Development and Validation of a Deep Learning Algorithm for Differentiation of Choroidal Nevi from Small Melanoma in Fundus Photographs.

Purpose: To develop and validate a deep learning algorithm capable of differentiating small choroidal melanomas from nevi. Design: Retrospective multicenter cohort study. Participants: A total of 802 images from 688 patients diagnosed with choroidal nevi or melanoma. Methods: Wide field and standard field fundus photographs were collected from patients diagnosed with choroidal nevi or melanoma by ocular oncologists during clinical examinations. A lesion was classified as a nevus if it was followed for at least 5 years without being rediagnosed as melanoma. A neural network optimized for image classification was trained and validated on cohorts of 495 and 168 images and subsequently tested on independent sets of 86 and 53 images. Main Outcome Measures: Area under the curve (AUC) in receiver operating characteristic analysis for differentiating small choroidal melanomas from nevi. Results: The algorithm achieved an AUC of 0.88 in both test cohorts, outperforming ophthalmologists using the Mushroom shape, Orange pigment, Large size, Enlargement, and Subretinal fluid (AUC 0.77) and To Find Small Ocular Melanoma Using Helpful Hints Daily (AUC 0.67) risk factors (DeLong's test, P < 0.001). The algorithm performed equally well for wide field and standard field photos (AUC 0.89 for both when analyzed separately). Using an optimal operating point of 0.63 (on a scale from 0.00 to 1.00) determined from the training and validation datasets, the algorithm achieved 100% sensitivity and 74% specificity in the first test cohort (F-score 0.72), and 80% sensitivity and 81% specificity in the second (F-score 0.71), which consisted of images from external clinics nationwide. It outperformed 12 ophthalmologists in sensitivity (Mann-Whitney U, P = 0.006) but not specificity (P = 0.54). The algorithm showed higher sensitivity than both resident and consultant ophthalmologists (Dunn's test, P = 0.04 and P = 0.006, respectively) but not ocular oncologists (P > 0.99, all P values Bonferroni corrected). Conclusions: This study develops and validates a deep learning algorithm for differentiating small choroidal melanomas from nevi, matching or surpassing the discriminatory performance of experienced human ophthalmologists. Further research will aim to validate its utility in clinical settings. Financial Disclosures: Financial DisclosuresProprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Mars's induced magnetosphere can degenerate.

The interaction between planets and stellar winds can lead to atmospheric loss and is, thus, important for the evolution of planetary atmospheres1. The planets in our Solar System typically interact with the solar wind, whose velocity is at a large angle to the embedded stellar magnetic field. For planets without an intrinsic magnetic field, this interaction creates an induced magnetosphere and a bow shock in front of the planet2. However, when the angle between the solar wind velocity and the solar wind magnetic field (cone angle) is small, the interaction is very different3. Here we show that when the cone angle is small at Mars, the induced magnetosphere degenerates. There is no shock on the dayside, only weak flank shocks. A cross-flow plume appears and the ambipolar field drives planetary ions upstream. Hybrid simulations with a 4° cone angle show agreement with observations by the Mars Atmosphere and Volatile Evolution mission4 and Mars Express5. Degenerate, induced magnetospheres are complex and not yet explored objects. It remains to be studied what the secondary effects are on processes like atmospheric loss through ion escape.

Future opportunities in solar system plasma science through ESA's exploration programme.

The solar wind interacts with all solar system bodies, inducing different types of dynamics depending on their atmospheric and magnetic environments. We here outline some key open scientific questions related to this interaction, with a focus on the Moon and Mars, that may be addressed by future Mars and Moon missions by the European Space Agency's Human and Robotic Exploration programme. We describe possible studies of plasma interactions with bodies with and without an atmosphere, using multi-point and remote measurements, and energetic particle observations, as well as recommend some actions to take.

Active anterior rhinomanometry: A study on nasal airway resistance, paradoxical reactions to decongestion, and repeatability in healthy subjects.

Objectives: Anterior active rhinomanometry (AAR) is widely used in Swedish routine clinical practice to decide if septoplasty is necessary. The scientific basis for the method needs to be strengthened. Therefore, the aims were to evaluate nasal airway resistance (NAR), paradoxical reactions to pharmacological decongestion, and test-retest characteristics of the Rhino-Comp® AAR in healthy subjects. Methods: A prospective longitudinal design was used. AAR was performed before and after decongestion at baseline and after ≥6 months on 60 healthy volunteers. The relationships between NAR, height, weight, BMI, sex, and allergic rhinitis were evaluated by regression analyses. Descriptive statistics were used to evaluate paradoxical reactions. Test-retest and repeatability characteristics were evaluated with intra-class coefficients (ICC), Cronbach's α, and standard error of measurement. Results: No statistically significant differences were found between genders or nasal cavity sides. NAR was statistically significantly related to height. Short- and long-term test-retest characteristics were good with ICC and Cronbach's α > .75. The minimal significant difference in NAR Log10V2 values between the two measurements was 0.11 and 0.09 (long- and short-term). Paradoxical reactions to pharmacological decongestion were rare, mostly weak, and not evidently reproducible. Conclusion: In this study, we report reference data for healthy subjects, test-retest capabilities, and the minimal relevant difference between two measurements for the Rhino-Comp® AAR, information that is vital and necessary for the appropriate use of AAR in clinical practice. An effective method for pharmacological decongestion is described and recommended for future studies and clinical practice. Paradoxical reactions to pharmacological decongestants exist but maybe without clinical significance. Level of Evidence: NA.

Detection of magnetospheric ion drift patterns at Mars.

Mars lacks a global magnetic field, and instead possesses small-scale crustal magnetic fields, making its magnetic environment fundamentally different from intrinsic magnetospheres like those of Earth or Saturn. Here we report the discovery of magnetospheric ion drift patterns, typical of intrinsic magnetospheres, at Mars using measurements from Mars Atmosphere and Volatile EvolutioN mission. Specifically, we observe wedge-like dispersion structures of hydrogen ions exhibiting butterfly-shaped distributions (pitch angle peaks at 22.5°-45° and 135°-157.5°) within the Martian crustal fields, a feature previously observed only in planetary-scale intrinsic magnetospheres. These dispersed structures are the results of drift motions that fundamentally resemble those observed in intrinsic magnetospheres. Our findings indicate that the Martian magnetosphere embodies an intermediate case where both the unmagnetized and magnetized ion behaviors could be observed because of the wide range of strengths and spatial scales of the crustal magnetic fields around Mars.

[Allergic rhinitis in children and adults - international recommendations adapted to the clinical situation in Sweden]. / Allergisk rinit hos barn och vuxna.

Allergic rhinitis is the most common chronic disease in Sweden, with impact on quality of life and with a heavy economic burden for the society. More than 20 years have passed since national recommendations were launched, and meanwhile both ARIA (Allergic rhinitis and its impact of asthma) and EUFOREA (The European Forum for Research and Education in Allergy and Airway Diseases) have presented international guidelines which in this article have been adapted to the clinical situation in Sweden. Visual analogue scale (VAS) is recommended for symptom evaluation, and the importance of correct allergen analysis and examination for coexisting asthma is emphasized. Treatment is recommended according to EUFOREA. Follow-up is important, and if VAS is ≥5 the disease is regarded as uncontrolled and must lead to a change of treatment. Since self-treatment is common in allergic rhinitis the importance of patient cooperation and information is underlined.

Automated treatment planning for proton pencil beam scanning using deep learning dose prediction and dose-mimicking optimization.

PURPOSE: The purpose of this study is to investigate the use of a deep learning architecture for automated treatment planning for proton pencil beam scanning (PBS). METHODS: A 3-dimensional (3D) U-Net model has been implemented in a commercial treatment planning system (TPS) that uses contoured regions of interest (ROI) binary masks as model inputs with a predicted dose distribution as the model output. Predicted dose distributions were converted to deliverable PBS treatment plans using a voxel-wise robust dose mimicking optimization algorithm. This model was leveraged to generate machine learning (ML) optimized plans for patients receiving proton PBS irradiation of the chest wall. Model training was carried out on a retrospective set of 48 previously-treated chest wall patient treatment plans. Model evaluation was carried out by generating ML-optimized plans on a hold-out set of 12 contoured chest wall patient CT datasets from previously treated patients. Clinical goal criteria and gamma analysis were used to compare dose distributions of the ML-optimized plans against the clinically approved plans across the test patients. RESULTS: Statistical analysis of mean clinical goal criteria indicates that compared to the clinical plans, the ML optimization workflow generated robust plans with similar dose to the heart, lungs, and esophagus while achieving superior dosimetric coverage to the PTV chest wall (clinical mean V95 = 97.6% vs. ML mean V95 = 99.1%, p < 0.001) across the 12 test patients. CONCLUSIONS: ML-based automated treatment plan optimization using the 3D U-Net model can generate treatment plans of similar clinical quality compared to human-driven optimization.

Machine learning-based automatic proton therapy planning: Impact of post-processing and dose-mimicking in plan robustness.

PURPOSE: Automated treatment planning strategies are being widely implemented in clinical routines to reduce inter-planner variability, speed up the optimization process, and improve plan quality. This study aims to evaluate the feasibility and quality of intensity-modulated proton therapy (IMPT) plans generated with four different knowledge-based planning (KBP) pipelines fully integrated into a commercial treatment planning system (TPS). MATERIALS/METHODS: A data set containing 60 oropharyngeal cancer patients was split into 11 folds, each containing 47 patients for training, five patients for validation, and five patients for testing. A dose prediction model was trained on each of the folds, resulting in a total of 11 models. Three patients were left out in order to assess if the differences introduced between models were significant. From voxel-based dose predictions, we analyze the two steps that follow the dose prediction: post-processing of the predicted dose and dose mimicking (DM). We focused on the effect of post-processing (PP) or no post-processing (NPP) combined with two different DM algorithms for optimization: the one available in the commercial TPS RayStation (RSM) and a simpler isodose-based mimicking (IBM). Using 55 test patients (five test patients for each model), we evaluated the quality and robustness of the plans generated by the four proposed KBP pipelines (PP-RSM, PP-IBM, NPP-RSM, NPP-IBM). After robust evaluation, dose-volume histogram (DVH) metrics in nominal and worst-case scenarios were compared to those of the manually generated plans. RESULTS: Nominal doses from the four KBP pipelines showed promising results achieving comparable target coverage and improved dose to organs at risk (OARs) compared to the manual plans. However, too optimistic post-processing applied to the dose prediction (i.e. important decrease of the dose to the organs) compromised the robustness of the plans. Even though RSM seemed to partially compensate for the lack of robustness in the PP plans, still 65% of the patients did not achieve the expected robustness levels. NPP-RSM plans seemed to achieve the best trade-off between robustness and OAR sparing. DISCUSSION/CONCLUSIONS: PP and DM strategies are crucial steps to generate acceptable robust and deliverable IMPT plans from ML-predicted doses. Before the clinical implementation of any KBP pipeline, the PP and DM parameters predefined by the commercial TPS need to be modified accordingly with a comprehensive feedback loop in which the robustness of the final dose calculations is evaluated. With the right choice of PP and DM parameters, KBP strategies have the potential to generate IMPT plans within clinically acceptable levels comparable to plans manually generated by dosimetrists.

Automated Robust Planning for IMPT in Oropharyngeal Cancer Patients Using Machine Learning.

PURPOSE: The aim of this study was to evaluate an automated treatment planning method for robustly optimized intensity modulated proton therapy (IMPT) plans for oropharyngeal carcinoma patients and to compare the results with manually optimized robust IMPT plans. METHODS AND MATERIALS: An atlas regression forest-based machine learning (ML) model for dose prediction was trained on CT scans, contours, and dose distributions of robust IMPT plans of 88 oropharyngeal cancer (OPC) patients. The ML model was combined with a robust voxel and dose volume histogram-based dose mimicking optimization algorithm for 21 perturbed scenarios to generate a machine-deliverable plan from the predicted dose distribution. Machine learning optimization (MLO) configuration was performed using a cross-validation approach with 3 × 8 tuning patients and comprised of adjustments to the mimicking optimization, to generate higher-quality MLO plans. Independent testing of the MLO algorithm was performed with another 25 patients. Plan quality of clinical and MLO plans was evaluated by the clinical target volume (D98% voxel-wise minimum dose >94%), organ at risk (OAR) doses, and the normal tissue complication probability (NTCP) (sum (Σ) of grade-2 and grade-3 dysphagia and xerostomia). RESULTS: Adequate robust target coverage was achieved in 24/25 clinical plans and in 23/25 MLO plans in the primary clinical target volume (CTV). In the elective CTV, 22/25 clinical plans and 24/25 MLO plans passed the robust target coverage evaluation threshold. The MLO average Σgrade 2 and Σgrade 3 NTCPs were comparable to the clinical plans (Σgrade 2 NTCPs: clinical 47.5% vs MLO 48.4%, Σgrade 3 NTCPs: clinical 11.9% vs MLO 12.3%). Significant increases in OAR average doses in MLO plans were found in the pharynx constrictor muscles (163 cGy, P = .002) and cervical esophagus (265 cGy, P = .002). The MLO plans were created within 45 minutes. CONCLUSION: This study showed that automated MLO planning can generate robustly optimized MLO plans with quality comparable to clinical plans in OPC patients.

Speech in adults treated for unilateral cleft lip and palate as rated by naïve listeners, speech-language pathologists, and patients.

Speech may be affected in patients with cleft lip and palate (CLP). Professional listeners, naïve listeners, and patients may perceive speech differently. The aim of the study was to assess speech among adults treated for unilateral CLP (UCLP) as rated by naïve listeners, speech-language pathologists (SLPs), and self-assessment and to evaluate how well these ratings correlate. All patients with complete UCLP treated at the Uppsala University Hospital, Uppsala, Sweden, in 1960-1987 were invited. A total of 73 of 109 patients (67%) participated, with a mean of 35 years since the initiation of treatment. The noncleft control group consisted of 55 volunteers. All participants answered questionnaires for self-rating of speech, and their speech was audio-recorded digitally. Fourteen naïve listeners and four SLPs rated the speech individually from blinded recordings. There were more speech abnormalities among patients compared to controls according to the ratings of naïve listeners and SLPs. In controls and patients, there were positive correlations between the speech ratings by naïve listeners and SLPs r = 0.44 to 0.71, p < 0.001, Spearman). The patients were less satisfied and rated to have more speech abnormalities than controls (p < 0.001). Although adults treated for UCLP considered their speech as fairly good, they were less satisfied than noncleft controls. The agreement between ratings by naïve listeners and SLPs were good, while the agreement between these ratings and self-assessment varied widely. When assessing speech in adults treated for UCLP, differences in perception of speech abnormalities by professionals, laymen, and patients should be considered.

Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency.

The interest in machine learning (ML) has grown tremendously in recent years, partly due to the performance leap that occurred with new techniques of deep learning, convolutional neural networks for images, increased computational power, and wider availability of large datasets. Most fields of medicine follow that popular trend and, notably, radiation oncology is one of those that are at the forefront, with already a long tradition in using digital images and fully computerized workflows. ML models are driven by data, and in contrast with many statistical or physical models, they can be very large and complex, with countless generic parameters. This inevitably raises two questions, namely, the tight dependence between the models and the datasets that feed them, and the interpretability of the models, which scales with its complexity. Any problems in the data used to train the model will be later reflected in their performance. This, together with the low interpretability of ML models, makes their implementation into the clinical workflow particularly difficult. Building tools for risk assessment and quality assurance of ML models must involve then two main points: interpretability and data-model dependency. After a joint introduction of both radiation oncology and ML, this paper reviews the main risks and current solutions when applying the latter to workflows in the former. Risks associated with data and models, as well as their interaction, are detailed. Next, the core concepts of interpretability, explainability, and data-model dependency are formally defined and illustrated with examples. Afterwards, a broad discussion goes through key applications of ML in workflows of radiation oncology as well as vendors' perspectives for the clinical implementation of ML.

A Swedish population-based study of complications due to acute rhinosinusitis in children 5-18 years old.

BACKGROUND: There are few population-based studies of complications due to acute rhinosinusitis in children. The aim was to clarify the admission and complication rate and analyze bacterial cultures in children five to 18 years old in Stockholm, Sweden. METHODS: This was a population-based observational cohort study with retrospectively collected data from individual medical records, from 1 July 2003 to 30 June 2016 in Stockholm, Sweden. Hospital admissions of children with a discharge diagnosis of rhinosinusitis and related complications were reviewed. RESULTS: Incidence of admission due to acute rhinosinusitis was 7.8 per 100 000 children per year (boys 9.2, girls 6.2) and 61% of the admitted children were boys. A severe - postseptal orbital, intracranial or osseous - complication, was present in 34% of admissions (postseptal orbital 28%, intracranial 6%, osseous 4%), resulting in an incidence of 2.6 severe complications per 100 000 children per year (boys 3.6, girls 1.6). Orbital preseptal cellulitis was present in 88% of admissions. Incidence of surgery was 1.3 per 100 000 per year (boys 1.8, girls 0.8) and the percentage of admitted children that had surgery increased with age. S. pyogenes was the most common pathogen found in the whole cohort (29 admissions), while S. milleri was the most common pathogen found among the children with severe complication and surgery. CONCLUSIONS: There is a relative high risk of severe complications in children between five to 18 years that are admitted due to acute rhinosinusitis. There is a need for prospective studies to further analyze the pathogens involved in complications due to acute rhinosinusitis.

Artificial intelligence and machine learning for medical imaging: A technology review.

Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence of disruptive technical advances and impressive experimental results, notably in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have seized the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, segmentation, or classification, the key for a safe and efficient use of clinical AI applications relies, in part, on informed practitioners. The aim of this review is to present the basic technological pillars of AI, together with the state-of-the-art machine learning methods and their application to medical imaging. In addition, we discuss the new trends and future research directions. This will help the reader to understand how AI methods are now becoming an ubiquitous tool in any medical image analysis workflow and pave the way for the clinical implementation of AI-based solutions.

Does the oral steroid treatment of patients with nasal polyposis cause osteopenia or osteoporosis?

OBJECTIVES: We aimed to investigate the bone mineral density (BMD) in a group of Swedish patients with chronic rhinosinusitis with nasal polyposis (CRSwNP) with or without asthma, as well as to evaluate whether the treatment of this patient group is in accordance with the EPOS recommendations. DESIGN, SETTINGS AND PARTICIPANTS: Adult patients with a diagnosis of CRSwNP, and a history of at least two courses of oral corticosteroids (OCS) during the last year, were consecutively included in this study at five centres. MAIN OUTCOME MEASURES: The BMD of the patients was measured by Dual-energy X-ray absorptiometry (DXA), which is the only technology for classifying BMD according to the criteria established by WHO. RESULTS: A total of 51 patients, with an average number of 7 years with OCS treatment, were enrolled. During the last 12 months, the mean number of OCS courses was 2.76, and the total mean intake was 891 mg of Prednisone equivalents. According to the T-scores, 17 patients were measured to have ≤-1 SD T-score lumbar spine, which is considered to be osteopenia, and five patients had <-2.5 SD T-score, considered as osteoporosis. However, when taking age and gender into account and analysing the Z-scores, only 2 patients had a reduced density of the spine and none in the hip, which is no difference compared to a matched Swedish population. CONCLUSIONS: This prospective study shows that 2-3 moderate courses of OCS annually may be used without high risk of causing osteopenia/osteoporosis in patients with CRSwNP.

Incident Chronic Rhinosinusitis Is Associated With Impaired Sleep Quality: Results of the RHINE Study.

STUDY OBJECTIVES: Chronic rhinosinusitis (CRS) is a common inflammatory disease of the nasal cavity and paranasal sinuses. Associations between CRS and poor sleep quality have been reported. This 10-year follow-up study investigates possible associations between incident CRS and sleep quality. METHODS: A questionnaire was sent to 16,500 individuals in Sweden, Norway, Denmark, Iceland and Estonia in 2000. It included questions on airway diseases, age, sex, body mass index, smoking habits, comorbidities, education and sleep quality. In 2010, a second questionnaire was sent to the same individuals, with a response rate of 53%. A subgroup of 5,145 individuals without nasal symptoms in 2000 was studied. Multiple logistic regression was performed to examine associations between CRS (defined according to the European position paper on rhinosinusitis and nasal polyps epidemiological criteria) at follow-up and sleep quality, with adjustment for potential confounders. Individuals with the respective sleep problem at baseline were excluded. RESULTS: Over 10 years, 141 (2.7%) of the individuals without nasal symptoms in 2000 had developed CRS. CRS was associated with difficulties inducing sleep (adjusted odds ratio 2.81 [95% CI 1.67-4.70]), difficulties maintaining sleep (2.07 [1.35-3.18]), early morning awakening (3.03 [1.91-4.81]), insomnia (2.21 [1.46-3.35]), excessive daytime sleepiness (2.85 [1.79-4.55]), and snoring (3.31 [2.07-5.31]). Three insomnia symptoms at baseline increased the risk of CRS at follow-up by 5.00 (1.93-12.99). CONCLUSIONS: Incident CRS is associated with impaired sleep quality and excessive daytime sleepiness. Insomnia symptoms may be a risk factor for the development of CRS.

The complex pathophysiology of allergic rhinitis: scientific rationale for the development of an alternative treatment option.

Allergic rhinitis (AR) poses a global health problem and can be challenging to treat. Many of the current symptomatic treatments for AR have been available for decades, yet there has been little improvement in patient quality of life or symptom burden over the years. In this review, we ask why this might be and explore the pathophysiological gaps that exist within the various AR treatment classes. We focus on the benefits and drawbacks of different treatment options and delivery routes for AR treatments and consider how, given what is known about AR pathophysiology and symptomatology, patients may be offered more effective treatment options for rapid, effective, and sustained AR control. In particular, we consider how a new AR preparation, MP-AzeFlu (Dymista®, Meda, Sweden), comprising a formulation of an intranasal antihistamine (azelastine hydrochloride), an intranasal corticosteroid (fluticasone propionate), and excipients delivered in a single spray, may offer benefits over and above single and multiple AR therapy options. We review the evidence in support of this treatment across the spectrum of AR disease. The concept of AR control is also reviewed within the context of new European Union and Contre les Maladies Chroniques pour un VIeillissement Actif-Allergic Rhinitis and its Impact on Asthma initiatives.

Voice Quality in Adults Treated for Unilateral Cleft Lip and Palate: Long-Term Follow-Up After One- or Two-Stage Palate Repair.

OBJECTIVES: The aim of the current study was to assess voice quality among adults treated for unilateral cleft lip and palate (UCLP), after one- or two-stage palate closure, and compare it to a noncleft control group. STUDY DESIGN: Cross-sectional study of patients with UCLP with long-term follow-up and noncleft controls. PARTICIPANTS: Patients with UCLP born between 1960 and 1987, treated at Uppsala University Hospital, Sweden, were examined (n = 73) at a mean of 35 years after primary surgery. Forty-seven (64%) patients had been treated with 1-stage palate closure and 26 with 2-stage closure (36%). The noncleft control group consisted of 63 age-matched volunteers. MAIN OUTCOME MEASURES: Ratings of perceptual voice characteristics from blinded voice recordings with Swedish Voice Evaluation Approach method. Acoustic voice analysis including pitch and spectral measures. RESULTS: Among the patients, the mean values for the 12 evaluated variables on a visual analog scale (0 = no abnormality, 100 = maximal abnormality) ranged between 0.1 and 17, and the mean for all was 6 mm. Voice variables were similar between patients and controls, except the total mean of all the perceptual voice variables, as well as "vocal fry"; both slightly lower among patients ( P = .018 and P = .009). There was no difference in any variable between patients treated with 1-stage and 2-stage palate closure. No clear relationship was found between velopharyngeal insufficiency and dysphonia. CONCLUSIONS: The voice characteristics among adults treated for UCLP in childhood are not different from those of individuals without cleft.

Voice Quality in Adults Treated for Unilateral Cleft Lip and Palate: Long-term Follow-up After 1- or 2-Stage Palate Repair.

OBJECTIVES: The aim of the current study was to assess voice quality among adults treated for unilateral cleft lip and palate (UCLP), after 1- or 2-stage palate closure, and compare it to a noncleft control group. STUDY DESIGN: Cross-sectional study in UCLP patients with long-term follow-up and noncleft controls. PARTICIPANTS: UCLP patients born 1960-1987, treated at Uppsala University Hospital, Sweden, were examined (n = 73) at a mean of 35 years after primary surgery. Forty-seven patients (64%) had been treated with 1-stage palate closure and 26 with 2-stage closure (36%). The noncleft control group consisted of 63 age-matched volunteers. MAIN OUTCOME MEASURE(S): Ratings of perceptual voice characteristics from blinded voice recordings with Swedish Voice Evaluation Approach (SVEA) method. Acoustic voice analysis including pitch and spectral measures. RESULTS: Among the patients, the mean values for the 12 evaluated variables on a VAS scale (0 = no abnormality, 100 = maximal abnormality) ranged between 1 and 22 and the mean for all was 6 mm. Voice variables were similar between patients and controls except the total mean of all the perceptual voice variables, as well as "vocal fry"-both slightly lower among patients ( P = .018 and P = .009). There was no difference in any variable between patients treated with 1-stage and 2-stage palate closure. No clear relationship was found between VPI and dysphonia. CONCLUSION: The voice characteristics among adults treated for UCLP in childhood are not different from those of individuals without cleft.

Chronic Rhinosinusitis Impairs Sleep Quality: Results of the GA2LEN Study.

Study objectives: To analyze the prevalence of sleep problems in subjects with Chronic rhinosinusitis (CRS) and to determine whether the disease severity of CRS affects sleep quality. Methods: Questionnaires were sent to a random sample of 45 000 adults in four Swedish cities. Questions on CRS, asthma, allergic rhinitis, co-morbidities, tobacco use, educational level, and physical activity were included. CRS was defined according to the European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS) epidemiological criteria. The disease severity of CRS was defined by the number of reported CRS symptoms. Sleep quality was assessed using the Basic Nordic Sleep Questionnaire. Results: Of the 26 647 subjects, 2249 (8.4%) had CRS. Reported sleep problems were 50%-90% more common among subjects with CRS compared with those without or the total population. The prevalence of reported sleep problems increased in conjunction with the severity of CRS. After adjusting for gender, BMI, age, tobacco use, asthma, somatic diseases, physical activity level, and educational level, participants with four symptoms of CRS (compared with subjects without CRS symptoms) displayed a higher risk of snoring (adj. OR [95% CI]: 3.13 [2.22-4.41]), difficulties inducing sleep (3.98 [2.94-5.40]), difficulties maintaining sleep (3.44 [2.55-4.64]), early morning awakening (4.71 [3.47-6.38]) and excessive daytime sleepiness (4.56 [3.36-6.18]). The addition of persistent allergic rhinitis to CRS further increased the risk of sleep problems. Conclusions: Sleep problems are highly prevalent among subjects with CRS. The disease severity of CRS negatively affects sleep quality.

Can objective measurements of the nasal form and function represent the clinical picture in unilateral cleft lip and palate?

BACKGROUND: The present study aimed to evaluate the potential correlations between objective measurements of nasal function and self-assessed nasal symptoms or clinical findings at nasal examination among adults treated for unilateral cleft lip and palate (UCLP), respectively. METHODS: All UCLP patients born between 1960 and 1987 (n = 109) treated at a tertiary referring center were invited. Participation rate was 76% (n = 83) at a mean of 37 years after the initial surgery. All participants completed the same study protocol including acoustic rhinometry (AR), rhinomanometry (RM), anterior rhinoscopy, and questionnaires regarding self-experienced nasal symptoms. RESULTS: A reduced volume of the anterior nasal cavity on the operated side (measured by AR) correlated to an expressed wish by the patient to change the function of the nose. A similar correlation was seen for the minimal cross-sectional area of anterior nasal cavity on the operated side. Furthermore, correlations were found between smaller volume and area of nasal cavity and a greater frequency of nasal obstruction. No further correlations were found. CONCLUSION: Objective measurements partly correlate to the clinical picture among adults treated for UCLP. However, these need to be combined with findings at clinical examination and patient self-assessment to represent the complete clinical picture.