Sleep Breath DOI 10.1007/s11325-014-1022-9
ORIGINAL ARTICLE
Positional OSA part 1: towards a clinical classification system for position-dependent obstructive sleep apnoea M. H. Frank & M. J. L. Ravesloot & J. P. van Maanen & E. Verhagen & J. de Lange & N. de Vries
Received: 13 January 2014 / Revised: 23 May 2014 / Accepted: 10 June 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Background In 1984, Cartwright suggested that physicians should differentiate between patients with either positional obstructive sleep apnoea (POSA) or non-positional OSA. Treatment of POSA has advanced dramatically recently with the introduction of a new generation of positional therapy (PT), a small device attached to either the neck or chest which corrects the patient from adopting the supine position through a vibrating stimulus. Encouraging data have been published suggesting that this simple therapy successfully prevents patients with POSA from adopting the supine position without negatively influencing sleep efficiency, as well as allowing for good adherence. Unfortunately, evaluating the efficacy of PT and comparing results are hindered by the fact that there are no universally used POSA criteria. In 1984, Cartwright introduced the arbitrary cut-off point of a difference of 50 % or more in apnoea index between supine and non-supine positions. Introduction The aim of this project was to introduce a new classification system, which ideally should identify suitable candidates for PT: patients that will benefit from a clinically significant improvement of their OSA with PT. The shared use M.H. Frank and M.J.L. Ravesloot equally contributed to this article. M. H. Frank : J. de Lange Department of Oral and Maxillofacial Surgery, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands M. J. L. Ravesloot (*) : J. P. van Maanen : N. de Vries Department of Otolaryngology/Head and Neck Surgery, Sint Lucas Andreas Ziekenhuis, Jan Tooropstraat 164, 1061 AE Amsterdam, The Netherlands e-mail: [email protected] E. Verhagen Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU Medical Center, Amsterdam, The Netherlands
of this classification can facilitate collection of data across multiple centres and comparison of results across studies. We report on the development and process that resulted in the Amsterdam Positional OSA Classification (APOC). Method A panel of three field experts were instructed to independently assign the diagnosis POSA to 100 randomly selected patients they considered likely to benefit from a clinically significant improvement of their OSA with PT. In a group setting, the completed lists were compared. Discrepancies were discussed until consensus was met. This resulted in the consensus standard used to calibrate the new classification. Using the nominal group technique, the APOC was developed. Results The APOC criteria evolve around the percentage of total sleep time spent in either the worst sleeping position (WSP) or the best sleeping position (BSP) and the apnoea– hypopnoea index (AHI) in BSP. On applying APOC, one discriminates between the true positional patient, the nonpositional patient and the multifactorial patient, whose OSA severity is influenced in part by sleep position. APOC has an increased sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) compared to previously applied POSA criteria in identifying patients that will benefit from positional therapy. Keywords Sleep apnoea . Obstructive . Sleeping position . Positional therapy
List of abbreviations AHI Apnoea–hypopnoea index APOC Amsterdam Positional OSA Classification BMI Body mass index BSP Best sleeping position CPAP Continuous positive airway pressure
Sleep Breath
DI ICC NPV OSA POSA PPV PSG PT SaO2 TBT TST WSP
Desaturation index Intercorrelation coefficient Negative predictive value Obstructive sleep apnoea Position-dependent obstructive sleep apnoea Positive predictive value Polysomnography Positional therapy Saturation oxygen Tennis ball technique Total sleep time Worst sleeping position
Introduction An increasing amount of literature is being published on the role of sleep position in obstructive sleep apnoea (OSA) and methods to avoid the worst sleeping position (WSP) [1]. It has become apparent that in the majority of patients with OSA, the frequency and duration of apnoeas are influenced by body position as well, the so-called position-dependent OSA (POSA) [2]. To treat patients with POSA, positional therapy (PT) can be considered, aimed at preventing patients from sleeping in the WSP. Various techniques have been described such as positional alarms or verbal instructions for example. The majority of studies on PT apply the so-called tennis ball technique (TBT): a bulky mass strapped to the patient’s back [1]. Even though TBT is simple and cheap, as well as effective in reducing the apnoea– hypopnoea index (AHI), results are unsatisfactory [2]. Ineffectiveness, backache, discomfort and no improvement in sleep quality or daytime alertness have been responsible for poor compliance and the subsequent disappointing long-term results of PT [3]. Compliance rates reported in the literature range from 40 % short term to 10 % long term [3–5]. Three recent studies have seen the introduction of a new generation of PT, a small device attached to either the neck or chest which corrects the patient from adopting the supine position through a vibrating stimulus [6–8]. The studies present encouraging data suggesting that this simple therapy successfully prevents patients with POSA from adopting the supine position without negatively influencing sleep efficiency as well as allowing for good adherence. It is to be expected that PT will gain momentum in the scope of OSA treatment, but evaluating the efficacy of new-generation PT and comparison of results are hindered by the fact that there are no universally used POSA criteria [9]. In 1984, Cartwright suggested that physicians should differentiate between patients with either positional or nonpositional OSA. She described the arbitrary cut-off point of a difference of 50 % or more in apnoea index between supine
and non-supine positions [10]. Despite being the most common classification system and definition used to date, various modified versions of Cartwright’s criteria have been applied in literature. In 1998, Marklund et al. defined supine-dependent sleep apnoea as follows: a supine AHI≥10, together with a lateral AHI50 % decrease in the AHI between the supine and non-supine postures [12,13]. In the study of Bignold et al., patients who met the following criteria were deemed position-dependent: overall AHI≥15/h, supine AHI≥twice the non-supine AHI, ≥20 min of sleep in supine and non-supine postures and nonsupine AHI30/h is severe OSA, as assessed by PSG.
experience treating OSA patients within a multidisciplinary unit, with special focus on treatment of patients with POSA, were appointed as panellists. Step 1 As a first step, each panellist was sent a list, containing data (overall AHI, AHI and total sleep time (TST) in supine position, AHI and TST in non-supine position) of 100 patients randomly selected by SPSS from the above-mentioned institutional database. The panellists were instructed to independently assign the diagnosis POSA to the subjects who were likely to benefit from a clinically significant improvement of their OSA with PT. The panellists were not allowed to consult each other nor use any aids such as a calculator. The panellists distinguished between non-positional and positional OSA based on their clinical experience and the provided data. We attributed the terminologies WSP (in the majority of cases the supine position) and best sleeping position (BSP) (in the majority of cases non-supine). Step 2 During a group meeting, facilitated by the moderator, the three completed lists were compared. Subject data were discussed if panellists had attributed a different rank to data. The panellist who was a ‘minority’ was prompted to discuss and clarify his or her motives followed by a group discussion. In most cases, consensus was met; if not, the ‘majority’ decided which rank would be attributed. The results from step 2, the diagnosis attributed to the 100 randomly selected patients, were considered the consensus standard and used as a surrogate gold standard to validate the new classification system. Step 3 The nominal group technique, a structured meeting that attempts to provide an orderly procedure for obtaining qualitative information from target groups who are most closely associated with a problem area, was applied to gain consensus and to build a new classification [15–18]. During group discussions, the panellists were invited to make proposals to resolve the weaknesses of Cartwright’s classification, which had been identified during step 2. This led to the construction of a new classification: the APOC. Step 4
Consensus standard We created a consensus standard as to be able to calibrate the new classification. A moderator and three panellists were appointed. Field experts with a minimum of 2 years of field
After precise formulation of the APOC criteria, another group meeting was convened during which the criteria for the APOC were discussed and checked. After approval of these criteria by all experts, the proposed APOC criteria were compared to
Sleep Breath
the consensus standard. Finally, a handout for the easy application of APOC in clinical practice was designed.
Table 1 Characteristics of the 100 randomly selected patients from the institutional database Mean (SD)
Range
AHI (per h) BMI (kg/m2) Age (years) Mean SaO2 (%)
23.4±20.1 29.9±6.3 50.0±9.8 94.0±2.2
5.0–92.0 19.7–59.5 25.0–72.0 83.0–98.0
Minimum SaO2 (%) Desaturation index (DI) Supine AHI (per h) Supine sleep time (% TST)
82.3±7.8 14.2±16.8 36.1±27.1 35.7±25.8
50.0–96.0 0.0–91.0 0.0–113.2 0.0–100.0
Statistical analysis All statistical analyses were conducted in SPSS (version 18, SPSS Inc., Chicago, USA). Descriptive statistics were calculated for baseline characteristics. Results of continuous data are reported with means (SDs) and categorical data as number and percentage. To assess interrater agreement, the intercorrelation coefficient was calculated. As we appointed three panellists, instead of two, the intercorrelation coefficient (ICC) was used instead of Cohen’s kappa. Sensitivity, specificity and positive and negative predictive values were calculated to test the performance of the various classification systems in comparison to the consensus standard.
Results Of the 343 patients who underwent a PSG during the 7-month study period, 100 OSA patients were randomly selected for the consensus list, of whom 66 were male and 34 female. Patient characteristics are summarized in Table 1. Based on the PSG results, 45 % of the patients had mild OSA, 32 % moderate OSA and 23 % severe OSA. Consensus standard The ICCs of the selected panellists were calculated: before the group meeting, the ICC was 0.817 (p
ORIGINAL ARTICLE
Positional OSA part 1: towards a clinical classification system for position-dependent obstructive sleep apnoea M. H. Frank & M. J. L. Ravesloot & J. P. van Maanen & E. Verhagen & J. de Lange & N. de Vries
Received: 13 January 2014 / Revised: 23 May 2014 / Accepted: 10 June 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Background In 1984, Cartwright suggested that physicians should differentiate between patients with either positional obstructive sleep apnoea (POSA) or non-positional OSA. Treatment of POSA has advanced dramatically recently with the introduction of a new generation of positional therapy (PT), a small device attached to either the neck or chest which corrects the patient from adopting the supine position through a vibrating stimulus. Encouraging data have been published suggesting that this simple therapy successfully prevents patients with POSA from adopting the supine position without negatively influencing sleep efficiency, as well as allowing for good adherence. Unfortunately, evaluating the efficacy of PT and comparing results are hindered by the fact that there are no universally used POSA criteria. In 1984, Cartwright introduced the arbitrary cut-off point of a difference of 50 % or more in apnoea index between supine and non-supine positions. Introduction The aim of this project was to introduce a new classification system, which ideally should identify suitable candidates for PT: patients that will benefit from a clinically significant improvement of their OSA with PT. The shared use M.H. Frank and M.J.L. Ravesloot equally contributed to this article. M. H. Frank : J. de Lange Department of Oral and Maxillofacial Surgery, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands M. J. L. Ravesloot (*) : J. P. van Maanen : N. de Vries Department of Otolaryngology/Head and Neck Surgery, Sint Lucas Andreas Ziekenhuis, Jan Tooropstraat 164, 1061 AE Amsterdam, The Netherlands e-mail: [email protected] E. Verhagen Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU Medical Center, Amsterdam, The Netherlands
of this classification can facilitate collection of data across multiple centres and comparison of results across studies. We report on the development and process that resulted in the Amsterdam Positional OSA Classification (APOC). Method A panel of three field experts were instructed to independently assign the diagnosis POSA to 100 randomly selected patients they considered likely to benefit from a clinically significant improvement of their OSA with PT. In a group setting, the completed lists were compared. Discrepancies were discussed until consensus was met. This resulted in the consensus standard used to calibrate the new classification. Using the nominal group technique, the APOC was developed. Results The APOC criteria evolve around the percentage of total sleep time spent in either the worst sleeping position (WSP) or the best sleeping position (BSP) and the apnoea– hypopnoea index (AHI) in BSP. On applying APOC, one discriminates between the true positional patient, the nonpositional patient and the multifactorial patient, whose OSA severity is influenced in part by sleep position. APOC has an increased sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) compared to previously applied POSA criteria in identifying patients that will benefit from positional therapy. Keywords Sleep apnoea . Obstructive . Sleeping position . Positional therapy
List of abbreviations AHI Apnoea–hypopnoea index APOC Amsterdam Positional OSA Classification BMI Body mass index BSP Best sleeping position CPAP Continuous positive airway pressure
Sleep Breath
DI ICC NPV OSA POSA PPV PSG PT SaO2 TBT TST WSP
Desaturation index Intercorrelation coefficient Negative predictive value Obstructive sleep apnoea Position-dependent obstructive sleep apnoea Positive predictive value Polysomnography Positional therapy Saturation oxygen Tennis ball technique Total sleep time Worst sleeping position
Introduction An increasing amount of literature is being published on the role of sleep position in obstructive sleep apnoea (OSA) and methods to avoid the worst sleeping position (WSP) [1]. It has become apparent that in the majority of patients with OSA, the frequency and duration of apnoeas are influenced by body position as well, the so-called position-dependent OSA (POSA) [2]. To treat patients with POSA, positional therapy (PT) can be considered, aimed at preventing patients from sleeping in the WSP. Various techniques have been described such as positional alarms or verbal instructions for example. The majority of studies on PT apply the so-called tennis ball technique (TBT): a bulky mass strapped to the patient’s back [1]. Even though TBT is simple and cheap, as well as effective in reducing the apnoea– hypopnoea index (AHI), results are unsatisfactory [2]. Ineffectiveness, backache, discomfort and no improvement in sleep quality or daytime alertness have been responsible for poor compliance and the subsequent disappointing long-term results of PT [3]. Compliance rates reported in the literature range from 40 % short term to 10 % long term [3–5]. Three recent studies have seen the introduction of a new generation of PT, a small device attached to either the neck or chest which corrects the patient from adopting the supine position through a vibrating stimulus [6–8]. The studies present encouraging data suggesting that this simple therapy successfully prevents patients with POSA from adopting the supine position without negatively influencing sleep efficiency as well as allowing for good adherence. It is to be expected that PT will gain momentum in the scope of OSA treatment, but evaluating the efficacy of new-generation PT and comparison of results are hindered by the fact that there are no universally used POSA criteria [9]. In 1984, Cartwright suggested that physicians should differentiate between patients with either positional or nonpositional OSA. She described the arbitrary cut-off point of a difference of 50 % or more in apnoea index between supine
and non-supine positions [10]. Despite being the most common classification system and definition used to date, various modified versions of Cartwright’s criteria have been applied in literature. In 1998, Marklund et al. defined supine-dependent sleep apnoea as follows: a supine AHI≥10, together with a lateral AHI50 % decrease in the AHI between the supine and non-supine postures [12,13]. In the study of Bignold et al., patients who met the following criteria were deemed position-dependent: overall AHI≥15/h, supine AHI≥twice the non-supine AHI, ≥20 min of sleep in supine and non-supine postures and nonsupine AHI30/h is severe OSA, as assessed by PSG.
experience treating OSA patients within a multidisciplinary unit, with special focus on treatment of patients with POSA, were appointed as panellists. Step 1 As a first step, each panellist was sent a list, containing data (overall AHI, AHI and total sleep time (TST) in supine position, AHI and TST in non-supine position) of 100 patients randomly selected by SPSS from the above-mentioned institutional database. The panellists were instructed to independently assign the diagnosis POSA to the subjects who were likely to benefit from a clinically significant improvement of their OSA with PT. The panellists were not allowed to consult each other nor use any aids such as a calculator. The panellists distinguished between non-positional and positional OSA based on their clinical experience and the provided data. We attributed the terminologies WSP (in the majority of cases the supine position) and best sleeping position (BSP) (in the majority of cases non-supine). Step 2 During a group meeting, facilitated by the moderator, the three completed lists were compared. Subject data were discussed if panellists had attributed a different rank to data. The panellist who was a ‘minority’ was prompted to discuss and clarify his or her motives followed by a group discussion. In most cases, consensus was met; if not, the ‘majority’ decided which rank would be attributed. The results from step 2, the diagnosis attributed to the 100 randomly selected patients, were considered the consensus standard and used as a surrogate gold standard to validate the new classification system. Step 3 The nominal group technique, a structured meeting that attempts to provide an orderly procedure for obtaining qualitative information from target groups who are most closely associated with a problem area, was applied to gain consensus and to build a new classification [15–18]. During group discussions, the panellists were invited to make proposals to resolve the weaknesses of Cartwright’s classification, which had been identified during step 2. This led to the construction of a new classification: the APOC. Step 4
Consensus standard We created a consensus standard as to be able to calibrate the new classification. A moderator and three panellists were appointed. Field experts with a minimum of 2 years of field
After precise formulation of the APOC criteria, another group meeting was convened during which the criteria for the APOC were discussed and checked. After approval of these criteria by all experts, the proposed APOC criteria were compared to
Sleep Breath
the consensus standard. Finally, a handout for the easy application of APOC in clinical practice was designed.
Table 1 Characteristics of the 100 randomly selected patients from the institutional database Mean (SD)
Range
AHI (per h) BMI (kg/m2) Age (years) Mean SaO2 (%)
23.4±20.1 29.9±6.3 50.0±9.8 94.0±2.2
5.0–92.0 19.7–59.5 25.0–72.0 83.0–98.0
Minimum SaO2 (%) Desaturation index (DI) Supine AHI (per h) Supine sleep time (% TST)
82.3±7.8 14.2±16.8 36.1±27.1 35.7±25.8
50.0–96.0 0.0–91.0 0.0–113.2 0.0–100.0
Statistical analysis All statistical analyses were conducted in SPSS (version 18, SPSS Inc., Chicago, USA). Descriptive statistics were calculated for baseline characteristics. Results of continuous data are reported with means (SDs) and categorical data as number and percentage. To assess interrater agreement, the intercorrelation coefficient was calculated. As we appointed three panellists, instead of two, the intercorrelation coefficient (ICC) was used instead of Cohen’s kappa. Sensitivity, specificity and positive and negative predictive values were calculated to test the performance of the various classification systems in comparison to the consensus standard.
Results Of the 343 patients who underwent a PSG during the 7-month study period, 100 OSA patients were randomly selected for the consensus list, of whom 66 were male and 34 female. Patient characteristics are summarized in Table 1. Based on the PSG results, 45 % of the patients had mild OSA, 32 % moderate OSA and 23 % severe OSA. Consensus standard The ICCs of the selected panellists were calculated: before the group meeting, the ICC was 0.817 (p
