Prediction of Obstructive Sleep Apnea Based on Respiratory Sounds Recorded Between Sleep Onset and Sleep Offset

Objectives To develop a simple algorithm for prescreening of obstructive sleep apnea (OSA) on the basis of respiratorysounds recorded during polysomnography during all sleep stages between sleep onset and offset. Methods Patients who underwent attended, in-laboratory, full-night polysomnography were included. For all patients, audiorecordings were performed with an air-conduction microphone during polysomnography. Analyses included allsleep stages (i.e., N1, N2, N3, rapid eye movement, and waking). After noise reduction preprocessing, data were segmentedinto 5-s windows and sound features were extracted. Prediction models were established and validated with10-fold cross-validation by using simple logistic regression. Binary classifications were separately conducted for threedifferent threshold criteria at apnea hypopnea index (AHI) of 5, 15, or 30. Prediction model characteristics, includingaccuracy, sensitivity, specificity, positive predictive value (precision), negative predictive value, and area under thecurve (AUC) of the receiver operating characteristic were computed. Results A total of 116 subjects were included; their mean age, body mass index, and AHI were 50.4 years, 25.5 kg/m2, and23.0/hr, respectively. A total of 508 sound features were extracted from respiratory sounds recorded throughoutsleep. Accuracies of binary classifiers at AHIs of 5, 15, and 30 were 82.7%, 84.4%, and 85.3%, respectively. Predictionperformances for the classifiers at AHIs of 5, 15, and 30 were AUC, 0.83, 0.901, and 0.91; sensitivity, 87.5%,81.6%, and 60%; and specificity, 67.8%, 87.5%, and 94.1%. Respective precision values of the classifiers were89.5%, 87.5%, and 78.2% for AHIs of 5, 15, and 30. Conclusion This study showed that our binary classifier predicted patients with AHI of ≥15 with sensitivity and specificityof >80% by using respiratory sounds during sleep. Since our prediction model included all sleep stage data, algorithmsbased on respiratory sounds may have a high value for prescreening OSA with mobile devices

Multivariate analysis of prognostic factors in patients with pulmonary actinomycosis

BACKGROUND: There have been few studies of pulmonary actinomycosis, which is an uncommon anaerobic infection. Consequently, the optimal therapeutic regimen, appropriate duration of treatment, long-term prognosis, and factors predicting prognosis are not well established. METHODS: We retrospectively reviewed the medical records of histopathologically confirmed cases of pulmonary actinomycosis seen between November 2003 and December 2012. RESULTS: The study included 68 patients with a mean age of 58.4 ± 11.6 years. Of the 68, initial surgery was performed in 15 patients (22.1%), while the remaining 53 (77.9%) received antibiotic therapy initially. In the initial antibiotic group, 45/53 (84.9%) were cured without relapse (median antibiotic duration 5.3 months). 5/53 (9.4%) patients were refractory medically (median antibiotic duration 9.7 months), and 3/53 (5.7%) experienced a recurrence (median time to relapse 35.3 months). In the initial surgery group, 14/15 (93.3%) were cured and treatment failure occurred in one (6.7%). In the multivariate analysis, the absence of an antibiotic response at 1 month was the only independent factor associated with a poor treatment outcome, with an adjusted odds ratio of 49.2 (95% CI, 3.34–724.30). There was no significant difference in treatment outcome based on the size of the parenchymal lesion, comorbidities, whether intravenous antibiotics were used, antibiotic therapy duration, or whether the initial treatment was surgical. CONCLUSIONS: Antibiotic treatment with or without surgery was effective for treatment of pulmonary actinomycosis. Nevertheless, treatment failure or recurrence occurred in a considerable proportion of patients, especially those resistant to the initial antibiotic treatment

Guidelines for Tailored Chemical Functionalization of Graphene

Graphene oxide (GO) has been synthesized by the Hummers method with modification of experimental condition by different research groups, but there is no guideline to prepare tailored GO for targeted applications. In this research, we suggest a guideline for tailor-fittable functionalization of graphene on the basis of the scope of our previous report on the two-step oxidation of GO. We describe a detailed procedure for synthesis of GO, effects of degree of step I oxidation on characteristics of GO and comparing them with effects of degree of step II oxidation. Characteristic changes of GO occurring during step I oxidation and those occurring during step II oxidation are different in species of oxygen functional groups, interlayer spacing, thermal stability, size distribution, and yield of GO. On the basis of the results, three types of tailor-fitted GO for a fiber, transparent conducting film, and hydrogen storage material are synthesized by controlling the degree of step I and step II oxidation. Compared to the reference GO synthesized by conventional modified Hummers method, the tailor-fitted GO showed 33.5%, 117%, and 104% enhanced performance in strength of the fiber, figure of merits of transparent conducting film, and hydrogen storage, respectively. Our results show that the performance of GO based application is significantly influenced by the synthesis condition of GO, and optimized performance of the applications can be obtained by the tailor-fitted functionalization of GO. We anticipate that this study would be helpful for a variety of researches, both synthesis and application of GO

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A novel root-index based prioritized random access scheme for 5G cellular networks

Cellular networks will play an important role in realizing the newly emerging Internet-of-Everything (IoE). One of the challenging issues is to support the quality of service (QoS) during the access phase, while accommodating a massive number of machine nodes. In this paper, we show a new paradigm of multiple access priorities in random access (RA) procedure and propose a novel root-index based prioritized random access (RIPRA) scheme that implicitly embeds the access priority in the root index of the RA preambles. The performance evaluation shows that the proposed RIPRA scheme can successfully support differentiated performance for different access priority levels, even though there exist a massive number of machine nodes

Vehicle Trajectory Prediction with Lane Stream Attention-Based LSTMs and Road Geometry Linearization

It is essential for autonomous vehicles at level 3 or higher to have the ability to predict the trajectories of surrounding vehicles to safely and effectively plan and drive along trajectories in complex traffic situations. However, predicting the future behavior of vehicles is a challenging issue because traffic vehicles each have different drivers with different driving tendencies and intentions and they interact with each other. This paper presents a Long Short-Term Memory (LSTM) encoder–decoder model that utilizes an attention mechanism that focuses on certain information to predict vehicles’ trajectories. The proposed model was trained using the Highway Drone (HighD) dataset, which is a high-precision, large-scale traffic dataset. We also compared this model to previous studies. Our model effectively predicted future trajectories by using an attention mechanism to manage the importance of the driving flow of the target and adjacent vehicles and the target vehicle’s dynamics in each driving situation. Furthermore, this study presents a method of linearizing the road geometry such that the trajectory prediction model can be used in a variety of road environments. We verified that the road geometry linearization mechanism can improve the trajectory prediction model’s performance on various road environments in a virtual test-driving simulator constructed based on actual road data

Selection model of representative items for the subcontractors’ cost index in multi‐family housing projects

Price index has played an important role in measuring the past performance of an industry, which it does by tracking the cost of the items used in the industry. It is the most widely used industry performance indicator because a small number of representative items covers a wide range of costs. The construction industry consists of various facility types that can be organized into many subcontractors’ works. Unfortunately, the existing cost indexes have difficulty monitoring the fluctuation of the subcontractors’ costs since they select representative items in macro‐scale terms, such as the type of construction or facility. Therefore, this study was conducted to develop a selection model that can select the effective representative items included in the subcontractors’ costs. To determine the characteristics of the subcontractors’ costs, the curve estimation function of SPSS® 12.0 for Windows was applied to the priced bills of quantities of 30 multi‐family housing projects. The results of the analysis show that the relationship between the coverage ratio and the percentage of the number of representative items follows Pareto's principle. Based on this, a selection model of representative items was developed, using the tangent function. The case study that was conducted to verify the usability of the model revealed that the proposed model can efficiently select the effective representative items from the cost items of each subcontractor's work included in multi‐family housing projects. Santrauka Kainos rodiklis yra labai svarbus analizuojant igyvendintus projektus ir yra tiriamas naudojamu tipiniu produktu pramoneje. Tai plačiai naudojamas pramones veiklos rodiklis, tačiau nedaugeliui tipiniu produktu būdingas platus kainu diapazonas. Statybos pramone apima ivairias paslaugu rūšis, kuriu daugeli teikia subrangovai. Deja, esami kainos rodiklio subrangovu išlaidu svyravimai sunkiai kontroliuojami, nes tipiniai produktai, tokie kaip statybos būdas ar gebejimai, atrenkami makroskales požiūriu. Todel šis tyrimas buvo atliktas siekiant sukurti atrankos modeli, pagal kuri būtu galima pasirinkti naudingiausia tipini produkta ir ivertinti subrangovu išlaidas. Subrangovu sanaudu charakteristikoms nustatyti taikyti kreives funkcijos skaičiavimai SPSS® 12.0 Windows, naudoti 30 daugiabučiu namu projektu ikainojimo dokumen‐tai. Tyrimu rezultatai rodo, kad santykis tarp apimčiu koeficiento ir tipiniu produktu procento pagristas Pareto principu. Juo remiantis buvo sukurtas tipiniu produktu atrankos modelis, taikant tangento funkcija. Atvejo tyrimas, atliktas siekiant patikrinti modelio naudojima, atskleide, kad numatomas atrankos modelis gali racionaliai parinkti kiekvieno subrangovo darbus pagal naudingiausius tipinius elementus, kurie itraukti i daugiabučiu namuprojektus. First Published Online: 24 Jun 2011 Reikšminiai žodžiai: gyvenamuju namu statybos projektai, tipiniai produktai, atrankos modelis, kainos rodiklis, subrangovu išlaidos, tangento funkcija, sanaudu rodikli

Recurrent Desaturation Events due to Opioid-Induced Chest Wall Rigidity after Low Dose Fentanyl Administration

Opioid-induced chest wall rigidity is an uncommon complication of opioids. Because of this, it is often difficult to make a differential diagnosis in a mechanically ventilated patient who experiences increased airway pressure and difficulty with ventilation. A 76-year-old female patient was admitted to the intensive care unit (ICU) after surgery for periprosthetic fracture of the femur neck. On completion of the surgery, airway pressure was increased, and oxygen saturation fell below 95% after a bolus dose of fentanyl. After ICU admission, the same event recurred. Manual ventilation was immediately started, and a muscle relaxant relieved the symptoms. There was no sign or symptom suggesting airway obstruction or asthma on physical examination. Early recognition and treatment should be made in a mechanically ventilated patient experiencing increased airway pressure in order to prevent further deterioration