Sphinganine is associated with 24-h MAP in the non-sleepy with OSA.

INTRODUCTION: Excessive daytime sleepiness is a debilitating symptom of obstructive sleep apnea (OSA) linked to cardiovascular disease, and metabolomic mechanisms underlying this relationship remain unknown. We examine whether metabolites from inflammatory and oxidative stress-related pathways that were identified in our prior work could be involved in connecting the two phenomena. METHODS: This study included 57 sleepy (Epworth Sleepiness Scale (ESS) ≥ 10) and 37 non-sleepy (ESS < 10) participants newly diagnosed and untreated for OSA that completed an overnight in-lab or at home sleep study who were recruited from the Emory Mechanisms of Sleepiness Symptoms Study (EMOSS). Differences in fasting blood samples of metabolites were explored in participants with sleepiness versus those without and multiple linear regression models were utilized to examine the association between metabolites and mean arterial pressure (MAP). RESULTS: The 24-h MAP was higher in sleepy 92.8 mmHg (8.4) as compared to non-sleepy 88.8 mmHg (8.1) individuals (P = 0.03). Although targeted metabolites were not significantly associated with MAP, when we stratified by sleepiness group, we found that sphinganine is significantly associated with MAP (Estimate = 8.7, SE = 3.7, P = 0.045) in non-sleepy patients when controlling for age, BMI, smoking status, and apnea-hypopnea index (AHI). CONCLUSION: This is the first study to evaluate the relationship of inflammation and oxidative stress related metabolites in sleepy versus non-sleepy participants with newly diagnosed OSA and their association with 24-h MAP. Our study suggests that Sphinganine is associated with 24 hour MAP in the non-sleepy participants with OSA.

Area Under the Expiratory Flow-Volume Curve (AEX): Assessing Bronchodilator Responsiveness.

BACKGROUND: Area under expiratory flow-volume curve (AEX) is a useful spirometric tool in stratifying respiratory impairment. The AEX approximations based on isovolumic flows can be used with reasonable accuracy when AEX is unavailable. We assessed here pre- to post-bronchodilator (BD) variability of AEX4 as a functional assessment tool for lung disorders. METHODS: The BD response was assessed in 4330 subjects by changes in FEV1, FVC, and AEX4, which were derived from FVC, peak expiratory flow, and forced expiratory flow at 25%, 50%, and 75% FVC. Newly proposed BD response categories (negative, minimal, mild, moderate and marked) have been investigated in addition to standard criteria. RESULTS: Using standard BD criteria, 24% of subjects had a positive response. Using the new BD response categories, only 23% of subjects had a negative response; 45% minimal, 18% mild, 9% moderate, and 5% had a marked BD response. Mean percent change of the square root AEX4 was 0.3% and 14.3% in the standard BD-negative and BD-positive response groups, respectively. In the new BD response categories of negative, minimal, mild, moderate, and marked, mean percent change of square root AEX4 was - 8.2%, 2.9%, 9.2%, 15.0%, and 24.8%, respectively. CONCLUSIONS: Mean pre- to post-BD variability of AEX4 was < 6% and stratified well between newly proposed categories of BD response (negative, minimal, mild, moderate and marked). We suggest that AEX4 (AEX) could become a useful measurement for stratifying dysfunction in obstructive lung disease and invite further investigation into indications for using bronchodilator agents or disease-modifying, anti-inflammatory therapies.

Contribution of Obstructive Sleep Apnea to Asthmatic Airway Inflammation and Impact of Its Treatment on the Course of Asthma.

Asthma and obstructive sleep apnea (OSA) are very common respiratory disorders in the general population. Beyond their high prevalence, shared risk factors, and genetic linkages, bidirectional relationships between asthma and OSA exist, each disorder affecting the other's presence and severity. The author reviews here some of the salient links between constituents of the alternative overlap syndrome, that is, OSA comorbid with asthma, with an emphasis on the effects of OSA or its treatment on inflammation in asthma. In the directional relationship from OSA toward asthma, beyond direct influences, multiple factors and comorbidities seem to contribute.

State of the art: Alternative overlap syndrome-asthma and obstructive sleep apnea.

In the general population, Bronchial Asthma (BA) and Obstructive Sleep Apnea (OSA) are among the most prevalent chronic respiratory disorders. Significant epidemiologic connections and complex pathogenetic pathways link these disorders via complex interactions at genetic, epigenetic, and environmental levels. The coexistence of BA and OSA in an individual likely represents a distinct syndrome, that is, a collection of clinical manifestations attributable to several mechanisms and pathobiological signatures. To avoid terminological confusion, this association has been named alternative overlap syndrome (vs overlap syndrome represented by the chronic obstructive pulmonary disease-OSA association). This comprehensive review summarizes the complex, often bidirectional links between the constituents of the alternative overlap syndrome. Cross-sectional, population, or clinic-based studies are unlikely to elucidate causality or directionality in these relationships. Even longitudinal epidemiological evaluations in BA cohorts developing over time OSA, or OSA cohorts developing BA during follow-up cannot exclude time factors or causal influence of other known or unknown mediators. As such, a lot of pathophysiological interactions described here have suggestive evidence, biological plausibility, potential or actual directionality. By showcasing existing evidence and current knowledge gaps, the hope is that deliberate, focused, and collaborative efforts in the near-future will be geared toward opportunities to shine light on the unknowns and accelerate discovery in this field of health, clinical care, education, research, and scholarly endeavors.

Area under the inspiratory flow-volume curve (AIN): Proposed normative values.

RATIONALE: Area under expiratory flow-volume curve (AEX) has been shown to be a valuable functional measurement in respiratory physiology. Area under inspiratory flow-volume loop (AIN) also shows promise in characterizing upper and/or lower airflow obstruction. OBJECTIVES: we aimed here to develop normative reference values for AIN, able to ascertain deviations from normal. METHODS: We analyzed AIN in 4,980 spirometry tests recorded in non-smoking, healthy individuals in the Pulmonary Function Testing Laboratory. RESULTS: The mean (95% confidence interval, CI), standard deviation and median (25th-75th interquartile range) AIN were 16.05 (15.79-16.31), 9.08 and 14.72 (9.12-21.42) L2·sec-1, respectively. The mean (95% CI) and standard deviation of the best-trial measurements for square root of AIN (Sqrt AIN) were 3.84 (3.81-3.87) and 1.14; 4.15 (4.12-4.18) and 1.03 in men, and 2.68 (2.63-2.72) and 0.72 L·sec-1/2 in women. The mean (standard deviation) of pre- and post-bronchodilator Sqrt AIN were 3.71 (1.17) and 3.81 (1.19) L·sec-1/2, respectively. The mean (95% CI), standard deviation and lowest 5th percentile (lower limit of normal, LLN) of Sqrt AIN/Sqrt AEX (%) were 101.3 (100.82-101.88), 18.7, and 71.8%; stratified by gender, it was 102.2 (101.6-102.8), 18.6, and 72.8% in men, and 98 (96.9-99.2), 18.8, and 68.6% in women, respectively. CONCLUSIONS: The availability of area under the inspiratory flow-volume curve (AIN) and the derived indices offers a promising opportunity to assess upper airway disease (e.g., involvement of larynx, trachea or major bronchi), especially because some of these measurements appear to be independent of age, race, height, and weight.

Deployment-related Cigarette Smoking Behaviors and Pulmonary Function Among U.S. Veterans.

INTRODUCTION: The effects of smoking on lung function among post-9/11 Veterans deployed to environments with high levels of ambient particulate matter are incompletely understood. MATERIALS AND METHODS: We analyzed interim data (04/2018-03/2020) from the Veterans Affairs (VA) Cooperative Studies Program #595, "Service and Health Among Deployed Veterans". Veterans with ≥1 land-based deployments enrolled at 1 of 6 regional Veterans Affairs sites completed questionnaires and spirometry. Multivariable linear regression models assessed associations between cigarette smoking (cumulative, deployment-related and non-deployment-related) with pulmonary function. RESULTS: Among 1,836 participants (mean age 40.7 ± 9.6, 88.6% male), 44.8% (n = 822) were ever-smokers (mean age 39.5 ± 9.5; 91.2% male). Among ever-smokers, 86% (n = 710) initiated smoking before deployment, while 11% (n = 90) initiated smoking during deployment(s). Smoking intensity was 50% greater during deployment than other periods (0.75 versus 0.50 packs-per-day; P < .05), and those with multiple deployments (40.4%) were more likely to smoke during deployment relative to those with single deployments (82% versus 74%). Total cumulative pack-years (median [IQR] = 3.8 [1, 10]) was inversely associated with post-bronchodilator FEV1%-predicted (-0.82; [95% CI] = [-1.25, -0.50] %-predicted per 4 pack-years) and FEV1/FVC%-predicted (-0.54; [95% CI] = [-0.78, -0.43] %-predicted per 4 pack-years). Deployment-related pack-years demonstrated similar point estimates of associations with FEV1%-predicted (-0.61; [95% CI] = [-2.28, 1.09]) and FEV1/FVC%-predicted (-1.09; [95% CI] = [-2.52, 0.50]) as non-deployment-related pack-years (-0.83; [95% CI] = [-1.26, -0.50] for FEV1%-predicted; -0.52; [95% CI] = [-0.73, -0.36] for FEV1/FVC%-predicted). CONCLUSIONS: Although cumulative pack-years smoking was modest in this cohort, an inverse association with pulmonary function was detectable. Deployment-related pack-years had a similar association with pulmonary function compared to non-deployment-related pack-years.

Integrating the overlap of obstructive lung disease and obstructive sleep apnoea: OLDOSA syndrome.

Obstructive lung diseases (OLD) such as asthma and chronic obstructive pulmonary disease (COPD) are very prevalent conditions. Disease phenotypes (e.g. chronic bronchitis, emphysema, etc.) often overlap, and significant confusion exists about their optimal nosologic characterization. Obstructive sleep apnoea (OSA) is also a common condition that features bidirectional interactions with OLD. OSA appears to be more commonly seen in patients with OLD, perhaps as a result of shared risk factors, for example obesity, smoking, increased airway resistance, local and systemic inflammation, anti-inflammatory therapy. Conversely, OSA is associated with worse clinical outcomes in patients with OLD, and continuous positive airway pressure therapy has potential beneficial effects on this vicious pathophysiological interaction. Possible shared mechanistic links include increased parasympathetic tone, hypoxaemia-related reflex bronchoconstriction/vasoconstriction, irritation of upper airway neural receptors, altered nocturnal neurohormonal secretion, pro-inflammatory mediators, within and inter-breath interactions between upper and lower airways, lung volume-airway dependence, etc. While the term overlap syndrome has been defined as the comorbid association of COPD and OSA, the interaction between asthma and OSA has not been integrated yet nosologically; in this review, the latter will be called alternative overlap syndrome. In an effort to bolster further investigations in this area, an integrated, lumping nomenclature for OSA in the setting of OLD is proposed here--OLDOSA (obstructive lung disease and obstructive sleep apnoea) syndrome.

Area under the expiratory flow-volume curve: normative values in the National Health and Nutrition Survey (NHANES) study.

The area under the expiratory flow-volume (AEX-FV) loop has been evaluated before as a spirometric tool for assessing respiratory functional impairment. We computed the AEX-FV curves in spirometry tests performed on 20,313 participants in the National Health and Nutrition Examination Survey (NHANES) study.We analyzed 108,939 spirometry tests performed between 2007 and 2012 (5964 children; 14,349 adults). In these tests, we computed the three areas from existing NHANES raw data on instantaneous expiratory flows measured at 0.01 s intervals.Mean best-trial measurements for AEX-FV were 3.4 in boys, 2.8 in girls, 11.8 in men and 7.7 L2/s in women. We characterized indices of central tendency and dispersion of the measurements (eg, means and fifth percentiles-lower limits of normal) by age group (children vs adults), gender, race or ethnicity group and effort grading. Simple regression equations using logarithmic transformations of the above areas and using age, gender and height as inputs provided good predictive ability for the variable AEX-FV.Regular, digital spirometry could and should make available to clinicians and researchers the area under the curves for flow versus volume graph, providing additional tools in our armamentarium to evaluate ventilatory impairments and patterns, and possibly respiratory disability.

Glucocorticoid therapy in respiratory illness: bench to bedside.

Each year, hundreds of millions of individuals are affected by respiratory disease leading to approximately 4 million deaths. Most respiratory pathologies involve substantially dysregulated immune processes that either fail to resolve the underlying process or actively exacerbate the disease. Therefore, clinicians have long considered immune-modulating corticosteroids (CSs), particularly glucocorticoids (GCs), as a critical tool for management of a wide spectrum of respiratory conditions. However, the complex interplay between effectiveness, risks and side effects can lead to different results, depending on the disease in consideration. In this comprehensive review, we present a summary of the bench and the bedside evidence regarding GC treatment in a spectrum of respiratory illnesses. We first describe here the experimental evidence of GC effects in the distal airways and/or parenchyma, both in vitro and in disease-specific animal studies, then we evaluate the recent clinical evidence regarding GC treatment in over 20 respiratory pathologies. Overall, CS remain a critical tool in the management of respiratory illness, but their benefits are dependent on the underlying pathology and should be weighed against patient-specific risks.

A meta-analysis of diagnostic test performance of peripheral arterial tonometry studies.

STUDY OBJECTIVES: The objective of this meta-analysis was to analyze agreement in apnea-hypopnea index (AHI) determination between peripheral arterial tonometry (PAT) and polysomnography (PSG) studies. METHODS: Mean AHI bias and standard deviation extracted from Bland-Altman plots reported in studies were pooled in a meta-analysis, which was then used to calculate percentage errors of limit agreement in AHI determination by PAT using PSG AHI as the reference. Individual participant data (where reported in studies) were used to compute Cohen's kappa to assess agreement between PSG and PAT on sleep apnea severity and for computing the sensitivity and specificity of PAT at different AHI thresholds using PSG AHI as the reference. RESULTS: From 17 studies and 1,318 participants (all underwent simultaneous PSG and use of the WatchPAT device), a pooled mean AHI bias of 0.30 (standard error [SE], 0.74) and a WatchPAT AHI percentage error of 230% was calculated. The meta-analysis of Cohen's kappa for agreement between PSG and WatchPAT studies for classifying patients with no sleep apnea, mild, moderate, or severe sleep apnea severity was 0.45 (SE, 0.06), 0.29 (SE, 0.05), 0.25 (SE, 0.07), and 0.64 (SE, 0.05), respectively. At AHI thresholds of 5, 15 and 30 events/h, WatchPAT studies showed pooled sensitivities and specificities of 94.11% and 43.47%, 92.21% and 72.39%, and 74.11% and 87.10%, respectively. Likelihood ratios were not significant at any AHI threshold. CONCLUSIONS: The results of this meta-analysis suggest clinically significant discordance between WatchPAT and PSG measurements of AHI, significant sleep apnea severity misclassification by PAT studies, and poor diagnostic test performance. CITATION: Iftikhar IH, Finch CE, Shah AS, Augunstein CA, Ioachimescu OC. A meta-analysis of diagnostic test performance of peripheral arterial tonometry studies. J Clin Sleep Med. 2022;18(4):1093-1102.

Area under the expiratory flow-volume curve: predicted values by regression and deep learning methods and recommendations for clinical practice.

BACKGROUND: In spirometry, the area under expiratory flow-volume curve (AEX-FV) was found to perform well in diagnosing and stratifying physiologic impairments, potentially lessening the need for complex lung volume testing. Expanding on prior work, this study assesses the accuracy and the utility of several models of estimating AEX-FV based on forced vital capacity (FVC) and several instantaneous flows. These models could be incorporated in regular spirometry reports, especially when actual AEX-FV measurements are not available. METHODS: We analysed 4845 normal spirometry tests, performed on 3634 non-smoking subjects without known respiratory disease or complaints. Estimated AEX-FV was computed based on FVC and several flows: peak expiratory flow, isovolumic forced expiratory flow at 25%, 50% and 75% of FVC (FEF25, FEF50 and FEF75, respectively). The estimations were based on simple regression with and without interactions, by optimised regression models and by a deep learning algorithm that predicted the response surface of AEX-FV without interference from any predictor collinearities or normality assumption violations. RESULTS: Median/IQR of actual square root of AEX-FV was 3.8/3.1-4.5 L2/s. The per cent of variance (R2) explained by the models selected was very high (>0.990), the effect of collinearities was negligible and the use of deep learning algorithms likely unnecessary for regular or routine pulmonary function testing laboratory usage. CONCLUSIONS: In the absence of actual AEX-FV, a simple regression model without interactions between predictors or use of optimisation techniques can provide a reasonable estimation for clinical practice, thus making AEX-FV an easily available additional tool for interpreting spirometry.

Assessing bronchodilator response by changes in per cent predicted forced expiratory volume in one second.

In pulmonary function testing by spirometry, bronchodilator responsiveness (BDR) evaluates the degree of volume and airflow improvement in response to an inhaled short-acting bronchodilator (BD). The traditional, binary categorization (present vs absent BDR) has multiple pitfalls and limitations. To overcome these limitations, a novel classification that defines five categories (negative, minimal, mild, moderate and marked BDR), and based on % and absolute changes in forced expiratory volume in 1 s (FEV1), has been recently developed and validated in patients with chronic obstructive pulmonary disease, and against multiple objective and subjective measurements. In this study, working on several large spirometry cohorts from two different institutions (n=31 598 tests), we redefined the novel BDR categories based on delta post-BD-pre-BD FEV1 % predicted values. Our newly proposed BDR partition is based on several distinct intervals for delta post-BD-pre-BD % predicted FEV1 using Global Lung Initiative predictive equations. In testing, training and validation cohorts, the model performed well in all BDR categories. In a validation set that included only normal baseline spirometries, the partition model had a higher rate of misclassification, possibly due to unrestricted BD use prior to baseline testing. A partition that uses delta % predicted FEV1 with the following intervals ≤0%, 0%-2%, 2%-4%, 4%-8% and >8% may be a valid and easy-to-use tool for assessing BDR in spirometry. We confirmed in our cohorts that these thresholds are characterized by low variance and that they are generally gender-independent and race-independent. Future validation in other cohorts and in other populations is needed.

An Alternative Spirometric Measurement. Area under the Expiratory Flow-Volume Curve.

Rationale: Interpretation of spirometry is influenced by inherent limitations and by the normal or predicted reference values used. For example, traditional spirometric parameters such as "distal" airflows do not provide sufficient differentiating capacity, especially for mixed patterns or small airway disease.Objectives: We assessed the utility of an alternative spirometric parameter (area under the expiratory flow-volume curve [AEX]) in differentiating between normal, obstruction, restriction, and mixed patterns, as well as in severity stratification of traditional functional impairments.Methods: We analyzed 15,308 spirometry tests in subjects who had same-day lung volume assessments in a pulmonary function laboratory. Using Global Lung Initiative predicted values and standard criteria for pulmonary function impairment, we assessed the diagnostic performance of AEX in best-split partition and artificial neural network models.Results: The average square root AEX values were 3.32, 1.81, 2.30, and 1.64 L⋅s-0.5 in normal, obstruction, restriction, and mixed patterns, respectively. As such, in combination with traditional spirometric measurements, the square root of AEX differentiated well between normal, obstruction, restriction, and mixed defects. Using forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC z-scores plus the square root of AEX in a machine learning algorithm, diagnostic categorization of ventilatory impairments was accomplished with very low rates of misclassification (<9%). Especially for mixed ventilatory patterns, the neural network model performed best in improving the rates of diagnostic misclassification.Conclusions: Using a novel approach to lung function assessment in combination with traditional spirometric measurements, AEX differentiates well between normal, obstruction, restriction and mixed impairments, potentially obviating the need for more complex lung volume-based determinations.

Area under the expiratory flow-volume curve (AEX): actual versus approximated values.

Previous work has shown that area under the expiratory flow-volume curve (AEX) performs well in diagnosing and stratifying respiratory physiologic impairment, thereby lessening the need to measure lung volumes. Extending this prior work, the current study assesses the accuracy and utility of several geometric approximations of AEX based on standard instantaneous flows. These approximations can be used in spirometry interpretation when actual AEX measurements are not available. We analysed 15 308 spirometry tests performed on subjects who underwent same-day lung volume assessments in the Pulmonary Function Laboratory. Diagnostic performance of four AEX approximations (AEX1-4) was compared with that of actual AEX. All four computations included forced vital capacity (FVC) and various instantaneous flows: AEX1 was derived from peak expiratoryflow (PEF); AEX2 from PEF and forced expiratoryflow at 50% FVC (FEF50); AEX3 from FVC, PEF, FEF at 25% FVC (FEF25) and at 75% FVC (FEF75), while AEX4 was computed from all four flows, PEF, FEF25, FEF50 and FEF75 Mean AEX, AEX1, AEX2, AEX3 and AEX4 were 6.6, 8.3, 6.7, 6.3 and 6.1 L2/s, respectively. All four approximations had strong correlations with AEX, that is, 0.95-0.99. Differences were the smallest for AEX-AEX4, with a mean of 0.52 (95% CI 0.51 to 0.54) and a SD of 0.75 (95% CI 0.74 to 0.76) L2/s. In the absence of AEX and in addition to the usual spirometric variables used for assessing functional impairments, parameters such as AEX4 can provide reasonable approximations of AEX and become useful new tools in future interpretative strategies.

Association between peak inspiratory flow rate and hand grip muscle strength in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease.

RATIONALE: Ineffective peak inspiratory flow rate (PIFR) generation in patients using inhalers results in insufficient drug delivery to the lungs and poor clinical outcomes. Low inspiratory muscle strength is associated with suboptimal PIFR. OBJECTIVE: To examine in a prospective study the relationship between PIFR and skeletal muscle strength using hand grip strength (HGS) as a surrogate. METHODS: Adult patients admitted with acute exacerbation of chronic obstructive pulmonary disease (COPD) were enrolled. PIFR was measured within 48 hours before discharge. PIFR below 60L/min was considered suboptimal. HGS was measured using a handheld dynamometer. Any readmissions and emergency department visit data were collected. The associations between PIFR, HGS, 30 and 90-day COPD and all-cause readmissions were examined, without and with adjustment for age, race and gender. RESULTS: Of the 75 enrolled patients, 56% had suboptimal PIFR; they were older (63.9±9.7 vs. 58.2±7.7 years) and had significantly lower HGS (24.2±11.1 vs. 30.9±10.9 Kg) compared to those with optimal PIFR. There were no significant differences between the two PIFR groups by gender, race, history of coronary artery disease, congestive heart failure, hypertension or functional scores. Each kilogram increase in HGS was associated with 0.50 (95%CI 0.18-0.89, p = 0.003) L/min increase in PIFR. We did not observe an association between PIFR and 30 or 90-day readmission rates. CONCLUSION: We found a significant association between HGS and PIFR in hospitalized patients with acute exacerbations of COPD. Whether interventions aimed at increasing skeletal muscle strength also result in improvement in PIFR remains unclear and need further study.

Area under the expiratory flow-volume curve: predicted values by artificial neural networks.

Area under expiratory flow-volume curve (AEX) has been proposed recently to be a useful spirometric tool for assessing ventilatory patterns and impairment severity. We derive here normative reference values for AEX, based on age, gender, race, height and weight, and by using artificial neural network (ANN) algorithms. We analyzed 3567 normal spirometry tests with available AEX values, performed on subjects from two countries (United States and Spain). Regular linear or optimized regression and ANN models were built using traditional predictors of lung function. The ANN-based models outperformed the de novo regression-based equations for AEXpredicted and AEX z scores using race, gender, age, height and weight as predictor factors. We compared these reference values with previously developed equations for AEX (by gender and race), and found that the ANN models led to the most accurate predictions. When we compared the performance of ANN-based models in derivation/training, internal validation/testing, and external validation random groups, we found that the models based on pooling samples from various geographic areas outperformed the other models (in both central tendency and dispersion of the residuals, ameliorating any cohort effects). In a geographically diverse cohort of subjects with normal spirometry, we computed by both regression and ANN models several predicted equations and z scores for AEX, an alternative measurement of respiratory function. We found that the dynamic nature of the ANN allows for continuous improvement of the predictive models' performance, thus promising that the AEX could become an essential tool in assessing respiratory impairment.

Sleep telemedicine training in fellowship programs: a survey of program directors.

STUDY OBJECTIVES: Telemedicine is a novel modality of health care delivery that can improve patients' access to sleep medicine services, but little is known about telemedicine training during sleep medicine fellowship. We studied telemedicine training prevalence, use, and attitudes of program directors (PDs) and other faculty members, PDs' receptiveness to a standardized telemedicine curriculum, and whether PDs have reviewed existing American Academy of Sleep Medicine (AASM) sleep telemedicine reference materials. METHODS: This was an anonymous online survey of all 86 PDs of accredited sleep medicine fellowships in the United States. RESULTS: Response rate was 45%. Thirteen (33.3%) of the PDs already offer telemedicine experience to their trainees, although none use a standard telemedicine curriculum. Among the 26 (66.7%) PDs not offering telemedicine experience, 38.5% plan to do so and 53.9% agree that it would benefit fellows. Most PDs (57.9%) report faculty using telemedicine now or within the next 3 years. Many PDs agree that telemedicine is technically feasible, but relatively few agree it is financially feasible (82.1% and 38%, respectively). Few PDs have reviewed both primary AASM telemedicine reference materials. Overall, 64.1% of PDs agree that a national sleep telemedicine curriculum could be useful. CONCLUSIONS: Although only a minority of current sleep medicine fellows are exposed to telemedicine, it is likely that most will get some exposure in the next 3 years. PDs' attitudes toward telemedicine vary significantly with respect to feasibility and importance to their programs. Nevertheless, most PDs believe a standardized sleep telemedicine training curriculum could be useful.