Background: Obstructive Sleep Apnea (OSA) syndrome is a respiratory sleep disorder characterized by partial or complete episodes of upper airway collapse with reduction or complete cessation of airflow. Although the connection remains debated, several mechanisms such as intermittent hypoxemia, sleep deprivation, hypercapnia disruption of the hypothalamic–pituitary–adrenal axis have been associated with poor neurocognitive performance. Different treatments have been proposed to treat OSAS patients as continuous positive airway pressure (CPAP), mandibular advancement devices (MAD), surgery; however, the effect on neurocognitive functions is still debated. This article presents the effect of OSAS treatments on neurocognitive performance by reviewing the literature. Methods: We performed a comprehensive review of the English language over the past 20 years using the following keywords: neurocognitive performance and sleep apnea, neurocognitive improvement and CPAP, OSAS, and cognitive dysfunction. We included in the analysis papers that correlated OSA treatment with neurocognitive performance improvement. All validated tests used to measure different neurocognitive performance improvements were considered. Results: Seventy papers reported neurocognitive Performance improvement in OSA patients after CPAP therapy. Eighty percent of studies found improved executive functions such as verbal fluency or working memory, with partial neural recovery at long-term follow-up. One article compared the effect of MAD, CPAP treatment on cognitive disorders, reporting better improvement of CPAP and MAD than placebo in cognitive function. Conclusions: CPAP treatment seems to improve cognitive defects associated with OSA. Limited studies have evaluated the effects of the other therapies on cognitive function.
The impact of elective neck treatment (ENT), whether by irradiation or dissection, on the prognosis of patients with cN0 sinonasal carcinomas (SNCs) remains an understudied issue. METHODS: A systematic review and meta-analysis of the literature were performed according to PRISMA guidelines in order to assess regional nodal relapse rate after ENT compared to observation in cN0 SNCs patients. Twenty-six articles for a total of 1178 clinically N0 patients were analyzed. Globally, the 5-year overall survival was 52%; 34.6% of patients underwent ENT and 140 regional recurrences were registered (5.9% in the ENT cohort and 15% in the observation group). ENT appears to confer a lower risk of regional recurrence compared to observation alone, with a cumulative OR of 0.38 (95% CI 0.25–0.58). Our meta-analysis supports the efficacy of ENT for reducing the risk of regional recurrence, but its overall impact on survival remains uncertain.
Background and Objectives
Postoperative morbidity after open partial laryngeal surgery (OPLS) may be serious, leading to a prolonged length of hospital stay and increasing costs. We sought to define the predictive factors of complications and to develop nomograms for patients eligible for OPLS based on clinical and surgical data.
Methods
We critically reviewed 535 patients with laryngeal carcinoma who underwent OPLS at our Institution from 1982 to 2007. We have identified patients affected by postoperative local, airway, dysphagia, bleeding, surgical site infection, dehiscence of pexy, emphysema, and laryngocutaneous fistula complications. We have analyzed them according to age, smoking, alcohol, tumor site, clinical T and N classification, type of OPLS and neck dissection, previous treatments. Prognostic factors were considered in a multivariate logistic regression model with backward stepwise elimination and selected to construct and design nomograms for overall and specific complications. The performance was assessed using the c‐index, receiver operating characteristic, and calibration curves.
Results
Age, clinical T classification, type of OPLS, and alcohol were related to overall (35%) and airway complications. Nomograms were built for overall, dysphagia, and airway complications.
Conclusions
We have developed nomograms that can identify high‐risk patients undergoing OPLS and that can help to prevent severe complications and to tailor surgical planning.
Objectives: To evaluate the role of clinical scores assessing the risk of disease severity in patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis was tested by applying artificial intelligence (AI) to demonstrate its effectiveness in distinguishing between mild–moderate OSA and severe OSA risk. Methods: A support vector machine model (SVM) was developed from the samples included in the analysis (N = 498), and they were split into 75% for training (N = 373) with the remaining for testing (N = 125). Two diagnostic thresholds were selected for OSA severity: mild to moderate (apnea–hypopnea index (AHI) ≥ 5 events/h and AHI < 30 events/h) and severe (AHI ≥ 30 events/h). The algorithms were trained and tested to predict OSA patient severity. Results: The sensitivity and specificity for the SVM model were 0.93 and 0.80 with an accuracy of 0.86; instead, the logistic regression full mode reported a value of 0.74 and 0.63, respectively, with an accuracy of 0.68. After backward stepwise elimination for features selection, the reduced logistic regression model demonstrated a sensitivity and specificity of 0.79 and 0.56, respectively, and an accuracy of 0.67. Conclusion: Artificial intelligence could be applied to patients with symptoms related to OSA to identify individuals with a severe OSA risk with clinical-based algorithms in the OSA framework.
Background: Narrow band imaging (NBI) endoscopy is an optical method that helps to characterise tissue vasculature. Its application in sinonasal pathology remains scarce and a systematic study of its application to rhinology is lacking. The aim of this study is to analyse and describe the normal sinonasal mucosa under NBI light and to characterise the microvascular features of various sinonasal pathologies. We also want to suggest a classification of the patterns, peculiar to this district, and to evaluate whether they can be indicative of a specific physiological or pathological condition.Methods: Digital videos and images under white light and NBI of 103 patients (82 evaluated) with 29 sinonasal pathologies and 55 controls (33 evaluated). were independently analysed by three otolaryngologists and the final pattern was then arranged for each image, reaching an agreement between the individual evaluations.
Results:Once the appearance of normal sinonasal (SN) mucosa was established (SN1), four patterns for the pathological mucosa were described and a working classification was proposed (SN2, SN3, SN4, SN5). We calculated specificity (80.6% vs 90.6%), sensitivity (20% vs 38.5%), PPV (46.1% vs 50%), NPV (54.7% vs 85.7%) and accuracy (53% vs 80.3%) of the ability of SN4 and SN5 pattern to discriminate between benign and malignant nasal neoformations.Conclusions: This is the first study to propose a systematic NBI description and a classification of the vasculature of healthy and pathological mucosa in the sinonasal tract. Our preliminary results show that this technique can help in the workup of several rhinologic conditions and especially in distinguishing benign from malignant tumors.
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