Association Between Obstructive Sleep Apnea and Post-Myocardial Infarction All-Cause Mortality: A Systematic Review and Meta-Analysis

Article information

J Sleep Med. 2026;23(1):1-9
Publication date (electronic) : 2026 April 30
doi : https://doi.org/10.13078/jsm.250025
1Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran; Department of Biostatistics, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
2Research Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran
3Fertility and Infertility Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
4Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
5School of Cancer Sciences, The University of Glasgow, United Kingdom
6Neurosciences Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
7Sleep Disorders Research Center, Health Policy and Promotion Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
8Donald and Barbara Zucker School of Medicine, Hempstead, NY, USA
9Department of Medicine, Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
10Department of Medicine, Baylor College of Medicine, Houston, TX, USA
Address for correspondence Azad Maroufi, MD Department of Psychiatry, Kurdistan University of Medical Sciences, Danesgah Boulevard, Sanandaj, 66177-13446, Iran Tel: +98-8733664645 E-mail: MaroufiMD@gmail.com
Masoud Mohammadi, PhD Research Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran Tel: +98-9189057962 E-mail: masoud.mohammadi1989@yahoo.com
Received 2025 October 11; Revised 2025 December 17; Accepted 2026 January 29.

Trans Abstract

Objectives

Evidence regarding the association between obstructive sleep apnea (OSA) and mortality following acute myocardial infarction (MI) remains inconsistent. This study aimed to clarify this relationship through a systematic review and meta-analysis.

Methods

A comprehensive search of six international databases (PubMed, Scopus, Web of Science, ScienceDirect, Google Scholar, and Embase) was conducted on November 11, 2024, without time restrictions. Statistical analyses included a random-effects model stratified by adjusted odds ratio (aOR) and adjusted hazard ratio (aHR). Short-term mortality was defined as in-hospital or ≤30-day mortality, whereas long-term mortality referred to outcomes assessed after a minimum follow-up of 3 months. Data synthesis was performed using Comprehensive Meta-Analysis software (Version 2).

Results

Six studies, including a total of 7,032,232 individuals, showed that short-term post–acute MI mortality was lower among individuals with OSA (aOR=0.67; 95% confidence interval [CI] 0.61–0.74). In contrast, pooled analysis of seven additional studies (n=12,545) reporting aHR indicated that OSA was associated with a 53% increased risk of long-term mortality (aHR=1.53; 95% CI 1.22–1.92). Egger’s test showed no evidence of publication bias.

Conclusions

OSA did not show a significant association with increased short-term post-MI mortality in aOR-based analyses but was linked to a higher risk of long-term mortality in aHR-based analyses. This discrepancy may reflect methodological differences, including the absence of time-to-event modeling in aOR and the greater sensitivity of aHR, as well as variations in study design and follow-up duration. Further well-designed studies are required to confirm these findings.

INTRODUCTION

Obstructive sleep apnea (OSA) is the most common clinical subtype of sleep-related breathing disorders and is characterized by recurrent episodes of partial or complete upper airway obstruction during sleep [1-3]. These episodes can result in significant physiological consequences, including nocturnal intermittent hypoxemia, hypercapnia, sympathetic nervous system activation, high blood pressure, and tachycardia [4,5]. OSA is prevalent among middle-aged adults, affecting approximately 13% of men and 6% of women [6]. Although OSA is highly prevalent among patients with myocardial infarction (MI), with active screening showing rates of 40%–65%, studies relying on administrative data or International Classification of Diseases (ICD)-coded diagnoses capture only previously diagnosed cases, likely leading to substantial underestimation [7].

The severity of OSA ranges from mild to severe, depending on the number of respiratory events, degree of hypoxemia, symptom intensity, and impact on quality of life [4,5]. Common symptoms include loud snoring, insomnia, frequent nocturnal awakening, nocturia, excessive daytime sleepiness, and morning headaches [3,4,8,9]. These manifestations impair sleep quality and may contribute to significant physical and psychological comorbidities [4].

OSA is presumed to contribute to serious cardiovascular conditions through mechanisms such as intermittent hypoxemia and chronic sympathetic activation. These conditions include hypertension, atrial fibrillation, heart failure, and other cardiovascular and cerebrovascular diseases. OSA has also been proposed as a risk factor for acute MI (AMI) [1,3,9-11]. Although some studies support the association between OSA and adverse cardiac outcomes and reduced long-term survival rates following MI, others suggest a potential protective effect. Specifically, the recurrent cycles of hypoxemia and reoxygenation characteristic of OSA may enhance ischemic tolerance, potentially limiting myocardial injury [1,2,10,12].

The prevalence of OSA is particularly high among patients with MI, with estimates ranging from 43% to 66% [13]. Mohananey et al. (2017) [11] reported an in-hospital mortality rate of 3.7% among patients with ST-elevation MI with recognized OSA, compared with 7.4% in those without OSA [2,14]. However, He et al. [8] found that obstructive sleep apnea–hypopnea syndrome was associated with significantly increased 3-year all-cause mortality rates among patients with MI with non-obstructive coronary arteries.

These seemingly conflicting results may be partly explained by differences in outcome measures (e.g., adjusted odds ratios [aORs] for short-term outcomes versus adjusted hazard ratios [aHRs] for long-term outcomes), variations in OSA ascertainment methods, and differences in follow-up duration and patient characteristics across studies. Although several studies have examined the association between OSA and post-MI mortality, the available evidence remains limited and inconsistent. Therefore, this study aimed to better characterize the association between OSA and MI mortality through a systematic review and meta-analysis.

METHODS

This study was a systematic review and meta-analysis of the association between OSA and post-MI mortality, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Search strategy

A comprehensive literature search was conducted on November 11, 2024, using the keywords sleep apnea, OSA, myocardial infarction, MI, and mortality, combined with the Boolean operators “OR” and “AND.” The search was conducted across six major databases: Web of Science, Google Scholar, Scopus, ScienceDirect, PubMed, and Embase. To identify additional relevant studies, the reference lists of retrieved articles were also examined. No restrictions were placed on the publication year. The search was updated on November 24, 2024. All retrieved records were imported into EndNote reference management software and screened according to the predefined eligibility criteria.

Inclusion and exclusion criteria

Studies were included if they met all of the following criteria: 1) examined the association between OSA and post-MI mortality, 2) had full text available, 3) reported sufficient data (e.g., sample size and prevalence rates), 4) were published in English, and 5) were observational analytical studies.

Studies were excluded if they were 1) case reports, interventional studies, or review articles; 2) duplicate publications; or 3) lacking essential statistics (e.g., OR or HR).

Study selection

Two authors independently screened and selected studies in accordance with PRISMA guidelines. Initially, duplicate records were excluded. Subsequently, titles and abstracts were assessed based on the predefined inclusion and exclusion criteria, leading to the exclusion of additional records. Finally, full texts of the remaining studies were reviewed in detail, and studies that did not meet the eligibility criteria were excluded.

When necessary, the corresponding authors were contacted via email to obtain additional information. To minimize bias, two reviewers independently performed all stages of study selection and data extraction. Disagreements were resolved through consultation with a third reviewer.

Quality assessment

The quality of the included studies was evaluated using the Strengthening the Reporting of Observational Studies in Epidemiology checklist. This tool consists of 22 main items organized into six sections: title and abstract, introduction, methods, results, discussion, and other information. Collectively, these items encompass 32 components addressing key aspects of study reporting, including the title, problem statement, objectives, design, target population, sampling method, sample size determination, variable definitions and procedures, data collection tools, statistical analysis methods, and findings. Each component was scored 1 (adequately addressed) or 0 (not adequately reported), yielding a maximum possible score of 32. Studies scoring <16 points were considered to have low methodological quality and were excluded.

Data extraction

Data were independently extracted by two researchers using a predesigned checklist. Extracted data included the first author’s name, publication year, study design, study location, MI sample size, number of participants with and without OSA, sex distribution in each group, and reported ORs and HRs for the association between OSA and post-MI mortality. Short-term mortality was defined a priori as in-hospital mortality or mortality occurring within 30 days of the index MI. Long-term mortality was defined as mortality assessed after a minimum follow-up of 3 months, with follow-up durations among the included studies ranging from several months to more than 5 years.

Statistical analysis

Statistical analyses were performed using Comprehensive Meta-Analysis software (Version 2). Heterogeneity across studies was assessed using the I2 statistic, and publication bias was evaluated with Egger’s test. Random-effects models were used. The distinction between short- and long-term outcomes was based on prespecified differences in follow-up duration rather than the effect measure itself. All studies reporting aORs assessed short-term mortality (in-hospital or 30-day mortali-ty), whereas studies reporting aHRs assessed long-term mortality over extended follow-up periods.

RESULTS

Results of study selection

A total of 2,024 records were identified through electronic database searches, and one additional record was identified through manual searching. All records were imported into EndNote, and 859 duplicate entries were removed. Two reviewers independently conducted a three-stage screening process, with disagreements resolved through consultation with a third reviewer. In the first stage, titles and abstracts were screened based on predefined inclusion and exclusion criteria, resulting in the exclusion of 1,070 articles. In the second stage, the full texts of the remaining 96 studies were assessed using the same criteria, leading to the exclusion of an additional 83 articles. Ultimately, 13 studies [1-5,8-12,14-16] were included in the final qualitative analysis (Fig. 1).

Fig. 1.

PRISMA flow diagram illustrating the study selection process.

Study characteristics

Of the 13 studies, 7 reported aHRs, and 6 reported aORs. Tables 1 and 2 summarize the main characteristics of these two groups of studies, respectively. All the included studies had a cohort design.

Characteristics of the included studies reporting aHRs

Characteristics of the included studies reporting aORs

Meta-analysis of studies reporting aHRs

Seven studies comprising 12,545 participants were included in the meta-analysis. Studies included in the short-term analysis evaluated the in-hospital or 30-day mortality, whereas those included in the long-term analysis reported followup durations ranging from 6 to 68 months. The heterogeneity was low (I2=22.3%), suggesting consistency across studies. A random-effects model was applied to produce more conservative results and increase generalizability of the findings. The pooled aHR for post-MI mortality in patients with OSA was 1.53 (95% CI 1.22–1.92), corresponding to a 53% increased risk of post-MI mortality compared with individuals without OSA (Fig. 2). Egger’s test showed no significant evidence of publication bias (p=0.152) (Fig. 3).

Fig. 2.

Forest plot of studies reporting aHRs for the association between OSA and post-MI mortality (random-effects model). aHR, adjusted hazard ratio; SE, standard error; CI, confidence interval; OSA, obstructive sleep apnea; MI, myocardial infarction.

Fig. 3.

Funnel plot for publication bias among studies reporting adjusted hazard ratios (HRs).

Meta-analysis of studies reporting aORs

Six studies, including 7,032,232 participants, were included in the meta-analysis. Substantial heterogeneity was observed (I2=79.7%); therefore, a random-effects model was used for the data synthesis. The pooled aOR for post-MI mortality in patients with OSA was 0.67 (95% CI 0.61–0.74), indicating significantly lower mortality among individuals with OSA than among those without OSA (Fig. 4). Egger’s test indicated no significant publication bias (p=0.140) (Fig. 5).

Fig. 4.

Forest plot of studies reporting aORs for the association between OSA and post-MI mortality (random-effects model). aOR, adjusted odds ratio; SE, standard error; CI, confidence interval; OSA, obstructive sleep apnea; MI, myocardial infarction.

Fig. 5.

Funnel plot for publication bias among studies reporting adjusted odds ratios (ORs).

DISCUSSION

In this systematic review and meta-analysis, we evaluated the association between OSA and all-cause mortality following AMI. Our findings demonstrate that compared with patients without OSA, those with OSA had lower adjusted odds of short-term post-MI mortality, whereas the aHRs indicated a substantially higher risk of long-term mortality.

This apparent discrepancy likely reflects the time-to-event sensitivity of the HR, as well as other factors. These include differences in follow-up duration, heterogeneity in OSA ascertainment methods (with administrative coding underestimating true prevalence), differences in patient populations across study types, and potential protective effects in the short term from greater in-hospital monitoring, more aggressive interventions, or use of continuous positive airway pressure (CPAP). These differences are partly attributable to the distinct follow-up durations: short-term studies were limited to inhospital or ≤30-day mortality, whereas long-term studies followed patients for several months to multiple years, allowing cumulative OSA-related risk to become more apparent. Given the limited number of studies and potential confounding inherent in short-term observational analyses, the apparent protective association observed for short-term mortality should be interpreted with caution and may reflect contextual clinical factors rather than a true biological effect.

In contrast, the increased post-AMI mortality risk in OSA can also be explained by several pathophysiological mechanisms. Recurrent cycles of intermittent hypoxia and reoxygenation promote sustained sympathetic activation, oxidative stress, and systemic inflammation. These processes induce endothelial dysfunction, impair coronary perfusion, and accelerate atherosclerosis, which may hinder myocardial healing after infarction and contribute to adverse ventricular remodeling. OSA also increases arrhythmogenic potential through autonomic imbalance, heightened vagal–sympathetic fluctuations, and myocardial electrical instability, thereby increasing the risk of sudden cardiac death. In addition, negative intrathoracic pressure swings during apneic episodes increase cardiac afterload and wall stress, further burdening the compromised myocardium. Collectively, these mechanisms create a vulnerable physiological environment that may amplify long-term post-MI mortality risk in individuals with OSA [2,5,7,9,10,13]. Together, these methodological and clinical factors may explain the divergence between short- and long-term associations.

Emerging evidence suggests that the timing of OSA screening in patients with MI may carry important prognostic implications. Studies have shown that OSA is highly prevalent when formally tested during hospitalization or within the first few weeks of discharge, indicating that early screening substantially increases the detection rate of previously unrecognized OSA. Small interventional studies indicate that early initiation of CPAP therapy in acute or subacute post-MI period may improve hemodynamic stability, reduce nocturnal hypoxemia, and potentially lower the risk of early cardiovascular events or readmission. However, findings remain heterogeneous, and large randomized controlled trials are needed to determine whether early treatment initiation during hospitalization confers a definitive survival benefit. These considerations underscore the need for structured screening protocols during AMI care [17-20].

The meta-analysis included 13 studies that evaluated the association between OSA and all-cause post-MI mortality. The pooled results from six studies reporting aOR showed lower short-term post-MI mortality rates in people with OSA (aOR=0.67, 95% CI 0.61–0.74). In contrast, the aHRs in seven other studies demonstrated a significant increase in longterm mortality risk (aHR=1.53, 95% CI 1.22–1.92), indicating that patients with OSA face a 53% higher risk of death over prolonged follow-up periods.

This discrepancy underscores the complex relationship between OSA and cardiovascular outcomes. Thus, not only the conceptual and methodological differences between the statistical measures but also the follow-up periods need to be taken into account. In our analysis, all studies contributing to aOR assessed short-term outcomes (in-hospital or ≤30-day mortality), whereas those contributing to the aHR estimate examined long-term outcomes (median follow-up ranging from several months to years). The aOR reflects only the cumulative association within the study period, without account-ing for time-to-event data, whereas the aHR incorporates event timing and is more sensitive in longitudinal analyses. This distinction supports the interpretation that acute post-MI mortality may be lower in patients with OSA, whereas long-term mortality risk is increased.

Several studies support our findings. He et al. [8] reported a mortality rate of 17% in patients with OSA compared with 10% in those without OSA. However, the limitations of this study, such as the small sample size and loss to follow-up, may have introduced a bias. Similarly, Kendzerska et al. [3] identified OSA as an independent risk factor for cardiovascular events and mortality in a cohort study with a 68-month follow-up period. In that study, nocturnal oxygen saturation <90% was the strongest predictor of endothelial damage, followed by sympathetic activation and sleep fragmentation. The larger sample size and longer follow-up period mitigated some of the limitations of He’s study. Hao et al. [2] also demonstrated a significantly increased risk of long-term post-MI mortality among patients with OSA.

Liu et al. [9] further showed that despite similar baseline cardiac function, patients with OSA exhibited greater myocardial hypertrophy and higher long-term mortality (12.4% vs. 3.7%) than controls, over a 24-month follow-up, highlighting the potential adverse effect of OSA on myocardial remodeling and survival.

Conversely, some studies have reported conflicting protective effects. Agrawal et al. [1] and Mohananey et al. [11] observed a low in-hospital post-MI mortality rate in patients with OSA, albeit with longer hospital stays. Agrawal et al. [1] proposed that ischemic preconditioning—recurrent hypoxic episodes inducing angiogenesis and collateral circulation—could increase myocardial tolerance to acute ischemia. However, this study lacked detailed information regarding CPAP use during hospitalization. Ramphul et al. [4] also showed that CPAP therapy in patients with OSA improved blood pressure control and long-term outcomes, potentially explaining the reduction in mortality. Additionally, patients with OSA may receive more intensive in-hospital diagnostic and therapeutic interventions, such as angiography, thrombolysis, or percutaneous coronary intervention, which can improve survival outcomes, albeit with higher resource utilization [15].

Overall, our findings indicate a complex and multifaceted relationship between OSA and post-MI mortality. Although some studies emphasize the increased long-term risk driven by physiological mechanisms, others highlight the potential short-term protective effects of adaptive responses and enhanced in-hospital care.

This study makes important contributions to the literature. First, outcomes were stratified into short-term (in-hospital or ≤30-day) versus long-term mortality, conducting separate pooled analyses for aOR- and aHR-based studies. This approach allows for a clearer interpretation of temporal differences in risk, in which previous meta-analyses have not addressed. Second, this study incorporated recently published large cohort and administrative database studies (up to November 2024), as well as new polysomnography-based studies. Third, by examining both follow-up duration and methodological differences between effect measures, this study provides a novel explanation for the apparent discrepancy between early protective and later adverse associations. These distinctions collectively extend prior evidence and offer a more nuanced understanding of how OSA influences the mortality risk following MI.

Limitations

This study has several limitations. First, heterogeneity in the diagnostic criteria for OSA and study design may have affected the pooled results. Second, the limited availability of detailed data on confounders, such as age, sex, comorbidities, and CPAP use, limited our ability to perform more granular subgroup analyses. Third, the potential influence of cofactors is strongly associated with both OSA and adverse post-MI outcomes. Conditions such as hypertension, obesity, diabetes, and dyslipidemia frequently coexist with OSA and may independently increase post-MI mortality risk. Although several of the included studies adjusted for major cardiovascular risk factors, residual and unmeasured confounding cannot be fully excluded. Variability in the recording of comorbidities, particularly in administrative database studies, further limits our ability to isolate the independent effect of OSA. Fourth, most studies were conducted in high-income countries, potentially limiting generalizability. Moreover, given the observational design of the included studies, causal inferences cannot be established. Finally, some of the included studies relied on ICDor claims-based definitions of OSA, identifying only previously diagnosed cases and likely underestimating true prevalence in patients with MI (often 40%–65% with active testing). This exposure misclassification may bias results toward the null and contribute to differences between short- and longterm outcomes.

Conclusion

This meta-analysis highlights the complex and dual relationship between OSA and post-AMI mortality. Although OSA was associated with reduced short-term post-MI mortality in aOR-based analyses, it was associated with significantly increased long-term mortality in aHR-based analyses. These differences likely reflect both methodological distinctions between effect measures, particularly the lack of time sensitivity in aORs compared with the greater sensitivity of aHR, and variations in study design and follow-up duration. Further well-designed prospective studies are needed to clarify this association.

Notes

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Azad Maroufi, Habibolah Khazaie, Amir Sharafkhaneh. Data curation: Nader Salari. Formal analysis: Nader Salari. Investigation: Masoud Mohammadi, Seyed Hamidreza Hashemian, Avijeh Rahimi. Methodology: Masoud Mohammadi, Seyed Rasoul Mousavi. Supervision: Habibolah Khazaie, Ritwick Agrawal, Robert Thomas, Amir Sharafkhaneh. Validation: Ritwick Agrawal, Robert Thomas. Writing—original draft: Seyed Hamidreza Hashemian, Azad Maroufi. Writing—review & editing: Amir Sharafkhaneh. Approval of final manuscript: all authors.

Funding Statement

None

Acknowledgments

The authors express their gratitude to the Student Research Committee of the Kermanshah University of Medical Sciences, Kermanshah, Iran, for their valuable support throughout this project.

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Article information Continued

Fig. 1.

PRISMA flow diagram illustrating the study selection process.

Fig. 2.

Forest plot of studies reporting aHRs for the association between OSA and post-MI mortality (random-effects model). aHR, adjusted hazard ratio; SE, standard error; CI, confidence interval; OSA, obstructive sleep apnea; MI, myocardial infarction.

Fig. 3.

Funnel plot for publication bias among studies reporting adjusted hazard ratios (HRs).

Fig. 4.

Forest plot of studies reporting aORs for the association between OSA and post-MI mortality (random-effects model). aOR, adjusted odds ratio; SE, standard error; CI, confidence interval; OSA, obstructive sleep apnea; MI, myocardial infarction.

Fig. 5.

Funnel plot for publication bias among studies reporting adjusted odds ratios (ORs).

Table 1.

Characteristics of the included studies reporting aHRs

Author Year Country MI With OSA Without OSA aHR Follow-up duration Short-term vs. long-term mortality Criteria for diagnosing OSA
Hao et al. [2] 2023 China 316 177 139 1.52 2.9-year mean follow-up Long-term In this study, OSA was diagnosed using a portable type III cardiorespiratory polygraphy. The diagnosis was based on the AHI, with OSA defined as AHI ≥15 events/hour.
Hayano et al. [10] 2012 Japan 379 132 247 1.23 25 months Median to long-term In this study, sleep apnea was diagnosed using a 24-hour Holter ECG analyzed with the autocorrelated wave detection with adaptive threshold algorithm, instead of traditional polysomnography.
He et al. [8] 2020 China 583 158 425 1.706 3 years Long-term In the study, the criteria for diagnosing OSA and its severity are clearly defined based on in-laboratory polysomnography. OSA defined as AHI ≥15 events/hour of total recorded time.
Kendzerska et al. [3] 2014 Canada 10,149 - - 1.27 68 months Long-term In the article, the criteria for diagnosing OSA and its severity are clearly defined based on in-laboratory polysomnography, a decrease of more than 50% of the baseline amplitude of breathing lasting 10 seconds or longer.
Liu et al. [9] 2014 China 198 89 109 11.19 24 months long-term In the study, the criteria for diagnosing OSA and its severity are clearly defined based on in-laboratory polysomnography. Apnea: >90% decrease in the airflow signal lasting for at least 10 seconds and hypopneas ≥30% decrease in airflow signal, with a relevant reduction in SpO2.
Maia et al. [14] 2017 Brazil 639 329 310 2.85 2.6-year mean follow-up Long-term In the study, the criteria for diagnosing OSA are based on the Berlin Questionnaire, which is used as a screening tool to identify individuals at high risk for OSA.
Won et al. [5] 2013 USA 281 - - 1.72 4.1-year mean follow-up Long-term In the study, the criteria for diagnosing OSA and its severity are clearly defined based on in-laboratory polysomnography. The AHI was quantified as the frequency of exclusively obstructive apneas and hypopneas per hour of sleep.

aHR, adjusted hazard ratio; MI, myocardial infarction; OSA, obstructive sleep apnea; AHI, apnea-hypopnea index; ECG, electrocardiogram.

Table 2.

Characteristics of the included studies reporting aORs

Author Year Country MI With OSA Without OSA aOR Follow-up duration Short-term vs. long-term mortality How to diagnose OSA
Agrawal et al. [1] 2023 USA 73,226 30,001 43,225 0.53 <30 days Short-term In the study, the criteria for diagnosing OSA are based on International Classification of Diseases codes from electronic medical records. OSA was considered a confirmed diagnosis if it appeared in the records in one of two ways:
 1) Two separate outpatient encounters with OSA as the primary diagnosis, at least 30 days apart.
 2) One inpatient encounter with OSA as the diagnosis.
 The OSA diagnosis had to be recorded within twelve months before or after the hospitalization for acute myocardial infarction.
Isa et al. [12] 2019 USA 1,984,432 123,551 1,860,881 0.73 <30 days Short-term The study does not explicitly describe the specific diagnostic criteria for OSA itself. However, the methodology states that the study used the National Inpatient Sample (NIS) database to identify patients.
Mohananey et al. [15] 2016 USA 1,850,625 19,305 1,831,320 0.65 <30 days Short-term The study does not explicitly describe the specific diagnostic criteria for OSA itself. However, the methodology states that the study used the NIS database to identify patients.
Mohananey et al. [11] 2017 USA 1,850,624 24,623 1,826,001 0.78 <30 days Short-term In the study, the criteria for diagnosing OSA are based on the use of the International Classification of Diseases, Ninth Edition code of 327.23 to identify patients with OSA.
Ramphul et al. [4] 2022 India 664,530 59,075 605,455 0.672 <30 days Short-term The study does not explicitly describe the specific diagnostic criteria for OSA itself. Instead, it focuses on analyzing patient data from the 2019 NIS database, identifying patients with a diagnosis of OSA recorded in their medical records, without detailing the criteria used for diagnosis.
Rzechorzek et al. [16] 2018 USA 608,795 38,755 570,040 0.66 <30 days Short-term The study does not explicitly describe the specific diagnostic criteria for OSA itself. However, the methodology states that the study used the NIS database to identify patients.

aORs, adjusted odds ratio; MI, myocardial infarction; OSA, obstructive sleep apnea.