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He S, Cistulli PA, de Chazal P. A Review of Novel Oximetry Parameters for the Prediction of Cardiovascular Disease in Obstructive Sleep Apnoea. Diagnostics (Basel) 2023; 13:3323. [PMID: 37958218 PMCID: PMC10649141 DOI: 10.3390/diagnostics13213323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
Obstructive sleep apnoea (OSA) is a sleep disorder with repetitive collapse of the upper airway during sleep, which leads to intermittent hypoxic events overnight, adverse neurocognitive, metabolic complications, and ultimately an increased risk of cardiovascular disease (CVD). The standard diagnostic parameter for OSA, apnoea-hypopnoea index (AHI), is inadequate to predict CVD morbidity and mortality, because it focuses only on the frequency of apnoea and hypopnoea events, and fails to reveal other physiological information for the prediction of CVD events. Novel parameters have been introduced to compensate for the deficiencies of AHI. However, the calculation methods and criteria for these parameters are unclear, hindering their use in cross-study analysis and studies. This review aims to discuss novel parameters for predicting CVD events from oximetry signals and to summarise the corresponding computational methods.
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Affiliation(s)
- Siying He
- Charles Perkins Centre, Faculty of Engineering, Sydney University, Camperdown, NSW 2050, Australia;
| | - Peter A. Cistulli
- Charles Perkins Centre, Faculty of Medicine and Health, Sydney University, Camperdown, NSW 2050, Australia;
- Department of Respiratory and Sleep Medicine, Royal North Shore Hospital, St Leonards, NSW 2065, Australia
| | - Philip de Chazal
- Charles Perkins Centre, Faculty of Engineering, Sydney University, Camperdown, NSW 2050, Australia;
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Bikov A, Frent S, Deleanu O, Meszaros M, Birza MR, Popa AM, Manzur AR, Gligor L, Mihaicuta S. Time Spent with Saturation below 80% versus 90% in Patients with Obstructive Sleep Apnoea. J Clin Med 2023; 12:4205. [PMID: 37445240 DOI: 10.3390/jcm12134205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/18/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Nocturnal hypoxaemia measured as the percentage of total sleep time spent with saturation below 90% (TST90%) may better predict cardiovascular consequences of obstructive sleep apnoea (OSA) than the number of obstructive respiratory events measured with the apnoea-hypopnea index (AHI). Deeper hypoxaemia may potentially induce more severe pathophysiological consequences. However, the additional value of the percentage of total sleep time spent with saturation below 80% (TST80%) to TST90% is not fully explored. METHODS Comprehensive medical history was taken and fasting lipid and C-reactive protein levels were measured in 797 volunteers participating in two cohort studies in Hungary and Romania. Sleep parameters, including AHI, TST90% and TST80%, were recorded following a polysomnography (PSG, n = 598) or an inpatient cardiorespiratory polygraphy (n = 199). The performance of TST80% to predict cardiovascular risk was compared with TST90% using linear and logistic regression analyses as well receiver operating characteristics curves. Sensitivity analyses were performed in patients who had PSG, separately. RESULTS Both parameters are significantly related to cardiovascular risk factors; however, TST80% did not show better predictive value for cardiovascular risk than TST90%. On the other hand, patients with more severe hypoxaemia reported more excessive daytime sleepiness. CONCLUSIONS TST80% has limited additional clinical value compared to TST90% when evaluating cardiovascular risk in patients with OSA.
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Affiliation(s)
- András Bikov
- Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Oxford Road, Manchester M13 9WL, UK
- Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, UK
| | - Stefan Frent
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Oana Deleanu
- Department of Pulmonology, University of Medicine and Pharmacy Carol Davila, Bulevardul Eroii Sanitari 8, 050474 Bucharest, Romania
| | - Martina Meszaros
- Department of Pulmonology, Semmelweis University, Tömő Street 25-29, Budapest 1083, Hungary
| | - Mariela Romina Birza
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Alina Mirela Popa
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Andrei Raul Manzur
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Loredana Gligor
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Stefan Mihaicuta
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
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Karhu T, Leppänen T, Korkalainen H, Myllymaa S, Duce B, Töyräs J, Nikkonen S. Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load. Sleep Med 2022; 100:479-486. [PMID: 36257201 DOI: 10.1016/j.sleep.2022.09.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/02/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVES/BACKGROUND Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature. PATIENTS/METHODS We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance. RESULTS The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734). CONCLUSIONS Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small.
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Affiliation(s)
- Tuomas Karhu
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
| | - Timo Leppänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Henri Korkalainen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Sami Myllymaa
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Brett Duce
- Department of Respiratory and Sleep Medicine, Princess Alexandra Hospital, Brisbane, Australia; Institute for Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Juha Töyräs
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; Science Service Center, Kuopio University Hospital, Kuopio, Finland
| | - Sami Nikkonen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
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Karhu T, Leppänen T, Töyräs J, Oksenberg A, Myllymaa S, Nikkonen S. ABOSA - Freely available automatic blood oxygen saturation signal analysis software: Structure and validation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 226:107120. [PMID: 36152624 DOI: 10.1016/j.cmpb.2022.107120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/04/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Many sleep recording software used in clinical settings have some tools to automatically analyze the blood oxygen saturation (SpO2) signal by detecting desaturations. However, these tools are often inadequate for scientific research as they do not provide SpO2 signal-based parameters which are superior in the estimation of sleep apnea severity and related medical consequences. In addition, these software require expensive licenses and they lack batch analysis tools. Thus, we developed the first freely available automatic blood oxygen saturation analysis software (ABOSA) that provides sophisticated SpO2 signal-based parameters and enables batch analysis of large datasets. METHODS ABOSA was programmed with MATLAB. ABOSA automatically detects desaturation and recovery events from the SpO2 signals (EDF files) and calculates numerous parameters, such as oxygen desaturation index (ODI) and desaturation severity (DesSev). The accuracy of the ABOSA software was evaluated by comparing its desaturation scorings to manual scorings in Kuopio (n = 1981) and Loewenstein (n = 930) sleep apnea patient datasets. Validation was performed in a second-by-second manner by calculating Matthew's correlation coefficients (MCC) and median differences in parameter values. Finally, the performance of the ABOSA software was compared to two commercial software, Noxturnal and Profusion, in 100 patient subpopulations. As Noxturnal or Profusion does not calculate novel desaturation parameters, these were calculated with custom-made functions. RESULTS The agreements between ABOSA and manual scorings were great in both Kuopio (MCC = 0.801) and Loewenstein (MCC = 0.898) datasets. However, ABOSA slightly overestimated the desaturation parameter values. The median differences in ODIs were 0.8 (Kuopio) and 0.0 (Loewenstein) events/h. Similarly, the median differences in DesSevs were 0.02 (Kuopio) and 0.01 (Loewenstein) percentage points. In a second-by-second analysis, ABOSA performed very similarly to Noxturnal and Profusion software in both Kuopio (MCCABOSA = 0.807, MCCNoxturnal = 0.807, MCCProfusion = 0.811) and Loewenstein (MCCABOSA = 0.904, MCCNoxturnal = 0.911, MCCProfusion = 0.871) datasets. Based on Noxturnal and Profusion scorings, the desaturation parameter values were similarly overestimated compared to ABOSA. CONCLUSIONS ABOSA is an accurate and freely available software that calculates both traditional clinical parameters and novel parameters, provides a detailed characterization of desaturation and recovery events, and enables batch analysis of large datasets. These are features that no other software currently provides making ABOSA uniquely suitable for scientific research use.
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Affiliation(s)
- Tuomas Karhu
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.
| | - Timo Leppänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Juha Töyräs
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; Science Service Center, Kuopio University Hospital, Kuopio, Finland
| | - Arie Oksenberg
- Sleep Disorders Unit, Loewenstein Hospital-Rehabilitation Center, Raanana, Israel
| | - Sami Myllymaa
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Sami Nikkonen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
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