Efficacy of Oral Appliance for Mild, Moderate, and Severe Obstructive Sleep Apnea: A Meta-analysis

OBJECTIVE

Oral appliances (OA) are the recommended first-line option for mild-to-moderate obstructive sleep apnea (OSA)-hypopnea. However, there is a lack of evidence to compare the effectiveness of OA in different severities of OSA. The purpose of this study was to investigate the therapeutic effects of preferred OA (tongue retention devices [TRD] and mandibular advancement device [MAD]) in different severities of OSA.

DATA SOURCES

PubMed/MEDLINE, The Cochrane Library, and Web of Science.

REVIEW METHODS

Concentrating on the efficacy of OA, 2 authors searched 3 databases up to November 10, 2022, independently and systematically, following the requirements and steps of the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines.

RESULTS

Ultimately, 42 studies with 2265 patients met the criteria for inclusion in OA. Overall, the apnea-hypopnea index improved by 48% (5.6), 67% (14.92), and 62% (32.1) in mild, moderate, and severe OSA, respectively. Subgroup analysis showed a significant difference between MAD and TRD efficacy in mild OSA (58% vs 21%). However, no significant difference was seen between MAD and TRD efficacy in moderate (67% vs 66%) and severe OSA (66% vs 51%). There was no significant difference across groups in the Epworth Sleepiness Scale, oxygen desaturation index (ODI), and lowest oxygen saturation (LSAT).

CONCLUSION

Overall, both TRD and MAD are effective treatments for moderate and severe OSA. MAD is efficacious in mild OSA, while TRD requires further validation. Furthermore, mild-moderate and severe OSA received similar improvements in sleepiness, ODI, and LSAT. This study complements the evidence for the efficacy of OA.

Head and Neck Malignant Paragangliomas: Experience from a Single Institution

Objectives: To summarize the clinicopathological and genetic features of malignant paragangliomas in head and neck cancer and to explore the appropriate treatment options for this rare lesion. Methods: Six patients harboring head and neck malignant paraganglioma from Beijing Tongren Hospital were retrospectively reviewed. The clinicopathological characteristics, gene mutations, and prognosis of these patients were analyzed. Results: Of these 6 patients, 3 were male and 3 were female; 4 patients harbored malignant carotid body tumors, and two had malignant vagal paragangliomas. Three patients had cervical lymph node metastasis, two presented with lung and bone metastasis, and 1 had lung and liver metastasis. Of the 6 patients, four underwent surgical resection, and the other two patients denied surgery and instead received chemotherapy with paclitaxel, ifosfamide, and dacarbazine. These 2 patients with vagal paraganglioma received postoperative radiotherapy. All 6 patients are still alive at the present time, with a median follow-up time of 66 months. Positive Ki-67 expression in tumor tissue ranged from 1% to 40%. Genetic mutations in SDHD, SDHB, ATR, and MAP3K13 were identified in 4 patients. Conclusions: After comprehensive treatment, head and neck malignant paraganglioma can attain a favorable prognosis. Genetic mutations are commonly detected in patients with malignant paragangliomas. This study also identified mutations in ATR and MAP3K13 in these patients.

Study on the impact of COVID-19 pandemic on the mental health of Chinese college students: a cross-sectional analysis

Background

The COVID-19 pandemic has significantly impacted the mental health of college students, prompting the need for universities to implement measures to mitigate these adverse effects. This study aims to assess the mental health status and mitigation measures of college students, identify the primary factors contributing to their mental health challenges, and provide suggestions for educational institutions to reduce negative psychological impacts.

Methods

In February 2023, a questionnaire survey was conducted among 1,445 college students. Statistical analysis was performed on the survey results, and multiple regression models were used to identify significant influencing factors and optimize the model.

Results

The study revealed correlations between factors affecting mental health during the pandemic, with interactions observed among some factors. Significant differences in mental health status were found among different groups of college students based on their information-sharing habits through apps and engagement in thesis research. Multiple regression analysis indicated that conducting academic research related to COVID-19 significantly increased the psychological stress of college students during the pandemic (p = 0.043). Among all mitigation measures, playing games demonstrated significant effectiveness in model analysis (p = 0.047). The optimization of the model showed that the multiple regression model considering the interaction of factors was more effective.

Conclusion

Our research identifies crucial factors influencing the mental health of college students and investigates the mental health status of various student groups. We recommend that educational institutions adopt proactive strategies and a multifaceted approach to support the mental health of college students and address potential issues that may arise.

Evaluation of force pain thresholds to ensure collision safety in worker-robot collaborative operations

With the growing demand for robots in the industrial field, robot-related technologies with various functions have been introduced. One notable development is the implementation of robots that operate in collaboration with human workers to share tasks, without the need of any physical barriers such as safety fences. The realization of such collaborative operations in practice necessitates the assurance of safety if humans and robots collide. Thus, it is important to establish criteria for such collision scenarios to ensure robot safety and prevent injuries. Collision safety must be ensured in both pinching (quasi-static contact) and impact (transient contact) situations. To this end, we measured the force pain thresholds associated with impacts and evaluated the biomechanical limitations. This measurements were obtained through clinical trials involving physical collisions between human subjects and a device designed for generating impacts, and the force pain thresholds associated with transient collisions between humans and robots were analyzed. Specifically, the force pain threshold was measured at two different locations on the bodies of 37 adults aged 19-32 years, using two impactors with different shapes. The force pain threshold was compared with the results of other relevant studies. The results can help identify biomechanical limitations in a precise and reliable manner to ensure the safety of robots in collaborative applications.

The value of T2-weighted MRI contrast ratio combined with DWI in evaluating the pathological grade of solid lung adenocarcinoma

AIM

To assess the predictive value of T2-weighted (T2W) magnetic resonance imaging (MRI) in combination with diffusion-weighted imaging (DWI) for determining the pathological grading of solid lung adenocarcinoma.

MATERIALS AND METHODS

The clinical and imaging data from 153 cases of solid lung adenocarcinoma (82 men, 71 women, mean age 63.2 years) confirmed at histopathology in The First Affiliated Hospital of Xi'an Jiaotong University from January 2017 to May 2022 were analysed retrospectively. Adenocarcinomas were classified into low-grade (G1 and G2) and high-grade (G3) groups following the 2020 pathological grading system proposed by the International Association for the Study of Lung Cancer. The T2-weighted contrast ratio (T2CR), calculated as the T2 signal intensity of the lung mass/nodule divided by the T2 signal intensity of the right rhomboid muscle was utilised. Two experienced radiologists reviewed the MRI images independently, measured the T2CR, and obtained apparent diffusion coefficient (ADC) values. The Mann-Whitney U-test was used to compare general characteristics (sex, age, maximum diameter), T2CR, and ADC values between the low-grade and high-grade groups. The non-parametric Kruskal-Wallis test determined differences in T2CR and ADC values among the five adenocarcinoma subtypes. Receiver characteristic curve (ROC) analysis, along with area under the curve (AUC) calculation, assessed the effectiveness of each parameter in distinguishing the pathological grade of lung adenocarcinoma. A Z-test was used to compare the AUC values.

RESULTS

Among the 153 patients with adenocarcinoma, 103 had low-grade adenocarcinoma, and 50 had high-grade adenocarcinoma. The agreement between T2CR and ADC observers was good (0.948 and 0.929, respectively). None of the parameters followed a normal distribution (p<0.05). The ADC value was lower in the high-grade adenocarcinoma group compared to the low-grade adenocarcinoma group (p=0.004), while the T2CR value was higher in the high-grade group (p=0.011). Statistically significant differences were observed in maximum diameter and gender between the two groups (p<0.001 and p=0.005, respectively), while no significant differences were noted in age (p=0.980). Among the five adenocarcinoma subtypes, only the lepidic and micropapillary subtypes displayed statistical differences in ADC values (p=0.047), with the remaining subtypes showing no statistical differences (p>0.05). The AUC values for distinguishing high-grade adenocarcinoma from low-grade adenocarcinoma were 0.645 for ADC and 0.627 for T2CR. Combining T2CR, ADC, sex, and maximum diameter resulted in an AUC of 0.778, sensitivity of 70%, and specificity of 75%. This combination significantly improved diagnostic efficiency compared to T2CR and ADC alone (p=0.008, z = 2.624; p=0.007, z = 2.679).

CONCLUSION

The MRI quantitative parameters are useful for distinguishing the pathological grades of solid lung adenocarcinoma, offering valuable insights for precise lung cancer treatment.

Association between overnight repetitive respiratory events and the accumulation of genioglossus fatigue in male patients with severe obstructive sleep apnea

PURPOSE

To evaluate the correlation between median frequency (MF) as a measure of genioglossus (GG) fatigue and overnight repetitive respiratory events in male patients with severe obstructive sleep apnea (OSA).

METHODS

GG electromyography (EMG) data were collected synchronously with polysomnography (PSG). Overnight respiratory events were divided based on whether they occurred during the first or second halves of the total number of overnight respiratory events, and differences in MF in the respiratory phase were compared in the same segments. Events were then sampled in pairs to compare MF. The correlation between MF and the order of respiratory events, as well as interindividual differences, were analyzed.

RESULTS

Twenty-two male patients were enrolled in this study and 2210 respiratory events were recorded. Before and during respiratory events, MF decreased significantly in the second half, especially during the inspiratory phase (segments 1-4: P = 0.014, P < 0.001, P < 0.001, P < 0.001, respectively). This trend was observed in non-rapid eye movement sleep and lateral position, but not in rapid eye movement sleep or the supine position, and remained after pairing for duration, stage, and position. MF correlated negatively with the order of respiratory events during the inspiratory phase. The trend of decrease in MF only existed in patients with apnea-hypopnea index > 30 events/h.

CONCLUSION

Overnight repetitive respiratory events were associated with increased GG fatigue, influenced by sleep stage and body position in male patients with severe OSA. GG fatigue depends on the order and frequency of respiratory events.

Associations Between Sleep Spindle Metrics, Age, Education and Executive Function in Young Adult and Middle-Aged Patients with Obstructive Sleep Apnea

Purpose

This study aimed to investigate the association between sleep spindle metrics and executive function in individuals with obstructive sleep apnea (OSA). Furthermore, we examined the association of age and education on executive function.

Patients and Methods

A total of 230 (40.90 ± 8.83 years, F/M = 45/185) participants were enrolled. Overnight electroencephalogram (C3-M2) recording detected sleep spindles by a novel U-Net-type neural network that integrates temporal information with time-frequency images. Sleep spindle metrics, including frequency (Hz), overall density (events/min), fast density (events/min), slow density (events/min), duration (sec) and amplitude (µV), were measured. Executive function was assessed using standardized neuropsychological tests. Associations between sleep spindle metrics, executive function, and demographic factors were analyzed using multivariate linear regression.

Results

In fully adjusted linear regression models, higher overall sleep spindle density (TMT-A, B=-1.279, p=0.009; TMT-B, B=-1.813, p=0.008), fast sleep spindle density (TMT-A, B=-1.542, p=0.048; TMT-B, B=-2.187, p=0.036) and slow sleep spindle density (TMT-A, B=-1.731, p=0.037; TMT-B, B=-2.449, p=0.034) were associated with better executive function. And the sleep spindle duration both during N2 sleep time (TMT-A, B=-13.932, p=0.027; TMT-B, B=-19.001, p=0.034) and N3 sleep time (TMT-B, B=-29.916, p=0.009; Stroop-incongruous, B=-21.303, p=0.035) was independently associated with better executive function in this population. Additionally, age and education were found to be highly associated with executive function.

Conclusion

Specific sleep spindle metrics, higher overall density, fast density and slow density during N2 sleep time, and longer duration during N2 and N3 sleep time, are independent and sensitive indicators of better executive function in young adult and middle-aged patients with OSA. Further research is needed to explore the underlying mechanisms and clinical implications of these findings.

Automatic prediction of obstructive sleep apnea event using deep learning algorithm based on ECG and thoracic movement signals

BACKGROUND

Obstructive sleep apnea (OSA) is a sleeping disorder that can cause multiple complications.

AIMS/OBJECTIVE

Our aim is to build an automatic deep learning model for OSA event detection using combined signals from the electrocardiogram (ECG) and thoracic movement signals.

MATERIALS AND METHODS

We retrospectively obtained 420 cases of PSG data and extracted the signals of ECG, as well as the thoracic movement signal. A deep learning algorithm named ResNeSt34 was used to construct the model using ECG with or without thoracic movement signal. The model performance was assessed by parameters such as accuracy, precision, recall, F1-score, receiver operating characteristic (ROC), and area under the ROC curve (AUC).

RESULTS

The model using combined signals of ECG and thoracic movement signal performed much better than the model using ECG alone. The former had accuracy, precision, recall, F1-score, and AUC values of 89.0%, 88.8%, 89.0%, 88.2%, and 92.9%, respectively, while the latter had values of 84.1%, 83.1%, 84.1%, 83.3%, and 82.8%, respectively.

CONCLUSIONS AND SIGNIFICANCE

The automatic OSA event detection model using combined signals of ECG and thoracic movement signal with the ResNeSt34 algorithm is reliable and can be used for OSA screening.

Sleep medicine in China: current clinical practice

The modern practice of sleep medicine in China was introduced in the 1980s and has undergone significant development over the past few decades. The field has witnessed an increase in sleep laboratories, the publication of guidelines for the diagnosis and treatment of sleep disorders, and the establishment of several sleep medicine associations. Despite these achievements, there is still much to be done in this field. By utilizing original national survey data, this study comprehensively discusses the current practice of sleep medicine in China, including sleep medicine training, diagnostic capacity, multidisciplinary care, clinical competence and standardization, sleep telemedicine, barriers to the practice of sleep medicine, and costs of sleep medicine. It is imperative for the Chinese health care authorities to enhance their attention and investment in the field of sleep medicine. Urgent implementation of standardized training programs and accreditation systems is necessary to promote the diagnosis and treatment of sleep disorders in China.

CITATION

Xu S, Li Y, Ye J, Han D. Sleep medicine in China: current clinical practice. J Clin Sleep Med. 2023;19(12):2125-2131.

Facial Contour Features Measured on CT Reflects Upper Airway Morphology in Patients With OSA

OBJECTIVE

To determine facial contour features, measured on computed tomography (CT), related to upper airway morphology in patients with obstructive sleep apnea (OSA); certain phenotype of facial abnormalities implying restriction of craniofacial skeleton and adipose tissue nimiety has predicted the value of the severity of OSA.

MATERIALS AND METHOD

Sixty-four male patients with OSA [apnea-hypopnea index (AHI) ≥10/h] who had upper airway CT were randomly selected to quantitatively measure indicators of facial contour and upper airway structures. Pearson correlation analyses were performed. Partial correlation procedure was used to examine correlations while controlling body mass index (BMI).

RESULTS

Upper airway anatomy can nearly all be reflected in the face, except retroglossal airway. Upper face width can be measured to assess the overall skeletal structures of the airway. Lower face width can be used to represent how much adipose tissue deposited. Hard palate, retropalatal, and hypopharyngeal airways have corresponding face indicators respectively. Midface width is a better predictor of AHI severity and minimum blood oxygen even than neck circumference because it contains the most anatomical information about the airway, including RP airway condition, soft palate length, tongue volume, etc. These correlations persisted even after correction for BMI.

CONCLUSIONS

All anatomical features of the upper airway except retroglossal airway can be reflected in the face, and midface width is the best predictor of AHI severity and minimum blood oxygen, even better than neck circumference and BMI.

Value of Opening the Middle Meatus in Patients With Nasal Airway Obstruction

OBJECTIVES

While surgeries to correct the anatomical malformations that cause nasal airway obstruction (NAO) are generally successful, the outcomes of such procedures are often unsatisfactory. The aim of the present study was to assess the value of opening the middle meatus in patients with NAO.

METHODS

Thirty-four patients with nasal obstruction due to nasal septal deviation were included in this study. After randomization, the middle meatus was either opened or not opened during septoplasty. The patients were evaluated through pre- and postoperative rhinomanometry and acoustic rhinometry. The Visual Analog Scale (VAS) scores of subjective symptoms along with responses to the 20-item Sinonasal Outcome Test (SNOT-20) were obtained before surgery and three months after surgery.

RESULTS

The VAS scores and SNOT-20 responses improved significantly in both groups after surgery. The effective treatment rate based on the nasal congestion score (NCS) was 64.7% in the single group (septoplasty alone) and 100% in the combined group (septoplasty in conjunction with opening the middle meatus), and the difference was statistically significant (P = .018). In both groups, surgery significantly improved nasal flow, resistance, minimal cross-sectional area, cross-sectional area 6 cm (CA6) from the anterior nostril and nasal volume. Nasal volume and CA6 after surgery were statistically different between the 2 groups (P = .004 and .019, respectively).

CONCLUSIONS

Opening the middle meatus may further improve the subjective perception of patency on the basis of septoplasty.

Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study

BACKGROUND

s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure.

METHODS

We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness.

RESULTS

At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5).

CONCLUSIONS

We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.

[Expert consensus on the biobank development of oral genetic diseases and rare diseases and storage codes of related biological samples from craniofacial and oral region]

The biological samples of oral genetic diseases and rare diseases are extremely precious. Collecting and preserving these biological samples are helpful to elucidate the mechanisms and improve the level of diagnose and treatment of oral genetic diseases and rare diseases. The standardized construction of biobanks for oral genetic diseases and rare diseases is important for achieving these goals. At present, there is very little information on the construction of these biobanks, and the standards or suggestions for the classification and coding of biological samples from oral and maxillofacial sources, and this is not conducive to the standardization and information construction of biobanks for special oral diseases. This consensus summarizes the background, necessity, principles, and key points of constructing the biobank for oral genetic diseases and rare diseases. On the base of the group standard "Classification and Coding for Human Biomaterial" (GB/T 39768-2021) issued by the National Technical Committee for Standardization of Biological Samples, we suggest 76 new coding numbers for different of biological samples from oral and maxillofacial sources. We hope the consensus may promote the standardization, and smartization on the biobank construction as well as the overall research level of oral genetic diseases and rare diseases in China.

[Measurement and analysis of the crown conical degree of maxillary incisors in patients with congenital tooth agenesis caused by different gene mutations]

Objective: To measure the crown conical degree of the remaining maxillary incisors in patients with congenital tooth agenesis, and to analyze the influence of different gene mutations on the crown conical degree of patients. Methods: Whole exome sequencing was performed on 85 patients with congenital tooth agenesis (50 males, 35 females, median age 19 years old) who visited the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2019 to January 2023. The pathogenic gene was identified. The width of the crowns of the maxillary central and lateral incisors at the incisal 1/3 and gingival 1/3 were measured on the panoramic radiograph, and the ratio was defined as the crown conical degree. The smaller the ratio is, the more likely is the crown to be peg shaped teeth. The control group was matched by age and gender with 85 other patients with intact maxillary permanent incisors who were treated in the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2019 to January 2023. The conical degree of the tooth agenesis group was compared with the control group by t-test, and the differences in the crown conical degree in different gene mutation groups were compared using one-way analysis of variance, and the multiple comparisons among gene groups were carried out using the LSD method. Results: Among the 85 tooth agenesis patients, the numbers of patients in each gene mutation group were 20 in ectodysplasin A (EDA) group, 8 in ectodysplasin A receptor (EDAR) group, 15 in wingless-type MMTV integration site family, member 10A (WNT10A) group, 16 in paired box 9 (PAX9) group, 10 in Msh homeobox 1 (MSX1) group, 10 in low-density lipoprotein receptor related protein 6 (LRP6) group, and 6 in bone morphogenetic protein4 (BMP4) group. The number of missing teeth were 1-27, median number 15 among the tooth agenesis patients. There was no significant difference in the conical degree between the left and right homonymous teeth in the congenital tooth agenesis group and the control group (P>0.05). The crown conical degree of maxillary central incisor and lateral incisor in the congenital missing teeth group (0.95±0.24, 0.90±0.22) was significantly smaller than that in the control group (1.12±0.09, 1.13±0.09) (t=-8.50, P<0.001; t=-11.47, P<0.001). In WNT10A mutants, the conical degree of lateral incisors (0.89±0.18) was less than that of central incisors (1.07±0.15)(t=3.68, P<0.001). The conical degree of central incisors and lateral incisors (0.70±0.23, 0.57±0.15) of EDA mutants was significantly lower than that in patients with other gene mutations (P>0.05). Conclusions: Compared with the normal control group, the remaining maxillary central and lateral incisors of the seven gene mutation groups of patients with congenital tooth agenesis all had different degrees of conical crown. Among them, the crown conical degree of maxillary central and lateral incisors of the EDA mutation was the most severe, and the WNT10A mutation affected the maxillary lateral incisors more specifically.

Evaluation of obstructive sleep apnea: an analysis based on aberrant genes

BACKGROUND

Obstructive sleep apnea (OSA) is an upstream disorder that frequently causes multisystem disorders. Much research has revealed the pathogenesis of OSA, but there is still a lack of research on the complications caused by OSA.

METHODS

The mRNA expression and methylation dataset based on peripheral blood mononuclear cells (PBMCs) were downloaded from the Gene Expression Omnibus (GEO) database. All differential expressed genes (DEGs) were ranked using the Robust Rank Aggregation (RRA) algorithm. A weighted gene co-expression network analysis (WGCNA) was constructed. Subsequently, we used immune infiltration, enrichment analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis for apnea and hypopnea index (AHI) and hypertension and excessive daytime sleepiness (EDS) and constructed diagnostic model using random forest algorithm.

RESULTS

In the present study, we identified 318 DEGs in PBMCs involved in pathogenesis or continuous positive airway pressure (CPAP) therapy. Pathway enrichment identified DEGs associated with protein regulation and metabolism. Notably, through intra group analysis, we found that the immune disorder was more significant for OSA in males, non-daytime sleepy, or non-hypertensive OSA. The area under the ROC curve of model for EDS prediction is 0.889 and 0.852 for hypertension. Notably, we found that the diagnostic model had a high linear predictive value for AHI.

CONCLUSIONS

Our results indicate that PBMCs are a significant component of alterations in OSA and are expected to explain the mechanism of multisystem diseases caused by OSA. The present study provides new insights for symptom evaluation, classification and treatment of OSA from the molecular level.

[Development and validation of prognostic nomogram for malignant pleural mesothelioma]

Objective: To development the prognostic nomogram for malignant pleural mesothelioma (MPM). Methods: Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People's Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training (n=112) and test (n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model's discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results: The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence (HR=2.127, 95% CI: 1.154-3.920), serum albumin (HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy (HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training (P=0.001) and test (P=0.003) sets. Conclusion: The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.

Optimized concurrent hearing and genetic screening in Beijing, China: A cross-sectional study

Concurrent screening has been proven to provide a comprehensive approach for management of congenital deafness and prevention of ototoxicity. The SLC26A4 gene is associated with late-onset hearing loss and is of great clinical concern. For much earlier detection of newborns with deafness-causing mutations in the SLC26A4 gene, the Beijing Municipal Government launched a chip for optimized genetic screening of 15 variants of 4 genes causing deafness based on a chip to screen for 9 variants of 4 genes, and 6 variants of the SLC26A4 gene have now been added. To ascertain the advantage of a screening chip including 15 variants of 4 genes, the trends in concurrent hearing and genetic screening were analyzed in 2019 and 2020. Subjects were 76,460 newborns who underwent concurrent hearing and genetic screening at 24 maternal and child care centers in Beijing from January 2019 to December 2020. Hearing screening was conducted using transiently evoked otoacoustic emissions (TEOAEs), distortion product otoacoustic emissions (DPOAE), or the automated auditory brainstem response (AABR). Dried blood spots were collected for genetic testing and 15 variants of 4 genes, namely GJB2, SLC26A4, mtDNA 12S rRNA, and GJB3, were screened for using a DNA microarray platform. The initial referral rate for hearing screening decreased from 3.60% (1,502/41,690) in 2019 to 3.23% (1,124/34,770) in 2020, and the total referral rate for hearing screening dropped form 0.57% (236/41,690) in 2019 to 0.54% (187/34,770) in 2020, indicating the reduced false positive rate of newborn hearing screening and policies to prevent hearing loss conducted by the Beijing Municipal Government have had a significant effect. Positivity according to genetic screening was similar in 2019 (4.970%, 2,072/41,690) and 2020 (4.863%,1,691/34,770), and the most frequent mutant alleles were c.235 del C in the GJB2 gene, followed by c.919-2 A > G in the SLC26A4 gene, and c.299 del AT in the GJB2 gene. In this cohort study, 71.43% (5/7) of newborns with 2 variants of the SLC26A4 gene were screened for newly added mutations, and 28.57% (2/7) of newborns with 2 variants of the SLC26A4 gene passed hearing screening, suggesting that a screening chip including 15 variants of 4 genes was superior at early detection of hearing loss, and especially in early identification of newborns with deafness-causing mutations in the SLC26A4 gene. These findings have clinical significance.

Analysis of nasal resistance regulation mechanism during postural changes in patients with obstructive sleep apnea by measuring heart rate variability

STUDY OBJECTIVES

Changes in nasal resistance (NR) during postural changes are influenced by venous filling pressure and autonomic nervous system mediation, and heart rate variability (HRV) can reflect changes in the autonomic nervous system. This study aimed to explore the regulatory mechanisms of NR in patients with obstructive sleep apnea (OSA) during postural changes.

METHODS

Healthy controls (apnea-hypopnea index < 5 events/h) and patients with OSA were recruited. NR and electrocardiogram data were collected in sitting, supine, left-lateral, and right-lateral postures. HRV parameters were obtained by analyzing the electrocardiogram data from each posture. Subgroups were divided according to sitting-supine NR changes, and HRV parameters were compared between different postures and groups/subgroups.

RESULTS

In total, 34 healthy controls and 39 patients with OSA (mean apnea-hypopnea index 34.34 ± 22.44 events/h) were recruited. During sitting-supine postural changes, the NR increased in the control group but did not change significantly in the OSA group. None of the autonomic nervous system-related HRV parameters changed significantly. After the groups were divided into NR-elevated and NR-unchanged subgroups, sympathetic activity-related HRV parameters were higher in the NR-unchanged subgroup but only statistically significant in the OSA group. When comparing the left and right postures, there was no significant change in NR; however, the OSA group had lower parasympathetic activity-related HRV parameters when in the right posture.

CONCLUSIONS

During postural changes from the sitting to supine positions, the total NR increases, and this increment is smaller in patients with OSA. This is likely due to overregulation of sympathetic activity, which may occur in patients with OSA.

CITATION

Shi Y, Lou H, Wang H, et al. Analysis of nasal resistance regulation mechanism during postural changes in obstructive sleep apnea patients by measuring heart rate variability. J Clin Sleep Med. 2023;19(4):643-650.

Prediction of obstructive sleep apnea using deep learning in 3D craniofacial reconstruction

Background

Obstructive sleep apnea (OSA) is a common sleep disorder. However, current diagnostic methods are labor-intensive and require professionally trained personnel. We aimed to develop a deep learning model using upper airway computed tomography (CT) to predict OSA and to warn the medical technician if a patient has OSA while the patient is undergoing any head and neck CT scan, even for other diseases.

Methods

A total of 219 patients with OSA [apnea-hypopnea index (AHI) ≥10/h] and 81 controls (AHI <10/h) were enrolled. We reconstructed each patient's CT into 3 types (skeletal structures, external skin structures, and airway structures) and captured reconstructed models in 6 directions (front, back, top, bottom, left profile, and right profile). The 6 images from each patient were imported into the ResNet-18 network to extract features and output the probability of OSA using two fusion methods: Add and Concat. Five-fold cross-validation was used to reduce bias. Finally, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated.

Results

All 18 views with Add as the feature fusion performed better than did the other reconstruction and fusion methods. This gave the best performance for this prediction method with an AUC of 0.882.

Conclusions

We present a model for predicting OSA using upper airway CT and deep learning. The model has satisfactory performance and enables CT to accurately identify patients with moderate to severe OSA.

Causal associations between obstructive sleep apnea and COVID-19: A bidirectional Mendelian randomization study

BACKGROUNDS

The COVID-19 pandemic has caused significant impact on human health. Whether obstructive sleep apnea (OSA) increases the risk of COVID-19 remains unclear. We sought to clarify this issue using two-sample Mendelian randomization (TSMR) analysis in large cohorts.

METHODS

Bidirectional two-sample Mendelian randomization (MR) was used to evaluate the potential causality between OSA and COVID-19 by selecting single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) from genome-wide association studies (GWAS). The inverse-variance weighted (IVW) method was selected as the main approach for data analysis to estimate the possible causal effects. Alternative methods such as MR-Egger, the MR pleiotropy residual sum and outlier (MR-PRESSO), and leave-one-out analysis methods were implemented as sensitivity analysis approaches to ensure the robustness of the results.

RESULTS

All forward MR analyses consistently indicated the absence of a causal relationship between OSA and any COVID-19 phenotype. In the reverse MR analysis, the IVW mode demonstrated that severe respiratory confirmed COVID-19 was correlated with a 4.9% higher risk of OSA (OR, 1.049; 95%CI, 1.018-1.081; P = 0.002), consistent in MR-PRESSO (OR = 1.049, 95%CI 1.018-1.081, P = 0.004), weighted median (OR = 1.048, 95%CI 1.003-1.095, P = 0.035), and MR-Egger (OR = 1.083, 95%CI 1.012-1.190, P = 0.041) methods.

CONCLUSIONS

There is no significant evidence supporting a causal association between OSA and any COVID phenotype, while we identified potential evidence for a causal effect of severe COVID-19 on an increased risk of OSA.

Clinical Characteristics Combined with Craniofacial Photographic Analysis in Children with Obstructive Sleep Apnea

Purpose

Distinguishing obstructive sleep apnea (OSA) in a high-risk population remains challenging. This study aimed to investigate clinical features to identify children with OSA combined with craniofacial photographic analysis.

Methods

One hundred and forty-five children (30 controls, 62 with primary snoring, and 53 with OSA) were included. Differences in general demographic characteristics and surface facial morphology among the groups were compared. Risk factors and prediction models for determining the presence of OSA (obstructive sleep apnea-hypopnea index>1) were developed using logistic regression analysis.

Results

The BMI (z-score), tonsil hypertrophy, and lower face width (adjusted age, gender, and BMI z-score) were showed significantly different in children with OSA compared with primary snoring and controls (adjusted p<0.05). The screening model based on clinical features and photography measurements correctly classified 79.3% of the children with 64.2% sensitivity and 89.1% specificity. The area under the curve of the model was 81.0 (95% CI, 73.5-98.4%).

Conclusion

A screening model based on clinical features and photography measurements would be helpful in clinical decision-making for children with highly suspected OSA if polysomnography remains inaccessible in resource-stretched healthcare systems.

Selection of OSA-specific pronunciations and assessment of disease severity assisted by machine learning

STUDY OBJECTIVES

To screen all of the obstructive sleep apnea (OSA)-characteristic pronunciations, explore the pronunciations which provide a better OSA classification effect than those used previously, and further clarify the correlation between speech signals and OSA.

METHODS

A total of 158 adult male Mandarin native speakers who completed polysomnography at the Sleep Medicine Center of Beijing Tongren Hospital from November 15, 2019, to January 19, 2020, were enrolled in this study. All Chinese syllables were collected from each participant in the sitting position. The syllables, vowels, consonants, and tones were screened to identify the pronunciations that were most effective for OSA classification.

RESULTS

The linear prediction coefficients of Chinese syllables were extracted as features and mathematically modeled using a decision tree model to dichotomize participants with apnea-hypopnea index thresholds of 10 and 30 events/h, and the leave-one-out method was used to verify the classification performance of Chinese syllables for OSA. Chinese syllables such as [leng] and [jue], consonant pronunciations such as [zh] and [f], and vowel pronunciations such as [ing] and [ai] were the most suitable pronunciations for classification of OSA. An OSA classification model consisting of several syllable combinations was constructed, with areas under curve of 0.83 (threshold of apnea-hypopnea index = 10) and 0.87 (threshold of apnea-hypopnea index = 30), respectively.

CONCLUSIONS

This study is the first comprehensive screening of OSA-characteristic pronunciations and can act as a guideline for the construction of OSA speech corpora in other languages.

CITATION

Ding Y, Sun Y, Li Y, et al. Selection of OSA-specific pronunciations and assessment of disease severity assisted by machine learning. J Clin Sleep Med. 2022;18(11):2663-2672.

[Sero-epidemiological characteristics of the hepatitis D virus infection among hepatitis B virus infected-patients at a single center in Xinjiang region]

Objective: To investigate the sero-epidemiological characteristics of the hepatitis D virus (HDV) infection among hepatitis B virus (HBV)-infected patients in Xinjiang region. Methods: A single-center cross-sectional analysis method was used to select 264 cases of hepatitis B virus infection who were hospitalized in the Center for Infectious Diseases and Liver Diseases of the First Affiliated Hospital of Xinjiang Medical University from August 2021 to January 2022. All patients were tested for HDV Ag, HDV IgM, HDV IgG, and HDV RNA. The infection status of hepatitis D virus was analyzed by grouping according to their clinical type, HBV viral load, and HBsAg level. A paired t-test was used for data with measurement data conforming to normal distribution. A paired rank sum test was used for data that did not conform to normal distribution before and after treatment. Results: A total of 36 cases (13.64%) and 26 cases (9.85%) were positive for HDV serological markers and HDV RNA. According to clinical type grouping, the positive rates of HDV serum markers in patients with chronic hepatitis B, hepatitis B-related cirrhosis, liver cancer, and liver failure were 13.46%, 12.43%, and 20.83%, respectively, and there was no statistically significant difference among the three groups (χ²=0.86, P=0.649). The positive rates of HDV RNA were 11.54%, 8.11%, and 20.83%, respectively, and there was no statistically significant difference among the three groups (χ²=4.015, P=0.134). According to HBV viral load grouping, the positive rates of HDV serum markers among patients with viral loads <20, 20-2 000, and >2 000 IU/ml were 17.15%, 7.81%, and 6.67%, respectively, and the difference was not statistically significant among the three groups (χ²=4.846, P=0.089). The positive rates of HDV RNA were 9.47%, 10.94%, and 10%, respectively, and the difference was not statistically significant among the three groups (χ²=0.113, P=0.945). According to HBsAg level grouping, the positive rates of HDV serum markers in HBsAg<0.05, 0.05~250, and >250 IU/ml were 14.29%, 16.67%, and 10.85%, respectively, and there was no statistically significance between the three groups (χ²=1.745, P=0.418). The positive rates of HDV RNA were 4.76%, 8.77%, and 11.63%, respectively, and there was no statistically significant difference among the three groups (χ²=1.221, P=0.543). Clinical outcome, disease course, HBV DNA, serological markers of viral hepatitis, routine blood test, biochemical indicators, coagulation function, and other laboratory indicators were compared between HDV serum marker and/or nucleic acid positive and negative patients, and there was no statistically significant difference (P>0.05). Conclusion: The positive rate of HDV serological markers and HDV RNA is 13.64% and 9.85%, respectively, at a single center in the Xinjiang region, and there is still a high HDV infection rate among the HBV-infected patients with low levels of viral load and HBsAg.

Classification of facial phenotypes in Asian patients with obstructive sleep apnea

BACKGROUD

The facial phenotypes of Asian obstructive sleep apnea (OSA) patients remain unclear.

OBJECTIVES

(1) To describe the facial features of OSA patients. (2) To develop a model based on facial contour indicators to predict OSA. (3) To classify the facial phenotypes of Asian OSA patients.

MATERIALS AND METHODS

110 patients with OSA (apnea-hypopnea index [AHI] ≥ 10/h) and 50 controls (AHI< 10/h) were selected to measure facial contour indicators. Indicators were compared between OSA patients and the control group. We used multivariable linear regression analysis to predict OSA severity and K-means cluster analysis to classify OSA patients into different phenotypes.

RESULTS

We built a model to predict OSA which explained 49.1% of its variance and classified OSA patients into four categories. Cluster 1 (Skeletal type) had the narrowest facial width indicators with narrowing of the retroglossal airway. Cluster 2 (Obese type) had the widest face, and narrowest hard palate, retropalatal, and hypopharyngeal airways. Cluster 3 (Nose type) had the narrowest nasal cavity. Cluster 4 (Long type) had the longest airway length.

CONCLUSIONS AND SIGNIFICANCE

Patients with OSA were classified into four categories, each of which identified different anatomic risk factors that can be used to select the treatment.

MRI-based radiomics analysis in differentiating solid non-small-cell from small-cell lung carcinoma: a pilot study

AIM

To investigate the ability of a T2-weighted (W) magnetic resonance imaging (MRI)-based radiomics signature to differentiate solid non-small-cell lung carcinoma (NSCLC) from small-cell lung carcinoma (SCLC).

MATERIALS AND METHODS

The present retrospective study enrolled 152 eligible patients (NSCLC = 125, SCLC = 27). All patients underwent MRI using a 3 T scanner and radiomics features were extracted from T2W MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression model was used to identify the optimal radiomics features for the construction of a radiomics model to differentiate solid NSCLC from SCLC. Threefold cross validation repeated 10 times was used for model training and evaluation. The conventional MRI morphology features of the lesions were also evaluated. The performance of the conventional MRI morphological features, and the radiomics signature model and nomogram model (combining radiomics signature with conventional MRI morphological features) was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Five optimal features were chosen to build a radiomics signature. There was no significant difference in age, gender, and the largest diameter. The radiomics signature and conventional MRI morphological features (only pleural indentation and lymph node enlargement) were independent predictive factors for differentiating solid NSCLC from SCLC. The area under the ROC curves (AUCs) for MRI morphological features, and the radiomics model, and nomogram model was 0.69, 0.85, and 0.90 (ROC), respectively.

CONCLUSIONS

The T2W MRI-based radiomics signature is a potential non-invasive approach for distinguishing solid NSCLC from SCLC.

User acceptance of wearable intelligent medical devices through a modified unified theory of acceptance and use of technology

Background

The acceptance of wearable intelligent medical devices and the factors influencing behavioral intention to use them have been scarcely studied. This study aimed to increase the current understanding of wearable intelligent medical devices and investigate the factors influencing their acceptance.

Methods

Integrating the unified theory of acceptance and use of technology and the theory of perceived risk, and based on the features of wearable intelligent medical devices, we proposed a modified unified theory of acceptance and use of technology model to identify factors influencing the acceptance of these devices. Using data collected from 2,192 respondents in China from an online survey, we used structural equation modeling to test the measurement and structural models.

Results

The findings suggested that facilitating conditions (path coefficient =0.942, P<0.001) were critical to the use of wearable intelligent medical devices. Behavioral intention significantly mediated the effects of perceived risk, perceived cost, health expectation, perceived ease of use, and social influence on user behavior (path coefficient =0.210, P<0.001). Health expectation (path coefficient =0.860, P<0.001), perceived ease of use (path coefficient =0.289, P<0.001), and social influence (path coefficient =0.153, P<0.001) were found to play essential roles in predicting behavioral intention. Perceived cost (path coefficient =0.034, P<0.05) and perceived risk (path coefficient =−0.031, P<0.05) had no significant effect on behavioral intention. People with underlying diseases had lower health expectations and perceived costs.

Conclusions

The modified unified theory of acceptance and use of technology model in our research is a reliable model to evaluate the user acceptance of wearable intelligent medical devices.

Differential expression profile of plasma exosomal microRNAs in chronic rhinosinusitis with nasal polyps

Exosomes mediate inflammation and immune responses. The aim of the study was to examine the expression profiles of plasma exosomal microRNAs (miRNAs) and analyze their target gene functions in participants with chronic rhinosinusitis with nasal polyps (CRSwNP). We measured plasma exosomal miRNAs in five patients with CRSwNP and five controls. Transcripts per million (TPM) was used to assess miRNAs expression and the Benjamini-Hochberg procedure was employed for multiple comparisons correction. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) analyses revealed biological annotation and functional prediction of target genes. Compared with controls, we found that 159 exosomal miRNAs were differentially expressed by miRNA sequencing in CRSwNP. The top three upregulated miRNAs were novel_miR_677, novel_miR_1037, and novel_miR_79, while the top three downregulated miRNAs were novel_miR_192, novel_miR_1022, and novel_miR_4. The target functions in the GO and KEGG analyses included axon guidance, extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, the calcium, the Hippo, the Notch, the ErbB, the cAMP signaling pathway, and focal adhesion. This study describes the dissection of plasma exosomal miRNA profiling in CRSwNP. Our findings may provide a certain basis for further mechanism research and exploration of diagnostic values.

Using clinical data to predict obstructive sleep apnea

Background

Methods

Results

Conclusions

Evaluation of the clinical efficacy of nasal surgery in the treatment of obstructive sleep apnoea

STUDY OBJECTIVES

The aim of the study was to evaluate the clinical efficacy of nasal surgery in the treatment of obstructive sleep apnoea (OSA) by comparing the improvement of subjective symptoms and objective metrics before surgery and after 6 months of surgery.

METHODS

Patients with the main complaint of nasal congestion combined with habitual snoring who were hospitalized and treated were selected. Patients underwent subjective symptom tests and objective indicator monitoring both before surgery and 6 months after surgery. Comparisons between groups were performed using the independent samples t-test.

RESULTS

Subjective scale evaluations demonstrated that nasal congestion, daytime sleepiness, snoring, nose-related symptoms, and sleep symptoms in patients with simple snoring or with OSA were improved after nasal surgery. Additionally, vitality was improved in all groups except for the patients with simple snoring and emotional consequence was improved in patients with simple snoring and mild OSA. Objective evaluations indicated the apnoea-hypopnoea index (AHI), the thickness of the soft palate, and the maximum cross-sectional area of the sagittal plane of the soft palate decreased after surgery in patients with mild OSA. The lowest blood oxygen concentration (LSaO₂) and anteroposterior diameter of the soft palate increased after surgery in patients with mild OSA. The arousal index also significantly decreased in patients with mild and moderate OSA. The nasal cavity volumes (NCVs) and the nasal minimal cross-sectional areas (NMCAs) of all groups showed significant differences after surgery.

CONCLUSIONS

Nasal surgery can effectively improve nose and sleep symptoms in patients with simple snoring or with OSA. It can significantly reduce the nasal resistance and increase the ventilation volume.

STATEMENT OF SIGNIFICANCE

Obstructive sleep apnoea (OSA) is becoming a global health problem. OSA is associated with several coexisting conditions, reduced health-related quality of life, and impaired work productivity. This study performed nasal surgery on OSA patients with the main complaint of nasal congestion combined with snoring and patients with simple snoring to compare the improvement of subjective symptoms and objective metrics before and after surgery. We found that: (1) symptoms such as nasal congestion, daytime sleepiness or snoring were improved after nasal surgery; (2) the apnoea-hypopnoea index (AHI) and arousal index decreased after surgery in patients with OSA; (3) the nasal and oropharyngeal cavity volumes increased after surgery. These findings suggest that patients with OSA or with simple snoring could benefit from nasal surgery.

Obstructive Sleep Apnea Detection Based on Sleep Sounds via Deep Learning

PURPOSE

This study aimed to propose a novel deep-learning method for automatic sleep apneic event detection and thus to estimate the apnea hypopnea index (AHI) and identify obstructive sleep apnea (OSA) in an event-by-event manner solely based on sleep sounds obtained by a noncontact audio recorder.

METHODS

We conducted a cross-sectional study of participants with habitual snoring or heavy breathing sounds during sleep to train and test a deep convolutional neural network named OSAnet for the detection of OSA based on sleep sounds. Polysomnography (PSG) was conducted, and sleep sounds were recorded simultaneously in a regular room without noise attenuation. The study was conducted in two phases. In phase one, eligible participants were enrolled and randomly allocated into training and validation groups for deep learning algorithm development. In phase two, eligible patients were enrolled in a test group for algorithm assessment. Sensitivity, specificity, accuracy, unweighted Cohen kappa coefficient (κ) and the area under the curve (AUC) were calculated using PSG as the reference standard.

RESULTS

A total of 135 participants were randomly divided into a training group (n, 116) and a validation group (n, 19). An independent test group of 59 participants was subsequently enrolled. Our algorithm achieved a precision of 0.81 and sensitivity of 0.78 in the test group for overall sleep event detection. The algorithm exhibited robust diagnostic performance to identify severe cases with a sensitivity of 95.6% and specificity of 91.6%.

CONCLUSION

Our results showed that a deep learning algorithm based on sleep sounds recorded by a noncontact voice recorder served as a feasible tool for apneic event detection and OSA identification. This technique may hold promise for OSA assessment in the community in a relatively comfortable and low-cost manner. Further studies to develop a tool based on a home-based setting are warranted.

Clinical outcomes of keratinized mucosa augmentation in jaws reconstructed with fibula or iliac bone flaps

This prospective study was undertaken to evaluate the treatment outcomes of keratinized mucosa augmentation (KMA) on the buccal and palatal/lingual sides of implants in jaws reconstructed after oncological surgery. Forty-two implants in 12 patients whose jaws had been reconstructed with a fibula or iliac bone flap were included. KMA was performed at 3 months after implant placement; this included an apically displaced partial-thickness flap and a free gingival graft (FGG) around the implants to increase the keratinized mucosa width (KMW). Patients were followed up for at least 6 months post-surgery. KMW, shrinkage, and patient pain and discomfort measured on a visual analogue scale were analysed. A histological analysis was performed of tissue epithelium from two patients. The results showed that KMW was >2 mm on both the buccal and palatal/lingual sides during follow-up. Before surgery, histological analysis showed epithelium with no epithelial spikes; normal keratinized epithelial spikes were observed at 8 weeks after KMA. Greater KMW was observed around implants in reconstructed maxillae than around those in reconstructed mandibles (P < 0.001). Patients felt more pain at the donor site than at the recipient site during the first 3 days post-surgery. KMA with FGG was predictable in reconstructed jaws and may help maintain the long-term stability of implants.

LINC00174 triggers the malignant development of breast cancer by negatively regulating miR-1827 level

OBJECTIVE

Long non-coding RNAs (lncRNAs) are extensively involved in tumor development. In-depth researches on cancer-associated lncRNAs provide a theoretical basis for developing prognostic hallmarks and individualized therapeutic targets in breast cancer (BCa). This study aims to detect expression characteristics of LINC00174 in BCa and its biological role in regulating BCa cell phenotypes.

PATIENTS AND METHODS

LINC00174 levels in BCa and adjacent normal tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The influence of LINC00174 on pathological indicators of BCa was analyzed. In MCF-7 and MDA-MB-231 cells with LINC00174 knockdown, proliferative and migratory abilities were examined by cell counting kit-8 (CCK-8), colony formation and transwell assay, respectively. At last, molecular mechanisms of LINC00174 and its downstream gene miR-1827 in regulating BCa development were explored by Luciferase assay and rescue experiments.

RESULTS

LINC00174 was upregulated in BCa tissues than adjacent normal ones. High level of LINC00174 predicted advanced tumor staging, high metastasis rate and poor prognosis in BCa. Knockdown of LINC00174 attenuated proliferative and migratory abilities in BCa cells. MiR-1827 was the target gene binding LINC00174, showing a negative correlation between each other. Silence of miR-1827 abolished the regulatory effects of LINC00174 on proliferative and migratory abilities in BCa cells.

CONCLUSIONS

LINC00174 is upregulated in BCa samples. It is closely linked to tumor staging, metastasis and prognosis in BCa. By negatively regulating miR-1827 level, LINC00174 aggravates the malignant development of BCa.

Machine learning from quantitative coronary computed tomography angiography predicts ischemia and impaired myocardial blood flow

Background

Atherosclerotic plaque characteristics influence the hemodynamic consequences of coronary lesions. This study sought to assess the performance of a machine learning (ML) score integrating coronary computed tomography angiography (CCTA)-based quantitative plaque features for the prediction of ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by [15O]H2O positron emission tomography (PET).

Methods

This post-hoc analysis of the PACIFIC (Prospective Comparison of Cardiac PET/CT, SPECT/CT Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography) trial included 208 patients with suspected coronary artery disease who underwent CCTA, [15O]H2O PET, and 3-vessel invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. A boosted ensemble ML algorithm (XGBoost) trained on data from the NXT (Analysis of Coronary Blood Flow using CT Angiography: Next Steps) trial was used to develop a ML score for the prediction of per-vessel ischemia (invasive FFR ≤0.80). The performance of the ML score was evaluated in 551 vessels from the PACIFIC trial for external validation. Thereafter, we assessed the discriminative ability of the ML score for per-vessel impaired hyperemic MBF (≤2.30 mL/min/g).

Results

In total, 138 (25.0%) vessels had ischemia and 195 (35.4%) vessels had impaired hyperemic MBF. CCTA-derived quantitative percent diameter stenosis and low-density noncalcified plaque (LDNCP) volume were higher in ischemic vessels compared with non-ischemic vessels (60.8% vs. 19.9%; and 42.3 mm3 vs. 9.1 mm3; both p&lt;0.001). The ML score demonstrated a significantly higher area under the receiver-operating characteristic curve (AUC) for predicting ischemia (0.92, 95% confidence interval [CI] 0.89–0.94) compared with visual stenosis grade (0.84, 95% CI 0.80–0.87; p&lt;0.001). Overall, quantitative percent diameter stenosis and LDNCP volume had greatest feature importance for ML, followed by percent area stenosis, minimum luminal diameter, and contrast density drop (Figure 1). An individualized explanation of ML ischemia prediction is shown in Figure 2. When applied for impaired MBF discrimination, the ML score exhibited an AUC of 0.82 (95% CI 0.78–0.85) and was superior to visual stenosis grade (AUC 0.76, 95% CI 0.72–0.80; p=0.03).

Conclusions

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and abnormal MBF by PET, outperforming standard visual CCTA interpretation.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute, United States Performance of the ML scoreIndividual explanation of ML prediction

[Trajectories of body mass index Z-score and risk of high blood pressure in late adolescence in Suzhou children]

Objective: To identify age and gender standardized body mass index among children and adolescents and explore their associations with high blood pressure (HBP) in late adolescence. Methods: The current study was based on the Health Promotion Program for Children and Adolescents, school-based surveillance successively conducted from 2012 to 2019 in Suzhou, China. A total of 11 812 children and adolescents aged 16-18 years, who had ≥4 examination records during 2012-2018 and were also involved in a surveillance program in 2019, were included. Latent class growth mixture modeling was used to identify the BMI-Z trajectories in different genders, and multivariate logistic regression was used to analyze the associations between different BMI-Z trajectories and risk of HBP in late adolescence. Results: Six distinct BMI-Z trajectories were determined for both genders:thin, slightly thin,standard, declining, overweight, and obese. Compared with the regular group, the obesity group had 94.0% (OR=1.94, 95%CI: 1.43-2.63) and 107.0% (OR=2.07, 95%CI: 1.33-3.22) increased risk of developing HBP in late adolescence in boys and girls, respectively. However, a neutral association was found between the descending group and HBP in late adolescence. Conclusions: Persistent obesity in children may increase the risk of HBP in their late adolescence. If an obese child restores normal weight before late adolescence, the risk of HBP may reduce.

Diagnostic accuracy of level IV portable sleep monitors versus polysomnography for pediatric obstructive sleep apnea: a systematic review and meta-analysis

BACKGROUND

Obstructive sleep apnea (OSA) is one of the common sleep-related breathing disorders in children. However, polysomnography (PSG) is an expensive and labor-intensive diagnostic modality that may not always be feasible, especially in low-income countries or in non-tertiary hospitals. Portable monitors (PMs), a new approach for OSA diagnosis, have become more widely used with lower intolerance and cost in recent years. We aimed to analyze the diagnostic performance of Level IV PMs compared with PSG for the diagnosis of pediatric OSA.

METHODS

PubMed and Embase databases were searched for studies published in English up to December 31, 2020 evaluating the diagnostic accuracy of Level IV PMs against the apnea-hypopnea index (AHI) measured using overnight in-laboratory polysomnography (PSG) in children and adolescents. A random-effects bivariate model was used to estimate the summary sensitivity and specificity of oximetry-based statistical classifiers. A qualitative evaluation of studies was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) rating.

RESULTS

In total, 20 studies involving 7062 participants were included in this systematic review. Among these articles, seven studies (oximetry based on new mathematical classifiers) involving 5098 individuals satisfied the criteria for quantitative synthesis. Compared with AHI evaluation measured by PSG, different PM systems achieved diagnostic accuracy with variable degrees of success. A meta-analysis showed a pooled sensitivity of 74% (95% confidence interval [CI]: 66-80%) and pooled specificity of 90% (95% CI: 85-94%). The area under the summary receiver operating characteristic (SROC) curve was 0.89 (95% CI: 0.86-0.92).

CONCLUSION

This study showed the potential of Level IV PMs for screening pediatric OSA patients. Oximetry based on new mathematical classifiers may provide a simple and effective alternative to PSG in the diagnosis of pediatric OSA especially in the context of appropriate clinical evaluation.