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Measuring severity in OSA: the arguments for collaboratively developing a multidimensional score

2023; American Academy of Sleep Medicine; Volume: 19; Issue: 10 Linguagem: Inglês

10.5664/jcsm.10722

1550-9397

Miguel Ángel Martínez‐García, Grace Oscullo, José Daniel Gómez-Olivas, David Gozal,

Respiratory Support and Mechanisms

Free AccessEditorialsMeasuring severity in OSA: the arguments for collaboratively developing a multidimensional score Miguel Ángel Martínez-García, MD, Grace Oscullo, MD, Jose Daniel Gomez-Olivas, MD, David Gozal, MD, MBA Miguel Ángel Martínez-García, MD Address correspondence to: Miguel Ángel Martínez-García, MD, Pneumology Department, Hospital Universitario y Politécnico La Fe, Avenida Fernando Abril Martorell 2026, Valencia, Spain; Tel: (+34) 609865934; Email: E-mail Address: [email protected] Servicio de Neumología, Hospital Universitario y Politécnico La Fe, Valencia, Spain CIBERES de Enfermedades Respiratorias, ISCIII, Madrid, Spain , Grace Oscullo, MD Servicio de Neumología, Hospital Universitario y Politécnico La Fe, Valencia, Spain , Jose Daniel Gomez-Olivas, MD Servicio de Neumología, Hospital Universitario y Politécnico La Fe, Valencia, Spain , David Gozal, MD, MBA Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia Published Online:October 1, 2023https://doi.org/10.5664/jcsm.10722SectionsEpubPDF ShareShare onFacebookTwitterLinkedInRedditEmail ToolsAdd to favoritesDownload CitationsTrack Citations AboutINTRODUCTIONRespiratory disorders are complex and heterogeneous conditions, particularly as it relates to their clinical presentation.1 One of the major implications of such phenotypic heterogeneity is that the severity of the disease (defined as the impact of the condition on the patient's quality of life or prognosis) cannot be readily evaluated via quantitation of a single measure.2 Many years have now elapsed since several of our colleagues realized that some respiratory illnesses, whether acute or chronic, required a multidimensional evaluation system and formulated composite scores that incorporated several key variables whose cumulative scores enabled more or less accurate estimates of the disease severity.3,4 For example, in the context of chronic obstructive pulmonary disease, the Body Mass Index, airflow Obstruction, Dyspnea, Exercise capacity (BODE) score was proposed. This multiparametric score, which includes body mass index, airway obstruction (forced expiratory volume in 1 s [FEV1]), dyspnea, and exercise capacity, showed markedly improved prognostic value when compared with each of these elements alone, and further instilled into clinical practice the conceptual framework that chronic obstructive pulmonary disease is much more than just airway obstruction as documented by the FEV1.5 Similar approaches have been readily incorporated with success among other conditions such as pulmonary embolism and the Pulmonary Embolism Severity Index (PESI),6 bronchiectasis and the FACED (acronym of FEV1, age, chronic colonization by Pseudomonas aeruginosa, radiological extension, and dyspnea) and Bronchiectasis Severity Index (BSI) scores,7,8 or community-acquired pneumonia and the Pneumonia Severity Index (PSI).9Obstructive sleep apnea (OSA) has clearly emerged as one of the most prevalent respiratory diseases globally around the world.10,11 Such awareness and circumstances have prompted over the last few years a renewed interest in improving the detection of the disease, and also instigated major efforts to achieve a better assessment of OSA severity that would also permit more efficacious treatment.12–15 However, in the real world, even currently, the apnea-hypopnea index (AHI) remains the single metric (sometimes paired with some cardinal symptoms such as the Epworth Sleepiness Scale) that serves as both the diagnostic criterion for OSA as well as the estimate of its severity.10 We should recall that, similar to many other respiratory diseases, OSA is a very complex disease that exhibits a remarkably heterogeneous clinical presentation, such that accurate evaluation of its severity with a single variable such as AHI is clearly insufficient and potentially misleading.16 Such observations on the inadequacy of the AHI prompted several investigators to use clustering methodologies in an effort to identify specific phenotypic subtypes that either incorporate or exclude the AHI, but can provide a more accurate appraisal of OSA severity or guide its treatment.13,14 Such efforts, however, are only incipient, and multidimensional scores for the appraisal of OSA severity and complexity are still lacking. Of note, delineation and validation of such multiparametric scores would likely constitute an intermediate, yet critical step in the formulation of approaches enabling personalized medicine in OSA.The vast array of comorbidities and end-organ targets affected by OSA further buttress the possibility of performing the necessary analyses obviously involving large OSA patient cohorts and thus identifying sub-phenotypes that provide improved accuracy at detecting OSA and at formulating adequate interventions that yield improved outcomes. The extensive work revolving around 2 of the cardinal hallmarks of OSA—namely, intermittent hypoxia and sleep fragmentation—has already uncovered both the similarities and divergences in the effects of each of these perturbations on major functional systems, such as behavior and cognition, cardiovascular, and metabolic.15–22 Still lacking is the systematic exploration of how different degrees and dosages of each of these perturbations affect any given end-organ and the inherent mechanisms underlying such phenotypes. Furthermore, the unique characteristics of the individuals exposed to these paradigms could be also investigated to identify unique susceptibility differences related to age, sex, race and ethnicity, nutritional characteristics, physical activity, and environmental living conditions (eg, pollution, ambient temperature, etc). Such efforts should be complementary to similar initiatives tackling large-population networks for whom collection of as much relevant data has been conducted cooperatively across large and diverse clinical networks.What variables should we include in this multiparametric theoretical score? Although their inclusion awaits specific studies in this direction, some a priori criteria emerge as necessary.1 The variables should be readily and easily measurable and quantifiable to enable their easy integration into clinical constructs in practice. For example, if sequential continuous blood pressure measurements during different phases of the respiratory event emerged as a critically important variable, such a variable would not necessarily be applicable to a large proportion of sleep laboratories, thereby hampering its adoption and implementation.2 Variables should be collected during the process of establishing the diagnosis of OSA. Such a criterion becomes obvious when considering that, if a multidimensional score is needed to establish the severity of formulate therapeutic decisions, the specific moment of reaching the correct diagnosis is essential3; identification of a panel of true biomarkers for OSA would be of great value. We are unfortunately unaware of any such panels having been developed and incorporated to clinical practice to date,23 and efforts in this direction incorporating multi-omics approaches seem worthwhile.4 The putative score should include all major nonoverlapping dimensions that define OSA as a disease. As such, some polygraphic/polysomnographic measures, age, sex, comorbidities, body mass index, or other improved reporters of visceral adiposity, neck circumference, specific symptoms, and some laboratory-based and widely available plasma or other biological fluid measures seem obvious choices (see Figure 1 for possible candidates to be assessed while prospective scores are being developed).5 And it is a prerequisite to reach a consensus a priori that constitutes OSA severity. In other words, what outcomes are to be included in the demarcation of the score? As immediate prospects, quality of life, memory or simple cognitive assessments, and cardiovascular or metabolic functional measures could all be considered together or each separately, and assist in delineating more specifically the criteria for instauration of treatment. Once a multicomponent score is developed based on its prediction of the desirable outcome element cluster, the statistical tools required for refining and progressively improving the ultimate multidimensional score being sought would not be very complicated in light of the current plethora of available approaches enabling such analyses to be correctly performed. For example, selection of the independent variables of interest divided based on specific severity criteria (tertiles, quartiles, continuous) and defined based on their weight and contribution to the outcome of interest is routinely conducted in biomedical research. The final score would then reflect the sum of each of the independent contributions by each of the selected variables. Downstream of this phase would require establishing severity categories (eg, mild, moderate, severe) that would enable differentiation and quantitation of outcome risk.Figure 1: Proposal for potential easy-to-measure variables that can be considered for inclusion in a multidimensional score system to assess obstructive sleep apnea severity at diagnosis.AHI = apnea-hypopnea index, AHT = arterial hypertension, HR = heart rate, CV = cardiovascular, CVE = cardiovascular event, ODI = oxygen desaturation index; SpO2 = Oxygen saturation, Tsat90% = Night-time spent <90% oxygen saturation.Download FigureIn the sphere of sleep medicine in general, and more particularly in the context of OSA, we are unfortunately dragging behind with regard to the progress realized in the above-mentioned directions of developing a multidimensional, validated, and pragmatically valuable score when compared with several other major respiratory diseases. We should be conscious that such diseases are all less prevalent than OSA, and yet even though they impose adverse morbidity and mortality consequences that are sometimes less impactful than OSA, they have already benefited from the invested effort required to develop their unique multidimensional scores. Reaching this desirable stage for OSA would obviously be of great benefit. Although it would not permit precision medicine outright, it would still enable what we would term an intermediary stage of "stratified medicine." The increased prevalence of OSA around the globe, the large number of extant databases, and options for their expansion through natural language exploration of electronic medical records are existing prerequisites for the definite feasibility of developing a uniquely valuable OSA score. "Where there is a need, there is a way" (Albert Einstein).DISCLOSURE STATEMENTThe authors report no conflicts of interest.REFERENCES1. 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CrossrefGoogle Scholar Next article FiguresReferencesRelatedDetails Volume 19 • Issue 10 • October 1, 2023ISSN (print): 1550-9389ISSN (online): 1550-9397Frequency: Monthly Metrics History Submitted for publicationJune 19, 2023Submitted in final revised formJune 29, 2023Accepted for publicationJune 29, 2023Published onlineOctober 1, 2023 Information© 2023 American Academy of Sleep MedicinePDF download