 0.783-0.934) and the specificity was 0.989 (95% CI 0.960-0.999). The positive predictive value was 0.973 (95% CI 0.904-0.993) and the negative predictive value was 0.935 (95% CI 0.901-0.965). The false positive rate was 0.006. The F1 number was 0.926 demonstrating a high accuracy for the model. CONCLUSION: The temporal bone is a complex anatomical region of interest to otolaryngologists. Surgical planning requires high-resolution computed tomography scans, the interpretation of which can be augmented with machine learning. This initial study demonstrates the feasibility of utilizing machine learning algorithms to discriminate anatomical variation with a high degree of accuracy. It is hoped this will lead to further investigation regarding more complex anatomical structures in the temporal bone.

Evaluating the generalizability of deep learning image classification algorithms to detect middle ear disease using otoscopy.

To evaluate the generalizability of artificial intelligence (AI) algorithms that use deep learning methods to identify middle ear disease from otoscopic images, between internal to external performance. 1842 otoscopic images were collected from three independent sources: (a) Van, Turkey, (b) Santiago, Chile, and (c) Ohio, USA. Diagnostic categories consisted of (i) normal or (ii) abnormal. Deep learning methods were used to develop models to evaluate internal and external performance, using area under the curve (AUC) estimates. A pooled assessment was performed by combining all cohorts together with fivefold cross validation. AI-otoscopy algorithms achieved high internal performance (mean AUC: 0.95, 95%CI: 0.80-1.00). However, performance was reduced when tested on external otoscopic images not used for training (mean AUC: 0.76, 95%CI: 0.61-0.91). Overall, external performance was significantly lower than internal performance (mean difference in AUC: -0.19, p ≤ 0.04). Combining cohorts achieved a substantial pooled performance (AUC: 0.96, standard error: 0.01). Internally applied algorithms for otoscopy performed well to identify middle ear disease from otoscopy images. However, external performance was reduced when applied to new test cohorts. Further efforts are required to explore data augmentation and pre-processing techniques that might improve external performance and develop a robust, generalizable algorithm for real-world clinical applications.

Inter-rater agreement between 13 otolaryngologists to diagnose otitis media in Aboriginal and Torres Strait Islander children using a telehealth approach.

INTRODUCTION: Telehealth programs are important to deliver otolaryngology services for Aboriginal and Torres Strait Islander children living in rural and remote areas, where distance and access to specialists is a critical factor. OBJECTIVE: To evaluate the inter-rater agreement and value of increasing levels of clinical data (otoscopy with or without audiometry and in-field nurse impressions) to diagnose otitis media using a telehealth approach. DESIGN: Blinded, inter-rater reliability study. SETTING: Ear health and hearing assessments collected from a statewide telehealth program for Indigenous children living in rural and remote areas of Queensland, Australia. PARTICIPANTS: Thirteen board-certified otolaryngologists independently reviewed 80 telehealth assessments from 65 Indigenous children (mean age 5.7 ± 3.1 years, 33.8% female). INTERVENTIONS: Raters were provided increasing tiers of clinical data to assess concordance to the reference standard diagnosis: Tier A) otoscopic images alone, Tier B) otoscopic images plus tympanometry and category of hearing loss, and Tier C) as B plus static compliance, canal volume, pure-tone audiometry, and nurse impressions (otoscopic findings and presumed diagnosis). For each tier, raters were asked to determine which of the four diagnostic categories applied: normal aerated ear, acute otitis media (AOM), otitis media with effusion (OME), and chronic otitis media (COM). MAIN OUTCOME MEASURES: Proportion of agreement to the reference standard, prevalence-and-bias adjusted κ coefficients, mean difference in accuracy estimates between each tier of clinical data. RESULTS: Accuracy between raters and the reference standard increased with increased provision of clinical data (Tier A: 65% (95%CI: 63-68%), κ = 0.53 (95%CI: 0.48-0.57); Tier B: 77% (95%CI: 74-79%), 0.68 (95%CI: 0.65-0.72); C: 85% (95%CI: 82-87%), 0.79 (95%CI: 0.76-0.82)). Classification accuracy significantly improved between Tier A to B (mean difference:12%, p < 0.001) and between Tier B to C (mean difference: 8%, p < 0.001). The largest improvement in classification accuracy was observed between Tier A and C (mean difference: 20%, p < 0.001). Inter-rater agreement similarly improved with increasing provision of clinical data. CONCLUSIONS: There is substantial agreement between otolaryngologists to diagnose ear disease using electronically stored clinical data collected from telehealth assessments. The addition of audiometry, tympanometry and nurse impressions significantly improved expert accuracy and inter-rater agreement, compared to reviewing otoscopic images alone.

Convolutional Neural Networks in ENT Radiology: Systematic Review of the Literature.

INTRODUCTION: Convolutional neural networks (CNNs) represent a state-of-the-art methodological technique in AI and deep learning, and were specifically created for image classification and computer vision tasks. CNNs have been applied in radiology in a number of different disciplines, mostly outside otolaryngology, potentially due to a lack of familiarity with this technology within the otolaryngology community. CNNs have the potential to revolutionize clinical practice by reducing the time required to perform manual tasks. This literature search aims to present a comprehensive systematic review of the published literature with regard to CNNs and their utility to date in ENT radiology. METHODS: Data were extracted from a variety of databases including PubMED, Proquest, MEDLINE Open Knowledge Maps, and Gale OneFile Computer Science. Medical subject headings (MeSH) terms and keywords were used to extract related literature from each databases inception to October 2020. Inclusion criteria were studies where CNNs were used as the main intervention and CNNs focusing on radiology relevant to ENT. Titles and abstracts were reviewed followed by the contents. Once the final list of articles was obtained, their reference lists were also searched to identify further articles. RESULTS: Thirty articles were identified for inclusion in this study. Studies utilizing CNNs in most ENT subspecialties were identified. Studies utilized CNNs for a number of tasks including identification of structures, presence of pathology, and segmentation of tumors for radiotherapy planning. All studies reported a high degree of accuracy of CNNs in performing the chosen task. CONCLUSION: This study provides a better understanding of CNN methodology used in ENT radiology demonstrating a myriad of potential uses for this exciting technology including nodule and tumor identification, identification of anatomical variation, and segmentation of tumors. It is anticipated that this field will continue to evolve and these technologies and methodologies will become more entrenched in our everyday practice.

Artificial intelligence to classify ear disease from otoscopy: A systematic review and meta-analysis.

OBJECTIVES: To summarise the accuracy of artificial intelligence (AI) computer vision algorithms to classify ear disease from otoscopy. DESIGN: Systematic review and meta-analysis. METHODS: Using the PRISMA guidelines, nine online databases were searched for articles that used AI computer vision algorithms developed from various methods (convolutional neural networks, artificial neural networks, support vector machines, decision trees and k-nearest neighbours) to classify otoscopic images. Diagnostic classes of interest: normal tympanic membrane, acute otitis media (AOM), otitis media with effusion (OME), chronic otitis media (COM) with or without perforation, cholesteatoma and canal obstruction. MAIN OUTCOME MEASURES: Accuracy to correctly classify otoscopic images compared to otolaryngologists (ground truth). The Quality Assessment of Diagnostic Accuracy Studies Version 2 tool was used to assess the quality of methodology and risk of bias. RESULTS: Thirty-nine articles were included. Algorithms achieved 90.7% (95%CI: 90.1-91.3%) accuracy to difference between normal or abnormal otoscopy images in 14 studies. The most common multiclassification algorithm (3 or more diagnostic classes) achieved 97.6% (95%CI: 97.3-97.9%) accuracy to differentiate between normal, AOM and OME in three studies. AI algorithms outperformed human assessors to classify otoscopy images achieving 93.4% (95%CI: 90.5-96.4%) versus 73.2% (95%CI: 67.9-78.5%) accuracy in three studies. Convolutional neural networks achieved the highest accuracy compared to other classification methods. CONCLUSION: AI can classify ear disease from otoscopy. A concerted effort is required to establish a comprehensive and reliable otoscopy database for algorithm training. An AI-supported otoscopy system may assist health care workers, trainees and primary care practitioners with less otology experience identify ear disease.

An Artificial Intelligence Computer-vision Algorithm to Triage Otoscopic Images From Australian Aboriginal and Torres Strait Islander Children.

OBJECTIVE: To develop an artificial intelligence image classification algorithm to triage otoscopic images from rural and remote Australian Aboriginal and Torres Strait Islander children. STUDY DESIGN: Retrospective observational study. SETTING: Tertiary referral center. PATIENTS: Rural and remote Aboriginal and Torres Strait Islander children who underwent tele-otology ear health screening in the Northern Territory, Australia between 2010 and 2018. INTERVENTIONS: Otoscopic images were labeled by otolaryngologists to classify the ground truth. Deep and transfer learning methods were used to develop an image classification algorithm. MAIN OUTCOME MEASURES: Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, area under the curve (AUC) of the resultant algorithm compared with the ground truth. RESULTS: Six thousand five hundred twenty seven images were used (5927 images for training and 600 for testing). The algorithm achieved an accuracy of 99.3% for acute otitis media, 96.3% for chronic otitis media, 77.8% for otitis media with effusion (OME), and 98.2% to classify wax/obstructed canal. To differentiate between multiple diagnoses, the algorithm achieved 74.4 to 92.8% accuracy and an AUC of 0.963 to 0.997. The most common incorrect classification pattern was OME misclassified as normal tympanic membranes. CONCLUSIONS: The paucity of access to tertiary otolaryngology care for rural and remote Aboriginal and Torres Strait Islander communities may contribute to an under-identification of ear disease. Computer vision image classification algorithms can accurately classify ear disease from otoscopic images of Indigenous Australian children. In the future, a validated algorithm may integrate with existing telemedicine initiatives to support effective triage and facilitate early treatment and referral.

Frontal Ostium Grade (FOG): A New Computer Tomography Grading System for Endoscopic Frontal Sinus Surgery.

OBJECTIVE: The location and size of the frontal sinus ostium are critical in determining surgical difficulty. The more anterior the ostium, the more difficult is the surgical access. We propose a novel computed tomography (CT) grading specific to the anatomical position of the frontal ostium. STUDY DESIGN: Observational study followed by a prospective part. SETTINGS: Tertiary rhinology practice. SUBJECT AND METHODS: On a specified sagittal CT cut, a vertical line was drawn through the posterior edge of the frontal process of the maxilla (frontal buttress/beak) along its vertical axis (reference [R-] line). A second (S-) line was placed at the point of upturn of the skull base. Based on if the S-line was posterior or anterior to the R-line, the frontal ostium was graded positive and more easily accessible or negative and thereby more challenging, respectively. If both lines overlapped, then a neutral (0) grading existed. RESULTS: A total of 297 CTs (594 ostia) were analyzed. In total, 394 (65%) ostia were grade positive, 52 (8.75%) were grade negative, and 103 (17.3%) were grade neutral. Ninety frontal sinusotomies were then performed using this grading system: 48 were positive, 21 negative, and 21 neutral. The average time to complete a frontal sinusotomy was 9.96 minutes for grade positive compared to 11.4 minutes for neutral and 16.05 minutes for grade negative (P < .005). CONCLUSION: This novel anatomical CT grading system is designed to be useful in planning and predicting the level of difficulty in endoscopic frontal sinus surgery.

Pneumothorax rates in CT-Guided lung biopsies: a comprehensive systematic review and meta-analysis of risk factors.

OBJECTIVE: This systematic review and meta-analysis investigated risk factors for pneumothorax following CT-guided percutaneous transthoracic lung biopsy. METHODS: A systematic search of nine literature databases between inception to September 2019 for eligible studies was performed. RESULTS: 36 articles were included with 23,104 patients. The overall pooled incidence for pneumothorax was 25.9% and chest drain insertion was 6.9%. Pneumothorax risk was significantly reduced in the lateral decubitus position where the biopsied lung was dependent compared to a prone or supine position [odds ratio (OR):3.15]. In contrast, pneumothorax rates were significantly increased in the lateral decubitus position where the biopsied lung was non-dependent compared to supine (OR:2.28) or prone position (OR:3.20). Other risk factors for pneumothorax included puncture site up compared to down through a purpose-built biopsy window in the CT table (OR:4.79), larger calibre guide/needles (≤18G vs >18G: OR 1.55), fissure crossed (OR:3.75), bulla crossed (OR:6.13), multiple pleural punctures (>1 vs 1: OR:2.43), multiple non-coaxial tissue sample (>1 vs 1: OR 1.99), emphysematous lungs (OR:3.33), smaller lesions (<4 cm vs 4 cm: OR:2.09), lesions without pleural contact (OR:1.73) and deeper lesions (≥3 cm vs <3cm: OR:2.38). CONCLUSION: This meta-analysis quantifies factors that alter pneumothorax rates, particularly with patient positioning, when planning and performing a CT-guided lung biopsy to reduce pneumothorax rates. ADVANCES IN KNOWLEDGE: Positioning patients in lateral decubitus with the biopsied lung dependent, puncture site down with a biopsy window in the CT table, using smaller calibre needles and using coaxial technique if multiple samples are needed are associated with a reduced incidence of pneumothorax.

The efficacy of diluted topical povidone-iodine rinses in the management of recalcitrant chronic rhinosinusitis: a prospective cohort study.

PURPOSE: Recalcitrant chronic rhinosinusitis is a persistent inflammatory condition of the sinonasal mucosa despite adequate medical therapy and sinus surgery. This study aimed to demonstrate the effectiveness and safety of dilute povidone-iodine (PVP-I) sinonasal rinses as an adjunctive therapy. METHODS: Prospective cohort study. Twenty-nine recalcitrant CRS patients with endoscopic evidence of ongoing inflammation and purulent discharge were prescribed 0.08% diluted PVP-I rinses. Changes to endoscopic modified Lund-Kennedy (MLK) scores at 7 weeks post-PVP-I rinsing served as the primary outcome measure. RESULTS: The median MLK-discharge score significantly decreased in all patients by 1.50 points post-PVP-I rinsing (p value < 0.01). The total MLK score significantly decreased in all patients by 1.50 points (p value = 0.01). Up to a 17% reduction in serum inflammatory markers was measured post-PVP-I rinsing. Sinonasal culture revealed a shift from moderate-heavy growth to lighter bacterial growth overall. Subjective SNOT-22 scores significantly improved overall by ≥ 1 minimal clinically important difference (MCID > 12; baseline median = 33; follow-up median = 20; p value < 0.01; n = 22). TSH levels increased non-significantly within normal ranges (baseline median = 1.59 mU/L; follow-up median = 1.92 mU/L; p = 0.10; n = 15). Mucociliary clearance time increased non-significantly within normal ranges (baseline median = 9 min; follow-up median = 10 min; p value = 0.53; n = 17). Olfactory Sniffin'16 scores non-significantly decreased within age-related normal ranges (baseline median = 14; follow-up median = 13; p value = 0.72; n = 18). CONCLUSION: A dilute 0.08% PVP-I sinonasal rinse as an ancillary therapy in recalcitrant CRS significantly reduces signs of infection alongside notable symptom improvement, without affecting thyroid function, mucociliary clearance or olfaction.

A Systematic Review of the Clinical Efficacy and Safety of CFTR Modulators in Cystic Fibrosis.

Several placebo-controlled trials have been recently published evaluating novel therapies targeting the defective CFTR protein. This systematic review examines the clinical efficacy and safety of CFTR modulators in individuals with cystic fibrosis (CF) with specific genetic mutations. Online sources were searched for placebo-controlled, parallel-design clinical trials investigating CFTR modulators from January 1, 2005 to March 31, 2018. The primary outcome of interest was FEV1% predicted (ppFEV1). Fourteen RCTs met our eligibility criteria. The largest improvement in ppFEV1 favouring treatment was observed for ivacaftor (IVA) in G551D individuals (≥6 years old). Both tezacaftor-ivacaftor (TEZ-IVA) and lumacaftor-ivacaftor (LUM-IVA) also improved ppFEV1 in F508del homozygous individuals but there was increased reporting of respiratory adverse events with LUM-IVA compared to placebo. IVA also significantly improved ppFEV1 in a sub-group of individuals ≥18 years old with an R117H mutation. No significant improvements in ppFEV1 were observed for IVA, LUM, or TEZ in F508del homozygous individuals, LUM or LUM-IVA in F508del heterozygous individuals, or ataluren in individuals with a nonsense mutation. Significant improvements in ppFEV1 and other clinical outcomes were observed for IVA in G551D individuals, TEV-IVA and LUM-IVA in F508del homozygous individuals, and IVA in adults with a R117H mutation.

Post-Biopsy Manoeuvres to Reduce Pneumothorax Incidence in CT-Guided Transthoracic Lung Biopsies: A Systematic Review and Meta-analysis.

This systematic review and meta-analysis investigated post-biopsy manoeuvres to reduce pneumothorax following computed tomography-guided percutaneous transthoracic lung biopsy. Twenty-one articles were included with 7080 patients. Chest drain insertion rates were significantly reduced by ninefold with the normal saline tract sealant compared to controls (OR 0.11, 95% CI 0.02-0.48), threefold with the rapid rollover manoeuvre to puncture site down (OR 0.34, 95% CI 0.18-0.63), threefold with the tract plug (OR 0.33, 95% CI 0.22-0.48) and threefold with the blood patch (OR 0.39, 95% CI 0.26-0.58). The absolute chest drain insertion rates were the lowest in the normal saline tract sealant (0.8% vs 7.3% for controls), rapid rollover (1.9% vs 5.2%), deep expiration and breath-hold on needle extraction (0.9% vs 1.8%) and standard rollover versus no rollover (2.6% vs 5.2%). These findings highlight post-biopsy manoeuvres which could help reduce pneumothorax and chest drain insertions following lung biopsies. LEVEL OF EVIDENCE: Level 1/no level of evidence, systematic review.

Prognosis of Chronic Rhinosinusitis With Nasal Polyps Using Preoperative Eosinophil/Basophil Levels and Treatment Compliance.

Background Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) have a high risk of disease recurrence and revision surgery. The ability to predict a polyp recurrence in this patient population is critical in order to provide adequately tailored postoperative management. Objective We aim to explore the role of appropriate postoperative care in the prognosis of CRSwNP patients in relation to preoperative eosinophil and basophils levels. Methods This was a retrospective case series; data were collected for 102 CRSwNP patients over a period of 15 months after surgery. Baseline eosinophil and basophil levels were compared between patients with and without polyp recurrences. The analysis was then stratified based on clinical diagnosis, comorbidities (atopy, asthma, and aspirin allergy), a single versus multiple episodes of sinonasal polyp recurrences, and medication adherence. Results Of the 102 included patients, 65 (63.7%) of the patients experienced no recurrences, 26 (25.5%) experienced a single episode of recurrence, and 11 (10.8%) experienced multiple recurrences. Mean baseline eosinophil count and percentage of total white blood cells were significantly higher in the multiple recurrences group (0.70 × 109/L and 10%) compared with the no recurrences group (0.36 × 109/L and 5%). Adherence to prescribed medical therapy prior to the first episode of recurrence was significantly lower for the single exacerbations group (42.3%) than the multiple recurrences group (88.9%). Conclusions Patients with multiple recurrences of nasal polyps had significantly higher baseline eosinophil counts and significantly higher medication adherence compared to single exacerbations of nasal polyps. Single exacerbations may not reflect true failures of surgery but rather a failure of postoperative medical care. Basophil levels were inadequate to predict polyp recurrence rates.

Comparing the efficacy of Silastic and gloved-Merocel middle meatal spacers for functional endoscopic sinus surgery: a randomized controlled trial.

BACKGROUND: Spacers are inserted into the middle meatal space (MMS) following functional endoscopic sinus surgery (FESS) to prevent lateralization of the middle turbinate, scarring, and synechiae. Our objective was to determine if the incidence of postoperative synechiae, facial pain/discomfort, pain during spacer removal, scarring, and discharge differed between nasal cavities receiving Silastic or gloved-Merocel (GM) spacers following FESS. METHODS: A double-blind, randomized controlled trial (RCT) was conducted in adults requiring bilateral FESS for chronic rhinosinusitis (CRS) ± nasal polyposis. Participants served as their own controls, with each subject receiving both a Silastic and GM spacer. Spacers were inserted into the MMS during FESS and left in situ for 6 days. Participants were reviewed at 6 days, 5 weeks, and 12 weeks postoperatively. The presence of synechiae and scarring were evaluated endoscopically. Inflammation, discharge, and pain during spacer removal were assessed using a visual analogue scale (VAS). RESULTS: Forty-eight participants (96 nasal cavities) were recruited. Preoperatively, Lund-Mackay computed tomography (CT) scores were similar between Silastic-treated and GM-treated cavities (6.38 ± 2.35 vs 6.18 ± 2.17). The incidence of synechiae and scarring did not differ significantly between spacers up to 12 weeks postoperatively. Pain during spacer removal was significantly greater for Silastic than GM spacers (2.13 ± 1.34 vs 1.51 ± 1.23, p = 0.020). Facial pain prior to removal and extent of discharge did not differ significantly between spacers. CONCLUSION: Following FESS, patients report less pain during removal of GM than Silastic spacers. However, the likelihood of synechiae and scarring did not differ between either of the spacers.

Potential risk factors associated with the development of synechiae following functional endoscopic sinus surgery.

PURPOSE: Synechiae formation in the middle meatus is the most common complication of functional endoscopic sinus surgery (FESS). Our objectives were to determine the incidence of synechiae occurring in a cohort of patients that have undergone FESS and identify characteristics associated with the development of synechiae postoperatively. METHODS: A retrospective chart review was conducted of CRS patients, with or without nasal polyposis, that had undergone bilateral FESS in the past. All patients had received non-absorbable spacers intraoperatively that were left in situ for 6 days. Demographic and preoperative variables were analyzed to identify synechiae risk factors. A multivariable logistic regression model was constructed to estimate the probability of developing synechiae, given demographic and preoperative variables. RESULTS: Two hundred cases of bilateral FESS were retrospectively reviewed. Thirty-eight (19.0%, 95% CI 13.6-24.4%) patients developed synechiae. Individuals receiving primary FESS and nasal septal reconstruction (NSR) were strongly associated with the development of synechiae (OR 3.5, 95% CI 1.5-8.5; OR 3.0, 95% CI 1.3-6.9). A multivariable logistic regression model adjusting for NSR, recurrent FESS, concha bullosa, requirement of anterior and posterior ethmoidectomy, Lund-Mackay CT score and gender, identified the likelihood of developing synechiae with a sensitivity of 68%, specificity of 73%, positive predictive value of 38% and likelihood ratio of 2.5. CONCLUSION: Patients undergoing primary FESS and NSR are at greatest odds of developing postoperative synechiae. Methods of assessing risk factors and preventing synechiae formation in this population should be evaluated in future prospective investigations.

Variables associated with olfactory disorders in adults: A U.S. population-based analysis.

OBJECTIVE: Olfactory dysfunction is known to have significant social, psychological, and safety implications. Despite increasingly recognized prevalence, potential risk factors for olfactory loss have been arbitrarily documented and knowledge is limited in scale. The aim of this study is to identify potential demographic and exposure variables correlating with olfactory dysfunction. METHODS: Cross-sectional analysis of the 2011-2012 and 2013-2014 editions of the National Health Examination and Nutrition Survey was performed. The utilized survey reports from a nationally representative sample of about 5000 persons each year located in counties across the United States. There is an interview and physical examination component which includes demographic, socioeconomic, dietary, and health-related questions as well as medical, dental, physiologic measurements, and laboratory tests. 3594 adult respondents from 2011 to 2012 and 3708 respondents from 2013 to 2014 were identified from the above population-based database. The frequency of self-reported disorders as well as performance on odor identification testing was determined in relation to demographic factors, occupational or environmental exposures, and urinary levels of environmental and industrial compounds. RESULTS: In both subjective and objective analysis, smell disorders were significantly more common with increasing age. While the non-Hispanic Black and non-Hispanic Asian populations were less likely to report subjective olfactory loss, they, along with Hispanics, performed more poorly on odor identification than Caucasians. Those with limited education had a decreased prevalence of hyposmia. Women outperformed men on smell testing. Those reporting exposure to vapors were more likely to experience olfactory dysfunction, and urinary levels of manganese, 2-Thioxothiazolidine-4-carboxylic acid, and 2-Aminothiazoline-4-carboxylic acid were lower among respondents with subjective smell disturbance. In odor detection, elevated serum levels of lead and urinary levels of 2,4 dichlorophenol were associated with anosmia and hyposmia, respectively. CONCLUSIONS: This study provides current, population-based data identifying demographic and exposure elements related to smell disturbances in U.S. adults. Age, race, gender, education, exposure to vapors, urinary levels of manganese, 2-Thioxothiazolidine-4-carboxylic acid, 2-Aminothiazoline-4-carboxylic acid, 2,4 dichlorophenol, and serum lead levels were all implicated in smell disturbance. Care should be taken in interpretation due to lack of consistency between subjective and objective measures of olfaction as well as limitations related to population-based data. Prospective trials are indicated to further elucidate these relationships.

Defining surgical criteria for empty nose syndrome: Validation of the office-based cotton test and clinical interpretability of the validated Empty Nose Syndrome 6-Item Questionnaire.

OBJECTIVES/HYPOTHESIS: The validated Empty Nose Syndrome 6-Item Questionnaire (ENS6Q) identifies empty nose syndrome (ENS) patients. The unvalidated cotton test assesses improvement in ENS-related symptoms. By first validating the cotton test using the ENS6Q, we define the minimal clinically important difference (MCID) score for the ENS6Q. STUDY DESIGN: Individual case-control study. METHODS: Fifteen patients diagnosed with ENS and 18 controls with non-ENS sinonasal conditions underwent office cotton placement. Both groups completed ENS6Q testing in three conditions-precotton, cotton in situ, and postcotton-to measure the reproducibility of ENS6Q scoring. Participants also completed a five-item transition scale ranging from "much better" to "much worse" to rate subjective changes in nasal breathing with and without cotton placement. Mean changes for each transition point, and the ENS6Q MCID, were then calculated. RESULTS: In the precotton condition, significant differences (P < .001) in all ENS6Q questions between ENS and controls were noted. With cotton in situ, nearly all prior ENS6Q differences normalized between ENS and control patients. For ENS patients, the changes in the mean differences between the precotton and cotton in situ conditions compared to postcotton versus cotton in situ conditions were insignificant among individuals. Including all 33 participants, the mean change in the ENS6Q between the parameters "a little better" and "about the same" was 4.25 (standard deviation [SD] = 5.79) and -2.00 (SD = 3.70), giving an MCID of 6.25. CONCLUSIONS: Cotton testing is a validated office test to assess for ENS patients. Cotton testing also helped to determine the MCID of the ENS6Q, which is a 7-point change from the baseline ENS6Q score. LEVEL OF EVIDENCE: 3b. Laryngoscope, 127:1746-1752, 2017.

Determinants and outcomes of upfront surgery versus medical therapy for chronic rhinosinusitis in cystic fibrosis.

BACKGROUND: The indications for surgical management of chronic rhinosinusitis (CRS) in patients with cystic fibrosis (CF) are poorly defined. In this study we compare outcomes of medical versus surgical treatment and examine trends associated with the transition from medical to surgical therapy in CF patients. METHODS: One hundred thirty-six patients with CF referred to a tertiary rhinology practice were retrospectively divided into 3 cohorts: Medical, Upfront Surgery, or Crossover, if they converted from medical to surgical management. The 22-item Sino-Nasal Outcome Test (SNOT-22) and pulmonary function test (PFT) data were assessed up to 48 months. RESULTS: Compared to patients initially managed medically (n = 90), those who pursued upfront surgery (n = 46) had a greater incidence of nasal polyposis (p = 0.0011), prior sinus surgery (p = 0.0025), lower percent-predicted forced expiratory volume in 1 second (%FEV1 ) (p = 0.0063), and higher Lund-Mackay (p = 0.0025) and SNOT-22 (p = 0.0229) scores. Within the medical group, 35.5% converted to surgery after a mean of 14.3 months. Crossover (n = 32) was associated with a 6.1-point increase in SNOT-22 and a 4.5% deterioration in %FEV1 . Despite worsened symptom severity, the Crossover cohort ultimately achieved similar postoperative SNOT-22 scores (p = 0.831) and %FEV1 (p = 0.114) as those who underwent upfront surgery. Although the Medical cohort had the lowest baseline SNOT-22 scores (p < 0.001), surgery at any time normalized scores to the same baseline level (p = 0.652). Neither medical therapy nor surgery improved PFTs. CONCLUSIONS: Surgery effectively reduces CRS-related symptoms in CF patients but may not improve pulmonary function. In patients who first pursue medical therapy, symptomatic decline may prompt eventual conversion to surgery. Patients who delay surgery may achieve similar outcomes as those who pursue surgery upfront.

The Empty Nose Syndrome 6-Item Questionnaire (ENS6Q): a validated 6-item questionnaire as a diagnostic aid for empty nose syndrome patients.

BACKGROUND: Empty nose syndrome (ENS) is considered an acquired condition that remains difficult to diagnose objectively. Defining specific symptoms that can be reliably associated with this disorder would be essential to identifying possible ENS patients. We sought to validate an ENS-specific, 6-item questionnaire as an adjunct to the standard Sino-Nasal Outcome Test 22 (SNOT-22) questionnaire to discriminate patients suspected of having ENS. METHODS: The Empty Nose Syndrome 6-item Questionnaire (ENS6Q) paired 6 common ENS symptoms (nasal suffocation, nasal burning, nasal openness, crusting, dryness, and impaired air sensation through nasal cavities) with testing on 75 patients divided in 3 patient cohorts: ENS; chronic rhinosinusitis without polyposis; and healthy controls. Participants answered 2 rounds of both the SNOT-22 questionnaire and ENS6Q within 48 hours of each other. No changes in treatments occurred in the test interval between questionnaires. Internal consistency, test-retest reliability, validity, and area under the curve were assessed to differentiate between patient cohorts using the 2 instruments. RESULTS: We found high internal consistency for ENS6Q and SNOT-22 questionnaire at 0.93 (95% CI, 0.90-0.95) and 0.94 (95% CI, 0.94-0.96), respectively. The test-retest reliability between timepoints for ENS6Q testing was 0.969. The ENS6Q statistically significantly discriminated between ENS and control patients and between ENS and chronic rhinosinusitis without polyposis (CRSsNP) patients, without significant differences between CRSsNP and controls. The area-under-the-curve (AUC) threshold score comparison further supported the ability of the ENS6Q to differentiate ENS from CRSsNP patients. CONCLUSION: The ENS6Q is the first validated, specific, adjunct questionnaire to the SNOT-22 to more reliably identify patients suspected of developing ENS.