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Introduction: The SERVE-HF trial included patients with heart failure and reduced ejection fraction (HFrEF) with sleep-disordered breathing, randomly assigned to treatment with Adaptive-Servo Ventilation (ASV) or control. The primary outcome was the first event of death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening heart failure. A subgroup analysis of the SERVE-HF trial suggested that patients with Cheyne-Stokes respiration (CSR) < 20% (low CSR) experienced a beneficial effect from ASV, whereas in patients with CSR ≥ 20% ASV might have been harmful. Identifying the proteomic signatures and the underlying mechanistic pathways expressed in patients with CSR could help generating hypothesis for future research. Methods: Using a large set of circulating protein-biomarkers (n = 276, available in 749 patients; 57% of the SERVE-HF population) we sought to investigate the proteins associated with CSR and to study the underlying mechanisms that these circulating proteins might represent. Results: The mean age was 69 ± 10 years and > 90% were male. Patients with CSR < 20% (n = 139) had less apnoea-hypopnea index (AHI) events per hour and less oxygen desaturation. Patients with CSR < 20% might have experienced a beneficial effect of ASV treatment (primary outcome HR [95% CI] = 0.55 [0.34–0.88]; p = 0.012), whereas those with CSR ≥ 20% might have experienced a detrimental effect of ASV treatment (primary outcome HR [95% CI] = 1.39 [1.09–1.76]; p = 0.008); p for interaction = 0.001. Of the 276 studied biomarkers, 8 were associated with CSR (after adjustment and with a FDR1%-corrected p value). For example, higher PAR-1 and ITGB2 levels were associated with higher odds of having CSR < 20%, whereas higher LOX-1 levels were associated with higher odds of CSR ≥ 20%. Signalling, metabolic, haemostatic and immunologic pathways underlie the expression of these biomarkers. Conclusion: We identified proteomic signatures that may represent underlying mechanistic pathways associated with patterns of CSR in HFrEF. These hypothesis-generating findings require further investigation towards better understanding of CSR in HFrEF. Summary of the findings. PAR-1 proteinase-activated receptor 1, ADM adrenomedullin, HSP-27 heat shock protein-27, ITGB2 integrin beta 2, GLO1 glyoxalase 1, ENRAGE/S100A12 S100 calcium-binding protein A12, LOX-1 lectin-like LDL receptor 1, ADAM-TS13 disintegrin and metalloproteinase with a thrombospondin type 1 motif, member13 also known as von Willebrand factor-cleaving protease. [ABSTRACT FROM AUTHOR]

Background: Polysomnography (PSG) is the gold standard for sleep analysis and the diagnosis of sleep-disordered breathing (SDB). As PSG is time-consuming and labor-intensive, it is the last step in a stepwise diagnostic workup. An early preliminary diagnosis can be obtained by a novel single-channel minimal-contact device which is placed under the patient’s mattress topper.Objectives: This study assessed the diagnostic accuracy of the novel minimal-contact device VitaLog (SWG Sportwerk GmbH & Co. KG, Dortmund, Germany) for sleep-wake classification and measurement of heart rate (HR). The results were compared to PSG.Materials and methods: VitaLog is a minimal-contact sensor that does not restrict sleep. The diagnostic accuracy of VitaLog was studied in 49 patients referred to our sleep research unit due to suspected SBD. Results obtained by VitaLog were compared to those of a simultaneous PSG to assess the diagnostic accuracy of VitaLog for sleep-wake classification and measurement of HR.Results: Compared to PSG, the accuracy of HR determined by VitaLog was excellent (r = 0.99) with a bias of 0.15 beats per min (bpm). Regarding total sleep time (TST), we found a good correlation of r = 0.8 and a bias of 14 min. For sleep efficiency (SE) estimated by VitaLog, the correlation was moderate with r = 0.6 with a bias of 4.0%. Sleep latency (SL) and wake after sleep onset (WASO) were underestimated by 1 and 12 min, respectively.Conclusions: VitaLog is a promising approach for the estimation of the sleep-related parameters TST, SE, SL, and WASO based on a minimal-contact sensor. In addition, it measures HR with excellent accuracy. However, algorithm modifications are desired to provide appropriate diagnostic accuracy in all sleep disorder cohorts. [ABSTRACT FROM AUTHOR]

Purpose: Recent studies found that the non-contact screening device SleepMinder (ResMed Sensor Technologies, Dublin, Ireland) detects sleep-disordered breathing (SDB) with high diagnostic accuracy in cohorts suspected of this disorder. However, it was reported that in patients with periodic limb movement in sleep (PLMS), this non-contact device overestimates the apnea-hypopnea index (AHI). We aimed to overcome this limitation by introducing the novel sleep disorder index (SDI) which is sum of the AHI and the period limb movement index (PLMI).Methods: Between January 2011 and December 2013, we studied a mixed cohort of 57 patients (31 OSA, 19 PLMS). The easy-to-use non-contact device emits a very weak electromagnetic radiation and detects body movement by measuring the Doppler effect. We interpreted the device-generated movement index as the SDI and validated the diagnostic accuracy against simultaneous application of the gold-standard polysomnography (PSG).Results: We found that the SDI of the non-contact device correlated well with the sum of AHI and PLMI derived from PSG (r = 0.79, p = 0.01). For PSG-derived SDI cutoff ≥ 15/h, we obtained a sensitivity of 92.2% and a specificity of 95.8%. Positive likelihood ratio was 23.3 and negative likelihood ratio 0.03.Conclusions: The studied non-contact screening device detects accurately the combination of the sleep disorders SDB and/or PLM. However, further testing is required in order to specify the nature of the underlying sleep disorder. At the current stage of algorithm development, the clinical strength is that the studied non-contact device can be used as a rule-out screening device for SDB and PLM. [ABSTRACT FROM AUTHOR]

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Purpose: Bilateral lung transplantation results in complete denervation of the lung and might impair hypercapnic ventilatory response (HCVR). However, experimental and clinical findings are scarce and conflicting. Therefore, this study investigated the relationship between HCVR and exercise capacity after long-term bilateral lung transplantation. Methods: This cross-sectional analysis enrolled 46 bilateral lung transplant recipients between October 2011 and July 2012 who underwent cardiopulmonary exercise testing to evaluate maximum workload, and carbon dioxide (CO) rebreathing. CO rebreathing was also evaluated in 35 control subjects. Results: In lung transplant recipients age was 54 ± 11 years, body mass index (BMI) 25.4 ± 4.1 kg/m, and time after transplantation 4.5 ± 2.5 years (range 9 months to 10 years). Controls were aged 41 ± 12 years and had a BMI of 24.9 ± 4.0 kg/m. There were significant differences between lung transplant recipients and controls in forced expiratory volume in 1 s (76 ± 22 vs. 94 ± 12 % predicted, p < 0.001) and inspiratory vital capacity (91 ± 20 vs. 105 ± 14 % predicted, p = 0.001). Blood gases did not differ significantly in patients versus controls. HCVR in lung transplant recipients was 1.44 ± 1.07 L/min/mmHg compared with 2.09 ± 1.14 L/min/mmHg in controls ( p = 0.001). Exercise capacity in lung transplant recipients (73 ± 24 W) was 49 % predicted. Linear regression analysis showed that exercise capacity was significantly associated with HCVR. A 1 L/min/mmHg decrease in HCVR decreased exercise capacity by 50 W. Conclusion: HCVR is reduced in long-term bilateral lung transplant recipients and this might explain the observed impairment of exercise capacity. [ABSTRACT FROM AUTHOR]

Purpose: Lung cancer accounts for one in five cancer deaths. Broad screening strategies for high-risk populations are unavailable, and the validation of biomarkers for early cancer detection remains a prime interest. Therefore, we investigated the value of circulating U2 small nuclear RNA fragments (RNU2-1f) as a biomarker for diagnosis, prognosis estimation and treatment monitoring in a large lung cancer cohort. Methods: We determined RNU2-1f abundance in sera of patients with treatment-naive lung cancer ( n = 211, 25.6 % early stage), chronic lung disease ( n = 56) and healthy controls ( n = 58) by reverse transcription quantitative PCR. Initial levels and changes after one chemotherapy cycle were correlated with treatment outcomes in patient subsets. Results: Relative serum RNU2-1f expression levels (REL) were elevated in lung cancer patients compared with patients with chronic lung disease and healthy controls ( p < 0.0001). The area under the receiver operating characteristic curve for the complete data set (lung cancer vs. healthy) was 0.91 (95 % CI 0.87-0.95). By applying a REL of −4.505 as diagnostic cutoff (Youden's criterion), sensitivity and specificity reached 0.86 and 0.81, respectively. To determine the generalization error, in a subsampling study, sensitivity and specificity were estimated as 0.82 and 0.77 for the application to future, independent samples. High initial RNU2-1f REL were associated with shorter median survival in stage IIIB/IV disease (RNU2-1f = 228 days/RNU2-1f = 484 days; p = 0.009, log-rank test, HR1.43 95 % CI 1.23-1.66). Multivariate analysis confirmed RNU2-1f as an independent prognostic factor. Patients with subsequent RNU2-1f reduction had a trend toward better treatment outcome. Conclusions: Serum RNU2-1f may serve as a biomarker for lung cancer detection, prognosis prediction and treatment monitoring. [ABSTRACT FROM AUTHOR]