Identification of sleep phenotypes in COPD using machine learning-based cluster analysis.

BACKGROUND: Disturbed sleep in patients with COPD impact quality of life and predict adverse outcomes. RESEARCH QUESTION: To identify distinct phenotypic clusters of patients with COPD using objective sleep parameters and evaluate the associations between clusters and all-cause mortality to inform risk stratification. STUDY DESIGN AND METHODS: A longitudinal observational cohort study using nationwide Veterans Health Administration data of patients with COPD investigated for sleep disorders. Sleep parameters were extracted from polysomnography physician interpretation using a validated natural language processing algorithm. We performed cluster analysis using an unsupervised machine learning algorithm (K-means) and examined the association between clusters and mortality using Cox regression analysis, adjusted for potential confounders, and visualized with Kaplan-Meier estimates. RESULTS: Among 9992 patients with COPD and a clinically indicated baseline polysomnogram, we identified five distinct clusters based on age, comorbidity burden and sleep parameters. Overall mortality increased from 9.4 % to 42 % and short-term mortality (<5.3 years) ranged from 3.4 % to 24.3 % in Cluster 1 to 5. In Cluster 1 younger age, in 5 high comorbidity burden and in the other three clusters, total sleep time and sleep efficiency had significant associations with mortality. INTERPRETATION: We identified five distinct clinical clusters and highlighted the significant association between total sleep time and sleep efficiency on mortality. The identified clusters highlight the importance of objective sleep parameters in determining mortality risk and phenotypic characterization in this population.

Validation of electronic diagnostic codes for rapid eye movement sleep behavior disorder.

We investigated the accuracy of International Classification of Diseases (ICD) codes for the identification of Veterans with rapid eye movement (REM) sleep behavior disorder (RBD). The charts of 139 randomly sampled Veterans with ≥1 ICD-9 and ICD-10 code(s) for RBD were reviewed for documentation of a suspected, previous, or current diagnosis; clinical symptoms; and/or empiric treatments for this disorder. Notably, 71 (51.1%) of patients with RBD electronic diagnoses lacked polysomnography (PSG), and 29 (20.9%) had PSG reports without commentary on REM sleep without atonia (RSWA). Sleep centers are therefore encouraged to include a brief sentence in PSG report templates commenting on the presence/absence of RSWA.

The role of lncRNAs in intermittent hypoxia and sleep Apnea: A review of experimental and clinical evidence.

In this narrative review, we present a comprehensive assessment on the putative roles of long non-coding RNAs (lncRNAs) in intermittent hypoxia (IH) and sleep apnea. Collectively, the evidence from cell culture, animal, and clinical research studies points to the functional involvement of lncRNAs in the pathogenesis, diagnosis, and potential treatment strategies for this highly prevalent disorder. Further research is clearly warranted to uncover the mechanistic pathways and to exploit the therapeutic potential of lncRNAs, thereby improving the management and outcomes of patients suffering from sleep apnea.

Trends in sleep apnea and heart failure related mortality in the United States from 1999 to 2019.

National estimates of deaths related to both heart failure (HF) and sleep apnea (SA) are not known. We evaluated the trends in HF and SA related mortality using the CDC-WONDER database in adults aged ≥25 years in the US. All deaths related to HF and SA as contributing or underlying causes of death were queried. Between 1999 and 2019, there were a total of 6,484,486 deaths related to HF, 204,824 deaths related to SA, and 53,957 deaths related to both. There was a statistically significant increase in the age-adjusted mortality rate (AAMR) for both SA-related (average annual percent change [AAPC] 8.2%) and combined HF and SA- related (AAPC 10.1 %) deaths. Men had consistently higher AAMRs compared with women, and both groups had a similar increasing trend in AAMR. Non-Hispanic (NH) Black individuals had the highest HF and SA-related AAMR, followed by NH White and Hispanic/Latino individuals. Adults aged >75 years consistently had the highest AAMR with the steepest increase (AAPC 11.1%). In conclusion, HF and SA-related mortality has significantly risen over the past two decades with the elderly, men, and NH Black at disproportionately higher risk.

Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data.

Rationale: Hospital readmission within 30 days poses challenges for healthcare providers, policymakers, and patients because of its impact on care quality, costs, and outcomes. Patients with interstitial lung disease (ILD) are particularly affected by readmission, which is associated with increased morbidity and mortality and reduced quality of life. Because small sample sizes have hindered previous studies, this study seeks to address this gap in knowledge by examining a large-scale dataset. Objective: To determine the rate and probability of 30-day all-cause readmission and secondary outcomes in patients with coronavirus disease (COVID-19) or ILD admitted to the hospital. Methods: This study is a nested cohort study that used the PearlDiver patient records database. Adult patients (age ⩾18 yr) who were admitted to hospitals in 28 states in the United States with COVID-19 or ILD diagnoses were included. We defined and analyzed two separate cohorts in this study. The first cohort consisted of patients with COVID-19 and was later divided into two groups with or without a history of ILD. The second cohort consisted of patients with ILD and was later divided into groups with COVID-19 or with a non-COVID-19 pneumonia diagnosis at admission. We also studied two other subcohorts of patients with and without idiopathic pulmonary fibrosis within the second cohort. Propensity score matching was employed to match confounders between groups. The Kaplan-Meier log rank test was applied to compare the probabilities of outcomes. Results: We assessed the data of 2,286,775 patients with COVID-19 and 118,892 patients with ILD. We found that patients with COVID-19 with preexisting ILD had an odds ratio of 1.6 for 30-day all-cause readmission. Similarly, an odds ratio of 2.42 in readmission rates was observed among hospitalized individuals with ILD who contracted COVID-19 compared with those who were hospitalized for non-COVID-19 pneumonia. Our study also found a significantly higher probability of intensive care admission among patients in both cohorts. Conclusions: Patients with ILD face heightened rates of hospital readmissions, particularly when ILD is combined with COVID-19, resulting in adverse outcomes such as decreased quality of life and increased healthcare expenses. It is imperative to prioritize preventive measures against COVID-19 and establish effective postdischarge care strategies for patients with ILD.

Obesity paradox or hypoxia preconditioning: How obstructive sleep apnea modifies the Obesity-MI relationship.

OBJECTIVES: The objective of this study was to evaluate the interaction between obesity and obstructive sleep apnea on acute MI in hospital mortality. METHODS: This retrospective cohort study utilized Veterans Health Administration data from years 1999-2020. Participants were categorized according to their body mass index (BMI) to non-obese (BMI <30) and obese (BMI ≥30) groups. Clinical obstructive sleep apnea (SA) diagnosis was confirmed using ICD9/10 codes and the study subgroups included non-obese with no obstructive sleep apnea (nOB-nSA), non-Obese with obstructive sleep apnea (nOB-SA), obese with no obstructive sleep apnea (OB-nSA), and obese with obstructive sleep apnea (OB-SA). The primary outcome was odds ratio of in-hospital mortality during the hospitalization with acute MI as the principal diagnosis adjusted for age, gender, race, ethnicity, and Charlson comorbidity index (CCI) with the nOB-nSA group as the comparison group. RESULTS: Among 72,036 veterans with acute-MI hospitalization, individuals with obesity and obstructive sleep apnea (OB-SA) had the lowest in-hospital mortality rate (1.0%) compared to those without obesity and obstructive sleep apnea (nOB-nSA, 2.8%), with obesity but without obstructive sleep apnea (OB-nSA, 2.4%), and with obesity and obstructive sleep apnea (nOB-SA, 1.4%). The adjusted odds ratio for mortality, compared to nOB-nSA, was 9% higher but not significant in OB-nSA (aOR, 1.09, 95%CI: 0.95, 1.25), 46% lower in OB-nSA (aOR, 0.54, 95%CI: 0.45, 0.66), and 52% lower in OB-SA (aOR, 0.48: 95%CI: 0.41, 0.57). CONCLUSION: Our data suggest that the association between obesity and improved survival in acute MI is largely driven by the presence of sleep apnea.

The association between OSA and glycemic control in diabetes.

Background: Obstructive sleep apnea (OSA) is the most common sleep-realted respiratory disorder. It is frequently comorbid with cardiovascular, cerebrovascular, and metabolic diseases and is commonly observed in populations with these comorbidities. Investigators aimed to assess the effect of OSA on glycemic control in patients with diabetes. Methods: In this cross-sectional study, 266 adult patients with diabetes mellitus (DM) attending the outpatient endocrinology clinic at the Guilan University of Medical Sciences were enrolled. Patients completed a checklist that included demographic characteristics, factors, and laboratory results in addition to Berlin and STOP-BANG questionnaires to evaluate the risk of OSA. Data were analyzed by independent t-test, Mann-Whitney U test, and Chi-squared or Fisher's exact tests using the Statistical Package for the Social Sciences (SPSS) version 17. Results: A total of 266 patients with DM were enrolled in this study (34.6% males, mean age 47.00 ± 19.04 years). Based on the Berlin Questionnaire, 38.6% of all participants were at high risk of developing OSA. Based on the STOP-BANG Questionnaire (SBQ), 45.1% were at moderate and high risks. Additionally, this questionnaire showed a significant difference between low and moderate-to-severe groups regarding sex, age, body mass index (BMI), neck size, other chronic diseases, types of DM, use of insulin, Berlin Questionnaire, fasting blood sugar (FBS), and mean HbA1c. Conclusions: Based on the SBQ, our results indicated a significant relationship between OSA and glycemic control according to mean HbA1c and FBS. Therefore, by controlling the OSA, we may find a way to acheieve better glycemic control in diabetic patients.

Obstructive sleep apnea modulates clinical outcomes post-acute myocardial infarction: A large longitudinal veterans' dataset report.

BACKGROUND: While the longer-term Obstructive Sleep apnea (OSA)-related intermittent hypoxia (IH) leads to various comorbidities, it has become increasingly evident that OSA confers protective advantages during and after acute myocardial infarction (AMI). We hypothesized in patients who were admitted with acute MI, the presence of OSA is associated with lower in-hospital mortality compared to those without a prior diagnosis of OSA. METHODS: In this nationwide retrospective study utilizing Veterans Health Administration records, we included patients hospitalized for MI with a history of sleep disorders from 1999 to 2020. We divided patients into two cohorts: those with OSA and those without OSA. The primary outcome was in-hospital mortality during AMI hospitalization. We analyzed the data using logistic regression and calculated the odds ratio of in-hospital mortality. RESULTS: Out of more than four million veterans with any sleep diagnosis, 76,359 patients were hospitalized with a diagnosis of AMI. We observed 30,116 with OSA (age, 64 ± 10 years; BMI, 33 ± 7 kg/m2) and 43,480 without OSA (age, 68 ± 12 years; BMI, 29 ± 6 kg/m2). The aOR of in-patient mortality (n = 333 (1.1%)) was lower in those with OSA (aOR, 0.43; 95% CI, 0.38 to 0.49) compared to without-OSA (n = 1,102, 2.5%). However, the OSA cohort had a higher proportion of the prolonged length of stay (28.1%). CONCLUSIONS: Presence of OSA is associated with lower in-hospital mortality among patients admitted for AMI, after adjusting for various demographic and co-morbidity factors. This study highlights the complex relationship between OSA and cardiovascular health and highlights the need for further research in this area.

Inflammatory Biomarkers Differ among Hospitalized Veterans Infected with Alpha, Delta, and Omicron SARS-CoV-2 Variants.

Mortality due to COVID-19 has been correlated with laboratory markers of inflammation, such as C-reactive protein (CRP). The lower mortality during Omicron variant infections could be explained by variant-specific immune responses or host factors, such as vaccination status. We hypothesized that infections due to Omicron variant cause less inflammation compared to Alpha and Delta, correlating with lower mortality. This was a retrospective cohort study of veterans hospitalized for COVID-19 at the Veterans Health Administration. We compared inflammatory markers among patients hospitalized during Omicron infection with those of Alpha and Delta. We reported the adjusted odds ratio (aOR) of the first laboratory results during hospitalization and in-hospital mortality, stratified by vaccination status. Of 2,075,564 Veterans tested for COVID-19, 29,075 Veterans met the criteria: Alpha (45.1%), Delta (23.9%), Omicron (31.0%). Odds of abnormal CRP in Delta (aOR = 1.85, 95% CI:1.64-2.09) and Alpha (aOR = 1.94, 95% CI:1.75-2.15) were significantly higher compared to Omicron. The same trend was observed for Ferritin, Alanine aminotransferase, Aspartate aminotransferase, Lactate dehydrogenase, and Albumin. The mortality in Delta (aOR = 1.92, 95% CI:1.73-2.12) and Alpha (aOR = 1.68, 95% CI:1.47-1.91) were higher than Omicron. The results remained significant after stratifying the outcomes based on vaccination status. Veterans infected with Omicron showed milder inflammatory responses and lower mortality than other variants.

Mortality Patterns Associated with Central Sleep Apnea among Veterans: A Large, Retrospective, Longitudinal Report.

Rationale: Central sleep apnea (CSA) is associated with high mortality. Current knowledge stems from studies with limited sample size (fewer than 100 subjects) and in homogeneous populations such as heart failure (HF). Objectives: To address this knowledge gap, we compared the mortality pattern and time to death between the CSA and obstructive sleep apnea (OSA) patients in the large Veterans Health Administration patient population using the big data analytic approach. Methods: This is a retrospective study using national Veterans Health Administration electronic medical records from October 1, 1999, through September 30, 2020. We grouped the patients with underlying sleep disorders into CSA and OSA, using the International Classification of Diseases, Ninth and Tenth Revision codes. We applied Cox regression analysis to compare the mortality rate and hazard ratio (HR) among the two groups and adjusted HR by gender, race, body mass index (BMI), age, and Charlson Comorbidity Index. In CSA groups, a machine-learning algorithm was used to determine the most important predictor of time to death. Further subgroup analysis was also performed in patients that had comorbid HF. Results: Evaluation of patients resulted in 2,961 grouped as CSA and 1,487,353 grouped as OSA. Patients with CSA were older (61.8 ± 15.6 yr) than those with OSA (56.7 ± 13.9 yr). A higher proportion of patients with CSA (25.1%) died during the study period compared with the OSA cohort (14.9%). The adjusted HR was 1.53 (95% confidence interval [CI], 1.43-4.65). Presence of HF history of cerebrovascular disease, hemiplegia, and having a BMI less than 18.5 were among the highest predictors of mortality in CSA. The subgroup analysis revealed that the presence of HF was associated with increased mortality both in CSA (HR, 7.4; 95% CI, 6.67-8.21) and OSA (HR, 4.3; 95% CI, 4.26-4.34) groups. Conclusions: Clinically diagnosed CSA was associated with a shorter time to death from the index diagnostic date. Almost one-fifth of patients with CSA died within 5 years of diagnosis. The presence of HF, history of cerebrovascular disease and hemiplegia, male sex, and being underweight were among the highest predictors of mortality in CSA. CSA was associated with higher mortality than OSA, independent of associated comorbidity.

Dual orexin receptor antagonists for treatment of insomnia: A systematic review and meta-analysis on randomized, double-blind, placebo-controlled trials of suvorexant and lemborexant.

Study objectives: Recent treatment guidelines for chronic insomnia recommend pharmacological and non-pharmacological therapies. One of the contemporary drug options for insomnia includes dual orexin receptor antagonist (DORA), such as suvorexant and lemborexant. We conducted a systematic review and meta-analysis for the treatment of insomnia with suvorexant and lemborexant based on randomized, double-blind, placebo-controlled Trials. Methods: We conducted a comprehensive search on three databases (PubMed/Medline, Web of Science, and Cochrane Library) till August 14, 2021, without any restrictions to retrieve the relevant articles. The effect sizes were computed presenting the pooled mean difference or risk ratio along with 95% confidence interval of each outcome. Results: Our search showed eight articles (five for suvorexant and three for lemborexant). Results of diary measures, rating scales, polysomnography results, treatment discontinuation, and adverse events were measured. All efficacy outcome measures favorably and significantly differed in the suvorexant compared to placebo. Safety profile did not differ significantly except for somnolence, excessive daytime sleepiness/sedation, fatigue, back pain, dry mouth, and abnormal dreams. Important adverse events including hallucinations, suicidal ideation/behavior and motor vehicle accidents did not differ between suvorexant and placebo. All the efficacy outcomes significantly differed between lemborexant 5 and lemborexant 10 compared to placebo. Somnolence rate for lemborexant 5 and lemborexant 10 and nightmare for lemborexant 10 were significantly higher than placebo. Conclusion: The present meta-analysis reported that suvorexant and lemborexant are efficacious and safe agents for the patients with insomnia. Further data in patients with insomnia and various comorbid conditions are needed.

Sentiment Analysis of Insomnia-Related Tweets via a Combination of Transformers Using Dempster-Shafer Theory: Pre- and Peri-COVID-19 Pandemic Retrospective Study.

BACKGROUND: The COVID-19 pandemic has imposed additional stress on population health that may result in a change of sleeping behavior. OBJECTIVE: In this study, we hypothesized that using natural language processing to explore social media would help with assessing the mental health conditions of people experiencing insomnia after the outbreak of COVID-19. METHODS: We designed a retrospective study that used public social media content from Twitter. We categorized insomnia-related tweets based on time, using the following two intervals: the prepandemic (January 1, 2019, to January 1, 2020) and peripandemic (January 1, 2020, to January 1, 2021) intervals. We performed a sentiment analysis by using pretrained transformers in conjunction with Dempster-Shafer theory (DST) to classify the polarity of emotions as positive, negative, and neutral. We validated the proposed pipeline on 300 annotated tweets. Additionally, we performed a temporal analysis to examine the effect of time on Twitter users' insomnia experiences, using logistic regression. RESULTS: We extracted 305,321 tweets containing the word insomnia (prepandemic tweets: n=139,561; peripandemic tweets: n=165,760). The best combination of pretrained transformers (combined via DST) yielded 84% accuracy. By using this pipeline, we found that the odds of posting negative tweets (odds ratio [OR] 1.39, 95% CI 1.37-1.41; P<.001) were higher in the peripandemic interval compared to those in the prepandemic interval. The likelihood of posting negative tweets after midnight was 21% higher than that before midnight (OR 1.21, 95% CI 1.19-1.23; P<.001). In the prepandemic interval, while the odds of posting negative tweets were 2% higher after midnight compared to those before midnight (OR 1.02, 95% CI 1.00-1.07; P=.008), they were 43% higher (OR 1.43, 95% CI 1.40-1.46; P<.001) in the peripandemic interval. CONCLUSIONS: The proposed novel sentiment analysis pipeline, which combines pretrained transformers via DST, is capable of classifying the emotions and sentiments of insomnia-related tweets. Twitter users shared more negative tweets about insomnia in the peripandemic interval than in the prepandemic interval. Future studies using a natural language processing framework could assess tweets about other types of psychological distress, habit changes, weight gain resulting from inactivity, and the effect of viral infection on sleep.

Telerehabilitation: Future of Phase II Cardiac Rehabilitation: Review of Preliminary Outcomes.

In this brief communication, we reported Telehealth Home-Based Cardiac Rehabilitation (CR) program structure and preliminary outcomes from patients that completed a 12-week program after coronary artery bypass graft surgery (CABG). We aim to advocate the use of Telerehabilitation as a Phase II CR in patients immediately after the CABG. This approach was innovative and encouraging because the patients were still in subacute phase. The program can serve as a continuation of care for the patients after being discharged from a hospital while regaining their functional ability at home. Our preliminary outcomes demonstrated improvements in resting heart rate, activity level, nutrition status, self-efficacy for managing cardiac diseases, muscle strength, endurance and depression. There were no adverse events during the virtual sessions. Patient satisfaction score was high.

Validation of a Natural Language Processing Algorithm for the Extraction of the Sleep Parameters from the Polysomnography Reports.

Background: There is a need to better understand the association between sleep and chronic diseases. In this study we developed a natural language processing (NLP) algorithm to mine polysomnography (PSG) free-text notes from electronic medical records (EMR) and evaluated the performance. Methods: Using the Veterans Health Administration EMR, we identified 46,093 PSG studies using CPT code 95,810 from 1 October 2000−30 September 2019. We randomly selected 200 notes to compare the accuracy of the NLP algorithm in mining sleep parameters including total sleep time (TST), sleep efficiency (SE) and sleep onset latency (SOL), wake after sleep onset (WASO), and apnea-hypopnea index (AHI) compared to visual inspection by raters masked to the NLP output. Results: The NLP performance on the training phase was >0.90 for precision, recall, and F-1 score for TST, SOL, SE, WASO, and AHI. The NLP performance on the test phase was >0.90 for precision, recall, and F-1 score for TST, SOL, SE, WASO, and AHI. Conclusions: This study showed that NLP is an accurate technique to extract sleep parameters from PSG reports in the EMR. Thus, NLP can serve as an effective tool in large health care systems to evaluate and improve patient care.

Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans.

The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans' Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection.

Impact of Obstructive Sleep Apnea Diagnosed Using the STOP-Bang Questionnaire Scale on Postoperative Complications Following Major Cardiac Surgery: A Prospective Observational Cohort Study.

Purpose Obstructive sleep apnea (OSA) is a common and often undiagnosed condition in patients undergoing major surgeries, including cardiac surgery. This disorder is associated with peri- and postoperative problems. This study measured the association between OSA and peri- and postoperative complications in patients undergoing elective cardiac surgery. Methods Candidates for elective cardiac surgery were evaluated for OSA by the STOP-Bang questionnaire before the surgery. We evaluated patients before and after the operation regarding the cardiac, respiratory, and neurologic complications. We divided the participants into high-risk (score of 5-8), intermediate-risk (score of 3-4), and low-risk groups (score of 0-2) based on the STOP-Bang questionnaire. Results Of the 306 patients who underwent cardiac surgery, 173 (56.5%) were in the high-risk group, 100 (32.7%) were in the intermediate-risk group, and 33 (10.8%) were in the low-risk group for OSA. Patients in the high-risk group were significantly older than the other two groups (p value=0.013), had higher BMI (p<0.001), and suffered more from relevant comorbid conditions, including diabetes mellitus, hypertension, and hyperlipidemia (all p-values significant at < 0.05). However, not significant, patients in the high-risk group suffered more from postoperative complications including cardiac, respiratory, and neurological complications. Conclusion OSA is common in patients undergoing cardiac surgery. Our findings indicate that these patients manifest a higher incidence of postoperative complications compared to those with a lower risk of OSA. Because of the limited use of polysomnography, a simple STOP-Bang questionnaire is beneficial to screen patients for the risk of OSA peri-operatively, and patients diagnosed with OSA can get extra care during and after the surgery.

Association Between Poor Sleep Quality and Glycemic Control in Adult Patients with Diabetes Referred to Endocrinology Clinic of Guilan: A Cross-sectional Study.

Background: Diabetes is a prevalent chronic medical comorbid condition worldwide. Diabetes mellitus is associated with various sleep disorders. Objectives: We aimed to determine the prevalence of poor sleep and the main factors of sleep interruptions in patients with diabetes mellitus. We further evaluated the association of sleep interruptions with glycemic control in this cohort. Methods: We conducted a cross-sectional study on 266 patients with type 1 and type 2 diabetes recruited from a university outpatient endocrinology clinic. Patients completed a checklist including demographic and disease-related characteristics in addition to the Pittsburgh Sleep Quality Index (PSQI) to evaluate sleep quality. Using the PSQI cutoff score of 5, we created two subgroups of good sleepers (GS) and poor sleepers (PS). Results: Our results showed that good sleeper and poor sleeper patients with diabetes were significantly different regarding sex, employment status, BMI, presence of diabetes-related complications, HbA1c, and 2-hour postprandial blood sugar (2HPPBS) (all significant at P < 0.05). The most prevalent factors of sleep interruptions were "waking up to use a bathroom", "feeling hot", "pain", "having coughs or snores", and "bad dreams". Among the subjective factors of sleep interruption, problems with sleep initiation, maintenance, or early morning awakenings in addition to having pain or respiratory problems such as coughing or snoring had the most significant associations with HbA1c. Conclusions: Our study showed significant subjective sleep disturbances (both quality and quantity) in patients with diabetes mellitus (both type I and II) and its association with diabetes control. We further identified the main factors that led to sleep interruptions in this cohort.

Elevated Risk of Chronic Respiratory Conditions within 60 Days of COVID-19 Hospitalization in Veterans.

SARS-CoV-2 infection prominently affects the respiratory system, and patients hospitalized with COVID-19 are at an increased risk of developing respiratory conditions. We examined the risk of new respiratory conditions of COVID-19 among hospitalized patients in the national Veterans Health Administration between 15 February 2020 and 16 June 2021. The study cohort included all COVID-19-tested, hospitalized individuals who survived the index admission and did not have any previously diagnosed chronic respiratory conditions (asthma, bronchitis, chronic lung disease, chronic obstructive pulmonary disease (COPD), emphysema, or venous thromboembolism) before SARS-CoV-2 testing. Of 373,048 patients hospitalized after SARS-CoV-2 testing, 18,686 positive and 37,372 negative patients met the inclusion/exclusion criteria and were matched by age, sex, and race using propensity score matching. The results showed that the SARS-CoV-2 positive group had a greater risk of developing asthma (adjusted odds ratio (aOR) = 1.37), bronchitis (aOR = 2.81), chronic lung disease (aOR = 2.14), COPD (aOR = 1.56), emphysema (aOR = 1.52), and venous thromboembolism (aOR = 1.92) within 60 days after the index COVID date of testing. These findings could inform that the clinical care team considers a risk of new respiratory conditions and address these conditions in the post-hospitalization management of the patient, which could potentially lead to reduce the risk of complications and optimize recovery.

Telemedicine and insomnia: a comprehensive systematic review and meta-analysis.

BACKGROUND: Telemedicine has been introduced as a new and effective method in dealing with public health challenges, improving access to health care, and reducing healthcare costs in today's world. Insomnia is the most common sleep disorder that can be managed with cognitive behavioural therapy, however, access to skilled therapists is an issue. Telemedicine improves access to care and thus, it may facilitate management of insomnia. The aim of this study was to assess whether telemedicine can be as effective as traditional in person sleep medicine service for the diagnosis, follow-up, and treatment of insomnia. METHODS: In this systematic review and meta-analysis, studies related to telemedicine and insomnia were identified and selected, using the keywords of telemedicine, insomnia, sleep disorder, treatment, non-pharmacological treatment. The international databases of Embase, ProQuest, ScienceDirect, Scopus, PubMed and Web of Science (WoS), and Google Scholar were searched without a lower time limit, and until July 12, 2021. Data were analysed within the Comprehensive Meta-Analysis (version 2) software, and the significance level of the test was considered P Ë‚ 0.05. RESULTS: A systematic review of 16 selected studies showed that telemedicine interventions have a positive effect on improving insomnia in different groups. The meta-analysis was performed on 2 studies. Based on the results, CBTI interventions based on telemedicine have a greater effect on improving chronic insomnia than face to face CBTI with an average difference of 2.05 ± 0.66 based on the random effects model. Moreover, the difference between the mean in the telemedicine intervention group and the non-intervention group was 0.65 ± 0.19, which shows the positive effect of the telemedicine intervention. CONCLUSION: The use of telemedicine in treatment of insomnia not only accelerates access to sleep services, but can also improve the efficiency of health services in terms of time and cost, as well as therapeutic effects.