Association between Atherogenic Index of Plasma and Hypertension in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome—A Retrospective Study

Summary

This protocol aims to evaluate the ability of the plasma atherosclerosis index (AIP) to differentiate hypertension in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) using retrospective clinical data and analysis of the subject's operation characteristic curve.

Abstract

This study aimed to investigate the relationship between the atherogenic index of plasma (AIP) and hypertension in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). A total of 381 OSAHS patients admitted to the hospital from January 2023 to December 2025 were retrospectively enrolled and divided into a hypertension group (n = 161) and a non-hypertension group (n = 220). Univariate and binary logistic regression analyses were performed to identify influencing factors. The Receiver Operating Characteristic (ROC) curve is used to evaluate the discriminative ability of the identified hypertension indicators. Significant differences between the two groups were observed in coronary heart disease, chronic obstructive pulmonary disease, Gastric Burning, chronic rhinitis, chronic pharyngitis, alcohol consumption, smoking, sedative use, strong tea consumption, family history, neck circumference, red cell distribution width-standard deviation (RDW-SD), aspartate aminotransferase (AST), blood urea nitrogen (BUN), and AIP (P < 0.05). Binary logistic regression indicated that both Coronary Heart Disease and AIP were independent factors for hypertension (P < 0.05). ROC analysis results showed that the AUC for AIP was 0.813 (95%CI: 0.767~0.859), with a standard error of 0.023 and Youden's index of 0.52, resulting in a sensitivity of 77.02% and specificity of 75.00%. These findings suggest that AIP was independently associated with the presence of hypertension in patients with OSAHS and showed moderate discriminatory ability for identifying patients with concomitant hypertension. However, the single-center design and limited sample size of this study warrant caution when generalizing the results.

Introduction

Obstructive sleep apnea-hypopnea syndrome (OSAHS), as a common respiratory system disorder, is characterized by recurrent collapse of the pharyngeal airway leading to intermittent reduction in airflow within the chest cavity during sleep. It not only results in periodic hypoxemia, sympathetic nervous system excitation, decreased sleep quality, and daytime sleepiness but is also closely associated with various cardiovascular abnormalities, particularly hypertension. The two conditions exhibit a bidirectional relationship, where the presence of one disease increases the risk of developing the other^1,2. Currently, hypertension is a major risk factor for diseases such as coronary heart disease and stroke, significantly impacting the health of a large population worldwide. In OSAHS patients, the prevalence of hypertension is higher, and some patients do not receive timely diagnosis and treatment, thereby increasing the likelihood of early-onset preventable cardiovascular diseases^3,4.

Atherogenic index of plasma (AIP), as an indicator reflecting lipid abnormalities and the degree of atherosclerosis, holds significant importance in cardiovascular disease research. Previous studies have indicated^5,6 its association with the occurrence, progression, and mortality of cardiovascular-related diseases. However, research on the association between AIP and hypertension in patients with OSAHS is currently insufficient. Delving deeper into the connection between these two factors can help further elucidate the pathogenesis of hypertension in OSAHS, providing new insights and targets for clinical prevention, diagnosis, and treatment. This exploration holds crucial value for improving patient outcomes, reducing the burden of cardiovascular diseases, and offering valuable insights into the mechanisms underlying OSAHS-related hypertension.

This study hypothesized that (1) AIP is independently associated with hypertension in OSAHS patients, and (2) AIP showed discriminatory ability for identifying OSAHS patients with concomitant hypertension.

Protocol

This study has been approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (ethics approval number: PJ-KS-KY-2-25-1247, approval number: 2025.12.25). As this study is a retrospective study, informed consent is exempted. The reagents and the equipment used are listed in the Table of Materials.

1. Research object

381 patients diagnosed with OSAHS and admitted to the hospital from January 2023 to December 2025 were selected for this study. Patients were categorized into hypertensive (n = 161) and non-hypertensive (n = 220) groups based on the presence of hypertension, as defined by⁷: a diagnosis of hypertension was established when systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg in three separate office measurements on different days in the absence of antihypertensive medications. Blood pressure was measured using a validated automated oscillometric device after the patient had rested in a seated position for at least 5 min, with the arm supported at heart level. Three readings were taken at 1 min intervals, and the average was recorded. Patients with a prior diagnosis of hypertension who were currently on antihypertensive medication were also included, irrespective of their current blood pressure values.

Inclusion criteria

(1) Patients meeting the diagnostic criteria for OSAHS with complete overnight polysomnography (PSG) showing an apnea-hypopnea index (AHI) ≥ 5 events/h⁸; (2) Patients with complete clinical data; (3) Patients aged >18 years.

Exclusion criteria

(1) Severe heart failure: New York Heart Association (NYHA) functional class III-IV; (2) Severe liver or kidney dysfunction; (3) Patients with malignant tumors; (4)The use of lipid-lowering medications (including statins and fibrates) within the 3 months prior to hospital admission.

2. General data collection

In this study, a comprehensive approach was employed to collect relevant information. This included patient demographics such as gender, age, coronary heart disease, chronic obstructive pulmonary disease (COPD), asthma, thyroid disease, Gastric Burning, chronic rhinitis, chronic pharyngitis, upper airway surgery, alcohol consumption, smoking, sedative use, strong tea consumption [Strong tea consumption was defined as drinking tea (any type) that was brewed with ≥3 g of tea leaves per 200 mL of water (or tea bags steeped for ≥5 min), consumed at least 5 days per week, and with a usual daily intake of ≥500 mL], coffee consumption, family history (Family history of OSAHS), body mass index (BMI), neck circumference, waist circumference, hip circumference, AHI, OSAHS severity, Apnea–Hypopnea Index(AHI)(REM), AHI (NREM), minimum oxygen saturation, hypoxemia, mean oxygen saturation, oxygen desaturation index, respiratory arousal index, arousal index, T90 percentage, longest apnea duration, slow wave sleep percentage, blood pressure patterns, among others.

3. Collection of laboratory-related indicators

Additionally, laboratory data were collected and measured in the fasting state in the morning, including white blood cell count (WBC), hemoglobin (Hb), platelet count (PLT), neutrophil count (NEU), lymphocyte count (LYM), red blood cell count (RBC), hematocrit (HCT), red cell distribution width-standard deviation (RDW-SD), mean corpuscular volume (MCV), platelet distribution width (PDW), mean platelet volume (MPV), monocyte count (MONO), plateletcrit (PCT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (γ-GT), blood urea nitrogen (BUN), uric acid (UA), creatinine (Cr), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (GLU), and others.

4. Quality control

All indicators are standardized laboratory processes, including indoor quality control (daily testing of high- and low-value quality controls) and inter-laboratory quality evaluation (regular participation in external proficiency testing) to ensure testing accuracy and reliability.

5. Biosafety and waste management

All blood samples were collected and handled in accordance with the institutional biosafety guidelines. Venipuncture was performed using sterile, single-use needles and vacuum tubes. After sample collection, needles were immediately discarded into puncture-proof sharps containers. All contaminated materials (e.g., gloves, gauze, used tubes, pipette tips) were disposed of as clinical biohazardous waste in labeled, leak-proof bags. Waste containers were sealed and incinerated by an authorized biomedical waste company. Work surfaces were decontaminated with 70% ethanol or 0.5% sodium hypochlorite solution before and after each procedure. Any accidental spill of blood or body fluids was covered with absorbent material, disinfected with 1% sodium hypochlorite for 30 min, and cleaned up using disposable forceps and absorbent pads; all cleaning materials were then discarded as biohazardous waste. Laboratory personnel wore appropriate personal protective equipment (PPE), including disposable gloves, lab coats, and face shields, during all sample processing steps. Hand hygiene was performed immediately after the removal of gloves.

6. The calculation method for AIP

AIP = log10(TG/HDL-C), using TG and HDL-C values in mmol/L⁹.

7. Statistical analysis

The collected experimental data were analyzed using SPSS software. Normality was assessed using the Shapiro-Wilk test. Normally distributed continuous data were presented as EQUATION ± S, compared using independent sample t-tests. Non-normally distributed data were represented by MQ2 (Q1, Q3) and analyzed using the Mann-Whitney U test. Categorical data were expressed as counts or percentages and compared using the χ² test or Fisher's exact test. Factors influencing hypertension were analyzed using univariate and binary logistic regression. The Identification ability of indicators for hypertension in OSAHS patients was evaluated using receiver operating characteristic (ROC) curves, with P < 0.05 considered statistically significant differences.

Results

Comparison of clinical indicators between two groups of patients

Statistically significant differences were observed in the comparison of clinical indicators, including coronary heart disease, COPD, Gastric Burning, chronic rhinitis, chronic pharyngitis, alcohol consumption, smoking, sedative use, strong tea consumption, family history, and neck circumference between the two groups (P < 0.05), as shown in Table 1.

Discussion

Numerous studies have confirmed a close association between OSAHS and hypertension. It has been reported¹ that approximately 30%–50% of OSAHS patients also suffer from hypertension, with at least 30% of hypertensive patients having concurrent OSAHS. In OSAHS patients, repeated collapse of the airway during sleep leads to episodes of apnea or hypopnea, triggering heightened sympathetic nervous system activity. This state of sympathetic excitation counteracts the natural nocturnal decrease in ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Flow cytometer	Beckman Coulter	CytoFLEX	Classify and count cells
Fully automated biochemical analyzer	Roche	Cobas c702	Analyze liver and kidney function, blood lipids, and other indicators
Fully automated blood analyzer	Sysmex Corporation	XN - 9000	Measure cell volume distribution, hemoglobin, hematocrit
SPSS 27.0	International Business Machines Corporation	27	Analyze all data
Vacuum blood collection tubes (with EDTA anticoagulant)	BD Biosciences	367863	Used for collecting venous blood