@misc{SkobelKamkeBoenneretal.2015,
  author    = {Skobel, Erik and Kamke, Wolfram and B{\"o}nner, Gerd and Alt, Bernd and Purucker, Hans-Christian and Schwaab, Bernhard and Einwang, Hans-Peter and Schr{\"o}der, Klaus and Langheim, Eike and V{\"o}ller, Heinz and Brandenburg, Alexandra and Graml, Andrea and Woehrle, Holger and Kr{\"u}ger, Stefan},
  title     = {Risk factors for, and prevalence of, sleep apnoea in cardiac rehabilitation facilities in Germany},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {400},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404814},
  pages     = {11},
  year      = {2015},
  abstract  = {Aim To determine the prevalence of, and the risk factors for, sleep apnoea in cardiac rehabilitation (CR) facilities in Germany. Methods 1152 patients presenting for CR were screened for sleep-disordered breathing with 2-channel polygraphy (ApneaLink; ResMed). Parameters recorded included the apnoea-hypopnoea index (AHI), number of desaturations per hour of recording (ODI), mean and minimum nocturnal oxygen saturation and number of snoring episodes. Patients rated subjective sleep quality on a scale from 1 (poor) to 10 (best) and completed the Epworth Sleepiness Scale (ESS). Results Clinically significant sleep apnoea (AHI 15/h) was documented in 33\% of patients. Mean AHI was 1416/h (range 0-106/h). Sleep apnoea was defined as being of moderate severity in 18\% of patients (AHI 15-29/h) and severe in 15\% (AHI 30/h). There were small, but statistically significant, differences in ESS score and subjective sleep quality between patients with and without sleep apnoea. Logistic regression model analysis identified the following as risk factors for sleep apnoea in CR patients: age (per 10 years) (odds ratio (OR) 1.51; p<0.001), body mass index (per 5 units) (OR 1.31; p=0.001), male gender (OR 2.19; p<0.001), type 2 diabetes mellitus (OR 1.45; p=0.040), haemoglobin level (OR 0.91; p=0.012) and witnessed apnoeas (OR 1.99; p<0.001). Conclusions The findings of this study indicate that more than one-third of patients undergoing cardiac rehabilitation in Germany have sleep apnoea, with one-third having moderate-to-severe SDB that requires further evaluation or intervention. Inclusion of sleep apnoea screening as part of cardiac rehabilitation appears to be appropriate.},
  language  = {en}
}
@article{RoehrigSalzwedelLinckEleftheriadisetal.2015,
  author    = {R{\"o}hrig, Bernd and Salzwedel, Annett and Linck-Eleftheriadis, Sigrid and V{\"o}ller, Heinz and Nosper, Manfred},
  title     = {Outcome Based Center Comparisons in Inpatient Cardiac Rehabilitation Results from the EVA-Reha (R) Cardiology Project},
  series = {Die Rehabilitation : Zeitschrift f{\"u}r Praxis und Forschung in der Rehabilitation},
  volume    = {54},
  journal   = {Die Rehabilitation : Zeitschrift f{\"u}r Praxis und Forschung in der Rehabilitation},
  number    = {1},
  publisher = {Thieme},
  address   = {Stuttgart},
  issn      = {0034-3536},
  doi       = {10.1055/s-0034-1395556},
  pages     = {45 -- 52},
  year      = {2015},
  abstract  = {Background: So far, for center comparisons in inpatient cardiac rehabilitation (CR), the objective outcome quality was neglected because of challenges in quantifying the overall success of CR. In this article, a multifactorial benchmark model measuring the individual rehabilitation success is presented. Methods: In 21 rehabilitation centers, 5 123 patients were consecutively enrolled between 01/2010 and 12/2012 in the prospective multicenter registry EVA-Reha (R) Cardiology. Changes in 13 indicators in the areas cardiovascular risk factors, physical performance and subjective health during rehabilitation were evaluated according to levels of severity. Changes were only rated for patients who needed a medical intervention. Additionally, the changes had to be clinically relevant. Therefore Minimal Important Differences (MID) were predefined. Ratings were combined to a single score, the multiple outcome criterion (MEK). Results: The MEK was determined for all patients (71.7 +/- 7.4 years, 76.9 \% men) and consisted of an average of 5.6 indicators. After risk adjustment for sociodemographic and clinical baseline parameters, MEK was used for center ranking. In addition, individual results of indicators were compared with means of all study sites. Conclusion: With the method presented here, the outcome quality can be quantified and outcome-based comparisons of providers can be made.},
  language  = {de}
}