Prevalence of Obstructive Sleep Apnea Among Atrial Fibrillation Patients: A Cross-Sectional Study from Jordan.

Background: Obstructive Sleep Apnea (OSA) is a common respiratory disorder that causes intermittent upper airway collapse during sleep and can lead to various acute cardiovascular complications. Atrial Fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with an increased risk of cardiovascular hospitalization and all-cause mortality. Our study aimed to investigate the prevalence of individuals with AF and those considered at high risk for OSA. Methods: A cross-sectional study was conducted with a population comprising patients who had visited KAUH cardiology clinics between 2017-2019; subjects were categorized into AF patients and general cardiology patients. Patients were surveyed for OSA using the Berlin Questionnaire to assess the degree of OSA symptoms and to classify patients into high- or low-risk groups based on their responses. Results: Of the 656 patients, 545 met our inclusion criteria, of whom 192 were diagnosed with AF. Comparable demographic characteristics were observed between the AF and non-AF groups, barring higher rates of obesity (p=0.001) and smoking (p=0.042) in the AF group. The prevalence of high-risk OSA was significantly higher in AF patients (68.2%) compared to non-AF patients (29.4%), with an adjusted odds ratio of 2.473 times (95% CI: 1.434 -4.266, p=0.001) greater for AF. The age, gender, and BMI categories did not differ significantly between the two groups. Binary logistic regression revealed significant associations between OSA and risk factors such as asthma (OR=4.408, 95% CI: 2.634-7.376, p=0.001). Conclusion: These results serve to display a statistically significant increase in high-risk OSA in existing AF patients, irrespective of the presence of conventional OSA risk factors; this could imply a more immediate and direct relationship between both diseases and calls to include routine screening for OSA in patients diagnosed, newly or otherwise, with AF.

Reported long-term effects of COVID-19 patients after hospital discharge in Jordan.

Coronavirus Disease 2019 (COVID-19) long-term effect is the new challenge facing healthcare providers that should be further assessed. We aim to describe the characteristics and patterns of long-term consequences of COVID-19 among recovered patients. COVID-19 patients baseline data was extracted from hospital records and alive patients filled self-reported symptoms questionnaires. A follow-up chest X-ray (CXR) was then scored based on lung abnormalities and compared with baseline CXR images. Six hundred ninety-four patients were included for the questionnaire and final analysis. Patients who were categorized as critical or severe were more prone to develop at least one symptom than those who were categorized as moderate. The most newly diagnosed comorbidities after discharge were diabetes (40.9%), cardiovascular diseases (18.6%), and hypertension (11.9%). Most patients with prolonged symptoms after discharge had a significant decrease in the quality of life. Small number of CXR showed persistent abnormalities in the middle right, the lower right, and lower left zones with an average overall score during admission 13.8 ± 4.9 and 0.3 ± 1.01 for the follow-up images. Effects of COVID-19 were found to persist even after the end of the infection. This would add on to the disease burden and would foster better management.

Factors contributing to poor COVID-19 outcomes in diabetic patients: Findings from a single-center cohort study.

Diabetes Mellitus (DM) is a frequent comorbidity in patients infected with the SARS-CoV-2 virus. The risk of developing severe or critical COVID-19 and higher mortality was observed to be increased in diabetic patients hospitalized due to COVID-19. In this study we aimed to find out the impact of clinical characteristics, comorbidities, laboratory results, and complications on the outcomes of diabetic patients hospitalized due to COVID-19. This article is a retrospective cohort study that include diabetic patients hospitalized with COVID-19 infection. A definition of diabetes was based on the past history of diabetes or if the HbA1c was 6.5% or higher. Demographics, clinical characteristics, comorbidities, laboratory results, and complications were extracted from the electronic medical records. The mortality rate increased with increasing age (from 5.56% in younger patients to 46% in the elderly) and with severity (from 25.71% in moderate cases to 43.77% in critical cases). We found that a critical severity on admission (OR: 5.26, 95% CI: 1.28-21.66, p = 0.0214), a history of stroke (OR: 8.37, 95% CI: 2.2-31.88, p = 0.0018), and low calcium levels on admission (OR: 2.23, 95% CI: 1.01-4.91, p = 0.0475) were significant risk factors predicting higher COVID-19 mortality in diabetic patients. The findings of this study suggest that reduced calcium levels could potentially indicate higher mortality due to COVID-19 in patients with DM. Furthermore, careful monitoring of diabetic patients hospitalized due to COVID-19 infection, especially those with critical disease severity or those with a history of stroke, may improve their outcome and lessen mortality.

Health-Related Quality of Life for Jordanian-Recovered Individuals During Post-COVID-19 Era: A Cross-Sectional Study.

Aim: This study aims to determine health-related quality of life (HRQoL) that includes the physical and mental health of recovered patients of COVID-19 and examines the significant impact of variables such as period of infection, sample demographics characteristics, hospitalization past, and chronic disease past and the other variables on HRQoL of COVID-19-recovered patients. Methods: An exploratory, community-based, cross-sectional research layout was adopted, using an electronic self-reporting survey disseminated online to recovered COVID-19 patients in Jordan. Targeted COVID-19 patients were individuals who were 18 years old or above. They had a documented background of COVID-19 illness, as stated in the following inclusion requirements: Those who had not been formally proven to have been afflicted by COVID-19 were excluded. Results: The mean of the physical well-being of study participants during COVID-19 was M=68.00 (SD=6.95), representing medium physical well-being status. The mean of psychological well-being of study participants during COVID-19 was M=60.20 (SD=8.85), representing medium physical health. Multiple regression showed that female recovered patients who are not working, with a low level of income, married women, and who getting COVID-19 more than once are having lower health-related quality of life compared to other recovered patients. Conclusion: The HRQoL of COVID-19 patients was significantly impacted, independent of the period since hospitalization or rehabilitation. Policymakers and health workers should research strong ways to enhance the HRQoL of COVID-19 patients as soon as possible. Elderly patients and those who have been infected more than one time and being hospitalized have a greater probability of decreased HRQoL after infection.

Skin Manifestations Among Patients Admitted with COVID-19: A Cross-Sectional Study at a University-Based Tertiary Hospital in Jordan.

Background: COVID-19 pandemic hit the entire world with severe health and economic consequences. Although the infection primarily affected the respiratory system, it was soon recognized that COVID-19 has a multi-systemic component with various manifestations including cutaneous involvement. Objective: The main objective of this study is to assess the incidence and patterns of cutaneous manifestations among moderate-to-severe COVID-19 patients who required hospitalization and whether there was a prognostic indication for cutaneous involvement and the outcome in terms of recovery or death. Methods: This is a cross-sectional observational study that included inpatients who were diagnosed with a moderate or severe COVID-19 infection. The demographic and clinical data of patients were assessed including age, sex, smoking, and comorbidities. All patients were examined clinically for the presence of skin manifestations. Patients were followed for the outcome of COVID-19 infection. Results: A total of 821 patients (356 females and 465 males) aged 4-95 years were included. More than half of patients (54.6%) aged >60 years. A total of 678 patients (82.6%) had at least one comorbid condition, mostly hypertension and diabetes mellitus. Sixty-two patients (7.55%) developed rashes; 5.24% cutaneous and 2.31% oral. The rashes were then grouped into five major types: group A, Exanthema: morbilliform, papulovesicular, varicella-like. Group B, Vascular: Chilblain-like lesions, purpuric/petechial, livedoid lesions. Group C, Reactive erythemas: Urticaria, Erythema multiforme. Group D, other skin rashes including flare-up of pre-existing disease, and O for oral involvement. Most patients (70%) developed rash after admission. The most frequent skin rashes were reactive erythema (23.3%), followed by vascular (20.9%), exanthema (16.3%), and other rashes with flare-ups of pre-existing diseases (39.5%). Smoking and loss of taste were associated with the appearance of various skin rashes. However, no prognostic implications were found between cutaneous manifestations and outcome. Conclusion: COVID-19 infection may present with various skin manifestations including worsening of pre-existing skin diseases.

Acid-base imbalance as a risk factor for mortality among COVID-19 hospitalized patients.

Severe coronavirus disease 2019 (COVID-19) infection can lead to extensive lung infiltrate, a significant increase in the respiratory rate, and respiratory failure, which can affect the acid-base balance. No research in the Middle East has previously examined acid-base imbalance in COVID-19 patients. The present study aimed to describe the acid-base imbalance in hospitalized COVID-19 patients, determine its causes, and assess its impact on mortality in a Jordanian hospital. The study divided patients into 11 groups based on arterial blood gas data. Patients in normal group were defined as having a pH of 7.35-7.45, PaCO2 of 35-45 mmHg, and HCO3- of 21-27 mEq/L. Other patients were divided into 10 additional groups: mixed acidosis and alkalosis, respiratory and metabolic acidosis with or without compensation, and respiratory and metabolic alkalosis with or without compensation. This is the first study to categorize patients in this way. The results showed that acid-base imbalance was a significant risk factor for mortality (P<0.0001). Mixed acidosis nearly quadruples the risk of death when compared with those with normal levels (OR = 3.61, P=0.05). Furthermore, the risk of death was twice as high (OR = 2) for metabolic acidosis with respiratory compensation (P=0.002), respiratory alkalosis with metabolic compensation (P=0.002), or respiratory acidosis with no compensation (P=0.002). In conclusion, acid-base abnormalities, particularly mixed metabolic and respiratory acidosis, were associated with increased mortality in hospitalized COVID-19 patients. Clinicians should be aware of the significance of these abnormalities and address their underlying causes.

Subclinical high-resolution chest CT scan features in psoriasis.

BACKGROUND: Although psoriasis is considered a systemic disease, no clear association has been established between psoriasis and lung diseases. This study aims to detect and describe subclinical pulmonary involvement in psoriasis patients with various degrees of cutaneous manifestations. METHODS: Adult psoriasis patients with no known active pulmonary disease or respiratory symptoms were screened for subclinical pulmonary manifestations and possible parenchymal changes using high-resolution computed tomography (HRCT) scan of the chest. Patients were classified according to the severity of skin manifestations. The clinical characteristics and radiographic findings of these patients were evaluated. RESULTS: Fifty-nine patients with psoriasis were included, among which 47 (79.7%) had abnormal HRCT scan features. Micronodules were the most common detected lung lesions (66.1%), followed by nonspecific interstitial changes (32.2%), including pleuro-parenchymal band/atelectasis, scarring, and focal ground-glass opacities. Other HRCT findings included emphysematous changes and calcified granulomas. Abnormal HRCT findings correlated with older age and duration of psoriasis but not with the severity of skin manifestations. CONCLUSIONS: Micronodules and minor focal nonspecific interstitial changes were the most detected lung alterations in patients with psoriasis. These findings of the pilot study highlight a possible pulmonary involvement in patients with psoriasis. Larger multicenter studies are needed to clarify these findings further. LIMITATIONS: A major limitation of the study, is the lack of a control group with similar radiologic findings of different conditions done in the same geographical region.

Development of a telemedicine group educational program for patients with heart failure: A delphi study.

Aims: Evidence regarding the most effective and feasible videoconferencing group educational program for patients with heart failure is still equivocal. This study aimed to reach consensus about the structure, acceptability, and feasibility of videoconferencing for people with heart failure in Jordan that improves access to healthcare and clinical outcomes. Methods: There were two Delphi survey studies of three rounds each. Delphi one survey involved 32 healthcare staff, experienced in heart failure clinical practice and telehealth, to obtain a consensus of opinion on a proposed group videoconferencing program for patients with heart failure. Delphi two involved seven staff of the information technology center, experienced in videoconferencing and using supporting applications, to obtain their consensus on the current capabilities of the healthcare system and patients about information technology. Descriptive statistics were used for each item to determine whether consensus was achieved or not. Items that received 80% disagreement or 80% agreement of participants were not presented for re-rating in the third round, while the items that scored varying degrees of agreement were presented for experts for re-rating. Results: In Delphi one a group of items reached consensus regarding structure, factors influencing, and effectiveness of the videoconferencing program. In Delphi two, the findings indicated that videoconferencing modality is applicable and feasible in Jordan. Conclusion: This is the first study that addresses the equivocal evidence for the design and implementation of heart failure videoconferencing programs. The framework of the current proposed program can be utilized as a guideline to test or develop a future videoconference program.

A dataset of COVID-19 x-ray chest images.

The distinction between normal chest x-ray (CXR) images and abnormal ones containing features of disease (e.g., opacities, consolidation, etc.) is important for accurate medical diagnosis. CXR images contain valuable information concerning the physiological and pathological state of the lungs and airways. In addition, they provide information about the heart, chest bones, and some arteries (e.g., Aorta and pulmonary arteries). Deep learning artificial intelligence has taken great strides in the development of sophisticated medical models in a wide range of applications. More specifically, it has been shown to provide highly accurate diagnosis and detection tools. The dataset presented in this article contains the chest x-ray images from the examination of confirmed COVID-19 subjects, who were admitted for a multiday stay at a local hospital in northern Jordan. To provide a diverse dataset, only one CXR image per subject was included in the data. The dataset can be used for the development of automated methods that detect COVID-19 from CXR images (COVID-19 vs. normal) and distinguish pneumonia caused by COVID-19 from other pulmonary diseases. ©202x The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Autoantibody profile in sarcoidosis, analysis from the GRADS sarcoidosis cohort.

BACKGROUND: Sarcoidosis, a multi-systemic granulomatous disease, is a predominantly T-cell disease but evidence for a role for humoral immunity in disease pathogenesis is growing. Utilizing samples from the Genomic Research in Alpha-1 anti-trypsin Deficiency and Sarcoidosis (GRADS) study, we examined the prevalence of autoantibodies in sarcoidosis patients with pulmonary-only and extra-pulmonary organ involvement compared to normal controls. STUDY DESIGN AND METHODS: We analyzed serum samples from sarcoidosis patients who participated in the GRADS study utilizing an autoantigen microarray platform for both IgM and IgG antibodies. The cohort included sarcoidosis patients with pulmonary-only disease (POS, n = 106), sarcoidosis patients with extra-pulmonary disease (EPS, n = 120) and a normal control cohort (NC, n = 101). Organ involvement was assessed following a standardized format across all GRADS participating centers. RESULTS: Sarcoidosis patients overall had increased levels of IgM and IgG autoantibodies compared to normal controls. In addition, several autoantibodies were elevated in the POS and EPS cohorts compared to the NC cohort. Differences in autoantibody levels were also noted between the POS and the EPS cohorts. When comparing organ involvement with sarcoidosis, bone, spleen and ear, nose and throat involvement had higher IgM expression than other organs. CONCLUSION: Sarcoidosis patients have elevated IgM and IgG autoantibody levels compared to normal controls. In addition, individuals with pulmonary as well as additional organ involvement had higher IgM expression. Further research is needed focusing on specific organ-autoantibody pairs and role of autoantibodies in disease pathogenesis.

Risk Factors Associated with Mortality in COVID-19 Hospitalized Patients: Data from the Middle East.

This study aimed to assess the risk factors for COVID-19 mortality among hospitalized patients in Jordan. All COVID-19 patients admitted to a tertiary hospital in Jordan from September 20, 2020, to August 8, 2021, were included in this study. Demographics, clinical characteristics, comorbidities, and laboratory results were extracted from the patients' electronic records. Multivariable logistic and machine learning (ML) methods were used to study variable importance. Out of 1,613 COVID-19 patients, 1,004 (62.2%) were discharged from the hospital (survived), while 609 (37.8%) died. Patients who were of elderly age (>65 years) (OR, 2.01; 95% CI, 1.28-3.16), current smokers (OR, 1.61; 95%CI, 1.17-2.23), and had severe or critical illness at admission ((OR, 1.56; 95%CI, 1.05-2.32) (OR, 2.94; 95%CI, 2.02-4.27); respectively), were at higher risk of mortality. Comorbidities including chronic kidney disease (OR, 2.90; 95% CI, 1.90-4.43), deep venous thrombosis (OR, 2.62; 95% CI, 1.08-6.35), malignancy (OR, 2.22; 95% CI, 1.46-3.38), diabetes (OR, 1.31; 95% CI, 1.04-1.65), and heart failure (OR, 1.51; 95% CI, 1.02-2.23) were significantly associated with increased risk of mortality. Laboratory abnormalities associated with mortality included hypernatremia (OR, 11.37; 95% CI, 4.33-29.81), elevated aspartate aminotransferase (OR, 1.81; 95% CI, 1.42-2.31), hypoalbuminemia (OR, 1.75; 95% CI, 1.37-2.25), and low platelets level (OR, 1.43; 95% CI, 1.05-1.95). Several demographic, clinical, and laboratory risk factors for COVID-19 mortality were identified. This study is the first to examine the risk factors associated with mortality using ML methods in the Middle East. This will contribute to a better understanding of the impact of the disease and improve the outcome of the pandemic worldwide.

Predictors of invasive mechanical ventilation in hospitalized COVID-19 patients: a retrospective study from Jordan.

OBJECTIVES: To identify early indicators for invasive mechanical ventilation utilization among COVID-19 patients. METHODS: This retrospective study evaluated COVID-19 patients who were admitted to hospital from 20 September 2020, to 8 August 2021. Multivariable logistic regression and machine learning (ML) methods were employed to assess variable significance. RESULTS: Among 1,613 confirmed COVID-19 patients, 365 patients (22.6%) received invasive mechanical ventilation (IMV). Factors associated with IMV included older age >65 years (OR,1.46; 95%CI, 1.13-1.89), current smoking status (OR, 1.71; 95%CI, 1.22-2.41), critical disease at admission (OR, 1.97; 95%CI, 1.28-3.03), and chronic kidney disease (OR, 2.07; 95%CI, 1.37-3.13). Laboratory abnormalities that were associated with increased risk for IMV included high leukocyte count (OR, 2.19; 95%CI, 1.68-2.87), low albumin (OR, 1.76; 95%CI, 1.33-2.34) and high AST (OR, 1.71; 95%CI, 1.31-2.22). CONCLUSION: Our study suggests that there are several factors associated with the increased need for IMV among COVID-19 patients. These findings will help in early identification of patients at high risk for IMV and reallocation of hospital resources toward patients who need them the most to improve their outcomes.

Berlin and Epworth Surveys to Predict Obstructive Sleep Apnea for Adults on Biomimetic Oral Appliance Therapy: A Nonrandomized Clinical Trial.

Background: Two questionnaires (Berlin Questionnaire (BQ) and Epworth Sleepiness Scale (ESS)) are the widely used screening instruments for subjects suffering from sleep disorders. Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing. The biomimetic oral appliance therapy (BOAT) offers an alternative nonsurgical method, which can improve symptoms and indices of OSA on objective sleep testing. Aim: To describe testing the ability of BQ and EES for prediction of BOAT outcomes during OSA. Methods: Seventeen adults (9 males, 8 females; age, mean (SD): 45.76 (10.31), BMI mean (SD): 33.5(13.43)) who underwent an overnight sleep study were diagnosed by a sleep specialist physician. The BQ and EES were recorded before and after BOAT treatment. Subjects with mild-to-moderate OSA had 2 months of follow-up visits and underwent a final overnight sleep study to measure apnea-hypopnea index (AHI). The subjects were asked to wear the appliance for 10-12 hours/day and at night. Findings were analyzed statistically using paired t-tests. Result: As per sleep test results, pre-BOAT AHI measures versus post-BOAT AHI measures showed significant improvement. Comparing the BQ before versus after treatment showed that at the pretreatment stage, 66.0% of patients had high-risk score, whereas 34% had low-risk score. After treatment, 66.0% of patient had low-risk scores, whereas 34% had high-risk scores. As for the ESS, treatment resulted in significant reduction of total score from 10.43 ± 6.32 to 5.00 ± 5.20 (P < 0.01, paired t-test). Finally, there was a mild negative correlation between AHI and each of the BQ and ESS scores that was not statistically significant (r = -0.420, N = 26, P > 0.05, and r = -0.41, N = 26, P > 0.05, respectively). Conclusion: The BOAT device may provide a useful form of therapy to improve OSA-related PSG parameters such as AHI. Both BQ and ESS were predictive to improvements detected by the sleep study during BOAT device use.

Clinical and biological indicators of periodontal disease in obese and non-obese adults with and without bronchial asthma.

OBJECTIVE: The present study aims to assess clinical and inflammatory parameters as indicators for periodontal disease in obese and non-obese adults with and without bronchial asthma (BA). METHODS: 168 patients visiting the outpatient pulmonary clinics were divided into four groups according to BA and obesity. Obesity was defined by body mass index (BMI) and BA was diagnosed by a pulmonary consultant and being on inhaled asthma medication for at least 12 months. Participants were examined for clinical periodontal parameters and samples of gingival crevicular fluid (GCF) were taken and analyzed for the levels of 5 different inflammatory cytokines. RESULTS: Compared with controls, obese asthmatic group had significant higher mean clinical attachment loss (CAL) (2.64 vs. 1.00, p < .001). Also, the occurrence of periodontitis was significantly higher among obese patients compared to non-obese patients (p = 0.003). Multivariate logistic regression model showed that age was the strongest predictor of periodontitis (aOR = 1.23). The levels of IL-1ß and IL-8 were significantly higher in the non-obese asthmatic group compared to the control group (p < 0.05). The level of IL-6 was significantly lower in the control group compared to the other groups (p < 0.001). Obese patients had significantly higher concentration of hsCRP compared to non-obese patients (p < 0.001). There was no significant difference in the level of TNF- α between groups. CONCLUSIONS: BA and obesity combined did not seem to be associated with a significant increased risk of having periodontitis. BA and obesity are associated with increased levels of some local proinflammatory cytokines which adds to the local and systemic inflammatory burden.

Trends in Insomnia, Burnout, and Functional Impairment among Health Care Providers over the First Year of the COVID-19 Pandemic.

Background: COVID-19 pandemic has negatively impacted the psychological well-being and quality of life of health care providers (HCPs). Objectives: This study assessed the trends in prevalence and predictors of insomnia, burnout, and functional impairment among HCPs over the first year of the pandemic. Methods: An online survey was conducted one month after the pandemic's onset (onset group) and a year later (one-year group). The demographic features of participants were collected. Insomnia, burnout, and functional impairment were assessed using Insomnia Severity Index (ISI), Mini-Z survey, and Sheehan Disability Scale (SDS), respectively. Results: The onset group included 211 HCPs (mean (SD) age 34.7 (9.3) years and 73% men), while 212 HCPs participated in the one-year survey (mean (SD) age 35.9 (10.5) years and 69% men). High prevalence estimates were found in both onset and one-year groups of symptoms of insomnia (52% vs. 49%), of diagnosis of clinical insomnia (15% vs. 18%), with a high mean ISI score (8.4 vs. 8.7), but with no significant difference between the onset and one-year groups. Risk factors for clinical insomnia included age in both groups, lower income and contact level with COVID-19 patients/samples in the onset group, and lower Mini-Z scores and higher SDS scores in the one-year group. Approximately one-third of respondents reported at least one or more burnout symptoms, with a higher percentage in the one-year group (35.4%) than in the onset group (24.2%) (p=0.012). Younger age, lower monthly income, and higher ISI and SDS scores were risk factors for burnout in both groups. Greater perceived changes in social life were associated with burnout in the onset group. In contrast, higher weekly working hours, worse participants' evaluation of their institution's preparation, and more changes in workload were risk factors for burnout in the one-year group. The SDS score and its subscales scores were higher in the one-year group than in the onset group. Changes in workload and social life predicted higher SDS scores among both groups. Living with older people predicted higher SDS scores among the onset group, while contact level and estimated number of COVID-19 patients that participants engaged in during caring predicted higher SDS scores among the one-year group. ISI scores were significantly correlated with the Mini-Z scores and SDS scores in both groups, while the Mini-Z and SDS scores were significantly correlated only in the one-year group. Conclusion: This study demonstrated high rates of insomnia, burnout, and functional impairment among HCPs during the pandemic. It reveals a significant rise in job burnout and functional impairment of HCPs overtime during the pandemic. Furthermore, high-risk subgroups are also highlighted for whom comprehensive psychosocial and occupational interventions might be warranted.

Detection of COVID-19 from Chest X-ray Images Using Deep Convolutional Neural Networks.

The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated applications that can meet clinical accuracy requirements. In this study, customized and pre-trained deep learning models based on convolutional neural networks were used to detect pneumonia caused by COVID-19 respiratory complications. Chest X-ray images from 368 confirmed COVID-19 patients were collected locally. In addition, data from three publicly available datasets were used. The performance was evaluated in four ways. First, the public dataset was used for training and testing. Second, data from the local and public sources were combined and used to train and test the models. Third, the public dataset was used to train the model and the local data were used for testing only. This approach adds greater credibility to the detection models and tests their ability to generalize to new data without overfitting the model to specific samples. Fourth, the combined data were used for training and the local dataset was used for testing. The results show a high detection accuracy of 98.7% with the combined dataset, and most models handled new data with an insignificant drop in accuracy.

Impact of daytime sleepiness and insomnia on simple and complex cognitive task performances.

OBJECTIVE: To examine the individual and combined effects of daytime sleepiness and insomnia disorder (ID) on measures of cognitive functioning. DESIGN AND SETTING: This study was conducted at a medical center using a cross-sectional research design. PARTICIPANTS: 35 persons with ID (Mage = 40.6 years; 25 women) and 54 normal sleepers (NS; Mage = 31.5 years; 38 women). METHODS AND MEASURES: Participants underwent two nights of home-based polysomnography (PSG) followed by daytime testing with a four-trial Multiple Sleep Latency Test (MSLT). Before each MSLT nap, they completed a computer-administered battery of reaction time tasks. Measures of response latencies and response accuracy were tabulated and used as dependent measures. The ID and NS groups were each subdivided into "alert" (eg, MSLT mean latency > 8 min) and "sleepy" (eg, MSLT mean latency ≤ 8 min) subgroups to identify hyperaroused persons with ID and allow for their comparisons with the other participant subgroups. RESULTS: Multivariate analyses of variance showed a significant main effect for level of daytime sleepiness (F [1, 84] = 8.52, p = 0.0045) on simpler performance tasks and a significant main effect for presence vs. absence of ID (F [1,84] = 6.62, p = 0.012) on complex tasks. A lack of significant participant type x MSLT alertness level interactions in study analyses suggested those ID participants with presumed hyperaousal were not relatively more impaired than the other participant subgroups. CONCLUSIONS: Daytime performance deficits on simple tasks seem most dependent on individuals' levels of daytime sleepiness, whereas performance deficits on more complex tasks appears related to the presence of ID. Therefore, it seems best to use complex performance measures both to document cognitive deficits among those with ID and to determine if insomnia treatments reduce such impairments. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02290405.

Determinants of the willingness of the general population to get vaccinated against COVID-19 in a developing country.

PURPOSE: Vaccination is a cost-efficient intervention to slow the spread of the coronavirus disease 2019 (COVID-19) pandemic. This study aims to assess the population's willingness to take the COVID-19 vaccine in Jordan and investigate potential determinants of their acceptance. MATERIALS AND METHODS: This study used an online survey distributed in November 2020, before introducing the vaccine, with items investigating socio-demographic characteristics, seasonal flu vaccination history, COVID-19 vaccine acceptance once available, and factors affecting their decision-making. Also, "COVID-19 risk perception" and beliefs toward COVID-19 vaccine benefits and barriers were assessed. RESULTS: A total of 2,208 participants completed the survey with a participation rate of 13.1%. The mean±standard deviation age was 33.2±13.5, and 55.7% were females. Study participants were almost equally distributed between willingness, unwillingness, and indecision to take the COVID-19 vaccine (30.4%, 36.4%, and 31.5%, respectively). Younger adults, males, and those who were not married, do not have children, have a bachelor or higher education, employees or being students, healthcare workers, and those who reported receiving flu vaccine had higher rates of COVID-19 vaccine acceptance compared to their counterparts (p<0.001 for each category). COVID-19 risk perception, and perceived vaccine benefits, and barriers were significant predictors of intention. Among those undecided or unwilling to take the COVID-19 vaccine, its safety and side effects were the most common concerns. CONCLUSION: The low rate of COVID-19 vaccine acceptance in a developing country is alarming, and a significant proportion are indecisive. Interventions to elevate vaccine acceptance by addressing its safety and efficacy and targeting vulnerable groups are recommended.

Efficacy of pillar implants to reduce snoring and daytime sleepiness.

OBJECTIVE: To measure the efficacy of pillar implants in reducing snoring. MATERIALS AND METHODS: A total of 30 adult patients who underwent pillar implants were assessed preoperatively and at 1, 3, 6 and 12 months after the implantation. Improvement was measured using snoring frequency, visual analog scale for snoring loudness, and Epworth sleepiness scale for daytime sleepiness. RESULTS: The mean snoring frequency, loudness and Epworth score were reduced from 6.9, 9.2 and 7.4 at the baseline to 5, 5.9 and 5.6, respectively, at 12 months postoperatively (all p < 0.03). The partial implant extrusion rate was 6.7%. CONCLUSION: We suggest that a pillar implant procedure should be considered before proceeding to more morbid surgeries in patients with snoring and daytime sleepiness.

Diagnostic value of electrocardiogram during routine electroencephalogram.

INTRODUCTION: A single-lead electrocardiogram (EKG) is routinely recorded with electroencephalogram (EEG). This study investigates the frequency and types of EKG abnormalities during routine EEG. METHODS: All routine EEGs (20-60 min) over one year were retrospectively analyzed. A blinded cardiologist interpreted EKG recordings. An epileptologist evaluated EEGs. Demographic data, underlying comorbidities, and indications for the EEG were extracted. RESULTS: A total of 433 recordings for 365 patients were included. Mean (±SD) age was 46.8 (±21.3) years and 50.4% were females. EKG abnormalities were detected in 28.5% of patients; sinus tachycardia (11%), premature ventricular contractions (7.9%), atrial fibrillation (Afib) (6.3%), sinus bradycardia (2.2%) and premature atrial contractions (1.1%). Afib was more common in females than males (p = 0.020), confirmed in six out of seven patients and discovered in 17 patients. Age (OR: 1.67, 95%CI: 1.05-2.66, p = 0.031), prior diagnosis of epilepsy (OR: 2.25, 95% CI: 1.22 - 4.14, p = 0.009), history of seizure (OR: 1.97,  95%CI: 1.09-3.54, p = 0.024), abnormal EEG (OR: 2.14, 95%CI: 1.25 - 3.66, p = 0.005) and EEGs evaluating seizures/epilepsy (OR: 4.18, 95% CI: 1.32 - 13.21, p = 0.015) or syncope (OR: 3.21, 95% CI: 1.16 - 8.84, p = 0.024) were independently associated with abnormal EKG. CONCLUSION: The frequency of EKG abnormalities captured during routine EEGs was high, with Afib being the most significant. Older age, history of epilepsy or seizure, abnormal EEGs, and EEGs evaluating seizures/epilepsy or syncope were significant predictors. These findings suggest neurologists to become more vigilant to EKG recorded during routine EEG as such findings might have diagnostic and therapeutic implications.